macaque_MST_map1

Electrophysiological dataset from macaque visual cortical area MST in response to a novel motion stimulus

Summary

We provide spiking responses from 172 single neurons in extrastriate visual area MST recorded in 139 sessions from 4 hemispheres of 3 rhesus macaque monkeys. The data was collected across 3 experiments, designed to characterize the response properties of MST neurons to complex motion stimuli. In Experiment 1 ("Spatial Mapping") a small random dot pattern was sequentially presented in different locations across the screen in order to map the neuron's spatial receptive field (see video). In Experiment 2 ("Tuning") a random dot pattern moving at different speeds in different directions in linear motion and spiral motion space was presented in multiple locations across each neuron's spatial receptive field (see video). In Experiment 3 ("Reverse Correlation") a newly developed random dot motion stimulus was used, which consists of a grid of positions, each with a direction and speed seed that determine the motion of dots in the vicinity of each grid location (see video).

The datasets contain detailed information about the stimulus parameters at high temporal resolution as well as offline sorted spiketimes. Metadata about the datasets such as the electrode position and depth is provided in a separate spreadsheet.

This data can be used to explore how information about visual stimuli (in this case: motion) is encoded in a high-level extrastriate area of the primate cortex. The third experiment in particular has been designed for analyses similar to those that have been used in earlier visual areas (e.g., V1), such as spike-triggered or regression based analyses.

Downloading the data

The entire repository has around 30GB. There are three ways of dowloading the data. We recommend the first option which, although it requires downloading a separate command-line interface tool, can download the entire repository with only 3 commands.

Using gin

Create an account on gin and download the gin client as described here. On your computer, log in using

gin login

Clone the repository using:

gin get cnl-dpz/macaque_MST_map1

Large data files will not be downloaded automatically. To get them, use

gin get-content <filename>

Downloaded large files will be locked (read-only). You must unlock the files using

gin unlock <filename>

To remove the contents of a large file again, use

gin lock <filename>
gin remove-content <filename>

See here for detailed information on how to use gin.

Using git annex

Make sure git and git-annex are installed on your computer. Create an account on gin and upload your public SSH key to your gin profile. Then clone the repository using

git clone git@gin.g-node.org:/cnl-dpz/macaque_MST_map1.git

Large data files will not be downloaded automatically. To get them, use

git annex get <filename>

Downloaded large files will be locked (read-only). You must unlock the files using

git annex unlock <filename>

To remove the contents of a large file again, use

git annex --force lock <filename>
git annex drop <filename>

See the git annex documentation for details.

Using the web browser

Download the latest release as a zip file by clicking on Releases on the main page at https://web.gin.g-node.org/cnl-dpz/macaque_MST_map1. This zip file will contain all small (text) files only, while large data files will not be downloaded automatically and an empty placeholder will be put in their place. To get the full content of such a large file , download these files individually as needed from the web interface by clicking on them in the repository browser.

Repository structure

Directory data

Contains the files meta_data.txt, and data_description (as a pdf and an xlsx) as well as three folders, MSTm, MSTn, and MSTt, which contain the data for each of the three experiments in the HDF5 format (.h5).

meta_data.txtcontains information about each recording session, in a spreadsheet where each row is one recording session. The columns are:

Column header	Description
format	Format version of the meta data table ("1.0" in call cases in this project)
recording_session	A running index of recording sessions
experimenter	The experimenter who recorded the data ("amm" for A.M. or "bew" for B.W.)
data	The date of the recording
monkey	The monkey ("sun", "igg", or "edg")
hemisphere	The hemisphere from which the data was recorded ("left" or "right")
chamber	A numerical identifier of the recording chamber on a hemisphere ("1" in all cases in this project)
session_number	A running counter of recording sessions for a given monkey (recorded as strings to include leading zeros which are needed to specify filenames)
daily_count	A running counter of separate recording attempts on a given day
hardware	The recording setup in which the file was recorded ("A" or "B") and the micropositioner that was used for the recording session (either "MM1" for the 5 electrode mini matrix, "MM2" for the 3 electrode mini matrix or "Kopf" for the hydraulic Model 650 Micropositioner, see Neural recording setup
offline_units_n	n (here: n = 3) columns with an identifier for up to n offline-sorted single cells. The digits before the decimal point specify the electrode while digits after the decimal point specify different offline sorted units recorded on the same electrode. For example, 34.1 and 34.2 are two units recorded on the same electrode that were sorted offline, whereas 34.1 and 35.1 are two units that were recorded on separate electrodes
ML_n	n (here: n = 3) columns with the stereotaxic coordinates on the mediolateral axis of the electrode for up to $n$ offline-sorted single cells that were identified in the columns offline_units_n (in mm)
AP_n	n (here: n = 3) columns with the stereotaxic coordinates on the anteroposterior axis of the electrode for up to $n$ offline-sorted single cells that were identified in the columns offline_units_n (in mm)
depth_n	n columns (here: n = 3) with depth positions of the electrode for up to $n$ offline-sorted single cells that were identified in the columns "offline_units_n", where 0 is the surface of the dura mater (in µm)
Exp_MSTm_tt, Exp_MSTt_tt, Exp_MSTn_tt	One column for each experiment (MSTm, MSTt, MSTn) that specifies the total number trials in this file ("tt" = "total trials")
Exp_MSTm_st_n, Exp_MSTt_st_n, Exp_MSTn_st_n	n columns (here: n = 3), for each combination of experiment (MSTm, MSTt, MSTn) and up to $n$ units that specify the range of trials on which spikes were recorded ("st" = "spike trials")
notes	Additional information about a recording session that is not recorded in any of the previous columns

data_description contains definitions of the events in the -task.h5 and -eye.h5 files.

The actual data is organized by experiment. Within each experiment folder there are two files for every recording session. Files ending in '-task.h5' contain information about the stimuli, behavior, and electrophysiological recordings; files ending in '-eye.h5' contain eye tracking data. Each of these file pairs contains the complete data from all the trials the monkey completed. In both files the data is structured as a series of "events". There are five types of events that can be recognized by their names (the first four types only occur in -task.h5 files and the last type only occurs in -eye.h5 files):

• events that describe stimulus features (e.g., the direction or speed of a random dot pattern) start with STIM_
• events that describe input/output variables (e.g., button press or reward delivery) start with IO_
• events that describe trial parameters (such as trial start or trial type) start with TRIAL_
• events that relate to action potential recordings start with SPIKE_
• events that describe eye tracking data start with EYE_ Each event has a value and a timestamp, specifying the time in microseconds since the MWorks server was started on the day of the recording session.

As a concrete example, in the recording session amm-MSTm-sun-120-01+01 the first value that is assigned to the event TRIAL_start is the integer 1 at 59453797µs (about 1 minute) after the MWorks server had been started. This information is saved in amm-MSTm-sun-120-01+01-task.h5 as event_value/TRIAL_start[0] = 1 and event_time/TRIAL_start[0] = 59453797 (note that if reading the data into Matlab, the index needs to be 1, rather than 0). In other words, event_time/TRIAL_start is an array whose length equals the number of trials and whose entries specify the start time of each trial. Correspondingly, event_value/TRIAL_start is an array of the values of TRIAL_start at each timestamp. In the case of TRIAL_start, these values are the trial numbers. For events that describe stimulus attributes, such as the event STIM_MappingProbe_posX -- which describes the x-coordinate of the random dot pattern that was presented in Experiment 1 (see Methods) -- this would be a list of x-positions. A description of events is included in each file in the form of attributes and additionally provided as a separate table in the repository for easy reference.

Directory data/MSTm

Contains the data for the "Spatial Mapping" experiment in the HDF5 .h5 file format.

Directory data/MSTt

Contains the data for the "Tuning" experiment in the HDF5 .h5 file format.

Directory data/MSTn

Contains the data for the "Reverse Correlation" experiment in the HDF5 .h5 file format.

Directory code

Contains example Matlab code to help in loading and analyzing the data.

Function/Script	Description
h5_extract	function that extracts parameters of experiment at speficified time points
technical_validation	script that performs a series of plausibility checks
example_raster_fr	function that demonstrates how individual spike times can be accessed and visualized
example_trial_histogram	script that demonstrates how multiple files can be accessed for population analyses
example_probe_time	function that extracts the values of all events at a given time point
example_rc_stim_extraction	function that extracts the direction and speed values of the newly developed motion stimulus in Experiment 3
example_eye_data	function that plots the x- and y-position of the monkey's gaze as well as the size of the right and left pupil for the first n trials
example_spatial_mapping_analysis	function that plots firing rate as a function of probe location in the Spatial Mapping experiment
example_tuning_analysis	function that plots firing rate as a function of probe direction and speed in the Tuning experiment

Most of the scripts assume that the repository is downloaded in its entirety and that the directory structure is left intact. Specifically, the use of the mfilename function assumes that the Matlab script lies in a directory /code which lies in a parent directory that also contains a directory /data.

Licensing

Electrophysiological dataset from macaque visual cortical area MST in response to a novel motion stimulus in the directory databy Abteilung Kognitive Neurowissenschaften, Deutsches Primatenzentrum Gesellschaft mit beschränkter Haftung – Leibniz Institut für Primatenforschung, Kellnerweg 4, 37077 Göttingen, Germany is licensed under a Creative Commons Attribution 4.0 International Public License. All code in the directory code is published under the BSD 3-clause licenses. See the LICENSE file in the corresponding directory for the full license.