{"title":"Emergence of brain function from structure: an algebraic quantum model","authors":"Elkaïoum M. Moutuou, Habib Benali","doi":"arxiv-2408.14221","DOIUrl":null,"url":null,"abstract":"A fundamental paradigm in neuroscience is that cognitive functions -- such as\nperception, learning, memory, and locomotion -- are governed by the brain's\nstructural organization. Yet, the theoretical principles explaining how the\nphysical architecture of the nervous system shapes its function remain elusive.\nHere, we combine concepts from quantum statistical mechanics and graph\nC*-algebras to introduce a theoretical framework where functional states of a\nstructural connectome emerge as thermal equilibrium states of the underlying\ndirected network. These equilibrium states, defined from the\nKubo-Martin-Schwinger states formalism (KMS states), quantify the relative\ncontribution of each neuron to the information flow within the connectome.\nUsing the prototypical connectome of the nematode {\\em Caenorhabditis elegans},\nwe provide a comprehensive description of these KMS states, explore their\nfunctional implications, and establish the predicted functional network based\non the nervous system's anatomical connectivity. Ultimately, we present a model\nfor identifying the potential functional states of a detailed structural\nconnectome and for conceptualizing the structure-function relationship.","PeriodicalId":501517,"journal":{"name":"arXiv - QuanBio - Neurons and Cognition","volume":"46 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Neurons and Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.14221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A fundamental paradigm in neuroscience is that cognitive functions -- such as
perception, learning, memory, and locomotion -- are governed by the brain's
structural organization. Yet, the theoretical principles explaining how the
physical architecture of the nervous system shapes its function remain elusive.
Here, we combine concepts from quantum statistical mechanics and graph
C*-algebras to introduce a theoretical framework where functional states of a
structural connectome emerge as thermal equilibrium states of the underlying
directed network. These equilibrium states, defined from the
Kubo-Martin-Schwinger states formalism (KMS states), quantify the relative
contribution of each neuron to the information flow within the connectome.
Using the prototypical connectome of the nematode {\em Caenorhabditis elegans},
we provide a comprehensive description of these KMS states, explore their
functional implications, and establish the predicted functional network based
on the nervous system's anatomical connectivity. Ultimately, we present a model
for identifying the potential functional states of a detailed structural
connectome and for conceptualizing the structure-function relationship.