Data

Flexibility of Intrinsic Neural Timescales During Distinct Behavioral StatesDescription of the data and file structureThe github page https://github.com/duodenum96/acwbehavior contains the MATLAB code to replicate the figures. The numerical data necessary for the figures are presented here. We present the data in two formats, .mat format for MATLAB users and .csv format as well. Non-MATLAB users can access the data in .mat files using conversion software such as scipy.io.loadmat as well. The correspondence between .mat and .csv files are explained in get_figure_data.m. For any questions, you can contact to [e-mail] and variablesget_figure_data.m: Correspondence between .csv and .mat filesmice_behavioral_states.csv (822 x 1): Each row corresponds to one behavioral state of mice, in agreement with mice_acw_values.csv.mice_acw_values.csv (822 x 92): Each row corresponds to one ACW value estimated from the 10 second interval. The states are in agreement with mice_behavioral_states.csv. Each row is an interval, each column is a ROI.mousenames.csv (822 x 1): Identifiers of the micelabels.csv (1 x 5): Five labels for behavioral states.\\\\_all_acws.csv (987 x 64): ACW values estimated from 10 second intervals in human EEG data. \\\\ corresponds to rest, self and other conditions. Each row is an interval, each column is an EEG channel.subjcode.csv (987 x 1): Subject identifiers in numeric form for human EEG data.acwdr_ca.mat: MATLAB struct containing mice data.\\\\_acws_acwdr.mat: MATLAB struct containing human data. \\\\ corresponds to rest, self and other conditions.Code/softwarecsv files do not require any specific software. MATLAB files can be opened via MATLAB or software such as scipy.io.loadmat (python) or R.matlab package (R, function readMat in particular) or MAT.jl (Julia).