MATLAB tools for spike count and signal correlation analyses of neurophysiological data
These MATLAB functions compute and plot spike count correlations (rsc), signal correlations (rsig), and rsc as a function of rsig, as in Leavitt et al. (2017) PNAS. See Cohen and Kohn (2011) Nat. Neuro. for an explanation and review of (rsc) and (rsig).
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 rsc or rsig.
mL_mean_matched_rsc: Compute rsc 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 rsc as a function of rsig.
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.