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Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing
One of the most paradoxical aspects of human language is that it is so unlike any other form of behavior in the animal world, yet at the same time, it has developed in a species that is not far removed from ancestral species that do not possess language. While aspects of non-human primate and avian...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733003/ https://www.ncbi.nlm.nih.gov/pubmed/23935589 http://dx.doi.org/10.3389/fpsyg.2013.00500 |
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author | Dominey, Peter F. |
author_facet | Dominey, Peter F. |
author_sort | Dominey, Peter F. |
collection | PubMed |
description | One of the most paradoxical aspects of human language is that it is so unlike any other form of behavior in the animal world, yet at the same time, it has developed in a species that is not far removed from ancestral species that do not possess language. While aspects of non-human primate and avian interaction clearly constitute communication, this communication appears distinct from the rich, combinatorial and abstract quality of human language. So how does the human primate brain allow for language? In an effort to answer this question, a line of research has been developed that attempts to build a language processing capability based in part on the gross neuroanatomy of the corticostriatal system of the human brain. This paper situates this research program in its historical context, that begins with the primate oculomotor system and sensorimotor sequencing, and passes, via recent advances in reservoir computing to provide insight into the open questions, and possible approaches, for future research that attempts to model language processing. One novel and useful idea from this research is that the overlap of cortical projections onto common regions in the striatum allows for adaptive binding of cortical signals from distinct circuits, under the control of dopamine, which has a strong adaptive advantage. A second idea is that recurrent cortical networks with fixed connections can represent arbitrary sequential and temporal structure, which is the basis of the reservoir computing framework. Finally, bringing these notions together, a relatively simple mechanism can be built for learning the grammatical constructions, as the mappings from surface structure of sentences to their meaning. This research suggests that the components of language that link conceptual structure to grammatical structure may be much simpler that has been proposed in other research programs. It also suggests that part of the residual complexity is in the conceptual system itself. |
format | Online Article Text |
id | pubmed-3733003 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-37330032013-08-09 Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing Dominey, Peter F. Front Psychol Psychology One of the most paradoxical aspects of human language is that it is so unlike any other form of behavior in the animal world, yet at the same time, it has developed in a species that is not far removed from ancestral species that do not possess language. While aspects of non-human primate and avian interaction clearly constitute communication, this communication appears distinct from the rich, combinatorial and abstract quality of human language. So how does the human primate brain allow for language? In an effort to answer this question, a line of research has been developed that attempts to build a language processing capability based in part on the gross neuroanatomy of the corticostriatal system of the human brain. This paper situates this research program in its historical context, that begins with the primate oculomotor system and sensorimotor sequencing, and passes, via recent advances in reservoir computing to provide insight into the open questions, and possible approaches, for future research that attempts to model language processing. One novel and useful idea from this research is that the overlap of cortical projections onto common regions in the striatum allows for adaptive binding of cortical signals from distinct circuits, under the control of dopamine, which has a strong adaptive advantage. A second idea is that recurrent cortical networks with fixed connections can represent arbitrary sequential and temporal structure, which is the basis of the reservoir computing framework. Finally, bringing these notions together, a relatively simple mechanism can be built for learning the grammatical constructions, as the mappings from surface structure of sentences to their meaning. This research suggests that the components of language that link conceptual structure to grammatical structure may be much simpler that has been proposed in other research programs. It also suggests that part of the residual complexity is in the conceptual system itself. Frontiers Media S.A. 2013-08-05 /pmc/articles/PMC3733003/ /pubmed/23935589 http://dx.doi.org/10.3389/fpsyg.2013.00500 Text en Copyright © 2013 Dominey. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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 | Psychology Dominey, Peter F. Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing |
title | Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing |
title_full | Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing |
title_fullStr | Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing |
title_full_unstemmed | Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing |
title_short | Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing |
title_sort | recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733003/ https://www.ncbi.nlm.nih.gov/pubmed/23935589 http://dx.doi.org/10.3389/fpsyg.2013.00500 |
work_keys_str_mv | AT domineypeterf recurrenttemporalnetworksandlanguageacquisitionfromcorticostriatalneurophysiologytoreservoircomputing |