Topic: excitation-inhibition balance

Nicolas Brunel discusses excitation-inhibition balance and mathematical explanations of irregular activity in cortical networks.

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide

Background: The balance of excitation and inhibition (E-I) is a key functional property of cortical microcircuits [1] which changes through lifespan. Adolescence is considered a crucial period for the maturation of E-I balance [2,3]. This has been primarily observed in animal studies, and human in vivo evidence on adolescent maturation of the E-I balance at an individual level is limited. Here, we investigated an in vivo marker of regional E-I balance in human adolescents based on individualized biophysical network models. Methods: Regional E-I balance was estimated using large-scale simulati

Background: Biophysical network modeling (BNM) of the brain is a promising technique for bridging macro- and microscale levels of investigation, enabling inferences about latent features of brain activity such as excitation-inhibition balance. This approach allows personalized models of the brain to be fitted to individual subjects’ imaging data through parameter optimization [1, 2]. However, the process typically requires several thousand simulations per subject, making it computationally expensive and limiting its scalability to larger subject pools and more complex models. To address this,