4 results match your criteria: "RIKEN Brain Science Institute Wako-City[Affiliation]"

Comparative performance of a genetically-encoded voltage indicator and a blue voltage sensitive dye for large scale cortical voltage imaging.

Front Cell Neurosci

May 2015

Laboratory for Neuronal Circuit Dynamics, RIKEN Brain Science Institute Wako City, Japan ; Division of Brain Sciences, Department of Medicine, Imperial College London London, UK.

Traditional small molecule voltage sensitive dye indicators have been a powerful tool for monitoring large scale dynamics of neuronal activities but have several limitations including the lack of cell class specific targeting, invasiveness and difficulties in conducting longitudinal studies. Recent advances in the development of genetically-encoded voltage indicators have successfully overcome these limitations. Genetically-encoded voltage indicators (GEVIs) provide sufficient sensitivity to map cortical representations of sensory information and spontaneous network activities across cortical areas and different brain states.

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We consider two types of causes leading to information loss when neural activities are passed and processed in the brain. One is responses of upstream neurons to stimuli being imperfectly observed by downstream neurons. The other is upstream neurons non-optimally decoding stimuli information contained in the activities of the downstream neurons.

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A generic property of the communication between neurons is the exchange of pulses at discrete time points, the action potentials. However, the prevalent theory of spiking neuronal networks of integrate-and-fire model neurons relies on two assumptions: the superposition of many afferent synaptic impulses is approximated by Gaussian white noise, equivalent to a vanishing magnitude of the synaptic impulses, and the transfer of time varying signals by neurons is assessable by linearization. Going beyond both approximations, we find that in the presence of synaptic impulses the response to transient inputs differs qualitatively from previous predictions.

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