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Paired spiking robustly shapes spontaneous activity in neural networks in vitro

2015-10-30

In vivo, neurons establish functional connections and preserve information along their synaptic pathways from one information processing stage to the next in a very efficient manner. Paired spiking (PS) enhancement plays a key role by acting as a temporal filter that deletes less informative spikes. We analyzed the spontaneous neural activity evolution in a hippocampal and a cortical network over several weeks exploring whether the same PS coding mechanism appears in neuronal cultures as well. We show that self-organized neural in vitro networks not only develop characteristic bursting activity, but feature robust in vivo-like PS activity. PS activity formed spatiotemporal patterns that started at early days in vitro (DIVs) and lasted until the end of the recording sessions. Initially random-like and sparse PS patterns became robust after three weeks in vitro (WIVs). They were characterized by a high number of occurrences and short inter-paired spike intervals (IPSIs). Spatially, the degree of complexity increased by recruiting new neighboring sites in PS as a culture matured. Moreover, PS activity participated in establishing functional connectivity between different sites within the developing network. Employing transfer entropy (TE) as an information transfer measure, we show that PS activity is robustly involved in establishing effective connectivities. Spiking activity at both individual sites and network level robustly followed each PS within a short time interval. PS may thus be considered a spiking predictor. These findings suggest that PS activity is preserved in spontaneously active in vitro networks as part of a robust coding mechanism as encountered in vivo. We suggest that, presumably in lack of any external sensory stimuli, PS may act as an internal surrogate stimulus to drive neural activity at different developmental stages.

📄 PDF Abstract BibTeX arXiv:1510.09138

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Cultural Vocal Bursts Intensity PredictionFunctional Connectivity

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