Brain Network Simulations Indicate Effects of Neuregulin-1 Genotype on Excitation-Inhibition Balance in Cortical Dynamics

Author:

Klein Pedro Costa1,Ettinger Ulrich2,Schirner Michael34,Ritter Petra34,Rujescu Dan5,Falkai Peter6,Koutsouleris Nikolaos6,Kambeitz-Ilankovic Lana16,Kambeitz Joseph1

Affiliation:

1. Department of Psychiatry, University of Cologne, Faculty of Medicine and University Hospital Cologne, 50937, Germany

2. Department of Psychology, University of Bonn, Bonn, 53111, Germany

3. Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Dept. of Neurology, 10117, Germany

4. Bernstein Focus State Dependencies of Learning & Bernstein Center for Computational Neuroscience, Berlin 10115, Germany

5. University Clinic for Psychiatry, Psychotherapy and Psychosomatic, Martin-Luther-University, Halle-Wittenberg, 06112, Germany

6. Department of Psychiatry, Ludwig Maximilians Universität München, 80336, Germany

Abstract

Abstract Neuregulin-1 (NRG1) represents an important factor for multiple processes including neurodevelopment, brain functioning or cognitive functions. Evidence from animal research suggests an effect of NRG1 on the excitation-inhibition (E/I) balance in cortical circuits. However, direct evidence for the importance of NRG1 in E/I balance in humans is still lacking. In this work, we demonstrate the application of computational, biophysical network models to advance our understanding of the interaction between cortical activity observed in neuroimaging and the underlying neurobiology. We employed a biophysical neuronal model to simulate large-scale brain dynamics and to investigate the role of polymorphisms in the NRG1 gene (rs35753505, rs3924999) in n = 96 healthy adults. Our results show that G/G-carriers (rs3924999) exhibit a significant difference in global coupling (P = 0.048) and multiple parameters determining E/I-balance such as excitatory synaptic coupling (P = 0.047), local excitatory recurrence (P = 0.032) and inhibitory synaptic coupling (P = 0.028). This indicates that NRG1 may be related to excitatory recurrence or excitatory synaptic coupling potentially resulting in altered E/I-balance. Moreover, we suggest that computational modeling is a suitable tool to investigate specific biological mechanisms in health and disease.

Funder

H2020 Research and Innovation Action grants VirtualBrainCloud

Human Brain Project

ERC Consolidator

German Research Foundation

Berlin Institute of Health & Foundation Charité; Johanna Quandt Excellence Initiative

Gauss Centre for Supercomputing

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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