Schmitter, C., Steinsträter, O., Kircher, T., van Kemenade, B.M.*, Straube, B.* (accepted). Commonalities and differences in predictive neural processing of discrete vs continuous action feedback. NeuroImage *contributed equally
Sensory action consequences are highly predictable and thus engage less neural resources compared to externally generated sensory events. While this has frequently been observed to lead to attenuated perceptual sensitivity and suppression of activity in sensory cortices, some studies conversely reported enhanced perceptual sensitivity for action consequences. These divergent findings might be explained by the type of action feedback, i.e., discrete outcomes vs. continuous feedback. Therefore, in the present study we investigated the impact of discrete and continuous action feedback on perceptual and neural processing during action feedback monitoring.
During fMRI data acquisition, participants detected temporal delays (0-417ms) between actively or passively generated wrist movements and visual feedback that was either continuously provided during the movement or that appeared as a discrete outcome.
Both feedback types resulted in (1) a neural suppression effect (active<passive) in a largely shared network including bilateral visual and somatosensory cortices, cerebellum and temporoparietal areas. Yet, compared to discrete outcomes, (2) processing continuous feedback led to stronger suppression in right superior temporal gyrus (STG), Heschl´s gyrus, and insula suggesting specific suppression of features linked to continuous feedback. Furthermore, (3) BOLD suppression in visual cortex for discrete outcomes was specifically related to perceptual enhancement.
Together, these findings indicate that neural representations of discrete and continuous action feedback are similarly suppressed but might depend on different predictive mechanisms, where reduced activation in visual cortex reflects facilitation specifically for discrete outcomes, and predictive processing in STG, Heschl´s gyrus, and insula is particularly relevant for continuous feedback.