Two-target cycling task, primate motor cortex
This dataset contains single-unit electrophysiology data from two rhesus macaque monkeys during the performance of a two-target cycling task first described in Russo et al Neuron 2018. For more information about data collection and preprocessing see Russo et al Neuron 2018 and Russo et al Neuron 2020. For use examples and more example kinematics from the task, see the following GitHub repositories: • https://github.com/aarusso/trajectory-tangling • https://github.com/aarusso/trajectory-divergence Each dataset (one for each monkey) contains muscle activity (EMG), neural activity recorded from primary motor cortex and dorsal premotor cortex (M1), and neural activity recorded from the supplementary motor area (SMA). The dataset is organized as a MATLAB struct with the following fields: • .xA: mean-centered and normalized, trial-averaged responses for primary motor cortical neurons in a TC x N matrix, where N corresponds to the number of neurons, and TC corresponds to timepoints concatenated across all conditions. • .xA_raw: as for .xA but before normalization and mean-centering. • .xA_sem: corresponds to the standard error of the mean for the data in .xA_raw before trial-averaging. • xNames: unique name identifier for each neuron Analogous fields pertain to the SMA (‘.uA’) and EMG (‘.zA’) data. All data were recorded at 1kHz. The fields .vA and .pA contain example hand velocity (vertical and horizontal hand velocity) and example hand position (vertical and horizontal hand position) for 4 example sessions. The datasets also contain a field .mask which is a structure containing information about the TC dimension in all aforementioned fields: • .condNum: a TC x 1 vector containing the numeric identifier (1-20, for each of the 20 conditions) corresponding to that element of the TC dimension across all fields. • .time: a TC x 1 vector corresponding to time in seconds within each condition with respect to movement onset. • .dist: a TC x 1 vector corresponding to the pedaling distance. May be 7 (7-cycles), 4 (4-cycles), 2, 1, 0.5. • .dir: a TC x 1 vector corresponding to the pedaling direction. May be 1 (forward pedaling) or -1 (backward pedaling). • .pos: a TC x 1 vector corresponding to the starting position. May be 0 (bottom-start) or 0.5 (top-start). To ensure proper use of the data, please review the method sections of Russo et al 2018 and review demos provided in the GitHub repositories linked at the top of this document.