Task‐dependent responses to muscle vibration during reaching

Abstract

Feedback corrections in reaching have been shown to be task‐dependent for proprioceptive, visual and vestibular perturbations, in line with predictions from optimal feedback control theory. Mechanical perturbations have been used to elicit proprioceptive errors, but have the drawback to actively alter the limb's trajectory, making it nontrivial to dissociate the subject's compensatory response from the perturbation itself. In contrast, muscle vibration provides an alternative tool to perturb the muscle afferents without changing the hands trajectory, inducing only changes in the estimated, but not the actual, limb position and velocity. Here, we investigate whether upper‐arm muscle vibration is sufficient to evoke task‐dependent feedback corrections during goal‐directed reaching to a narrow versus a wide target. Our main result is that for vibration of biceps and triceps, compensatory responses were down‐regulated for the wide compared to the narrow target. The earliest detectable difference between these target‐specific corrections is at about 100 ms, likely reflecting a task‐dependent feedback control policy rather than a voluntary response.

Integration of proprioceptive and visual feedback during online control of reaching

“…Although it is clear that visual and proprioceptive feedback can generate rapid motor responses to counter errors or disturbances, most research has focused on exploring how each sensory modality on its own influences motor output. These studies highlight that mechanical disturbances of the arm elicit a spinal stretch reflex in as little as 25 ms that predominantly considers disturbance size, and a second response beginning at 60 ms that includes transcortical feedback and considers a broad range of contexts such as target redundancy and the presence of obstacles ( 4 – 8 ). Similarly, visual shifts elicit two different motor responses: one motor response starting at 90 ms that considers the shift size, task relevance of the disturbances (i.e., statistical properties of the environment), and the distance to the target at the point a disturbance was applied ( 9 – 14 ).…”

Somatosensory deafferentation reveals lateralized roles of proprioception in feedback and adaptive feedforward control of movement and posture

“…Feedforward mechanisms provide the ability to anticipate system responses to future output and, thus, allow for stability of behavior when predictions are fairly accurate. It should be stressed that feedforward mechanisms can be used to modulate feedback systems, allowing robustness in the face of inaccurate predictions due to environmental variations, prediction errors, and/or neural noise (see [9][10][11][12] for recent articles on optimal feedback control and gain modulation).…”

Proprioceptive and visual feedback responses in macaques exploit goal redundancy

“…A common approach is to have participants reach to a spatially redundant goal such as a wide rectangular bar (Knill et al, 2011;Nashed et al, 2012;de Brouwer et al, 2017;Keyser et al, 2017Keyser et al, , 2019. Participants exhibit greater trial-to-trial variability in their reach endpoints when reaching for a wide as compared to a narrow goal.…”

“…Differences in these corrective responses arise in muscle activity ~90ms after the jump (Franklin and Wolpert, 2008;Cross et al, 2019). Similar corrective responses occur when mechanical loads are applied to the limb with differences between corrective responses starting ~70ms after the load (Nashed et al, 2012;Lowrey et al, 2017;Keyser et al, 2019). However, despite the prevalence of OFC as a theory of motor control, we know little about the neural circuits used to generate OFC-like behaviours.…”

“…Several studies demonstrate that the motor system exploits task redundancies similar to OFC controllers (Diedrichsen, 2007; Dimitriou et al, 2012; Cluff and Scott, 2015; Weiler et al, 2015, 2016). A common approach is to have participants reach to a spatially redundant goal such as a wide rectangular bar (Knill et al, 2011; Nashed et al, 2012; de Brouwer et al, 2017; Keyser et al, 2017, 2019). Participants exhibit greater trial-to-trial variability in their reach endpoints when reaching for a wide as compared to a narrow goal.…”