Holz, N. | Search bioRxiv

bioRxiv2024

Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modeling

The balance of excitation and inhibition is a key functional property of cortical microcircuits which changes through the lifespan. Adolescence is considered a crucial period for the maturation of excitation-inhibition balance. This has been primarily observed in animal studies, yet human in vivo evidence on adolescent maturation of the excitation-inhibition balance at the individual level is limited. Here, we developed an individualized in vivo marker of regional excitation-inhibition balance in human adolescents, estimated using large-scale simulations of biophysical network models fitted to resting-state functional magnetic resonance imaging data from two independent cross-sectional (N = 752) and longitudinal (N = 149) cohorts. We found a widespread relative increase of inhibition in association cortices paralleled by a relative age-related increase of excitation, or lack of change, in sensorimotor areas across both datasets. This developmental pattern co-aligned with multiscale markers of sensorimotor-association differentiation. The spatial pattern of excitation-inhibition development in adolescence was robust to inter-individual variability of structural connectomes and modeling configurations. Notably, we found that alternative simulation-based markers of excitation-inhibition balance show a variable sensitivity to maturational change. Taken together, our study highlights an increase of inhibition during adolescence in association areas using cross sectional and longitudinal data, and provides a robust computational framework to estimate microcircuit maturation in vivo at the individual level.

neuroscience↗

bioRxiv2023

Early life adversities affect expected value signaling in the adult brain

BackgroundEarly adverse experiences are assumed to affect fundamental processes of reward learning and decision-making. However, computational neuroimaging studies investigating these circuits are sparse and limited to studies that investigated adversities retrospectively in adolescent samples. MethodsWe used prospective data from a longitudinal birth cohort study (n=156, 87 females, mean age=32.2) to investigate neurocomputational components underlying reinforcement learning in an fMRI-based passive avoidance task. We applied a principal component analysis to capture common variation across seven prenatal and postnatal adversity measures. The resulting adversity factors (factor 1: postnatal psychosocial adversities and prenatal maternal smoking, factor 2: prenatal maternal stress and obstetric adversity, and factor 3: lower maternal stimulation) and single adversity measures were then linked to computational markers of reward learning (i.e. expected value, prediction errors) in the core reward network. ResultsUsing the adversity factors, we found that adversities were linked to lower expected value representation in striatum, ventromedial prefrontal cortex (vmPFC) and anterior cingulate cortex (ACC). Expected value encoding in vmPFC further mediated the relationship between adversities and psychopathology. In terms of specific adversity effects, we found that obstetric adversity was associated with lower prediction error signaling in the vmPFC and ACC, whereas lower maternal stimulation was related to lower expected value encoding in the striatum, vmPFC, and ACC. ConclusionsOur results suggested that adverse experiences have a long-term disruptive effect on reward learning in several important reward-related brain regions, which can be associated with non-optimal decision-making and thereby increase the vulnerability of developing psychopathology.

neuroscience↗