It is widely believed that predicted tactile action outcomes are perceptually attenuated. The present experiments determined whether predictive mechanisms necessarily generate attenuation or, instead, can enhance perception—as typically observed in sensory cognition domains outside of action. We manipulated probabilistic expectations in a paradigm often used to demonstrate tactile attenuation. Adult participants produced actions and subsequently rated the intensity of forces on a static finger. Experiment 1 confirmed previous findings that action outcomes are perceived less intensely than passive stimulation but demonstrated more intense perception when active finger stimulation was removed. Experiments 2 and 3 manipulated prediction explicitly and found that expected touch during action is perceived more intensely than unexpected touch. Computational modeling suggested that expectations increase the gain afforded to expected tactile signals. These findings challenge a central tenet of prominent motor control theories and demonstrate that sensorimotor predictions do not exhibit a qualitatively distinct influence on tactile perception.

It is widely believed that predicted action outcomes are perceptually attenuated. The present experiments determined whether predictive mechanisms in fact generate attenuation, or instead enhance perception -via neural 'sharpening' mechanisms assumed to operate in sensory cognition domains outside of action. We manipulated probabilistic expectations in a force judgement task. Participants produced actions and rated the intensity of concurrent tactile forces. Experiment 1 confirmed previous findings that action outcomes are perceived less intensely than similar passive stimulation, but demonstrated more intense perception when reducing the contribution of non-predictive gating processes. Experiments 2 and 3 manipulated prediction explicitly and found that expected outcomes are perceived more, not less, intensely than unexpected outcomes. These findings challenge a central tenet of prominent motor control theories and demonstrate that sensorimotor prediction operates via qualitatively similar mechanisms to other prediction and regardless of the sensory domain.

Povinelli, Bierschwale, and Cech (1999) reported that when tested on a visual attention task, the behavior of juvenile chimpanzees did not support a high-level understanding of visual attention. This study replicates their research using adult humans and aims to investigate the validity of their experimental design. Participants were trained to respond to pointing cues given by an experimenter, and then tested on their ability to locate hidden objects from visual cues. Povinelli et al.'s assertion that the generalization of pointing to gaze is indicative of a high-level framework was not supported by our findings: Training improved performance only on initial probe trials when the experimenter's gaze was not directed at the baited cup. Furthermore, participants performed above chance on such trials, the same result exhibited by chimpanzees and used as evidence by Povinelli et al. to support a low-level framework. These findings, together with the high performance of participants in an incongruent condition, in which the experimenter pointed to or gazed at an unbaited container, challenge the validity of their experimental design.

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Perceivers can use past experiences to make sense of ambiguous sensory signals. However, this may be inappropriate when the world changes and past experiences no longer predict what the future holds. Optimal learning models propose that observers decide whether to stick with or update their predictions by tracking the uncertainty or “precision” of their expectations. However, contrasting theories of prediction have argued that we are prone to misestimate uncertainty—leading to stubborn predictions that are difficult to dislodge. To compare these possibilities, we had participants learn novel perceptual predictions before using fMRI to record visual brain activity when predictive contingencies were disrupted—meaning that previously “expected” events become objectively improbable. Multivariate pattern analyses revealed that expected events continued to be decoded with greater fidelity from primary visual cortex, despite marked changes in the statistical structure of the environment, which rendered these expectations no longer valid. These results suggest that our perceptual systems do indeed form stubborn predictions even from short periods of learning—and more generally suggest that top–down expectations have the potential to help or hinder perceptual inference in bounded minds like ours.