ArticleFrontiers in computational neuroscience2023
The mesoanatomy of the cortex, minimization of free energy, and generative cognition.
Article in Frontiers in computational neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Memory Gate Controlled by Contexts: Potential Key Structure That Could Link Small Associative Failures With Severe Cognitive Disorders.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025Review
- Adaptive consolidation of active inference: excitatory and inhibitory mechanisms for organizing feedforward and feedback memory systems in sleep.Cerebral cortex (New York, N.Y. : 1991) · 2025Review
- Minimization of prediction errors during cerebral embryogenesis and the emergence of agency.Frontiers in systems neuroscience · 2025Article
- Cortical development in the structural model and free energy minimization.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Markov Blankets and Mirror Symmetries-Free Energy Minimization and Mesocortical Anatomy.Entropy (Basel, Switzerland) · 2024Article
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Abstract
Capacity for generativity and unlimited association is the defining characteristic of sentience, and this capacity somehow arises from neuronal self-organization in the cortex. We have previously argued that, consistent with the free energy principle, cortical development is driven by synaptic and cellular selection maximizing synchrony, with effects manifesting in a wide range of features of mesoscopic cortical anatomy. Here, we further argue that in the postnatal stage, as more structured inputs reach the cortex, the same principles of self-organization continue to operate at multitudes of local cortical sites. The unitary ultra-small world structures that emerged antenatally can represent sequences of spatiotemporal images. Local shifts of presynapses from excitatory to inhibitory cells result in the local coupling of spatial eigenmodes and the development of Markov blankets, minimizing prediction errors in each unit's interactions with surrounding neurons. In response to the superposition of inputs exchanged between cortical areas, more complicated, potentially cognitive structures are competitively selected by the merging of units and the elimination of redundant connections that result from the minimization of variational free energy and the elimination of redundant degrees of freedom. The trajectory along which free energy is minimized is shaped by interaction with sensorimotor, limbic, and brainstem mechanisms, providing a basis for creative and unlimited associative learning.
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