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.predictive coding | prediction error | mismatch negativity | frontal cortex | high γ-activity
Change blindness is the failure to detect changes in visual scenes. Changes can elicit phenomenologically different perceptual experiences, possibly relating to different mechanisms: changes may be entirely missed, merely detected, located, or identified. We presented sequences of meaningful objects, one of which could change between the presentations. Changes had to be located and identified. Observers sometimes located the change without knowing which object had changed. However, effects of localization with and without identification were remarkably similar on a sequence of event-related potential components (including change-related positivity and N2pc). Only a late contralateral positivity was found exclusively for identified changes, indicating that change localization and change identification initially rely on a common processing sequence and differ only at later stages.
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