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Miller-Mills, B.

Publications and source records attributed to Miller-Mills, B..

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Benefits of dual-tasking on implicit sensorimotor adaptation

Attention plays a crucial role in maintaining precision and effectiveness in goal-directed actions. Although there is evidence that dividing attention across tasks impairs performance in various domains, the impact of attention on sensorimotor adaptation remains inconclusive, with some studies reporting deficits and others showing no effects. Because sensorimotor adaptation arises from the interaction of explicit and implicit processes, this discrepancy may reflect differential effects of attention on each process. Here, we investigate how divided attention influences implicit sensorimotor adaptation using an error-clamp paradigm, coupled with a random dot kinematogram (RDK) motion coherence discrimination task. We also assessed whether the timing of the secondary task affects error processing during sensorimotor adaptation by presenting the RDK either during the outward movement (coinciding with error feedback), or the inward movement (following error feedback). We observed that attentional manipulation influenced implicit sensorimotor adaptation only when the RDK was presented on the outward movement, not the inward movement. Remarkably, implicit sensorimotor adaptation was enhanced when attention was divided, compared to when attention was focused entirely on the adaptation task. This suggests that implicit sensorimotor adaptation is sensitive to attentional demand, particularly during the time window where error feedback is received.

neuroscience↗

Enhanced neural representation of reach target direction for high reward magnitude but not high target probability.

Many characteristics of goal-directed movements, such as their initiation time, initial direction, and speed, are influenced both by the details of previously executed movements (i.e. action history), and by the degree to which previous movements were rewarded or punished (i.e. reward history). In reinforcement learning terms, when movements are externally cued, action and reward history jointly define the probability and magnitude of positive/negative outcomes of available options, and therefore their pre-stimulus expected value. To dissociate which of these neurocomputational variables influence sensorimotor brain processing, we studied how reach behaviour and evoked brain responses are affected by independent manipulations of action and reward history. We found that movements were initiated earlier both for more frequently repeated targets and targets associated with higher reward magnitude, but only movements to highly rewarded targets had higher movement speeds. Classical visually-evoked encephalographic (EEG) potentials (P1/N1) were not affected by either reward magnitude or target probability. There were, however, amplified midline ERP responses at centroparietal electrodes for rewarded targets and movements compared to control, but no differences between more frequently presented targets and control. Critically, the spatial precision of decoded target locations extracted from a multivariate linear decoding model of EEG data was greater for target locations associated with higher reward magnitude than for control target locations ([~]150-300ms after target presentation). Again, there were no differences in the precision of decoded target direction representations between more frequent target locations and control target locations. These data suggest that the expected reward magnitude associated with an action, rather than its long-run expected value, determines the precision of early sensorimotor processing. Significance StatementWe move more quickly and more accurately toward goals that we value more highly, and this is due partly to enhanced motor preparation. However, our expectations about the value of an action depend both on the probability of its requirement and the magnitude of the reward associated with it. Here we disentangled the influence of reward magnitude and probability on early sensorimotor processing via a multivariate linear decoding approach to extract target direction from scalp encephalograms. We found that the spatial precision of decoded target direction was greater for high reward targets but not for more probable targets. Thus, early sensorimotor processing is sharpened when the magnitude of reward associated with movement to a cued target is high. HighlightsO_LIThe direction of movement can be reliably decoded from the scalp EEG from [~]80ms after target presentation. C_LIO_LIThe neural representation of movement direction is more precise for targets that are associated with high reward, but not for targets that are more probable. C_LIO_LIThe magnitude of reward associated with movement to a presented target, rather than the long-run expected value of the movement, sharpens the spatial precision of early sensorimotor processing. C_LI

neuroscience↗