4.7 Article

Processing asymmetry of transitions between order and disorder in human auditory cortex

Journal

JOURNAL OF NEUROSCIENCE
Volume 27, Issue 19, Pages 5207-5214

Publisher

SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.0318-07.2007

Keywords

auditory evoked response; magnetoencephalography; auditory cortex; integration window; change detection; scene analysis; M100; M50; MMN

Categories

Funding

  1. NIDCD NIH HHS [R01 DC005660, R01DC05660] Funding Source: Medline

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Auditory environments vary as a result of the appearance and disappearance of acoustic sources, as well as fluctuations characteristic of the sources themselves. The appearance of an object is often manifest as a transition in the pattern of ongoing fluctuation, rather than an onset or offset of acoustic power. How does the system detect and process such transitions? Based on magnetoencephalography data, we show that the temporal dynamics and response morphology of the neural temporal-edge detection processes depend in precise ways on the nature of the change. We measure auditory cortical responses to transitions between disorder, modeled as a sequence of random frequency tone pips, and order, modeled as a constant tone. Such transitions embody key characteristics of natural auditory edges. Early cortical responses (from similar to 50 ms post-transition) reveal that order-disorder transitions, and vice versa, are processed by different neural mechanisms. Their dynamics suggest that the auditory cortex optimally adjusts to stimulus statistics, even when this is not required for overt behavior. Furthermore, this response profile bears a striking similarity to that measured from another order-disorder transition, between interaurally correlated and uncorrelated noise, a radically different stimulus. This parallelism suggests the existence of a general mechanism that operates early in the processing stream on the abstract statistics of the auditory input, and is putatively related to the processes of constructing a new representation or detecting a deviation from a previously acquired model of the auditory scene. Together, the data reveal information about the mechanisms with which the brain samples, represents, and detects changes in the environment.

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