The Cortex and the Critical Point
How the cerebral cortex operates near a critical phase transition point for optimum performance. Individual neurons have limited computational powers, but when they work together, it is almost like magic. Firing synchronously and then breaking off to improvise by themselves, they can be paradoxicall...
Sábháilte in:
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| Formáid: | Online |
| Teanga: | Béarla |
| Foilsithe / Cruthaithe: |
The MIT Press
2022
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| Ábhair: | |
| Rochtain ar líne: | ONIX_20221025_9780262370349_18 |
| Clibeanna: |
Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!
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| _version_ | 1869515764130643968 |
|---|---|
| author | Beggs, John M. |
| author_browse | Beggs, John M. |
| author_facet | Beggs, John M. |
| author_sort | Beggs, John M. |
| collection | Directory of Open Access Books |
| description | How the cerebral cortex operates near a critical phase transition point for optimum performance. Individual neurons have limited computational powers, but when they work together, it is almost like magic. Firing synchronously and then breaking off to improvise by themselves, they can be paradoxically both independent and interdependent. This happens near the critical point: when neurons are poised between a phase where activity is damped and a phase where it is amplified, where information processing is optimized, and complex emergent activity patterns arise. The claim that neurons in the cortex work best when they operate near the critical point is known as the criticality hypothesis. In this book John Beggs—one of the pioneers of this hypothesis—offers an introduction to the critical point and its relevance to the brain. Drawing on recent experimental evidence, Beggs first explains the main ideas underlying the criticality hypotheses and emergent phenomena. He then discusses the critical point and its two main consequences—first, scale-free properties that confer optimum information processing; and second, universality, or the idea that complex emergent phenomena, like that seen near the critical point, can be explained by relatively simple models that are applicable across species and scale. Finally, Beggs considers future directions for the field, including research on homeostatic regulation, quasicriticality, and the expansion of the cortex and intelligence. An appendix provides technical material; many chapters include exercises that use freely available code and data sets. |
| format | Online |
| id | doab-20.500.12854ir-93164 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | The MIT Press |
| publisherStr | The MIT Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-931642024-04-05T17:30:39Z The Cortex and the Critical Point Beggs, John M. Critical point Phase transition Cortex Neuronal avalanche Power law Homeostasis Optimality Universality Epilepsy Neural network Computational neuroscience Neuroscience Information theory Electrophysiology. thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PH Physics::PHV Applied physics::PHVS Cryogenics thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQN Neural networks and fuzzy systems How the cerebral cortex operates near a critical phase transition point for optimum performance. Individual neurons have limited computational powers, but when they work together, it is almost like magic. Firing synchronously and then breaking off to improvise by themselves, they can be paradoxically both independent and interdependent. This happens near the critical point: when neurons are poised between a phase where activity is damped and a phase where it is amplified, where information processing is optimized, and complex emergent activity patterns arise. The claim that neurons in the cortex work best when they operate near the critical point is known as the criticality hypothesis. In this book John Beggs—one of the pioneers of this hypothesis—offers an introduction to the critical point and its relevance to the brain. Drawing on recent experimental evidence, Beggs first explains the main ideas underlying the criticality hypotheses and emergent phenomena. He then discusses the critical point and its two main consequences—first, scale-free properties that confer optimum information processing; and second, universality, or the idea that complex emergent phenomena, like that seen near the critical point, can be explained by relatively simple models that are applicable across species and scale. Finally, Beggs considers future directions for the field, including research on homeostatic regulation, quasicriticality, and the expansion of the cortex and intelligence. An appendix provides technical material; many chapters include exercises that use freely available code and data sets. 2022-10-25T08:59:54Z 2022-10-25T08:59:54Z 2022 book ONIX_20221025_9780262370349_18 9780262370349 9780262544030 https://directory.doabooks.org/handle/20.500.12854/93164 eng The MIT Press image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://doi.org/10.7551/mitpress/13588.001.0001 The MIT Press The MIT Press 10.7551/mitpress/13588.001.0001 10.7551/mitpress/13588.001.0001 ae0cf962-f685-4933-93d1-916defa5123d 9780262370349 9780262544030 The MIT Press 216 Cambridge open access |
| spellingShingle | Critical point Phase transition Cortex Neuronal avalanche Power law Homeostasis Optimality Universality Epilepsy Neural network Computational neuroscience Neuroscience Information theory Electrophysiology. thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PH Physics::PHV Applied physics::PHVS Cryogenics thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQN Neural networks and fuzzy systems Beggs, John M. The Cortex and the Critical Point |
| title | The Cortex and the Critical Point |
| title_full | The Cortex and the Critical Point |
| title_fullStr | The Cortex and the Critical Point |
| title_full_unstemmed | The Cortex and the Critical Point |
| title_short | The Cortex and the Critical Point |
| title_sort | cortex and the critical point |
| topic | Critical point Phase transition Cortex Neuronal avalanche Power law Homeostasis Optimality Universality Epilepsy Neural network Computational neuroscience Neuroscience Information theory Electrophysiology. thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PH Physics::PHV Applied physics::PHVS Cryogenics thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQN Neural networks and fuzzy systems |
| topic_facet | Critical point Phase transition Cortex Neuronal avalanche Power law Homeostasis Optimality Universality Epilepsy Neural network Computational neuroscience Neuroscience Information theory Electrophysiology. thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences thema EDItEUR::P Mathematics and Science::PH Physics::PHV Applied physics::PHVS Cryogenics thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQN Neural networks and fuzzy systems |
| url | ONIX_20221025_9780262370349_18 |
| work_keys_str_mv | AT beggsjohnm thecortexandthecriticalpoint AT beggsjohnm cortexandthecriticalpoint |