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"<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><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>whichAnimalPerUnit.mat indicates which animal a certain unit belongs to. <br>For the use of other data, see the associated code from the paper, https://github.com/XieLuanLab/temporal_code_stability<br><br>

本数据集对应论文《时间编码比随时间变化的放电率更能维持稳定的皮层视觉表征》的相关研究数据。

针对Research_Data_XX_TS.mat文件（其中XX代表论文中提及的刺激类型：DG/SG/RFG/NI），其为MATLAB细胞数组，包含1204行（对应神经元）与15列（对应实验天数）；每个单元格均为维度依次为实验试次数量×刺激条件数量×时间窗数量的多维数组，每个时间窗时长为0.5ms，其二值变量用于标记是否存在锋电位（spike）。

unitAttendance.mat文件用于说明每个神经元在各实验天数的检测与追踪状态。
highAttendanceUnit.mat 进一步从1204个神经元中筛选出1037个在至少2个实验天数中均可被检测到的神经元。

notInleast15percentPoorlyTuned.mat 则进一步从上述1037个高检出率神经元中，筛选出约830个在多天内对自然图像刺激的调谐特性未处于最差15%行列的神经元。

SignificantTuning_XX.mat文件用于说明：针对XX类型刺激（DG/SG/RFG/NI），给定的高检出率神经元在任意实验天数内，基于放电率的刺激调谐是否具有统计学显著性。

whichAnimalPerUnit.mat文件用于标记特定神经元所属的实验动物。
其他数据集的使用方法可参见论文配套代码：https://github.com/XieLuanLab/temporal_code_stability