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Related Concept Videos

Auditory Pathway01:15

Auditory Pathway

Auditory pathways constitute the complex neural circuits responsible for transmitting and interpreting auditory information from the peripheral auditory system to the brain. Sound waves are initially captured by the outer ear, funneled through the ear canal, and reach the tympanic membrane (eardrum). These vibrations are transmitted via the middle ear's ossicles to the inner ear's cochlea.
When viewed cross-sectionally, the cochlea reveals the scala vestibuli and scala tympani flanking the...
Hearing01:31

Hearing

When we hear a sound, our nervous system is detecting sound waves—pressure waves of mechanical energy traveling through a medium. The frequency of the wave is perceived as pitch, while the amplitude is perceived as loudness.
Association Areas of the Cortex01:21

Association Areas of the Cortex

Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
Motor and Sensory Areas of the Cortex01:14

Motor and Sensory Areas of the Cortex

The cerebral cortex, the brain's outermost layer, is pivotal in processing complex cognitive tasks, emotions, and various sensory inputs and executing voluntary motor activities. This intricate structure is divided into three primary functional areas: the motor areas, sensory areas, and association areas.
Motor Areas
The motor areas located in the frontal lobe are central to controlling voluntary movements. This region is further subdivided into the primary motor cortex and the premotor cortex.

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Related Experiment Video

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Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities
09:38

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities

Published on: January 29, 2014

Temporal predictive codes for spoken words in auditory cortex.

Pierre Gagnepain1, Richard N Henson, Matthew H Davis

  • 1MRC Cognition and Brain Sciences Unit, Cambridge, UK.

Current Biology : CB
|March 20, 2012
PubMed
Summary
This summary is machine-generated.

Spoken word recognition is efficient because the brain predicts upcoming sounds, not just by competing words. This predictive coding model in the superior temporal gyrus (STG) explains how we quickly identify words.

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Area of Science:

  • Cognitive Neuroscience
  • Computational Linguistics
  • Auditory Processing

Background:

  • Human spoken word recognition is remarkably fast and accurate.
  • The brain identifies words from partial acoustic information, like hearing 'formu…' to recognize 'formula'.
  • Two models exist: lexical competition (words inhibit each other) and segment prediction (predicting upcoming sounds reduces error).

Purpose of the Study:

  • To differentiate between lexical competition and segment prediction models of spoken word recognition.
  • To investigate the neural mechanisms underlying spoken word recognition using magnetoencephalography (MEG).
  • To propose and validate a predictive coding model for auditory processing.

Main Methods:

  • Participants learned novel words (e.g., 'formubo') that resembled existing words ('formula').
  • Computational simulations were used to model lexical competition and segment prediction error.
  • Magnetoencephalography (MEG) recorded brain responses in the superior temporal gyrus (STG) during word recognition tasks.

Main Results:

  • Learning 'formubo' increased lexical competition but reduced segment prediction error for 'formu…'.
  • Divergence in sounds between novel and existing words showed opposing effects on competition and prediction error.
  • MEG data from the STG uniquely supported the segment prediction account.

Conclusions:

  • Spoken word recognition relies on predicting upcoming speech sounds, minimizing prediction errors.
  • A predictive coding model, where STG neurons signal prediction errors, explains recognition efficiency.
  • This model simulates neural activity in auditory regions and clarifies the speed of human word recognition.