Browsing by Author "Sullivan, Seth R."

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    Roles and interplay of reinforcement-based and error-based processes during reaching and gait in neurotypical adults and individuals with Parkinson’s disease
    (PLoS Computational Biology, 2024-10-14) Roth, Adam M.; Buggeln, John H.; Hoh, Joanna E.; Wood, Jonathan M.; Sullivan, Seth R.; Ngo, Truc T.; Calalo, Jan A.; Lokesh, Rakshith; Morton, Susanne M.; Grill, Stephen; Jeka, John J.; Carter, Michael J.; Cashaback, Joshua G. A.
    From a game of darts to neurorehabilitation, the ability to explore and fine tune our movements is critical for success. Past work has shown that exploratory motor behaviour in response to reinforcement (reward) feedback is closely linked with the basal ganglia, while movement corrections in response to error feedback is commonly attributed to the cerebellum. While our past work has shown these processes are dissociable during adaptation, it is unknown how they uniquely impact exploratory behaviour. Moreover, converging neuroanatomical evidence shows direct and indirect connections between the basal ganglia and cerebellum, suggesting that there is an interaction between reinforcement-based and error-based neural processes. Here we examine the unique roles and interaction between reinforcement-based and error-based processes on sensorimotor exploration in a neurotypical population. We also recruited individuals with Parkinson’s disease to gain mechanistic insight into the role of the basal ganglia and associated reinforcement pathways in sensorimotor exploration. Across three reaching experiments, participants were given either reinforcement feedback, error feedback, or simultaneously both reinforcement & error feedback during a sensorimotor task that encouraged exploration. Our reaching results, a re-analysis of a previous gait experiment, and our model suggests that in isolation, reinforcement-based and error-based processes respectively boost and suppress exploration. When acting in concert, we found that reinforcement-based and error-based processes interact by mutually opposing one another. Finally, we found that those with Parkinson’s disease had decreased exploration when receiving reinforcement feedback, supporting the notion that compromised reinforcement-based processes reduces the ability to explore new motor actions. Understanding the unique and interacting roles of reinforcement-based and error-based processes may help to inform neurorehabilitation paradigms where it is important to discover new and successful motor actions. Author summary Reinforcement-based and error-based processes play a pivotal role in regulating our movements. Converging neuroanatomical evidence show interconnected reinforcement-based and error-based neural circuits. Yet is unclear how reinforcement-based and error-based processes interact to influence sensorimotor behavior. In our past work we showed that reinforcement-based and error-based processes are dissociable. Building on this work, here we show that these process can also interact to influence trial-by-trial sensorimotor behaviour.
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    The Sensorimotor System Modulates Muscular Co-Contraction Relative to Visuomotor Feedback Responses to Regulate Movement Variability
    (Journal of Neurophysiology, 2023-04-01) Calalo, Jan A.; Roth, Adam M.; Lokesh, Rakshith; Sullivan, Seth R.; Wong, Jeremy D.; Semrau, Jennifer A.; Cashaback, Joshua G. A.
    The naturally occurring variability in our movements often poses a significant challenge when attempting to produce precise and accurate actions, which is readily evident when playing a game of darts. Two differing, yet potentially complementary, control strategies that the sensorimotor system may use to regulate movement variability are impedance control and feedback control. Greater muscular co-contraction leads to greater impedance that acts to stabilize the hand, while visuomotor feedback responses can be used to rapidly correct for unexpected deviations when reaching toward a target. Here, we examined the independent roles and potential interplay of impedance control and visuomotor feedback control when regulating movement variability. Participants were instructed to perform a precise reaching task by moving a cursor through a narrow visual channel. We manipulated cursor feedback by visually amplifying movement variability and/or delaying the visual feedback of the cursor. We found that participants decreased movement variability by increasing muscular co-contraction, aligned with an impedance control strategy. Participants displayed visuomotor feedback responses during the task but, unexpectedly, there was no modulation between conditions. However, we did find a relationship between muscular co-contraction and visuomotor feedback responses, suggesting that participants modulated impedance control relative to feedback control. Taken together, our results highlight that the sensorimotor system modulates muscular co-contraction, relative to visuomotor feedback responses, to regulate movement variability and produce accurate actions. NEW & NOTEWORTHY: The sensorimotor system has the constant challenge of dealing with the naturally occurring variability in our movements. Here, we investigated the potential roles of muscular co-contraction and visuomotor feedback responses to regulate movement variability. When we visually amplified movements, we found that the sensorimotor system primarily uses muscular co-contraction to regulate movement variability. Interestingly, we found that muscular co-contraction was modulated relative to inherent visuomotor feedback responses, suggesting an interplay between impedance and feedback control.
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    Visual accuracy dominates over haptic speed for state estimation of a partner during collaborative sensorimotor interactions
    (Journal of Neurophysiology, 2023-07-01) Lakesh, Rakshith; Sullivan, Seth R.; Germain, Laura St.; Roth, Adam M.; Calalo, Jan A.; Buggeln, John; Ngo, Truc; Marchhart, Vanessa R. F.; Carter, Michael J.; Cashaback, Joshua G. A.
    We routinely have physical interactions with others, whether it be handing someone a glass of water or jointly moving a heavy object together. These sensorimotor interactions between humans typically rely on visual feedback and haptic feedback. Recent single-participant studies have highlighted that the unique noise and time delays of each sense must be considered to estimate the state, such as the position and velocity, of one’s own movement. However, we know little about how visual feedback and haptic feedback are used to estimate the state of another person. Here, we tested how humans utilize visual feedback and haptic feedback to estimate the state of their partner during a collaborative sensorimotor task. Across two experiments, we show that visual feedback dominated haptic feedback during collaboration. Specifically, we found that visual feedback led to comparatively lower task-relevant movement variability, smoother collaborative movements, and faster trial completion times. We also developed an optimal feedback controller that considered the noise and time delays of both visual feedback and haptic feedback to estimate the state of a partner. This model was able to capture both lower task-relevant movement variability and smoother collaborative movements. Taken together, our empirical and modeling results support the idea that visual accuracy is more important than haptic speed to perform state estimation of a partner during collaboration. NEW & NOTEWORTHY Physical collaboration between two or more individuals involves both visual and haptic feedback. Here, we investigated how visual and haptic feedback is used to estimate the movements of a partner during a collaboration task. Our experimental and computational modeling results parsimoniously support the notion that greater visual accuracy is more important than faster yet noisier haptic feedback when estimating the state of a partner.