A
Aleksey Malyshev
Researcher at Russian Academy of Sciences
Publications - 46
Citations - 823
Aleksey Malyshev is an academic researcher from Russian Academy of Sciences. The author has contributed to research in topics: Helix lucorum & Clione limacina. The author has an hindex of 16, co-authored 46 publications receiving 722 citations. Previous affiliations of Aleksey Malyshev include University of Connecticut & Ruhr University Bochum.
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Correlations and synchrony in threshold neuron models.
Tatjana Tchumatchenko,Aleksey Malyshev,Theo Geisel,Maxim Volgushev,Maxim Volgushev,Fred Wolf +5 more
TL;DR: This work studies how threshold models and neocortical neurons transfer temporal and interneuronal input correlations to correlations of spikes and shows that pairs with different firing rates driven by common inputs in general exhibit asymmetric spike correlations.
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Ultrafast Population Encoding by Cortical Neurons
TL;DR: This study presents conclusive evidence showing that cortical neurons are capable of rapidly relaying subtle mean current signals, which provides a vital mechanism for the propagation of rate-coded information within and across brain areas.
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Fast Computations in Cortical Ensembles Require Rapid Initiation of Action Potentials
TL;DR: It is concluded that fast-onset dynamics is a genuine property of cortical AP generators that enables fast computations in cortical circuits that are rich in recurrent connections both within each region and across the hierarchy of areas.
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Chloride conducting light activated channel GtACR2 can produce both cessation of firing and generation of action potentials in cortical neurons in response to light.
Aleksey Malyshev,M. V. Roshchin,G. R. Smirnova,Dmitry A. Dolgikh,Pavel M. Balaban,M. A. Ostrovsky +5 more
TL;DR: Despite strong inhibition the light stimulation of GtACR2-positive neurons can surprisingly lead to generation of action potentials, presumably initiated in the axonal terminals, which should be taken into account when using the Gt ACR2 in optogenetics experiments.
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Estimating short-term synaptic plasticity from pre- and postsynaptic spiking.
TL;DR: Two model-based approaches for estimating synaptic weights and short-term plasticity from pre- and postsynaptic spike observations alone are presented and it is found that, using only spike observations, both methods can accurately reconstruct the time-varying synaptic weights of presynaptic inputs for different types of STP.