DOI: 10.5061/dryad.h18931zmm
title: Data from: Emerging experience-dependent dynamics in primary somatosensory cortex reflect behavioral adaptation

description: 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.
description: 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.
description: In order to access the data and computer code that support the
 findings of this study, all files can be downloaded from Dryad. Files are
 compressed ZIP files (Windows 10) and need to be saved and extracted
 before access. The main dataset contains GEVI
 (genetically encoded voltage imaging) data from primary somatosensory
 cortex (S1) and simultaneously recorded behavioral readouts (licks and
 whisker stimulation) in a Go-No-go detection task.
 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).
 https://uni-tuebingen.de/en/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/neuronale-informationsverarbeitung/research/software/psignifit/ MATLAB Download: https://github.com/wichmann-lab/psignifit/archive/master.zip python Download: https://github.com/wichmann-lab/python-psignifit/archive/master.zip All other analyses were performed with custom MATLAB programs. All provided data and code can be accessed with MATLAB. The dataset is structured as follows: GEVI_data: Each folder corresponds to an animal (e.g. A_ID01, A_ID05, etc.). Within each animal folder, there are multiple folders for different stimulus conditions (e.g. “STIM1”, “STIM2”, etc. For lesions, e.g. “A_ID14_X_STIM1”). Within each stimulus condition are multiple days/sessions of imaging (e.g. Awake_04_03_s1.mat, etc.). These files can be loaded and accessed via MATLAB (see “code_files”). Note, due to exclusion of mice that did not express GEVI, animal ID’s in the manuscript deviate from ID’s from the original experiments. The updated ID’s are described in a separate document, “Animal_IDs.xlsx”. Behav_data: These files contain processed psychometric data from each animal (for basic learning, e.g. “mouse05_learning.mat”. For different stimulus distributions, e.g. “mouse05_range.mat”. For lesions, e.g. “mouse14_lesion.mat”). In addition, this folder contains group data/analysis/modeling results from multiple animals (e.g. “M01_M05_M06_M07_M13_M14_Full.mat”). All files can be loaded and accessed via MATLAB (see “code_files”). code_files: This folder contains MATLAB programs for all analysis. Note, Psychometric data analysis and curve fits were performed using open-source software psignifit (see above link for download). The sub-folder “Code for figures” contains all necessary MATLAB code to re-produce the main figures of the manuscript. Within each code, loading files, data analysis/statistics and plotting procedures are described step-by-step. Histology: This folder contains histology images (TIF files) that were used for the manuscript (Fig. 1 and Fig. 6). All other histology images are available from the corresponding author upon reasonable request. For detailed questions about the data and computer code, please contact the corresponding author garrett.stanley@bme.gatech.edu