by Stefan Dürschmid, Erik Edwards, Christoph Reichert, Callum Dewar, Hermann Hinrichs, Hans-Jochen Heinze, Heidi E. Kirsch, Sarang S. Dalal, Leon Y. Deouell, Robert T. Knight
Abstract:
Predictive coding theories posit that neural networks learn statistical regularities in the environment for comparison with actual outcomes, signaling a prediction error (PE) when sensory deviation occurs. PE studies in audition have capitalized on low-frequency event-related potentials (LF-ERPs), such as the mismatch negativity. However, local cortical activity is well-indexed by higher-frequency bands [high-γ band (Hγ): 80–150 Hz]. We compared patterns of human Hγ and LF-ERPs in deviance detection using electrocorticographic recordings from subdural electrodes over frontal and temporal cortices. Patients listened to trains of task-irrelevant tones in two conditions differing in the predictability of a deviation from repetitive background stimuli (fully predictable vs. unpredictable deviants). We found deviance-related responses in both frequency bands over lateral temporal and inferior frontal cortex, with an earlier latency for Hγ than for LF-ERPs. Critically, frontal Hγ activity but not LF-ERPs discriminated between fully predictable and unpredictable changes, with frontal cortex sensitive to unpredictable events. The results highlight the role of frontal cortex and Hγ activity in deviance detection and PE generation.
Reference:
Hierarchy of prediction errors for auditory events in human temporal and frontal cortex (Stefan Dürschmid, Erik Edwards, Christoph Reichert, Callum Dewar, Hermann Hinrichs, Hans-Jochen Heinze, Heidi E. Kirsch, Sarang S. Dalal, Leon Y. Deouell, Robert T. Knight), In Proceedings of the National Academy of Sciences, 2016.
Bibtex Entry:
@article{durschmid_hierarchy_2016,
	title = {Hierarchy of prediction errors for auditory events in human temporal and frontal cortex},
	url = {http://www.pnas.org/content/early/2016/05/26/1525030113.abstract},
	doi = {10.1073/pnas.1525030113},
	abstract = {Predictive coding theories posit that neural networks learn statistical regularities in the environment for comparison with actual outcomes, signaling a prediction error (PE) when sensory deviation occurs. PE studies in audition have capitalized on low-frequency event-related potentials (LF-ERPs), such as the mismatch negativity. However, local cortical activity is well-indexed by higher-frequency bands [high-γ band (Hγ): 80–150 Hz]. We compared patterns of human Hγ and LF-ERPs in deviance detection using electrocorticographic recordings from subdural electrodes over frontal and temporal cortices. Patients listened to trains of task-irrelevant tones in two conditions differing in the predictability of a deviation from repetitive background stimuli (fully predictable vs. unpredictable deviants). We found deviance-related responses in both frequency bands over lateral temporal and inferior frontal cortex, with an earlier latency for Hγ than for LF-ERPs. Critically, frontal Hγ activity but not LF-ERPs discriminated between fully predictable and unpredictable changes, with frontal cortex sensitive to unpredictable events. The results highlight the role of frontal cortex and Hγ activity in deviance detection and PE generation.},
	journal = {Proceedings of the National Academy of Sciences},
	author = {Dürschmid, Stefan and Edwards, Erik and Reichert, Christoph and Dewar, Callum and Hinrichs, Hermann and Heinze, Hans-Jochen and Kirsch, Heidi E. and Dalal, Sarang S. and Deouell, Leon Y. and Knight, Robert T.},
	month = may,
	year = {2016}
}