Functional Connections Among Neurons within Single Columns of Macaque V1

Overview

This repository contains code for analyzing cross-correlations between the spikes trains of pairs of neurons in macaque V1 and generating the figures for the following paper:

Trepka, Zhu et al., (2022) Functional Interactions Among Neurons within Single Columns of Macaque V1. eLife 11:e79322. https://doi.org/10.7554/eLife.79322

Data format

Here, we include intermediate data files in the output directory that can be used to replicate all figures. The intermediate files contain the cross-correlograms for all pairs of neurons and the output of clustering these cross-correlograms.

Reproducing figures

To reproduce all figures, clone the repo and run plot_all.m in MATLAB and plot_figures123.ipynb in Jupyter Notebook or VS code. Note that the boxplots in plot_figure5 require MATLAB 2022a or later, but all other plots work in earlier versions of MATLAB as well.

Reproducing all analyses from raw data

Raw data has been deposited as described in the publication, and can be used to reproduce the results.

The main directory contains all scripts necessary to compute, cluster, postprocess, and plot CCGs. The run_all function executes each of these scrips in the order in which they should be executed. To reproduce all figures from the raw data, place raw data in a directory named data and then run run_all.m Note that the computation of jitter-corrected CCGs can take a substantial amount of time, so CCG analyses were run in parallel on multiple CPUs prior to running the other scripts.

Code organization

Here, we describe each of the scripts in the main directory:

• config stores constants for the analyses
• compute_ccgs computes all cross-correlograms for a given session.
• postprocess extracts relevant CCG attributes such as the peak, lag, and neuronal layer pairing for each CCG
• compute_clusters clusters the CCGs using parameters and methods defined in config
• plot_figureX plots the indicated main figure in the paper
• plot_distribution plots the supplemental figure showing the distribution of clusters across layers
• plot_figures123.ipynb is a jupyter notebook that contains code necessary for plotting the first three main figures and various supplementary figures

The remaining folders are organized as follows:
├───analysis - helper functions for computing CCGs
├───helpers - generic helper functions
├───data - spike trains from recordings (not currently included)
├───output - intermediate output from analyses