Deep inverse modeling reveals dynamic-dependent invariances in neural circuit mechanisms
Richard Gao, Michael Deistler, Auguste Schulz, Pedro Goncalves, Jakob Macke · COSYNE 2025
Neural population dynamics are shaped by many cellular, synaptic, and network properties. Not only is it important to understand how coordinated changes in circuit parameters alter neural activity, but also when dynamics are unaffected by---or invariant to---such changes. Computational modeling has revealed invariances in single neurons and small circuits that are thought to reflect their robustness against variability and perturbations. However, generalizing these insights to larger circuits in cortex and other brain areas remains challenging. A key bottleneck lies in inverse modeling of neur
ePoster · Neuroscience