Dynamic coordination and segregation mechanisms in higher cortex for parallel task processing

The dataset includes behavioral and neural data from single-task and dual-task performance . Behavioral data contains performance measures from single-task and dual-task conditions. Neural data include activity recorded during single-task and dual-task trials across early, middle, and late stages of dual-task training. Each file contains data from one dual-task training stage for a single animal. Animals are identified as M1, M2, M3, M4, M5, M6, M7, M10. Variables named trial* contain trial-aligned neural activity. Each array has the shape: n_neurons × n_timepoints × n_trials. Neural activity was aligned to Go/No-Go cue onset and extracted from a time window of [-5, 10] seconds relative to cue onset. The imaging frame rate was 15 Hz. The variable ID_active contains the indices of task-responsive neurons identified in single-task and dual-task conditions. Variables named GNG_suc* contain the Go/No-Go behavioral outcome for each corresponding trial in the trial* variables. A value of 1 indicates a successful trial, and a value of 0 indicates a failed trial. The accompanying analysis code includes: Coding direction analysis Generalized linear model analysis Neural network modeling analysis本数据集涵盖单任务与双任务作业场景下采集的行为学与神经生理学数据。 行为学数据包含单任务、双任务条件下的作业绩效指标。 神经数据涵盖双任务训练早、中、晚三个阶段内，单任务与双任务试次中记录到的神经活动。 每个数据文件对应单只受试动物的一个双任务训练阶段，受试动物编号为M1、M2、M3、M4、M5、M6、M7、M10。 以trial*命名的变量存储了试次对齐后的神经活动数据。每个数组的维度为：神经元数量 × 时间点数 × 试次数量。神经活动已对齐至Go/No-Go提示（Go/No-Go cue）的出现时刻，并提取了以该提示出现为参照的[-5, 10]秒时间窗口内的信号，本次实验成像帧率为15 Hz。 变量ID_active存储了在单任务与双任务条件下筛选得到的任务响应神经元的索引。 以GNG_suc*命名的变量对应trial*变量中各试次的Go/No-Go行为学结果：取值为1代表试次成功，取值为0代表试次失败。 随数据集附带的分析代码涵盖以下内容： 1. 编码方向分析 2. 广义线性模型分析 3. 神经网络建模分析