Temporal discrimination from the interaction between dynamic synapses and intrinsic subthreshold oscillations

•We assess the interplay of intrinsic subthreshold oscillations and dynamic synapses.•This co-action builds nontrivial and channel specific input-output relationships.•The phenomenon provides temporal structure discrimination in single neurons.•We describe analytical results in a mathematically trea...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) Vol. 417; pp. 543 - 557
Main Authors: Torres, Joaquin J., Baroni, Fabiano, Latorre, Roberto, Varona, Pablo
Format: Journal Article
Language:English
Published: Elsevier B.V 05.12.2020
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ISSN:0925-2312, 1872-8286
Online Access:Get full text
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Summary:•We assess the interplay of intrinsic subthreshold oscillations and dynamic synapses.•This co-action builds nontrivial and channel specific input-output relationships.•The phenomenon provides temporal structure discrimination in single neurons.•We describe analytical results in a mathematically treatable model.•Nontrivial preferences are resistant to noise and changes in synaptic strength. The interaction between synaptic and intrinsic dynamics can efficiently shape neuronal input–output relationships in response to temporally structured spike trains. We use a neuron model with subthreshold oscillations receiving inputs through a synapse with short-term depression and facilitation to show that the combination of intrinsic subthreshold and synaptic dynamics leads to channel-specific nontrivial responses and recognition of specific temporal structures. Our study employs the Generalized Integrate-and-Fire (GIF) model, which can be subjected to analytical characterization. We map the temporal structure of spike input trains to the type of spike response, and show how the emergence of nontrivial input–output preferences is modulated by intrinsic and synaptic parameters in a synergistic manner. We demonstrate that these temporal input discrimination properties are robust to noise and to variations in synaptic strength. Furthermore, we also illustrate the presence of these input–output relationships in conductance-based models. Our results suggest a widespread computationally economic and easily tunable mechanism for temporal information discrimination in single neurons.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2020.07.031