Analyzing the Auditory Scene: Neurophysiologic Evidence of a Dissociation Between Detection of Regularity and Detection of Change

Alessia Pannese, Christoph S. Herrmann, Elyse Sussman

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

Detecting regularity and change in the environment is crucial for survival, as it enables making predictions about the world and informing goal-directed behavior. In the auditory modality, the detection of regularity involves segregating incoming sounds into distinct perceptual objects (stream segregation). The detection of change from this within-stream regularity is associated with the mismatch negativity, a component of auditory event-related brain potentials (ERPs). A central unanswered question is how the detection of regularity and the detection of change are interrelated, and whether attention affects the former, the latter, or both. Here we show that the detection of regularity and the detection of change can be empirically dissociated, and that attention modulates the detection of change without precluding the detection of regularity, and the perceptual organization of the auditory background into distinct streams. By applying frequency spectra analysis on the EEG of subjects engaged in a selective listening task, we found distinct peaks of ERP synchronization, corresponding to the rhythm of the frequency streams, independently of whether the stream was attended or ignored. Our results provide direct neurophysiological evidence of regularity detection in the auditory background, and show that it can occur independently of change detection and in the absence of attention.

Original languageEnglish (US)
Pages (from-to)411-422
Number of pages12
JournalBrain Topography
Volume28
Issue number3
DOIs
StatePublished - May 1 2015

Keywords

  • Auditory scene analysis
  • Event-related potentials
  • Mismatch negativity
  • Stream segregation

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

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