Abstract

Sensory information can be encoded using the average firing rate and spike occurrence times in neuronal network responses to external stimuli. Decoding or retrieving stimulus characteristics from the response pattern generally implies that the corresponding neural network has a selective response to various input signals. The role of various spiking activity characteristics (e.g., spike rate and precise spike timing) for basic information processing was widely investigated on the level of neural populations but gave inconsistent evidence for particular mechanisms. Multisite electrophysiology of cultured neural networks grown on microelectrode arrays is a recently developed tool and currently an active research area. In this study, we analyzed the stimulus responses represented by network-wide bursts evoked from various spatial locations (electrodes). We found that the response characteristics, such as the burst initiation time and the spike rate, can be used to retrieve information about the stimulus location. The best selectivity in the response spiking pattern could be found for a small subpopulation of neurones (electrodes) at relatively short post-stimulus intervals. Such intervals were unique for each culture due to the non-uniform organization of the functional connectivity in the network during spontaneous development.Electronic supplementary materialThe online version of this article (doi:10.1007/s11571-016-9380-6) contains supplementary material, which is available to authorized users.

Highlights

  • Selectivity is one of the key properties of brain dynamics necessary for the classification of sensory information

  • We found that the response characteristics, such as the burst initiation time and the spike rate, can be used to retrieve information about the stimulus location

  • Raster plots and poststimulus histograms (PSTHs) of the responses from two stimulation sites are illustrated in Fig. 1f–i, respectively

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Summary

Introduction

Selectivity is one of the key properties of brain dynamics necessary for the classification of sensory information. A neuron’s selectivity to different stimuli has been well studied in the visual cortex (Sigala and Logothetis 2002; Maunsell and Van Essen 1983; Crook et al 1998; Sompolinsky and Shapley 1997), intraparietal area (Fanini and Assad 2009), somatosensory cortex (Wilent and Contreras 2005) and temporal cortex (Kraskov et al 2007). Most of these works have been done using single cell or single unit (electrode) recording techniques. It has been established that unique features of the sensory stimuli in

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