ArticleScientific reports2025
Overcoming the limitations of motion sensor models by considering dendritic computations.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A Neural Model for V1 That Incorporates Dendritic Nonlinearities and Backpropagating Action Potentials.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Plaid masking explained with input-dependent dendritic nonlinearities.Scientific reports · 2024Article
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Authors and funding
3 authors.
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Abstract
The estimation of motion is an essential process for any sighted animal. Computational models of motion sensors have a long and successful history but they still suffer from basic shortcomings, as they disagree with physiological evidence and each model is dedicated to a specific type of motion, which is controversial from a biological standpoint. In this work, we propose a new approach to modeling motion sensors that considers dendritic computations, a key aspect for predicting single-neuron responses that had previously been absent from motion models. We show how, by taking into account the dynamic and input-dependent nature of dendritic nonlinearities, our motion sensor model is able to overcome the fundamental limitations of standard approaches.
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