Inferring context-dependent computations through linear approximations of prefrontal cortex dynamics

• DOI: 10.1101/2023.02.06.527389
• Publication Date: 2023-02-07T07:20:25Z
• Authors: Joana Soldado-Mag...; Valerio Mante; Maneesh Sahani
• Keywords: Dynamics

Abstract The complex neural population activity of prefrontal cortex (PFC) is a hallmark cognitive processes. How these rich dynamics emerge and support computations largely unknown. Here, we infer mechanisms underlying the context-dependent selection integration sensory inputs by fitting dynamical models to PFC responses behaving monkeys. A class implementing linear driven external accurately captured within each context, achieving performance comparable without constraints. Two distinct input were equally consistent with data. One implemented recurrent dynamics, as previously proposed, relied on transient amplification. other subtle contextual modulation inputs, providing quantitative constraints attentional effects in areas required explain flexible behavior. Both consistently revealed properties missing more simplified, incomplete descriptions responses. By revealing cortical our modeling approach provides principled general framework link computation.