DOI: 10.5061/dryad.1c59zw3rs
title: Data from: Control of adaptive action selection by secondary motor cortex during flexible visual categorization

description: Adaptive action selection during stimulus categorization is an important
 feature of flexible behavior. To examine neural mechanism underlying this
 process, we trained mice to categorize the spatial frequencies of visual
 stimuli according to a boundary that changed between blocks of trials in a
 session. Using a model with a dynamic decision criterion, we found that
 sensory history was important for adaptive action selection after the
 switch of boundary. Bilateral inactivation of the secondary motor cortex
 (M2) impaired adaptive action selection by reducing the behavioral
 influence of sensory history. Electrophysiological recordings showed that
 M2 neurons carried more information about upcoming choice and previous
 sensory stimuli when sensorimotor association was being remapped than when
 it was stable. Thus, M2 causally contributes to flexible action selection
 during stimulus categorization, with the representations of upcoming
 choice and sensory history regulated by the demand to remap
 stimulus-action association.
description: Behavioral  experiments were controlled by custom Matlab
 (Mathworks) scripts and digital I/O devices (PCI-6503, National
 Instruments Corporation). Neural signals were amplified and filtered using
 the Cerebus 32-channel system (Blackrock Microsystems). Task-related
 behavioral events were digitized as TTL levels and recorded by the Cerebus
 system. Data analyses were performed in Matlab.
description: Dataset: Behavior Each mat file contains
 behavior data from one session of one mice performing the flexible visual
 categorization task, and can be opened in MATLAB.
 variables: log.pic_Fname: the name and path of
 visual stimuli, indicates the spatial frequency used.
 log.res_vector_cw: outcome,block,stimulus of each
 trial.     sign of the number means correct/wrong. + is
 correct, - is wrong.     tens place is block indentity.
 1 is low boundary block, 2 is high boundary block.   
  ones place is visual stimulus identity. 1 is the lowest spatial frequency
 in the stimulus set,<br>         7 is the higher spatial frequency.
 check BasicIn.stim_list for exact number.     as such,
 -14 means a trial peformed in the low boundary block, with the
 intermediate SF (the 4th stimulus, reverisng stimulus) shown.<br>   
      <br>         since it is a wrong trial, with reversing stimulus
 in the low boundary block, from the rule of the task,
         it indicates that the action the mouse took in that trial
 is left choice (see paper). log.rsp_vector_cw: response
 latency of each trial.   <br>
 Dataset: Recording Each mat file contains
 electrophysiology recording data from one mice performing the flexible
 visual categorization task, and can be opened in MATLAB.
 Data shared here have gone through cross-channel duplicate
 screening and unit tracking procedures described in the paper.
 Spike times are aligned to the onset of "Go" signal of
 each trial. <br> Variables:
 BasicIn.stim_list: spatial frequency of visual stimuli used, in
 cyc/deg. BasicIn.coarse_binsize: bin size for data in
 res_psth_cbin, in ms. BasicIn.t_pre: time window before
 "Go" signal, in ms. BasicIn.t_post: time
 window after "Go" signal, in ms.
 BasicIn.pre_bin_num: number of timebin before "Go"
 signal, according to BasicIn.t_pre and BasicIn.coarse_binsize.
 BasicIn.post_bin_num: number of timebin after "Go"
 signal, according to BasicIn.t_post and BasicIn.coarse_binsize.
 id: existence of tracked units in each session.
 res_block_num_each_unit: number of blocks for each tracked
 unit.     For example, "[6;8;7]" in the 6th
 cell means for the 6th tracked unit, data are from 3 sessions, and the
 mouse performed 6、8、7 blocks<br> during each session.
 <br> res_block_size_each_unit: size of each block for each
 tracked unit. res_psth_1ms: psth in 1ms
 timebin. res_psth_cbin: psth in timebin of
 BasicIn.coarse_binsize. res_spk_train: spk time for
 each unit during each trial. res_vector_cw_each_unit:
 behavior trial information (outcome,block,stimulus) of each tracked
 unit. wmean: average waveform of tracked
 unit.