ArticlePLoS computational biology2018
A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Chemically Programmable Retinomorphic GaN p-n Diode for Multimode Visual Sensing.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Embodied decisions as active inference.PLoS computational biology · 2025Article
- How the conception of control influences our understanding of actions.Nature reviews. Neuroscience · 2023Review
- Idiosyncratic selection of active touch for shape perception.Scientific reports · 2022Article
- Initial contact shapes the perception of friction.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Passive perceptual learning modulates motor inhibitory control in superior frontal regions.Human brain mapping · 2020Article
- Closed loop motor-sensory dynamics in human vision.PloS one · 2020Article
- Clustering of Neural Activity: A Design Principle for Population Codes.Frontiers in computational neuroscience · 2020Article
- Circuit Investigations With Open-Source Miniaturized Microscopes: Past, Present and Future.Frontiers in cellular neuroscience · 2019Review
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2 authors.
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Abstract
During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone.
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