Abstract
This paper presents a visualization technique specifically designed to support the analysis of synchronous firings in multiple, simultaneously recorded, spike trains. This technique, called the correlation grid, enables investigators to identify groups of spike trains, where each pair of spike trains has a high probability of generating spikes approximately simultaneously or within a constant time shift. Moreover, the correlation grid was developed to help solve the following reverse problem: identification of the connection architecture between spike train generating units, which may produce a spike train dataset similar to the one under analysis. To demonstrate the efficacy of this approach, results are presented from a study of three simulated, noisy, spike train datasets. The parameters of the simulated neurons were chosen to reflect the typical characteristics of cortical pyramidal neurons. The schemes of neuronal connections were not known to the analysts. Nevertheless, the correlation grid enabled the analysts to find the correct connection architecture for each of these three data sets.
DOI
10.1016/j.biosystems.2004.09.011
Publication Date
2005-01-01
Publication Title
BIOSYSTEMS
Volume
79
Issue
45352
Publisher
Elsevier BV
ISSN
1872-8324
Embargo Period
2024-11-22
Keywords
information visualisation, data analysis, spike trains, synchrony, cross-correlogram, correlation grid
First Page
223
Last Page
233
Recommended Citation
Stuart, L., Walter, M., & Borisyuk, R. (2005) 'The correlation grid: analysis of synchronous spiking in multi-dimensional spike train data and identification of feasible connection architectures', BIOSYSTEMS, 79(45352), pp. 223-233. Elsevier BV: Available at: https://doi.org/10.1016/j.biosystems.2004.09.011
