Information measure for analyzing specific spiking patterns and applications to LGN bursts.
ABSTRACT Neural spiking responses can include a variety of spiking patterns. However, neither the mere presence of the patterns nor the pattern's frequency indicates that the pattern conveys distinct stimulus information. Here, we present an in-depth analysis of a Pattern Information measure, which quantifies how informative it is to distinguish a particular pattern of spikes from either a single spike or an another pattern. (1) We show how a shuffle-controlled estimation method minimizes the impact of sampling bias. (2) We describe how the Pattern Information could arise from time-varying firing rates, and we demonstrate an analysis to determine whether Pattern Information associated with a particular pattern captures structure not contained in the time-varying firing rate. (3) Because patterns may contain several spikes or inter-spike intervals, we extend the Pattern Information measure to determine whether the complete pattern carries information distinct from sub-patterns containing only a fraction of these spikes or intervals. (4) The Pattern Information is applied to determine whether a plurality of patterns carry distinct stimulus information from one another. In particular, we demonstrate these concepts using data from cells of the lateral geniculate nucleus (LGN), thereby extending previous analysis demonstrating that distinguishes between bursts of spikes and single spikes providing visual information.
Article: Bursts and isolated spikes code for opposite movement directions in midbrain electrosensory neurons.[show abstract] [hide abstract]
ABSTRACT: Directional selectivity, in which neurons respond strongly to an object moving in a given direction but weakly or not at all to the same object moving in the opposite direction, is a crucial computation that is thought to provide a neural correlate of motion perception. However, directional selectivity has been traditionally quantified by using the full spike train, which does not take into account particular action potential patterns. We investigated how different action potential patterns, namely bursts (i.e. packets of action potentials followed by quiescence) and isolated spikes, contribute to movement direction coding in a mathematical model of midbrain electrosensory neurons. We found that bursts and isolated spikes could be selectively elicited when the same object moved in opposite directions. In particular, it was possible to find parameter values for which our model neuron did not display directional selectivity when the full spike train was considered but displayed strong directional selectivity when bursts or isolated spikes were instead considered. Further analysis of our model revealed that an intrinsic burst mechanism based on subthreshold T-type calcium channels was not required to observe parameter regimes for which bursts and isolated spikes code for opposite movement directions. However, this burst mechanism enhanced the range of parameter values for which such regimes were observed. Experimental recordings from midbrain neurons confirmed our modeling prediction that bursts and isolated spikes can indeed code for opposite movement directions. Finally, we quantified the performance of a plausible neural circuit and found that it could respond more or less selectively to isolated spikes for a wide range of parameter values when compared with an interspike interval threshold. Our results thus show for the first time that different action potential patterns can differentially encode movement and that traditional measures of directional selectivity need to be revised in such cases.PLoS ONE 01/2012; 7(6):e40339. · 4.09 Impact Factor