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Zhou C, Qiu C, Pan C, Li Y, Tang Y, Chen Z, Liu Y, Guo S, Lu J, Yan B, Hao X. Brain changes in sleep-related hypermotor epilepsy observed from wakefulness and N2 sleep: A matched case-control study. Clin Neurophysiol 2025; 171:31-37. [PMID: 39862840 DOI: 10.1016/j.clinph.2024.12.020] [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: 09/26/2024] [Revised: 11/19/2024] [Accepted: 12/18/2024] [Indexed: 01/27/2025]
Abstract
OBJECTIVE Sleep-related hypermotor epilepsy (SHE) is a relatively uncommon epilepsy syndrome, characterized by seizures closely related to the sleep cycle. This study aims to explore interictal electroencephalographic (EEG) characteristics in SHE. METHODS We compared EEG data from 20 patients with SHE, 20 patients with focal epilepsy (FE), and 14 healthy controls, carefully matched for age, sex, education level, epilepsy duration, and drug-resistant epilepsy. RESULTS Our findings revealed distinct patterns of power spectral density in SHE patients during wakefulness and N2 sleep compared to other groups, suggesting potential diagnostic value. During wakefulness, SHE patients showed enhanced frontal lobe power across all frequency bands, but decreased frontal lobe power in low-frequency bands during N2 sleep. Additionally, a positive correlation was found between frontal γ band power and epilepsy duration in SHE patients during N2 sleep but not during wakefulness. CONCLUSIONS These findings suggest that interictal EEG abnormalities during wakefulness and N2 sleep might be used as potential biomarkers for the diagnosis of SHE. SIGNIFICANCE This study is the first to simultaneously characterize EEG during sleep and wakefulness in SHE patients during interictal periods, with potential utility for diagnosis.
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Affiliation(s)
- Changqiong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China; Department of Neurology, Liangshan Hospital of Integrated Traditional Chinese and Western Medicine, Liangshan 615000, Sichuan, China
| | - Chenxi Qiu
- Key Lab for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China
| | - Chunge Pan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yan Li
- Key Lab for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China
| | - Yingying Tang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Ziyi Chen
- Key Lab for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China
| | - Ying Liu
- Key Lab for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China
| | - Sijia Guo
- Key Lab for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China
| | - Jing Lu
- Key Lab for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China
| | - Bo Yan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China; Department of Neurology, Chengdu Shangjin Nanfu Hospital, Chengdu 611730, Sichuan, China.
| | - Xiaoting Hao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China.
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Dimitriadis SI, Castells-Sánchez A, Roig-Coll F, Dacosta-Aguayo R, Lamonja-Vicente N, Torán-Monserrat P, García-Molina A, Monte-Rubio G, Stillman C, Perera-Lluna A, Mataró M. Intrinsic functional brain connectivity changes following aerobic exercise, computerized cognitive training, and their combination in physically inactive healthy late-middle-aged adults: the Projecte Moviment. GeroScience 2024; 46:573-596. [PMID: 37872293 PMCID: PMC10828336 DOI: 10.1007/s11357-023-00946-8] [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: 06/13/2023] [Accepted: 09/13/2023] [Indexed: 10/25/2023] Open
Abstract
Lifestyle interventions have positive neuroprotective effects in aging. However, there are still open questions about how changes in resting-state functional connectivity (rsFC) contribute to cognitive improvements. The Projecte Moviment is a 12-week randomized controlled trial of a multimodal data acquisition protocol that investigated the effects of aerobic exercise (AE), computerized cognitive training (CCT), and their combination (COMB). An initial list of 109 participants was recruited from which a total of 82 participants (62% female; age = 58.38 ± 5.47) finished the intervention with a level of adherence > 80%. Only in the COMB group, we revealed an extended network of 33 connections that involved an increased and decreased rsFC within and between the aDMN/pDMN and a reduced rsFC between the bilateral supplementary motor areas and the right thalamus. No global and especially local rsFC changes due to any intervention mediated the cognitive benefits detected in the AE and COMB groups. Projecte Moviment provides evidence of the clinical relevance of lifestyle interventions and the potential benefits when combining them.
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Affiliation(s)
- Stavros I Dimitriadis
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain.
- Institut de Neurociències, University of Barcelona, Barcelona, Spain.
| | - Alba Castells-Sánchez
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Barcelona, Spain
| | - Francesca Roig-Coll
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Barcelona, Spain
| | - Rosalía Dacosta-Aguayo
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Unitat de Suport a La Recerca Metropolitana Nord, Fundació Institut Universitari Per a La Recerca a L'Atenció Primària de Salut Jordi Gol I Gurina, Mataró, Spain
- Institut d'Investigació en Ciències de La Salut Germans Trias I Pujol (IGTP), Badalona, Spain
| | - Noemí Lamonja-Vicente
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Barcelona, Spain
- Unitat de Suport a La Recerca Metropolitana Nord, Fundació Institut Universitari Per a La Recerca a L'Atenció Primària de Salut Jordi Gol I Gurina, Mataró, Spain
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Pere Torán-Monserrat
- Unitat de Suport a La Recerca Metropolitana Nord, Fundació Institut Universitari Per a La Recerca a L'Atenció Primària de Salut Jordi Gol I Gurina, Mataró, Spain
- Department of Medicine, Universitat de Girona, Girona, Spain
| | - Alberto García-Molina
- Institut d'Investigació en Ciències de La Salut Germans Trias I Pujol (IGTP), Badalona, Spain
- Institut Guttmann, Institut Universitari de Neurorehabilitació, Universitat Autònoma de Barcelona, Badalona, Spain
| | - Gemma Monte-Rubio
- Centre for Comparative Medicine and Bioimage (CMCiB), Germans Trias I Pujol Research Institute (IGTP), Badalona, Spain
| | - Chelsea Stillman
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alexandre Perera-Lluna
- B2SLab, Departament d'Enginyeria de Sistemes, CIBER-BBN, Automàtica I Informàtica Industrial, Universitat Politècnica de Catalunya, 08028, Barcelona, Spain
- Department of Biomedical Engineering, Institut de Recerca Pediàtrica Hospital Sant Joan de Déu, 08950, Esplugues de Llobregat, Barcelona, Spain
| | - Maria Mataró
- Department of Clinical Psychology and Psychobiology, University of Barcelona, Passeig Vall d'Hebron 171, 08035, Barcelona, Spain.
- Institut de Neurociències, University of Barcelona, Barcelona, Spain.
- Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain.
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3
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Zhou Y, Xue T, Cheng Y, Wang J, Dong F, Jia S, Zhang F, Wang X, Lv X, Wang H, Yuan K, Yu D. The changes of intrinsic connectivity contrast in young smokers. Addict Biol 2023; 28:e13347. [PMID: 38017637 DOI: 10.1111/adb.13347] [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: 04/02/2023] [Revised: 07/07/2023] [Accepted: 09/26/2023] [Indexed: 11/30/2023]
Abstract
Previous studies demonstrated that reward circuit plays an important role in smoking. The differences of functional and structural connectivity were found among several brain regions such as thalamus and frontal lobe. However, few studies focused on functional connectivity (FC) in whole-brain voxel level of young smokers. In this study, intrinsic connectivity contrast (ICC) was used to perform voxel-based whole-brain analyses in 55 young smokers and 55 matched non-smokers to identify brain regions with significant group differences. ICC results showed that the connectivity of young smokers in medial frontal cortex (MedFC), supramarginal gyrus anterior division left (L_aSMG), central opercular cortex left (L_CO) and middle frontal gyrus left (L_MidFG) showed a significantly lower trend compared with the non-smokers. The seed-based FC analysis about MedFC indicated that young smokers showed reduced connectivity between the MedFC and left hippocampus, left amygdala compared to non-smokers. Correlation analysis showed that the ICC of MedFC in young smokers was significantly negatively correlated with Fagerstrom test for nicotine dependence (FTND) and Questionnaire on Smoking Urges (QSU). The FC between the MedFC and left hippocampus, left amygdala was significantly negatively correlated with Pack_years. The mediation analysis indicated that ICC of MedFC completely mediated FTND and QSU of young smokers. The results suggest that nicotine accumulation may affect the communication of the frontal lobe with the whole brain to some extent, leading to changes in smoking cravings. The above research also provides in-depth insights into the mechanism of adolescent smoking addiction and related intervention treatment.
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Affiliation(s)
- Yang Zhou
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Yongxin Cheng
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Juan Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Shaodi Jia
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Fan Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Xiaoqing Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
| | - Xiaoqi Lv
- College of Information Engineering, Inner Mongolia University of Technology, Hohhot, Inner Mongolia, China
| | - Hongde Wang
- Xilinguole Meng Mongolian General Hospital, Xilinhaote, Inner Mongolia, China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, China
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Abujamea AH, Almosa M, Uzair M, Alabdullatif N, Bashir S. Reduced Cortical Complexity in Children with Developmental Delay in Saudi Arabia. Cureus 2023; 15:e48291. [PMID: 38058330 PMCID: PMC10696479 DOI: 10.7759/cureus.48291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2023] [Indexed: 12/08/2023] Open
Abstract
INTRODUCTION Developmental delay (DD) is a neurodevelopmental disorder characterized by delays in multiple domains. The investigation of brain structure in DD has been enhanced by advanced neuroimaging techniques that can identify regional surface deformities. Neuroimaging studies have identified structural brain abnormalities in individuals with DD, but research specific to the Saudi Arabian population is limited. In this study, we examine the neuroanatomical abnormalities in the cortical and subcortical regions of Saudi Arabian children with DD. METHOD A T1-weighted, 1-mm-thick MRI was used to acquire structural brain images of 29 children with DD and age-matched healthy controls. RESULTS Analysis of the MRI data revealed significant differences in several cortical and subcortical structures of gray matter (GM) and white matter (WM) in several brain regions of the DD group. Specifically, significant deformities were observed in the caudate nucleus, globus pallidus, frontal gyrus, pars opercularis, pars orbitalis, cingulate gyrus, and subcallosal gyrus. These findings suggest disrupted neurodevelopment in these regions, which may contribute to the cognitive, motor, and behavioral impairments commonly observed in individuals with DD. CONCLUSIONS The present study provides valuable insights into the neuroanatomical differences in Saudi Arabian children with DD. Our results provide evidence for cortical and subcortical abnormalities in DD. Deformities in the observed regions may contribute to cognitive impairment, emotional dysregulation, mood disorders, and language deficits commonly observed in DD. The structural analysis may enable the identification of neuroanatomical biomarkers to facilitate the early diagnosis or progression of DD. These results suggest that lower cortical complexity in DD children due to alterations in networks may play a critical role in early brain development.
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Affiliation(s)
- Abdullah H Abujamea
- Department of Radiology and Medical Imaging, King Saud University Medical City, King Saud University, Riyadh, SAU
| | - Mohammed Almosa
- Department of Radiology and Medical Imaging, King Saud University Medical City, King Saud University, Riyadh 12372, Saudi Arabia, Riyadh, SAU
| | - Mohammad Uzair
- Department of Biological Sciences, Faculty of Basic & Applied Sciences, International Islamic University, Islamabad, PAK
| | | | - Shahid Bashir
- Department of Neuroscience, Neuroscience Center, King Fahad Specialist Hospital, Dammam, SAU
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5
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Huang H, Rong B, Chen C, Wan Q, Liu Z, Zhou Y, Wang G, Wang H. Common and Distinct Functional Connectivity of the Orbitofrontal Cortex in Depression and Schizophrenia. Brain Sci 2023; 13:997. [PMID: 37508929 PMCID: PMC10377532 DOI: 10.3390/brainsci13070997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/12/2023] [Accepted: 06/22/2023] [Indexed: 07/30/2023] Open
Abstract
Schizophrenia and depression are psychiatric disorders with overlapping clinical and biological features. This study aimed to identify common and distinct neuropathological mechanisms in schizophrenia and depression patients using resting-state functional magnetic resonance imaging (fMRI). The study included 28 patients with depression (DEP), 29 patients with schizophrenia (SCH), and 30 healthy control subjects (HC). Intrinsic connectivity contrast (ICC) was used to identify functional connectivity (FC) changes at the whole-brain level, and significant ICC differences were found in the bilateral orbitofrontal cortex (OFC) across all three groups. Further seed-based FC analysis indicated that compared to the DEP and HC groups, the FC between bilateral OFC and medial prefrontal cortex (MPFC), right anterior insula, and right middle frontal gyrus were significantly lower in the SCH group. Additionally, the FC between right OFC and left thalamus was decreased in both patient groups compared to the HC group. Correlation analysis showed that the FC between OFC and MPFC was positively correlated with cognitive function in the SCH group. These findings suggest that OFC connectivity plays a critical role in the pathophysiology of schizophrenia and depression and may provide new insights into the potential neural mechanisms underlying these two disorders.
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Affiliation(s)
- Huan Huang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Bei Rong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Cheng Chen
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Qirong Wan
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yuan Zhou
- Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Hubei Institute of Neurology and Psychiatry Research, Wuhan 430060, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Department of Psychiatry, Zhongxiang Hospital of Renmin Hospital of Wuhan University, Zhongxiang 431900, China
- Hubei Provincial Key Laboratory of Developmentally Originated Disease, Wuhan 430071, China
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6
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Kato S, Maesawa S, Bagarinao E, Nakatsubo D, Tsugawa T, Mizuno S, Kawabata K, Tsuboi T, Suzuki M, Shibata M, Takai S, Ishizaki T, Torii J, Mutoh M, Saito R, Wakabayashi T, Katsuno M, Ozaki N, Watanabe H, Sobue G. Magnetic resonance-guided focused ultrasound thalamotomy restored distinctive resting-state networks in patients with essential tremor. J Neurosurg 2023; 138:306-317. [PMID: 35901706 DOI: 10.3171/2022.5.jns22411] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 05/19/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVE Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy ameliorates symptoms in patients with essential tremor (ET). How this treatment affects canonical brain networks has not been elucidated. The purpose of this study was to clarify changes of brain networks after MRgFUS thalamotomy in ET patients by analyzing resting-state networks (RSNs). METHODS Fifteen patients with ET were included in this study. Left MRgFUS thalamotomy was performed in all cases, and MR images, including resting-state functional MRI (rsfMRI), were taken before and after surgery. MR images of 15 age- and sex-matched healthy controls (HCs) were also used for analysis. Using rsfMRI data, canonical RSNs were extracted by performing dual regression analysis, and the functional connectivity (FC) within respective networks was compared among pre-MRgFUS patients, post-MRgFUS patients, and HCs. The severity of tremor was evaluated using the Clinical Rating Scale for Tremor (CRST) score pre- and postoperatively, and its correlation with RSNs was examined. RESULTS Preoperatively, ET patients showed a significant decrease in FC in the sensorimotor network (SMN), primary visual network (VN), and visuospatial network (VSN) compared with HCs. The decrease in FC in the SMN correlated with the severity of tremor. After MRgFUS thalamotomy, ET patients still exhibited a significant decrease in FC in a small area of the SMN, but they exhibited an increase in the cerebellar network (CN). In comparison between pre- and post-MRgFUS patients, the FC in the SMN and the VSN significantly increased after treatment. Quantitative evaluation of the FCs in these three groups showed that the SMN and VSN increased postoperatively and demonstrated a trend toward those of HCs. CONCLUSIONS The SMN and CN, which are considered to be associated with the cerebello-thalamo-cortical loop, exhibited increased connectivity after MRgFUS thalamotomy. In addition, the FC of the visual network, which declined in ET patients compared with HCs, tended to normalize postoperatively. This could be related to the hypothesis that visual feedback is involved in tremor severity in ET patients. Overall, the analysis of the RSNs by rsfMRI reflected the pathophysiology with the intervention of MRgFUS thalamotomy in ET patients and demonstrated a possibility of a biomarker for successful treatment.
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Affiliation(s)
- Sachiko Kato
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya.,2Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nakagawa, Nagoya
| | - Satoshi Maesawa
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya.,3Brain and Mind Research Center, Nagoya University, Showa, Nagoya
| | | | - Daisuke Nakatsubo
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya.,2Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nakagawa, Nagoya
| | - Takahiko Tsugawa
- 2Focused Ultrasound Therapy Center, Nagoya Kyoritsu Hospital, Nakagawa, Nagoya
| | - Satomi Mizuno
- 4Department of Rehabilitation, National Hospital Organization, Nagoya Medical Center, Naka, Nagoya
| | - Kazuya Kawabata
- 5Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya
| | - Takashi Tsuboi
- 5Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya
| | - Masashi Suzuki
- 5Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya
| | - Masashi Shibata
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya
| | - Sou Takai
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya
| | - Tomotaka Ishizaki
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya
| | - Jun Torii
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya
| | - Manabu Mutoh
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya
| | - Ryuta Saito
- 1Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya
| | | | - Masahisa Katsuno
- 5Department of Neurology, Nagoya University Graduate School of Medicine, Showa, Nagoya
| | - Norio Ozaki
- 3Brain and Mind Research Center, Nagoya University, Showa, Nagoya.,6Department of Psychiatry, Nagoya University Graduate School of Medicine, Showa, Nagoya; and
| | - Hirohisa Watanabe
- 3Brain and Mind Research Center, Nagoya University, Showa, Nagoya.,7Department of Neurology, Fujita Medical University, Kutsukake, Toyoake; and
| | - Gen Sobue
- 3Brain and Mind Research Center, Nagoya University, Showa, Nagoya.,8Aichi Medical University, Karimata, Nagakute, Aichi, Japan
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Abstract
Dendritic spine features in human neurons follow the up-to-date knowledge presented in the previous chapters of this book. Human dendrites are notable for their heterogeneity in branching patterns and spatial distribution. These data relate to circuits and specialized functions. Spines enhance neuronal connectivity, modulate and integrate synaptic inputs, and provide additional plastic functions to microcircuits and large-scale networks. Spines present a continuum of shapes and sizes, whose number and distribution along the dendritic length are diverse in neurons and different areas. Indeed, human neurons vary from aspiny or "relatively aspiny" cells to neurons covered with a high density of intermingled pleomorphic spines on very long dendrites. In this chapter, we discuss the phylogenetic and ontogenetic development of human spines and describe the heterogeneous features of human spiny neurons along the spinal cord, brainstem, cerebellum, thalamus, basal ganglia, amygdala, hippocampal regions, and neocortical areas. Three-dimensional reconstructions of Golgi-impregnated dendritic spines and data from fluorescence microscopy are reviewed with ultrastructural findings to address the complex possibilities for synaptic processing and integration in humans. Pathological changes are also presented, for example, in Alzheimer's disease and schizophrenia. Basic morphological data can be linked to current techniques, and perspectives in this research field include the characterization of spines in human neurons with specific transcriptome features, molecular classification of cellular diversity, and electrophysiological identification of coexisting subpopulations of cells. These data would enlighten how cellular attributes determine neuron type-specific connectivity and brain wiring for our diverse aptitudes and behavior.
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Affiliation(s)
- Josué Renner
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
| | - Alberto A Rasia-Filho
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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8
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Cortical electrical activity changes in healthy aging using EEG-eLORETA analysis. NEUROIMAGE: REPORTS 2022. [DOI: 10.1016/j.ynirp.2022.100143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
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9
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The impact of aging on human brain network target controllability. Brain Struct Funct 2022; 227:3001-3015. [DOI: 10.1007/s00429-022-02584-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 10/09/2022] [Indexed: 11/27/2022]
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10
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Malagurski B, Deschwanden PF, Jäncke L, Mérillat S. Longitudinal functional connectivity patterns of the default mode network in healthy older adults. Neuroimage 2022; 259:119414. [PMID: 35760292 DOI: 10.1016/j.neuroimage.2022.119414] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 06/18/2022] [Accepted: 06/23/2022] [Indexed: 11/29/2022] Open
Abstract
Cross-sectional studies have consistently identified age-associated alterations in default mode network (DMN) functional connectivity (FC). Yet, research on longitudinal trajectories of FC changes of the DMN in healthy aging is less conclusive. For the present study, we used a resting state functional MRI dataset drawn from the Longitudinal Healthy Aging Brain Database Project (LHAB) collected in 5 occasions over a course of 7 years (baseline N = 232, age range: 64-87 y, mean age = 70.85 y). FC strength changes within the DMN and its regions were investigated using a network-based statistical method suitable for the analysis of longitudinal data. The average DMN FC strength remained stable, however, various DMN components showed differential age- and time-related effects. Our results revealed a complex pattern of longitudinal change seen as decreases and increases of FC strength encompassing the majority of DMN regions, while age-related effects were negative and present in select brain areas. These findings testify to the growing importance of longitudinal studies using more sophisticated fine-grained tools needed to highlight the complexity of the functional reorganization of DMN with healthy aging.
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Affiliation(s)
- Brigitta Malagurski
- University Research Priority Program "Dynamics of Healthy Aging", University of Zürich, Switzerland
| | | | - Lutz Jäncke
- University Research Priority Program "Dynamics of Healthy Aging", University of Zürich, Switzerland; Division of Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Susan Mérillat
- University Research Priority Program "Dynamics of Healthy Aging", University of Zürich, Switzerland.
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11
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Kawabata K, Bagarinao E, Watanabe H, Maesawa S, Mori D, Hara K, Ohdake R, Masuda M, Ogura A, Kato T, Koyama S, Katsuno M, Wakabayashi T, Kuzuya M, Hoshiyama M, Isoda H, Naganawa S, Ozaki N, Sobue G. Functional connector hubs in the cerebellum. Neuroimage 2022; 257:119263. [PMID: 35500805 DOI: 10.1016/j.neuroimage.2022.119263] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 03/17/2022] [Accepted: 04/27/2022] [Indexed: 01/11/2023] Open
Abstract
Accumulating evidence from anatomical and neuroimaging studies suggests that the cerebellum is engaged in a variety of motor and cognitive tasks. Given its various functions, a key question is whether the cerebellum also plays an important role in the brain's integrative functions. Here, we hypothesize the existence of connector regions, also known as connector hubs, where multiple resting state networks converged in the cerebellum. To verify this, we employed a recently developed voxel-level network measure called functional connectivity overlap ratio (FCOR), which could be used to quantify the spatial extent of a region's connection to several large-scale cortical networks. Using resting state functional MRI data from 101 healthy participants, cerebellar FCOR maps were constructed and used to identify the locations of connector hubs in the cerebellum. Results showed that a number of cerebellar regions exhibited strong connectivity with multiple functional networks, verifying our hypothesis. These highly connected regions were located in the posterior cerebellum, especially in lobules VI, VII, and IX, and mainly connected to the core neurocognitive networks such as default mode and executive control networks. Regions associated with the sensorimotor network were also localized in lobule V, VI, and VIII, albeit in small clusters. These cerebellar connector hubs may play an essential role in the processing of information across the core neurocognitive networks.
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Affiliation(s)
- Kazuya Kawabata
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Neurology, Medical University of Innsbruck, Austria.
| | - Epifanio Bagarinao
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Hirohisa Watanabe
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi 470-1192, Japan.
| | - Satoshi Maesawa
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Daisuke Mori
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan
| | - Reiko Ohdake
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi 470-1192, Japan
| | - Michihito Masuda
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan
| | - Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan
| | - Toshiyasu Kato
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan
| | - Shuji Koyama
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan
| | - Toshihiko Wakabayashi
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Masafumi Kuzuya
- Department of Community Healthcare and Geriatrics, Nagoya University Graduate School of Medicine and Institutes of Innovation for Future Society, Nagoya, Aichi, Japan
| | - Minoru Hoshiyama
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Haruo Isoda
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Shinji Naganawa
- Department of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Norio Ozaki
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi 466-8550, Japan; Aichi Medical University, Nagakute, Japan.
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12
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Maesawa S, Mizuno S, Bagarinao E, Watanabe H, Kawabata K, Hara K, Ohdake R, Ogura A, Mori D, Nakatsubo D, Isoda H, Hoshiyama M, Katsuno M, Saito R, Ozaki N, Sobue G. Resting State Networks Related to the Maintenance of Good Cognitive Performance During Healthy Aging. Front Hum Neurosci 2021; 15:753836. [PMID: 34803636 PMCID: PMC8604343 DOI: 10.3389/fnhum.2021.753836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 10/19/2021] [Indexed: 11/17/2022] Open
Abstract
Purpose: Maintenance of cognitive performance is important for healthy aging. This study aims to elucidate the relationship between brain networks and cognitive function in subjects maintaining relatively good cognitive performance. Methods: A total of 120 subjects, with equal number of participants from each age group between 20 and 70 years, were included in this study. Only participants with Addenbrooke’s Cognitive Examination – Revised (ACE-R) total score greater than 83 were included. Anatomical T1-weighted MR images and resting-state functional MR images (rsfMRIs) were taken from all participants using a 3-tesla MRI scanner. After preprocessing, several factors associated with age including the ACE-R total score, scores of five domains, sub-scores of ACE-R, and brain volumes were tested. Morphometric changes associated with age were analyzed using voxel based morphometry (VBM) and changes in resting state networks (RSNs) were examined using dual regression analysis. Results: Significant negative correlations with age were seen in the total gray matter volume (GMV, r = −0.58), and in the memory, attention, and visuospatial domains. Among the different sub-scores, the score of the delayed recall (DR) showed the highest negative correlation with age (r = −0.55, p < 0.001). In VBM analysis, widespread regions demonstrated negative correlation with age, but none with any of the cognitive scores. Quadratic approximations of cognitive scores as functions of age showed relatively delayed decline compared to total GMV loss. In dual regression analysis, some cognitive networks, including the dorsal default mode network, the lateral dorsal attention network, the right / left executive control network, the posterior salience network, and the language network, did not demonstrate negative correlation with age. Some regions in the sensorimotor networks showed positive correlation with the DR, memory, and fluency scores. Conclusion: Some domains of the cognitive test did not correlate with age, and even the highly correlated sub-scores such as the DR score, showed delayed decline compared to the loss of total GMV. Some RSNs, especially involving cognitive control regions, were relatively maintained with age. Furthermore, the scores of memory, fluency, and the DR were correlated with the within-network functional connectivity values of the sensorimotor network, which supported the importance of exercise for maintenance of cognition.
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Affiliation(s)
- Satoshi Maesawa
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Satomi Mizuno
- Department of Rehabilitation Medicine, National Hospital Organization, Nagoya Medical Center, Nagoya, Japan
| | | | - Hirohisa Watanabe
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Kazuya Kawabata
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Reiko Ohdake
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Daisuke Mori
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Daisuke Nakatsubo
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Haruo Isoda
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Minoru Hoshiyama
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Ryuta Saito
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Norio Ozaki
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan.,Department of Neurology, Aichi Medical University, Nagakute, Japan
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13
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Watanabe H, Bagarinao E, Maesawa S, Hara K, Kawabata K, Ogura A, Ohdake R, Shima S, Mizutani Y, Ueda A, Ito M, Katsuno M, Sobue G. Characteristics of Neural Network Changes in Normal Aging and Early Dementia. Front Aging Neurosci 2021; 13:747359. [PMID: 34880745 PMCID: PMC8646086 DOI: 10.3389/fnagi.2021.747359] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/18/2021] [Indexed: 12/03/2022] Open
Abstract
To understand the mechanisms underlying preserved and impaired cognitive function in healthy aging and dementia, respectively, the spatial relationships of brain networks and mechanisms of their resilience should be understood. The hub regions of the brain, such as the multisensory integration and default mode networks, are critical for within- and between-network communication, remain well-preserved during aging, and play an essential role in compensatory processes. On the other hand, these brain hubs are the preferred sites for lesions in neurodegenerative dementias, such as Alzheimer's disease. Disrupted primary information processing networks, such as the auditory, visual, and sensorimotor networks, may lead to overactivity of the multisensory integration networks and accumulation of pathological proteins that cause dementia. At the cellular level, the brain hub regions contain many synapses and require a large amount of energy. These regions are rich in ATP-related gene expression and had high glucose metabolism as demonstrated on positron emission tomography (PET). Importantly, the number and function of mitochondria, which are the center of ATP production, decline by about 8% every 10 years. Dementia patients often have dysfunction of the ubiquitin-proteasome and autophagy-lysosome systems, which require large amounts of ATP. If there is low energy supply but the demand is high, the risk of disease can be high. Imbalance between energy supply and demand may cause accumulation of pathological proteins and play an important role in the development of dementia. This energy imbalance may explain why brain hub regions are vulnerable to damage in different dementias. Here, we review (1) the characteristics of gray matter network, white matter network, and resting state functional network changes related to resilience in healthy aging, (2) the mode of resting state functional network disruption in neurodegenerative dementia, and (3) the cellular mechanisms associated with the disruption.
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Affiliation(s)
- Hirohisa Watanabe
- Department of Neurology, Fujita Health University, Toyoake, Japan
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Epifanio Bagarinao
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Satoshi Maesawa
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Department of Neurosurgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuhiro Hara
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kazuya Kawabata
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Aya Ogura
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Reiko Ohdake
- Department of Neurology, Fujita Health University, Toyoake, Japan
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
| | - Sayuri Shima
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Yasuaki Mizutani
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Akihiro Ueda
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Mizuki Ito
- Department of Neurology, Fujita Health University, Toyoake, Japan
| | - Masahisa Katsuno
- Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Gen Sobue
- Brain and Mind Research Center, Nagoya University, Nagoya, Japan
- Aichi Medical University, Nagakute, Japan
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14
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Kavroulakis E, Simos NJ, Maris TG, Zaganas I, Panagiotakis S, Papadaki E. Evidence of Age-Related Hemodynamic and Functional Connectivity Impairment: A Resting State fMRI Study. Front Neurol 2021; 12:633500. [PMID: 33833727 PMCID: PMC8021915 DOI: 10.3389/fneur.2021.633500] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/01/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: To assess age-related changes in intrinsic functional brain connectivity and hemodynamics during adulthood in the context of the retrogenesis hypothesis, which states that the rate of age-related changes is higher in late-myelinating (prefrontal, lateral-posterior temporal) cerebrocortical areas as compared to early myelinating (parietal, occipital) regions. In addition, to examine the dependence of age-related changes upon concurrent subclinical depression symptoms which are common even in healthy aging. Methods: Sixty-four healthy adults (28 men) aged 23-79 years (mean 45.0, SD = 18.8 years) were examined. Resting-state functional MRI (rs-fMRI) time series were used to compute voxel-wise intrinsic connectivity contrast (ICC) maps reflecting the strength of functional connectivity between each voxel and the rest of the brain. We further used Time Shift Analysis (TSA) to estimate voxel-wise hemodynamic lead or lag for each of 22 ROIs from the automated anatomical atlas (AAL). Results: Adjusted for depression symptoms, gender and education level, reduced ICC with age was found primarily in frontal, temporal regions, and putamen, whereas the opposite trend was noted in inferior occipital cortices (p < 0.002). With the same covariates, increased hemodynamic lead with advancing age was found in superior frontal cortex and thalamus, with the opposite trend in inferior occipital cortex (p < 0.002). There was also evidence of reduced coupling between voxel-wise intrinsic connectivity and hemodynamics in the inferior parietal cortex. Conclusion: Age-related intrinsic connectivity reductions and hemodynamic changes were demonstrated in several regions-most of them part of DMN and salience networks-while impaired neurovascular coupling was, also, found in parietal regions. Age-related reductions in intrinsic connectivity were greater in anterior as compared to posterior cortices, in line with implications derived from the retrogenesis hypothesis. These effects were affected by self-reported depression symptoms, which also increased with age.
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Affiliation(s)
- Eleftherios Kavroulakis
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Heraklion, Greece
| | - Nicholas J Simos
- Department of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece.,Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology - Hellas, Heraklion, Greece
| | - Thomas G Maris
- Department of Medical Physics, School of Medicine, University of Crete, University Hospital of Heraklion, Heraklion, Greece
| | - Ioannis Zaganas
- Department of Neurology, School of Medicine, University of Crete, University Hospital of Heraklion, Heraklion, Greece
| | - Simeon Panagiotakis
- Department of Internal Medicine, University Hospital of Heraklion, Heraklion, Greece
| | - Efrosini Papadaki
- Department of Radiology, School of Medicine, University of Crete, University Hospital of Heraklion, Heraklion, Greece.,Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology - Hellas, Heraklion, Greece
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