ArticlePLoS computational biology2016
Optimal Information Representation and Criticality in an Adaptive Sensory Recurrent Neuronal Network.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Article
- Two views of the brain are reconciled by a unifying principle of maximal information processing.bioRxiv : the preprint server for biology · 2025Article
- Adaptive proximity to criticality underlies amplification of ultra-slow fluctuations during free recall.PLoS computational biology · 2025Article
- Abnormally enhanced temporal correlations of alpha oscillations across multiple timescales in tinnitus patients.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Article
- Neural field modeling and analysis of consciousness states in the brain.Neuroscience of consciousness · 2025Article
- Information Thermodynamics: From Physics to Neuroscience.Entropy (Basel, Switzerland) · 2024Article
- Trial-by-trial variability in cortical responses exhibits scaling of spatial correlations predicted from critical dynamics.Cell reports · 2024Article
- Multilevel and multifaceted brain response features in spiking, ERP and ERD: experimental observation and simultaneous generation in a neuronal network model with excitation-inhibition balance.Cognitive neurodynamics · 2023Article
- Critical-like Brain Dynamics in a Continuum from Second- to First-Order Phase Transition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks.Nature communications · 2023Article
- Exploring the criticality hypothesis using programmable swarm robots with Vicsek-like interactions.Journal of the Royal Society, Interface · 2023Article
- Article
- A pattern of cognitive resource disruptions in childhood psychopathology.Network neuroscience (Cambridge, Mass.) · 2023Article
- Improvements in task performance after practice are associated with scale-free dynamics of brain activity.Network neuroscience (Cambridge, Mass.) · 2023Article
- Evidence of Critical Dynamics in Movements of Bees inside a Hive.Entropy (Basel, Switzerland) · 2022Article
- Hippocampal gamma and sharp wave/ripples mediate bidirectional interactions with cortical networks during sleep.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Replay, the default mode network and the cascaded memory systems model.Nature reviews. Neuroscience · 2022Review
- Criticality enhances the multilevel reliability of stimulus responses in cortical neural networks.PLoS computational biology · 2022Article
- Tinnitus-like "hallucinations" elicited by sensory deprivation in an entropy maximization recurrent neural network.PLoS computational biology · 2021Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Recurrent connections play an important role in cortical function, yet their exact contribution to the network computation remains unknown. The principles guiding the long-term evolution of these connections are poorly understood as well. Therefore, gaining insight into their computational role and into the mechanism shaping their pattern would be of great importance. To that end, we studied the learning dynamics and emergent recurrent connectivity in a sensory network model based on a first-principle information theoretic approach. As a test case, we applied this framework to a model of a hypercolumn in the visual cortex and found that the evolved connections between orientation columns have a "Mexican hat" profile, consistent with empirical data and previous modeling work. Furthermore, we found that optimal information representation is achieved when the network operates near a critical point in its dynamics. Neuronal networks working near such a phase transition are most sensitive to their inputs and are thus optimal in terms of information representation. Nevertheless, a mild change in the pattern of interactions may cause such networks to undergo a transition into a different regime of behavior in which the network activity is dominated by its internal recurrent dynamics and does not reflect the objective input. We discuss several mechanisms by which the pattern of interactions can be driven into this supercritical regime and relate them to various neurological and neuropsychiatric phenomena.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.