Data supporting the results of the study 'Mouse prefrontal cortex represents learned rules for categorization'

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Rule-switch experiment 1d215f806a Fixed reward variable 4 days ago
Task-change experiment a9f9f2738d Uploaded one file per mouse 1 year ago
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README.md

Category-learning_mPFC

This repository contains the data supporting the results in the study ‘Mouse prefrontal cortex represents learned rules for categorization’. doi/link

In each folder are the data of all mice in that respective experiment. Mice in the folder ‘Rule-switch experiment’ were trained on two rules for categorization sequentially (Fig. 1-3), mice in the folder ‘Task-change experiment’ performed a change in task design from ‘go’/’nogo’ to left/right (Fig. 4). Additionally, the folder 'Figure source data' contains the source data of every display item in the manuscript, as can be found at the end of each figure legend.

Rule-switch experiment: Per mouse, one MATLAB file ‘Mousename.mat’ consists of the following fields for every time point of two-photon imaging (7 time points for M01 and M02, 8 time points for all others):

• Trials X 1 -> Sequence of Category ID of presented stimuli (1: Category 1, non-rewarded, 5: Category 2, rewarded)

• Trials X 1 -> Sequence of Stimulus ID of presented stimuli (1-36: individual stimuli)

• Trials X 1 -> Sequence of Stimulus spatial frequency of presented stimuli

• Trials X 1 -> Sequence of Stimulus orientation of presented stimuli

• Trials X 1 -> Mouse Choice (1: ‘go’ response, 0: ‘nogo’ response)

• Trials X 1 -> Reward (1: rewarded trial, 0: no reward given)

• Trials X 1 -> Mean running speed of the mouse [cm/s]

• Trials X cells -> Mean inferred spike rate during stimulus presentation

• Cells X 1 -> CTI, calculated based on mean inferred spike rate during stimulus presentation, applying the active rule (only for T1, T5 and T8)

• Cells X 1 -> CTI orthogonal, calculated based on mean inferred spike rate during stimulus presentation, applying the inactive rule (only for T1, T5 and T8)

• Cells X 1 -> Performance of Bayesian decoder predicting category identity trial-by-trial (only for T1 and T5)

• Active rule (SF: spatial frequency, ORI: orientation)

Task-change experiment: Per mouse, one MATLAB file ‘Mousename.mat’ consists of the following fields for the two time points of two-photon imaging (T5 and L/R):

• Trials X 1 -> Sequence of Category ID of presented stimuli (1: Category 1, 2: Category 2)

• Trials X 1 -> Sequence of Stimulus ID of presented stimuli (1-36: individual stimuli)

• Trials X 1 -> Mouse Choice (T5 -> 1: ‘go’ response, 0: ‘nogo’ response, L/R -> 2: ‘go right’, 1:’go left’, 0: ‘nogo’)

• Trials X 1 -> Reward (1: rewarded trial, 0: no reward given)

• Trials X 1 -> Mouse ‘go right’ (T5 -> 0, L/R -> 1: ‘go right’, 0:’go left’ or ‘nogo’)

• Trials X 1 -> Mouse ‘go left’ (T5 -> 0, L/R -> 1: ‘go left’, 0:’go right’ or ‘nogo’)

• Mouse body and eye parameter names

• Trials X 7 -> Mean mouse body and eye parameters during stimulus presentation, extracted with DLC

• Trials X cells -> Mean inferred spike rate during stimulus presentation

• Cells X 1 -> CTI, calculated based on mean inferred spike rate during stimulus presentation, applying the active rule

• Cells X 1 -> CTI orthogonal, calculated based on mean inferred spike rate during stimulus presentation, applying the inactive rule

• Active rule (SF: spatial frequency, ORI: orientation)