Schedule of Events | Symposia

Precision Brain Modeling Reveals a Bifurcation Mechanism and Local Circuitry Underlying Individual Differences

Poster Session F - Tuesday, April 1, 2025, 8:00 – 10:00 am EDT, Back Bay Ballroom/Republic Ballroom

Matthew Singh^1,2, ShiNung Ching³, Todd Braver³; ¹University of Illinois, Urbana-Champaign, ²The Beckman Institute for Advanced Science and Technology, ³Washington University in St. Louis

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics (“precision brain models") and making quantitative predictions. We extensively validate the models' performance in forecasting future brain activity and predicting individual variability in key M/EEG metrics. We then resolve a dynamical systems mechanisms whereby variation in inhibitory connection strength generate a sudden shift in attractor topology—from equilibria to limit-cycles (stable oscillations). Individuals straddle this bifurcation boundary at resting-state (some with equilibria, some with limit cycles). Surprisingly, this distinction is the strongest predictor of individual differences in alpha and beta power at rest. Interestingly, it even differentiates slight age groups (early 20s vs. early 30s) with accompanying changes in spectral power distribution. We highlight implications for personalized neurostimulation and cognitive-enhancement through simulated optimal-treatments. Together, these findings highlight the potential of precision brain models to inform the neuroscience of individual differences.

Topic Area: METHODS: Other