growlix / spike-count-correlations

MATLAB tools for spike count and signal correlation analyses of neurophysiological data

spike-count-correlations

MATLAB tools for spike count and signal correlation analyses of neurophysiological data

These MATLAB functions compute and plot spike count correlations (r_sc), signal correlations (r_sig), and r_sc as a function of r_sig, as in Leavitt et al. (2017) PNAS. See Cohen and Kohn (2011) Nat. Neuro. for an explanation and review of (r_sc) and (r_sig).

Function overview.

mL_example_rsc_rsig_analysis: Script to demonstrate function usage. Running this will approximately recreate Figures 2A&B of Leavitt et al. (2017) PNAS.

mL_rsc_rsig: Compute r_sc or r_sig.

mL_mean_matched_rsc: Compute r_sc across groups of neurons whose distributions of geometric mean firing rates have been matched (see Methods section of Leavitt et al. (2017) PNAS).

mL_mean_matched_rsc_vs_rsig: Compute geometric mean-matched r_sc as a function of r_sig.

mL_matchDistributions: Function for matching distributions (see Methods section of Leavitt et al. (2017) PNAS).

mL_geometricMeanRates: Simple function for computing geometric mean for each pair of values in a vector.

mL_plotShadedErrorBar: The bar plot is dead.

ciplot: For plotting a line with error. Lightly modified from the version on the MATLAB file exchange.

example_attention_data: Data from one session of Tremblay et al., (2015) Neuron.

Examine the function files for full details.