Brain-imaging evidence for compression of binary sound sequences in human memory.
auditory processing
compression
human
language of thought
neuroscience
sequence
syntax
working memory
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
01 11 2023
01 11 2023
Historique:
received:
21
10
2022
accepted:
14
10
2023
medline:
3
11
2023
pubmed:
1
11
2023
entrez:
1
11
2023
Statut:
epublish
Résumé
According to the language-of-thought hypothesis, regular sequences are compressed in human memory using recursive loops akin to a mental program that predicts future items. We tested this theory by probing memory for 16-item sequences made of two sounds. We recorded brain activity with functional MRI and magneto-encephalography (MEG) while participants listened to a hierarchy of sequences of variable complexity, whose minimal description required transition probabilities, chunking, or nested structures. Occasional deviant sounds probed the participants' knowledge of the sequence. We predicted that task difficulty and brain activity would be proportional to the complexity derived from the minimal description length in our formal language. Furthermore, activity should increase with complexity for learned sequences, and decrease with complexity for deviants. These predictions were upheld in both fMRI and MEG, indicating that sequence predictions are highly dependent on sequence structure and become weaker and delayed as complexity increases. The proposed language recruited bilateral superior temporal, precentral, anterior intraparietal, and cerebellar cortices. These regions overlapped extensively with a localizer for mathematical calculation, and much less with spoken or written language processing. We propose that these areas collectively encode regular sequences as repetitions with variations and their recursive composition into nested structures.
Identifiants
pubmed: 37910588
doi: 10.7554/eLife.84376
pii: 84376
pmc: PMC10619979
doi:
pii:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : European Research Council
ID : NeuroSyntax - Grant agreement ID: 695403
Pays : International
Informations de copyright
© 2023, Al Roumi, Planton et al.
Déclaration de conflit d'intérêts
FA, SP, LW, SD No competing interests declared
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