readme.md 4.8 KB

Shield: CC BY-NC-SA 4.0

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CC BY-NC-SA 4.0

Description of data

Validation data provided here was used to generate figures for 'OPETH: Open Source Solution for Real-time Peri-event Time Histogram Based on Open Ephys' by András Széll, Sergio Martínez-Bellver, Panna Hegedüs and Balázs Hangya, depositied on bioRxiv: https://www.biorxiv.org/content/10.1101/783688v1

The experimental data is provided in Cellbase format. CellBase software is a Matlab-based, open source data handling and analysis tool, and available at https://github.com/hangyabalazs/CellBase See CellBase documentation for details on variable structure.

The Behaviour/ folder contains tetrode recordings in a behavioural recording sesssion: event.mat contains TTL event timestamps. TT1.mat, TT2.mat,... contains spike data from each tetrode. TT1_1.mat,... contains spike data after spike sorting in MClust (A.D.Redish). DBO07_190826a.mat contains raw behavioural data. TrialEvents.mat contains Trial events structure (see CellBase). StimEvents.mat contains Stimulus events structure (see CellBase). EVENTSPIKES and STIMSPIKES files contain pre-aligned spike times (see CellBase). The Tagging/ folders contain tetrode recordings in optogenetic tagging sesssions in the same format. Please note that CellBase code relies on this particular folder structure (see CellBase documentation.)

Desription of code

read_openephy.m performs offline spike detection. read_openephys.m calls common_avg_ref.m for common average referenceing and oedisc.m for thershold-based spike discrimination. oedisc.m calls the low-level discrimininator disc.m. These functions depend on load_open_ephys_data from Open Ephys and the butter.m function for Butterworth filtering from Matlab Signal Processing Toolbox.

lightpsth.m is included, which was used to calculated light-triggered PETH for unsorted tetrode data offline. lightpsth.m calls convert_events.m for Open Ephys event conversion to Matlab.

LoadTT_Intan.m is included, which is a loading engine for MClust3.5.

All other code, including offline PETH tools for sorted data are part of MClust 3.5 (A.D Redish) or CellBase software packagages, are available online.

Dependencies

Open ephys to Matlab conversion requires load_open_ephys_data.m available at Open Ephys.

Spike sorting was carried out in MClust3.5 (by A. D. Redish).

Offline PETH on sorted data requires the CellBase analysis software package

Requires Matlab R2016a (or newer) with Signal Processing Toolbox.

Execution instructions

Open ephys '.continuous' source files were converted to Matlab by read_open_ephys.m using offline threshold-based spike detection.

lightpsth.m can be executed using the lightpsth(sessionpath) syntax, where sessionpath is a string input containing full path to the recording session files. This function returns offline PETH aligned to light flashes for the given session (spikes are not sprted into putative single neurons).

Spike sorting on any recording sesssion can be performed by the MClust.m GUI (available in MClust3.5 package from A.D.Redish). Sorted spikes were also uploaded in the data session folders and can be loaded into MClust for validation. Note that this requires the LoadTT_Intan loading engine. Move LoadTT_Intan.m to the MClust/LoaingEngines folder and set this loading engine before importing clusters.

Further data processing for offline raster plots and PETH calculations for sorted neurons was performed by viewcell2b.m. viewcell2b.m requires preprocessing by prealignSpikes.m. These functions are part of the CellBase R2013a release of the CellBase data analysis package. The preprocessed files are also available in the data session folders.

Installation

Move the .m files on your MATLAB path. Download and install MClust3.5. Move LoadTT_Intan.m to the MClust/LoaingEngines folder. Download CellBase R2013a and move all .m files on your MATLAB path.

System requirements

Windows 10 64bits
Any Intel or AMD x86-64 processor
8 GB RAM
MatlabR2016a or higher
MATLAB Signal Processing Toolbox

Please contact us with any questions, bug reports, and general feedback:

Sergio Martinez-Bellver and Balazs Hangya
martinez-bellver.sergio@koki.mta.hu
hangya.balazs@koki.mta.hu