mdhumphries/NeuralEnsembleAnalysis
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 analysing neural ensembles.
It contains a collection of scripts and functions for analysing ensembles assuming:
(1) you've got a clustering of your spike-train data into ensembles (as might be obtained by: https://github.com/mdhumphries/SpikeTrainCommunitiesToolBox)
(2) you've got your spike-trains in some time-series format (i.e. either binned or "spike-density" - convolved each spike with a window function) (as might be obtained by: https://github.com/mdhumphries/SpikeTrainCommunitiesToolBox)
The focus is on classifying ensembles: this allows us to then go back to each recording and start to decompose the dynamical systems captured within
Full details are in Bruno, Frost & Humphries (2015, Neuron)
Cite As
mdhumphries (2024). mdhumphries/NeuralEnsembleAnalysis (https://github.com/mdhumphries/NeuralEnsembleAnalysis), GitHub. Retrieved .
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- AI, Data Science, and Statistics > Deep Learning Toolbox > Function Approximation, Clustering, and Control >
- Sciences > Neuroscience > Cellular Neuroscience > Electrophysiology >
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1.0.0.0 |
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