Intracranial Electrophysiology Reveals Reproducible Intrinsic Functional Connectivity within Human Brain Networks

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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Discriminative Analysis of Symptom Severity and Ultra-High Risk of Schizophrenia Using Intrinsic Functional Connectivity

International Journal of Neural Systems ◽

10.1142/s0129065720500471 ◽

2020 ◽

Vol 30 (09) ◽

pp. 2050047

Author(s):

Lubin Wang ◽

Xianbin Li ◽

Yuyang Zhu ◽

Bei Lin ◽

Qijing Bo ◽

...

Keyword(s):

High Risk ◽

Functional Connectivity ◽

Symptom Severity ◽

Large Scale ◽

Brain Networks ◽

Brain Regions ◽

Support Vector ◽

Healthy Controls ◽

Intrinsic Functional Connectivity ◽

Ultra High Risk

Past studies have consistently shown functional dysconnectivity of large-scale brain networks in schizophrenia. In this study, we aimed to further assess whether multivariate pattern analysis (MVPA) could yield a sensitive predictor of patient symptoms, as well as identify ultra-high risk (UHR) stage of schizophrenia from intrinsic functional connectivity of whole-brain networks. We first combined rank-based feature selection and support vector machine methods to distinguish between 43 schizophrenia patients and 52 healthy controls. The constructed classifier was then applied to examine functional connectivity profiles of 18 UHR individuals. The classifier indicated reliable relationship between MVPA measures and symptom severity, with higher classification accuracy in more severely affected schizophrenia patients. The UHR subjects had classification scores falling between those of healthy controls and patients, suggesting an intermediate level of functional brain abnormalities. Moreover, UHR individuals with schizophrenia-like connectivity profiles at baseline presented higher rate of conversion to full-blown illness in the follow-up visits. Spatial maps of discriminative brain regions implicated increases of functional connectivity in the default mode network, whereas decreases of functional connectivity in the cerebellum, thalamus and visual areas in schizophrenia. The findings may have potential utility in the early diagnosis and intervention of schizophrenia.

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