Adolescent development of multiscale cortical wiring and functional connectivity in the human connectome

Adolescence is a time of profound changes in the structural wiring of the brain and maturation of large-scale functional interactions. Here, we analyzed structural and functional brain network development in an accelerated longitudinal cohort spanning 14-25 years (n = 199). Core to our work was an advanced model of cortical wiring that incorporates multimodal MRI features of (i) cortico-cortical proximity, (ii) microstructural similarity, and (iii) diffusion tractography. Longitudinal analyses assessing age-related changes in cortical wiring during adolescence identified increases in cortical wiring within attention and default-mode networks, as well as between transmodal and attention, and sensory and limbic networks, indicative of a continued differentiation of cortico-cortical structural networks. Cortical wiring changes were statistically independent from age-related cortical thinning seen in the same subjects. Conversely, resting-state functional MRI analysis in the same subjects indicated an increasing segregation of sensory and transmodal systems during adolescence, with age-related reductions in their functional connectivity alongside with an increase in structural wiring distance. Our findings provide new insights into adolescent brain network development, illustrating how the maturation of structural wiring interacts with the development of macroscale network function.

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Functional brain network reconfiguration during learning in a dynamic environment

10.1101/800284 ◽

2019 ◽

Cited By ~ 1

Author(s):

Chang-Hao Kao ◽

Ankit N. Khambhati ◽

Danielle S. Bassett ◽

Matthew R. Nassar ◽

Joseph T. McGuire ◽

...

Keyword(s):

Functional Connectivity ◽

Large Scale ◽

Functional Integration ◽

Dynamic Environment ◽

Brain Network ◽

Uncertain Environments ◽

Whole Brain ◽

Functional Brain Network ◽

Brain Pattern ◽

Brain Functional Connectivity

AbstractWhen learning about dynamic and uncertain environments, people should update their beliefs most strongly when new evidence is most informative, such as when the environment undergoes a surprising change or existing beliefs are highly uncertain. Here we show that modulations of surprise and uncertainty are encoded in a particular, temporally dynamic pattern of whole-brain functional connectivity, and this encoding is enhanced in individuals that adapt their learning dynamics more appropriately in response to these factors. The key feature of this whole-brain pattern of functional connectivity is stronger connectivity, or functional integration, between the fronto-parietal and other functional systems. Our results provide new insights regarding the association between dynamic adjustments in learning and dynamic, large-scale changes in functional connectivity across the brain.

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Age-related changes in spatial and temporal features of resting state fMRI

10.1101/109181 ◽

2017 ◽

Author(s):

Shruti G. Vij ◽

Jason S. Nomi ◽

Dina R. Dajani ◽

Lucina Q. Uddin

Keyword(s):

Resting State ◽

Large Scale ◽

Spectral Composition ◽

Brain Network ◽

Functional Networks ◽

Functional Changes ◽

Age Related ◽

Temporal Features ◽

Functional Brain Network ◽

Age Related Changes

AbstractDevelopment and aging are associated with functional changes in the brain across the lifespan. These changes can be detected in spatial and temporal features of resting state functional MRI (rs-fMRI) data. Independent vector analysis (IVA) is a whole-brain multivariate approach that can be used to comprehensively assess these changes in spatial and temporal features. We present a multi-dimensional approach to assessing age-related changes in spatial and temporal features of statistically independent components identified by IVA in a cross-sectional lifespan sample (ages 6-85 years). We show that while large-scale brain network configurations remain consistent throughout the lifespan, changes continue to occur in both local organization and in the spectral composition of these functional networks. We show that the spatial extent of functional networks decreases with age, but with no significant change in the peak functional loci of these networks. Additionally, we show differential age-related patterns across the frequency spectrum; lower frequency correlations decrease across the lifespan whereas higher-frequency correlations increase. These changes indicate an increasing stability of networks with age. In addition to replicating results from previous studies, the current results uncover new aspects of functional brain network changes across the lifespan that are frequency band-dependent.

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Age-related changes in functional connectivity between young adulthood and late adulthood

Analytical Methods ◽

10.1039/c5ay00699f ◽

2015 ◽

Vol 7 (10) ◽

pp. 4111-4122 ◽

Cited By ~ 4

Author(s):

Xin Xu ◽

Qifan Kuang ◽

Yongqing Zhang ◽

Huijun Wang ◽

Zhining Wen ◽

...

Keyword(s):

Functional Connectivity ◽

Young Adulthood ◽

Brain Network ◽

Late Adulthood ◽

Functional Brain ◽

Age Related ◽

Functional Brain Network ◽

Significant Difference ◽

Network Metrics ◽

Age Related Changes

The functional brain network in late adulthood has been found to show a significant difference from that in young adulthood using a variety of network metrics.

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Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

eLife ◽

10.7554/elife.32696 ◽

2018 ◽

Vol 7 ◽

Cited By ~ 4

Author(s):

Ruedeerat Keerativittayayut ◽

Ryuta Aoki ◽

Mitra Taghizadeh Sarabi ◽

Koji Jimura ◽

Kiyoshi Nakahara

Keyword(s):

Functional Connectivity ◽

Human Brain ◽

Large Scale ◽

Brain Regions ◽

Brain Network ◽

Time Varying ◽

Memory Encoding ◽

Graph Metrics ◽

Connectivity Patterns ◽

Network States

Although activation/deactivation of specific brain regions has been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here, we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.

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Altered Functional Connectivity after Epileptic Seizure Revealed by Scalp EEG

Neural Plasticity ◽

10.1155/2020/8851415 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8

Author(s):

Yi Liang ◽

Chunli Chen ◽

Fali Li ◽

Dezhong Yao ◽

Peng Xu ◽

...

Keyword(s):

Functional Connectivity ◽

Brain Activity ◽

Epileptic Seizures ◽

Local Area ◽

Brain Network ◽

Fuzzy Entropy ◽

Clustering Coefficient ◽

Characteristic Path Length ◽

Functional Brain Network ◽

Before And After

Epileptic seizures are considered to be a brain network dysfunction, and chronic recurrent seizures can cause severe brain damage. However, the functional brain network underlying recurrent epileptic seizures is still left unveiled. This study is aimed at exploring the differences in a related brain activity before and after chronic repetitive seizures by investigating the power spectral density (PSD), fuzzy entropy, and functional connectivity in epileptic patients. The PSD analysis revealed differences between the two states at local area, showing postseizure energy accumulation. Besides, the fuzzy entropies of preseizure in the frontal, central, and temporal regions are higher than that of postseizure. Additionally, attenuated long-range connectivity and enhanced local connectivity were also found. Moreover, significant correlations were found between network metrics (i.e., characteristic path length and clustering coefficient) and individual seizure number. The PSD, fuzzy entropy, and network analysis may indicate that the brain is gradually impaired along with the occurrence of epilepsy, and the accumulated effect of brain impairment is observed in individuals with consecutive epileptic bursts. The findings of this study may provide helpful insights into understanding the network mechanism underlying chronic recurrent epilepsy.

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Individual Variation in Functional Brain Network Topography is Linked to Schizophrenia Symptomatology

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa088 ◽

2020 ◽

Author(s):

Uzma Nawaz ◽

Ivy Lee ◽

Adam Beermann ◽

Shaun Eack ◽

Matcheri Keshavan ◽

...

Keyword(s):

Individual Differences ◽

Functional Connectivity ◽

Negative Symptom ◽

Individual Variation ◽

Symptom Severity ◽

Spatial Organization ◽

Brain Connectivity ◽

Brain Network ◽

Brain Organization ◽

Functional Brain Network

Abstract Resting-state fMRI (rsfMRI) demonstrates that the brain is organized into distributed networks. Numerous studies have examined links between psychiatric symptomatology and network functional connectivity. Traditional rsfMRI analyses assume that the spatial organization of networks is invariant between individuals. This dogma has recently been overturned by the demonstration that networks show significant variation between individuals. We tested the hypothesis that previously observed relationships between schizophrenia-negative symptom severity and network connectivity are actually due to individual differences in network spatial organization. Forty-four participants diagnosed with schizophrenia underwent rsfMRI scans and clinical assessments. A multivariate pattern analysis determined how whole-brain functional connectivity correlates with negative symptom severity at the individual voxel level. Brain connectivity to a region of the right dorsolateral prefrontal cortex correlates with negative symptom severity. This finding results from individual differences in the topographic distribution of 2 networks: the default mode network (DMN) and the task-positive network (TPN). Both networks demonstrate strong (r = ~0.49) and significant (P < .001) relationships between topography and symptom severity. For individuals with low symptom severity, this critical region is part of the DMN. In highly symptomatic individuals, this region is part of the TPN. Previously overlooked individual variation in brain organization is tightly linked to differences in schizophrenia symptom severity. Recognizing critical links between network topography and pathological symptomology may identify key circuits that underlie cognitive and behavioral phenotypes. Individual variation in network topography likely guides different responses to clinical interventions that rely on anatomical targeting (eg, transcranial magnetic stimulation [TMS]).

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Large-Scale Functional Brain Network Architecture Changes Associated With Trauma-Related Dissociation

American Journal of Psychiatry ◽

10.1176/appi.ajp.2020.19060647 ◽

2020 ◽

pp. appi.ajp.2020.1

Author(s):

Lauren A.M. Lebois ◽

Meiling Li ◽

Justin T. Baker ◽

Jonathan D. Wolff ◽

Danhong Wang ◽

...

Keyword(s):

Network Architecture ◽

Large Scale ◽

Brain Network ◽

Functional Brain ◽

Functional Brain Network

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Dynamic Reorganization of the Cortical Functional Brain Network in Affective Processing and Cognitive Reappraisal

International Journal of Neural Systems ◽

10.1142/s0129065720500513 ◽

2020 ◽

Vol 30 (10) ◽

pp. 2050051

Author(s):

Feng Fang ◽

Thomas Potter ◽

Thinh Nguyen ◽

Yingchun Zhang

Keyword(s):

Emotion Regulation ◽

Large Scale ◽

Brain Networks ◽

Cognitive Reappraisal ◽

Brain Network ◽

Affective Processing ◽

Functional Brain ◽

Affective Stimuli ◽

Functional Brain Network ◽

Functional Brain Networks

Emotion and affect play crucial roles in human life that can be disrupted by diseases. Functional brain networks need to dynamically reorganize within short time periods in order to efficiently process and respond to affective stimuli. Documenting these large-scale spatiotemporal dynamics on the same timescale they arise, however, presents a large technical challenge. In this study, the dynamic reorganization of the cortical functional brain network during an affective processing and emotion regulation task is documented using an advanced multi-model electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) technique. Sliding time window correlation and [Formula: see text]-means clustering are employed to explore the functional brain connectivity (FC) dynamics during the unaltered perception of neutral (moderate valence, low arousal) and negative (low valence, high arousal) stimuli and cognitive reappraisal of negative stimuli. Betweenness centralities are computed to identify central hubs within each complex network. Results from 20 healthy subjects indicate that the cortical mechanism for cognitive reappraisal follows a ‘top-down’ pattern that occurs across four brain network states that arise at different time instants (0–170[Formula: see text]ms, 170–370[Formula: see text]ms, 380–620[Formula: see text]ms, and 620–1000[Formula: see text]ms). Specifically, the dorsolateral prefrontal cortex (DLPFC) is identified as a central hub to promote the connectivity structures of various affective states and consequent regulatory efforts. This finding advances our current understanding of the cortical response networks of reappraisal-based emotion regulation by documenting the recruitment process of four functional brain sub-networks, each seemingly associated with different cognitive processes, and reveals the dynamic reorganization of functional brain networks during emotion regulation.

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Neurocognitive Aging and Functional Connectivity Using Functional Magnetic Resonance Imaging

Oxford Research Encyclopedia of Psychology ◽

10.1093/acrefore/9780190236557.013.385 ◽

2018 ◽

Author(s):

Hana Burianová

Keyword(s):

Functional Connectivity ◽

Cognitive Processes ◽

Large Scale ◽

Healthy Aging ◽

Brain Activity ◽

Brain Regions ◽

Effective Strategies ◽

Cognitive Improvement ◽

Age Related ◽

Neurocognitive Aging

Determining the mechanisms that underlie neurocognitive aging, such as compensation or dedifferentiation, and facilitating the development of effective strategies for cognitive improvement is essential due to the steadily rising aging population. One approach to study the characteristics of healthy aging comprises the assessment of functional connectivity, delineating markers of age-related neurocognitive plasticity. Functional connectivity paradigms characterize complex one-to-many (or many-to-many) structure–function relations, as higher-level cognitive processes are mediated by the interaction among a number of functionally related neural areas rather than localized to discrete brain regions. Task-related or resting-state interregional correlations of brain activity have been used as reliable indices of functional connectivity, delineating age-related alterations in a number of large-scale brain networks, which subserve attention, working memory, episodic retrieval, and task-switching. Together with behavioral and regional activation studies, connectivity studies and modeling approaches have contributed to our understanding of the mechanisms of age-related reorganization of distributed functional networks; specifically, reduced neural specificity (dedifferentiation) and associated impairment in inhibitory control and compensatory neural recruitment.

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