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Related Experiment Video

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Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
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Temporal context in speech processing and attentional stream selection: a behavioral and neural perspective.

Elana M Zion Golumbic1, David Poeppel, Charles E Schroeder

  • 1Department of Psychiatry, Columbia University Medical Center, 710 W 168th St., New York, NY 10032, USA. ezg2101@columbia.edu

Brain and Language
|January 31, 2012
PubMed
Summary

Neural oscillations entrain to speech's temporal structure, aiding speech decoding and attention. This "Active Sensing" model explains how the brain processes complex auditory information, like in the "Cocktail Party" effect.

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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

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Area of Science:

  • Neuroscience
  • Auditory Perception
  • Cognitive Science

Background:

  • Human speech processing is complex, involving concurrent information across multiple timescales.
  • The 'Cocktail Party' effect highlights the brain's ability to selectively attend to one sound source amidst noise.
  • Neural mechanisms for real-time speech decoding and attentional selection remain poorly understood.

Purpose of the Study:

  • To review behavioral and neurophysiological evidence on the role of speech's temporal structure in perception.
  • To discuss the hypothesis that neural oscillation entrainment facilitates speech decoding and attentional stream selection.
  • To frame speech processing and attention within the 'Active Sensing' framework.

Main Methods:

  • Review of existing behavioral investigations.
  • Synthesis of neurophysiological study findings.
  • Theoretical discussion of neural oscillation entrainment and active sensing.

Main Results:

  • The temporal structure of speech is crucial for perceptual feats like decoding and stream selection.
  • Neuronal oscillations entrain to speech's temporal structure across multiple timescales.
  • This entrainment is hypothesized to facilitate speech decoding and attentional selection.

Conclusions:

  • Speech decoding and attentional stream selection are examples of 'Active Sensing'.
  • Active Sensing involves a dynamic interplay between top-down predictive modulation and bottom-up sensory input.
  • Understanding neural entrainment to speech's temporal dynamics is key to elucidating these cognitive functions.