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Deshpande G, Wang Y, Robinson J. Resting state fMRI connectivity is sensitive to laminar connectional architecture in the human brain. Brain Inform 2022; 9:2. [PMID: 35038072 PMCID: PMC8764001 DOI: 10.1186/s40708-021-00150-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/28/2021] [Indexed: 11/10/2022] Open
Abstract
Previous invasive studies indicate that human neocortical graymatter contains cytoarchitectonically distinct layers, with notable differences in their structural connectivity with the rest of the brain. Given recent improvements in the spatial resolution of anatomical and functional magnetic resonance imaging (fMRI), we hypothesize that resting state functional connectivity (FC) derived from fMRI is sensitive to layer-specific thalamo-cortical and cortico-cortical microcircuits. Using sub-millimeter resting state fMRI data obtained at 7 T, we found that: (1) FC between the entire thalamus and cortical layers I and VI was significantly stronger than between the thalamus and other layers. Furthermore, FC between somatosensory thalamus (ventral posterolateral nucleus, VPL) and layers IV, VI of the primary somatosensory cortex were stronger than with other layers; (2) Inter-hemispheric cortico-cortical FC between homologous regions in superficial layers (layers I-III) was stronger compared to deep layers (layers V-VI). These findings are in agreement with structural connections inferred from previous invasive studies that showed that: (i) M-type neurons in the entire thalamus project to layer-I; (ii) Pyramidal neurons in layer-VI target all thalamic nuclei, (iii) C-type neurons in the VPL project to layer-IV and receive inputs from layer-VI of the primary somatosensory cortex, and (iv) 80% of collosal projecting neurons between homologous cortical regions connect superficial layers. Our results demonstrate for the first time that resting state fMRI is sensitive to structural connections between cortical layers (previously inferred through invasive studies), specifically in thalamo-cortical and cortico-cortical networks.
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Affiliation(s)
- Gopikrishna Deshpande
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA. .,Department of Psychological Sciences, Auburn University, Auburn, AL, USA. .,Alabama Advanced Imaging Consortium, Birmingham, AL, USA. .,Center for Neuroscience, Auburn University, Auburn, AL, USA. .,Key Laboratory for Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India. .,Centre for Brain Research, Indian Institute of Science, Bangalore, India.
| | - Yun Wang
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA.,Department of Psychiatry, Columbia University, New York, NY, USA
| | - Jennifer Robinson
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA.,Department of Psychological Sciences, Auburn University, Auburn, AL, USA.,Alabama Advanced Imaging Consortium, Birmingham, AL, USA.,Center for Neuroscience, Auburn University, Auburn, AL, USA
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Ferré P, Benhajali Y, Steffener J, Stern Y, Joanette Y, Bellec P. Resting-state and Vocabulary Tasks Distinctively Inform On Age-Related Differences in the Functional Brain Connectome. LANGUAGE, COGNITION AND NEUROSCIENCE 2019; 34:949-972. [PMID: 31457069 PMCID: PMC6711486 DOI: 10.1080/23273798.2019.1608072] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 03/05/2019] [Indexed: 05/23/2023]
Abstract
Most of the current knowledge about age-related differences in brain neurofunctional organization stems from neuroimaging studies using either a "resting state" paradigm, or cognitive tasks for which performance decreases with age. However, it remains to be known if comparable age-related differences are found when participants engage in cognitive activities for which performance is maintained with age, such as vocabulary knowledge tasks. A functional connectivity analysis was performed on 286 adults ranging from 18 to 80 years old, based either on a resting state paradigm or when engaged in vocabulary tasks. Notable increases in connectivity of regions of the language network were observed during task completion. Conversely, only age-related decreases were observed across the whole connectome during resting-state. While vocabulary accuracy increased with age, no interaction was found between functional connectivity, age and task accuracy or proxies of cognitive reserve, suggesting that older individuals typically benefits from semantic knowledge accumulated throughout one's life trajectory, without the need for compensatory mechanisms.
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Affiliation(s)
- Perrine Ferré
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Université de Montréal, 4545 Queen Mary Road, Montréal, Qc, H3W 1W3, CANADA
| | - Yassine Benhajali
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Université de Montréal, 4545 Queen Mary Road, Montréal, Qc, H3W 1W3, CANADA
| | - Jason Steffener
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Université de Montréal, 4545 Queen Mary Road, Montréal, Qc, H3W 1W3, CANADA
- PERFORM Center, Concordia University
- Interdisciplinary School of Health Sciences, University of Ottawa, 200 Lees, Lees Campus, Office # E-250C, Ottawa, Ontario. K1S 5S9, CANADA
| | - Yaakov Stern
- Cognitive Neuroscience Division, Columbia University, 710 W 168th St, New York, NY 10032, USA
| | - Yves Joanette
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Université de Montréal, 4545 Queen Mary Road, Montréal, Qc, H3W 1W3, CANADA
| | - Pierre Bellec
- Centre de recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Université de Montréal, 4545 Queen Mary Road, Montréal, Qc, H3W 1W3, CANADA
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Zhai J, Li K. Predicting Brain Age Based on Spatial and Temporal Features of Human Brain Functional Networks. Front Hum Neurosci 2019; 13:62. [PMID: 30863296 PMCID: PMC6399206 DOI: 10.3389/fnhum.2019.00062] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 02/05/2019] [Indexed: 12/01/2022] Open
Abstract
The organization of human brain networks can be measured by capturing correlated brain activity with functional MRI data. There have been a variety of studies showing that human functional connectivities undergo an age-related change over development. In the present study, we employed resting-state functional MRI data to construct functional network models. Principal component analysis was performed on the FC matrices across all the subjects to explore meaningful components especially correlated with age. Coefficients across the components, edge features after a newly proposed feature reduction method as well as temporal features based on fALFF, were extracted as predictor variables and three different regression models were learned to make prediction of brain age. We observed that individual's functional network architecture was shaped by intrinsic component, age-related component and other components and the predictive models extracted sufficient information to provide comparatively accurate predictions of brain age.
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Affiliation(s)
- Jian Zhai
- School of Mathematical Science, Zhejiang University, Hangzhou, China
| | - Ke Li
- School of Mathematical Science, Zhejiang University, Hangzhou, China
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Finn ES, Scheinost D, Finn DM, Shen X, Papademetris X, Constable RT. Can brain state be manipulated to emphasize individual differences in functional connectivity? Neuroimage 2017; 160:140-151. [PMID: 28373122 PMCID: PMC8808247 DOI: 10.1016/j.neuroimage.2017.03.064] [Citation(s) in RCA: 193] [Impact Index Per Article: 27.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 03/14/2017] [Accepted: 03/21/2017] [Indexed: 02/07/2023] Open
Abstract
While neuroimaging studies typically collapse data from many subjects, brain functional organization varies between individuals, and characterizing this variability is crucial for relating brain activity to behavioral phenotypes. Rest has become the default state for probing individual differences, chiefly because it is easy to acquire and a supposed neutral backdrop. However, the assumption that rest is the optimal condition for individual differences research is largely untested. In fact, other brain states may afford a better ratio of within- to between-subject variability, facilitating biomarker discovery. Depending on the trait or behavior under study, certain tasks may bring out meaningful idiosyncrasies across subjects, essentially enhancing the individual signal in networks of interest beyond what can be measured at rest. Here, we review theoretical considerations and existing work on how brain state influences individual differences in functional connectivity, present some preliminary analyses of within- and between-subject variability across conditions using data from the Human Connectome Project, and outline questions for future study.
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Affiliation(s)
- Emily S Finn
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA.
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Daniel M Finn
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
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Schlesinger KJ, Turner BO, Lopez BA, Miller MB, Carlson JM. Age-dependent changes in task-based modular organization of the human brain. Neuroimage 2017; 146:741-762. [DOI: 10.1016/j.neuroimage.2016.09.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Revised: 08/14/2016] [Accepted: 09/01/2016] [Indexed: 02/08/2023] Open
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Bas-Hoogendam JM, Blackford JU, Brühl AB, Blair KS, van der Wee NJ, Westenberg PM. Neurobiological candidate endophenotypes of social anxiety disorder. Neurosci Biobehav Rev 2016; 71:362-378. [DOI: 10.1016/j.neubiorev.2016.08.040] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Revised: 07/15/2016] [Accepted: 08/31/2016] [Indexed: 02/07/2023]
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