Brain network simulations indicate effects of neuregulin-1 genotype on excitation-inhibition balance in cortical dynamics

Pedro Costa Klein, Ulrich Ettinger, Michael Schirner, Petra Ritter, Dan Rujescu, Peter Falkai, Nikolaos Koutsouleris, Lana Kambeitz-Ilankovic, Joseph Kambeitz

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.

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Cereb Cortex. 31(4):2013-2025 (2020)


brain stimulationcomputational neuroscienceDynamic Mean Field Modelexcitatory/inhibitory balanceneuregulin-1
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