Data for "Temporal coding carries more stable cortical visual representations than firing rate over time"

Research Data for "Temporal coding carries more stable cortical visual representations than firing rate over time" For Research_Data_XX_TS.mat files, where XX represents the stimulus types (DG/SG/RFG/NI) indicated in the paper, they are cell arrays with 1204 rows (neurons) and 15 columns (days), each cell is multi-dimensional array of number of trials - by - number of stimulus conditions - by - number of time bins, each bin is 0.5ms and is a binary variable indicating the presence/absence of a spike. unitAttendance.mat explains for each neuron and each day, whether that neuron was detected/tracked. highAttendanceUnit.mat further shortlists 1037 neurons out of the 1204 that appeared for more than 2 days. notInleast15percentPoorlyTuned.mat further shortlist ~830 neurons out of the 1037 high attendance units that are not among the worst 15% in their tuning to natural image stimuli across days. SignificantTuning_XX.mat explains for XX stimuli (DG/SG/RFG/NI) whether the firing rate-based tuning to stimuli was significant for a given high attendance neuron in any given day. whichAnimalPerUnit.mat indicates which animal a certain unit belongs to. For the use of other data, see the associated code from the paper, https://github.com/XieLuanLab/temporal_code_stability