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A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex
How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336927/ https://www.ncbi.nlm.nih.gov/pubmed/30687022 http://dx.doi.org/10.3389/fncir.2018.00121 |
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author | Hawkins, Jeff Lewis, Marcus Klukas, Mirko Purdy, Scott Ahmad, Subutai |
author_facet | Hawkins, Jeff Lewis, Marcus Klukas, Mirko Purdy, Scott Ahmad, Subutai |
author_sort | Hawkins, Jeff |
collection | PubMed |
description | How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework. |
format | Online Article Text |
id | pubmed-6336927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63369272019-01-25 A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex Hawkins, Jeff Lewis, Marcus Klukas, Mirko Purdy, Scott Ahmad, Subutai Front Neural Circuits Neuroscience How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework. Frontiers Media S.A. 2019-01-11 /pmc/articles/PMC6336927/ /pubmed/30687022 http://dx.doi.org/10.3389/fncir.2018.00121 Text en Copyright © 2019 Hawkins, Lewis, Klukas, Purdy and Ahmad. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Hawkins, Jeff Lewis, Marcus Klukas, Mirko Purdy, Scott Ahmad, Subutai A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex |
title | A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex |
title_full | A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex |
title_fullStr | A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex |
title_full_unstemmed | A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex |
title_short | A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex |
title_sort | framework for intelligence and cortical function based on grid cells in the neocortex |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336927/ https://www.ncbi.nlm.nih.gov/pubmed/30687022 http://dx.doi.org/10.3389/fncir.2018.00121 |
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