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Biophysical models reveal distinct role of parietal lobe and sensory regions in the emergence of FC

Poster No:

1731 

Submission Type:

Abstract Submission 

Authors:

Songjun Peng1, Xinran Wu1, Yunman Xia1, Jie Zhang1

Institutions:

1Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China

First Author:

Songjun Peng  
Institute of Science and Technology for Brain-inspired Intelligence, Fudan University
Shanghai, China

Co-Author(s):

Xinran Wu  
Institute of Science and Technology for Brain-inspired Intelligence, Fudan University
Shanghai, China
Yunman Xia  
Institute of Science and Technology for Brain-inspired Intelligence, Fudan University
Shanghai, China
Jie Zhang  
Institute of Science and Technology for Brain-inspired Intelligence, Fudan University
Shanghai, China
E-Poster

Introduction:

Brain function emerges from the complex multi-scale neural networks(Suárez et al., 2020). However, how neural dynamics characteristics (such as excitation-inhibition balance of neural networks) at the micro-scale shape the non-linear dependence between structural connectivity and functional connectivity(FC) at the macro-scale, and eventually lead to the emergence of functional activities from structural connectivity, is still unclear.

Methods:

To explore the role of excitation-inhibition balance in the emergence of resting-state whole-brain functional connectivity patterns, we built brain network models based on group-averaged structural connectivity(Kong et al., 2021) and dynamic mean field models(Deco et al., 2014) to predict group-averaged resting-state functional connectivity, and then conducted modulations of global and local excitation-inhibition ratios on the models. The group-averaged connectivities were derived from MRI data of the Human Connectome Project (HCP) S1200 release(Van Essen et al., 2013)

Results:

Simulations found that changes of global excitation-inhibition ratio can lead to significant changes in whole-brain functional connectivity. In this process, two core subnetworks distributed in frontal and parietal lobes respectively, consisting of rich-club nodes(Heuvel & Sporns, 2011) and high-weighted edges, play a dominant role. Analysis of local excitation-inhibition ratio modulations shows that the emergence of resting-state functional connectivity relies on the levels of excitation in parietal lobe (superior parietal lobe, inferior parietal lobe and precuneus) and sensory regions. Specifically, when the parietal lobe is in the intermediate state between excitation and inhibition, which is sensitive to external perturbations, and the sensory regions is in the excited state, the brain network models can better simulate resting-state functional connectivity. In addition, meta-analysis based on neurosynth(Yarkoni et al., 2011) showed that activities in parietal lobe are related to higher-order cognitive functions of top-down processing.

Conclusions:

The study demonstrates the significant impact of the excitation-inhibition balance of local neural circuits on the patterns of resting-state whole-brain function under the topological constraints of structural connectivity, and the selective dependence of the emergence of resting-state functional connectivity on different dynamic states in higher-order brain regions and sensory regions. It provides a reference for further understanding the mechanisms of emergence of resting-state functional connectivity and the underlying cognitive processes.

Modeling and Analysis Methods:

Connectivity (eg. functional, effective, structural) 2
fMRI Connectivity and Network Modeling 1

Keywords:

Computational Neuroscience
Other - Structure-function relationship

1|2Indicates the priority used for review
Supporting Image: Figure.png
 

Provide references using author date format

Deco, G., Ponce-Alvarez, A., Hagmann, P., Romani, G.L., Mantini, D. & Corbetta, M. (2014) ‘How Local Excitation–Inhibition Ratio Impacts the Whole Brain Dynamics’, Journal of Neuroscience, 34(23), pp. 7886–7898.
Heuvel, M.P. van den & Sporns, O. (2011) ‘Rich-Club Organization of the Human Connectome’, Journal of Neuroscience, 31(44), pp. 15775–15786.
Kong, X., Kong, R., Orban, C., Wang, P., Zhang, S., Anderson, K., Holmes, A., Murray, J.D., Deco, G., van den Heuvel, M. & Yeo, B.T.T. (2021) ‘Sensory-motor cortices shape functional connectivity dynamics in the human brain’, Nature Communications, 12(1), p. 6373.
Suárez, L.E., Markello, R.D., Betzel, R.F. & Misic, B. (2020) ‘Linking Structure and Function in Macroscale Brain Networks’, Trends in Cognitive Sciences, 24(4), pp. 302–315.
Van Essen, D.C., Smith, S.M., Barch, D.M., Behrens, T.E.J., Yacoub, E. & Ugurbil, K. (2013) ‘The WU-Minn Human Connectome Project: An overview’, NeuroImage, 80pp. 62–79.
Yarkoni, T., Poldrack, R.A., Nichols, T.E., Van Essen, D.C. & Wager, T.D. (2011) ‘Large-scale automated synthesis of human functional neuroimaging data’, Nature Methods, 8(8), pp. 665–670.