Human Auditory Cortical Processing of Transitions Between ‘Order’ and ‘Disorder’
Sensitivity to changes in sound is important to auditory scene analysis and detection of the appearance of new objects in the environment. In this chapter we describe two experiments that used Magnetoencephalography (MEG) to investigate the temporal dynamics of auditory cortical responses to changes in ongoing stimuli. The experiments used very different stimuli (dichotic vs diotic, noiselike vs tonal, stationary vs dynamic), but shared the abstract characteristic that they both involved a transition from a state of order to disorder, or viceversa (Fig. 1). In one experiment (Chait et al. 2005) we studied changes in the interaural correlation (IAC) of wide-band noise. Stimuli consisted of interaurally correlated noise (identical noise signals played to the two ears) that changed into uncorrelated noise (different noise signals at the two ears) or vice versa. The stimuli of the second experiment (Chait et al. 2007) were designed to mimic the abstract properties of those in the IAC experiment, while changing the acoustic properties completely. Signals consisted of a constant tone that changed into a sequence of random tone pips, or vice versa. In both experiments, magnetic responses were gathered while subjects attended to an auditory task unrelated to the dimension along which the stimuli varied. The responses are thus presumed to reflect pre-attentive ‘bottom-up’ mechanisms, processing aspects of sound that the subject does not attend to consciously.
Unable to display preview. Download preview PDF.
- Polich J (2003) Detection of change: event related potential and fMRI findings. Kluwer Academic Press, Boston, MA.Google Scholar
- Chait M, Poeppel D, Simon JZ (in press) Stimulus contexts affects auditory cortical responses to changes in interaural correlation. J NeurophysiolGoogle Scholar
- Rupp A, Uppenkamp S, Bailes J, Gutschalk A, Patterson RD (2005) Time constants in temporal pitch extraction: a comparison of psychophysical and magnetic data. In: Pressnitzer D, de Cheveigné A, McAdams S, Collet L (eds) Auditory signal processing: physiology, psychoacoustics, and models. Springer, Berlin Heidelberg New York, pp 119–125.Google Scholar