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Related Concept Videos

Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
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Language and Cognition01:27

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Language Development01:22

Language Development

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
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Components of Language01:24

Components of Language

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Lateralization01:28

Lateralization

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Brain lateralization refers to the division of mental processes and functions between the two hemispheres of the brain, a phenomenon that optimizes neural efficiency and underpins complex abilities in humans. This specialization allows each hemisphere to perform tasks where it has a comparative advantage, facilitating more refined cognitive capabilities across different domains.
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fMRI Validation of fNIRS Measurements During a Naturalistic Task
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fMRI reveals language-specific predictive coding during naturalistic sentence comprehension.

Cory Shain1, Idan Asher Blank2, Marten van Schijndel3

  • 1The Ohio State University, 43210, USA.

Neuropsychologia
|December 25, 2019
PubMed
Summary

Brain's language processing is domain-specific, using local word patterns and structure for predictions, not general executive control. This reveals specialized predictive coding in language comprehension.

Keywords:
LanguageMultiple demand networkNaturalisticPredictive codingSentence processingSurprisalSyntactic structurefMRI

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Area of Science:

  • Cognitive Neuroscience
  • Neuroimaging
  • Psycholinguistics

Background:

  • Prediction is a fundamental cognitive process across various domains.
  • Debate exists on whether predictive coding arises from domain-general or domain-specific neural circuits.
  • Understanding the information sources for predictions is crucial.

Purpose of the Study:

  • To investigate whether predictive coding in language processing is domain-specific or domain-general.
  • To determine if predictions are based on local word co-occurrence or hierarchical linguistic structure.
  • To explore the neural implementation of predictive coding during naturalistic language comprehension.

Main Methods:

  • Functional magnetic resonance imaging (fMRI) was employed during a naturalistic language comprehension task.
  • A continuous-time deconvolutional regression technique was utilized to analyze blood-oxygen-level-dependent (BOLD) signals.
  • This method allowed for data-driven discovery of hemodynamic response functions from continuous BOLD fluctuations.

Main Results:

  • Evidence of predictive coding effects was found within the language network, not the multiple-demand network.
  • Predictions were sensitive to both local word co-occurrence patterns and hierarchical linguistic structure.
  • Surface-level and structural prediction effects were separable within the language network, explaining over 37% of variance.

Conclusions:

  • Language processing involves domain-specific predictive coding mechanisms.
  • These mechanisms utilize both local and structural linguistic information for prediction.
  • Predictions are generated by specialized language processing circuits, not high-level executive control.