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Shin HG, Li X, Heo HY, Knutsson L, Szczepankiewicz F, Nilsson M, van Zijl PCM. Compartmental anisotropy of filtered exchange imaging (FEXI) in human white matter: What is happening in FEXI? Magn Reson Med 2024; 92:660-675. [PMID: 38525601 PMCID: PMC11142880 DOI: 10.1002/mrm.30086] [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: 09/04/2023] [Revised: 01/30/2024] [Accepted: 02/28/2024] [Indexed: 03/26/2024]
Abstract
PURPOSE To investigate the effects of compartmental anisotropy on filtered exchange imaging (FEXI) in white matter (WM). THEORY AND METHODS FEXI signals were measured using multiple combinations of diffusion filter and detection directions in five healthy volunteers. Additional filters, including a trace-weighted diffusion filter with trapezoidal gradients, a spherical b-tensor encoded diffusion filter, and a T2 filter, were tested with trace-weighted diffusion detection. RESULTS A large range of apparent exchange rates (AXR) and both positive and negative filter efficiencies (σ) were found depending on the mutual orientation of the filter and detection gradients relative to WM fiber orientation. The data demonstrated that the fast-diffusion compartment suppressed by diffusional filtering is not exclusively extra-cellular, but also intra-cellular. While not comprehensive, a simple two-compartment diffusion tensor model with water exchange was able to account qualitatively for the trends in positive and negative filtering efficiencies, while standard model imaging (SMI) without exchange could not. This two-compartment diffusion tensor model also demonstrated smaller AXR variances across subjects. When employing trace-weighted diffusion detection, AXR values were on the order of the R1 (=1/T1) of water at 3T for crossing fibers, while being less than R1 for parallel fibers. CONCLUSION Orientation-dependent AXR and σ values were observed when using multi-orientation filter and detection gradients in FEXI, indicating that WM FEXI models need to account for compartmental anisotropy. When using trace-weighted detection, AXR values were on the order of or less than R1, complicating the interpretation of FEXI results in WM in terms of biological exchange properties. These findings may contribute toward better understanding of FEXI results in WM.
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Affiliation(s)
- Hyeong-Geol Shin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hye-Young Heo
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Linda Knutsson
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Filip Szczepankiewicz
- Department of Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Markus Nilsson
- Department of Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Chan SY, Fitzgerald E, Ngoh ZM, Lee J, Chuah J, Chia JSM, Fortier MV, Tham EH, Zhou JH, Silveira PP, Meaney MJ, Tan AP. Examining the associations between microglia genetic capacity, early life exposures and white matter development at the level of the individual. Brain Behav Immun 2024; 119:781-791. [PMID: 38677627 DOI: 10.1016/j.bbi.2024.04.038] [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: 03/15/2024] [Revised: 04/17/2024] [Accepted: 04/23/2024] [Indexed: 04/29/2024] Open
Abstract
There are inter-individual differences in susceptibility to the influence of early life experiences for which the underlying neurobiological mechanisms are poorly understood. Microglia play a role in environmental surveillance and may influence individual susceptibility to environmental factors. As an index of neurodevelopment, we estimated individual slopes of mean white matter fractional anisotropy (WM-FA) across three time-points (age 4.5, 6.0, and 7.5 years) for 351 participants. Individual variation in microglia reactivity was derived from an expression-based polygenic score(ePGS) comprised of Single Nucleotide Polymorphisms (SNPs) functionally related to the expression of microglia-enriched genes.A higher ePGS denotes an increased genetic capacity for the expression of microglia-related genes, and thus may confer a greater capacity to respond to the early environment and to influence brain development. We hypothesized that this ePGS would associate with the WM-FA index of neurodevelopment and moderate the influence of early environmental factors.Our findings show sex dependency, where a significant association between WM-FA and microglia ePGS was only obtained for females.We then examined associations with perinatal factors known to decrease (optimal birth outcomes and familial conditions) or increase (systemic inflammation) the risk for later mental health problems.In females, individuals with high microglia ePGS showed a negative association between systemic inflammation and WM-FA and a positive association between more advantageous environmental conditions and WM-FA. The microglia ePGS in females thus accounted for variations in the influence of the quality of the early environment on WM-FA.Finally, WM-FA slopes mediated the association of microglia ePGS with interpersonal problems and social hostility in females. Our findings suggest the genetic capacity for microglia function as a potential factor underlying differential susceptibility to early life exposuresthrough influences on neurodevelopment.
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Affiliation(s)
- Shi Yu Chan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Eamon Fitzgerald
- Ludmer Centre for Neuroinformatics and Mental Health, McGill University, 1010 Rue Sherbrooke O, QC H3A 2R7, Canada; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, 6875 Bd LaSalle, QC H4H 1R3, Canada
| | - Zhen Ming Ngoh
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Janice Lee
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Jasmine Chuah
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Joanne S M Chia
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore; Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, 100 Bukit Timah Rd, Singapore 229899, Singapore; Duke-NUS Medical School, 8 College Rd, Singapore 169857, Singapore
| | - Elizabeth H Tham
- Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Khoo Teck Puat-National University Children's Medical Institute, National University Health System (NUHS), 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
| | - Juan H Zhou
- Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
| | - Patricia P Silveira
- Ludmer Centre for Neuroinformatics and Mental Health, McGill University, 1010 Rue Sherbrooke O, QC H3A 2R7, Canada; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, 6875 Bd LaSalle, QC H4H 1R3, Canada; Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, 6875 Bd LaSalle, QC H4H 1R3, Canada; Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Brain - Body Initiative Program, Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, Connexis North Tower, Singapore 138632, Singapore
| | - Ai Peng Tan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), 30 Medical Dr, Singapore 117609, Singapore; Yong Loo Lin School of Medicine, National University of Singapore (NUS), 10 Medical Dr, Singapore 117597, Singapore; Brain - Body Initiative Program, Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, Connexis North Tower, Singapore 138632, Singapore; Department of Diagnostic Imaging, National University Health System, 1E Kent Ridge Rd, Singapore 119228, Singapore.
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Jalnefjord O, Björkman-Burtscher IM. Comparison of methods for intravoxel incoherent motion parameter estimation in the brain from flow-compensated and non-flow-compensated diffusion-encoded data. Magn Reson Med 2024; 92:303-318. [PMID: 38321596 DOI: 10.1002/mrm.30042] [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: 12/08/2023] [Revised: 01/12/2024] [Accepted: 01/22/2024] [Indexed: 02/08/2024]
Abstract
PURPOSE Joint analysis of flow-compensated (FC) and non-flow-compensated (NC) diffusion MRI (dMRI) data has been suggested for increased robustness of intravoxel incoherent motion (IVIM) parameter estimation. For this purpose, a set of methods commonly used or previously found useful for IVIM analysis of dMRI data obtained with conventional diffusion encoding were evaluated in healthy human brain. METHODS Five methods for joint IVIM analysis of FC and NC dMRI data were compared: (1) direct non-linear least squares fitting, (2) a segmented fitting algorithm with estimation of the diffusion coefficient from higher b-values of NC data, (3) a Bayesian algorithm with uniform prior distributions, (4) a Bayesian algorithm with spatial prior distributions, and (5) a deep learning-based algorithm. Methods were evaluated on brain dMRI data from healthy subjects and simulated data at multiple noise levels. Bipolar diffusion encoding gradients were used with b-values 0-200 s/mm2 and corresponding flow weighting factors 0-2.35 s/mm for NC data and by design 0 for FC data. Data were acquired twice for repeatability analysis. RESULTS Measurement repeatability as well as estimation bias and variability were at similar levels or better with the Bayesian algorithm with spatial prior distributions and the deep learning-based algorithm for IVIM parametersD $$ D $$ andf $$ f $$ , and for the Bayesian algorithm only forv d $$ {v}_d $$ , relative to the other methods. CONCLUSION A Bayesian algorithm with spatial prior distributions is preferable for joint IVIM analysis of FC and NC dMRI data in the healthy human brain, but deep learning-based algorithms appear promising.
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Affiliation(s)
- Oscar Jalnefjord
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - Isabella M Björkman-Burtscher
- Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Radiology, Section of Neuroradiology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
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Rosmarin DH, Kumar P, Kaufman CC, Drury M, Harper D, Forester BP. Neurobiological correlates of religious coping among older adults with and without mood disorders: An exploratory study. Psychiatry Res Neuroimaging 2024; 341:111812. [PMID: 38631136 DOI: 10.1016/j.pscychresns.2024.111812] [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: 11/29/2023] [Revised: 03/14/2024] [Accepted: 03/25/2024] [Indexed: 04/19/2024]
Abstract
In this study, 32 older adults with and without mood disorders completed resting-state functional Magnetic Resonance Imaging and measures of demographics, spirituality/religion, positive and negative religious coping, and depression. Group Independent Component Analysis identified and selected three a priori resting state networks [cingulo-opercular salience (cSN), central executive (CEN) and Default Mode Networks (DMN)] within the Triple Network Mode. We investigated associations of religious coping with within- and between-network connectivity, controlling for age. Insular connectivity within the cSN was associated with negative religious coping. Religious coping was associated with anti-correlation between the DMN and CEN even when controlling for depression.
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Affiliation(s)
- David H Rosmarin
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Spirituality & Mental Health Program, McLean Hospital, Belmont, MA, United States.
| | - Poornima Kumar
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Laboratory for Translational and Affective Neuroscience, McLean Hospital, Belmont, MA, United States
| | - Caroline C Kaufman
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Spirituality & Mental Health Program, McLean Hospital, Belmont, MA, United States
| | - Mia Drury
- Spirituality & Mental Health Program, McLean Hospital, Belmont, MA, United States
| | - David Harper
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Geriatric Psychiatry Research Program, McLean Hospital, Belmont, MA, United States
| | - Brent P Forester
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Geriatric Psychiatry Research Program, McLean Hospital, Belmont, MA, United States; Tufts Medical Center, Tufts University School of Medicine, United States
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Lee HK, Basak C, Grant SJ, Ray NR, Skolasinska PA, Oehler C, Qin S, Sun A, Smith ET, Sherard GH, Rivera-Dompenciel A, Merzenich M, Voss MW. The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae075. [PMID: 38686621 PMCID: PMC11165429 DOI: 10.1093/geronb/gbae075] [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: 07/24/2023] [Indexed: 05/02/2024] Open
Abstract
OBJECTIVES Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults. METHODS One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64). RESULTS After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure. DISCUSSION Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT. CLINICAL TRIAL REGISTRATION NCT03197454.
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Affiliation(s)
- Hyun Kyu Lee
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | | | - Sarah-Jane Grant
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Nicholas R Ray
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Chris Oehler
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
| | - Shuo Qin
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Andrew Sun
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - Evan T Smith
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | - G Hulon Sherard
- Department of Psychology, University of Texas at Dallas, Dallas, Texas, USA
| | | | - Mike Merzenich
- Department of Research and Development, Posit Science Corporation, San Francisco, California, USA
| | - Michelle W Voss
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA
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6
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Liu Q, Ning L, Shaik IA, Liao C, Gagoski B, Bilgic B, Grissom W, Nielsen JF, Zaitsev M, Rathi Y. Reduced cross-scanner variability using vendor-agnostic sequences for single-shell diffusion MRI. Magn Reson Med 2024; 92:246-256. [PMID: 38469671 PMCID: PMC11055665 DOI: 10.1002/mrm.30062] [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: 12/07/2023] [Revised: 01/31/2024] [Accepted: 02/05/2024] [Indexed: 03/13/2024]
Abstract
PURPOSE To reduce the inter-scanner variability of diffusion MRI (dMRI) measures between scanners from different vendors by developing a vendor-neutral dMRI pulse sequence using the open-source vendor-agnostic Pulseq platform. METHODS We implemented a standard EPI based dMRI sequence in Pulseq. We tested it on two clinical scanners from different vendors (Siemens Prisma and GE Premier), systematically evaluating and comparing the within- and inter-scanner variability across the vendors, using both the vendor-provided and Pulseq dMRI sequences. Assessments covered both a diffusion phantom and three human subjects, using standard error (SE) and Lin's concordance correlation to measure the repeatability and reproducibility of standard DTI metrics including fractional anisotropy (FA) and mean diffusivity (MD). RESULTS Identical dMRI sequences were executed on both scanners using Pulseq. On the phantom, the Pulseq sequence showed more than a 2.5× reduction in SE (variability) across Siemens and GE scanners. Furthermore, Pulseq sequences exhibited markedly reduced SE in-vivo, maintaining scan-rescan repeatability while delivering lower variability in FA and MD (more than 50% reduction in cortical/subcortical regions) compared to vendor-provided sequences. CONCLUSION The Pulseq diffusion sequence reduces the cross-scanner variability for both phantom and in-vivo data, which will benefit multi-center neuroimaging studies and improve the reproducibility of neuroimaging studies.
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Affiliation(s)
- Qiang Liu
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Lipeng Ning
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Imam Ahmed Shaik
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States
| | - Berkin Bilgic
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Harvard/MIT Health Sciences and Technology, Cambridge, MA, United States
| | - William Grissom
- Department of Biomedical Engineering, Case School of Medicine, Case Western Reserve University, Cleveland, OH, United States
| | - Jon-Fredrik Nielsen
- fMRI Laboratory and Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Maxim Zaitsev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Yogesh Rathi
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
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Wu W. Dynamic field mapping and distortion correction using single-shot blip-rewound EPI and joint multi-echo reconstruction. Magn Reson Med 2024; 92:82-97. [PMID: 38308081 DOI: 10.1002/mrm.30038] [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: 08/17/2023] [Revised: 01/02/2024] [Accepted: 01/16/2024] [Indexed: 02/04/2024]
Abstract
PURPOSE To develop a method for dynamic∆ B 0 $$ \Delta {B}_0 $$ mapping and distortion correction. METHODS A blip-rewound EPI trajectory was developed to acquire multiple 2D EPI images in a single readout with an interleaved order, which allows a short TE difference. A joint multi-echo reconstruction was utilized to exploit the shared information between EPI images. The reconstructed images from each readout are combined to produce a final magnitude image. A∆ B 0 $$ \Delta {B}_0 $$ map is calculated from the phase of these images for distortion correction. The efficacy of the proposed method is assessed with phantom and in vivo experiments. The performance of the proposed method in the presence of subject motion is also investigated. RESULTS Compared to conventional multi-echo EPI, the proposed method allows dynamic∆ B 0 $$ \Delta {B}_0 $$ mapping at matched resolution with a much shorter TR. Phantom and in vivo results show that the proposed method can provide a comparable magnitude image as conventional single-shot EPI. The∆ B 0 $$ \Delta {B}_0 $$ maps calculated from the proposed method are consistent with conventional multi-echo EPI in the phantom experiment. For in vivo experiments, the proposed method provides a more accurate estimation of∆ B 0 $$ \Delta {B}_0 $$ than conventional multi-echo EPI, which is prone to phase wrapping problems due to the long TE difference. In-vivo scan with subject motion shows the proposed dynamic field mapping method can improve the temporal stability of EPI time series compared to gradient echo (GRE) based static field mapping. CONCLUSION The proposed method allows accurate dynamic∆ B 0 $$ \Delta {B}_0 $$ mapping for robust distortion correction without compromising spatial or temporal resolution.
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Affiliation(s)
- Wenchuan Wu
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Chen J, Liu T, Shi H. End-stage renal disease accompanied by mild cognitive impairment: A study and analysis of trimodal brain network fusion. PLoS One 2024; 19:e0305079. [PMID: 38870175 DOI: 10.1371/journal.pone.0305079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024] Open
Abstract
The function and structure of brain networks (BN) may undergo changes in patients with end-stage renal disease (ESRD), particularly in those accompanied by mild cognitive impairment (ESRDaMCI). Many existing methods for fusing BN focus on extracting interaction features between pairs of network nodes from each mode and combining them. This approach overlooks the correlation between different modal features during feature extraction and the potentially valuable information that may exist between more than two brain regions. To address this issue, we propose a model using a multi-head self-attention mechanism to fuse brain functional networks, white matter structural networks, and gray matter structural networks, which results in the construction of brain fusion networks (FBN). Initially, three networks are constructed: the brain function network, the white matter structure network, and the individual-based gray matter structure network. The multi-head self-attention mechanism is then applied to fuse the three types of networks, generating attention weights that are transformed into an optimized model. The optimized model introduces hypergraph popular regular term and L1 norm regular term, leading to the formation of FBN. Finally, FBN is employed in the diagnosis and prediction of ESRDaMCI to evaluate its classification performance and investigate the correlation between discriminative brain regions and cognitive dysfunction. Experimental results demonstrate that the optimal classification accuracy achieved is 92.80%, which is at least 3.63% higher than the accuracy attained using other methods. This outcome confirms the effectiveness of our proposed method. Additionally, the identification of brain regions significantly associated with scores on the Montreal cognitive assessment scale may shed light on the underlying pathogenesis of ESRDaMCI.
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Affiliation(s)
- Jie Chen
- Department of Security, Huaide College of Changzhou University, Jingjiang, Jiangsu, China
| | - Tongqiang Liu
- Department of Nephrology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
| | - Haifeng Shi
- Department of Radiology, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, Jiangsu, China
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Hüper L, Steinacker P, Polyakova M, Mueller K, Godulla J, Herzig S, Danek A, Engel A, Diehl-Schmid J, Classen J, Fassbender K, Fliessbach K, Jahn H, Kassubek J, Kornhuber J, Landwehrmeyer B, Lauer M, Obrig H, Oeckl P, Prudlo J, Saur D, Anderl-Straub S, Synofzik M, Wagner M, Wiltfang J, Winkelmann J, Volk AE, Huppertz HJ, Otto M, Schroeter ML. Neurofilaments and progranulin are related to atrophy in frontotemporal lobar degeneration - A transdiagnostic study cross-validating atrophy and fluid biomarkers. Alzheimers Dement 2024. [PMID: 38865340 DOI: 10.1002/alz.13863] [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: 12/21/2023] [Revised: 03/22/2024] [Accepted: 03/24/2024] [Indexed: 06/14/2024]
Abstract
INTRODUCTION Frontotemporal lobar degeneration (FTLD) encompasses behavioral variant frontotemporal dementia (bvFTD), progressive supranuclear palsy, corticobasal syndrome/degeneration, and primary progressive aphasias (PPAs). We cross-validated fluid biomarkers and neuroimaging. METHODS Seven fluid biomarkers from cerebrospinal fluid and serum were related to atrophy in 428 participants including these FTLD subtypes, logopenic variant PPA (lvPPA), Alzheimer's disease (AD), and healthy subjects. Atrophy was assessed by structural magnetic resonance imaging and atlas-based volumetry. RESULTS FTLD subtypes, lvPPA, and AD showed specific profiles for neurofilament light chain, phosphorylated heavy chain, tau, phospho-tau, amyloid beta1-42 from serum/cerebrospinal fluid, and brain atrophy. Neurofilaments related to regional atrophy in bvFTD, whereas progranulin was associated with atrophy in semantic variant PPA. Ubiquitin showed no effects. DISCUSSION Results specify biomarker and atrophy patterns in FTLD and AD supporting differential diagnosis. They identify neurofilaments and progranulin in interaction with structural imaging as promising candidates for monitoring disease progression and therapy. HIGHLIGHTS Study cross-validated neuroimaging and fluid biomarkers in dementia. Five kinds of frontotemporal lobar degeneration and two variants of Alzheimer's disease. Study identifies disease-specific fluid biomarker and atrophy profiles. Fluid biomarkers and atrophy interact in a disease-specific way. Neurofilaments and progranulin are proposed as biomarkers for diagnosis and therapy.
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Affiliation(s)
- Lea Hüper
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Petra Steinacker
- Department of Neurology, University Clinic Halle, Martin Luther University Halle-Wittenberg, Halle, Saale, Germany
| | - Maryna Polyakova
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Karsten Mueller
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jannis Godulla
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Sabine Herzig
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Adrian Danek
- Department of Neurology, Ludwig Maximilians University Munich, Munich, Germany
| | - Annerose Engel
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Janine Diehl-Schmid
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
- kbo-Inn-Salzach-Klinikum, Clinical Center for Psychiatry, Psychotherapy, Psychosomatic Medicine, Geriatrics and Neurology, Wasserburg/Inn, Germany
| | - Joseph Classen
- Department for Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Klaus Fassbender
- Department of Neurology, Saarland University Hospital, Homburg, Germany
| | - Klaus Fliessbach
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Holger Jahn
- Department of Psychiatry and Psychotherapy, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, University Hospital Erlangen, Erlangen, Germany
| | | | - Martin Lauer
- Department of Psychiatry and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Hellmuth Obrig
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Patrick Oeckl
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Johannes Prudlo
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University Medicine Rostock, Rostock, Germany
| | - Dorothee Saur
- Department for Neurology, University Hospital Leipzig, Leipzig, Germany
| | | | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurodegenerative Diseases, Center of Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Matias Wagner
- Institute of Human Genetics, School of Medicine and Health, Technical University Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Center Munich, Neuherberg, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Göttingen, Germany
- Neurosciences and Signaling Group, Department of Medical Sciences, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Center Munich, Neuherberg, Germany
| | - Alexander E Volk
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Markus Otto
- Department of Neurology, University Clinic Halle, Martin Luther University Halle-Wittenberg, Halle, Saale, Germany
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Matthias L Schroeter
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
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10
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Madden DJ, Merenstein JL, Mullin HA, Jain S, Rudolph MD, Cohen JR. Age-related differences in resting-state, task-related, and structural brain connectivity: graph theoretical analyses and visual search performance. Brain Struct Funct 2024:10.1007/s00429-024-02807-2. [PMID: 38856933 DOI: 10.1007/s00429-024-02807-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 05/13/2024] [Indexed: 06/11/2024]
Abstract
Previous magnetic resonance imaging (MRI) research suggests that aging is associated with a decrease in the functional interconnections within and between groups of locally organized brain regions (modules). Further, this age-related decrease in the segregation of modules appears to be more pronounced for a task, relative to a resting state, reflecting the integration of functional modules and attentional allocation necessary to support task performance. Here, using graph-theoretical analyses, we investigated age-related differences in a whole-brain measure of module connectivity, system segregation, for 68 healthy, community-dwelling individuals 18-78 years of age. We obtained resting-state, task-related (visual search), and structural (diffusion-weighted) MRI data. Using a parcellation of modules derived from the participants' resting-state functional MRI data, we demonstrated that the decrease in system segregation from rest to task (i.e., reconfiguration) increased with age, suggesting an age-related increase in the integration of modules required by the attentional demands of visual search. Structural system segregation increased with age, reflecting weaker connectivity both within and between modules. Functional and structural system segregation had qualitatively different influences on age-related decline in visual search performance. Functional system segregation (and reconfiguration) influenced age-related decline in the rate of visual evidence accumulation (drift rate), whereas structural system segregation contributed to age-related slowing of encoding and response processes (nondecision time). The age-related differences in the functional system segregation measures, however, were relatively independent of those associated with structural connectivity.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA.
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, 27710, USA.
- Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
| | - Hollie A Mullin
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- Department of Psychology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Shivangi Jain
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- AdventHealth Research Institute, Neuroscience Institute, Orlando, FL, 32804, USA
| | - Marc D Rudolph
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
| | - Jessica R Cohen
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
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11
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Ensel S, Uhrig L, Ozkirli A, Hoffner G, Tasserie J, Dehaene S, Van De Ville D, Jarraya B, Pirondini E. Transient brain activity dynamics discriminate levels of consciousness during anesthesia. Commun Biol 2024; 7:716. [PMID: 38858589 PMCID: PMC11164921 DOI: 10.1038/s42003-024-06335-x] [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: 10/20/2023] [Accepted: 05/15/2024] [Indexed: 06/12/2024] Open
Abstract
The awake mammalian brain is functionally organized in terms of large-scale distributed networks that are constantly interacting. Loss of consciousness might disrupt this temporal organization leaving patients unresponsive. We hypothesize that characterizing brain activity in terms of transient events may provide a signature of consciousness. For this, we analyze temporal dynamics of spatiotemporally overlapping functional networks obtained from fMRI transient activity across different anesthetics and levels of anesthesia. We first show a striking homology in spatial organization of networks between monkeys and humans, indicating cross-species similarities in resting-state fMRI structure. We then track how network organization shifts under different anesthesia conditions in macaque monkeys. While the spatial aspect of the networks is preserved, their temporal dynamics are highly affected by anesthesia. Networks express for longer durations and co-activate in an anesthetic-specific configuration. Additionally, hierarchical brain organization is disrupted with a consciousness-level-signature role of the default mode network. In conclusion, large-scale brain network temporal dynamics capture differences in anesthetic-specific consciousness-level, paving the way towards a clinical translation of these cortical signature.
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Affiliation(s)
- Scott Ensel
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lynn Uhrig
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Department of Anesthesiology and Critical Care, Necker Hospital, AP-HP, Université Paris Cité, Paris, France
| | - Ayberk Ozkirli
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Guylaine Hoffner
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
| | - Jordy Tasserie
- Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Stanislas Dehaene
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Collège de France, Paris, France
| | - Dimitri Van De Ville
- Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Béchir Jarraya
- NeuroSpin Center, Institute of BioImaging Commissariat à l'Energie Atomique, Gif/Yvette, France
- Cognitive Neuroimaging Unit, INSERM, U992, Gif/Yvette, France
- Université Paris-Saclay (UVSQ), Saclay, France
- Neuroscience Pole, Foch Hospital, Suresnes, France
| | - Elvira Pirondini
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
- Department of Physical Medicine & Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.
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12
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Chung S, Bacon T, Rath JF, Alivar A, Coelho S, Amorapanth P, Fieremans E, Novikov DS, Flanagan SR, Bacon JH, Lui YW. Callosal Interhemispheric Communication in Mild Traumatic Brain Injury: A Mediation Analysis on WM Microstructure Effects. AJNR Am J Neuroradiol 2024; 45:788-794. [PMID: 38637026 DOI: 10.3174/ajnr.a8213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 01/27/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND AND PURPOSE Because the corpus callosum connects the left and right hemispheres and a variety of WM bundles across the brain in complex ways, damage to the neighboring WM microstructure may specifically disrupt interhemispheric communication through the corpus callosum following mild traumatic brain injury. Here we use a mediation framework to investigate how callosal interhemispheric communication is affected by WM microstructure in mild traumatic brain injury. MATERIALS AND METHODS Multishell diffusion MR imaging was performed on 23 patients with mild traumatic brain injury within 1 month of injury and 17 healthy controls, deriving 11 diffusion metrics, including DTI, diffusional kurtosis imaging, and compartment-specific standard model parameters. Interhemispheric processing speed was assessed using the interhemispheric speed of processing task (IHSPT) by measuring the latency between word presentation to the 2 hemivisual fields and oral word articulation. Mediation analysis was performed to assess the indirect effect of neighboring WM microstructures on the relationship between the corpus callosum and IHSPT performance. In addition, we conducted a univariate correlation analysis to investigate the direct association between callosal microstructures and IHSPT performance as well as a multivariate regression analysis to jointly evaluate both callosal and neighboring WM microstructures in association with IHSPT scores for each group. RESULTS Several significant mediators in the relationships between callosal microstructure and IHSPT performance were found in healthy controls. However, patients with mild traumatic brain injury appeared to lose such normal associations when microstructural changes occurred compared with healthy controls. CONCLUSIONS This study investigates the effects of neighboring WM microstructure on callosal interhemispheric communication in healthy controls and patients with mild traumatic brain injury, highlighting that neighboring noncallosal WM microstructures are involved in callosal interhemispheric communication and information transfer. Further longitudinal studies may provide insight into the temporal dynamics of interhemispheric recovery following mild traumatic brain injury.
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Affiliation(s)
- Sohae Chung
- From the Department of Radiology (S. Chung, A.A., S. Coelho, E.F., D.S.N., Y.W.L.), Center for Advanced Imaging Innovation and Research, NY University Grossman School of Medicine, New York, New York
- Department of Radiology (S. Chung, A.A., S. Coehlo, E.F., D.S.N., Y.W.L.), Bernard and Irene Schwartz Center for Biomedical Imaging, NY University Grossman School of Medicine, New York, New York
| | - Tamar Bacon
- Department of Neurology (T.B., J.H.B.), NY University Grossman School of Medicine, New York, New York
| | - Joseph F Rath
- Department of Rehabilitation Medicine (J.F.R., P.A., S.R.F.), New York University Grossman School of Medicine, New York, New York
| | - Alaleh Alivar
- From the Department of Radiology (S. Chung, A.A., S. Coelho, E.F., D.S.N., Y.W.L.), Center for Advanced Imaging Innovation and Research, NY University Grossman School of Medicine, New York, New York
- Department of Radiology (S. Chung, A.A., S. Coehlo, E.F., D.S.N., Y.W.L.), Bernard and Irene Schwartz Center for Biomedical Imaging, NY University Grossman School of Medicine, New York, New York
| | - Santiago Coelho
- From the Department of Radiology (S. Chung, A.A., S. Coelho, E.F., D.S.N., Y.W.L.), Center for Advanced Imaging Innovation and Research, NY University Grossman School of Medicine, New York, New York
- Department of Radiology (S. Chung, A.A., S. Coehlo, E.F., D.S.N., Y.W.L.), Bernard and Irene Schwartz Center for Biomedical Imaging, NY University Grossman School of Medicine, New York, New York
| | - Prin Amorapanth
- Department of Rehabilitation Medicine (J.F.R., P.A., S.R.F.), New York University Grossman School of Medicine, New York, New York
| | - Els Fieremans
- From the Department of Radiology (S. Chung, A.A., S. Coelho, E.F., D.S.N., Y.W.L.), Center for Advanced Imaging Innovation and Research, NY University Grossman School of Medicine, New York, New York
- Department of Radiology (S. Chung, A.A., S. Coehlo, E.F., D.S.N., Y.W.L.), Bernard and Irene Schwartz Center for Biomedical Imaging, NY University Grossman School of Medicine, New York, New York
| | - Dmitry S Novikov
- From the Department of Radiology (S. Chung, A.A., S. Coelho, E.F., D.S.N., Y.W.L.), Center for Advanced Imaging Innovation and Research, NY University Grossman School of Medicine, New York, New York
- Department of Radiology (S. Chung, A.A., S. Coehlo, E.F., D.S.N., Y.W.L.), Bernard and Irene Schwartz Center for Biomedical Imaging, NY University Grossman School of Medicine, New York, New York
| | - Steven R Flanagan
- Department of Rehabilitation Medicine (J.F.R., P.A., S.R.F.), New York University Grossman School of Medicine, New York, New York
| | - Joshua H Bacon
- Department of Neurology (T.B., J.H.B.), NY University Grossman School of Medicine, New York, New York
| | - Yvonne W Lui
- From the Department of Radiology (S. Chung, A.A., S. Coelho, E.F., D.S.N., Y.W.L.), Center for Advanced Imaging Innovation and Research, NY University Grossman School of Medicine, New York, New York
- Department of Radiology (S. Chung, A.A., S. Coehlo, E.F., D.S.N., Y.W.L.), Bernard and Irene Schwartz Center for Biomedical Imaging, NY University Grossman School of Medicine, New York, New York
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13
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Nusbaum F, Hannoun S, Barile B, Suprano I, Mouchet S, Sappey-Marinier D. Personal Income Performance Correlates with Brain Structural Network Modularity but Not Intelligence Quotient. Brain Connect 2024. [PMID: 38848246 DOI: 10.1089/brain.2023.0077] [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: 06/09/2024] Open
Abstract
Introduction: This study aims to use diffusion tensor imaging (DTI) in conjunction with brain graph techniques to define brain structural connectivity and investigate its association with personal income (PI) in individuals of various ages and intelligence quotients (IQ). Methods: MRI examinations were performed on 55 male subjects (mean age: 40.1 ± 9.4 years). Graph data and metrics were generated, and DTI images were analyzed using tract-based spatial statistics (TBSS). All subjects underwent the Wechsler Adult Intelligence Scale for a reliable estimation of the full-scale IQ (FSIQ), which includes verbal comprehension index, perceptual reasoning index, working memory index, and processing speed index. The performance score was defined as the monthly PI normalized by the age of the subject. Results: The analysis of global graph metrics showed that modularity correlated positively with performance score (p = 0.003) and negatively with FSIQ (p = 0.04) and processing speed index (p = 0.005). No significant correlations were found between IQ indices and performance scores. Regional analysis of graph metrics showed modularity differences between right and left networks in sub-cortical (p = 0.001) and frontal (p = 0.044) networks. TBSS analysis showed greater axial and mean diffusivities in the high-performance group in correlation with their modular brain organization. Conclusion: This study showed that PI performance is strongly correlated with a modular organization of brain structural connectivity, which implies short and rapid networks, providing automatic and unconscious brain processing. Additionally, the lack of correlation between performance and IQ suggests a reduced role of academic reasoning skills in performance to the advantage of high uncertainty decision-making networks.
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Affiliation(s)
- Fanny Nusbaum
- Health Systemic Process (P2S), UR 4129, Université Claude Bernard-Lyon 1, Université de Lyon, Lyon, France
| | - Salem Hannoun
- Medical Imaging Sciences Program, Division of Health Professions, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Berardino Barile
- CREATIS, CNRS UMR 5220, INSERM U1294, Université Claude Bernard-Lyon1, INSA-Lyon, Université de Lyon, Villeurbanne, France
| | - Ilaria Suprano
- CREATIS, CNRS UMR 5220, INSERM U1294, Université Claude Bernard-Lyon1, INSA-Lyon, Université de Lyon, Villeurbanne, France
| | - Sabine Mouchet
- Service de Psychiatrie Légale - Pôle Santé Mentale des Détenus et Psychiatrie Légale, Centre Hospitalier le Vinatier, Bron, France
| | - Dominique Sappey-Marinier
- CREATIS, CNRS UMR 5220, INSERM U1294, Université Claude Bernard-Lyon1, INSA-Lyon, Université de Lyon, Villeurbanne, France
- CERMEP-Imagerie du Vivant, Université de Lyon, Bron, France
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14
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Sundermann B, Pfleiderer B, McLeod A, Mathys C. Seeing more than the Tip of the Iceberg: Approaches to Subthreshold Effects in Functional Magnetic Resonance Imaging of the Brain. Clin Neuroradiol 2024:10.1007/s00062-024-01422-2. [PMID: 38842737 DOI: 10.1007/s00062-024-01422-2] [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: 10/23/2023] [Accepted: 05/05/2024] [Indexed: 06/07/2024]
Abstract
Many functional magnetic resonance imaging (fMRI) studies and presurgical mapping applications rely on mass-univariate inference with subsequent multiple comparison correction. Statistical results are frequently visualized as thresholded statistical maps. This approach has inherent limitations including the risk of drawing overly-selective conclusions based only on selective results passing such thresholds. This article gives an overview of both established and newly emerging scientific approaches to supplement such conventional analyses by incorporating information about subthreshold effects with the aim to improve interpretation of findings or leverage a wider array of information. Topics covered include neuroimaging data visualization, p-value histogram analysis and the related Higher Criticism approach for detecting rare and weak effects. Further examples from multivariate analyses and dedicated Bayesian approaches are provided.
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Affiliation(s)
- Benedikt Sundermann
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany.
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
- Clinic of Radiology, Medical Faculty, University of Münster, Münster, Germany.
| | - Bettina Pfleiderer
- Clinic of Radiology, Medical Faculty, University of Münster, Münster, Germany
| | - Anke McLeod
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany
| | - Christian Mathys
- Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus Oldenburg, Universitätsmedizin Oldenburg, Steinweg 13-17, 26122, Oldenburg, Germany
- Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
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15
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Hocking MC, Schultz RT, Yerys BE, Minturn JE, Fantozzi P, Herrington JD. White matter connectivity and social functioning in survivors of pediatric brain tumor. J Neurooncol 2024:10.1007/s11060-024-04724-0. [PMID: 38837018 DOI: 10.1007/s11060-024-04724-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 05/25/2024] [Indexed: 06/06/2024]
Abstract
OBJECTIVE Survivors of pediatric brain tumors (SPBT) are at risk for social deficits, fewer friendships, and poor peer relations. SPBT also experience reduced brain connectivity via microstructural disruptions to white matter from neurological insults. Research with other populations implicates white matter connectivity as a key contributor to poor social functioning. This case-controlled diffusion-weighted imaging study evaluated structural connectivity in SPBT and typically developing controls (TDC) and associations between metrics of connectivity and social functioning. METHODS Diffusion weighted-imaging results from 19 SPBT and 19 TDC were analyzed using probabilistic white matter tractography. Survivors were at least 5 years post-diagnosis and 2 years off treatment. Graph theory statistics measured group differences across several connectivity metrics, including average strength, global efficiency, assortativity, clustering coefficient, modularity, and betweenness centrality. Analyses also evaluated the effects of neurological risk on connectivity among SPBT. Correlational analyses evaluated associations between connectivity and indices of social behavior. RESULTS SPBT demonstrated reduced global connectivity compared to TDC. Several medical factors (e.g., chemotherapy, recurrence, multimodal therapy) were related to decreased connectivity across metrics of integration (e.g., average strength, global efficiency) in SPBT. Connectivity metrics were related to peer relationship quality and social challenges in the SPBT group and to social challenges in the total sample. CONCLUSIONS Microstructural white matter connectivity is diminished in SPBT and related to neurological risk and peer relationship quality. Additional neuroimaging research is needed to evaluate associations between brain connectivity metrics and social functioning in SPBT.
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Affiliation(s)
- Matthew C Hocking
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- The University of Pennsylvania, Philadelphia, PA, USA.
| | - Robert T Schultz
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin E Yerys
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The University of Pennsylvania, Philadelphia, PA, USA
| | - Jane E Minturn
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The University of Pennsylvania, Philadelphia, PA, USA
| | - Peter Fantozzi
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - John D Herrington
- The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The University of Pennsylvania, Philadelphia, PA, USA
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16
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Lam HW, Patodia S, Zeicu C, Lim YM, Mrzyglod A, Scott C, Oliveira J, De Tisi J, Legouhy A, Zhang H, Koepp M, Diehl B, Thom M. Quantitative cellular pathology of the amygdala in temporal lobe epilepsy and correlation with magnetic resonance imaging volumetry, tissue microstructure, and sudden unexpected death in epilepsy risk factors. Epilepsia 2024. [PMID: 38837385 DOI: 10.1111/epi.18033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 05/18/2024] [Accepted: 05/20/2024] [Indexed: 06/07/2024]
Abstract
OBJECTIVE Amygdala enlargement can occur in temporal lobe epilepsy, and increased amygdala volume is also reported in sudden unexpected death in epilepsy (SUDEP). Apnea can be induced by amygdala stimulation, and postconvulsive central apnea (PCCA) and generalized seizures are both known SUDEP risk factors. Neurite orientation dispersion and density imaging (NODDI) has recently provided additional information on altered amygdala microstructure in SUDEP. In a series of 24 surgical temporal lobe epilepsy cases, our aim was to quantify amygdala cellular pathology parameters that could predict enlargement, NODDI changes, and ictal respiratory dysfunction. METHODS Using whole slide scanning automated quantitative image analysis methods, parallel evaluation of myelin, axons, dendrites, oligodendroglia, microglia, astroglia, neurons, serotonergic networks, mTOR-pathway activation (pS6) and phosphorylated tau (pTau; AT8, AT100, PHF) in amygdala, periamygdala cortex, and white matter regions of interest were compared with preoperative magnetic resonance imaging data on amygdala size, and in 13 cases with NODDI and evidence of ictal-associated apnea. RESULTS We observed significantly higher glial labeling (Iba1, glial fibrillary acidic protein, Olig2) in amygdala regions compared to cortex and a strong positive correlation between Olig2 and Iba1 in the amygdala. Larger amygdala volumes correlated with lower microtubule-associated protein (MAP2), whereas higher NODDI orientation dispersion index correlated with lower Olig2 cell densities. In the three cases with recorded PCCA, higher MAP2 and pS6-235 expression was noted than in those without. pTau did not correlate with SUDEP risk factors, including seizure frequency. SIGNIFICANCE Histological quantitation of amygdala microstructure can shed light on enlargement and diffusion imaging alterations in epilepsy to explore possible mechanisms of amygdala dysfunction, including mTOR pathway activation, that in turn may increase the risk for SUDEP.
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Affiliation(s)
- Hou Wang Lam
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Smriti Patodia
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Claudia Zeicu
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Yau Mun Lim
- Division of Neuropathology, UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
| | - Alicja Mrzyglod
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Catherine Scott
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
| | - Joana Oliveira
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
| | - Jane De Tisi
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Antoine Legouhy
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Hui Zhang
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Matthias Koepp
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
| | - Beate Diehl
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
- Department of Clinical Neurophysiology, National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
| | - Maria Thom
- Department of Clinical and Experimental Epilepsy, University College London (UCL) Queen Square Institute of Neurology, London, UK
- Division of Neuropathology, UCL Queen Square Institute of Neurology and National Hospital for Neurology and Neurosurgery, University College Hospitals NHS Foundation Trust, London, UK
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17
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Ito A, Yang S, Shinto E, Shinto A, Toyofuku A, Kurata J. Interhemispheric and Corticothalamic White-Matter Dysfunction Underlies Affective Morbidity and Impaired Pain Modulation in Chronic Pain. Anesth Analg 2024:00000539-990000000-00827. [PMID: 38837907 DOI: 10.1213/ane.0000000000006992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
BACKGROUND Although patients with chronic pain show behavioral signs of impaired endogenous pain modulation, responsible cerebral networks have yet to be anatomically delineated. We used diffusion tensor imaging (DTI) to examine the white-matter alterations in patients with chronic pain compared with healthy subjects. We further measured thermal pain modulatory responses using the offset analgesia (OA) paradigm. We tested whether the white-matter indices be associated with psychophysical parameters reflecting morbidity and modulatory responses of pain in patients, and whether they could serve as diagnostic biomarkers of chronic pain. METHODS Twenty-six patients with chronic pain and 18 age- and gender-matched healthy controls were enrolled. After completing psychophysical questionnaires, they underwent OA measurement and whole-brain DTI in a 3 Tesla magnetic resonance imaging scanner. Fractional anisotropy (FA) and radial diffusivity (RD) of the white-matter were computed and compared between the groups with tract-based spatial statistics using the FMRIB Software Library (FSL) software. Correlations were sought among white-matter indices, thermal pain responses, and psychophysical parameters. The white-matter indices and OA-related parameters were tested whether they distinguish patients from controls by receiver operating characteristic analysis. RESULTS During OA, patients showed a shorter latency to the maximum (maximum visual analog scale [VAS] latency, 16.0 ± 3.7 vs 18.9 ± 3.1 second [mean ± standard deviation, SD]; P = .032) but a longer latency to the minimum pain (OA latency, 15.6 ± 3.5 vs 11.1 ± 4.2 seconds; P = .004) than controls. They showed a smaller mean FA (0.44 ± 0.12 vs 0.45 ± 0.11; P = .012) and a larger mean RD of the global white-matter (0.00057 ± 0.00002 vs 0.00056 ± 0.00002; P = .038) than controls, at specific areas including the corpus callosum, anterior thalamic radiation, and forceps major. FA of the splenium of the corpus callosum was associated with maximum VAS latency (r = 0.493) and OA latency (r = -0.552). The Pain Catastrophizing Scale scores showed strong negative correlations with FA across those specific areas (r = -0.405). Those latencies during OA and white-matter metrics distinguished patients from controls (P < .05). CONCLUSIONS Patients with chronic pain showed dysfunction of the white matter concerned with interhemispheric communication of sensorimotor information as well as descending corticothalamic modulation of pain in association with affective morbidity and altered temporal dynamics of pain perception. We suggest that an impaired interhemispheric modulation of pain, through the corpus callosum, might be a novel cerebral mechanism in chronification of pain.
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Affiliation(s)
- Atsushi Ito
- From the Department of Psychosomatic Dentistry, Tokyo Medical and Dental University Graduate School of Medical and Dental Sciences, Tokyo, Japan
| | - Sushuang Yang
- Department of Anesthesiology, Jikei University Graduate School of Medicine, Tokyo, Japan
| | - Eri Shinto
- Department of Anesthesiology, Jikei University Graduate School of Medicine, Tokyo, Japan
| | - Atsushi Shinto
- Department of Anesthesiology, Keio University Graduate School of Medicine, Tokyo, Japan
| | - Akira Toyofuku
- From the Department of Psychosomatic Dentistry, Tokyo Medical and Dental University Graduate School of Medical and Dental Sciences, Tokyo, Japan
| | - Jiro Kurata
- From the Department of Psychosomatic Dentistry, Tokyo Medical and Dental University Graduate School of Medical and Dental Sciences, Tokyo, Japan
- Department of Anesthesiology, Jikei University Graduate School of Medicine, Tokyo, Japan
- Department of Anesthesiology, Keio University Graduate School of Medicine, Tokyo, Japan
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18
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Pinho AL, Richard H, Ponce AF, Eickenberg M, Amadon A, Dohmatob E, Denghien I, Torre JJ, Shankar S, Aggarwal H, Thual A, Chapalain T, Ginisty C, Becuwe-Desmidt S, Roger S, Lecomte Y, Berland V, Laurier L, Joly-Testault V, Médiouni-Cloarec G, Doublé C, Martins B, Varoquaux G, Dehaene S, Hertz-Pannier L, Thirion B. Individual Brain Charting dataset extension, third release for movie watching and retinotopy data. Sci Data 2024; 11:590. [PMID: 38839770 PMCID: PMC11153490 DOI: 10.1038/s41597-024-03390-1] [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: 11/21/2023] [Accepted: 05/20/2024] [Indexed: 06/07/2024] Open
Abstract
The Individual Brain Charting (IBC) is a multi-task functional Magnetic Resonance Imaging dataset acquired at high spatial-resolution and dedicated to the cognitive mapping of the human brain. It consists in the deep phenotyping of twelve individuals, covering a broad range of psychological domains suitable for functional-atlasing applications. Here, we present the inclusion of task data from both naturalistic stimuli and trial-based designs, to uncover structures of brain activation. We rely on the Fast Shared Response Model (FastSRM) to provide a data-driven solution for modelling naturalistic stimuli, typically containing many features. We show that data from left-out runs can be reconstructed using FastSRM, enabling the extraction of networks from the visual, auditory and language systems. We also present the topographic organization of the visual system through retinotopy. In total, six new tasks were added to IBC, wherein four trial-based retinotopic tasks contributed with a mapping of the visual field to the cortex. IBC is open access: source plus derivatives imaging data and meta-data are available in public repositories.
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Affiliation(s)
- Ana Luísa Pinho
- Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France.
- Department of Computer Science, Western University, London, Ontario, Canada.
- Western Centre for Brain and Mind, Western University, London, Ontario, Canada.
| | - Hugo Richard
- Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France
- Criteo AI Labs, Paris, France
- FAIRPLAY - IA coopérative: équité, vie privée, incitations, Paris, France
| | | | - Michael Eickenberg
- Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France
- Flatiron Institute, New York, USA
| | - Alexis Amadon
- Université Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, 91191, Gif-sur-Yvette, France
| | - Elvis Dohmatob
- Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France
- Meta FAIR, Paris, France
| | - Isabelle Denghien
- Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin center, 91191, Gif-sur-Yvette, France
| | | | - Swetha Shankar
- Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France
| | | | - Alexis Thual
- Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France
- Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin center, 91191, Gif-sur-Yvette, France
- Collège de France, Paris, France
| | | | | | | | | | - Yann Lecomte
- CEA Saclay/DRF/IFJ/NeuroSpin/UNIACT, Paris, France
| | | | | | | | | | | | | | - Gaël Varoquaux
- Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France
| | - Stanislas Dehaene
- Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay, NeuroSpin center, 91191, Gif-sur-Yvette, France
- Collège de France, Paris, France
| | - Lucie Hertz-Pannier
- CEA Saclay/DRF/IFJ/NeuroSpin/UNIACT, Paris, France
- UMR 1141, NeuroDiderot, Université de Paris, Paris, France
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19
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Monti MM. The subcortical basis of subjective sleep quality. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.29.596530. [PMID: 38854024 PMCID: PMC11160773 DOI: 10.1101/2024.05.29.596530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Study objectives To assess the association between self-reported sleep quality and cortical and subcortical local morphometry. Methods Sleep and neuroanatomical data from the full release of the young adult Human Connectome Project dataset were analyzed. Sleep quality was operationalized with the Pittsburgh Sleep Quality Index (PSQI). Local cortical and subcortical morphometry was measured with subject-specific segmentations resulting in voxelwise thickness measurements for cortex and relative (i.e., cross-sectional) local atrophy measurements for subcortical regions. Results Relative atrophy across several subcortical regions, including bilateral pallidum, striatum, and thalamus, was negatively associated with both global PSQI score and sub-components of the index related to sleep duration, efficiency, and quality. Conversely, we found no association between cortical morphometric measurements and self-reported sleep quality. Conclusions This work shows that subcortical regions such as the bilateral pallidum, thalamus, and striatum, might be interventional targets to ameliorate self-reported sleep quality.
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Affiliation(s)
- Martin M. Monti
- Department of Psychology, University of California Los Angeles, 502 Portola Plaza, Los Angeles, 90095, CA, USA
- Brain Injury Research Center (BIRC), Department of Neurosurgery, University of California Los Angeles, 300 Stein Plaza Driveway, Los Angeles, 90095, CA, USA
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20
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Fiscone C, Sighinolfi G, Manners DN, Motta L, Venturi G, Panzera I, Zaccagna F, Rundo L, Lugaresi A, Lodi R, Tonon C, Castelli M. Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis. Sci Data 2024; 11:575. [PMID: 38834674 DOI: 10.1038/s41597-024-03418-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 05/24/2024] [Indexed: 06/06/2024] Open
Abstract
Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific lesions. Quantitative MRI techniques are capable of quantifying imaging biomarkers in vivo, offering the potential to identify specific signs related to pre-clinical inflammation. Among those techniques, Quantitative Susceptibility Mapping (QSM) is particularly useful for studying processes that influence the magnetic properties of brain tissue, such as alterations in myelin concentration. Because of its intrinsic quantitative nature, it is particularly well-suited to be analyzed through radiomics, including techniques that extract a high number of complex and multi-dimensional features from radiological images. The dataset presented in this work provides information about normal-appearing white matter (NAWM) in a cohort of MS patients and healthy controls. It includes QSM-based radiomic features from NAWM and its tracts, and MR sequences necessary to implement the pipeline: T1w, T2w, QSM, DWI. The workflow is outlined in this article, along with an application showing feature reliability assessment.
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Affiliation(s)
- Cristiana Fiscone
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Giovanni Sighinolfi
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - David Neil Manners
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
- Department for Life Quality Sciences, University of Bologna, Bologna, Italy.
| | - Lorenzo Motta
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Greta Venturi
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Ivan Panzera
- UOSI Riabilitazione Sclerosi Multipla, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Fulvio Zaccagna
- Department of Imaging, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
- Investigative Medicine Division, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Leonardo Rundo
- Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano, Italy
| | - Alessandra Lugaresi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- UOSI Riabilitazione Sclerosi Multipla, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Raffaele Lodi
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Caterina Tonon
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Mauro Castelli
- NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Campus de Campolide, 1070-312, Lisbon, Portugal
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21
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Goldstein-Marcusohn Y, Asaad R, Asaad L, Freud E. The large-scale organization of shape processing in the ventral and dorsal pathways is dissociable from attention. Cereb Cortex 2024; 34:bhae221. [PMID: 38832533 PMCID: PMC11148664 DOI: 10.1093/cercor/bhae221] [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: 01/24/2024] [Revised: 05/02/2024] [Accepted: 05/09/2024] [Indexed: 06/05/2024] Open
Abstract
The two visual pathways model posits that visual information is processed through two distinct cortical systems: The ventral pathway promotes visual recognition, while the dorsal pathway supports visuomotor control. Recent evidence suggests the dorsal pathway is also involved in shape processing and may contribute to object perception, but it remains unclear whether this sensitivity is independent of attentional mechanisms that were localized to overlapping cortical regions. To address this question, we conducted two fMRI experiments that utilized different parametric scrambling manipulations in which human participants viewed novel objects in different levels of scrambling and were instructed to attend to either the object or to another aspect of the image (e.g. color of the background). Univariate and multivariate analyses revealed that the large-scale organization of shape selectivity along the dorsal and ventral pathways was preserved regardless of the focus of attention. Attention did modulate shape sensitivity, but these effects were similar across the two pathways. These findings support the idea that shape processing is at least partially dissociable from attentional processes and relies on a distributed set of cortical regions across the visual pathways.
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Affiliation(s)
- Yael Goldstein-Marcusohn
- Department of Psychology and the Centre for Vision Research, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
| | - Rahaf Asaad
- Department of Psychology and the Centre for Vision Research, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
| | - Leen Asaad
- Department of Psychology and the Centre for Vision Research, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
| | - Erez Freud
- Department of Psychology and the Centre for Vision Research, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
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22
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Wearn A, Tremblay SA, Tardif CL, Leppert IR, Gauthier CJ, Baracchini G, Hughes C, Hewan P, Tremblay-Mercier J, Rosa-Neto P, Poirier J, Villeneuve S, Schmitz TW, Turner GR, Spreng RN. Neuromodulatory subcortical nucleus integrity is associated with white matter microstructure, tauopathy and APOE status. Nat Commun 2024; 15:4706. [PMID: 38830849 PMCID: PMC11148077 DOI: 10.1038/s41467-024-48490-z] [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: 11/29/2023] [Accepted: 05/01/2024] [Indexed: 06/05/2024] Open
Abstract
The neuromodulatory subcortical nuclei within the isodendritic core (IdC) are the earliest sites of tauopathy in Alzheimer's disease (AD). They project broadly throughout the brain's white matter. We investigated the relationship between IdC microstructure and whole-brain white matter microstructure to better understand early neuropathological changes in AD. Using multiparametric quantitative magnetic resonance imaging we observed two covariance patterns between IdC and white matter microstructure in 133 cognitively unimpaired older adults (age 67.9 ± 5.3 years) with familial risk for AD. IdC integrity related to 1) whole-brain neurite density, and 2) neurite orientation dispersion in white matter tracts known to be affected early in AD. Pattern 2 was associated with CSF concentration of phosphorylated-tau, indicating AD specificity. Apolipoprotein-E4 carriers expressed both patterns more strongly than non-carriers. IdC microstructure variation is reflected in white matter, particularly in AD-affected tracts, highlighting an early mechanism of pathological development.
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Affiliation(s)
- Alfie Wearn
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, QC, Canada.
| | - Stéfanie A Tremblay
- Department of Physics, Concordia University, Montreal, H4B 1R6, QC, Canada
- Montreal Heart Institute, Montreal, H1T 1C8, QC, Canada
- School of Health, Concordia University, Montreal, H4B 1R6, QC, Canada
| | - Christine L Tardif
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, H3A 2B4, QC, Canada
- Department of Biomedical Engineering, McGill University, McGill, H3A 2B4, QC, Canada
| | - Ilana R Leppert
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, H3A 2B4, QC, Canada
| | - Claudine J Gauthier
- Department of Physics, Concordia University, Montreal, H4B 1R6, QC, Canada
- Montreal Heart Institute, Montreal, H1T 1C8, QC, Canada
- School of Health, Concordia University, Montreal, H4B 1R6, QC, Canada
| | - Giulia Baracchini
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, QC, Canada
| | - Colleen Hughes
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, QC, Canada
| | - Patrick Hewan
- Department of Psychology, York University, Toronto, M3J 1P3, ON, Canada
| | | | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, H3A 2B4, QC, Canada
- Douglas Mental Health University Institute-Research Center, Verdun, H4H 1R3, QC, Canada
| | - Judes Poirier
- Douglas Mental Health University Institute-Research Center, Verdun, H4H 1R3, QC, Canada
- Department of Psychiatry, McGill University, Montreal, H3A 1A1, QC, Canada
| | - Sylvia Villeneuve
- McConnell Brain Imaging Centre, McGill University, Montreal, H3A 2B4, QC, Canada
- Douglas Mental Health University Institute-Research Center, Verdun, H4H 1R3, QC, Canada
- Department of Psychiatry, McGill University, Montreal, H3A 1A1, QC, Canada
| | - Taylor W Schmitz
- Department of Physiology & Pharmacology, Western Institute for Neuroscience, Western University, London, N6A 5C1, ON, Canada
| | - Gary R Turner
- Department of Psychology, York University, Toronto, M3J 1P3, ON, Canada
| | - R Nathan Spreng
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, H3A 2B4, QC, Canada.
- McConnell Brain Imaging Centre, McGill University, Montreal, H3A 2B4, QC, Canada.
- Douglas Mental Health University Institute-Research Center, Verdun, H4H 1R3, QC, Canada.
- Department of Psychiatry, McGill University, Montreal, H3A 1A1, QC, Canada.
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23
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Aleksic S, Fleysher R, Weiss EF, Tal N, Darby T, Blumen HM, Vazquez J, Ye KQ, Gao T, Siegel SM, Barzilai N, Lipton ML, Milman S. Hypothalamic MRI-derived microstructure is associated with neurocognitive aging in humans. Neurobiol Aging 2024; 141:102-112. [PMID: 38850591 DOI: 10.1016/j.neurobiolaging.2024.05.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 05/17/2024] [Accepted: 05/31/2024] [Indexed: 06/10/2024]
Abstract
The hypothalamus regulates homeostasis across the lifespan and is emerging as a regulator of aging. In murine models, aging-related changes in the hypothalamus, including microinflammation and gliosis, promote accelerated neurocognitive decline. We investigated relationships between hypothalamic microstructure and features of neurocognitive aging, including cortical thickness and cognition, in a cohort of community-dwelling older adults (age range 65-97 years, n=124). Hypothalamic microstructure was evaluated with two magnetic resonance imaging diffusion metrics: mean diffusivity (MD) and fractional anisotropy (FA), using a novel image processing pipeline. Hypothalamic MD was cross-sectionally positively associated with age and it was negatively associated with cortical thickness. Hypothalamic FA, independent of cortical thickness, was cross-sectionally positively associated with neurocognitive scores. An exploratory analysis of longitudinal neurocognitive performance suggested that lower hypothalamic FA may predict cognitive decline. No associations between hypothalamic MD, age, and cortical thickness were identified in a younger control cohort (age range 18-63 years, n=99). To our knowledge, this is the first study to demonstrate that hypothalamic microstructure is associated with features of neurocognitive aging in humans.
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Affiliation(s)
- Sandra Aleksic
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States.
| | - Roman Fleysher
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States; Department of Radiology, Albert Einstein College of Medicine, Gruss Magnetic Resonance Research Center, Bronx, NY, United States
| | - Erica F Weiss
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Noa Tal
- Department of Medicine, Cedars-Sinai, Los Angeles, CA, United States
| | - Timothy Darby
- Albert Einstein College of Medicine, Bronx, NY, United States
| | - Helena M Blumen
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Juan Vazquez
- Department of Internal Medicine, John Hopkins University, Baltimore, MD, United States
| | - Kenny Q Ye
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Tina Gao
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Shira M Siegel
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States
| | - Nir Barzilai
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Michael L Lipton
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States; Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Sofiya Milman
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, United States
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24
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Lapucci C, Boccia VD, Clementi TD, Schiavi S, Benedetti L, Uccelli A, Novi G, Cellerino M, Inglese M. Brain lesion microstructure in neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein disease. J Neuroimaging 2024. [PMID: 38831519 DOI: 10.1111/jon.13218] [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: 04/17/2024] [Revised: 05/20/2024] [Accepted: 05/21/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND AND PURPOSE Neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) diagnosis are based on the presence of serological and magnetic resonance imaging (MRI) biomarkers. Diffusion tensor imaging (DTI), neurites orientation dispersion and density imaging (NODDI), and the Spherical Mean Technique (SMT) may be helpful to provide a microstructural characterization of the different types of white matter lesions and give an insight about their different pathological mechanisms. The aim of the study was to characterize microstructural differences between brain typical lesions (TLs) and nontypical lesions (nTLs). METHODS A total of 17 NMOSD and MOGAD patients [9 Aquaporin4 (AQP4) + NMO, 2 seronegative-NMO, 6 MOGAD] underwent MRI scans on a 3 Tesla MAGNETON PRISMA. Diffusion parameters (fractional anisotropy; mean diffusivity [MD]; intracellular volume fraction [ICVF]; extra-neurite transverse diffusivity; and extra-neurite MD; neurite signal fraction) were obtained using DTI, NODDI, and SMT. Microstructural parameters within lesions were compared through a generalized linear model using age, sex, and total lesion volume as covariates. RESULTS In NMOSD/MOGAD whole cohort (total lesions = 477), TLs showed increased MD and decreased ICVF compared to nTLs (p < .05), indicating higher inflammation and axonal loss. Similar results were found also in the AQP4 + NMO subgroup (decreased ICVF, p < .05). Furthermore, in NMOSD/MOGAD whole cohort and in AQP4 + NMO subgroup, TLs showed a trend toward higher EXRATRANS than nTLs, suggesting a more severe degree of demyelination within TLs. CONCLUSIONS TLs and nTLs in NMOSD/MOGAD showed different diffusion MRI-derived microstructural features, with TLs showing a more severe degree of inflammation and fiber disruption with respect to nTLs.
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Affiliation(s)
| | - Vincenzo Daniele Boccia
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Thoma Dario Clementi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | | | - Antonio Uccelli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Giovanni Novi
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Maria Cellerino
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Matilde Inglese
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
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25
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Alshehri A, Koussis N, Al-Iedani O, Khormi I, Lea R, Ramadan S, Lechner-Scott J. Improvement of the thalamocortical white matter network in people with stable treated relapsing-remitting multiple sclerosis over time. NMR IN BIOMEDICINE 2024; 37:e5119. [PMID: 38383137 DOI: 10.1002/nbm.5119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 12/28/2023] [Accepted: 01/18/2024] [Indexed: 02/23/2024]
Abstract
Advanced imaging techniques (tractography) enable the mapping of white matter (WM) pathways and the understanding of brain connectivity patterns. We combined tractography with a network-based approach to examine WM microstructure on a network level in people with relapsing-remitting multiple sclerosis (pw-RRMS) and healthy controls (HCs) over 2 years. Seventy-six pw-RRMS matched with 43 HCs underwent clinical assessments and 3T MRI scans at baseline (BL) and 2-year follow-up (2-YFU). Probabilistic tractography was performed, accounting for the effect of lesions, producing connectomes of 25 million streamlines. Network differences in fibre density across pw-RRMS and HCs at BL and 2-YFU were quantified using network-based statistics (NBS). Longitudinal network differences in fibre density were quantified using NBS in pw-RRMS, and were tested for correlations with disability, cognition and fatigue scores. Widespread network reductions in fibre density were found in pw-RRMS compared with HCs at BL in cortical regions, with more reductions detected at 2-YFU. Pw-RRMS had reduced fibre density at BL in the thalamocortical network compared to 2-YFU. This effect appeared after correction for age, was robust across different thresholds, and did not correlate with lesion volume or disease duration. Pw-RRMS demonstrated a robust and long-distance improvement in the thalamocortical WM network, regardless of age, disease burden, duration or therapy, suggesting a potential locus of neuroplasticity in MS. This network's role over the disease's lifespan and its potential implications in prognosis and treatment warrants further investigation.
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Affiliation(s)
- Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Department of Radiology, King Fahd University Hospital, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Nikitas Koussis
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Psychological Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW, Australia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
| | - Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Rodney Lea
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Department of Neurology, John Hunter Hospital, New Lambton Heights, NSW, Australia
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW, Australia
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26
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Forbes E, Hassien A, Tan RJ, Wang D, Lega B. Modulation of hippocampal theta oscillations via deep brain stimulation of the parietal cortex depends on cognitive state. Cortex 2024; 175:28-40. [PMID: 38691923 DOI: 10.1016/j.cortex.2024.03.010] [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: 07/31/2023] [Revised: 12/07/2023] [Accepted: 03/24/2024] [Indexed: 05/03/2024]
Abstract
The angular gyrus (AG) and posterior cingulate cortex (PCC) demonstrate extensive structural and functional connectivity with the hippocampus and other core recollection network regions. Consequently, recent studies have explored neuromodulation targeting these and other regions as a potential strategy for restoring function in memory disorders such as Alzheimer's Disease. However, determining the optimal approach for neuromodulatory devices requires understanding how parameters like selected stimulation site, cognitive state during modulation, and stimulation duration influence the effects of deep brain stimulation (DBS) on electrophysiological features relevant to episodic memory. We report experimental data examining the effects of high-frequency stimulation delivered to the AG or PCC on hippocampal theta oscillations during the memory encoding (study) or retrieval (test) phases of an episodic memory task. Results showed selective enhancement of anterior hippocampal slow theta oscillations with stimulation of the AG preferentially during memory retrieval. Conversely, stimulation of the PCC attenuated slow theta oscillations. We did not observe significant behavioral effects in this (open-loop) stimulation experiment, suggesting that neuromodulation strategies targeting episodic memory performance may require more temporally precise stimulation approaches.
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Affiliation(s)
- Eugenio Forbes
- The University of Texas Southwestern Medical Center, Dallas, TX, United States.
| | - Alexa Hassien
- The University of Texas Southwestern Medical Center, Dallas, TX, United States.
| | - Ryan Joseph Tan
- The University of Texas Southwestern Medical Center, Dallas, TX, United States.
| | - David Wang
- The University of Texas Southwestern Medical Center, Dallas, TX, United States.
| | - Bradley Lega
- The University of Texas Southwestern Medical Center, Dallas, TX, United States.
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Bermudez C, Kerley CI, Ramadass K, Farber-Eger EH, Lin YC, Kang H, Taylor WD, Wells QS, Landman BA. Volumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia. Magn Reson Imaging 2024; 109:49-55. [PMID: 38430976 DOI: 10.1016/j.mri.2024.02.016] [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: 01/04/2023] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024]
Abstract
Heart failure with preserved ejection fraction (HFpEF) is an important, emerging risk factor for dementia, but it is not clear whether HFpEF contributes to a specific pattern of neuroanatomical changes in dementia. A major challenge to studying this is the relative paucity of datasets of patients with dementia, with/without HFpEF, and relevant neuroimaging. We sought to demonstrate the feasibility of using modern data mining tools to create and analyze clinical imaging datasets and identify the neuroanatomical signature of HFpEF-associated dementia. We leveraged the bioinformatics tools at Vanderbilt University Medical Center to identify patients with a diagnosis of dementia with and without comorbid HFpEF using the electronic health record. We identified high resolution, clinically-acquired neuroimaging data on 30 dementia patients with HFpEF (age 76.9 ± 8.12 years, 61% female) as well as 301 age- and sex-matched patients with dementia but without HFpEF to serve as comparators (age 76.2 ± 8.52 years, 60% female). We used automated image processing pipelines to parcellate the brain into 132 structures and quantify their volume. We found six regions with significant atrophy associated with HFpEF: accumbens area, amygdala, posterior insula, anterior orbital gyrus, angular gyrus, and cerebellar white matter. There were no regions with atrophy inversely associated with HFpEF. Patients with dementia and HFpEF have a distinct neuroimaging signature compared to patients with dementia only. Five of the six regions identified in are in the temporo-parietal region of the brain. Future studies should investigate mechanisms of injury associated with cerebrovascular disease leading to subsequent brain atrophy.
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Affiliation(s)
- Camilo Bermudez
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Cailey I Kerley
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Eric H Farber-Eger
- Department of Cardiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Ya-Chen Lin
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Warren D Taylor
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quinn S Wells
- Department of Cardiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Bennett A Landman
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN, USA.
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28
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Hechenberger S, Helmlinger B, Tinauer C, Jauk E, Ropele S, Heschl B, Wurth S, Damulina A, Eppinger S, Demjaha R, Khalil M, Enzinger C, Pinter D. Evaluation of a self-administered iPad ®-based processing speed assessment for people with multiple sclerosis in a clinical routine setting. J Neurol 2024; 271:3268-3278. [PMID: 38441609 PMCID: PMC11136781 DOI: 10.1007/s00415-024-12274-8] [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: 01/08/2024] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Limited resources often hinder regular cognitive assessment of people with multiple sclerosis (pwMS) in standard clinical care. A self-administered iPad®-based cognitive screening-tool (Processing Speed Test; PST) might mitigate this problem. OBJECTIVE To evaluate the PST in clinical routine. METHODS We investigated the feasibility of the PST in both a quiet and a waiting room setting. We assessed the validity of the PST in comparison with the established Symbol Digit Modalities Test (SDMT). We explored associations between processing speed assessments and the Brief International Cognitive Assessment for MS (BICAMS), magnetic resonance imaging (MRI) parameters, and psychological factors. Additionally, we explored the ability of the PST to detect impairment in processing speed compared to the SDMT. RESULTS The PST was feasible in the waiting room setting. PST and SDMT correlated comparably with the BICAMS, MRI parameters, and psychological variables. Of 172 pwMS, 50 (30.8%) showed cognitive impairment according to the BICAMS; respective values were 47 (27.3%) for the SDMT and 9 (5.2%) for the PST. CONCLUSIONS The PST performed in a waiting room setting correlates strongly with established cognitive tests. It thus may be used to assess processing speed in a resource-efficient manner and complement cognitive assessment in clinical routine. Despite comparable validity of the PST and SDMT, we identified more pwMS with impaired processing speed using normative data of the SDMT compared to the PST and advise caution, that the common cut-off score of - 1.5 SD from the current PST is not appropriate in Europe.
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Affiliation(s)
- Stefanie Hechenberger
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Birgit Helmlinger
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Emanuel Jauk
- Department of Medical Psychology, Psychosomatics, and Psychotherapy, Medical University of Graz, Graz, Austria
- Clinical Psychology and Behavioral Neuroscience, Technische Universität Dresden, Dresden, Germany
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Bettina Heschl
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Sebastian Wurth
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Anna Damulina
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Sebastian Eppinger
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Rina Demjaha
- Department of Neurology, Medical University of Graz, Graz, Austria
- Neurology Biomarker Research Unit, Medical University of Graz, Graz, Austria
| | - Michael Khalil
- Department of Neurology, Medical University of Graz, Graz, Austria
- Neurology Biomarker Research Unit, Medical University of Graz, Graz, Austria
| | - Christian Enzinger
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Daniela Pinter
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria.
- Department of Neurology, Medical University of Graz, Graz, Austria.
- Head of Research Unit for Neuronal Plasticity and Repair, Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036, Graz, Austria.
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Fan J, Woods KJ, Jacobson JL, Taylor PA, Toich JTF, Molteno CD, Jacobson SW, Meintjes EM. Lower resting state functional connectivity partially mediates adverse effects of prenatal alcohol exposure on arithmetic performance in children. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:1050-1062. [PMID: 38697927 DOI: 10.1111/acer.15332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 03/06/2024] [Accepted: 04/03/2024] [Indexed: 05/05/2024]
Abstract
BACKGROUND Fetal alcohol spectrum disorders (FASD) include a range of neurocognitive and behavioral impairments resulting from prenatal alcohol exposure (PAE). Among the PAE-related cognitive deficits, number processing is particularly affected. This study examines alterations in number processing networks and whether changes in functional connectivity mediate the adverse effects of PAE on arithmetic performance. METHODS Magnetic resonance imaging (MRI) was acquired in 57 children (mean (SD) age = 11.3 (+0.9) yr), 38 with FASD (19 fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 heavily exposed (HE)) and 19 controls. Whole-brain correlation analyses were performed from five seeds located in regions involved in number processing. RESULTS Children with FAS/PFAS showed dose-dependent reductions in resting state functional connectivity between the seed in the right (R) posterior superior parietal lobule and a cluster in the left (L) inferior frontal gyrus, and between a seed in the R horizontal intraparietal sulcus and clusters in the R precentral gyrus and L cerebellar lobule VI. HE children showed lower resting state functional connectivity in a subset of these regions. Lower functional connectivity in the two fronto-parietal connections partially mediated the adverse effects of PAE on arithmetic performance. CONCLUSION This study demonstrates PAE-related functional connectivity impairments in functional networks involved in number processing. The weaker connectivity between the R posterior superior parietal lobule and the L inferior frontal gyrus suggests that impaired verbal processing and visuospatial working memory may play a role in number processing deficits, while weaker connectivity between the R intraparietal sulcus and the R precentral gyrus points to poorer finger-based numerical representation, which has been linked to arithmetic computational skills.
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Affiliation(s)
- Jia Fan
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Keri J Woods
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Joseph L Jacobson
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, USA
- Department of Human Biology, University of Cape Town, Cape Town, South Africa
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institutes of Health, Bethesda, Maryland, USA
| | - Jadrana T F Toich
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
| | - Christopher D Molteno
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Sandra W Jacobson
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, USA
- Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Ernesta M Meintjes
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, Cape Town, South Africa
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van Dijk SE, Drenth N, Hafkemeijer A, Labadie G, Witjes-Ané MNW, Blauw GJ, Rombouts SA, van der Grond J, van Rooden S. Neurovascular coupling in early stage dementia - A case-control study. J Cereb Blood Flow Metab 2024; 44:1013-1023. [PMID: 37994030 DOI: 10.1177/0271678x231214102] [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: 11/24/2023]
Abstract
Cerebral amyloid angiopathy (CAA) is frequently found post mortem in Alzheimer's dementia, but often undetected during life especially since in vivo hallmarks of CAA and its vascular damage become overt relatively late in the disease process. Decreased neurovascular coupling to visual stimulation has been put forward as an early MRI marker for CAA disease severity. The current study investigates the role of neurovascular coupling in AD related dementia and its early stages. We included 25 subjective cognitive impairment, 33 mild cognitive impairment and 17 dementia patients and 44 controls. All participants underwent magnetic resonance imaging of the brain and neuropsychological assessment. Univariate general linear modeling analyses were used to assess neurovascular coupling between patient groups and controls. Moreover, linear regression analyses was used to assess the associations between neurovascular coupling and cognition. Our data show that BOLD amplitude is lower in dementia (mean 0.8 ± 0.2, p = 0.001) and MCI patients (mean 0.9 ± 0.3, p = 0.004) compared with controls (mean 1.1 ± 0.2). A low BOLD amplitude was associated with low scores in multiple cognitive domains. We conclude that cerebrovascular dysfunction, most likely due CAA, is an important comorbidity in early stages of dementia and has an independent effect on cognition.
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Affiliation(s)
- Suzanne E van Dijk
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Nadieh Drenth
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anne Hafkemeijer
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Gerda Labadie
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marie-Noëlle W Witjes-Ané
- Department of Geriatrics and Psychiatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Gerard J Blauw
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
- Department of Geriatrics, Haaglanden Medical Center, The Hague, the Netherlands
| | - Serge Arb Rombouts
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Jeroen van der Grond
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sanneke van Rooden
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
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31
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Yu L, Wang T, Hansson O, Janelidze S, Lamar M, Arfanakis K, Bennett DA, Schneider JA, Boyle PA. MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults. Neurol Clin Pract 2024; 14:e200291. [PMID: 38720951 PMCID: PMC11073883 DOI: 10.1212/cpj.0000000000200291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 01/25/2024] [Indexed: 05/12/2024]
Abstract
Background and Objectives Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia. Methods Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics. Results A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT. Discussion Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.
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Affiliation(s)
- Lei Yu
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Tianhao Wang
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Oskar Hansson
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Shorena Janelidze
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Melissa Lamar
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Konstantinos Arfanakis
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - David A Bennett
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Julie A Schneider
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Patricia A Boyle
- Rush Alzheimer's Disease Center (LY, TW, ML, KA, DAB, JAS, PAB), Rush University Medical Center, Chicago, IL; and Clinical Memory Research Unit (OH, SJ), Department of Clinical Sciences, Lund University, Malmö, Sweden
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Claaß LV, Hedrich A, Reinelt J, Sehm B, Villringer A, Schlagenhauf F, Kaminski J. Influence of noninvasive brain stimulation on connectivity and local activation: a combined tDCS and fMRI study. Eur Arch Psychiatry Clin Neurosci 2024; 274:827-835. [PMID: 37597023 PMCID: PMC11127864 DOI: 10.1007/s00406-023-01666-y] [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: 12/09/2022] [Accepted: 07/31/2023] [Indexed: 08/21/2023]
Abstract
The effect of transcranial direct current stimulation (tDCS) on neurobiological mechanisms underlying executive function in the human brain remains elusive. This study aims at examining the effect of anodal and cathodal tDCS over the left dorsolateral prefrontal cortex (DLPFC) in comparison with sham stimulation on resting-state connectivity as well as functional activation and working memory performance. We hypothesized perturbed fronto-parietal resting-state connectivity during stimulation and altered working memory performance combined with modified functional working memory-related activation. We applied tDCS with 1 mA for 21 min over the DLPFC inside an fMRI scanner. During stimulation, resting-state fMRI was acquired and task-dependent fMRI during working memory task performance was acquired directly after stimulation. N = 36 healthy subjects were studied in a within-subject design with three different experimental conditions (anodal, cathodal and sham) in a double-blind design. Seed-based functional connectivity analyses and dynamic causal modeling were conducted for the resting-state fMRI data. We found a significant stimulation by region interaction in the seed-based ROI-to-ROI resting-state connectivity, but no effect on effective connectivity. We also did not find an effect of stimulation on task-dependent signal alterations in working memory activation in our regions of interest and no effect on working memory performance parameters. We found effects on measures of seed-based resting-state connectivity, while measures of effective connectivity and task-based connectivity did not show any stimulation effect. We could not replicate previous findings of tDCS stimulation effects on behavioral outcomes. We critically discuss possible methodological limitations and implications for future studies.
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Affiliation(s)
- Luise Victoria Claaß
- Department of Neurology, Max-Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1, 04103, Leipzig, Germany
| | - Annika Hedrich
- Department of Neurology, Max-Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1, 04103, Leipzig, Germany
- Department of Psychiatry and Neurosciences CCM, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany
| | - Janis Reinelt
- Department of Neurology, Max-Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1, 04103, Leipzig, Germany
| | - Bernhard Sehm
- Department of Neurology, Max-Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1, 04103, Leipzig, Germany
- Department of Neurology, Martin Luther University of Halle-Wittenberg, Ernst-Grube-Str. 40, 06120, Halle, Germany
| | - Arno Villringer
- Department of Neurology, Max-Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1, 04103, Leipzig, Germany
- Day Clinic for Cognitive Neurology, University Hospital at the University of Leipzig, Liebigstraße 16, 04103, Leipzig, Germany
- Berlin School of Mind and Brain, MindBrainBody Institute, Humboldt-Universität zu Berlin, Unter den Linden 6, 10999, Berlin, Germany
| | - Florian Schlagenhauf
- Department of Neurology, Max-Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1, 04103, Leipzig, Germany
- Department of Psychiatry and Neurosciences CCM, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany
| | - Jakob Kaminski
- Department of Neurology, Max-Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1, 04103, Leipzig, Germany.
- Department of Psychiatry and Neurosciences CCM, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany.
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Mitte, Charitéplatz 1, 10117, Berlin, Germany.
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Bontempi P, Piccolantonio G, Busato A, Conti A, Angelini G, Lopez N, Bani A, Constantin G, Marzola P. Resting-state functional magnetic resonance imaging reveals functional connectivity alteration in the experimental autoimmune encephalomyelitis model of multiple sclerosis. NMR IN BIOMEDICINE 2024; 37:e5127. [PMID: 38450807 DOI: 10.1002/nbm.5127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 01/08/2024] [Accepted: 01/25/2024] [Indexed: 03/08/2024]
Abstract
Multiple sclerosis (MS) is an autoimmune degenerative disease targeting white matter in the central nervous system. The most common animal model that mimics MS is experimental autoimmune encephalomyelitis (EAE) and it plays a crucial role in pharmacological research, from the identification of a therapeutic target to the in vivo validation of efficacy. Magnetic resonance imaging (MRI) is largely used to detect MS lesions, and resting-state functional MRI (rsfMRI) to investigate alterations in the brain functional connectivity (FC). MRI was mainly used in EAE studies to detect lesions in the spinal cord and brain. The current longitudinal MRI study aims to validate rsfMRI as a biomarker of the disease progression in the myelin oligodendrocyte glycoprotein 35-55 induced EAE animal model of MS. MR images were acquired 14, 25, and 50 days postimmunization. Seed-based analysis was used to investigate the whole-brain FC with some predefined areas, such as the thalamic regions, cerebellum, motor and somatosensory cortex. When compared with the control group, the EAE group exhibited a slightly altered FC and a decreasing trend in the total number of activated voxels along the disease progression. The most interesting result regards the whole-brain FC with the cerebellum. A hyperconnectivity behavior was found at an early phase and a significant reduced connectivity at a late phase. Moreover, we found a negative correlation between the total number of activated voxels during the late phase and the cumulative disease index. The results obtained provide a clinically relevant experimental platform that may be pivotal for the elucidation of the key mechanisms of accumulation of irreversible disability, as well as the development of innovative therapies for MS. Moreover, the negative correlation between the disease severity and the size of the activated area suggests a possible research pathway to follow for the resolution of the clinico-radiological paradox.
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Affiliation(s)
- Pietro Bontempi
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Giusi Piccolantonio
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | - Alice Busato
- Department of Computer Science, University of Verona, Verona, Italy
- Evotec Company, Verona, Italy
| | - Anita Conti
- Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | | | - Nicola Lopez
- Department of Medicine, University of Verona, Verona, Italy
| | | | | | - Pasquina Marzola
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
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Kraljević N, Langner R, Küppers V, Raimondo F, Patil KR, Eickhoff SB, Müller VI. Network and state specificity in connectivity-based predictions of individual behavior. Hum Brain Mapp 2024; 45:e26753. [PMID: 38864353 PMCID: PMC11167405 DOI: 10.1002/hbm.26753] [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: 05/16/2023] [Revised: 04/17/2024] [Accepted: 05/23/2024] [Indexed: 06/13/2024] Open
Abstract
Predicting individual behavior from brain functional connectivity (FC) patterns can contribute to our understanding of human brain functioning. This may apply in particular if predictions are based on features derived from circumscribed, a priori defined functional networks, which improves interpretability. Furthermore, some evidence suggests that task-based FC data may yield more successful predictions of behavior than resting-state FC data. Here, we comprehensively examined to what extent the correspondence of functional network priors and task states with behavioral target domains influences the predictability of individual performance in cognitive, social, and affective tasks. To this end, we used data from the Human Connectome Project for large-scale out-of-sample predictions of individual abilities in working memory (WM), theory-of-mind cognition (SOCIAL), and emotion processing (EMO) from FC of corresponding and non-corresponding states (WM/SOCIAL/EMO/resting-state) and networks (WM/SOCIAL/EMO/whole-brain connectome). Using root mean squared error and coefficient of determination to evaluate model fit revealed that predictive performance was rather poor overall. Predictions from whole-brain FC were slightly better than those from FC in task-specific networks, and a slight benefit of predictions based on FC from task versus resting state was observed for performance in the WM domain. Beyond that, we did not find any significant effects of a correspondence of network, task state, and performance domains. Together, these results suggest that multivariate FC patterns during both task and resting states contain rather little information on individual performance levels, calling for a reconsideration of how the brain mediates individual differences in mental abilities.
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Affiliation(s)
- Nevena Kraljević
- Institute of Systems Neuroscience, Medical Faculty and University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty and University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Vincent Küppers
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany
| | - Federico Raimondo
- Institute of Systems Neuroscience, Medical Faculty and University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Kaustubh R. Patil
- Institute of Systems Neuroscience, Medical Faculty and University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty and University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
| | - Veronika I. Müller
- Institute of Systems Neuroscience, Medical Faculty and University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
- Institute of Neuroscience and Medicine (INM‐7: Brain and Behaviour)Research Centre JülichJülichGermany
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Lopez FV, O'Shea A, Huo Z, DeKosky ST, Trouard TP, Alexander GE, Woods AJ, Bowers D. Frontal-temporal regional differences in brain energy metabolism and mitochondrial function using 31P MRS in older adults. GeroScience 2024; 46:3185-3195. [PMID: 38225480 PMCID: PMC11009166 DOI: 10.1007/s11357-023-01046-3] [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: 10/19/2023] [Accepted: 12/07/2023] [Indexed: 01/17/2024] Open
Abstract
Aging is a major risk for cognitive decline and transition to dementia. One well-known age-related change involves decreased brain efficiency and energy production, mediated in part by changes in mitochondrial function. Damaged or dysfunctional mitochondria have been implicated in the pathogenesis of age-related neurodegenerative conditions like Alzheimer's disease (AD). The aim of the current study was to investigate mitochondrial function over frontal and temporal regions in a sample of 70 cognitively normal older adults with subjective memory complaints and a first-degree family history of AD. We hypothesized cerebral mitochondrial function and energy metabolism would be greater in temporal as compared to frontal regions based on the high energy consumption in the temporal lobes (i.e., hippocampus). To test this hypothesis, we used phosphorous (31P) magnetic resonance spectroscopy (MRS) which is a non-invasive and powerful method for investigating in vivo mitochondrial function via high energy phosphates and phospholipid metabolism ratios. We used a single voxel method (left temporal and bilateral prefrontal) to achieve optimal sensitivity. Results of separate repeated measures analyses of variance showed 31P MRS ratios of static energy, energy reserve, energy consumption, energy demand, and phospholipid membrane metabolism were greater in the left temporal than bilateral prefrontal voxels. Our findings that all 31P MRS ratios were greater in temporal than bifrontal regions support our hypothesis. Future studies are needed to determine whether findings are related to cognition in older adults.
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Affiliation(s)
- Francesca V Lopez
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, PO Box 100165, Gainesville, FL, 32610, USA.
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory, Evelyn F. McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Zhiguang Huo
- Department of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Steven T DeKosky
- Department of Neurology, Fixel Center for Neurological Diseases, College of Medicine, and Evelyn F. McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Theodore P Trouard
- Department of Biomedical Engineering, College of Engineering, and Evelyn F. McKnight Brain Institute, University of Arizona and Alzheimer's Disease Consortium, Tucson, AZ, USA
| | - Gene E Alexander
- Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Disease Consortium, Tucson, AZ, USA
| | - Adam J Woods
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, PO Box 100165, Gainesville, FL, 32610, USA
- Center for Cognitive Aging and Memory, Evelyn F. McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Dawn Bowers
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, PO Box 100165, Gainesville, FL, 32610, USA
- Department of Neurology, Fixel Center of Neurological Diseases, College of Medicine, University of Florida, Gainesville, FL, USA
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Du J, DiNicola LM, Angeli PA, Saadon-Grosman N, Sun W, Kaiser S, Ladopoulou J, Xue A, Yeo BTT, Eldaief MC, Buckner RL. Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function. J Neurophysiol 2024; 131:1014-1082. [PMID: 38489238 DOI: 10.1152/jn.00308.2023] [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: 08/16/2023] [Revised: 01/18/2024] [Accepted: 02/16/2024] [Indexed: 03/17/2024] Open
Abstract
The cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks from functional MRI (fMRI) data in intensively sampled participants. The procedure was developed in two participants (scanned 31 times) and then prospectively applied to 15 participants (scanned 8-11 times). Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as supra-areal association megaclusters (SAAMs). Within each SAAM, two candidate control regions were adjacent to three separate domain-specialized regions. Response properties were explored with task data. The somatomotor and visual networks responded to body movements and visual stimulation, respectively. Second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions dissociated across language, social, and spatial/episodic processing domains. These results suggest that progressively higher-order networks nest outward from primary sensory and motor cortices. Within the apex zones of association cortex, there is specialization that repeatedly divides domain-flexible from domain-specialized regions. We discuss implications of these findings, including how repeating organizational motifs may emerge during development.NEW & NOTEWORTHY The organization of cerebral networks was estimated within individuals with intensive, repeat sampling of fMRI data. A hierarchical organization emerged in each individual that delineated first-, second-, and third-order cortical networks. Regions of distinct third-order association networks consistently exhibited side-by-side juxtapositions that repeated across multiple cortical zones, with clear and robust functional specialization among the embedded regions.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Wendy Sun
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Stephanie Kaiser
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Joanna Ladopoulou
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Aihuiping Xue
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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Do KT, Prinstein MJ, Lindquist KA, Telzer EH. Neural Tracking of Perceived Parent, but Not Peer, Norms Is Associated with Longitudinal Changes in Adolescent Attitudes about Externalizing Behaviors. J Cogn Neurosci 2024; 36:1221-1237. [PMID: 38579244 PMCID: PMC11095915 DOI: 10.1162/jocn_a_02152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2024]
Abstract
Adolescents' perceptions of parent and peer norms about externalizing behaviors influence the extent to which they adopt similar attitudes, yet little is known about how the trajectories of perceived parent and peer norms are related to trajectories of personal attitudes across adolescence. Neural development of midline regions implicated in self-other processing may underlie developmental changes in parent and peer influence. Here, we examined whether neural processing of perceived parent and peer norms in midline regions during self-evaluations would be associated with trajectories of personal attitudes about externalizing behaviors. Trajectories of adolescents' perceived parent and peer norms were examined longitudinally with functional neuroimaging (n = 165; ages 11-16 years across three waves; 86 girls, 79 boys; 29.7% White, 21.8% Black, 35.8% Latinx, 12.7% other/multiracial). Behavioral results showed perceived parent norms were less permissive than adolescents' own attitudes about externalizing behaviors, whereas perceived peer norms were more permissive than adolescents' own attitudes, effects that increased from early to middle adolescence. Although younger adolescents reported less permissive attitudes when they spontaneously tracked perceived parent norms in the ventromedial and medial pFCs during self-evaluations, this effect weakened as they aged. No brain-behavior effects were found when tracking perceived peer norms. These findings elucidate how perceived parent and peer norms change in parallel with personal attitudes about externalizing behaviors from early to middle adolescence and underscore the importance of spontaneous neural tracking of perceived parent norms during self-evaluations for buffering permissive personal attitudes, particularly in early adolescence.
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Affiliation(s)
- Kathy T Do
- University of North Carolina at Chapel Hill
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38
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Guo J. Optimizing background suppression for dual-module velocity-selective arterial spin labeling: Without using additional background-suppression pulses. Magn Reson Med 2024; 91:2320-2331. [PMID: 38173296 PMCID: PMC10997483 DOI: 10.1002/mrm.29995] [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: 09/27/2023] [Revised: 12/12/2023] [Accepted: 12/14/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE Background suppression (BS) is recommended in arterial spin labeling (ASL) for improved SNR but is difficult to optimize in existing velocity-selective ASL (VSASL) methods. Dual-module VSASL (dm-VSASL) enables delay-insensitive, robust, and SNR-efficient perfusion imaging, while allowing efficient BS, but its optimization has yet to be thoroughly investigated. METHODS The inversion effects of the velocity-selective labeling pulses, such as velocity-selective inversion (VSI), can be used for BS, and were modeled for optimizing BS in dm-VSASL. In vivo experiments using dual-module VSI (dm-VSI) were performed to compare two BS strategies: a conventional one with additional BS pulses and a new one without any BS pulse. Their BS performance, temporal noise, and temporal SNR were examined and compared, with pulsed and pseudo-continuous ASL (PASL and PCASL) as the reference. RESULTS The in vivo experiments validated the BS modeling. Strong positive linear correlations (r > 0.82, p < 0.0001) between the temporal noise and the tissue signal were found in PASL/PCASL and dm-VSI. Optimal BS can be achieved with and without additional BS pulses in dm-VSI; the latter improved the ASL signals by 8.5% in gray matter (p = 0.006) and 12.2% in white matter (p = 0.014) and tended to provide better temporal SNR. The dm-VSI measured significantly higher ASL signal (p < 0.016) and temporal SNR (p < 0.018) than PASL and PCASL. Complex reconstruction was found necessary with aggressive BS. CONCLUSION Guided by modeling, optimal BS can be achieved without any BS pulse in dm-VSASL, further improving the ASL signal and the SNR performance.
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Affiliation(s)
- Jia Guo
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA
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Ma L, Zhang Y, Zhang H, Cheng L, Yang Z, Lu Y, Shi W, Li W, Zhuo J, Wang J, Fan L, Jiang T. BAI-Net: Individualized Anatomical Cerebral Cartography Using Graph Neural Network. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024; 35:7446-7457. [PMID: 36315537 DOI: 10.1109/tnnls.2022.3213581] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Brain atlas is an important tool in the diagnosis and treatment of neurological disorders. However, due to large variations in the organizational principles of individual brains, many challenges remain in clinical applications. Brain atlas individualization network (BAI-Net) is an algorithm that subdivides individual cerebral cortex into segregated areas using brain morphology and connectomes. The presented method integrates group priors derived from a population atlas, adjusts areal probabilities using the context of connectivity fingerprints derived from the fiber-tract embedding of tractography, and provides reliable and explainable individualized brain areas across multiple sessions and scanners. We demonstrate that BAI-Net outperforms the conventional iterative clustering approach by capturing significantly heritable topographic variations in individualized cartographies. The topographic variability of BAI-Net cartographies has shown strong associations with individual variability in brain morphology, connectivity as well as higher relationship on individual cognitive behaviors and genetics. This study provides an explainable framework for individualized brain cartography that may be useful in the precise localization of neuromodulation and treatments on individual brains.
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Fenoy AJ, Chu ZD, Ritter RJ, Conner CR, Kralik SF. Evaluating functional connectivity differences between DBS ON/OFF states in essential tremor. Neurotherapeutics 2024:e00375. [PMID: 38824101 DOI: 10.1016/j.neurot.2024.e00375] [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: 10/29/2023] [Revised: 05/05/2024] [Accepted: 05/13/2024] [Indexed: 06/03/2024] Open
Abstract
Deep brain stimulation (DBS) targeting the ventral intermediate (Vim) nucleus of the thalamus is an effective treatment for essential tremor (ET). We studied 15 ET patients undergoing DBS to a major input/output tract of the Vim, the dentato-rubro-thalamic tract (DRTt), using resting state functional MRI (rsfMRI) to evaluate connectivity differences between DBS ON and OFF and elucidate significant regions most influential in impacting tremor control and/or concomitant gait ataxia. Anatomical/functional 1.5T MRIs were acquired and replicated for each DBS state. Tremor severity and gait ataxia severity were scored with DBS ON at optimal stimulation parameters and immediately upon DBS OFF. Whole brain analysis was performed using dual regression analysis followed by randomized permutation testing for multiple correction comparison. Regions of interest (ROI) analysis was also performed. All 15 patients had tremor improvement between DBS ON/OFF (p < 0.001). Whole brain analysis revealed significant connectivity changes between states in the left pre-central gyrus and left supplemental motor area. Group analysis of ROIs revealed that, with threshold p < 0.05, in DBS ON vs. OFF both tremor duration and tremor improvement were significantly correlated to changes in connectivity. A sub-group analysis of patients with greater ataxia had significantly decreased functional connectivity between multiple ROIs in the cortex and cerebellum when DBS was ON compared to OFF. Stimulation of the DRTt and concordant improvement of tremor resulted in connectivity changes seen in multiple regions outside the motor network; when combined with both structural and electrophysiologic connectivity, this may help to serve as a biomarker to improve DBS targeting and possibly predict outcome.
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Affiliation(s)
- Albert J Fenoy
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA; Departments of Neurosurgery and Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
| | - Zili D Chu
- Edward B. Singleton Department of Radiology, Baylor College of Medicine at Texas Children's Hospital, Houston, TX, USA
| | - Robert J Ritter
- Department of Neurosurgery, McGovern School of Medicine, UTHealth Houston, Houston, TX, USA
| | - Christopher R Conner
- Division of Neurosurgery, Dept. of Surgery, University of Connecticut, Hartford, CT, USA
| | - Stephen F Kralik
- Edward B. Singleton Department of Radiology, Baylor College of Medicine at Texas Children's Hospital, Houston, TX, USA
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Radunsky D, Solomon C, Stern N, Blumenfeld-Katzir T, Filo S, Mezer A, Karsa A, Shmueli K, Soustelle L, Duhamel G, Girard OM, Kepler G, Shrot S, Hoffmann C, Ben-Eliezer N. A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla. PLoS One 2024; 19:e0297244. [PMID: 38820354 PMCID: PMC11142522 DOI: 10.1371/journal.pone.0297244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 01/01/2024] [Indexed: 06/02/2024] Open
Abstract
Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.
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Affiliation(s)
- Dvir Radunsky
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Chen Solomon
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Neta Stern
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | | | - Shir Filo
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aviv Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Anita Karsa
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | | | | | | | - Gal Kepler
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Science, Tel Aviv University, Tel Aviv, Israel
| | - Shai Shrot
- Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat-Gan, Israel
| | - Chen Hoffmann
- Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat-Gan, Israel
| | - Noam Ben-Eliezer
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY, United States of America
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Udayakumar P, Subhashini R. Connectome-based schizophrenia prediction using structural connectivity - Deep Graph Neural Network(sc-DGNN). JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2024:XST230426. [PMID: 38820060 DOI: 10.3233/xst-230426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
Background Connectome is understanding the complex organization of the human brain's structural and functional connectivity is essential for gaining insights into cognitive processes and disorders. Objective To improve the prediction accuracy of brain disorder issues, the current study investigates dysconnected subnetworks and graph structures associated with schizophrenia. Method By using the proposed structural connectivity-deep graph neural network (sc-DGNN) model and compared with machine learning (ML) and deep learning (DL) models.This work attempts to focus on eighty-eight subjects of diffusion magnetic resonance imaging (dMRI), three classical ML, and five DL models. Result The structural connectivity-deep graph neural network (sc-DGNN) model is proposed to effectively predict dysconnectedness associated with schizophrenia and exhibits superior performance compared to traditional ML and DL (GNNs) methods in terms of accuracy, sensitivity, specificity, precision, F1-score, and Area under receiver operating characteristic (AUC). Conclusion The classification task on schizophrenia using structural connectivity matrices and experimental results showed that linear discriminant analysis (LDA) performed 72% accuracy rate in ML models and sc-DGNN performed at a 93% accuracy rate in DL models to distinguish between schizophrenia and healthy patients.
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Affiliation(s)
- P Udayakumar
- School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, Tamilnadu, India
| | - R Subhashini
- School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, Tamilnadu, India
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43
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Parker KJ, Kabir IE, Doyley MM, Faiyaz A, Uddin MN, Flores G, Schifitto G. Brain elastography in aging relates to fluid/solid trendlines. Phys Med Biol 2024; 69:115037. [PMID: 38670141 DOI: 10.1088/1361-6560/ad4446] [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: 01/23/2024] [Accepted: 04/26/2024] [Indexed: 04/28/2024]
Abstract
The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.
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Affiliation(s)
- Kevin J Parker
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
| | - Irteza Enan Kabir
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
| | - Marvin M Doyley
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
| | - Abrar Faiyaz
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
| | - Md Nasir Uddin
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Neurology, University of Rochester Medical Center, 601 Elmwood Ave, Box 673, Rochester, NY 14642, United States of America
| | - Gilmer Flores
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
| | - Giovanni Schifitto
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
- Department of Neurology, University of Rochester Medical Center, 601 Elmwood Ave, Box 673, Rochester, NY 14642, United States of America
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Hu W, Qiu Z, Huang Q, Lin Y, Mo J, Wang L, Wang J, Deng K, Feng Y, Zhang X, Tan X. Microstructural changes of the white matter in systemic lupus erythematosus patients without neuropsychiatric symptoms: a multi-shell diffusion imaging study. Arthritis Res Ther 2024; 26:110. [PMID: 38807248 PMCID: PMC11134659 DOI: 10.1186/s13075-024-03344-3] [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: 01/22/2024] [Accepted: 05/22/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) provide more comprehensive and informative perspective on microstructural alterations of cerebral white matter (WM) than single-shell diffusion tensor imaging (DTI), especially in the detection of crossing fiber. However, studies on systemic lupus erythematosus patients without neuropsychiatric symptoms (non-NPSLE patients) using multi-shell diffusion imaging remain scarce. METHODS Totally 49 non-NPSLE patients and 41 age-, sex-, and education-matched healthy controls underwent multi-shell diffusion magnetic resonance imaging. Totally 10 diffusion metrics based on DKI (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis and radial kurtosis) and NODDI (neurite density index, orientation dispersion index and volume fraction of the isotropic diffusion compartment) were evaluated. Tract-based spatial statistics (TBSS) and atlas-based region-of-interest (ROI) analyses were performed to determine group differences in brain WM microstructure. The associations of multi-shell diffusion metrics with clinical indicators were determined for further investigation. RESULTS TBSS analysis revealed reduced FA, AD and RK and increased ODI in the WM of non-NPSLE patients (P < 0.05, family-wise error corrected), and ODI showed the best discriminative ability. Atlas-based ROI analysis found increased ODI values in anterior thalamic radiation (ATR), inferior frontal-occipital fasciculus (IFOF), forceps major (F_major), forceps minor (F_minor) and uncinate fasciculus (UF) in non-NPSLE patients, and the right ATR showed the best discriminative ability. ODI in the F_major was positively correlated to C3. CONCLUSION This study suggested that DKI and NODDI metrics can complementarily detect WM abnormalities in non-NPSLE patients and revealed ODI as a more sensitive and specific biomarker than DKI, guiding further understanding of the pathophysiological mechanism of normal-appearing WM injury in SLE.
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Affiliation(s)
- Wenjun Hu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Ziru Qiu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Qin Huang
- Department of Rheumatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuhao Lin
- Departments of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Jiaying Mo
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Linhui Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jingyi Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kan Deng
- Philips Healthcare, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Xinyuan Zhang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
- Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.
| | - Xiangliang Tan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
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Power LC, Mirro AE, Binkley MM, Wang J, Guilliams KP, Lewis JB, Ford AL, Shimony JS, An H, Lee JM, Fields ME. Reversibility of Cognitive Deficits and Functional Connectivity With Transfusion in Children With Sickle Cell Disease. Neurology 2024; 102:e209429. [PMID: 38710015 DOI: 10.1212/wnl.0000000000209429] [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: 05/08/2024] Open
Abstract
BACKGROUND AND OBJECTIVES People with sickle cell disease (SCD) are at risk of cognitive dysfunction independent of stroke. Diminished functional connectivity in select large-scale networks and white matter integrity reflect the neurologic consequences of SCD. Because chronic transfusion therapy is neuroprotective in preventing stroke and strengthening executive function abilities in people with SCD, we hypothesized that red blood cell (RBC) transfusion facilitates the acute reversal of disruptions in functional connectivity while white matter integrity remains unaffected. METHODS Children with SCD receiving chronic transfusion therapy underwent a brain MRI measuring white matter integrity with diffusion tensor imaging and resting-state functional connectivity within 3 days before and after transfusion of RBCs. Cognitive assessments with the NIH Toolbox were acquired after transfusion and then immediately before the following transfusion cycle. RESULTS Sixteen children with a median age of 12.5 years were included. Global assessments of functional connectivity using homotopy (p = 0.234) or modularity (p = 0.796) did not differ with transfusion. Functional connectivity within the frontoparietal network significantly strengthened after transfusion (median intranetwork Z-score 0.21 [0.17-0.30] before transfusion, 0.29 [0.20-0.36] after transfusion, p < 0.001), while there was not a significant change seen within the sensory motor, visual, auditory, default mode, dorsal attention, or cingulo-opercular networks. Corresponding to the change within the frontoparietal network, there was a significant improvement in executive function abilities after transfusion (median executive function composite score 87.7 [81.3-90.7] before transfusion, 90.3 [84.3-93.7] after transfusion, p = 0.021). Participants with stronger connectivity in the frontoparietal network before transfusion had a significantly greater improvement in the executive function composite score with transfusion (r = 0.565, 95% CI 0.020-0.851, p = 0.044). While functional connectivity and executive abilities strengthened with transfusion, there was not a significant change in white matter integrity as assessed by fractional anisotropy and mean diffusivity within 16 white matter tracts or globally with tract-based spatial statistics. DISCUSSION Strengthening of functional connectivity with concomitant improvement in executive function abilities with transfusion suggests that functional connectivity MRI could be used as a biomarker for acutely reversible neurocognitive injury as novel therapeutics are developed for people with SCD.
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Affiliation(s)
- Landon C Power
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Amy E Mirro
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Micahel M Binkley
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jinli Wang
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Kristin P Guilliams
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Josiah B Lewis
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Andria L Ford
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Joshua S Shimony
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Hongyu An
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Jin-Moo Lee
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
| | - Melanie E Fields
- From the Department of Pediatrics (L.C.P., A.E.M., M.M.B., K.P.G., M.E.F.), Center for Biostatistics and Data Science (J.W.), Department of Neurology (K.P.G., J.B.L., A.L.F., J.-M.L., M.E.F.), Mallinckrodt Institute of Radiology (K.P.G., A.L.F., J.S.S., H.A., J.-M.L.), and Department of Biomedical Engineering (J.-M.L.), Washington University School of Medicine, St. Louis, MO
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Lazari A, Tachrount M, Valverde JM, Papp D, Beauchamp A, McCarthy P, Ellegood J, Grandjean J, Johansen-Berg H, Zerbi V, Lerch JP, Mars RB. The mouse motor system contains multiple premotor areas and partially follows human organizational principles. Cell Rep 2024; 43:114191. [PMID: 38717901 DOI: 10.1016/j.celrep.2024.114191] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 12/10/2023] [Accepted: 04/17/2024] [Indexed: 06/01/2024] Open
Abstract
While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher-order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we show that axonal tracer, functional connectivity, myelin mapping, gene expression, and optogenetics data contradict this notion. Our analyses reveal three premotor areas in the mouse, anterior-lateral motor cortex (ALM), anterior-lateral M2 (aM2), and posterior-medial M2 (pM2), with distinct structural, functional, and behavioral properties. By using the same techniques across mice and humans, we show that ALM has strikingly similar functional and microstructural properties to human anterior ventral premotor areas and that aM2 and pM2 amalgamate properties of human pre-SMA and cingulate cortex. These results provide evidence for the existence of multiple premotor areas in the mouse and chart a comparative map between the motor systems of humans and mice.
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Affiliation(s)
- Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Mohamed Tachrount
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Juan Miguel Valverde
- DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark; A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, 70150 Kuopio, Finland
| | - Daniel Papp
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Antoine Beauchamp
- Mouse Imaging Centre, The Hospital for Sick Children, Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Paul McCarthy
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Jacob Ellegood
- Mouse Imaging Centre, The Hospital for Sick Children, Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
| | - Joanes Grandjean
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, 1015 Lausanne, Switzerland; CIBM Center for Biomedical Imaging, 1015 Lausanne, Switzerland
| | - Jason P Lerch
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Mouse Imaging Centre, The Hospital for Sick Children, Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
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Julian A, Ruthotto L. PyHySCO: GPU-enabled susceptibility artifact distortion correction in seconds. Front Neurosci 2024; 18:1406821. [PMID: 38863882 PMCID: PMC11165994 DOI: 10.3389/fnins.2024.1406821] [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] [Received: 03/25/2024] [Accepted: 04/25/2024] [Indexed: 06/13/2024] Open
Abstract
Over the past decade, reversed gradient polarity (RGP) methods have become a popular approach for correcting susceptibility artifacts in echo-planar imaging (EPI). Although several post-processing tools for RGP are available, their implementations do not fully leverage recent hardware, algorithmic, and computational advances, leading to correction times of several minutes per image volume. To enable 3D RGP correction in seconds, we introduce PyTorch Hyperelastic Susceptibility Correction (PyHySCO), a user-friendly EPI distortion correction tool implemented in PyTorch that enables multi-threading and efficient use of graphics processing units (GPUs). PyHySCO uses a time-tested physical distortion model and mathematical formulation and is, therefore, reliable without training. An algorithmic improvement in PyHySCO is its use of the one-dimensional distortion correction method by Chang and Fitzpatrick to initialize the non-linear optimization. PyHySCO is published under the GNU public license and can be used from the command line or its Python interface. Our extensive numerical validation using 3T and 7T data from the Human Connectome Project suggests that PyHySCO can achieve accuracy comparable to that of leading RGP tools at a fraction of the cost. We also validate the new initialization scheme, compare different optimization algorithms, and test the algorithm on different hardware and arithmetic precisions.
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Affiliation(s)
- Abigail Julian
- Department of Computer Science, Emory University, Atlanta, GA, United States
| | - Lars Ruthotto
- Department of Computer Science, Emory University, Atlanta, GA, United States
- Department of Mathematics, Emory University, Atlanta, GA, United States
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Lockwood PL, Cutler J, Drew D, Abdurahman A, Jeyaretna DS, Apps MAJ, Husain M, Manohar SG. Human ventromedial prefrontal cortex is necessary for prosocial motivation. Nat Hum Behav 2024:10.1038/s41562-024-01899-4. [PMID: 38802539 DOI: 10.1038/s41562-024-01899-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 04/23/2024] [Indexed: 05/29/2024]
Abstract
Ventromedial prefrontal cortex (vmPFC) is vital for decision-making. Functional neuroimaging links vmPFC to processing rewards and effort, while parallel work suggests vmPFC involvement in prosocial behaviour. However, the necessity of vmPFC for these functions is unknown. Patients with rare focal vmPFC lesions (n = 25), patients with lesions elsewhere (n = 15) and healthy controls (n = 40) chose between rest and exerting effort to earn rewards for themselves or another person. vmPFC damage decreased prosociality across behavioural and computational measures. vmPFC patients earned less, discounted rewards by effort more, and exerted less force when another person benefited, compared to both control groups. Voxel-based lesion mapping revealed dissociations between vmPFC subregions. While medial damage led to antisocial behaviour, lateral damage increased prosocial behaviour relative to patients with damage elsewhere. vmPFC patients also showed reduced effort sensitivity overall, but reward sensitivity was limited to specific subregions. These results reveal multiple causal contributions of vmPFC to prosocial behaviour, effort and reward.
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Affiliation(s)
- Patricia L Lockwood
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK.
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK.
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - Jo Cutler
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK.
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK.
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - Daniel Drew
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ayat Abdurahman
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Deva Sanjeeva Jeyaretna
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Neurology, John Radcliffe Hospital, Oxford, UK
| | - Matthew A J Apps
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Masud Husain
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Neurology, John Radcliffe Hospital, Oxford, UK
| | - Sanjay G Manohar
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Neurology, John Radcliffe Hospital, Oxford, UK
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Lahnakoski JM, Nolte T, Solway A, Vilares I, Hula A, Feigenbaum J, Lohrenz T, King-Casas B, Fonagy P, Montague PR, Schilbach L. A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivity. J Affect Disord 2024; 360:345-353. [PMID: 38806064 DOI: 10.1016/j.jad.2024.05.125] [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: 01/22/2024] [Revised: 05/23/2024] [Accepted: 05/24/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Functional connectivity has garnered interest as a potential biomarker of psychiatric disorders including borderline personality disorder (BPD). However, small sample sizes and lack of within-study replications have led to divergent findings with no clear spatial foci. AIMS Evaluate discriminative performance and generalizability of functional connectivity markers for BPD. METHOD Whole-brain fMRI resting state functional connectivity in matched subsamples of 116 BPD and 72 control individuals defined by three grouping strategies. We predicted BPD status using classifiers with repeated cross-validation based on multiscale functional connectivity within and between regions of interest (ROIs) covering the whole brain-global ROI-based network, seed-based ROI-connectivity, functional consistency, and voxel-to-voxel connectivity-and evaluated the generalizability of the classification in the left-out portion of non-matched data. RESULTS Full-brain connectivity allowed classification (∼70 %) of BPD patients vs. controls in matched inner cross-validation. The classification remained significant when applied to unmatched out-of-sample data (∼61-70 %). Highest seed-based accuracies were in a similar range to global accuracies (∼70-75 %), but spatially more specific. The most discriminative seed regions included midline, temporal and somatomotor regions. Univariate connectivity values were not predictive of BPD after multiple comparison corrections, but weak local effects coincided with the most discriminative seed-ROIs. Highest accuracies were achieved with a full clinical interview while self-report results remained at chance level. LIMITATIONS The accuracies vary considerably between random sub-samples of the population, global signal and covariates limiting the practical applicability. CONCLUSIONS Spatially distributed functional connectivity patterns are moderately predictive of BPD despite heterogeneity of the patient population.
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Affiliation(s)
- Juha M Lahnakoski
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Center Jülich, Wilhelm-Johnen-Straße, 52428 Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstr. 5, 40225 Düsseldorf, Germany.
| | - Tobias Nolte
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Anna Freud National Centre for Children and Families, London, United Kingdom
| | - Alec Solway
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA
| | - Iris Vilares
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Andreas Hula
- Austrian Institute of Technology, Vienna, Austria
| | - Janet Feigenbaum
- Research Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
| | - Terry Lohrenz
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA
| | - Brooks King-Casas
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA; Department of Psychology, Virginia Tech, Blacksburg, VA, USA
| | - Peter Fonagy
- Anna Freud National Centre for Children and Families, London, United Kingdom; Research Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom
| | - P Read Montague
- Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom; Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA; Department of Physics, Virginia Tech, Blacksburg, VA, USA; Department of Psychiatry and Behavioral Medicine, Virginia Tech Carilion School of Medicine, Virginia Tech, Roanoke, VA, USA
| | - Leonhard Schilbach
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany; Department of Psychiatry, Ludwig-Maximilians-Universität, Munich, Germany
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50
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Anumba N, Kelberman MA, Pan W, Marriott A, Zhang X, Xu N, Weinshenker D, Keilholz S. The Effects of Locus Coeruleus Optogenetic Stimulation on Global Spatiotemporal Patterns in Rats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595327. [PMID: 38826205 PMCID: PMC11142206 DOI: 10.1101/2024.05.23.595327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Whole-brain intrinsic activity as detected by resting-state fMRI can be summarized by three primary spatiotemporal patterns. These patterns have been shown to change with different brain states, especially arousal. The noradrenergic locus coeruleus (LC) is a key node in arousal circuits and has extensive projections throughout the brain, giving it neuromodulatory influence over the coordinated activity of structurally separated regions. In this study, we used optogenetic-fMRI in rats to investigate the impact of LC stimulation on the global signal and three primary spatiotemporal patterns. We report small, spatially specific changes in global signal distribution as a result of tonic LC stimulation, as well as regional changes in spatiotemporal patterns of activity at 5 Hz tonic and 15 Hz phasic stimulation. We also found that LC stimulation had little to no effect on the spatiotemporal patterns detected by complex principal component analysis. These results show that the effects of LC activity on the BOLD signal in rats may be small and regionally concentrated, as opposed to widespread and globally acting.
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Affiliation(s)
- Nmachi Anumba
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Michael A Kelberman
- Department of Human Genetics, Emory University, Atlanta, GA, United States
- Molecular Cellular and Developmental Biology Department, University of Colorado Boulder, Boulder, CO, United States
| | - Wenju Pan
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Alexia Marriott
- Department of Human Genetics, Emory University, Atlanta, GA, United States
| | - Xiaodi Zhang
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Nan Xu
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - David Weinshenker
- Department of Human Genetics, Emory University, Atlanta, GA, United States
| | - Shella Keilholz
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
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