data_behavior
收藏资源简介：
Behavioral Data from humans performing an Attentional Deployment Task.<b>Data format</b><b>:</b> *.mat files (Matlab)<b>Data description:</b>Filename:Each file corresponds to one session (one participant) of the task. All filenames have the form: "data_XX_yyyy_mm_dd_hh-min". The two letters after "data" correspond to a randomly created subject ID. Then it contains the date and time info (year, month, day, hour and minutes) of the session.Inside, each file contains a single structure array called "BehavData", which has two fields: "vars" and "info". The latter contains metadata from the session (subject code name, gender, age, date, time start, time finish). The "vars" (variables) field contains the actual behavioral data. It has 7 fields:<br>"Picture_seq": matrix of dimensions pictures x trials x blocks containing the info of the picture sequences that were presented on each trial. Each trial consists of 5 pictures, and there are 5 types of pictures. Each entry consists of a 3-digit number. First digit correspond to the picture type (1 to 5), second and third digits are the file number within the folder of the corresponding picture type."Block_dumm": vector of trials, with each entry containing the block number to which the trial belongs."Stim_seq": vector of trials, with each entry containing the stimulus type (1 to 5) of each trial."RTintensity_seq": vector of trials, with each entry containing the response time that participants took when delivering intensity ratings (possible values: 0 to 2; units: seconds)."ResponseIntensity_seq": vector of trials, with each entry containing the intensity rating assigned by the participant to a given trial (possible values: integers 1 to 9; units: rating scale)"RTvalence_seq": same as RTintensity_seq but for valence ratings.<br>"ResponseValence_seq": same as ResponseIntensity_seq but for intensity ratings.<br><b>References:</b>Task design is based on the following publication (data does NOT come from it):Jamie Ferri, Joseph Schmidt, Greg Hajcak, Turhan Canli (2013). Neural correlates of attentional deployment within unpleasant pictures. Neuroimage 15:70:268-77.doi: 10.1016/j.neuroimage.2012.12.030.
本数据集为人类执行<b>注意分配任务（Attentional Deployment Task）</b>时产生的行为数据。 <b>数据格式</b><b>:</b> *.mat文件（Matlab格式） <b>数据描述:</b>文件名：每个文件对应一次实验会话（即一名被试的全部实验数据），所有文件名均遵循"data_XX_yyyy_mm_dd_hh-min"的命名规则。其中"data"后的两位字符为随机生成的被试ID，后续字段依次为会话的年、月、日、小时与分钟时间信息。 每个文件内部包含一个名为"BehavData"的结构体数组，该数组包含两个字段："vars"与"info"。其中"info"字段存储会话元数据，包括被试代码、性别、年龄、实验开始时间与结束时间；"vars"（变量字段）存储实际行为数据，共包含7个子字段：<br>"Picture_seq"：维度为[图片数量×试次数量×区块数量]的矩阵，记录各试次呈现的图片序列信息。每个试次包含5张图片，共5类图片，矩阵元素为3位数字：第一位为图片类型编号（1至5），第二位与第三位为对应图片类型文件夹内的图片文件编号。<br>"Block_dumm"：长度与试次总数一致的向量，每个元素代表该试次所属的区块编号。<br>"Stim_seq"：长度与试次总数一致的向量，每个元素代表该试次的刺激类型编号（1至5）。<br>"RTintensity_seq"：长度与试次总数一致的向量，记录被试完成强度评分任务的反应时（RT），取值范围为0至2秒。<br>"ResponseIntensity_seq"：长度与试次总数一致的向量，记录被试为对应试次给出的强度评分，取值范围为1至9的整数，对应标准化评分量表结果。<br>"RTvalence_seq"：长度与试次总数一致的向量，与"RTintensity_seq"格式一致，对应效价评分任务的反应时。<br>"ResponseValence_seq"：长度与试次总数一致的向量，与"ResponseIntensity_seq"格式一致，原文标注为对应强度评分任务（存在笔误，实际应为效价评分任务），记录被试为对应试次给出的评分。 <b>参考文献:</b>本任务的实验范式基于以下发表文献（本数据集并非来自该文献）：Jamie Ferri、Joseph Schmidt、Greg Hajcak、Turhan Canli (2013). 《不愉快图片情境下注意分配的神经关联》. *Neuroimage* 15:70:268-77. DOI: 10.1016/j.neuroimage.2012.12.030.
