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Neural processes underlying statistical learning for speech segmentation in dogs.

Marianna Boros1, Lilla Magyari2, Dávid Török1

  • 1MTA-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.

Current Biology : CB
|October 31, 2021
PubMed
Summary

Dogs can learn words by detecting statistical patterns in speech, similar to humans. This study used electroencephalography (EEG) and fMRI to find neural markers for speech segmentation in dogs.

Keywords:
EEGERPauditory cortexbasal gangliadogsfMRIlanguage acquisitionspeech processingstatistical learningword segmentation

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Area of Science:

  • Neuroscience
  • Comparative Cognition
  • Bioacoustics

Background:

  • Humans learn language by extracting statistical regularities from speech.
  • The neural basis of speech segmentation in non-human animals is not well understood.
  • Dogs are adept at navigating human social and linguistic environments.

Purpose of the Study:

  • To investigate computational and neural markers of speech segmentation in dogs.
  • To compare dog speech processing with human speech segmentation mechanisms.

Main Methods:

  • Electroencephalography (EEG) was used to analyze event-related responses (ERPs) to artificial words embedded in continuous speech with varying statistical properties.
  • Functional magnetic resonance imaging (fMRI) was employed to identify brain regions responsive to statistical regularities in speech.
  • Analysis focused on transitional probability and word frequency effects.

Main Results:

  • EEG revealed an early effect (220-470 ms) linked to transitional probability.
  • A later EEG component (590-790 ms) was influenced by both word frequency and transitional probability.
  • fMRI showed reduced basal ganglia activity (involved in sequence learning) and auditory cortex repetition enhancement in response to structured speech.

Conclusions:

  • Speech segmentation in dogs involves complex computations, mirroring human abilities.
  • The findings suggest engagement of both domain-general and modality-specific brain areas in dogs' speech processing.
  • This study provides crucial insights into the neural underpinnings of speech segmentation in a phylogenetically distant mammal.