ArticleEntropy (Basel, Switzerland)2021
Linear Response of General Observables in Spiking Neuronal Network Models.
Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Entropy, Inhibition and Memory in Balanced Spiking Reservoirs.Entropy (Basel, Switzerland) · 2026Article
- Fluctuation-response relations for integrate-and-fire models with an absolute refractory period.Biological cybernetics · 2024Article
- Retinal Processing: Insights from Mathematical Modelling.Journal of imaging · 2022Article
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Authors and funding
3 authors.
Funding
Abstract
We establish a general linear response relation for spiking neuronal networks, based on chains with unbounded memory. This relation allow us to predict the influence of a weak amplitude time dependent external stimuli on spatio-temporal spike correlations, from the spontaneous statistics (without stimulus) in a general context where the memory in spike dynamics can extend arbitrarily far in the past. Using this approach, we show how the linear response is explicitly related to the collective effect of the stimuli, intrinsic neuronal dynamics, and network connectivity on spike train statistics. We illustrate our results with numerical simulations performed over a discrete time integrate and fire model.
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Registered trials
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