Neural Comput - Synaptic scaling stabilizes persistent activity driven by asynchronous neurotransmitter release.

Tópicos

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Resumo

Small networks of cultured hippocampal neurons respond to transient stimulation with rhythmic network activity (reverberation) that persists for several seconds, constituting an in vitro model of synchrony, working memory, and seizure. This mode of activity has been shown theoretically and experimentally to depend on asynchronous neurotransmitter release (an essential feature of the developing hippocampus) and is supported by a variety of developing neuronal networks despite variability in the size of populations (10-200 neurons) and in patterns of synaptic connectivity. It has previously been reported in computational models that "small-world" connection topology is ideal for the propagation of similar modes of network activity, although this has been shown only for neurons utilizing synchronous (phasic) synaptic transmission. We investigated how topological constraints on synaptic connectivity could shape the stability of reverberations in small networks that also use asynchronous synaptic transmission. We found that reverberation duration in such networks was resistant to changes in topology and scaled poorly with network size. However, normalization of synaptic drive, by reducing the variance of synaptic input across neurons, stabilized reverberation in such networks. Our results thus suggest that the stability of both normal and pathological states in developing networks might be shaped by variance-normalizing constraints on synaptic drive. We offer an experimental prediction for the consequences of such regulation on the behavior of small networks.

Resumo Limpo

small network cultur hippocamp neuron respond transient stimul rhythmic network activ reverber persist sever second constitut vitro model synchroni work memori seizur mode activ shown theoret experiment depend asynchron neurotransmitt releas essenti featur develop hippocampus support varieti develop neuron network despit variabl size popul neuron pattern synapt connect previous report comput model smallworld connect topolog ideal propag similar mode network activ although shown neuron util synchron phasic synapt transmiss investig topolog constraint synapt connect shape stabil reverber small network also use asynchron synapt transmiss found reverber durat network resist chang topolog scale poor network size howev normal synapt drive reduc varianc synapt input across neuron stabil reverber network result thus suggest stabil normal patholog state develop network might shape variancenorm constraint synapt drive offer experiment predict consequ regul behavior small network

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