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Performance monitoring for sensorimotor confidence: A visuomotor tracking study.

ABSTRACT: To best interact with the external world, humans are often required to consider the quality of their actions. Sometimes the environment furnishes rewards or punishments to signal action efficacy. However, when such feedback is absent or only partial, we must rely on internally generated signals to evaluate our performance (i.e., metacognition). Yet, very little is known about how humans form such judgements of sensorimotor confidence. Do they monitor their actual performance or do they rely on cues to sensorimotor uncertainty? We investigated sensorimotor metacognition in two visuomotor tracking experiments, where participants followed an unpredictably moving dot cloud with a mouse cursor as it followed a random horizontal trajectory. Their goal was to infer the underlying target generating the dots, track it for several seconds, and then report their confidence in their tracking as better or worse than their average. In Experiment 1, we manipulated task difficulty with two methods: varying the size of the dot cloud and varying the stability of the target's velocity. In Experiment 2, the stimulus statistics were fixed and duration of the stimulus presentation was varied. We found similar levels of metacognitive sensitivity in all experiments, which was evidence against the cue-based strategy. The temporal analysis of metacognitive sensitivity revealed a recency effect, where error later in the trial had a greater influence on the sensorimotor confidence, consistent with a performance-monitoring strategy. From these results, we conclude that humans predominantly monitored their tracking performance, albeit inefficiently, to build a sense of sensorimotor confidence.

SUBMITTER: Locke SM

PROVIDER: S-EPMC7669557 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeThe purpose of this study was to utilize a visuomotor tracking task, with both the jaw and hand, to add to the literature regarding non-speech motor practice and sensorimotor integration (outside of auditory-motor integration domain) in adults who do (PWS) and do not (PWNS) stutter.MethodParticipants were 15 PWS (14 males, mean age = 27.0) and 15 PWNS (14 males, mean age = 27.2). Participants tracked both predictable and unpredictable moving targets separately with their jaw and their dominant hand, and accuracy was assessed by calculating phase and amplitude difference between the participant and the target. Motor practice effect was examined by comparing group performance over consecutive tracking trials of predictable conditions as well as within the first trial of same conditions.ResultsResults showed that compared to PWNS, PWS were not significantly different in matching either the phase (timing) or the amplitude of the target in both jaw and hand tracking of predictable and unpredictable targets. Further, there were no significant between-group differences in motor practice effects for either jaw or hand tracking. Both groups showed improved tracking accuracy within and between the trials.ConclusionOur findings revealed no statistically significant differences in non-speech motor practice effects and integration of sensorimotor feedback between PWS and PWNS, at least in the context of the visuomotor tracking tasks employed in the study. In general, both talker groups exhibited practice effects (i.e., increased accuracy over time) within and between tracking trials during both jaw and hand tracking. Implications for these results are discussed.Educational objectivesThe reader will be able to: (a) describe the importance of motor learning and sensory-motor integration for speech, (b) summarize past research on PWS's performance during speech and nonspeech motor tasks, and (c) describe the relation between different aspects of speech and non-speech motor control and stuttering.

Project description:Humans can learn and store multiple visuomotor mappings (dual-adaptation) when feedback for each is provided alternately. Moreover, learned context cues associated with each mapping can be used to switch between the stored mappings. However, little is known about the associative learning between cue and required visuomotor mapping, and how learning generalises to novel but similar conditions. To investigate these questions, participants performed a rapid target-pointing task while we manipulated the offset between visual feedback and movement end-points. The visual feedback was presented with horizontal offsets of different amounts, dependent on the targets shape. Participants thus needed to use different visuomotor mappings between target location and required motor response depending on the target shape in order to "hit" it. The target shapes were taken from a continuous set of shapes, morphed between spiky and circular shapes. After training we tested participants performance, without feedback, on different target shapes that had not been learned previously. We compared two hypotheses. First, we hypothesised that participants could (explicitly) extract the linear relationship between target shape and visuomotor mapping and generalise accordingly. Second, using previous findings of visuomotor learning, we developed a (implicit) Bayesian learning model that predicts generalisation that is more consistent with categorisation (i.e. use one mapping or the other). The experimental results show that, although learning the associations requires explicit awareness of the cues' role, participants apply the mapping corresponding to the trained shape that is most similar to the current one, consistent with the Bayesian learning model. Furthermore, the Bayesian learning model predicts that learning should slow down with increased numbers of training pairs, which was confirmed by the present results. In short, we found a good correspondence between the Bayesian learning model and the empirical results indicating that this model poses a possible mechanism for simultaneously learning multiple visuomotor mappings.

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Performance monitoring for sensorimotor confidence: A visuomotor tracking study.

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