کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6262797 | 1613813 | 2015 | 10 صفحه PDF | دانلود رایگان |
- Encoding of an alternation rule was tested by chirp- and omission-evoked responses.
- Predictability modulated chirp-evoked responses at the Na component of the MLR.
- Omission-evoked responses were affected by predictability later than the MLR range.
- Regular sequences engaged the right hemisphere stronger than the left hemisphere.
- Regularity encoding is organized in a hierarchical manner.
By encoding acoustic regularities present in the environment, the human brain can generate predictions of what is likely to occur next. Recent studies suggest that deviations from encoded regularities are detected within 10-50Â ms after stimulus onset, as indicated by electrophysiological effects in the middle latency response (MLR) range. This is upstream of previously known long-latency (LLR) signatures of deviance detection such as the mismatch negativity (MMN) component. In the present study, we created predictable and unpredictable contexts to investigate MLR and LLR signatures of the encoding of spatial auditory regularities and the generation of predictions from these regularities. Chirps were monaurally delivered in an either regular (predictable: left-right-left-right) or a random (unpredictable left/right alternation or repetition) manner. Occasional stimulus omissions occurred in both types of sequences. Results showed that the Na component (peaking at 34Â ms after stimulus onset) was attenuated for regular relative to random chirps, albeit no differences were observed for stimulus omission responses in the same latency range. In the LLR range, larger chirp-and omission-evoked responses were elicited for the regular than for the random condition, and predictability effects were more prominent over the right hemisphere. We discuss our findings in the framework of a hierarchical organization of spatial regularity encoding.This article is part of a Special Issue entitled SI: Prediction and Attention.
Journal: Brain Research - Volume 1626, 11 November 2015, Pages 21-30