Academic Journal
Why statistical learning researchers should study nonhuman animals.
| Τίτλος: | Why statistical learning researchers should study nonhuman animals. |
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| Συγγραφείς: | Tosatto L; School of Biological Sciences, Monash University, Australia; Normandie University, UNICAEN, CNRS, EthoS, UMR 6552, 14000 Caen, France., Avarguès-Weber A; CNRS, University of Toulouse, Centre de Recherches sur la Cognition Animale (CRCA-CBI), Toulouse, France. Electronic address: aurore.avargues-weber@utoulouse.fr. |
| Πηγή: | Current opinion in neurobiology [Curr Opin Neurobiol] 2026 Oct; Vol. 100, pp. 103261. Date of Electronic Publication: 2026 Aug 19. |
| Τύπος έκδοσης: | Journal Article; Review |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Current Biology Country of Publication: England NLM ID: 9111376 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-6882 (Electronic) Linking ISSN: 09594388 NLM ISO Abbreviation: Curr Opin Neurobiol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: London, UK : Current Biology, c1991- |
| Ιατρικοί όροι (MeSH): | Learning*/physiology , Brain*/physiology , Cognition*/physiology , Probability Learning*, Animals ; Humans ; Biological Evolution |
| Περίληψη: | Statistical learning (SL) - the ability to detect patterns in sensory input without explicit instruction - is crucial for building internal models of the environment. In humans, it notably supports language acquisition, including word segmentation and grammar learning. Evidence across primates, songbirds, rodents, and insects indicate that SL is a widely shared evolutionarily conserved ability. The computational complexity of the mechanisms involved; however, varies between species, likely reflecting specific cognitive limitations. Alternatively, specific competences may have evolved to support the emergence of demanding, ecologically relevant, functions such as complex communication systems. These findings challenge the idea of a human-specific SL module while raising key questions about its evolutionary drivers and underlying mechanisms. Addressing these questions requires the expansion of cross-species, cross-modal studies with ecologically valid, unsupervised paradigms. Comparative approaches are indeed essential to uncover shared properties and species-specific SL adaptations. Framing SL as a foundational component of cognition, informed by animal research, offers new insights into brain function, and implicit learning in light of the evolution of sophisticated, emergent cognitive abilities such as complex communication systems. (Copyright © 2026 The Authors. Published by Elsevier Ltd.. All rights reserved.) |
| Competing Interests: | Declaration of competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Entry Date(s): | Date Created: 20260819 Date Completed: 20260904 Latest Revision: 20260904 |
| Update Code: | 20260905 |
| DOI: | 10.1016/j.conb.2026.103261 |
| PMID: | 42617431 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1873-6882 |
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| DOI: | 10.1016/j.conb.2026.103261 |