Evidence map›Paper›PMID 34717832›Full record

ArticleCurrent biology : CB2021

Neural processes underlying statistical learning for speech segmentation in dogs.

Marianna Boros, Lilla Magyari, Dávid Török, Anett Bozsik, Andrea Deme, Attila Andics

Abstract readVideo-Audio Media
In one paragraph

Article in Current biology : CB, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  15. Long-Horizon Associative Learning Explains Human Sensitivity to Statistical and Network Structures in Auditory Sequences.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Marianna BorosMTA-ELTE "Lendület" Neuroethology of Communication Research Group, Hungarian Academy of Sciences - Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary; Department of Ethology, Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary. Electronic address: marianna.cs.boros@gmail.com.
Lilla MagyariMTA-ELTE "Lendület" Neuroethology of Communication Research Group, Hungarian Academy of Sciences - Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary; Department of Ethology, Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary; Norwegian Reading Centre for Reading Education and Research, Faculty of Arts and Education, University of Stavanger, Professor Olav Hanssens vei 10, 4036 Stavanger, Norway.
Dávid TörökMTA-ELTE "Lendület" Neuroethology of Communication Research Group, Hungarian Academy of Sciences - Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary; Department of Ethology, Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary.
Anett BozsikMTA-ELTE "Lendület" Neuroethology of Communication Research Group, Hungarian Academy of Sciences - Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary; Department of Anatomy and Histology, University of Veterinary Medicine, 1078 Budapest, István utca 2, Hungary.
Andrea DemeDepartment of Applied Linguistics and Phonetics, Eötvös Loránd University, 1088 Budapest, Múzeum krt. 4/A, Hungary; MTA-ELTE "Lendület" Lingual Articulation Research Group, 1088 Budapest, Múzeum krt. 4/A, Hungary.
Attila AndicsMTA-ELTE "Lendület" Neuroethology of Communication Research Group, Hungarian Academy of Sciences - Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary; Department of Ethology, Eötvös Loránd University, 1117 Budapest, Pázmány Péter sétány 1/C, Hungary. Electronic address: attila.andics@gmail.com.

Funding

European Research Council 950159
6 · The paper itself

Abstract

To learn words, humans extract statistical regularities from speech. Multiple species use statistical learning also to process speech, but the neural underpinnings of speech segmentation in non-humans remain largely unknown. Here, we investigated computational and neural markers of speech segmentation in dogs, a phylogenetically distant mammal that efficiently navigates humans' social and linguistic environment. Using electroencephalography (EEG), we compared event-related responses (ERPs) for artificial words previously presented in a continuous speech stream with different distributional statistics. Results revealed an early effect (220-470 ms) of transitional probability and a late component (590-790 ms) modulated by both word frequency and transitional probability. Using fMRI, we searched for brain regions sensitive to statistical regularities in speech. Structured speech elicited lower activity in the basal ganglia, a region involved in sequence learning, and repetition enhancement in the auditory cortex. Speech segmentation in dogs, similar to that of humans, involves complex computations, engaging both domain-general and modality-specific brain areas. VIDEO ABSTRACT.

Indexed as

SpeechSpeech PerceptionAnimalsDogsElectroencephalographyEvoked PotentialsLearningMammalsauditory cortexbasal gangliadogsEEGERPfMRIlanguage acquisitionspeech processingstatistical learningword segmentation

Identifiers

PMID34717832
PMCPMC7612233

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.