Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh–Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.
RTXI v1.4 Released
This version of RTXI includes new modules, bug fixes, and introduces RTXI’s Patch Clamp Electrophysiology Suite. This marks a new … more →
Bug Fixes for RTXI HDF5 MATLAB Scripts
Due to an issue with the the MATLAB scripts not correctly acquiring data when the data file contained >= 10 … more →
New ways to stay in touch!
RTXI is moving along quickly and we have a few new ways for you to stay in touch with updates … more →
Updated MATLAB functions for HDF5
A tutorial on using HDF5 files and a collection of MATLAB functions are available here: http://www.rtxi.org/docs/RTXIh5.zip RTXI HDF5 Matlab Files … more →
RTXI Update: New COMMENT Datatype for DefaultGUIModel
RTXI v1.2 now has a COMMENT type for Workspaces that also works for DefaultGUIModel. RTXI v1.2 is currently only available … more →
- RTXI v1.4 Released