2023 - T1B - WS1 - Structural learning by the brain

Collection 2023 - T1B - WS1 - Structural learning by the brain

Organisateur(s) Galves, Antonio ; Löcherbach, Eva ; Pouzat, Christophe ; Vargas, Claudia D.
Date(s) 06/03/2023 - 10/03/2023
URL associée https://indico.math.cnrs.fr/event/7794/
5 15

Computation, coherence, coding, chemistry, communication in the brain

De William Lytton

The hypothesis of coexisting causes should come as no surprise in the complex multiscale dynamical systems of the brain. Here we explore several hypotheses for dynamical sources -dendritic, chemical, network, single-cell causes. These are complementary. Hence there is no falsifiability through eliminating one from the system as there would be with a physics hypothesis; either eliminating intrinsic effects on a large scale or eliminating network effects will produce a new dynamical system that will not speak to any hypothesis. In the case of eliminating the network through block of all synaptic connections (again locally so as not to kill the animal), effects will trivially be eliminated. The difficulties of multiscale modeling, and multiscale concepts, in biology are of a different order than those in many fields because of the failure of layer-by-layer encapsulation. Famously, the individual atoms of a gas can be encapsulated as particles for the purposes of understanding the gas laws and thermodynamics: there is no need to consider electron shells or intranuclear forces. By contrast, the scale of a particular ion channel type cannot be fully encapsulated as a phenomenological inductor for the purpose of understanding neuron dynamics; the scale of the single neuron cannot be fully encapsulated as a sum-and-squash point neuron for understanding network dynamics; the scale of thalamus cannot be encapsulated as part of thalamocortical dynamics; \etc. This failure of encapsulation (a complication of scale-overlap) is seen throughout biology and manifests particularly clearly in brain.

Informations sur la vidéo

Données de citation

  • DOI 10.57987/IHP.2023.T1B.WS1.005
  • Citer cette vidéo Lytton, William (08/03/2023). Computation, coherence, coding, chemistry, communication in the brain. IHP. Audiovisual resource. DOI: 10.57987/IHP.2023.T1B.WS1.005
  • URL https://dx.doi.org/10.57987/IHP.2023.T1B.WS1.005

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