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Woods S, McKiel A, Herda T, Klentrou P, Holmes MWR, Gabriel DA, Falk B. Different discrete motor-unit activation patterns in the flexor carpi radialis in boys and men. Eur J Appl Physiol 2024; 124:1933-1942. [PMID: 38285213 DOI: 10.1007/s00421-024-05417-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 01/06/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND Lower activation of higher threshold (type-II) motor units (MUs) has been suggested in children compared with adults. We examined child-adult differences in discrete MU activation of the flexor carpi radialis (FCR). METHODS Fifteen boys (10.2 ± 1.4 years), and 17 men (25.0 ± 2.7 years) completed 2 laboratory sessions. Following a habituation session, maximal voluntary isometric wrist flexion torque (MVIC) was determined before completing trapezoidal isometric contractions at 70%MVIC. Surface electromyography was captured by Delsys Trigno Galileo sensors and decomposed into individual MU action potential trains. Recruitment threshold (RT), and MU firing rates (MUFR) were calculated. RESULTS MVIC was significantly greater in men (10.19 ± 1.92 Nm) than in boys (4.33 ± 1.47 Nm) (p < 0.05), but not statistically different after accounting for differences in body size. Mean MUFR was not different between boys (17.41 ± 7.83 pps) and men (17.47 ± 7.64 pps). However, the MUFR-RT slope was significantly (p < 0.05) steeper (more negative) in boys, reflecting a progressively greater decrease in MUFR with increasing RT. Additionally, boys recruited more of their MUs early in the ramped contraction. CONCLUSION Compared with men, boys tended to recruit their MUs earlier and at a lower percentage of MVIC. This difference in MU recruitment may explain the greater decrease in MUFR with increasing RT in boys compared with men. Overall, these findings suggest an age-related difference in the neural strategy used to develop moderate-high torque in wrist flexors, where boys recruit more of their MUs earlier in the force gradation process, possibly resulting in a narrower recruitment range.
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Affiliation(s)
- Stacey Woods
- Department of Kinesiology, Faculty of Applied Health Sciences, Brock University, St. Catharines, ON, L2S 3A1, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
| | - Andrew McKiel
- Department of Kinesiology, Faculty of Applied Health Sciences, Brock University, St. Catharines, ON, L2S 3A1, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
| | - Trent Herda
- School of Education and Human Sciences, University of Kansas, Lawrence, KS, USA
| | - Panagiota Klentrou
- Department of Kinesiology, Faculty of Applied Health Sciences, Brock University, St. Catharines, ON, L2S 3A1, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
| | - Michael W R Holmes
- Department of Kinesiology, Faculty of Applied Health Sciences, Brock University, St. Catharines, ON, L2S 3A1, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
| | - David A Gabriel
- Department of Kinesiology, Faculty of Applied Health Sciences, Brock University, St. Catharines, ON, L2S 3A1, Canada
| | - Bareket Falk
- Department of Kinesiology, Faculty of Applied Health Sciences, Brock University, St. Catharines, ON, L2S 3A1, Canada.
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada.
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Hu M, Lou Y, Zhu C, Chen J, Liu S, Liang Y, Liu S, Tang Y. Evaluating the Impact of Intracranial Volume Correction Approaches on the Quantification of Intracranial Structures in MRI: A Systematic Analysis. J Magn Reson Imaging 2024; 59:2164-2177. [PMID: 37702125 DOI: 10.1002/jmri.28974] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/10/2023] [Accepted: 08/10/2023] [Indexed: 09/14/2023] Open
Abstract
BACKGROUND In neuroscience, accurately quantifying individual brain regions in large cohorts is a challenge. Differences in intracranial structures can suggest functional differences, but they also reflect the effects of other factors. However, there is currently no standardized method for the correction of intracranial structure measurements. PURPOSE To identify the optimal method to counteract the influence of total intracranial volume (TIV) and gender on the measurement of intracranial structures. STUDY TYPE Prospective. POPULATION/SUBJECTS One hundred forty-one healthy adult volunteers (70 male, mean age 21.8 ± 1.7 years). FIELD STRENGTH/SEQUENCE T1-weighted 3D gradient-echo sequence at 3.0 T. ASSESSMENT A radiologist with 5 years of work experience screened the raw images to exclude poor-quality images. Freesurfer then performed automated segmentation to obtain measurements of intracranial structures. Male-only, female-only, and TIV-matched sub-samples were created separately. Comparisons between the original data and these sub-samples were used to assess the effects of gender and TIV. Comparison the consistency between TIV-matched sample and corrected data that corrected by four methods: Proportion method, power-corrected proportion method, covariate regression method, and residual method. STATISTICAL TESTS Cohen's d for examining group distribution disparities, t-tests for probing mean differences, correlation coefficients to assess the relationships between intracranial substructure measurements and TIV. Multiple comparison corrections were applied to the results. RESULTS The correlation coefficients between TIV and the volumes of intracranial structures ranged from 0.033 to 0.883, with an average of 0.467. Thirty significant volume differences were found among 36 structures in the original sample, while no differences were observed in the TIV-matched sample. Among the four correction methods, the residual method had highest consistency (similarity 94.4%) with the TIV-matched group. DATA CONCLUSION The variation in intracranial structure sizes between genders was largely attributable to TIV. The residual method offers a more accurate and effective approach for correcting the effects of TIV on intracranial structures. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Minqi Hu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China
| | - Yunxia Lou
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China
- Department of Ultrasound, Cheeloo Hospital, Shandong University, Jinan, Shandong, China
| | - Caiting Zhu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China
| | - Jiachen Chen
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China
| | - Shizhou Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China
| | - Yongfeng Liang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Department of Radiology, Cheeloo Hospital, Shandong University, Jinan, Shandong, China
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China
- Advanced Medical Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
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Liao C, Cao X, Iyer SS, Schauman S, Zhou Z, Yan X, Chen Q, Li Z, Wang N, Gong T, Wu Z, He H, Zhong J, Yang Y, Kerr A, Grill-Spector K, Setsompop K. High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting. Magn Reson Med 2024; 91:2278-2293. [PMID: 38156945 PMCID: PMC10997479 DOI: 10.1002/mrm.29990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 12/11/2023] [Accepted: 12/11/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. METHODS We developed 3D visualization of short transverse relaxation time component (ViSTa)-MRF, which combined ViSTa technique with MR fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multicompartment fitting that could introduce bias and/or noise from additional assumptions or priors. RESULTS The in vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in vivo results of 1 mm- and 0.66 mm-isotropic resolution datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30× slower with lower SNR. Furthermore, we applied the proposed method to enable 5-min whole-brain 1 mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples. CONCLUSIONS In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1 and 0.66 mm isotropic resolution in 5 and 15 min, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.
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Affiliation(s)
- Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Siddharth Srinivasan Iyer
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sophie Schauman
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Zihan Zhou
- Department of Radiology, Stanford University, Stanford, CA, USA
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaoqian Yan
- Department of Psychology, Stanford University, Stanford, CA, USA
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Quan Chen
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Zhitao Li
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Nan Wang
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Ting Gong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Zhe Wu
- Techna Institute, University Health Network, Toronto, ON, Canada
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- School of Physics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Imaging Sciences, University of Rochester, Rochester, NY, USA
| | - Yang Yang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Adam Kerr
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Stanford Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA, USA
| | | | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
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Zhang T, Wang H, Ouyang F, Yang H, Zhang J, Zhang N. Does brain-derived neurotrophic factor play a role in the association between maternal prenatal mental health and neurodevelopment in 2-year-old children? J Affect Disord 2024; 359:171-179. [PMID: 38777264 DOI: 10.1016/j.jad.2024.05.074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 05/11/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVE To evaluate the role of brain-derived neurotrophic factor (BDNF)-a crucial modulator of neural development and plasticity-in the association between prenatal maternal anxiety, depression, and perceived stress and child neurodevelopment in a prospective cohort study. METHODS We included 526 eligible mother-child pairs from the Shanghai Birth Cohort in the study. Maternal mental health was assessed at mid-pregnancy using Zung's Self-Rating Anxiety Scale, Center for Epidemiologic Studies Depression Scale, and Perceived Stress Scale. The concentration of BDNF in cord blood was measured by ELISA. The offspring neurodevelopment at 24 months of age was assessed using the Bayley Scales. Linear and non-linear regression models were used. RESULTS The average cord blood BDNF levels were higher in female newborns and those born via vaginal delivery, full term, and normal birth weight. Prenatal maternal anxiety (β = -0.32; 95 % CI: -0.55, -0.09), depression (β = -0.30; 95 % CI: -0.52, -0.08), and perceived stress (β = -0.41; 95 % CI: -0.71, -0.12) scores were negatively associated with social-emotional performance at 24 months of age. However, no significant associations were found between prenatal maternal anxiety, depression, or perceived stress at mid-pregnancy and cord blood BDNF levels, as well as between cord blood BDNF levels and child neurodevelopment. LIMITATIONS Maternal mental health at different timepoints during pregnancy and generalizability of the results warrant further assessment. CONCLUSIONS Prenatal mental health was not associated with cord blood BDNF level and that BDNF may not be a mediator in the association between prenatal mental health and child neurodevelopment.
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Affiliation(s)
- Tian Zhang
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huizi Wang
- Hainan Women and Children's Medical Center, Haikou, China
| | - Fengxiu Ouyang
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hua Yang
- Hainan Women and Children's Medical Center, Haikou, China
| | - Jun Zhang
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Na Zhang
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Song L, Peng Y, Ouyang M, Peng Q, Feng L, Sotardi S, Yu Q, Kang H, Sindabizera KL, Liu S, Huang H. Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels. Hum Brain Mapp 2024; 45:e26695. [PMID: 38727010 PMCID: PMC11083905 DOI: 10.1002/hbm.26695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 03/11/2024] [Accepted: 04/10/2024] [Indexed: 05/13/2024] Open
Abstract
Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.
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Affiliation(s)
- Limei Song
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- School of Medical ImagingWeifang Medical UniversityWeifangChina
| | - Yun Peng
- Department of Radiology, Beijing Children's HospitalCapital Medical UniversityBeijingChina
| | - Minhui Ouyang
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Qinmu Peng
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Lei Feng
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Susan Sotardi
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Qinlin Yu
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Huiying Kang
- Department of Radiology, Beijing Children's HospitalCapital Medical UniversityBeijingChina
| | - Kay L. Sindabizera
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Shuwei Liu
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
| | - Hao Huang
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Mao W, Chen Y, He Z, Wang Z, Xiao Z, Sun Y, He L, Zhou J, Guo W, Ma C, Zhao L, Kendrick KM, Zhou B, Becker B, Liu T, Zhang T, Jiang X. Brain Structural Connectivity Guided Vision Transformers for Identification of Functional Connectivity Characteristics in Preterm Neonates. IEEE J Biomed Health Inform 2024; 28:2223-2234. [PMID: 38285570 DOI: 10.1109/jbhi.2024.3355020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Preterm birth is the leading cause of death in children under five years old, and is associated with a wide sequence of complications in both short and long term. In view of rapid neurodevelopment during the neonatal period, preterm neonates may exhibit considerable functional alterations compared to term ones. However, the identified functional alterations in previous studies merely achieve moderate classification performance, while more accurate functional characteristics with satisfying discrimination ability for better diagnosis and therapeutic treatment is underexplored. To address this problem, we propose a novel brain structural connectivity (SC) guided Vision Transformer (SCG-ViT) to identify functional connectivity (FC) differences among three neonatal groups: preterm, preterm with early postnatal experience, and term. Particularly, inspired by the neuroscience-derived information, a novel patch token of SC/FC matrix is defined, and the SC matrix is then adopted as an effective mask into the ViT model to screen out input FC patch embeddings with weaker SC, and to focus on stronger ones for better classification and identification of FC differences among the three groups. The experimental results on multi-modal MRI data of 437 neonatal brains from publicly released Developing Human Connectome Project (dHCP) demonstrate that SCG-ViT achieves superior classification ability compared to baseline models, and successfully identifies holistically different FC patterns among the three groups. Moreover, these different FCs are significantly correlated with the differential gene expressions of the three groups. In summary, SCG-ViT provides a powerfully brain-guided pipeline of adopting large-scale and data-intensive deep learning models for medical imaging-based diagnosis.
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Woods S, McKiel A, Herda T, Klentrou P, Holmes M, Gabriel D, Falk B. Developmental changes in motor unit activity patterns: child-adult comparison using discrete motor unit analysis. Appl Physiol Nutr Metab 2024. [PMID: 38471135 DOI: 10.1139/apnm-2023-0339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024]
Abstract
Using global surface electromyography (sEMG) and the sEMG threshold it has been suggested that children activate their type-II motor unit (MU) to a lesser extent compared with adults. However, when age-related differences in discrete MU activation are examined using sEMG decomposition this phenomenon is not observed. Furthermore, findings from these studies are inconsistent and conflicting. Therefore, the purpose of this study was to examine differences in discrete MU activation of the vastus lateralis (VL) between boys and men during moderate-intensity knee extensions. Seventeen boys and 20 men completed two laboratory sessions. Following a habituation session, maximal voluntary isometric knee extension (MVIC) torque was determined before completing trapezoidal contractions at 70% MVIC. sEMG of the VL was captured and mathematically decomposed into individual MU action potential trains. Motor unit action potential amplitude (MUAPamp), recruitment threshold (RT), and MU firing rates (MUFR) were calculated. We observed that MUAPamp-RT slope was steeper in men compared with boys (p < 0.05) even after accounting for fat thickness and quadriceps muscle depth. The mean MUFR and y-intercept of the MUFR-RT relationship were significantly (p < 0.001) lower in boys than in men. The slope of the MUFR-RT relationship tended to be steeper in men, but the differences did not reach statistical significance (p = 0.056). Overall, our results suggest that neural strategies used to produce torque are different among boys and men. Such differences may be related, in part, to boys' lower MUFR and lesser ability to activate their higher-threshold MUs. Although, other factors (e.g., muscle composition) likely also play a role.
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Affiliation(s)
- Stacey Woods
- Department of Kinesiology, Brock University, St. Catharines, ON, Canada
| | - Andrew McKiel
- Department of Kinesiology, Brock University, St. Catharines, ON, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
| | - Trent Herda
- School of Education and Human Sciences, University of Kansas, Lawrence, KS, USA
| | - Panagiota Klentrou
- Department of Kinesiology, Brock University, St. Catharines, ON, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
| | - Michael Holmes
- Department of Kinesiology, Brock University, St. Catharines, ON, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
| | - David Gabriel
- Department of Kinesiology, Brock University, St. Catharines, ON, Canada
| | - Bareket Falk
- Department of Kinesiology, Brock University, St. Catharines, ON, Canada
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, Canada
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Manrique HM, Read DW, Walker MJ. On some statistical and cerebral aspects of the limits of working memory capacity in anthropoid primates, with particular reference to Pan and Homo, and their significance for human evolution. Neurosci Biobehav Rev 2024; 158:105543. [PMID: 38220036 DOI: 10.1016/j.neubiorev.2024.105543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 12/10/2023] [Accepted: 01/09/2024] [Indexed: 01/16/2024]
Abstract
Some comparative ontogenetic data imply that effective working-memory capacity develops in ways that are independent of brain size in humans. These are interpreted better from neuroscientific considerations about the continuing development of neuronal architecture in adolescents and young adults, than from one about gross brain mass which already is reached in childhood. By contrast, working-memory capacity in Pan never develops beyond that of three- or four-year-old children. The phylogenetic divergence begs the question of whether it is any longer plausible to infer from the fossil record, that over the past two million years, an ostensibly gradual increase in endocranial volumes, assigned to the genus Homo, can be correlated in a scientifically-meaningful manner with the gradual evolution of our effective executive working memory. It is argued that whereas Pan's effective working-memory capacity is relatively similar to that of its storage working-memory, our working memory is relatively larger with deeper executive control.
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Affiliation(s)
- Héctor M Manrique
- Department of Psychology and Sociology, Universidad de Zaragoza, Campus Universitario de Teruel, Ciudad Escolar, s/n. 44003 Teruel, Spain.
| | - Dwight W Read
- Department of Anthropology and Department of Statistics, University of California, Los Angeles, CA 90095, USA.
| | - Michael J Walker
- Department of Zoology and Physical Anthropology, Faculty of Biology, University of Murcia, Murcia, Spain.
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Israel A, Merzon E, Krone B, Faraone SV, Green I, Golan Cohen A, Vinker S, Cohen S, Ashkenazi S, Magen E, Weizman A, Manor I. The Association Between Repeated Measured Febrile Episodes During Early Childhood and Attention Deficit Hyperactivity Disorder: A Large-Scale Population-Based Study. J Atten Disord 2024; 28:677-685. [PMID: 38281128 DOI: 10.1177/10870547231215289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2024]
Abstract
OBJECTIVE We examined the association between the number, magnitude, and frequency of febrile episodes during the 0 to 4 years of life and subsequent diagnosis of ADHD. METHODS This population-based case-control study in an Israeli HMO, Leumit Health Services (LHS), uses a database for all LHS members aged 5 to 18 years between 1/1/2002 and 1/30/2022. The number and magnitude of measured fever episodes during the 0 to 4 years were recorded in individuals with ADHD (N = 18,558) and individually matched non-ADHD controls in a 1:2 ratio (N = 37,116). RESULTS A significant, independent association was found between the number and magnitude of febrile episodes during the 0 to 4 years and the probability of a later diagnosis of ADHD. Children who never had a measured temperature >37.5°C had a significantly lower rate of ADHD (OR = 0.834, 95% CI [0.802, 0.866], p < .0001). CONCLUSIONS Febrile episodes during 0 to 4 years are associated with a significantly increased rate of a later diagnosis of ADHD in a doseresponse relationship.
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Affiliation(s)
- Ariel Israel
- Department of Epidemiology and Disease Prevention, School of Public Health, Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Eugene Merzon
- Department of Epidemiology and Disease Prevention, School of Public Health, Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Adelson School of Medicine, Ariel University, Ariel, Israel
| | - Beth Krone
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Ilan Green
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | - Shlomo Vinker
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | - Shai Ashkenazi
- Adelson School of Medicine, Ariel University, Ariel, Israel
| | - Eli Magen
- Ben-Gurion University of the Negev Marcus Family Campus, Beer-Sheva, Israel
| | | | - Iris Manor
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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10
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McVey Neufeld SF, Ahn M, Kunze WA, McVey Neufeld KA. Adolescence, the Microbiota-Gut-Brain Axis, and the Emergence of Psychiatric Disorders. Biol Psychiatry 2024; 95:310-318. [PMID: 37839790 DOI: 10.1016/j.biopsych.2023.10.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/06/2023] [Accepted: 10/07/2023] [Indexed: 10/17/2023]
Abstract
Second only to early life, adolescence is a period of dramatic change and growth. For the developing young adult, this occurs against a backdrop of distinct environmental challenges and stressors. A significant body of work has identified an important role for the microbiota-gut-brain (MGB) axis in the development and function of the brain. Given that the MGB axis is both highly plastic during the teenage years and vulnerable to environmental stressors, more attention needs to be drawn to its potential role in the emergence of psychiatric illnesses, many of which first manifest during adolescence. Here, we review the current literature surrounding the developing microbiome, enteric nervous system, vagus nerve, and brain during the adolescent period. We also examine preclinical and clinical research involving the MGB axis during this dynamic developmental window and argue that more research is needed to further understand the role of the MGB in the pathogenesis of brain disorders. Greater understanding of the adolescent MGB axis will open up the exciting potential for new microbial-based therapeutics for the treatment of these often-refractory psychiatric illnesses.
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Affiliation(s)
| | - Matthew Ahn
- McMaster Brain-Body Institute at St Joseph's Healthcare, McMaster University, Hamilton, Ontario, Canada
| | - Wolfgang A Kunze
- McMaster Brain-Body Institute at St Joseph's Healthcare, McMaster University, Hamilton, Ontario, Canada
| | - Karen-Anne McVey Neufeld
- McMaster Brain-Body Institute at St Joseph's Healthcare, McMaster University, Hamilton, Ontario, Canada.
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11
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Kiss O, Qu Z, Müller-Oehring EM, Baker FC, Mirzasoleiman B. Sleep, brain systems, and persistent stress in early adolescents during COVID-19: Insights from the ABCD study. J Affect Disord 2024; 346:234-241. [PMID: 37944709 PMCID: PMC10842722 DOI: 10.1016/j.jad.2023.10.158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/27/2023] [Accepted: 10/30/2023] [Indexed: 11/12/2023]
Abstract
PURPOSE The first year of the COVID-19 pandemic constituted a major life stress event for many adolescents, associated with disrupted school, behaviors, social networks, and health concerns. However, pandemic-related stress was not equivalent for everyone and could have been influenced by pre-pandemic factors including brain structure and sleep, which both undergo substantial development during adolescence. Here, we analyzed clusters of perceived stress levels across the pandemic and determined developmentally relevant pre-pandemic risk factors in brain structure and sleep of persistently high stress during the first year of the COVID-19 pandemic. METHODS We investigated longitudinal changes in perceived stress at six timepoints across the first year of the pandemic (May 2020-March 2021) in 5559 adolescents (50 % female; age range: 11-14 years) in the United States (U.S.) participating in the Adolescent Brain Cognitive Development (ABCD) study. In 3141 of these adolescents, we fitted machine learning models to identify the most important pre-pandemic predictors from structural MRI brain measures and self-reported sleep data that were associated with persistently high stress across the first year of the pandemic. RESULTS Patterns of perceived stress levels varied across the pandemic, with 5 % reporting persistently high stress. Our classifiers accurately detected persistently high stress (AUC > 0.7). Pre-pandemic brain structure, specifically cortical volume in temporal regions, and cortical thickness in multiple parietal and occipital regions, predicted persistent stress. Pre-pandemic sleep difficulties and short sleep duration were also strong predictors of persistent stress, along with more advanced pubertal stage. CONCLUSIONS Adolescents showed variable stress responses during the first year of the COVID-19 pandemic, and some reported persistently high stress across the whole first year. Vulnerability to persistent stress was evident in several brain structural and self-reported sleep measures, collected before the pandemic, suggesting the relevance of other pre-existing individual factors beyond pandemic-related factors, for persistently high stress responses.
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Affiliation(s)
- Orsolya Kiss
- Center for Health Sciences, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA.
| | - Zihan Qu
- Electrical and Computer Engineering Department, University of California Los Angeles, 420 Westwood Plaza, Los Angeles, CA 90095, USA
| | - Eva M Müller-Oehring
- Center for Health Sciences, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA; Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA 94305, USA
| | - Fiona C Baker
- Center for Health Sciences, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA; Brain Function Research Group, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa
| | - Baharan Mirzasoleiman
- Computer Science Department, University of California Los Angeles, 404 Westwood Plaza, Los Angeles, CA 90095, USA
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12
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Knights H, Coleman A, Hobbs NZ, Tabrizi SJ, Scahill RI. Freesurfer Software Update Significantly Impacts Striatal Volumes in the Huntington's Disease Young Adult Study and Will Influence HD-ISS Staging. J Huntingtons Dis 2024; 13:77-90. [PMID: 38489194 DOI: 10.3233/jhd-231512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
Abstract
Background The Huntington's Disease Integrated Staging System (HD-ISS) defined disease onset using volumetric cut-offs for caudate and putamen derived from FreeSurfer 6 (FS6). The impact of the latest software update (FS7) on volumes remains unknown. The Huntington's Disease Young Adult Study (HD-YAS) is appropriately positioned to explore differences in FS bias when detecting early atrophy. Objective Explore the relationships and differences between raw caudate and putamen volumes, calculated total intracranial volumes (cTICV), and adjusted caudate and putamen volumes, derived from FS6 and FS7, in HD-YAS. Methods Images from 123 participants were segmented and quality controlled. Relationships and differences between volumes were explored using intraclass correlation (ICC) and Bland-Altman analysis. Results Across the whole cohort, ICC for raw caudate and putamen was 0.99, cTICV 0.93, adjusted caudate 0.87, and adjusted putamen 0.86 (all p < 0.0005). Compared to FS6, FS7 calculated: i) larger raw caudate (+0.8%, p < 0.00005) and putamen (+1.9%, p < 0.00005), with greater difference for larger volumes; and ii) smaller cTICV (-5.1%, p < 0.00005), with greater difference for smaller volumes. The systematic and proportional difference in cTICV was greater than raw volumes. When raw volumes were adjusted for cTICV, these effects compounded (adjusted caudate +7.0%, p < 0.00005; adjusted putamen +8.2%, p < 0.00005), with greater difference for larger volumes. Conclusions As new software is released, it is critical that biases are explored since differences have the potential to significantly alter the findings of HD trials. Until conversion factors are defined, the HD-ISS must be applied using FS6. This should be incorporated into the HD-ISS online calculator.
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Affiliation(s)
- Harry Knights
- Department of Neurodegenerative Disease, Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Annabelle Coleman
- Department of Neurodegenerative Disease, Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Nicola Z Hobbs
- Department of Neurodegenerative Disease, Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah J Tabrizi
- Department of Neurodegenerative Disease, Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rachael I Scahill
- Department of Neurodegenerative Disease, Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
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13
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Hon YY, Wang J, Abodakpi H, Balakrishnan A, Pacanowski M, Chakder S, Smpokou P, Donohue K, Wang YC. Dose selection for biological enzyme replacement therapy indicated for inborn errors of metabolism. Clin Transl Sci 2023; 16:2438-2457. [PMID: 37735717 PMCID: PMC10719471 DOI: 10.1111/cts.13652] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/29/2023] [Accepted: 09/04/2023] [Indexed: 09/23/2023] Open
Abstract
This paper summarizes key features of the dose-finding strategies used in the development of 11 approved new molecular entities that are first-in-class enzyme replacement therapy (ERT), with a goal to gain insight into the dose exploration approaches to inform efficient dose-finding in future development of biological products for Inborn Errors of Metabolism (IEM). Dose exploration should preferably begin in in vitro studies, followed by testing multiple doses in an appropriate animal disease model, when available, which can provide important information for dose assessment in humans. Performing adequate dose-finding in early phase clinical studies in a well-defined study population, including pediatric subjects, is generally critical to inform dose selection for pivotal trials; alternatively, additional dose exploration can be incorporated as part of a pivotal trial. Two important considerations for successful dose selection include (1) identifying appropriate disease-specific endpoints, including pharmacodynamic (PD) end points and intermediate clinical end points or clinical end points, and (2) designing a study with adequate treatment durations for evaluating these end points. Appropriately selected PD biomarkers is useful for dose selection, and early development of these biomarkers can facilitate the overall clinical development program. Optimization of ERT doses, as well as evaluations of patient intrinsic factors and/or immune tolerance strategies may be necessary to overcome antibody responses or increase efficacy in IEM.
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Affiliation(s)
- Yuen Yi Hon
- Division of Rare Diseases and Medical Genetics, Office of Rare Diseases, Pediatrics, Urologic and Reproductive Medicine, Office of New Drugs (OND), Center of Drug Evaluation and Research (CDER)Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Jie Wang
- Office of Clinical Pharmacology, Office of Translational Sciences, CDERFood and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Henrietta Abodakpi
- Office of Clinical Pharmacology, Office of Translational Sciences, CDERFood and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Anand Balakrishnan
- Office of Clinical Pharmacology, Office of Translational Sciences, CDERFood and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Michael Pacanowski
- Office of Clinical Pharmacology, Office of Translational Sciences, CDERFood and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Sushanta Chakder
- Division of Pharmacology and Toxicology, Office of Immunology and Inflammation, OND, CDERFood and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Patroula Smpokou
- Division of Rare Diseases and Medical Genetics, Office of Rare Diseases, Pediatrics, Urologic and Reproductive Medicine, Office of New Drugs (OND), Center of Drug Evaluation and Research (CDER)Food and Drug Administration (FDA)Silver SpringMarylandUSA
- Present address:
BioMarin Pharmaceutical Inc.San RafaelCaliforniaUSA
| | - Kathleen Donohue
- Division of Rare Diseases and Medical Genetics, Office of Rare Diseases, Pediatrics, Urologic and Reproductive Medicine, Office of New Drugs (OND), Center of Drug Evaluation and Research (CDER)Food and Drug Administration (FDA)Silver SpringMarylandUSA
| | - Yow‐Ming C. Wang
- Office of Clinical Pharmacology, Office of Translational Sciences, CDERFood and Drug Administration (FDA)Silver SpringMarylandUSA
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14
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Cacciaguerra L, Rocca MA, Filippi M. Understanding the Pathophysiology and Magnetic Resonance Imaging of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders. Korean J Radiol 2023; 24:1260-1283. [PMID: 38016685 DOI: 10.3348/kjr.2023.0360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/09/2023] [Accepted: 08/21/2023] [Indexed: 11/30/2023] Open
Abstract
Magnetic resonance imaging (MRI) has been extensively applied in the study of multiple sclerosis (MS), substantially contributing to diagnosis, differential diagnosis, and disease monitoring. MRI studies have significantly contributed to the understanding of MS through the characterization of typical radiological features and their clinical or prognostic implications using conventional MRI pulse sequences and further with the application of advanced imaging techniques sensitive to microstructural damage. Interpretation of results has often been validated by MRI-pathology studies. However, the application of MRI techniques in the study of neuromyelitis optica spectrum disorders (NMOSD) remains an emerging field, and MRI studies have focused on radiological correlates of NMOSD and its pathophysiology to aid in diagnosis, improve monitoring, and identify relevant prognostic factors. In this review, we discuss the main contributions of MRI to the understanding of MS and NMOSD, focusing on the most novel discoveries to clarify differences in the pathophysiology of focal inflammation initiation and perpetuation, involvement of normal-appearing tissue, potential entry routes of pathogenic elements into the CNS, and existence of primary or secondary mechanisms of neurodegeneration.
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Affiliation(s)
- Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milano, Italy.
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15
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Etami Y, Lildharrie C, Manza P, Wang GJ, Volkow ND. Neuroimaging in Adolescents: Post-Traumatic Stress Disorder and Risk for Substance Use Disorders. Genes (Basel) 2023; 14:2113. [PMID: 38136935 PMCID: PMC10743116 DOI: 10.3390/genes14122113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 11/17/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
Trauma in childhood and adolescence has long-term negative consequences in brain development and behavior and increases the risk for psychiatric disorders. Among them, post-traumatic stress disorder (PTSD) during adolescence illustrates the connection between trauma and substance misuse, as adolescents may utilize substances to cope with PTSD. Drug misuse may in turn lead to neuroadaptations in learning processes that facilitate the consolidation of traumatic memories that perpetuate PTSD. This reflects, apart from common genetic and epigenetic modifications, overlapping neurocircuitry engagement triggered by stress and drug misuse that includes structural and functional changes in limbic brain regions and the salience, default-mode, and frontoparietal networks. Effective strategies to prevent PTSD are needed to limit the negative consequences associated with the later development of a substance use disorder (SUD). In this review, we will examine the link between PTSD and SUDs, along with the resulting effects on memory, focusing on the connection between the development of an SUD in individuals who struggled with PTSD in adolescence. Neuroimaging has emerged as a powerful tool to provide insight into the brain mechanisms underlying the connection of PTSD in adolescence and the development of SUDs.
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Affiliation(s)
| | | | | | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD 20892, USA; (Y.E.); (C.L.); (P.M.); (N.D.V.)
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16
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Carrica LK, Gulley JM. The role of sex and drug use during adolescence in determining the risk for adverse consequences of amphetamines. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2023; 99:125-144. [PMID: 38467479 DOI: 10.1016/bs.apha.2023.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Use of amphetamines during adolescence, a critical period of brain development and reorganization, may lead to particularly adverse outcomes that are long-lasting. Similarly, female users may be uniquely vulnerable to certain aspects of drug use. A recognition of the role of use during adolescence and sex on outcomes of amphetamine and methamphetamine exposure are of critical importance in understanding and treating substance use disorders. This chapter highlights what human research, which has been largely epidemiological, suggests about sex and age differences in drug use patterns and outcomes. We also discuss work in laboratory animals that has typically utilized rats or mice exposed to drugs in a non-contingent manner (i.e., involuntarily) or through volitional self-administration. Lastly, we draw attention to the fact that advancing our understanding of the effects of amphetamine and methamphetamine use, the development of problematic drug taking, and the mechanisms that contribute to relapse will require an emphasis on inclusion of age and sex as moderating factors in future studies.
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Affiliation(s)
- Lauren K Carrica
- Department of Psychology, University of Illinois, Urbana-Champaign, IL, United States
| | - Joshua M Gulley
- Department of Psychology, University of Illinois, Urbana-Champaign, IL, United States; Neuroscience Program, University of Illinois, Urbana-Champaign, IL, United States; Carl R. Woese Institute for Genomic Biology, University of Illinois, Urbana-Champaign, IL, United States.
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17
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Borairi S, Ozdemir B, Jenkins J, Shah PS, Kingdom J, Ganea P. A follow up investigation of placental pathology, responsive parenting, and preschool children's executive functioning and language development. Child Neuropsychol 2023:1-18. [PMID: 37811813 DOI: 10.1080/09297049.2023.2264535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 09/22/2023] [Indexed: 10/10/2023]
Abstract
Despite documented effects linking underlying placental diseases and neurological impairments in children, little is known about the long-term effects of placental pathology on children's neurocognitive outcomes. In addition, maternal responsivity, known to positively influence early postnatal cognitive development, may act to protect children from putative adverse effects of placental pathology. The current study is a follow up of medically healthy, term born, preschool age children, born with placental pathology. A sample of 118 children (45 comparison children with normal placental findings, 73 born with placental pathology) were followed when children were 3-4 years old. In comparison to children born to mothers with normal placentas, placental pathology was associated with poorer performance in the executive function involving cognitive flexibility, but not inhibitory control or receptive language. Maternal responsivity was observed to be marginally protective on the impact of placental pathology risk on cognitive flexibility, but this was not seen for either inhibitory control or receptive language.
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Affiliation(s)
- Sahar Borairi
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada
| | - Begum Ozdemir
- Department of Psychology, Maltepe University, Maltepe, Turkey
| | - Jennifer Jenkins
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada
| | - Prakesh S Shah
- Department of Pediatrics, Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - John Kingdom
- Department of Obstetrics and Gynecology, Maternal Fetal Medicine Division, Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - Patricia Ganea
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada
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18
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Lamontagne-Caron R, Desrosiers P, Potvin O, Doyon N, Duchesne S. Predicting cognitive decline in a low-dimensional representation of brain morphology. Sci Rep 2023; 13:16793. [PMID: 37798311 PMCID: PMC10556003 DOI: 10.1038/s41598-023-43063-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 09/19/2023] [Indexed: 10/07/2023] Open
Abstract
Identifying early signs of neurodegeneration due to Alzheimer's disease (AD) is a necessary first step towards preventing cognitive decline. Individual cortical thickness measures, available after processing anatomical magnetic resonance imaging (MRI), are sensitive markers of neurodegeneration. However, normal aging cortical decline and high inter-individual variability complicate the comparison and statistical determination of the impact of AD-related neurodegeneration on trajectories. In this paper, we computed trajectories in a 2D representation of a 62-dimensional manifold of individual cortical thickness measures. To compute this representation, we used a novel, nonlinear dimension reduction algorithm called Uniform Manifold Approximation and Projection (UMAP). We trained two embeddings, one on cortical thickness measurements of 6237 cognitively healthy participants aged 18-100 years old and the other on 233 mild cognitively impaired (MCI) and AD participants from the longitudinal database, the Alzheimer's Disease Neuroimaging Initiative database (ADNI). Each participant had multiple visits ([Formula: see text]), one year apart. The first embedding's principal axis was shown to be positively associated ([Formula: see text]) with participants' age. Data from ADNI is projected into these 2D spaces. After clustering the data, average trajectories between clusters were shown to be significantly different between MCI and AD subjects. Moreover, some clusters and trajectories between clusters were more prone to host AD subjects. This study was able to differentiate AD and MCI subjects based on their trajectory in a 2D space with an AUC of 0.80 with 10-fold cross-validation.
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Affiliation(s)
- Rémi Lamontagne-Caron
- Département de médecine, Université Laval, Quebec, QC, G1V 0A6, Canada.
- Centre de recherche CERVO, Quebec, QC, G1J 2G3, Canada.
| | - Patrick Desrosiers
- Centre de recherche CERVO, Quebec, QC, G1J 2G3, Canada
- Centre interdisciplinaire en modélisation mathématique, Université Laval, Quebec, QC, G1V 0A6, Canada
- Département de physique, de génie physique et d'optique, Université Laval, Quebec, QC, G1V 0A6, Canada
| | | | - Nicolas Doyon
- Centre de recherche CERVO, Quebec, QC, G1J 2G3, Canada
- Centre interdisciplinaire en modélisation mathématique, Université Laval, Quebec, QC, G1V 0A6, Canada
- Département de mathématiques et de statistique, Université Laval, Quebec, QC, G1V 0A6, Canada
| | - Simon Duchesne
- Centre de recherche CERVO, Quebec, QC, G1J 2G3, Canada
- Département de radiologie et médecine nucléaire, Université Laval, Quebec, QC, G1V 0A6, Canada
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19
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Vogt LM, Yan H, Santyr B, Breitbart S, Anderson M, Germann J, Lizarraga KJ, Hewitt AL, Fasano A, Ibrahim GM, Gorodetsky C. Deep Brain Stimulation for Refractory Status Dystonicus in Children: Multicenter Case Series and Systematic Review. Ann Neurol 2023. [PMID: 37714824 DOI: 10.1002/ana.26799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 09/14/2023] [Accepted: 09/14/2023] [Indexed: 09/17/2023]
Abstract
OBJECTIVE We sought to better understand the workflow, outcomes, and complications of deep brain stimulation (DBS) for pediatric status dystonicus (SD). We present a systematic review, alongside a multicenter case series of pediatric patients with SD treated with DBS. METHODS We collected individual data regarding treatment, stimulation parameters, and dystonia severity for a multicenter case series (n = 8) and all previously published cases (n = 77). Data for case series were used to create probabilistic voxelwise maps of stimulated tissue associated with dystonia improvement. RESULTS In our institutional series, DBS was implanted a mean of 25 days after SD onset. Programming began a mean of 1.6 days after surgery. All 8 patients in our case series and 73 of 74 reported patients in the systematic review had resolution of their SD with DBS, most within 2 to 4 weeks of surgery. Mean follow-up for patients in the case series was 16 months. DBS target for all patients in the case series and 68 of 77 in our systematic review was the globus pallidus pars interna (GPi). In our case series, stimulation of the posterior-ventrolateral GPi was associated with improved dystonia. Mean dystonia improvement was 32% and 51% in our institutional series and systematic review, respectively. Mortality was 4% in the review, which is lower than reported for treatment with pharmacotherapy alone (10-12.5%). INTERPRETATION DBS is a feasible intervention with potential to reverse refractory pediatric SD and improve survival. More work is needed to increase awareness of DBS in this setting, so that it can be implemented in a timely manner. ANN NEUROL 2023.
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Affiliation(s)
- Lindsey M Vogt
- Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Han Yan
- Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Brendan Santyr
- Krembil Brain Institute, Toronto, Ontario, Canada
- Center for Advancing Neurotechnological Innovation to Application, Toronto, Ontario, Canada
| | - Sara Breitbart
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Melanie Anderson
- Library Services, University Health Network, Toronto, Ontario, Canada
| | - Jürgen Germann
- Krembil Brain Institute, Toronto, Ontario, Canada
- Center for Advancing Neurotechnological Innovation to Application, Toronto, Ontario, Canada
| | - Karlo J Lizarraga
- Motor Physiology and Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA
| | - Angela L Hewitt
- Motor Physiology and Neuromodulation Program, Division of Movement Disorders, Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA
- Division of Child Neurology, Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA
| | - Alfonso Fasano
- Krembil Brain Institute, Toronto, Ontario, Canada
- Center for Advancing Neurotechnological Innovation to Application, Toronto, Ontario, Canada
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
- Division of Neurology, University of Toronto, Toronto, Ontario, Canada
| | - George M Ibrahim
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Surgery, University of Toronto, Toronto, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Carolina Gorodetsky
- Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada
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20
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Kiss O, Goldstone A, de Zambotti M, Yüksel D, Hasler BP, Franzen PL, Brown SA, De Bellis MD, Nagel BJ, Nooner KB, Tapert SF, Colrain IM, Clark DB, Baker FC. Effects of emerging alcohol use on developmental trajectories of functional sleep measures in adolescents. Sleep 2023; 46:zsad113. [PMID: 37058610 PMCID: PMC10848227 DOI: 10.1093/sleep/zsad113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 02/17/2023] [Indexed: 04/16/2023] Open
Abstract
STUDY OBJECTIVES Adolescence is characterized by significant brain development, accompanied by changes in sleep timing and architecture. It also is a period of profound psychosocial changes, including the initiation of alcohol use; however, it is unknown how alcohol use affects sleep architecture in the context of adolescent development. We tracked developmental changes in polysomnographic (PSG) and electroencephalographic (EEG) sleep measures and their relationship with emergent alcohol use in adolescents considering confounding effects (e.g. cannabis use). METHODS Adolescents (n = 94, 43% female, age: 12-21 years) in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study had annual laboratory PSG recordings across 4-years. Participants were no/low drinkers at baseline. RESULTS Linear mixed effect models showed developmental changes in sleep macrostructure and EEG, including a decrease in slow wave sleep and slow wave (delta) EEG activity with advancing age. Emergent moderate/heavy alcohol use across three follow-up years was associated with a decline in percentage rapid eye movement (REM) sleep over time, a longer sleep onset latency (SOL) and shorter total sleep time (TST) in older adolescents, and lower non-REM delta and theta power in males. CONCLUSIONS These longitudinal data show substantial developmental changes in sleep architecture. Emergent alcohol use during this period was associated with altered sleep continuity, architecture, and EEG measures, with some effects dependent on age and sex. These effects, in part, could be attributed to the effects of alcohol on underlying brain maturation processes involved in sleep-wake regulation.
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Affiliation(s)
- Orsolya Kiss
- Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, USA
| | - Aimée Goldstone
- Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, USA
| | | | - Dilara Yüksel
- Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, USA
| | - Brant P Hasler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Peter L Franzen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Sandra A Brown
- Department of Psychiatry, University of California, San Diego, San Diego, CA, USA
| | - Michael D De Bellis
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Bonnie J Nagel
- School of Medicine, Division of Clinical Psychology, Oregon Health and Sciences University, Portland, OR, USA
| | - Kate B Nooner
- Psychology Department, University of North Carolina Wilmington, Wilmington, NC, USA
| | - Susan F Tapert
- Department of Psychiatry, University of California, San Diego, San Diego, CA, USA
| | - Ian M Colrain
- Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, USA
| | - Duncan B Clark
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Fiona C Baker
- Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, USA
- Brain Function Research Group, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa
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21
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Pandey SK, Kalmar CL, Bonfield CM, Golinko MS. Frontal sinus hypoplasia in unoperated older patients with craniosynostosis: a pilot study. Childs Nerv Syst 2023; 39:2139-2146. [PMID: 37133486 DOI: 10.1007/s00381-023-05927-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 03/17/2023] [Indexed: 05/04/2023]
Abstract
PURPOSE The purpose of this study is to determine whether patients with unoperated craniosynostosis have different frontal sinus pneumatization than unaffected controls. METHODS Retrospective review was performed between 2009 and 2020 of previously unoperated patients with craniosynostosis older than 5 years old at first presentation to our institution. Total frontal sinus volume (FSV) was calculated using 3D volume rendering tool in Sectra IDS7 PACS system. Age-matched normative FSV data was collected from 100 normal CT scans for the control group. The two groups were statistically compared using Fisher's exact test and T-test. RESULTS Study group included nine patients, 5-39 years old, median age 7 years. Frontal sinus pneumatization was absent in 12% of the normal 7-year-old controls, while frontal sinus pneumatization was absent in 89% of the studied craniosynostosis patients (p < .001). Mean FSV of the study group (113 ± 340 mm3) was significantly different from that of age matched control mean FSV (2016 ± 2529 mm3) (p = .027). CONCLUSIONS Frontal sinus pneumatization is suppressed in unreleased craniosynostosis and may be an intracranial space conservation phenomenon. This absent frontal sinus can have implications in future frontal region trauma and frontal osteotomies.
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Affiliation(s)
- Sonia K Pandey
- Department of Plastic Surgery, Vanderbilt University Medical Center, 1211 Medical Center Dr, Nashville, TN, 37232, USA
| | - Christopher L Kalmar
- Department of Plastic Surgery, Vanderbilt University Medical Center, 1211 Medical Center Dr, Nashville, TN, 37232, USA.
| | | | - Michael S Golinko
- Department of Plastic Surgery, Vanderbilt University Medical Center, 1211 Medical Center Dr, Nashville, TN, 37232, USA
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22
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González Fuentes J, Cebada-Sánchez S, Arroyo-Jiménez MDM, Muñoz-López M, Rivas-Infante E, Lozano G, Mansilla F, Cortes F, Insausti R, Marcos P. Study of the human hippocampal formation: a method for histological and magnetic resonance correlation in perinatal cases. Brain Imaging Behav 2023; 17:403-413. [PMID: 37024762 PMCID: PMC10435394 DOI: 10.1007/s11682-023-00768-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/20/2023] [Indexed: 04/08/2023]
Abstract
Little information is available on the magnetic resonance imaging (MRI) determination of the hippocampal formation (HF) during the perinatal period. However, this exploration is increasingly used, which requires defining visible HF landmarks on MRI images, validated through histological analysis. This study aims to provide a protocol to identify HF landmarks on MRI images, followed by histological validation through serial sections of the temporal lobe of the samples examined, to assess the longitudinal extent of the hippocampus during the perinatal period. We examined ex vivo MRI images from nine infant control brain samples. Histological validation of the hippocampal formation MRI images was obtained through serial sectioning and examination of Nissl-stained sections at 250 μm intervals along the entire length of the hippocampal formation. Up to six landmarks were identified both in MRI images and the serial histological sections. Proceeding in an anterior to posterior (rostrocaudal) direction, these were as follows: 1) the limen insulae (fronto-temporal junction); 2) the beginning of the amygdaloid complex; 3) the beginning of the lateral ventricle; 4) the caudal limit of the uncus, indicated by the start of the lateral geniculate nucleus (at the level of the gyrus intralimbicus); 5) the end of the lateral geniculate nucleus (beginning of the pulvinar); and 6) the beginning of the fornix. After histological validation of each of these landmarks, the full longitudinal length of the hippocampal formation and distances between landmarks were calculated. No statistically significant differences were found in total length or between landmarks. While the HF is anatomically organized at birth, its annotation is particularly challenging to perform. The histological validation of HF landmarks allows a better understanding of MRI images. The proposed protocol could be useful to assess MRI hippocampal quantification in children and possible variations due to different neurological diseases.
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Affiliation(s)
- Joaquín González Fuentes
- Centro Regional de Investigaciones Biomédicas (CRIB), Avenida de Almansa 14, 02006, Albacete, Spain.
- Department of Health Sciences, University of Castilla-La Mancha, School of Pharmacy, Albacete, Spain.
| | - Sandra Cebada-Sánchez
- Centro Regional de Investigaciones Biomédicas (CRIB), Avenida de Almansa 14, 02006, Albacete, Spain
- Human Neuroanatomy Laboratory, Department of Health Sciences, University of Castilla-La Mancha, School of Medicine, Albacete, Spain
| | - Maria Del Mar Arroyo-Jiménez
- Centro Regional de Investigaciones Biomédicas (CRIB), Avenida de Almansa 14, 02006, Albacete, Spain
- Human Neuroanatomy Laboratory, Department of Health Sciences, University of Castilla-La Mancha, School of Medicine, Albacete, Spain
| | - Mónica Muñoz-López
- Centro Regional de Investigaciones Biomédicas (CRIB), Avenida de Almansa 14, 02006, Albacete, Spain
- Human Neuroanatomy Laboratory, Department of Health Sciences, University of Castilla-La Mancha, School of Medicine, Albacete, Spain
| | - Eloy Rivas-Infante
- Servicio de Anatomía Patológica, Hospital Virgen del Rocío. Avenida Manuel Siurot, 41013, Sevilla, Spain
| | - Guillermo Lozano
- Centro Regional de Investigaciones Biomédicas (CRIB), Avenida de Almansa 14, 02006, Albacete, Spain
- Human Neuroanatomy Laboratory, Department of Health Sciences, University of Castilla-La Mancha, School of Medicine, Albacete, Spain
| | - Francisco Mansilla
- Radiology Department, University Hospital, Hermanos Falcó, 02006, Albacete, Spain
| | - Francisca Cortes
- Radiology Department, University Hospital, Hermanos Falcó, 02006, Albacete, Spain
| | - Ricardo Insausti
- Centro Regional de Investigaciones Biomédicas (CRIB), Avenida de Almansa 14, 02006, Albacete, Spain
- Human Neuroanatomy Laboratory, Department of Health Sciences, University of Castilla-La Mancha, School of Medicine, Albacete, Spain
| | - Pilar Marcos
- Centro Regional de Investigaciones Biomédicas (CRIB), Avenida de Almansa 14, 02006, Albacete, Spain
- Human Neuroanatomy Laboratory, Department of Health Sciences, University of Castilla-La Mancha, School of Medicine, Albacete, Spain
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23
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Joo Y, Lee S, Hwang J, Kim J, Cheon YH, Lee H, Kim S, Yurgelun-Todd DA, Renshaw PF, Yoon S, Lyoo IK. Differential alterations in brain structural network organization during addiction between adolescents and adults. Psychol Med 2023; 53:3805-3816. [PMID: 35440353 PMCID: PMC10317813 DOI: 10.1017/s0033291722000423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 01/06/2022] [Accepted: 02/04/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND The adolescent brain may be susceptible to the influences of illicit drug use. While compensatory network reorganization is a unique developmental characteristic that may restore several brain disorders, its association with methamphetamine (MA) use-induced damage during adolescence is unclear. METHODS Using independent component (IC) analysis on structural magnetic resonance imaging data, spatially ICs described as morphometric networks were extracted to examine the effects of MA use on gray matter (GM) volumes and network module connectivity in adolescents (51 MA users v. 60 controls) and adults (54 MA users v. 60 controls). RESULTS MA use was related to significant GM volume reductions in the default mode, cognitive control, salience, limbic, sensory and visual network modules in adolescents. GM volumes were also reduced in the limbic and visual network modules of the adult MA group as compared to the adult control group. Differential patterns of structural connectivity between the basal ganglia (BG) and network modules were found between the adolescent and adult MA groups. Specifically, adult MA users exhibited significantly reduced connectivity of the BG with the default network modules compared to control adults, while adolescent MA users, despite the greater extent of network GM volume reductions, did not show alterations in network connectivity relative to control adolescents. CONCLUSIONS Our findings suggest the potential of compensatory network reorganization in adolescent brains in response to MA use. The developmental characteristic to compensate for MA-induced brain damage can be considered as an age-specific therapeutic target for adolescent MA users.
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Affiliation(s)
- Yoonji Joo
- Ewha Brain Institute, Ewha Womans University, Seoul, South Korea
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, South Korea
| | - Suji Lee
- Ewha Brain Institute, Ewha Womans University, Seoul, South Korea
| | - Jaeuk Hwang
- Department of Psychiatry, Soonchunhyang University College of Medicine, Seoul, South Korea
| | - Jungyoon Kim
- Ewha Brain Institute, Ewha Womans University, Seoul, South Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul, South Korea
| | - Young-Hoon Cheon
- Department of Psychiatry, Incheon Chamsarang Hospital, Incheon, South Korea
| | - Hyangwon Lee
- Ewha Brain Institute, Ewha Womans University, Seoul, South Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul, South Korea
| | - Shinhye Kim
- Ewha Brain Institute, Ewha Womans University, Seoul, South Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul, South Korea
| | - Deborah A. Yurgelun-Todd
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Diagnostic Neuroimaging, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, VA VISN 19 Mental Illness Research, Education and Clinical Center (MIRECC), Salt Lake City, UT, USA
| | - Perry F. Renshaw
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Diagnostic Neuroimaging, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, VA VISN 19 Mental Illness Research, Education and Clinical Center (MIRECC), Salt Lake City, UT, USA
| | - Sujung Yoon
- Ewha Brain Institute, Ewha Womans University, Seoul, South Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul, South Korea
| | - In Kyoon Lyoo
- Ewha Brain Institute, Ewha Womans University, Seoul, South Korea
- Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, South Korea
- Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul, South Korea
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
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24
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Jacobson MM, Jenkins LM, Feldman DA, Crane NA, Langenecker SA. Reduced connectivity of the cognitive control neural network at rest in young adults who had their first drink of alcohol prior to age 18. Psychiatry Res Neuroimaging 2023; 332:111642. [PMID: 37086604 PMCID: PMC10247408 DOI: 10.1016/j.pscychresns.2023.111642] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/21/2023] [Accepted: 04/05/2023] [Indexed: 04/24/2023]
Abstract
The cognitive control network (CCN) is an important network responsible for performing and modulating executive functions. In adolescents, alcohol use has been associated with weaker cognitive control, higher reward sensitivity, and later-in-life alcohol problems. Given that the CCN continues to develop into young adulthood, it is important to understand relations between early alcohol use, the CCN, and reward networks. Participants included individuals 18-23 years without alcohol use disorder. Based upon self-reported age of first alcoholic drink, participants were split into two groups: Early (onset) Drinkers (first drink < age 18, N = 52) and Late (onset) Drinkers (first drink > age 18, N = 44). All participants underwent an 8-minute resting-state fMRI scan. Seed regions of interest included the anterior dorsolateral prefrontal cortex (DLPFC), amygdala, and ventral striatum. Early Drinkers demonstrated significant reduced connectivity of CCN regions, including bilateral anterior DLPFC, compared to Late Drinkers. There were no significant differences between Early and Late Drinkers in connectivity between reward and CCN regions. These results suggest that individuals who begin drinking alcohol earlier in life may have alterations in the development of the CCN; however, longitudinal research is necessary to determine whether lower connectivity precedes or follows early alcohol use, and any other relevant factors.
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Affiliation(s)
- Maci M Jacobson
- Department of Psychiatry, The University of Utah, United States; Interdisciplinary Neuroscience Program, The University of Utah, United States.
| | - Lisanne M Jenkins
- Department of Psychiatry and Behavioral Sciences, Northwestern University, United States; Department of Psychiatry, The University of Illinois at Chicago, United States
| | | | - Natania A Crane
- Department of Psychiatry, The University of Illinois at Chicago, United States
| | - Scott A Langenecker
- Department of Psychiatry, The University of Utah, United States; Interdisciplinary Neuroscience Program, The University of Utah, United States; Department of Psychiatry, The University of Illinois at Chicago, United States
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25
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Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 42] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
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Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
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DiPiero M, Rodrigues PG, Gromala A, Dean DC. Applications of advanced diffusion MRI in early brain development: a comprehensive review. Brain Struct Funct 2023; 228:367-392. [PMID: 36585970 PMCID: PMC9974794 DOI: 10.1007/s00429-022-02605-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/21/2022] [Indexed: 01/01/2023]
Abstract
Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.
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Affiliation(s)
- Marissa DiPiero
- Department of Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Alyssa Gromala
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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27
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Dibbs RP, Ferry AM, Davies L, Bauer DF, Buchanan EP, Beh HZ. Elevated Intracranial Pressure After Primary Surgical Correction of Sagittal Suture Craniosynostosis. Craniomaxillofac Trauma Reconstr 2023; 16:70-77. [PMID: 36824189 PMCID: PMC9941297 DOI: 10.1177/19433875211064680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Study Design: A Case Report. Objective: Craniosynostosis is a craniofacial condition defined by premature fusion of at least one cranial suture. Resynostosis or secondary craniosynostosis of a previously patent adjacent suture following primary repair is a relatively common complication. While studies have assessed the rates of secondary craniosynostosis and subsequent reoperation, extremely limited data regarding reoperation techniques is available. Methods: We present a unique case of a pediatric patient with sagittal craniosynostosis who previously underwent a modified pi procedure and later developed resynostosis of the sagittal suture and secondary synostosis of the bicoronal sutures. We subsequently performed total cranial vault reconstruction with virtual surgical planning (VSP). Results: At his 31-month postoperative follow-up, he displayed normal head shape and denied any clinical signs of elevated intracranial pressures with a normal ophthalmological exam. Conclusions: The reoperation was successful with no significant postoperative complications noted. Performing geometric expansion with VSP to manage fusion of a previously open suture following primary treatment of sagittal synostosis should be considered within the armamentarium of operative options.
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Affiliation(s)
- Rami P. Dibbs
- Division of Plastic Surgery, Texas Children’s Hospital, Houston, TX, USA
- Division of Plastic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Andrew M. Ferry
- Division of Plastic Surgery, Texas Children’s Hospital, Houston, TX, USA
- Division of Plastic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Lesley Davies
- Division of Plastic Surgery, Texas Children’s Hospital, Houston, TX, USA
| | - David F. Bauer
- Department of Neurosurgery, Texas Children’s Hospital, Houston, TX, USA
| | - Edward P. Buchanan
- Division of Plastic Surgery, Texas Children’s Hospital, Houston, TX, USA
- Division of Plastic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Han Zhuang Beh
- Division of Plastic Surgery, Texas Children’s Hospital, Houston, TX, USA
- Division of Plastic Surgery, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA
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28
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Lv Z, Li Y, Wang Y, Cong F, Li X, Cui W, Han C, Wei Y, Hong X, Liu Y, Ma L, Jiao Y, Zhang C, Li H, Jin M, Wang L, Ni S, Liu J. Safety and efficacy outcomes after intranasal administration of neural stem cells in cerebral palsy: a randomized phase 1/2 controlled trial. Stem Cell Res Ther 2023; 14:23. [PMID: 36759901 PMCID: PMC9910250 DOI: 10.1186/s13287-022-03234-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 06/05/2022] [Indexed: 02/11/2023] Open
Abstract
BACKGROUND Neural stem cells (NSCs) are believed to have the most therapeutic potential for neurological disorders because they can differentiate into various neurons and glial cells. This research evaluated the safety and efficacy of intranasal administration of NSCs in children with cerebral palsy (CP). The functional brain network (FBN) analysis based on electroencephalogram (EEG) and voxel-based morphometry (VBM) analysis based on T1-weighted images were performed to evaluate functional and structural changes in the brain. METHODS A total of 25 CP patients aged 3-12 years were randomly assigned to the treatment group (n = 15), which received an intranasal infusion of NSCs loaded with nasal patches and rehabilitation therapy, or the control group (n = 10) received rehabilitation therapy only. The primary endpoints were the safety (assessed by the incidence of adverse events (AEs), laboratory and imaging examinations) and the changes in the Gross Motor Function Measure-88 (GMFM-88), the Activities of Daily Living (ADL) scale, the Sleep Disturbance Scale for Children (SDSC), and some adapted scales. The secondary endpoints were the FBN and VBM analysis. RESULTS There were only four AEs happened during the 24-month follow-up period. There was no significant difference in the laboratory examinations before and after treatment, and the magnetic resonance imaging showed no abnormal nasal and intracranial masses. Compared to the control group, patients in the treatment group showed apparent improvements in GMFM-88 and ADL 24 months after treatment. Compared with the baseline, the scale scores of the Fine Motor Function, Sociability, Life Adaptability, Expressive Ability, GMFM-88, and ADL increased significantly in the treatment group 24 months after treatment, while the SDSC score decreased considerably. Compared with baseline, the FBN analysis showed a substantial decrease in brain network energy, and the VBM analysis showed a significant increase in gray matter volume in the treatment group after NSCs treatment. CONCLUSIONS Our results showed that intranasal administration of NSCs was well-tolerated and potentially beneficial in children with CP. TRIAL REGISTRATION The study was registered in ClinicalTrials.gov (NCT03005249, registered 29 December 2016, https://www. CLINICALTRIALS gov/ct2/show/NCT03005249 ) and the Medical Research Registration Information System (CMR-20161129-1003).
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Affiliation(s)
- Zhongyue Lv
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China
| | - Ying Li
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China
| | - Yachen Wang
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China
| | - Fengyu Cong
- grid.30055.330000 0000 9247 7930School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, Liaoning Province, China ,grid.9681.60000 0001 1013 7965Faculty of Information Technology, University of Jyvaskyla, 40014 Jyvaskyla, Finland
| | - Xiaoyan Li
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China
| | - Wanming Cui
- grid.452435.10000 0004 1798 9070Department of Ent, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning China
| | - Chao Han
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China
| | - Yushan Wei
- grid.452435.10000 0004 1798 9070Scientific Research Department, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning China
| | - Xiaojun Hong
- grid.452435.10000 0004 1798 9070Neurophysiological Center, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning China
| | - Yong Liu
- grid.452435.10000 0004 1798 9070Department of Rehabilitation, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning China
| | - Luyi Ma
- grid.452435.10000 0004 1798 9070Department of Pediatrics, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning China
| | - Yang Jiao
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China ,grid.452435.10000 0004 1798 9070Department of Neurology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning China
| | - Chi Zhang
- grid.30055.330000 0000 9247 7930School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, Liaoning Province, China
| | - Huanjie Li
- grid.30055.330000 0000 9247 7930School of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning China
| | - Mingyan Jin
- grid.30055.330000 0000 9247 7930School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, Liaoning Province, China
| | - Liang Wang
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China
| | - Shiwei Ni
- grid.452435.10000 0004 1798 9070Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011 Liaoning China ,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning China
| | - Jing Liu
- Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, No. 193, Lianhe Road, Shahekou District, Dalian, 116011, Liaoning, China. .,Dalian Innovation Institute of Stem Cell and Precision Medicine, Dalian, Liaoning, China.
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Yu Q, Ouyang M, Detre J, Kang H, Hu D, Hong B, Fang F, Peng Y, Huang H. Infant brain regional cerebral blood flow increases supporting emergence of the default-mode network. eLife 2023; 12:e78397. [PMID: 36693116 PMCID: PMC9873253 DOI: 10.7554/elife.78397] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 01/12/2023] [Indexed: 01/25/2023] Open
Abstract
Human infancy is characterized by most rapid regional cerebral blood flow (rCBF) increases across lifespan and emergence of a fundamental brain system default-mode network (DMN). However, how infant rCBF changes spatiotemporally across the brain and how the rCBF increase supports emergence of functional networks such as DMN remains unknown. Here, by acquiring cutting-edge multi-modal MRI including pseudo-continuous arterial-spin-labeled perfusion MRI and resting-state functional MRI of 48 infants cross-sectionally, we elucidated unprecedented 4D spatiotemporal infant rCBF framework and region-specific physiology-function coupling across infancy. We found that faster rCBF increases in the DMN than visual and sensorimotor networks. We also found strongly coupled increases of rCBF and network strength specifically in the DMN, suggesting faster local blood flow increase to meet extraneuronal metabolic demands in the DMN maturation. These results offer insights into the physiological mechanism of brain functional network emergence and have important implications in altered network maturation in brain disorders.
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Affiliation(s)
- Qinlin Yu
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Minhui Ouyang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - John Detre
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Neurology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Huiying Kang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Di Hu
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Bo Hong
- Department of Biomedical Engineering, Tsinghua UniversityBeijingChina
| | - Fang Fang
- School of Psychological and Cognitive Sciences, Peking UniversityBeijingChina
| | - Yun Peng
- Department of Radiology, Beijing Children’s Hospital, Capital Medical UniversityBeijingChina
| | - Hao Huang
- Department of Radiology, Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Radiology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
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30
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A Voxel-Based Morphometric Study of Gray Matter in Specific Phobia. LIFE (BASEL, SWITZERLAND) 2022; 13:life13010119. [PMID: 36676068 PMCID: PMC9864817 DOI: 10.3390/life13010119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 12/28/2022] [Accepted: 12/29/2022] [Indexed: 01/03/2023]
Abstract
The objective of this study was to analyze the neurostructural abnormalities of brain areas responsible for the acquisition and maintenance of fear in small animal phobia by comparing gray matter volume (GMV) in individuals with phobia and non-fearful controls. Structural magnetic resonance imaging was obtained from 62 adults (79% female) assigned to one of two groups: 31 were diagnosed with small animal phobia and 31 were non-fearful controls. To investigate structural alterations, a whole-brain voxel-based morphometry analysis was conducted to compare the GMV of the brain areas involved in fear between both groups. The results indicated that individuals with a small animal specific phobia showed smaller GMV in cortical regions, such as the orbitofrontal (OFC) and medial frontal cortex, and greater GMV in the putamen than non-fearful controls. These brain areas are responsible for avoidant behavior (putamen) and emotional regulation processes or inhibitory control (prefrontal cortex (PFC)), which might suggest a greater vulnerability of phobic individuals to acquiring non-adaptive conditioned responses and emotional dysregulation. The findings provide preliminary support for the involvement of structural deficits in OFC and medial frontal cortex in phobia, contributing to clarify the neurobiological substrates for phobias.
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31
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Nerland S, Stokkan TS, Jørgensen KN, Wortinger LA, Richard G, Beck D, van der Meer D, Westlye LT, Andreassen OA, Agartz I, Barth C. A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age. Hum Brain Mapp 2022; 43:4620-4639. [PMID: 35708198 PMCID: PMC9491281 DOI: 10.1002/hbm.25978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/28/2022] [Accepted: 05/30/2022] [Indexed: 11/05/2022] Open
Abstract
Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI) studies, both as a covariate and as a variable of interest. Findings of associations between ICV and age have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where longitudinal data was also available. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We found overall high correlations across ICV estimation method, with the lowest observed correlations between FSL and eTIV (r = .87) and between FSL and CAT12 (r = .89). Widespread proportional bias was found, indicating that the agreement between methods varied as a function of head size. Body weight, age, sex, and mean ICV across methods explained the most variance in the differences between ICV estimation methods, indicating possible confounding for some estimation methods. We found both positive and negative cross-sectional associations with age, depending on dataset and ICV estimation method. Longitudinal ICV reductions were found for all ICV estimation methods, with annual percentage change ranging from -0.293% to -0.416%. This convergence of longitudinal results across ICV estimation methods offers strong evidence for age-related ICV reductions in mid- to late adulthood.
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Affiliation(s)
- Stener Nerland
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Therese S Stokkan
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Kjetil N Jørgensen
- NORMENT, University of Oslo, Oslo, Norway.,Department of Psychiatry, Telemark Hospital, Skien, Norway
| | - Laura A Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Geneviève Richard
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dani Beck
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
| | - Dennis van der Meer
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway.,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.,NORMENT, University of Oslo, Oslo, Norway
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32
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Hill SY, Wellman JL, Zezza N, Steinhauer SR, Sharma V, Holmes B. Epigenetic Effects in HPA Axis Genes Associated with Cortical Thickness, ERP Components and SUD Outcome. Behav Sci (Basel) 2022; 12:347. [PMID: 36285916 PMCID: PMC9598712 DOI: 10.3390/bs12100347] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/29/2022] [Accepted: 09/01/2022] [Indexed: 09/09/2023] Open
Abstract
Association between familial loading for alcohol use disorders (AUD) and event-related potentials (ERPs) suggests a genetic basis for these oscillations though much less is known about epigenetic pathways influenced by environmental variation. Early life adversity (ELA) influences negative outcomes much later in life. The stress-activated neuropeptide corticotropin-releasing hormone (CRH) contributes to the deleterious effects of ELA on brain structure and function in animals. Accordingly, we hypothesized that ELA would be related to cortical thickness and electrophysiological characteristics through an epigenetic effect on CRH receptor type-1 (CRHR1) methylation. A total of 217 adolescent and young adult participants from either multiplex alcohol dependence or control families were scanned using magnetic resonance imaging (MRI) at 3T and cortical thickness was determined. Longitudinal follow-up across childhood, adolescence, and young adulthood provided developmental ERP data and measures of adversity. Blood samples for genetic and epigenetic analyses were obtained in childhood. Cortical thickness and visual ERP components were analyzed for their association and tested for familial risk group differences. Visual P300 amplitude at Pz and cortical thickness of the left lateral orbitofrontal region (LOFC), were significantly related to risk group status. LOFC cortical thickness showed a negative correlation with CRHR1 methylation status and with childhood total stress scores from the Life Stressors and Social Resources Inventory (LISRES). Stress scores were also significantly related to P300 amplitude recorded in childhood. The present results suggest that early life adversity reflected in greater total LISRES stress scores in childhood can impact the methylation of the CRHR1 gene with implications for brain development as seen in cortical thickness and electrophysiological signals emanating from particular brain regions.
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Affiliation(s)
- Shirley Y. Hill
- Department of Psychiatry, University of Pittsburgh School of Medicine, 3811 O’Hara St., Pittsburgh, PA 15213, USA
| | - Jeannette L. Wellman
- Department of Psychiatry and Magee Women’s Hospital, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Nicholas Zezza
- Department of Psychiatry and Shadyside Hospital, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | | | - Vinod Sharma
- Department of Psychiatry, University of Pittsburgh School of Medicine, 3811 O’Hara St., Pittsburgh, PA 15213, USA
| | - Brian Holmes
- UPMC Children’s Hospital of Pittsburgh, 4401 Penn Ave., Pittsburgh, PA 15224, USA
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Kashyap R, Bhattacharjee S, Bharath RD, Venkatasubramanian G, Udupa K, Bashir S, Oishi K, Desmond JE, Chen SHA, Guan C. Variation of cerebrospinal fluid in specific regions regulates focality in transcranial direct current stimulation. Front Hum Neurosci 2022; 16:952602. [PMID: 36118967 PMCID: PMC9479459 DOI: 10.3389/fnhum.2022.952602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/11/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundConventionally, transcranial direct current stimulation (tDCS) aims to focalize the current reaching the target region-of-interest (ROI). The focality can be quantified by the dose-target-determination-index (DTDI). Despite having a uniform tDCS setup, some individuals receive focal stimulation (high DTDI) while others show reduced focality (“non-focal”). The volume of cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM) underlying each ROI govern the tDCS current distribution inside the brain, thereby regulating focality.AimTo determine the regional volume parameters that differentiate the focal and non-focal groups.MethodsT1-weighted images of the brain from 300 age-sex matched adults were divided into three equal groups- (a) Young (20 ≤ × < 40 years), (b) Middle (40 ≤ × < 60 years), and (c) Older (60 ≤ × < 80 years). For each group, inter and intra-hemispheric montages with electrodes at (1) F3 and right supraorbital region (F3-RSO), and (2) CP5 and Cz (CP5-Cz) were simulated, targeting the left- Dorsolateral Prefrontal Cortex (DLPFC) and -Inferior Parietal Lobule (IPL), respectively. Both montages were simulated for two current doses (1 and 2 mA). For each individual head simulated for a tDCS configuration (montage and dose), the current density at each region-of-interest (ROI) and their DTDI were calculated. The individuals were categorized into two groups- (1) Focal (DTDI ≥ 0.75), and (2) Non-focal (DTDI < 0.75). The regional volume of CSF, GM, and WM of all the ROIs was determined. For each tDCS configuration and ROI, three 3-way analysis of variance was performed considering- (i) GM, (ii) WM, and (iii) CSF as the dependent variable (DV). The age group, sex, and focality group were the between-subject factors. For a given ROI, if any of the 3 DV’s showed a significant main effect or interaction involving the focality group, then that ROI was classified as a “focal ROI.”ResultsRegional CSF was the principal determinant of focality. For interhemispheric F3-RSO montage, interaction effect (p < 0.05) of age and focality was observed at Left Caudate Nucleus, with the focal group exhibiting higher CSF volume. The CSF volume of focal ROI correlated positively (r ∼ 0.16, p < 0.05) with the current density at the target ROI (DLPFC). For intrahemispheric CP5-Cz montage, a significant (p < 0.05) main effect was observed at the left pre- and post-central gyrus, with the focal group showing lower CSF volume. The CSF volume correlated negatively (r ∼ –0.16, p < 0.05) with current density at left IPL. The results were consistent for both current doses.ConclusionThe CSF channels the flow of tDCS current between electrodes with focal ROIs acting like reservoirs of current. The position of focal ROI in the channel determines the stimulation intensity at the target ROI. For focal stimulation in interhemispheric F3-RSO, the proximity of focal ROI reserves the current density at the target ROI (DLPFC). In contrast, for intrahemispheric montage (CP5-Cz), the far-end location of focal ROI reduces the current density at the target (IPL).
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Affiliation(s)
- Rajan Kashyap
- Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
- *Correspondence: Rajan Kashyap,
| | - Sagarika Bhattacharjee
- Department of Neurophysiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
- Psychology, School of Social Sciences (SSS), Nanyang Technological University, Singapore, Singapore
| | - Rose Dawn Bharath
- Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - Ganesan Venkatasubramanian
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - Kaviraja Udupa
- Department of Neurophysiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Shahid Bashir
- Neuroscience Center, King Fahad Specialist Hospital Dammam, Dammam, Saudi Arabia
| | - Kenichi Oishi
- The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - John E. Desmond
- The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - S. H. Annabel Chen
- Psychology, School of Social Sciences (SSS), Nanyang Technological University, Singapore, Singapore
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
- Lee Kong Chian School of Medicine (LKC Medicine), Nanyang Technological University, Singapore, Singapore
- National Institute of Education, Nanyang Technological University, Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
- Cuntai Guan,
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Atanasova T, Laganaro M. Word Production Changes through Adolescence: A Behavioral and ERP Investigation of Referential and Inferential Naming. Dev Neuropsychol 2022; 47:295-313. [PMID: 35997517 DOI: 10.1080/87565641.2022.2112195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Changes in word production occur across the lifespan, with adolescence representing a knot point between children's and adults' performance and underlying brain processes. Previous studies on referential word production using picture naming tasks have shown a completely adult-like pattern in 17-year-old adolescents and an intermediate pattern between children and adults in adolescents aged 14-16 years old, suggesting a possible involvement of visuo-conceptual processes in the transition from childhood to adulthood. Given the visual nature of the picture naming task, it is unclear whether changes in visuo-conceptual processes are specifically related to the referential word production or if overall changes in conceptual to lexical processes drive maturation. To answer this question, we turned to an inferential word production task, i.e., naming from auditory definitions, involving different conceptual to lexical processes relative to referential naming. Behavior and electroencephalographic Event-Related Potentials (ERP) in a (visual) referential word production task and an (auditory) inferential word production task were recorded and compared in three groups of adolescents (respectively, aged 10 to 13, 14 to 16, and 17 to 18). Only the youngest group displayed longer production latencies and lower accuracy than the two older groups of adolescents who performed similarly on both tasks. Crucially, ERP waveform analysis and topographic pattern analysis revealed significant intergroup differences on both tasks. Changes across ages are not merely linked to the visual-conceptual processes of a picture naming task but are rather related to lexical-semantic processes involved in word production.
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Affiliation(s)
- Tanja Atanasova
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Marina Laganaro
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
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35
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Boness CL, Gatten N, Treece M, Miller MB. A mixed-methods approach to improve the measurement of alcohol-induced blackouts: ABOM-2. Alcohol Clin Exp Res 2022; 46:1497-1514. [PMID: 35702924 PMCID: PMC9427728 DOI: 10.1111/acer.14882] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/16/2022] [Accepted: 06/07/2022] [Indexed: 01/31/2023]
Abstract
BACKGROUND Alcohol-induced blackouts describe memory loss resulting from alcohol consumption. Approximately half of college students report experiencing a blackout in their lifetime. Blackouts are associated with an increased risk for negative consequences, including serious injury. Research has documented two types of blackouts, en bloc (EB) and fragmentary (FB). However, research is limited by the lack of a validated measure that differentiates between these two forms of blackout. This study used a mixed-methods approach to improve the assessment of FB and EB among young adults. Specifically, we sought to improve the existing Alcohol-Induced Blackout Measure (ABOM), which was derived from a relatively small pool of items that did not distinguish FB from EB. METHODS Study 1 used three rounds of cognitive interviewing with U.S. college students (N = 31) to refine existing assessment items. Nineteen refined blackout items were retained for Study 2. Study 2 used face validity, factor analysis, item response theory, and external validation analyses to test the two-factor blackout model among U.S. heavy-drinking college students (N = 474) and to develop and validate a new blackout measure (ABOM-2). RESULTS Iterative factor analyses demonstrated that the items were well represented by correlated EB and FB factors, consistent with our hypothesis. External validation analyses demonstrated convergent and discriminant validity. These analyses also provided preliminary evidence for the two factors having differential predictive validity (e.g., FB correlated with enhancement drinking motives, while EB correlated with coping and conformity motives). CONCLUSIONS The Alcohol-Induced Blackout Measure-2 (ABOM-2) improves the measurement of blackout experiences among college students. Its use could facilitate the examination of EB and FB as differential predictors of alcohol-related outcomes in future studies.
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Affiliation(s)
- Cassandra L. Boness
- Center on Alcohol, Substance use, And Addictions, University of New Mexico,Department of Psychological Science, University of Missouri
| | - Natalie Gatten
- Department of Psychological Science, University of Missouri
| | - McKenna Treece
- Department of Psychological Science, University of Missouri,Department of Counseling and Counseling Psychology, University of Missouri Kansas City
| | - Mary Beth Miller
- Department of Psychological Science, University of Missouri,Department of Psychiatry, University of Missouri
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36
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The heritability of vocal tract structures estimated from structural MRI in a large cohort of Dutch twins. Hum Genet 2022; 141:1905-1923. [PMID: 35831475 DOI: 10.1007/s00439-022-02469-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 06/18/2022] [Indexed: 11/04/2022]
Abstract
While language is expressed in multiple modalities, including sign, writing, or whistles, speech is arguably the most common. The human vocal tract is capable of producing the bewildering diversity of the 7000 or so currently spoken languages, but relatively little is known about its genetic bases, especially in what concerns normal variation. Here, we capitalize on five cohorts totaling 632 Dutch twins with structural magnetic resonance imaging (MRI) data. Two raters placed clearly defined (semi)landmarks on each MRI scan, from which we derived 146 measures capturing the dimensions and shape of various vocal tract structures, but also aspects of the head and face. We used Genetic Covariance Structure Modeling to estimate the additive genetic, common environmental or non-additive genetic, and unique environmental components, while controlling for various confounds and for any systematic differences between the two raters. We found high heritability, h2, for aspects of the skull and face, the mandible, the anteroposterior (horizontal) dimension of the vocal tract, and the position of the hyoid bone. These findings extend the existing literature, and open new perspectives for understanding the complex interplay between genetics, environment, and culture that shape our vocal tracts, and which may help explain cross-linguistic differences in phonetics and phonology.
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Mori S, Onda K, Fujita S, Suzuki T, Ikeda M, Zay Yar Myint K, Hikage J, Abe O, Tomimoto H, Oishi K, Taguchi J. Brain atrophy in middle age using magnetic resonance imaging scans from Japan’s health screening programme. Brain Commun 2022; 4:fcac211. [PMID: 36043138 PMCID: PMC9416065 DOI: 10.1093/braincomms/fcac211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 06/12/2022] [Accepted: 08/20/2022] [Indexed: 12/21/2022] Open
Abstract
Although health screening plays a key role in the management of chronic diseases associated with lifestyle choices, brain health is not generally monitored, remaining a black box prior to the manifestation of clinical symptoms. Japan is unique in this regard, as brain MRI scans have been widely performed for more than two decades as part of Brain Dock, a comprehensive health screening programme. A vast number of stored images (well over a million) of longitudinal scans and extensive health data are available, offering a valuable resource for investigating the prevalence of various types of brain-related health conditions occurring throughout adulthood. In this paper, we report on the findings of our preliminary quantitative analysis of T1-weighted MRIs of the brain obtained from 13 980 subjects from three participating sites during the period 2015–19. We applied automated segmentation analysis and observed age-dependent volume loss of various brain structures. We subsequently investigated the effects of scan protocols and the feasibility of calibration for pooling the data. Last, the degree of brain atrophy was correlated with four known risk factors of dementia; blood glucose level, hypertension, obesity, and alcohol consumption. In this initial analysis, we identified brain ventricular volume as an effective marker of age-dependent brain atrophy, being highly sensitive to ageing and evidencing strong robustness against protocol variability. We established the normal range of ventricular volumes at each age, which is an essential first step for establishing criteria used to interpret data obtained for individual participants. We identified a subgroup of individuals at midlife with ventricles that substantially exceeded the average size. The correlation studies revealed that all four risk factors were associated with greater ventricular volumes at midlife, some of which reached highly significant sizes. This study demonstrates the feasibility of conducting a large-scale quantitative analysis of existing Brain Dock data in Japan. It will importantly guide future efforts to investigate the prevalence of large ventricles at midlife and the potential reduction of this prevalence, and hence of dementia risk, through lifestyle changes.
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Affiliation(s)
- Susumu Mori
- Department of Radiology, Johns Hopkins University, School of Medicine , 330 Traylor Bldg, 217 Rutland Ave, Baltimore, MD 21205 , USA
| | - Kengo Onda
- Tokyo Medical and Dental University , 1 Chome-5-45 Yushima, Bunkyo City, Tokyo 113-0034 , Japan
| | - Shohei Fujita
- Department of Radiology, The University of Tokyo, Graduate School of Medicine , 7-3-1 Hongo, Bunkyo City, Tokyo 113-0033 , Japan
| | - Toshiaki Suzuki
- Resorttrust.Inc, Engyou Bldg.8F , Roppongi 7-15-14, Minato-ku, Tokyo 106-0032 , Japan
| | - Mikimasa Ikeda
- Resorttrust.Inc, Engyou Bldg.8F , Roppongi 7-15-14, Minato-ku, Tokyo 106-0032 , Japan
| | - Khin Zay Yar Myint
- Advanced Medical Care Inc. , Midtown Tower 6F, Akasaka 9-7-1, Minato-ku, Tokyo 107-6206 , Japan
| | - Jun Hikage
- Resorttrust.Inc, Engyou Bldg.8F , Roppongi 7-15-14, Minato-ku, Tokyo 106-0032 , Japan
| | - Osamu Abe
- Department of Radiology, The University of Tokyo, Graduate School of Medicine , 7-3-1 Hongo, Bunkyo City, Tokyo 113-0033 , Japan
| | - Hidekazu Tomimoto
- Department of Neurology, Hidekazu Tomimoto, Mie University 2-174 , Edobashi, Tsu, Mie 514-0001 , Japan
| | - Kenichi Oishi
- Department of Radiology, Johns Hopkins University, School of Medicine , 330 Traylor Bldg, 217 Rutland Ave, Baltimore, MD 21205 , USA
| | - Junichi Taguchi
- Tokyo Midtown Clinic , 9-7-1-6F Akasaka, Minato, Tokyo 107-6206 , Japan
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Effects of aging on functional connectivity in a neurodegenerative risk cohort: resting state versus task measurement using near-infrared spectroscopy. Sci Rep 2022; 12:11262. [PMID: 35788629 PMCID: PMC9253312 DOI: 10.1038/s41598-022-13326-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 05/16/2022] [Indexed: 11/23/2022] Open
Abstract
Changes in functional brain organization are considered to be particularly sensitive to age-related effects and may precede structural cognitive decline. Recent research focuses on aging processes determined by resting state (RS) functional connectivity (FC), but little is known about differences in FC during RS and cognitive task conditions in elderly participants. The purpose of this study is to compare FC within and between the cognitive control (CCN) and dorsal attention network (DAN) at RS and during a cognitive task using functional near-infrared spectroscopy (fNIRS). In a matched, neurodegenerative high-risk cohort comprising early (n = 98; 50–65 y) and late (n = 98; 65–85 y) elder subjects, FC was measured at RS and during performance of the Trail Making Test (TMT) via fNIRS. Both, under RS and task conditions our results revealed a main effect for age, characterized by reduced FC for late elder subjects within the left inferior frontal gyrus. During performance of the TMT, negative correlations of age and FC were confirmed in various regions of the CCN and DAN. For the whole sample, FC of within-region connections was elevated, while FC between regions was decreased at RS. The results confirm a reorganization of functional brain connectivity with increasing age and cognitive demands.
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Goto M, Murata S, Hori M, Nemoto K, Kamatgata K, Aoki S, Abe O, Sakamoto H, Sakano Y, Kyogoku S, Daida H. Using modulated and smoothed data improves detectability of volume difference in group comparison, but reduces accuracy with atlas-based volumetry using Statistical Parametric Mapping 12 software. Acta Radiol 2022; 63:814-821. [PMID: 34279134 DOI: 10.1177/02841851211032442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Atlas-based volumetry using three-dimensional T1-weighted (3D-T1W) magnetic resonance imaging (MRI) has been used previously to evaluate the volumes of intracranial tissues. PURPOSE To evaluate the detectability of volume difference and accuracy for volumetry using smoothed data with an atlas-based method. MATERIAL AND METHODS Twenty healthy individuals and 24 patients with idiopathic normal-pressure hydrocephalus (iNPH) underwent 3-T MRI, and sagittal 3D-T1W images were obtained in all participants. Signal values (as tissue probability) of voxels in five segmented data types (gray matter, white matter, cerebrospinal fluid [CSF], skull, soft tissue) derived from the 3D-T1W images with SPM 12 software were assigned simulated 3D-T1W signal intensities to each tissue image. The assigned data were termed "reference data." We created a reference 3D-T1W image that included the reference data of all five tissue types. Standard volumes were measured for the reference CSF data with region of interest of lateral ventricle in native space, and measured volumes were obtained for non-smoothed and smoothed-modulated data. Detectability was evaluated between measured volumes in the healthy control and iNPH groups. Accuracy was evaluated as the difference between the mean measured and standard volumes. RESULTS In group comparison of measured volumes between the healthy control and iNPH groups, the lowest P value was for smoothed-modulated CSF data. In both groups, the largest difference from the standard volume was found for the mean of the measured volumes for smoothed-modulated CSF data. CONCLUSION Our study shows that using smoothed data can improve detectability in group comparison. However, using smoothed data reduces the accuracy of volumetry.
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Affiliation(s)
- Masami Goto
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, Juntendo University, Tokyo, Japan
| | - Syo Murata
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Kiyotaka Nemoto
- Department of Neuropsychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Koji Kamatgata
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Osamu Abe
- Department of Radiology, The University of Tokyo Hospital, Tokyo, Japan
| | - Hajime Sakamoto
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, Juntendo University, Tokyo, Japan
| | - Yasuaki Sakano
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, Juntendo University, Tokyo, Japan
| | - Shinsuke Kyogoku
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, Juntendo University, Tokyo, Japan
| | - Hiroyuki Daida
- Department of Radiological Technology, Faculty of Health Science, Juntendo University, Juntendo University, Tokyo, Japan
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Atrooz F, Alrousan G, Hassan A, Salim S. Early-Life Sleep Deprivation Enhanced Alcohol Consumption in Adolescent Rats. Front Neurosci 2022; 16:856120. [PMID: 35546871 PMCID: PMC9081815 DOI: 10.3389/fnins.2022.856120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 02/24/2022] [Indexed: 12/05/2022] Open
Abstract
Evidence in the literature suggests that sleep deprivation during early-life developmental stages, by impacting important processes such as the reward circuit maturation, may increase the vulnerability for alcohol and substance use. The mechanisms involved are not fully understood. In this study, utilizing our previously established model, we examined the impact of early-life sleep deprivation on alcohol consumption in adolescent rats. Male Sprague Dawley rats served as either the control (CON) or sleep-deprived (SD) group. Sleep deprivation was induced using a Pinnacle automated sleep deprivation apparatus. The SD group of rats was sleep deprived for 6–8 h/day for 14 days from postnatal day (PND)19 to PND32. At PND33, anxiety- and depression-like behaviors were assessed in rats using elevated plus maze and sucrose splash test, respectively. At PND39, alcohol consumption was assessed in rats for five consecutive days using the two-bottle choice paradigm, water versus 5% ethanol. SD rats exhibited significant anxiety- and depression-like behaviors as compared to CON rats. Interestingly, SD rats consumed a larger volume of alcohol when compared to CON rats, which was significantly higher at day 5 (mean of alcohol consumption (ml) ± SD; CON = 6.67 ± 3.42; SD = 19.00 ± 6.05, p = 0.0126). SD rats also showed high preference for alcohol over water, which was significantly higher at day 5 (mean of alcohol preference (%) ± SD; CON = 26.85 ± 14.97; SD = 57.69 ± 5.61, p = 0.014). Our data suggest that early-life sleep deprivation enhanced alcohol consumption in adolescent rats.
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Affiliation(s)
- Fatin Atrooz
- Department of Pharmacological and Pharmaceutical Sciences, University of Houston, Houston, TX, United States
| | - Ghalya Alrousan
- Department of Pharmacological and Pharmaceutical Sciences, University of Houston, Houston, TX, United States
| | - Arham Hassan
- Department of Pharmacological and Pharmaceutical Sciences, University of Houston, Houston, TX, United States
| | - Samina Salim
- Department of Pharmacological and Pharmaceutical Sciences, University of Houston, Houston, TX, United States
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WOODS STACEY, O’MAHONEY CARAGH, MAYNARD JAMES, DOTAN RAFFY, TENENBAUM GERSHON, FILHO EDSON, FALK BAREKET. Increase in Volitional Muscle Activation from Childhood to Adulthood: A Systematic Review and Meta-analysis. Med Sci Sports Exerc 2022; 54:789-799. [PMID: 34967802 PMCID: PMC9012528 DOI: 10.1249/mss.0000000000002853] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
INTRODUCTION Children's maximal muscle strength is consistently lower than adults', even when normalized to body size. Lower volitional muscle activation (VA) in children is often considered one of the main reasons for age-related differences in muscular performance. However, some recent studies have reported similar VA in children and adults, bringing into question whether there is indeed an age-related increase in VA. The purpose of this review was to determine the effect of age on VA during maximal isometric contractions. METHODS Literature examining VA differences, using twitch interpolation in children (7-14 yr) and adults (16-28 yr), was systematically reviewed. Of the 1915 studies initially identified, 19 data sets were eligible for inclusion in the qualitative analysis and 14 in the quantitative meta-analysis (comprising 207 children and 193 adults). RESULTS Significantly lower VA in children was reported in 9/19 (47%) studies. A random-effects meta-analysis found a strong effect of age on VA, supporting lower VA in children compared with adults (Hedges' g = 1.55; confidence interval: 0.9-2.13). Moderator analysis included muscle group, sex, children's age, stimulation number (singlet, multiple), type (electric, magnetic), and location (muscle, nerve), of which only muscle group was significant (P < 0.001). A significant Egger's regression test and asymmetrical funnel plot suggest that publication bias may be present. CONCLUSIONS Overall, these findings suggest that compared with adults, children activate their motor-unit pool less compared with adults. Moreover, that the degree of VA increase with age may be influenced by the muscle examined (upper vs lower extremity). However, more research is needed to elucidate the influence of this possible factor, as the current review contains limited data from upper body muscles. The developmental mechanism responsible for children's lower VA requires further research.
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Affiliation(s)
- STACEY WOODS
- Department of Kinesiology, Brock University, St. Catharines, ON, CANADA
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, CANADA
| | - CARAGH O’MAHONEY
- Department of Kinesiology, Brock University, St. Catharines, ON, CANADA
| | - JAMES MAYNARD
- Department of Kinesiology, Brock University, St. Catharines, ON, CANADA
| | - RAFFY DOTAN
- Department of Kinesiology, Brock University, St. Catharines, ON, CANADA
| | - GERSHON TENENBAUM
- B. Ivcher School of Psychology, Reichman University, Herzliya, ISRAEL
| | - EDSON FILHO
- Wheelock College of Education and Human Development, Boston University, Boston, MA
| | - BAREKET FALK
- Department of Kinesiology, Brock University, St. Catharines, ON, CANADA
- Centre for Bone and Muscle Health, Brock University, St. Catharines, ON, CANADA
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van der Eijk Y, Chen JIP. Case for raising the minimum legal age of tobacco sale to 25. Tob Control 2022; 31:487-492. [PMID: 33414266 DOI: 10.1136/tobaccocontrol-2020-055964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 10/15/2020] [Accepted: 11/17/2020] [Indexed: 11/03/2022]
Abstract
Restricting youth access to tobacco is an essential component of a comprehensive tobacco control policy. While there has been a growing movement to raise the minimum legal age (MLA) of purchasing tobacco from 18 to 21, more restrictive measures, such as raising the MLA to 25 (MLA25), have been criticised as being overly restrictive on adult's free choice. We argue that, even within a policy approach that prioritises freedom of choice, there is a strong case for MLA25 in view of neurobiological evidence which shows that, before age 25, people are neurobiologically vulnerable to developing an addiction. We discuss further considerations for an MLA25 policy, in particular its potential impact on the free choice of young adults to start or quit smoking, potential public health impact and potential effectiveness considering that most underage youth source cigarettes from older peers.
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Affiliation(s)
- Yvette van der Eijk
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Jacinta I-Pei Chen
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
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Hill AT, Clark GM, Bigelow FJ, Lum JAG, Enticott PG. Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood. Dev Cogn Neurosci 2022; 54:101076. [PMID: 35085871 PMCID: PMC8800045 DOI: 10.1016/j.dcn.2022.101076] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 01/10/2022] [Accepted: 01/21/2022] [Indexed: 11/27/2022] Open
Abstract
The neurodevelopmental period spanning early-to-middle childhood represents a time of significant growth and reorganisation throughout the cortex. Such changes are critical for the emergence and maturation of a range of social and cognitive processes. Here, we utilised both eyes open and eyes closed resting-state electroencephalography (EEG) to examine maturational changes in both oscillatory (i.e., periodic) and non-oscillatory (aperiodic, '1/f-like') activity in a large cohort of participants ranging from 4-to-12 years of age (N = 139, average age=9.41 years, SD=1.95). The EEG signal was parameterised into aperiodic and periodic components, and linear regression models were used to evaluate if chronological age could predict aperiodic exponent and offset, as well as well as peak frequency and power within the alpha and beta ranges. Exponent and offset were found to both decrease with age, while aperiodic-adjusted alpha peak frequency increased with age; however, there was no association between age and peak frequency for the beta band. Age was also unrelated to aperiodic-adjusted spectral power within either the alpha or beta bands, despite both frequency ranges being correlated with the aperiodic signal. Overall, these results highlight the capacity for both periodic and aperiodic features of the EEG to elucidate age-related functional changes within the developing brain.
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Affiliation(s)
- Aron T Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Australia.
| | - Gillian M Clark
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Australia
| | - Felicity J Bigelow
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Australia
| | - Jarrad A G Lum
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Australia
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Australia
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Ligges C, Ligges M, Gaser C. Cross-Sectional Investigation of Brain Volume in Dyslexia. Front Neurol 2022; 13:847919. [PMID: 35350399 PMCID: PMC8957969 DOI: 10.3389/fneur.2022.847919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 02/04/2022] [Indexed: 01/18/2023] Open
Abstract
The goal of the study was to determine whether dyslexia is associated with differences in local brain volume, and whether these local brain volume differences show cross-sectional age-effects. We investigated the local volume of gray and white brain matter with voxel-based morphometry (VBM) as well as reading performance in three age groups of dyslexic and neurotypical normal reading subjects (children, teenagers and adults). Performance data demonstrate a steady improvement of reading skills in both neurotypical as well as dyslexic readers. However, the pattern of gray matter volumes tell a different story: the children are the only group with significant differences between neurotypical and dyslexic readers in local gray matter brain volume. These differences are localized in brain areas associated with the reading network (angular, middle temporal and inferior temporal gyrus as well as the cerebellum). Yet the comparison of neurotypical and normal readers over the age groups shows that the steady increase in performance in neurotypical readers is accompanied by a steady decrease of gray matter volume, whereas the brain volumes of dyslexic readers do not show this linear correlation between brain volume and performance. This is further evidence that dyslexia is a disorder with a neuroanatomical basis in the form of a lower volume of gray matter in parts of the reading network in early dyslexic readers. The present data point out that network shaping processes in gray matter volume in the reading network does take place over age in dyslexia. Yet this neural foundation does not seem to be sufficient to allow normal reading performances even in adults with dyslexia. Thus dyslexia is a disorder with lifelong consequences, which is why consistent support for affected individuals in their educational and professional careers is of great importance. Longitudinal studies are needed to verify whether this holds as a valid pattern or whether there is evidence of greater interindividual variance in the neuroanatomy of dyslexia.
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Affiliation(s)
- Carolin Ligges
- Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Marc Ligges
- Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.,Department of Neurology, Jena University Hospital, Jena, Germany
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Lodha J, Brocato E, Wolstenholme JT. Areas of Convergence and Divergence in Adolescent Social Isolation and Binge Drinking: A Review. Front Behav Neurosci 2022; 16:859239. [PMID: 35431830 PMCID: PMC9009335 DOI: 10.3389/fnbeh.2022.859239] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 03/07/2022] [Indexed: 11/13/2022] Open
Abstract
Adolescence is a critical developmental period characterized by enhanced social interactions, ongoing development of the frontal cortex and maturation of synaptic connections throughout the brain. Adolescents spend more time interacting with peers than any other age group and display heightened reward sensitivity, impulsivity and diminished inhibitory self-control, which contribute to increased risky behaviors, including the initiation and progression of alcohol use. Compared to adults, adolescents are less susceptible to the negative effects of ethanol, but are more susceptible to the negative effects of stress, particularly social stress. Juvenile exposure to social isolation or binge ethanol disrupts synaptic connections, dendritic spine morphology, and myelin remodeling in the frontal cortex. These structural effects may underlie the behavioral and cognitive deficits seen later in life, including social and memory deficits, increased anxiety-like behavior and risk for alcohol use disorders (AUD). Although the alcohol and social stress fields are actively investigating the mechanisms through which these effects occur, significant gaps in our understanding exist, particularly in the intersection of the two fields. This review will highlight the areas of convergence and divergence in the fields of adolescent social stress and ethanol exposure. We will focus on how ethanol exposure or social isolation stress can impact the development of the frontal cortex and lead to lasting behavioral changes in adulthood. We call attention to the need for more mechanistic studies and the inclusion of the evaluation of sex differences in these molecular, structural, and behavioral responses.
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Affiliation(s)
- Jyoti Lodha
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, United States
| | - Emily Brocato
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, United States
| | - Jennifer T. Wolstenholme
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, United States
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, VA, United States
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Huang J, Ke P, Chen X, Li S, Zhou J, Xiong D, Huang Y, Li H, Ning Y, Duan X, Li X, Zhang W, Wu F, Wu K. Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients. Front Aging Neurosci 2022; 14:823502. [PMID: 35309897 PMCID: PMC8929292 DOI: 10.3389/fnagi.2022.823502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 01/18/2022] [Indexed: 11/13/2022] Open
Abstract
Accelerated brain aging had been widely reported in patients with schizophrenia (SZ). However, brain aging trajectories in SZ patients have not been well-documented using three-modal magnetic resonance imaging (MRI) data. In this study, 138 schizophrenia patients and 205 normal controls aged 20–60 were included and multimodal MRI data were acquired for each individual, including structural MRI, resting state-functional MRI and diffusion tensor imaging. The brain age of each participant was estimated by features extracted from multimodal MRI data using linear multiple regression. The correlation between the brain age gap and chronological age in SZ patients was best fitted by a positive quadratic curve with a peak chronological age of 47.33 years. We used the peak to divide the subjects into a youth group and a middle age group. In the normal controls, brain age matched chronological age well for both the youth and middle age groups, but this was not the case for schizophrenia patients. More importantly, schizophrenia patients exhibited increased brain age in the youth group but not in the middle age group. In this study, we aimed to investigate brain aging trajectories in SZ patients using multimodal MRI data and revealed an aberrant brain age trajectory in young schizophrenia patients, providing new insights into the pathophysiological mechanisms of schizophrenia.
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Affiliation(s)
- Jiayuan Huang
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China
| | - Pengfei Ke
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
| | - Xiaoyi Chen
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China
| | - Shijia Li
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
| | - Jing Zhou
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
| | - Dongsheng Xiong
- Department of Biomedical Engineering, School of Material Science and Engineering, South China University of Technology, Guangzhou, China
| | - Yuanyuan Huang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Hehua Li
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Yuping Ning
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Xujun Duan
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaobo Li
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Wensheng Zhang
- Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Fengchun Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, China
- *Correspondence: Fengchun Wu,
| | - Kai Wu
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China
- National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China
- Guangdong Province Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou, China
- Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
- Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China
- Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Kai Wu,
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Walhovd KB, Fjell AM, Wang Y, Amlien IK, Mowinckel AM, Lindenberger U, Düzel S, Bartrés-Faz D, Ebmeier KP, Drevon CA, Baaré WFC, Ghisletta P, Johansen LB, Kievit RA, Henson RN, Madsen KS, Nyberg L, R Harris J, Solé-Padullés C, Pudas S, Sørensen Ø, Westerhausen R, Zsoldos E, Nawijn L, Lyngstad TH, Suri S, Penninx B, Rogeberg OJ, Brandmaier AM. Education and Income Show Heterogeneous Relationships to Lifespan Brain and Cognitive Differences Across European and US Cohorts. Cereb Cortex 2022; 32:839-854. [PMID: 34467389 PMCID: PMC8841563 DOI: 10.1093/cercor/bhab248] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 06/25/2021] [Accepted: 06/28/2021] [Indexed: 12/19/2022] Open
Abstract
Higher socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. We ask whether relationships between SES, brain volumes and cognitive ability differ across cohorts, by age and national origin. European and US cohorts covering the lifespan were studied (4-97 years, N = 500 000; 54 000 w/brain imaging). There was substantial heterogeneity across cohorts for all associations. Education was positively related to intracranial (ICV) and total gray matter (GM) volume. Income was related to ICV, but not GM. We did not observe reliable differences in associations as a function of age. SES was more strongly related to brain and cognition in US than European cohorts. Sample representativity varies, and this study cannot identify mechanisms underlying differences in associations across cohorts. Differences in neuroanatomical volumes partially explained SES-cognition relationships. SES was more strongly related to ICV than to GM, implying that SES-cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. The relatively stronger SES-ICV associations rather are compatible with SES-brain volume relationships being established early in life, as ICV stabilizes in childhood. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo 0424, Norway
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo 0424, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin D-14195, Germany
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Barcelona 08036, Spain
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Christian A Drevon
- Vitas AS, Oslo 0349, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo 0317, Norway
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- UniDistance Suisse, Brig, Brig 3900, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva 1212, Switzerland
| | - Louise Baruël Johansen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Glostrup 2600, Denmark
| | - Rogier A Kievit
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen 6500 GL, The Netherlands
| | - Richard N Henson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, Copenhagen 1799, Denmark
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå 901 87, Sweden
- Department of Integrative Medical Biology, Umeå University, Umeå 901 87, Sweden
- Department of Radiation Sciences, Radiology, Umeå University, 901 87 Umeå, Sweden
| | - Jennifer R Harris
- Division for Health Data and Digitalisation, The Norwegian Institute of Public Health, Oslo 0213, Norway
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Barcelona 08036, Spain
| | - Sara Pudas
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå 901 87, Sweden
- Department of Radiation Sciences, Radiology, Umeå University, 901 87 Umeå, Sweden
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - René Westerhausen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam 1081 HJ, The Netherlands
| | - Torkild Hovde Lyngstad
- Department of Sociology and Human Geography, Faculty of Social Sciences, University of Oslo, Oslo 0317, Norway
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Brenda Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam 1081 HJ, The Netherlands
| | | | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin D-14195, Germany
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Stuart N, Whitehouse A, Palermo R, Bothe E, Badcock N. Eye Gaze in Autism Spectrum Disorder: A Review of Neural Evidence for the Eye Avoidance Hypothesis. J Autism Dev Disord 2022; 53:1884-1905. [PMID: 35119604 PMCID: PMC10123036 DOI: 10.1007/s10803-022-05443-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2022] [Indexed: 12/27/2022]
Abstract
Reduced eye contact early in life may play a role in the developmental pathways that culminate in a diagnosis of autism spectrum disorder. However, there are contradictory theories regarding the neural mechanisms involved. According to the amygdala theory of autism, reduced eye contact results from a hypoactive amygdala that fails to flag eyes as salient. However, the eye avoidance hypothesis proposes the opposite-that amygdala hyperactivity causes eye avoidance. This review evaluated studies that measured the relationship between eye gaze and activity in the 'social brain' when viewing facial stimuli. Of the reviewed studies, eight of eleven supported the eye avoidance hypothesis. These results suggest eye avoidance may be used to reduce amygdala-related hyperarousal among people on the autism spectrum.
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Affiliation(s)
- Nicole Stuart
- University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia.
| | - Andrew Whitehouse
- Telethon Kids Institute, Perth Children's Hospital, 15 Hospital Avenue, Nedlands, WA, 6009, Australia
| | - Romina Palermo
- University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
| | - Ellen Bothe
- University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
| | - Nicholas Badcock
- University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia
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Tuckute G, Paunov A, Kean H, Small H, Mineroff Z, Blank I, Fedorenko E. Frontal language areas do not emerge in the absence of temporal language areas: A case study of an individual born without a left temporal lobe. Neuropsychologia 2022; 169:108184. [DOI: 10.1016/j.neuropsychologia.2022.108184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 12/07/2021] [Accepted: 02/15/2022] [Indexed: 10/19/2022]
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Statsenko Y, Habuza T, Smetanina D, Simiyu GL, Uzianbaeva L, Neidl-Van Gorkom K, Zaki N, Charykova I, Al Koteesh J, Almansoori TM, Belghali M, Ljubisavljevic M. Brain Morphometry and Cognitive Performance in Normal Brain Aging: Age- and Sex-Related Structural and Functional Changes. Front Aging Neurosci 2022; 13:713680. [PMID: 35153713 PMCID: PMC8826453 DOI: 10.3389/fnagi.2021.713680] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 09/27/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND The human brain structure undergoes considerable changes throughout life. Cognitive function can be affected either negatively or positively. It is challenging to segregate normal brain aging from the accelerated one. OBJECTIVE To work out a descriptive model of brain structural and functional changes in normal aging. MATERIALS AND METHODS By using voxel-based morphometry and lesion segmentation along with linear statistics and machine learning (ML), we analyzed the structural changes in the major brain compartments and modeled the dynamics of neurofunctional performance throughout life. We studied sex differences in lifelong dynamics of brain volumetric data with Mann-Whitney U-test. We tested the hypothesis that performance in some cognitive domains might decline as a linear function of age while other domains might have a non-linear dependence on it. We compared the volumetric changes in the major brain compartments with the dynamics of psychophysiological performance in 4 age groups. Then, we tested linear models of structural and functional decline for significant differences between the slopes in age groups with the T-test. RESULTS White matter hyperintensities (WMH) are not the major structural determinant of the brain normal aging. They should be viewed as signs of a disease. There is a sex difference in the speed and/or in the onset of the gray matter atrophy. It either starts earlier or goes faster in males. Marked sex difference in the proportion of total cerebrospinal fluid (CSF) and intraventricular CSF (iCSF) justifies that elderly men are more prone to age-related brain atrophy than women of the same age. CONCLUSION The article gives an overview and description of the conceptual structural changes in the brain compartments. The obtained data justify distinct patterns of age-related changes in the cognitive functions. Cross-life slowing of decision-making may follow the linear tendency of enlargement of the interhemispheric fissure because the center of task switching and inhibitory control is allocated within the medial wall of the frontal cortex, and its atrophy accounts for the expansion of the fissure. Free online tool at https://med-predict.com illustrates the tests and study results.
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Affiliation(s)
- Yauhen Statsenko
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
- Big Data Analytics Center, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Tetiana Habuza
- Big Data Analytics Center, United Arab Emirates University, Al Ain, United Arab Emirates
- College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Darya Smetanina
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Gillian Lylian Simiyu
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Liaisan Uzianbaeva
- Department of Biomedical Engineering, Wayne State University, Detroit, MI, United States
- Department of Obstetrics and Gynecology, Bronxcare Hospital System, Bronx, NY, United States
| | - Klaus Neidl-Van Gorkom
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Nazar Zaki
- Big Data Analytics Center, United Arab Emirates University, Al Ain, United Arab Emirates
- College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Inna Charykova
- Laboratory of Psychology, Republican Scientific-Practical Center of Sports, Minsk, Belarus
| | - Jamal Al Koteesh
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
- Department of Radiology, Tawam Hospital, Al Ain, United Arab Emirates
| | - Taleb M. Almansoori
- Department of Radiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Maroua Belghali
- Department of Health and Physical Education, College of Education, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Milos Ljubisavljevic
- Department of Physiology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
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