Abstract
This study investigates adaptation of high-frequency cortical responses [_60 Hz; high-gamma (HG)] to simple and complex sounds in human nonprimary auditory cortex. We used intracranial electrocorticographic recordings to measure event-related changes in HG power as a function of stimulus probability. Tone and speech stimuli were presented in a series of traditional oddball and control paradigms. We hypothesized that HG power attenuates with stimulus repetition over multiple concurrent time scales in auditory association cortex. Timefrequency analyses were performed to identify auditory-responsive sites. Single-trial analyses and quantitative modeling were then used to measure trial-to-trial changes in HG power for high (frequent), low (infrequent), and equal (control) stimulus probabilities. Results show strong reduction of HG responses to frequently repeated tones and speech, with no differences in responses to infrequent and equalprobability stimuli. Adaptation of the HG frequent response, and not stimulus-acoustic differences or deviance-detection enhancement effects, accounted for the differential responses observed for frequent and infrequent sounds. Adaptation of HG responses showed a rapid onset (less than two trials) with slower adaptation between consecutive, repeated trials (2-10 s) and across trials in a stimulus block (∼7 min). The auditory-evoked N100 response also showed repetitionrelated adaptation, consistent with previous human scalp and animal single-unit recordings. These findings indicate that HG responses are highly sensitive to the regularities of simple and complex auditory events and show adaptation on multiple concurrent time scales in human auditory association cortex.
Original language | English (US) |
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Pages (from-to) | 2147-2163 |
Number of pages | 17 |
Journal | Journal of neurophysiology |
Volume | 112 |
Issue number | 9 |
DOIs | |
State | Published - Nov 1 2014 |
Keywords
- Adaptation
- Auditory cortex
- Deviance detection
- Electrocorticography
- Gamma
- Oddball
ASJC Scopus subject areas
- General Neuroscience
- Physiology