<b>Data set for article "Divergent Subregional Information Processing in Mouse Prefrontal Cortex during Working Memory"</b>

This data repository contains six structures storing the data from the Sonneborn et al. Communications Biology publication "Divergent Subregional Information Processing in Mouse Prefrontal Cortex during Working Memory". The six structures contain the raw data used tomake all figures in the paper. Each of the three brain regions in the paper has two corresponding structures, one for raw spike data, and one for sorted behavioral data, including sorted by ports visited. It also containes 2 custom MATLAB functions. <br>The SPIKE STRUCTURES have the raw spiking data for all recorded neurons aligned to important poke events. Each row of these structures corresponds to an individualneuron. The columns are listed below:<br>Column 1 - Session_Name: Shows the mouse number and (session) during which that neuron was recorded. Example: the label NMTP_1(5) has neurons from mouse #1, session #5.<br>Column 2 - Spike_Times: A vector of raw spike timestamps from the output of Kilosort3. Sampled at 30kHz. <br>Remaining Columns: Logical arrays organized in trials x time (30 kHz) matrices. The rows of each matrix are sorted by either the sample ports on individual trials (sample sorted) or the choice ports on individual drials (choice sorted). For example, the column 'SampleSortedChoice' contains logical spike data (1s for spikes, 0s for no spike), sorted by sample port location (Left or Right), during the delay phase of the DNMTP task). <br>The PORT STRUCTURES contain info about how data in the spike arrays was organized by trial type, and also include behavioral data used in several figures. For example, the columnSortedSamplePorts includes the sorting key for individual sessions which shows exactlywhich trials were left and right sample trials for the corresponding neurons in the spikestruct. There is also a similar column for choice struct. For sample ports, Left = 1 and Right = 5. For choice ports, Left = 1, Right = 5, and Center = 3.<br>The functions take the structures as input (one subregion at at time). One function plotsthe cross-temporal support vector machines used in several figures, and the other providesthe GLM analysis used in Figures 6 and 7. Each function contains detailed instructions onhow to input the structures into the functions and read the output.该数据仓库包含六个数据结构，存储着Sonneborn等人发表于《Communications Biology》的论文《小鼠前额叶皮层工作记忆期间的亚区信息处理差异》（'Divergent Subregional Information Processing in Mouse Prefrontal Cortex during Working Memory'）中的数据。这六个结构包含论文所有图表制作所用的原始数据。论文涉及的三个脑区各对应两个结构：一个用于原始Spike数据（raw spike data），另一个用于经分类的行为数据（包括按访问端口分类的数据）。仓库还包含2个自定义MATLAB函数。 SPIKE结构包含所有记录神经元的原始Spike数据，这些数据与重要的探鼻事件（poke events）对齐。每个结构的行对应单个神经元，列说明如下： 列1 - Session_Name：显示记录该神经元的小鼠编号及实验场次。例如，标签NMTP_1(5)表示来自1号小鼠第5场实验的神经元。 列2 - Spike_Times：Kilosort3输出的原始Spike时间戳向量，采样率为30kHz。 其余列：以“试次×时间（30kHz）”矩阵形式组织的逻辑数组。每个矩阵的行按单个试次的样本端口（样本分类）或选择端口（选择分类）排序。例如，‘SampleSortedChoice’列包含逻辑Spike数据（1表示有Spike，0表示无），这些数据在DNMTP任务的延迟阶段按样本端口位置（左或右）排序。 PORT结构包含Spike数组中数据按试次类型的组织方式信息，还包括若干图表中使用的行为数据。例如，SortedSamplePorts列包含各场次的排序键，明确显示Spike结构中对应神经元的左、右样本试次。选择结构中也有类似列。样本端口的左=1、右=5；选择端口的左=1、右=5、中=3。 这些函数以数据结构为输入（每次一个亚区）。其中一个函数绘制若干图表中使用的跨时间支持向量机（cross-temporal support vector machines），另一个提供图6和图7中使用的广义线性模型（GLM）分析。每个函数均包含关于如何输入结构及读取输出的详细说明。