ArticlePLoS computational biology2015
Modeling Inhibitory Interneurons in Efficient Sensory Coding Models.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Simultaneous encoding of sensory features: the role of multiplexing and noise in tactile perception and neural representation.Biological reviews of the Cambridge Philosophical Society · 2026Review
- A multi-stage auditory model for binaural sound localization using the locally competitive algorithm.Scientific reports · 2025Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.bioRxiv : the preprint server for biology · 2023Article
- Normative and mechanistic model of an adaptive circuit for efficient encoding and feature extraction.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb.Advances in neural information processing systems · 2023Article
- Constrained brain volume in an efficient coding model explains the fraction of excitatory and inhibitory neurons in sensory cortices.PLoS computational biology · 2022Article
- Natural gradient enables fast sampling in spiking neural networks.Advances in neural information processing systems · 2022Article
- Contextual Integration in Cortical and Convolutional Neural Networks.Frontiers in computational neuroscience · 2020Article
- Constrained inference in sparse coding reproduces contextual effects and predicts laminar neural dynamics.PLoS computational biology · 2019Article
- Back-Propagation Learning in Deep Spike-By-Spike Networks.Frontiers in computational neuroscience · 2019Article
- A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents.Frontiers in neuroinformatics · 2019Article
- Synaptic E-I Balance Underlies Efficient Neural Coding.Frontiers in neuroscience · 2018Review
- Model Constrained by Visual Hierarchy Improves Prediction of Neural Responses to Natural Scenes.PLoS computational biology · 2016Article
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2 authors.
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Abstract
There is still much unknown regarding the computational role of inhibitory cells in the sensory cortex. While modeling studies could potentially shed light on the critical role played by inhibition in cortical computation, there is a gap between the simplicity of many models of sensory coding and the biological complexity of the inhibitory subpopulation. In particular, many models do not respect that inhibition must be implemented in a separate subpopulation, with those inhibitory interneurons having a diversity of tuning properties and characteristic E/I cell ratios. In this study we demonstrate a computational framework for implementing inhibition in dynamical systems models that better respects these biophysical observations about inhibitory interneurons. The main approach leverages recent work related to decomposing matrices into low-rank and sparse components via convex optimization, and explicitly exploits the fact that models and input statistics often have low-dimensional structure that can be exploited for efficient implementations. While this approach is applicable to a wide range of sensory coding models (including a family of models based on Bayesian inference in a linear generative model), for concreteness we demonstrate the approach on a network implementing sparse coding. We show that the resulting implementation stays faithful to the original coding goals while using inhibitory interneurons that are much more biophysically plausible.
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