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Related Experiment Video

Updated: May 12, 2026

Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis
10:33

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Left fronto-temporal dynamics during agreement processing: evidence for feature-specific computations.

Nicola Molinaro1, Horacio A Barber, Alejandro Pérez

  • 1BCBL, Basque Center on Cognition, Brain and Language, Donostia, Spain. n.molinaro@bcbl.eu

Neuroimage
|April 23, 2013
PubMed
Summary
This summary is machine-generated.

This study reveals how the brain processes Spanish noun phrase agreement violations. It identifies specific brain regions and timing for number and gender agreement computations, supporting a derivational approach.

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Area of Science:

  • Neuroscience
  • Linguistics
  • Cognitive Science

Background:

  • Grammatical agreement is crucial for syntax and conveys lexical/semantic information.
  • Understanding agreement processing in the brain offers insights into language comprehension.

Purpose of the Study:

  • To investigate the neural basis of number and gender agreement processing in Spanish noun phrases.
  • To identify the temporal dynamics and brain regions involved in agreement violation detection.

Main Methods:

  • Magnetoencephalography (MEG) was used to record brain activity.
  • Spanish noun phrases with number or gender agreement violations were presented to participants.
  • Brain activity was time-locked to the onset of the noun.

Main Results:

  • A left-lateralized network involving anterior temporal and ventro-lateral prefrontal regions was activated by agreement violations.
  • Occipito-temporal regions showed early activation for number marking analysis (~170 ms).
  • Anterior temporal regions were sensitive to gender mismatches (~170 ms), and left superior temporal regions reflected semantic relevance of number (~340 ms).

Conclusions:

  • The brain employs multi-level analyses for agreement computation, with distinct temporal and spatial patterns for number and gender.
  • Findings support a derivational approach to agreement computation in language processing.