delayed_center-out_uncertainty_Riehle

Monkey behavioral neurophysiology during a delayed center-out reach task with ambiguous target information.

This data set contains behavioral and neurophysiological data obtained in two behaving monkeys. The experimental task involves a delayed center-out arm-reach in three experimental conditions that varied the degree of information (either complete or incomplete) about the final movement target as cued at the start of the delay period. The data set contains the trigger events for the experimentally cued stimuli, behavioral events, and acute multiple single-unit recordings from the primary motor cortex (M1) and premotor cortex dorsal (PMd) for both monkeys. All experiments were designed by and conducted under the supervision of Dr. Alexa Riehle, UMR7289 Institut de Neurosciences de la Timone (INT), Centre National de la Recherche Scientifique (CNRS)—Aix-Marseille Université (AMU), Marseille, France, and Institute for Advanced Simulation (IAS-6), Jülich Research Center, Jülich, Germany.

Please cite this dataset using the acquired DOI.

Behavioral task and recordings in the monkey.

The experiments were conducted with two monkeys (Macaca Mulatta) in Alexa Riehle's lab at the CNRS Marseille, France, in accordance with European and French government regulations. Both monkeys were born and raised at the Station de Primatologie, UAR846 des CNRS, 13790 Rousset-sur-Arc, France. One male monkey (joe) was born in 05/1992 and three to four years old when experiments were conducted, one female monkey (lili) was born in 05/1993 and four to five years old during the experimenting period. Both monkeys performed the same delayed center-out reaching task, which involved three different task conditions that differed in the amount of initial target information available to the monkey as described in ^1,2. The monkey was seated in front of a vertical panel featuring a hexagonal array of touch-sensitive target LEDs and a central LED indicating the starting position. The monkey initiated a trial by touching the central LED (trial start, TS). During the 1 s delay period starting at t=500 ms the preparatory signal (PS) provided either complete or incomplete information about the final movement target and consisted of either a single target LED (Condition 1), two adjacent target LEDs (Condition 2), or three adjacent target LEDs (Condition 3) that lit up in green. At t=1500 ms the response signal (RS) appeared and one of the green target LEDs turned red. This indicated the final movement target and prompted the monkey to move his hand to that target. In Conditions 2 and 3 the final target was randomly chosen among the PS-cued targets, while the other target LEDs went dark. The behavioral trigger times of movement onset (MO) and movement end (ME) were recorded and if the monkey touched the correct target LED, the trial was registered as successful and a drop of juice was given as a reward. A premature onset of the behavior before RS led to the abortion of the trial and no reward was given. Only successful trials are included in this dataset.

The task conditions of one, two or three possible targets presented during the 1 s preparatory period were executed in blocks and the order of these blocks were randomized across recordings sessions. In each block, 150 trials with randomly selected target direction were carried out such that each of the directions appeared on average 25 times per condition. Note that, to obtain the same number of possible trial types in all conditions, not all possible combinations of directions for the preparatory stimulus were used in Conditions~2 and~3. Since six combinations are possible for Condition~1, only the pairs 1-2, 3-4 and 5-6 were used in Condition 2 and for Condition 3, only two cases occurred (6-1-2, 3-4-5).

Extracellular recordings were obtained with a multielectrode microdrive (Reitböck system; Thomas Recording) to insert transdurally seven independently movable electrodes within the area of the recording chamber, which was positioned over the motor cortex close to the central sulcus in monkey joe and slightly more anterior in monkey lili covering in parts primary and dorsal premotor cortex². Online spike sorting resulted in up to seven simultaneously recorded single-unit spike trains¹. Not on all experimental days all three conditions could be successfully completed.

The following event markers were recorded:

• TS: trial start
• PS: preparatory signal
• RS: response signal
• MO: movement onset
• ME: movement end
• RW: reward
• TE: trial end
  

Data structure

Data is provided for the two monkeys (joe and lili). Each monkey performed the task across multiple sessions. Spike trains are stored per single unit in each session. We provide the data in pickle format as well as csv and hdf5 format. These files are derived from the original pickle files.

• The directory pickle contains the data in pickle protocol 2 format.
• The directory derived_files/HDF5 contains code to convert pickle files and the derived files in hdf5 format in a subdirectory.
• The directory derived_files/CSV contains code to convert pickle files and the derived files in csv format in a subdirectory.

The filenames encode the monkey, the session and the unit. The filename of pickle and hdf5 files is of the form <monkey><session>_<unit>.<format>.

pickle files

Each .pickle contains a dictionary with the following keys:

• eventtimes : A Trials x 7 numpy-array of behavioral and experimental events in milliseconds (relative to the start of the trial).
• event_names : Column names of the events.
• spiketimes : A 3xN numpy-array. The first row contains the spike times in milliseconds, the second row contains the trial number and the third row contains the direction of RS.
• gdf_file : Name of original gdf file, containing the raw data.
• column_names : Row names of spiketimes.

The pickle files were created with the pickle protocol 2. To load the data use the following code:

import numpy as np
import pickle
with open('<monkey><session>_<unit>.pickle', 'rb') as f:
    data = pickle.load(f, encoding='latin1')
print(data.keys())

The folder contains a file named toc. It is a product of our analysis and contains metadata about the files to speed up the filtering of the data.

HDF5 files

The .hdf5 files contain the same data as the pickle files. The data is stored in the following groups:

• events : Contains the datasets eventtimes and event_names. The dataset eventtimes is a Trials x 7 numpy-array of behavioral and experimental events in milliseconds (relative to the start of the trial). The dataset event_names contains the column names of eventtimes.

• spiketimes : Contains the dataset spiketimes and row_names. The dataset spiketimes is a 3xN numpy-array. The first row contains the spike times in milliseconds, the second row contains the trial number and the third row contains the direction of RS. The dataset row_names contains the row names of spiketimes. The files contain the attributes gdf_file with the name of the original gdf file. HDF5 files were created with the h5py³ library. To load the data use the following code:

  import h5py
  import numpy as np
  with h5py.File('<monkey><session>_<unit>.hdf5', 'r') as f:
  print(list(f.keys()))
  print(list(f['events'].keys()))
  print(list(f['spiketimes'].keys()))
  print(f['events']['eventtimes'][:])
  print(f['spiketimes']['spiketimes'][:])
  

  CSV files

  The data is stored in three files which are named in the following pattern:

  • <monkey><session>_<unit>_events.csv: contains a table with the event markers of each trial
  • <monkey><session>_<unit>_spikes.csv: contains a table of spiketimes with trial numbers and direction of RS
  • <monkey><session>_<unit>_gdf_file.txt: contains the original gdf file

  Downloading the data

  The data can be either downloaded via the command line or via the browser.

  Using the command line

  git clone https://gin.g-node.org/nawrotlab/delayed_center-out_uncertainty_Riehle
  

Using the browser

Download the latest release as a zip file by clicking on Releases on the main page at https://gin.g-node.org/nawrotlab/delayed_center-out_uncertainty_Riehle. This zip file contains all files.

References

1. Bastian A, Schöner G, Riehle A. Preshaping and continuous evolution of motor cortical representations during movement preparation. Eur J Neurosci. 2003 Oct;18(7):2047-58. doi: 10.1046/j.1460-9568.2003.02906.x.
2. Rickert J, Riehle A, Aertsen A, Rotter S, Nawrot MP. Dynamic encoding of movement direction in motor cortical neurons. J Neurosci. 2009 Nov 4;29(44):13870-82. doi: 10.1523/JNEUROSCI.5441-08.2009.
3. https://docs.h5py.org/