Data for a pending publication on stability in visual systems

Research Data for "Temporal coding carries more stable cortical visual representations than firing rate over time"<br><br>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. <br><br>unitAttendance.mat explains for each neuron and each day, whether that neuron was detected/tracked.<br>highAttendanceUnit.mat further shortlists 1037 neurons out of the 1204 that appeared for more than 2 days.<br> <br>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. <br>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. <br><br>For the use of other data, see the associated code from the paper, https://github.com/XieLuanLab/temporal_code_stability<br><br>