Emerging experience-dependent dynamics in primary somatosensory cortex reflect behavioral adaptation

Behavioral experience and flexibility are crucial for survival in a constantly changing environment. Despite evolutionary pressures to develop adaptive behavioral strategies in a dynamically changing sensory landscape, the underlying neural correlates have not been well explored. Here, we use genetically encoded voltage imaging to measure signals in primary somatosensory cortex (S1) during sensory learning and behavioral adaptation in the mouse. In response to changing stimulus statistics, mice adopt a strategy that modifies their detection behavior in a context dependent manner as to maintain reward expectation. Surprisingly, neuronal activity in S1 shifts from simply representing stimulus properties to transducing signals necessary for adaptive behavior in an experience dependent manner. Our results suggest that neuronal signals in S1 are part of an adaptive framework that facilitates flexible behavior as individuals gain experience, which could be part of a general scheme that dynamically distributes the neural correlates of behavior during learning. Methods Behavior set up was programmed as a custom software written in Matlab and Simulink (Ver. 2015b; The MathWorks, Natick, Massachusetts, USA), which is available upon request. Voltage fluorescent data was collected using MiCAM05-N256 (Scimedia, Ltd) software. Open-source software was used for Image data processing (MiCAM05-N256, Scimedia, Ltd). Psychometric data analysis and curve fits were performed using open-source software psignifit toolbox version 2.5.6 for MATLAB version 5 and up (Wichmann & Hill, 2001 a,b). All other analyses were performed with custom MATLAB programs, which is available in “Dryad” with the identifier https://doi.org/10.5061/dryad.h18931zmm.