Representation of spatial sequences using nested rules in human prefrontal cortex
Memory for spatial sequences does not depend solely on the number of locations to be stored, but also on the presence of spatial regularities. Here, we show that the human brain quickly stores spatial sequences by detecting geometrical regularities at multiple time scales and encoding them in a form...
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2019
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_10538119_v186_n_p245_Wang http://hdl.handle.net/20.500.12110/paper_10538119_v186_n_p245_Wang |
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paper:paper_10538119_v186_n_p245_Wang |
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paper:paper_10538119_v186_n_p245_Wang2023-06-08T16:03:03Z Representation of spatial sequences using nested rules in human prefrontal cortex adult Article controlled study dorsal inferior prefrontal cortex dorsolateral prefrontal cortex female gaze human human experiment language processing learning male memory consolidation nerve cell network neuroanatomy neurophysiology normal human prediction prefrontal cortex priority journal working memory Memory for spatial sequences does not depend solely on the number of locations to be stored, but also on the presence of spatial regularities. Here, we show that the human brain quickly stores spatial sequences by detecting geometrical regularities at multiple time scales and encoding them in a format akin to a programming language. We measured gaze-anticipation behavior while spatial sequences of variable regularity were repeated. Participants’ behavior suggested that they quickly discovered the most compact description of each sequence in a language comprising nested rules, and used these rules to compress the sequence in memory and predict the next items. Activity in dorsal inferior prefrontal cortex correlated with the amount of compression, while right dorsolateral prefrontal cortex encoded the presence of embedded structures. Sequence learning was accompanied by a progressive differentiation of multi-voxel activity patterns in these regions. We propose that humans are endowed with a simple “language of geometry” which recruits a dorsal prefrontal circuit for geometrical rules, distinct from but close to areas involved in natural language processing. © 2018 2019 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_10538119_v186_n_p245_Wang http://hdl.handle.net/20.500.12110/paper_10538119_v186_n_p245_Wang |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
adult Article controlled study dorsal inferior prefrontal cortex dorsolateral prefrontal cortex female gaze human human experiment language processing learning male memory consolidation nerve cell network neuroanatomy neurophysiology normal human prediction prefrontal cortex priority journal working memory |
| spellingShingle |
adult Article controlled study dorsal inferior prefrontal cortex dorsolateral prefrontal cortex female gaze human human experiment language processing learning male memory consolidation nerve cell network neuroanatomy neurophysiology normal human prediction prefrontal cortex priority journal working memory Representation of spatial sequences using nested rules in human prefrontal cortex |
| topic_facet |
adult Article controlled study dorsal inferior prefrontal cortex dorsolateral prefrontal cortex female gaze human human experiment language processing learning male memory consolidation nerve cell network neuroanatomy neurophysiology normal human prediction prefrontal cortex priority journal working memory |
| description |
Memory for spatial sequences does not depend solely on the number of locations to be stored, but also on the presence of spatial regularities. Here, we show that the human brain quickly stores spatial sequences by detecting geometrical regularities at multiple time scales and encoding them in a format akin to a programming language. We measured gaze-anticipation behavior while spatial sequences of variable regularity were repeated. Participants’ behavior suggested that they quickly discovered the most compact description of each sequence in a language comprising nested rules, and used these rules to compress the sequence in memory and predict the next items. Activity in dorsal inferior prefrontal cortex correlated with the amount of compression, while right dorsolateral prefrontal cortex encoded the presence of embedded structures. Sequence learning was accompanied by a progressive differentiation of multi-voxel activity patterns in these regions. We propose that humans are endowed with a simple “language of geometry” which recruits a dorsal prefrontal circuit for geometrical rules, distinct from but close to areas involved in natural language processing. © 2018 |
| title |
Representation of spatial sequences using nested rules in human prefrontal cortex |
| title_short |
Representation of spatial sequences using nested rules in human prefrontal cortex |
| title_full |
Representation of spatial sequences using nested rules in human prefrontal cortex |
| title_fullStr |
Representation of spatial sequences using nested rules in human prefrontal cortex |
| title_full_unstemmed |
Representation of spatial sequences using nested rules in human prefrontal cortex |
| title_sort |
representation of spatial sequences using nested rules in human prefrontal cortex |
| publishDate |
2019 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_10538119_v186_n_p245_Wang http://hdl.handle.net/20.500.12110/paper_10538119_v186_n_p245_Wang |
| _version_ |
1768546502548914176 |