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In vitro method for information calculation

Create and analyze data for MI experiment as described in the following paper:

Zeldenrust, F., de Knecht, S., Wadman, W. J., Denève, S., Gutkin, B., Knecht, S. De, Denève, S. (2017). Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series. Frontiers in Computational Neuroscience, 11, 49. doi:10.3389/FNCOM.2017.00049

Please cite this reference when using this method.

About

This MATLAB toolbox creates a hidden state and fluctuating input, that can be used in current-clamp experiments. Moreover, it provides the functions to calculate the entropy of the hidden state, the mutual information between the hidden state and the input, and the mutual information between the hidden state and an output spike train (calculated from a recorded membrane potential). Finally, it also gives the response of the 'Bayesian Neuron' for comparison.

For how to use the method on the data in
da Silva Lantyer, A., Calcini, N., Bijlsma, A., Zeldenrust, F., Scheenen, W. J. J., Celikel, T. (under review) A databank for intracellular electrophysiological mapping of the adult somatosensory cortex. GigaScience
Please look at this repository: https://github.com/DepartmentofNeurophysiology/Analysis-tools-for-electrophysiological-somatosensory-cortex-databank

Use

see: Example_experiment

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Create and analyze data for in vitro MI experiment.

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  • MATLAB 100.0%