Optimizing Biophysical Large-Scale Brain Circuit Models With Deep Neural Networks.

ABSTRACT: Biophysical modeling provides mechanistic insights into brain function, from single-neuron dynamics to large-scale circuit models bridging macro-scale brain activity with microscale measurements. Biophysical models are governed by biologically meaningful parameters, many of which can be experimentally measured. Some parameters are unknown, and optimizing their values can dramatically improve adherence to experimental data, significantly enhancing biological plausibility. Previous optimization methods - such as exhaustive search, gradient descent, evolutionary strategies and Bayesian optimization - require repeated, computationally expensive numerical integration of biophysical differential equations, limiting scalability to population-level datasets. Here, we introduce DELSSOME (DEep Learn

SUBMITTER: Zeng T 

PROVIDER: S-EPMC12026898 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature