trajectory-tangling

MATLAB code, demo, and sample data to analyze data for trajectory tangling as in Russo et al Neuron 2018

Author: Abigail Russo, May 2019

Datasets

The data included in this demo were recorded in the Churchland lab at Columbia University. Single-unit neural data were recorded sequentially from a macaque monkey during the performance of a hand-pedaling task. Monkeys grasped a hand crank and cycled through a virtual environment for a number of prescribed cycles as indicated by a visual cue. The data included here correspond to two seven-cycle conditions. EMG data were recorded with intramuscular electrodes and are rectified and filtered to obtain an envelope of the muscle response. Neural and EMG were filtered with a Gaussian kernel with a standard deviation of 25ms and trial averaged. For more information about data processing and the task, see Russo et al Neuron 2018.

Data should be formatted as for jPCA. Each data structure (e.g. D_m1, located in M1_sampleData.mat) contains C elements corresponding to the number of conditions (here, 2). The t x n matrix 'A' contains the trial-averaged firing rates as a function of time for each neuron. All other fields are optional. The 'times' field indicates the time course of each sample in A and the 'analyzeTimes' field indicates which of these times should be analyzed for tangling. For more information on formatting, see the tangleAnalysis code comments.

• M1_sampleData.mat: trial-avergaged firing rates from 116 neurons
• EMG_sampleData.mat: trial-avergaged activity from 29 muscles
• kinematic_sampleData.mat: trial-avergaged kinematic data corresponding to a variety of behavioral parameters such as hand position and velocity

Code

• tangleAnalysis.m: compute trajectory tangling on data formatted as described above
• tangling_demo.m: visualize task kinematics, compute tangling on sample datasets, play around with parameters, visualize tangling in two dimensions
• tangle_visualize.m: aids visualization of tangling on the sample datasets.
• formattedScatter.m: makes pretty scatter plots

Supporting functions: AxisMMC.m (makes pretty axes, used by formattedScatter), arrowMMC.m (makes pretty arrows, used by tangle_visualize)