Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior.

ABSTRACT: Neural dynamics can reflect intrinsic dynamics or dynamic inputs, such as sensory inputs or inputs from other brain regions. To avoid misinterpreting temporally structured inputs as intrinsic dynamics, dynamical models of neural activity should account for measured inputs. However, incorporating measured inputs remains elusive in joint dynamical modeling of neural-behavioral data, which is important for studying neural computations of behavior. We first show how training dynamical models of neural activity while considering behavior but not input or input but not behavior may lead to misinterpretations. We then develop an analytical learning method for linear dynamical models that simultaneously accounts for neural activity, behavior, and measured inputs. The method provides the capability

SUBMITTER: Vahidi P 

PROVIDER: S-EPMC10873612 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature