ArticlePLoS computational biology2013
Cellular adaptation facilitates sparse and reliable coding in sensory pathways.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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28 citing papers in PubMed, 58 citations in OpenAlex.
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- Corticothalamic modulation of somatosensory thalamic tactile processing.The Journal of physiology · 2025Article
- Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information.Nature communications · 2024Article
- Decomposition of an odorant in olfactory perception and neural representation.Nature human behaviour · 2024Article
- Prediction error drives associative learning and conditioned behavior in a spiking model of Drosophila larva.iScience · 2024Article
- Olfactory receptor neurons generate multiple response motifs, increasing coding space dimensionality.eLife · 2023Article
- A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains.Biological cybernetics · 2022Article
- Sensory adaptation mediates efficient and unambiguous encoding of natural stimuli by vestibular thalamocortical pathways.Nature communications · 2022Article
- A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets.eLife · 2021Article
- Interspike interval correlations in neuron models with adaptation and correlated noise.PLoS computational biology · 2021Article
- Adaptive temporal processing of odor stimuli.Cell and tissue research · 2021Review
- A spiking neural program for sensorimotor control during foraging in flying insects.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Cortical reliability amid noise and chaos.Nature communications · 2019Article
- Article
- Activation of Corticothalamic Layer 6 Cells Decreases Angular Tuning in Mouse Barrel Cortex.Frontiers in neural circuits · 2019Article
- Segregation of Unknown Odors From Mixtures Based on Stimulus Onset Asynchrony in Honey Bees.Frontiers in behavioral neuroscience · 2019Article
- Winnerless competition in clustered balanced networks: inhibitory assemblies do the trick.Biological cybernetics · 2018Article
- Neural Organization of A3 Mushroom Body Extrinsic Neurons in the Honeybee Brain.Frontiers in neuroanatomy · 2018Article
- Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex.Frontiers in neural circuits · 2018Article
- Dynamic Information Encoding With Dynamic Synapses in Neural Adaptation.Frontiers in computational neuroscience · 2018Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture.
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