Acetylcholine boosts dendritic NMDA spikes in a CA3 pyramidal neuron model

Humphries, Rachel; Mellor, Jack R.; O’Donnell, Cian

doi:10.1101/2021.03.01.433406

Cited by 2 publications

(1 citation statement)

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“…Recent experimental studies in CA3 pyramidal neurons prove that a single dendritic branch induces branch-constrained synaptic plasticity through NMDA spikes and Ca 2+ transients [72] . A compartmental model shows that neuromodulator acetylcholine inhibiting K + channels could generate NMDA spiking, which is necessary for facilitating local plasticity [73] . The dendritic abstraction we proposed divides the neuron into independent computational subunits, which allows synaptic plasticity to occur faster within the compartment.…”

Section: Discussionmentioning

confidence: 99%

A multilayer-multiplexer network processing scheme based on the dendritic integration in a single neuron

Lorenzo¹,

Binczak²,

Jacquir³

2022

AIMSN

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<abstract> <p>Advances in neuronal studies suggest that a single neuron can perform integration functions previously associated only with neuronal networks. Here, we proposed a dendritic abstraction employing a dynamic thresholding function that models the spatiotemporal dendritic integration process of a CA3 pyramidal neuron. First, we developed an input-output quantification process that considers the natural neuronal response and the full range of dendritic dynamics. We analyzed the IO curves and demonstrated that dendritic integration is branch-specific and dynamic rather than the commonly employed static nonlinearity. Second, we completed the integration model by creating a dendritic abstraction incorporating the spatiotemporal characteristics of the dendrites. Furthermore, we predicted the dendritic activity in each dendritic layer and the corresponding somatic firing activity by employing the dendritic abstraction in a multilayer-multiplexer information processing scheme comparable to a neuronal network. The subthreshold activity influences the suprathreshold regions via its dynamic threshold, a parameter that is dependent not only on the driving force but also on the number of activated synapses along the dendritic branch. An individual dendritic branch performs multiple integration modes by shifting from supralinear to linear then to sublinear. The abstraction includes synaptic input location-dependent voltage delay and decay, time-dependent linear summation, and dynamic thresholding function. The proposed dendritic abstraction can be used to create multilayer-multiplexer neurons that consider the spatiotemporal properties of the dendrites and with greater computational capacity than the conventional schemes.</p> </abstract>

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Section: Discussionmentioning

confidence: 99%