Brain dynamics: the temporal variability of connectivity, and differences in schizophrenia and ADHD

Edmund T Rolls,Jianfeng Feng,Wei Cheng

doi:10.1038/s41398-021-01197-x

Abstract

We describe advances in the understanding of brain dynamics that are important for understanding the operation of the cerebral cortex in health and disease. In data from 1017 participants from the Human Connectome Project, we show that early visual and connected areas have low temporal variability of their functional connectivity. We show that a low temporal variability of the connectivity of cortical areas is related to high mean functional connectivity between those areas, and provide an account of how these dynamics arise. We then investigate how these concepts help to understand brain dynamics in mental disorders. We find that in both first episode and long-term schizophrenia, reduced functional connectivity of early visual and related temporal cortex areas is associated with increased temporal variability of the functional connectivity, consistent with decreased stability of attractor networks related to sensory processing. In ADHD, we find these functional connectivities are increased and their temporal variability is decreased, and relate this to increased engagement with visual sensory input as manifest in high screen time usage in ADHD. We further show that these differences in the dynamics of the cortex in schizophrenia, and ADHD can be related to differences in the functional connectivity of the specific sensory vs. association thalamic nuclei. These discoveries help to advance our understanding of cortical operation in health, and in some mental disorders.

Highlights

Resting-state functional magnetic resonance imaging techniques have contributed significantly to our understanding of brain activity, both in health and disease[1,2,3,4]
The high functional connectivity between them makes them all tend to move together dynamically, because of their strong connections with each other, keeping the temporal variability measure low. This contrasts with other areas such as the hippocampus and parahippocampal gyrus, amygdala, and orbitofrontal cortex that have high temporal variability of the functional connectivity, relating it is suggested to their connections with many brain regions, and can all move independently of each other dynamically, because they have connections with many brain areas
We found in four replications with different datasets (Figs. 1–4) that the temporal variability of the functional connectivity of different anatomical labeling atlas 3 (AAL3) brain regions is low in areas such as the early visual cortical areas with high mean functional connectivity with each other (Fig. 1C); and is high in areas such as the orbitofrontal cortex, amygdala, and hippocampus which have relatively low functional connectivity with early visual cortical areas, as well as connectivity with a number of different brain regions in a hub-like way (Fig. 1C)

Summary

Introduction

Resting-state functional magnetic resonance imaging (rs-fMRI) techniques have contributed significantly to our understanding of brain activity, both in health and disease[1,2,3,4]. Classical methods are based on the continuous fluctuation of the brain blood oxygen level dependent (BOLD) signal. Functional connectivities (FC) can be measured between spatially separated brain regions, in terms of correlation, coherence, and spatial grouping based on temporal similarities[5]. The dynamical fluctuations of the BOLD signals, and how they relate to interactions between brain. When we made progress with addressing these aims in a large-scale investigation using data from 1017 participants from the Human Connectome Project (HCP), we wished to further test the hypotheses, and assess their utility, by examining data from participants with mental disorders, who might have differences in the measures investigated, and which might help to support the answers provided by investigation of the healthy volunteers in the HCP dataset. We hoped that investigation in these participants with the mental disorders schizophrenia and ADHD might help to elucidate how differences in brain dynamics may be related to these disorders.

Methods

Results

Discussion

Conclusion