Synchrony, metastability, dynamic integration, and competition in the spontaneous functional connectivity of the human brain

Abstract Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31–42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.

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Task-switching Cost and Intrinsic Functional Connectivity in the Human Brain: Toward Understanding Individual Differences in Cognitive Flexibility

PLoS ONE ◽

10.1371/journal.pone.0145826 ◽

2015 ◽

Vol 10 (12) ◽

pp. e0145826 ◽

Cited By ~ 12

Author(s):

Shouhang Yin ◽

Ting Wang ◽

Weigang Pan ◽

Yijun Liu ◽

Antao Chen

Keyword(s):

Individual Differences ◽

Functional Connectivity ◽

Human Brain ◽

Cognitive Flexibility ◽

Task Switching ◽

Switching Cost ◽

Intrinsic Functional Connectivity

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Comparing the temporal relationship of structural and functional connectivity changes in different adult human brain networks: a single-case study

Wellcome Open Research ◽

10.12688/wellcomeopenres.14572.1 ◽

2018 ◽

Vol 3 ◽

pp. 50 ◽

Cited By ~ 1

Author(s):

Takamitsu Watanabe ◽

Geraint Rees

Keyword(s):

Functional Connectivity ◽

Human Brain ◽

Large Scale ◽

Single Case ◽

Brain Networks ◽

Structural Connectivity ◽

Time Lags ◽

Single Case Study ◽

Adult Human

Background: Despite accumulated evidence for adult brain plasticity, the temporal relationships between large-scale functional and structural connectivity changes in human brain networks remain unclear. Methods: By analysing a unique richly detailed 19-week longitudinal neuroimaging dataset, we tested whether macroscopic functional connectivity changes lead to the corresponding structural alterations in the adult human brain, and examined whether such time lags between functional and structural connectivity changes are affected by functional differences between different large-scale brain networks. Results: In this single-case study, we report that, compared to attention-related networks, functional connectivity changes in default-mode, fronto-parietal, and sensory-related networks occurred in advance of modulations of the corresponding structural connectivity with significantly longer time lags. In particular, the longest time lags were observed in sensory-related networks. In contrast, such significant temporal differences in connectivity change were not seen in comparisons between anatomically categorised different brain areas, such as frontal and occipital lobes. These observations survived even after multiple validation analyses using different connectivity definitions or using parts of the datasets. Conclusions: Although the current findings should be examined in independent datasets with different demographic background and by experimental manipulation, this single-case study indicates the possibility that plasticity of macroscopic brain networks could be affected by cognitive and perceptual functions implemented in the networks, and implies a hierarchy in the plasticity of functionally different brain systems.

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Distinct cortical systems reinstate the content and context of episodic memories

10.1101/2020.08.20.248567 ◽

2020 ◽

Author(s):

James E. Kragel ◽

Youssef Ezzyat ◽

Bradley C. Lega ◽

Michael R. Sperling ◽

Gregory A. Worrell ◽

...

Keyword(s):

Free Recall ◽

Functional Connectivity ◽

Human Brain ◽

Semantic Content ◽

Cortical Activity ◽

Temporal Context ◽

Cortical Networks ◽

Semantic Organization ◽

Episodic Memories

AbstractEpisodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. We identified dissociable cortical networks via functional connectivity that uniquely reinstated semantic content and temporal context of previously studied stimuli during free recall. Network-specific reinstatement predicted the temporal and semantic organization of recall sequences, demonstrating how specialized cortical systems enable the human brain to target specific memories.

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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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