Active inference unifies intentional and conflict-resolution imperatives of motor control

The field of motor control has long focused on the achievement of external goals through action (e.g., reaching and grasping objects). However, recent studies in conditions of multisensory conflict, such as when a subject experiences the rubber hand illusion or embodies an avatar in virtual reality, reveal the presence of unconscious movements that are not goal-directed, but rather aim at resolving multisensory conflicts; for example, by aligning the position of a person’s arm with that of an embodied avatar. This second, conflict-resolution imperative of movement control did not emerge in classical studies of motor adaptation and online corrections, which did not allow movements to reduce the conflicts; and has been largely ignored so far in formal theories. Here, we propose a model of movement control grounded in the theory of active inference that integrates intentional and conflict-resolution imperatives. We present three simulations showing that the active inference model is able to characterize movements guided by the intention to achieve an external goal, by the necessity to resolve multisensory conflict, or both. Furthermore, our simulations reveal a fundamental difference between the (active) inference underlying intentional and conflict-resolution imperatives, respectively, by showing that it is driven by two different (model and sensory) kinds of prediction errors. Finally, our simulations show that when movement is only guided by conflict-resolution, the model incorrectly infers that is velocity is zero, as if it was not moving. This result suggests a novel speculative explanation for the fact that people are unaware of their subtle compensatory movements to avoid multisensory conflict. Furthermore, it can potentially help shed light on deficits of motor awareness that arise in psychopathological conditions.

Smoothness discriminates physical from motor imagery practice of arm-reaching movements.

Physical practice (PP) and motor imagery practice (MP) lead to the execution of fast and accurate arm movements. However, there is currently no information about the influence of MP on movement smoothness, nor about which performance parameters best discriminate these practices. In the current study, we assessed motor performances with an arm pointing task with constrained precision before and after PP (n= 15), MP (n= 15), or no practice (n= 15). We analyzed gains between Pre- and Post-Test for five performance parameters: movement duration, mean and maximal velocities, total displacements, and the number of velocity peaks characterizing movement smoothness. The results showed an improvement of performance after PP and MP for all parameters, except for total displacements. The gains for movement duration, and mean and maximal velocities were statistically higher after PP and MP than after no practice, and comparable between practices. However, motor gains for the number of velocity peaks were higher after PP than MP, suggesting that movements were smoother after PP than after MP. A discriminant analysis also identified the number of velocity peaks as the most relevant parameter that differentiated PP from MP. The current results provide evidence that PP and MP specifically modulate movement smoothness during arm reaching tasks. This difference may rely on online corrections through sensory feedback integration, available during PP but not during MP.

Differential effects of cerebellar degeneration on feedforward versus feedback control across speech and reaching movements

Errors that result from a mismatch between predicted movement outcomes and sensory afference are used to correct ongoing movements through feedback control and to adapt feedforward control of future movements. The cerebellum has been identified as a critical part of the neural circuit underlying implicit adaptation across a wide variety of movements (reaching, gait, eye movements, and speech). The contribution of this structure to feedback control is less well understood: although it has recently been shown in the speech domain that individuals with cerebellar degeneration produce even larger online corrections for sensory perturbations than control participants, similar behavior has not been observed in other motor domains. Currently, comparisons across domains are limited by different population samples and potential ceiling effects in existing tasks. To assess the relationship between changes in feedforward and feedback control associated with cerebellar degeneration across motor domains, we evaluated adaptive (feedforward) and compensatory (feedback) responses to sensory perturbations in reaching and speech production in individuals with cerebellar degeneration and neurobiologically healthy controls. As expected, the cerebellar group demonstrated impaired adaptation in both reaching and speech. In contrast, the groups did not differ in their compensatory response in either domain. Moreover, compensatory and adaptive responses in the cerebellar group were not correlated within or across motor domains. Together, these results point to a general impairment in feedforward control with spared feedback control in cerebellar degeneration. However, the magnitude of feedforward impairments and potential changes in feedback-based control manifest in a domain-specific manner across individuals.Significance StatementThe cerebellum contributes to feedforward updating of movement in response to sensory errors, but its role in feedback control is less understood. Here, we tested individuals with cerebellar degeneration (CD), using sensory perturbations to assess adaptation of feedforward control and feedback gains during reaching and speech production tasks. The results confirmed that CD leads to reduced adaption in both domains. However, feedback gains were unaffected by CD in either domain. Interestingly, measures of feedforward and feedback control were not correlated across individuals within or across motor domains. Together, these results indicate a general impairment in feedforward control with spared feedback control in CD. However, the magnitude of feedforward impairments manifests in a domain-specific manner across individuals.

Daily patient geometry correction: application of NAL and eNAL protocols

Purpose: To test the NAL and eNAL correction protocols using daily patient setup displacements.Methods and material: In total, the analysis was performed for 749 and 797 kV CBCT images for gynecological and prostate patients, respectively, each of 30 patients. After the planning procedure, patients were set up on the treatment table in the treatment position every day. The on-line correction protocol was applied. KV CBCT images were acquired by means of x-ray lamp mounted orthogonally on Linac. Patient setup displacement was assigned. NAL and eNAL corrections protocols were simulated using daily data from online corrections for these two groups of patients. The overall systematic error and random error were calculated for each direction.Results: For the prostate group, the random errors for daily Raw data (no correction) in LAT, LONG, and VERT directions were 2.0 mm, 1.6 mm, and 3.2 mm, respectively. For NAL and eNAL protocols, they were in the range of 1.8 mm to 3.2 mm. For the gynecological group, the random errors were: for daily Raw data 2.2 mm, 1.7 mm, and 3.2 mm, respectively. For NAL and eNAL protocols, they were in the range of 2.0 to 3.4 mm.For the prostate group, values of systematic errors 1.8 mm, 1.8 mm, and 3.3 mm, respectively for Raw data. For NAL and eNAL protocols, these values were less than 1.8 mm. For the gynecological group, the systematic errors were 2.6 mm, 2.3 mm, and 2.8 mm, respectively, for Raw data. For NAL ana eNAL protocols less than 1.8 mm.For the gynecological group, for Raw data, 45% of the total displacement vectors exceeded 5 mm, whereas only 25% did after the NAL procedure and 29% after the eNAL procedure. For the prostate group, for Raw data, 34% of the total displacement vectors exceeded 5 mm, whereas only 22% did after NAL procedure and 28% after eNAL procedure Conclusions: For gynecological and prostate cancer patients, the NAL and eNAL correction protocols can be safely applied to substantially reduce setup errors.

How a mouse licks a spout: Cortex-dependent corrections as the tongue reaches for, and misses, targets

Precise tongue control is necessary for drinking, eating, and vocalizing1, 2. Yet because tongue movements are fast and difficult to resolve, neural control of lingual kinematics remains poorly understood. Here we combine kilohertz frame-rate imaging and a deep learning based neural network to resolve 3D tongue kinematics in mice drinking from a water spout. Successful licks required previously unobserved corrective submovements (CSMs) which, like online corrections during primate reaches3–10, occurred after the tongue missed unseen, distant, or displaced targets. Photoinhibition of anterolateral motor cortex (ALM) impaired online corrections, resulting in hypometric licks that missed the spout. ALM neural activity reflected upcoming, ongoing, and past CSMs, as well as errors in predicted spout contact. Though less than a tenth of a second in duration, a single mouse lick exhibits hallmarks of online motor control associated with a primate reach, including cortex-dependent corrections after misses.

Learning feedback and feedforward control in a mirror-reversed visual environment

When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers.

Online gain update for manual following response accompanied by gaze shift during arm reaching

To capture objects by hand, online motor corrections are required to compensate for self-body movements. Recent studies have shown that background visual motion, usually caused by body movement, plays a significant role in such online corrections. Visual motion applied during a reaching movement induces a rapid and automatic manual following response (MFR) in the direction of the visual motion. Importantly, the MFR amplitude is modulated by the gaze direction relative to the reach target location (i.e., foveal or peripheral reaching). That is, the brain specifies the adequate visuomotor gain for an online controller based on gaze-reach coordination. However, the time or state point at which the brain specifies this visuomotor gain remains unclear. More specifically, does the gain change occur even during the execution of reaching? In the present study, we measured MFR amplitudes during a task in which the participant performed a saccadic eye movement that altered the gaze-reach coordination during reaching. The results indicate that the MFR amplitude immediately after the saccade termination changed according to the new gaze-reach coordination, suggesting a flexible online updating of the MFR gain during reaching. An additional experiment showed that this gain updating mostly started before the saccade terminated. Therefore, the MFR gain updating process would be triggered by an ocular command related to saccade planning or execution based on forthcoming changes in the gaze-reach coordination. Our findings suggest that the brain flexibly updates the visuomotor gain for an online controller even during reaching movements based on continuous monitoring of the gaze-reach coordination.