Individual differences in the neural strategies to control the lateral and medial head of the quadriceps during a mechanically constrained task

This repository contains all the raw HD-EMG data, the extracted and manually edited motor units, and the binary spike trains used to calculate the within- and between-muscle coherence.Contact: Francois Hug ([e-mail])Simon Avrillon ([e-mail])=================================FILE NAME: Decomposition_results.zip This compressed file contains raw data for each muscle. Motor units were identified and manually edited (FH and SA) using the DEMUSE tool (v4.9; The University of Maribor, Slovenia) [participant_number]_[muscle]_edited_v1.mat These files can be opened with Matlab 2015b (Mathworks) or the DEMUSE tool. VARIABLES (only the variables used in the manuscript are described below) : - DecompRuns: number of decomposition runs (50 for most of the files) - discardChannelsVec: discarded channels for the 13*5 EMG grid (ELSCH064NM2, SpesMedica, Battipaglia). "1" means that the channnel has been discarded due to noise/artifacts. Note that one electrode was absent on a corner [1,1]. - fsamp: sampling rate - IED: inter-electrode distance - IPTs: Innervation Pulse Rrain (IPT, i.e. train of motor unit discharge times as estimated by the gCKC decomposition technique - MUPulses (1*number of motor units array). For each identified units, there is a vector of motor units discharge times (in datapoint). - PNR: Pulse-to-noise ratio for each identified MU - ref_signal: force signal (not calibrated) - SIG (13*5 cell array): raw EMG signal organised on a 13*5 cell array. Each cell corresponds to an EMG channel. - SIGlength: duration of the signal in seconds=================================FILE NAME: Data.matThe file data.mat contains a structure of cells with torque data and the binary spike trains from the 22 participants. They are the data used to calculate the within- and between-muscle coherence.In the first level of the structure, there are 22 cells where each cell is a participant. e.g., Data{4,1} is the data for participant #4.In the second level of the structure, there is a matrix of cells with 2 lines and 4 columns.Each line is a muscle with line 1 = VL and line 2 = VM.Columns 1, 2 and 3 are the data for contractions 1, 2, and 3. Column 4 is the concatenate data for coherence analysis.e.g., Data{4,1}{1,2} is the data for the VL during the second contraction from participant #4.In the third level, you can find a matrix with torque data and motor unit binary spike trainsLine 1 = TimeLine 2 = TorqueLine 3:end = binary spike trains (one motor unit per line)e.g., Data{4,1}{1,2}(2,:) is the torque during the second contraction from participant #4.e.g., Data{4,1}{1,2}(3,:) is the binary spike train of motor unit #1 of the VL during the second contraction from participant #4.本仓库收录全部原始高密度肌电（High-Density Electromyography, HD-EMG）数据、经提取与人工编辑的运动单位，以及用于计算肌肉内与肌肉间相干性的二进制脉冲序列。联系方式：Francois Hug（[e-mail]）、Simon Avrillon（[e-mail]） ================================= 文件名：Decomposition_results.zip 该压缩包包含各肌肉的原始数据。运动单位已通过DEMUSE工具（v4.9；斯洛文尼亚马里博尔大学）完成识别与人工编辑（FH与SA）。文件命名格式为`[participant_number]_[muscle]_edited_v1.mat`，可使用Matlab 2015b（Mathworks）或DEMUSE工具打开。 下文仅介绍论文中用到的变量： - DecompRuns：分解运行次数（多数文件为50次） - discardChannelsVec：13×5肌电网格（ELSCH064NM2，SpesMedica，意大利巴蒂帕格里亚）的丢弃通道标记，“1”表示该通道因噪声/伪影被丢弃。需注意，角落位置[1,1]的电极存在缺失。 - fsamp：采样率 - IED：电极间距（Inter-electrode Distance, IED） - IPTs：神经支配脉冲序列（Innervation Pulse Train, IPT），即通过gCKC分解技术估算得到的运动单位放电时序序列，为1×运动单位数量的数组。每个已识别运动单位对应一个以数据点为单位存储其放电时序的向量。 - MUPulses：1×运动单位数量的数组。针对每个已识别运动单位，存储其放电时序的向量（以数据点为单位）。 - PNR：各已识别运动单位的脉冲信噪比（Pulse-to-Noise Ratio, PNR） - ref_signal：未校准的肌力信号 - SIG：13×5元胞数组，为按13×5网格排布的原始肌电信号，每个元胞对应一个肌电通道。 - SIGlength：信号持续时长，单位为秒 ================================= 文件名：Data.mat 该文件包含一个元胞结构体，存储了22名受试者的力矩数据与二进制脉冲序列，即用于计算肌肉内与肌肉间相干性的原始数据集。 结构体的第一层级包含22个元胞，每个元胞对应一名受试者。例如，Data{4,1}代表第4名受试者的数据。 结构体的第二层级为2行4列的元胞矩阵：每行对应一块肌肉，第1行为股外侧肌（Vastus Lateralis, VL），第2行为股内侧肌（Vastus Medialis, VM）；第1、2、3列分别对应第1、2、3次收缩的实验数据，第4列为用于相干性分析的拼接后数据集。例如，Data{4,1}{1,2}为第4名受试者在第2次收缩时的股外侧肌数据。 结构体的第三层级为包含力矩数据与运动单位二进制脉冲序列的矩阵：第1行=时间轴数据，第2行=力矩数据，第3行及后续各行分别为单个运动单位的二进制脉冲序列（每行对应一个运动单位）。例如，Data{4,1}{1,2}(2,:)为第4名受试者在第2次收缩时的力矩数据；Data{4,1}{1,2}(3,:)为第4名受试者在第2次收缩时的股外侧肌第1号运动单位的二进制脉冲序列。