top of page

CODE/ANALYSIS

All our code libraries for analysing neural population recordings

Spectral estimation for networks (toolbox)

The MATLAB toolbox to find and analyse low-dimensional structure in networks. Use a spectral approach to estimate departures from a specified null model network.

Accompanies the paper "Spectral estimation for detecting low-dimensional structure in networks using arbitrary null models" published in PLoS ONE.  

Example of applying spectral estimation of the Allen Mouse Brain gene atlas

Detecting attractors in population recordings

Combines dimension reduction, recurrence analysis, and dynamical systems theory to find and quantify low-dimensional attractors in cellular-resolution population recording data.

​

A suite of MATLAB code for the eLife paper "A spiral attractor drives rhythmic locomotion" (Angela Bruno, Bill Frost & Mark Humphries)

Low-D_projection.png

Spike-train communities toolbox

MATLAB toolbox for spike-train community detection
A set of functions for analysing large-scale recordings of cellular-level neural activity, based on community detection ideas from network theory.

Spike-train-communities.png

Neural Ensemble Analysis toolbox

MATLAB toolbox for analysing neural ensembles.

​

So you've found some ensembles of neurons (or "cell assemblies") in your population recording data - now what? This toolbox tackles this problem by laying out a set of tools for quantifying and comparing neural ensembles.

NeuralEnsemble_Types.png

Small-world-ness toolbox

MATLAB code for computing small-world-ness on networks.

example_directed_SWN.png
bottom of page