Beta-triggered adaptive deep brain stimulation during reaching movement in Parkinson's disease.

Subthalamic nucleus (STN) beta-triggered adaptive deep brain stimulation (ADBS) has been shown to provide clinical improvement comparable to conventional continuous DBS (CDBS) with less energy delivered to the brain and less stimulation induced side effects. However, several questions remain unanswered. First, there is a normal physiological reduction of STN beta band power just prior to and during voluntary movement. ADBS systems will therefore reduce or cease stimulation during movement in people with Parkinson's disease and could therefore compromise motor performance compared to CDBS. Second, beta power was smoothed and estimated over a time period of 400 ms in most previous ADBS studies, but a shorter smoothing period could have the advantage of being more sensitive to changes in beta power, which could enhance motor performance. In this study, we addressed these two questions by evaluating the effectiveness of STN beta-triggered ADBS using a standard 400 ms and a shorter 200 ms smoothing window during reaching movements. Results from 13 people with Parkinson's disease showed that reducing the smoothing window for quantifying beta did lead to shortened beta burst durations by increasing the number of beta bursts shorter than 200 ms and more frequent switching on/off of the stimulator but had no behavioural effects. Both ADBS and CDBS improved motor performance to an equivalent extent compared to no DBS. Secondary analysis revealed that there were independent effects of a decrease in beta power and an increase in gamma power in predicting faster movement speed, while a decrease in beta event related desynchronization (ERD) predicted quicker movement initiation. CDBS suppressed both beta and gamma more than ADBS, whereas beta ERD was reduced to a similar level during CDBS and ADBS compared with no DBS, which together explained the achieved similar performance improvement in reaching movements during CDBS and ADBS. In addition, ADBS significantly improved tremor compared with no DBS but was not as effective as CDBS. These results suggest that STN beta-triggered ADBS is effective in improving motor performance during reaching movements in people with Parkinson's disease, and that shortening of the smoothing window does not result in any additional behavioural benefit. When developing ADBS systems for Parkinson's disease, it might not be necessary to track very fast beta dynamics; combining beta, gamma, and information from motor decoding might be more beneficial with additional biomarkers needed for optimal treatment of tremor.

The effects of a single bout of moderate-intensity aerobic exercise on visuomotor adaptation and its savings.

Performing exercise before or after motor skill learning is thought to have a positive impact on acquisition and retention of motor memories stored in our nervous system. It has been shown that performing 25 min of moderate-intensity aerobic exercise prior to visuomotor adaptation can enhance both visuomotor adaptation and its retention compared to 25 min of rest before the adaptation. To determine whether a single bout of aerobic exercise could actually facilitate the formation of a neural representation associated with a novel visuomotor condition, we examined aftereffects and savings associated with a visuomotor adaptation task following either an exercise or a rest condition. Sixteen healthy young individuals (18-35 years) first experienced 25 min of moderate-intensity cycling or rest, and then adapted to a 30-degree visuomotor rotation condition. Immediately following that, participants experienced a washout session, which was followed by a readaptation session. Results indicated that all subjects adapted to the visuomotor rotation completely, although no difference was found between the cycling and rest conditions. Aftereffects and savings were also observed in both conditions, but with no difference between the conditions. These findings suggest that compared to a short rest session, a single bout of moderate-intensity cycling may not have a greater impact for enhancing visuomotor adaptation and its retention. Further research is needed, in which the effects of certain factors such as exercise intensity, duration and timing are more systematically investigated.

Novel evaluation of upper-limb motor performance after stroke based on normal reaching movement model.

BACKGROUND: Upper-limb rehabilitation robots provide repetitive reaching movement training to post-stroke patients. Beyond a pre-determined set of movements, a robot-aided training protocol requires optimization to account for the individuals' unique motor characteristics. Therefore, an objective evaluation method should consider the pre-stroke motor performance of the affected arm to compare one's performance relative to normalcy. However, no study has attempted to evaluate performance based on an individual's normal performance. Herein, we present a novel method for evaluating upper limb motor performance after a stroke based on a normal reaching movement model. METHODS: To represent the normal reaching performance of individuals, we opted for three candidate models: (1) Fitts' law for the speed-accuracy relationship, (2) the Almanji model for the mouse-pointing task of cerebral palsy, and (3) our proposed model. We first obtained the kinematic data of healthy (n = 12) and post-stroke (n = 7) subjects with a robot to validate the model and evaluation method and conducted a pilot study with a group of post-stroke patients (n = 12) in a clinical setting. Using the models obtained from the reaching performance of the less-affected arm, we predicted the patients' normal reaching performance to set the standard for evaluating the affected arm. RESULTS: We verified that the proposed normal reaching model identifies the reaching of all healthy (n = 12) and less-affected arm (n = 19; 16 of them showed an R2 > 0.7) but did not identify erroneous reaching of the affected arm. Furthermore, our evaluation method intuitively and visually demonstrated the unique motor characteristics of the affected arms. CONCLUSIONS: The proposed method can be used to evaluate an individual's reaching characteristics based on an individuals normal reaching model. It has the potential to provide individualized training by prioritizing a set of reaching movements.

Failing to attend versus failing to stop: Single-trial decomposition of action-stopping in the stop signal task.

The capacity to stop impending or ongoing actions contributes to executive control over behavior. Action-stopping, however, is difficult to directly quantify. It is therefore assayed via computational modeling of behavior in the stop signal task to estimate the latency of stopping (stop signal reaction time, SSRT) and, more recently, the reliability of stopping in terms of the distribution of SSRTs (standard deviation, SD-SSRT) and the frequency with which one outright fails to react to a stop signal (trigger failures, TF). Critically, the validity of computational estimates remains unknown because we currently have no direct readouts of behavior against which to compare them. Here, we developed a method for providing single-trial behavioral readouts of SSRT and trigger failures. The method relies on an adaptation of the stop signal task in which participants respond by moving a computer mouse. In two online experiments, we used movement kinematics to quantify stopping performance (SSRT, SD-SSRT, and TF), and then applied the standard Race Model and recent BEESTS model in order to examine the convergent validity of the methods. Overall, we demonstrate good correspondence between kinematics- and model-based estimates of stopping performance at the group and individual level. We conclude that the new method provides valid estimates of stopping performance that, unlike model-based estimates, can be read out at the level of single trials. Our approach might therefore be useful for interrogating single-trial neurophysiological correlates of stopping and for large-scale, online studies of behavioral stopping.

Optimal reaching trajectories based on feedforward control.

In human upper-arm reaching movements, the variance of the hand position increases until the middle of the movement and then decreases toward the endpoint. Such decrease in positional variance has been suggested as an evidence to support the hypothesis that our nervous system uses feedback control, rather than feedforward control, for arm reaching tasks. In this study, we computed the optimal trajectories based on feedforward control under several criteria for a one-link two-muscle arm model with considering the stochastic property of muscle activities in order to reexamine the hypothesis. The results showed that the feedforward control also represents the decrease in positional variance in the latter half of the movement when the control signal is planned under the minimum energy cost and minimum variance models. Furthermore, the optimal trajectory that minimizes energy cost represents not only the decrease in positional variance but also many other characteristics of the human reaching movements, e.g., the three-phasic activity of antagonistic muscle, bell-shaped speed curve, N-shaped equilibrium trajectory, and bimodal profile of joint stiffness. These results suggest that minimum energy cost model well expresses the characteristics of hand reaching movements, and our central nervous system would make use of not only a feedback control but also feedforward control.

Divisively Normalized Integration of Multisensory Error Information Develops Motor Memories Specific to Vision and Proprioception.

Both visual and proprioceptive information contribute to the accuracy of limb movement, but the mechanism of integration of these different modality signals for movement control and learning remains controversial. We aimed to elucidate the mechanism of multisensory integration for motor adaptation by evaluating single-trial adaptation (i.e., aftereffect) induced by visual and proprioceptive perturbations while male and female human participants performed reaching movements. The force-channel method was used to precisely impose several combinations of visual and proprioceptive perturbations (i.e., error), including an instance when the directions of perturbation in both stimuli opposed each another. In the subsequent probe force-channel trial, the lateral force against the channel was quantified as the aftereffect to clarify the mechanism by which the motor adaptation system corrects movement in the event of visual and proprioceptive errors. We observed that the aftereffects had complex dependence on the visual and proprioceptive errors. Although this pattern could not be explained by previously proposed computational models based on the reliability of sensory information, we found that it could be reasonably explained by a mechanism known as divisive normalization, which was the reported mechanism underlying the integration of multisensory signals in neurons. Furthermore, we discovered evidence that the motor memory for each sensory modality developed separately in accordance with a divisive normalization mechanism and that the outputs of both memories were integrated. These results provide a novel view of the utilization and integration of different sensory modality signals in motor adaptation.SIGNIFICANCE STATEMENT The mechanism of utilization of multimodal sensory information by the motor control system to perform limb movements with accuracy is a fundamental question. However, the mechanism of integration of these different sensory modalities for movement control and learning remains highly debatable. Herein, we demonstrate that multisensory integration in the motor learning system can be reasonably explained by divisive normalization, a canonical computation, ubiquitously observed in the brain (Carandini and Heeger, 2011). Moreover, we provide evidence of a novel idea that integration does not occur at the sensory information processing level, but at the motor execution level, after the motor memory for each sensory modality is separately created.

Cortical dynamics of movement-evoked pain in chronic low back pain.

KEY POINTS: Cortical activity underlying movement-evoked pain is not well understood, despite being a key symptom of chronic musculoskeletal pain. We combined high-density electroencephalography with a full-body reaching protocol in a virtual reality environment to assess cortical activity during movement-evoked pain in chronic low back pain. Movement-evoked pain in individuals with chronic low back pain was associated with longer reaction times, delayed peak velocity and greater movement variability. Movement-evoked pain was associated with attenuated disinhibition in prefrontal motor areas, as evidenced by an attenuated reduction in beta power in the premotor cortex and supplementary motor area. ABSTRACT: Although experimental pain alters neural activity in the cortex, evidence of changes in neural activity in individuals with chronic low back pain (cLBP) remains scarce and results are inconsistent. One of the challenges in studying cLBP is that the clinical pain fluctuates over time and often changes during movement. The goal of the present study was to address this challenge by recording high-density electroencephalography (HD-EEG) data during a full-body reaching task to understand neural activity during movement-evoked pain. HD-EEG data were analysed using independent component analyses, source localization and measure projection analyses to compare neural oscillations between individuals with cLBP who experienced movement-evoked pain and pain-free controls. We report two novel findings. First, movement-evoked pain in individuals with cLBP was associated with longer reaction times, delayed peak velocity and greater movement variability. Second, movement-evoked pain was associated with an attenuated reduction in beta power in the premotor cortex and supplementary motor area. Our observations move the field forward by revealing attenuated disinhibition in prefrontal motor areas during movement-evoked pain in cLBP.

Online modification of goal-directed control in human reaching movements.

Humans are able to perform very sophisticated reaching movements in a myriad of contexts based on flexible control strategies influenced by the task goal and environmental constraints such as obstacles. However, it remains unknown whether these control strategies can be adjusted online. The objective of this study was to determine whether the factors that determine control strategies during planning also modify the execution of an ongoing movement following sudden changes in task demand. More precisely, we investigated whether, and at which latency, feedback responses to perturbation loads followed the change in the structure of the goal target or environment. We changed the target width (square or rectangle) to alter the task redundancy, or the presence of obstacles to induce different constraints on the reach path, and assessed based on surface electromyography (EMG) recordings when the change in visual display altered the feedback response to mechanical perturbations. Task-related EMG responses were detected within 150 ms of a change in target shape. Considering visuomotor delays of ∼ 100 ms, these results suggest that it takes 50 ms to change control policy within a trial. An additional 30-ms delay was observed when the change in context involved sudden appearance or disappearance of obstacles. Overall, our results demonstrate that the control policy within a reaching movement is not static: contextual factors that influence movement planning also influence movement execution at surprisingly short latencies. Moreover, the additional 30 ms associated with obstacles suggests that these two types of changes may be mediated via distinct processes.NEW & NOTEWORTHY The present work demonstrates that the control strategies used to perform reaching movements are adjusted online when the structure of the target or the presence of obstacles are altered during movements. Thus, the properties of goal-directed reaching control are not simply selected during the planning stage of a movement prior to execution. Rather, they are dynamically and rapidly adjusted online, within ∼150 ms, according to changes in environment.

Online corrective responses following target jump in altered gravitoinertial force field point to nested feedforward and feedback control.

Studies on goal-directed arm movements have shown a close link between feedforward and feedback control in protocols where both planning and online control processes faced a similar type of perturbation, either mechanical or visual. This particular context might have facilitated the use of an adapted internal model by feedforward and feedback control. Here, we considered this link in a context where, after feedforward control was adapted through proprioception-based processes, feedback control was tested under visual perturbation. We analyzed the response of the reaching hand to target displacements following adaptation to an altered force field induced by rotating participants at constant velocity. Reaching corrections were assessed through variables related to the accuracy (lateral and longitudinal end point errors) and kinematics (movement time, peak velocity) of the corrective movements. The electromyographic activity of different arm muscles (pectoralis, posterior deltoid, biceps brachii, and triceps brachii) was analyzed. Statistical analyses revealed that accuracy and kinematics of corrective movements were strikingly alike between normal and altered gravitoinertial force fields. However, pectoralis and biceps muscle activities recorded during corrective movements were significantly modified to counteract the effect of rotation-induced Coriolis and centrifugal forces on the arm. Remarkably, feedback control was functional from the very first time participants encountered a target jump in the altered force field. Overall, the present results demonstrate that feedforward control enables immediate functional feedback control even when applied to distinct sensorimotor processes.NEW & NOTEWORTHY We investigated the link between feedforward and feedback control when applying a double-step perturbation (visual target jump) during reaching movements performed in modified gravitoinertial environments. Altogether, kinematics and EMG analyses showed that movement corrections were highly effective in the different force fields, suggesting that, although feedforward and feedback control were driven by different sensory inputs, feedback control was remarkably functional from the very first time participants encountered a target jump in the altered force field.

The sequelae of mastectomy and quadrantectomy with respect to the reaching movement in breast cancer survivors: evidence for an integrated rehabilitation protocol during oncological care.

BACKGROUND: Breast cancer (BC) is the most common cancer among women in developed countries. Several types of surgical interventions are commonly used in BC, such as mastectomy and quadrantectomy, followed by radiation or not. Today, BC rehabilitation can help survivors obtain and maintain the highest physical, social, psychological, and vocational functioning possible, within the limits that are created by cancer and its treatments. OBJECTIVE: To verify, before and after a specific rehabilitation protocol treatment, the recovery of the fluidity of the reaching movement. METHODS: Patients after BC surgery were enrolled and assigned by cluster randomization into 2 groups through a block randomization list: mastectomy (Mas) and quadrantectomy (Quad). Evaluation scales (DASH and VAS) were administered, and biomechanical evaluations were performed for each group before treatment (T0 = baseline), at the end of the rehabilitative treatment (T1 = 12 sessions, 2/week), and after 3 months of follow-up (T2). RESULTS: Fifty-nine (Mas group = 29; Quad group = 30) after BC surgery were enrolled. VAS scores improved along the evaluation times at T0-T1 and T0-T2 (p < 0.001), without a statistically significant difference between groups. With regard to the normalized jerk, there was no significant interaction between time group (F = 2.029; p = 0.136). There was a significant decrease between T0-T1 and T1-T2 (F = 60.189; p < 0.001). Velocity improved significantly between T0-T1 and T1-T2 (F = 10.322; p < 0.001). There was a significant interaction for the elbow angle at the end of movement between time and group at T2 (F = 5.022; p = 0.029). CONCLUSION: The integrated, low-intensity, rehabilitative intervention is effective, even if it is not performed in the first period after BC surgery, without any difference between mastectomy and quadrantectomy.

Intention Prediction and Human Health Condition Detection in Reaching Tasks with Machine Learning Techniques.

Detecting human motion and predicting human intentions by analyzing body signals are challenging but fundamental steps for the implementation of applications presenting human-robot interaction in different contexts, such as robotic rehabilitation in clinical environments, or collaborative robots in industrial fields. Machine learning techniques (MLT) can face the limit of small data amounts, typical of this kind of applications. This paper studies the illustrative case of the reaching movement in 10 healthy subjects and 21 post-stroke patients, comparing the performance of linear discriminant analysis (LDA) and random forest (RF) in: (i) predicting the subject's intention of moving towards a specific direction among a set of possible choices, (ii) detecting if the subject is moving according to a healthy or pathological pattern, and in the case of discriminating the damage location (left or right hemisphere). Data were captured with wearable electromagnetic sensors, and a sub-section of the acquired signals was required for the analyses. The possibility of detecting with which arm (left or right hand) the motion was performed, and the sensitivity of the MLT to variations in the length of the signal sub-section were also evaluated. LDA and RF prediction accuracies were compared: Accuracy improves when only healthy subjects or longer signals portions are considered up to 11% and at least 10%, respectively. RF reveals better estimation performance both as intention predictor (on average 59.91% versus the 62.19% of LDA), and health condition detector (over 90% in all the tests).

3D human arm reaching movement planning with principal patterns in successive phases.

There are observations indicating that the central nervous system (CNS) decomposes a movement into several successive sub-movements as an effective strategy to control the motor task. In this study, we propose an algorithm in which, Arm Reaching Movement (ARM) in 3D space is decomposed into several successive phases using zero joint angle jerk features of the arm kinematic data. The presented decomposition algorithm for 3D motions is, in fact, an improved and generalized version of the decomposition method proposed earlier by Emadi and Bahrami in 2012 for 2D movements. They assumed that the motion is coordinated by minimum jerk characteristics in joint angles space in each phase. However, at the first glance, it seems that in 3D ARM joint angles are not coordinated based on the minimum jerk features. Therefore, we defined a resultant variable in the joint space and showed that one can use its jerk properties together with those of the elbow joint in movement decomposition. We showed that phase borders determined with the proposed algorithm in 3D ARM, are defined with jerk characteristics of ARM's performance variable. We observed the same results in the Sit-to-Stand (STS) movement, too. Thus, based on our results, we suggested that any 3D motion can be decomposed into several phases, such that in each phase a set of principal patterns (PPs) extracted by Principal Component Analysis (PCA) method are linearly recruited to regenerate angle trajectories of each joint. Our results also suggest that the CNS, as the primary policy, may simplify the control of the ARMs by reducing the dimension of the control space. This dimension reduction might be accomplished by decomposing the movement into successive phases in which the movement satisfies the minimum joint angle jerk constraint. Then, in each phase, a set of PPs are recruited in the joint space to regenerate angle trajectory of each joint. Then, the dimension of the control space will be the number of the recruitment coefficients.

Modulation of Beta Bursts in the Subthalamic Nucleus Predicts Motor Performance.

Considerable evidence suggests a role of beta-band oscillations in voluntary movements. However, most of the studies linking beta power to motor performance are based on data averaged across trials that ignore the fast dynamics of oscillatory activity and trial-to-trial variations in motor responses. Recently, emphasis has shifted from the functional implications of the mean beta power to the presence and nature of episodic bursts of beta activity. Here we test the hypothesis that beta bursts, though short in duration in more physiological state, may help explain spontaneous variations in motor behavior of human adults at the single-trial level. To this end, we recorded local field potential activity from the subthalamic nucleus of parkinsonian patients of both genders whose motor behavior had been normalized as far as possible through treatment with the dopamine prodrug, levodopa. We found that beta bursts present in a time-limited window well before movement onset in the contralateral subthalamic nucleus reduce the peak velocity of that movement and that this effect is further amplified by the amplitude of the burst. Additionally, prolonged reaction times are observed when bursts occur immediately after the GO cue. Together, these results suggest that the modulation of the timing and amplitude of beta bursts might serve to dynamically adapt motor performance. These results offer new insight in the pathology of Parkinson's disease, and suggest that beta bursts whose presence and nature are modulated by context may have a physiological role in modulating behavior.SIGNIFICANCE STATEMENT Beta oscillations (∼13-30 Hz) have been increasingly interpreted as transient bursts rather than as rhythmically sustained oscillations (Feingold et al., 2015). Prolonged and increased probability of beta bursts in the subthalamic nucleus correlates with the severity of motor impairment in Parkinson's disease (Tinkhauser et al., 2017a, b). However, it remains unclear whether beta bursts act to modify motor performance on a trial-by-trial basis under more physiological condition. Here, we found that, according to the time window in which they fall, beta bursts reduced the velocity of the forthcoming movement or prolonged the reaction time. These results offer new insight in the pathology of Parkinson's disease and also suggest that the modulation of beta bursts might serve to dynamically adapt motor performance.

Adaptation and spatial generalization to a triaxial visuomotor perturbation in a virtual reality environment.

We explored visuomotor adaptation and spatial generalization of three-dimensional reaching movements performed in a virtual reality environment. We used a multiphase learning paradigm. First, subjects performed reaching movements to six targets without visual feedback (VF) (pre-exposure phase). Next, participants aimed at one target with veridical VF (baseline phase). Immediately after, they were required to adapt their movements to a triaxial visuomotor perturbation (horizontal, vertical, and sagittal translations) between actual hand motion and VF of hand motion in the virtual environment (learning phase). Finally, subjects aimed at the same targets as in the baseline (aftereffect) and pre-exposure phases (generalization) without VF (post-exposure phase). The results revealed spatial axis-dependent visuomotor adaptation capacities. First, subjects showed smaller intertrial variability along the horizontal compared to the sagittal and vertical axes during the baseline and learning phases. Second, although subjects were unaware of the visual distortion, they adapted their movements to each component of the triaxial perturbation. However, they showed reduced learning rate and less persistent adaptation (aftereffect) along the vertical than the horizontal and sagittal axes. Similarly, subjects transferred the newly learned visuomotor association to untrained regions of the workspace, but their average level of generalization was smaller along the vertical than the horizontal and sagittal axes. Collectively, our results suggest that adapting three-dimensional movements to a visual distortion involves distinct processes according to the specific sensorimotor integration demands of moving along each spatial axis. This finding supports the idea that the brain employs a modular decomposition strategy to simplify complex multidimensional visuomotor tasks.

Effector-Invariant Movement Encoding in the Human Motor System.

Ipsilateral motor areas of cerebral cortex are active during arm movements and even reliably predict movement direction. Is coding similar during ipsilateral and contralateral movements? If so, is it in extrinsic (world-centered) or intrinsic (joint-configuration) coordinates? We addressed these questions by examining the similarity of multivoxel fMRI patterns in visuomotor cortical regions during unilateral reaching movements with both arms. The results of three complementary analyses revealed that fMRI response patterns were similar across right and left arm movements to identical targets (extrinsic coordinates) in visual cortices, and across movements with equivalent joint-angles (intrinsic coordinates) in motor cortices. We interpret this as evidence for the existence of distributed neural populations in multiple motor system areas that encode ipsilateral and contralateral movements in a similar manner: according to their intrinsic/joint coordinates.SIGNIFICANCE STATEMENT Cortical motor control exhibits clear lateralization: each hemisphere controls the motor output of the contralateral body. Nevertheless, neural populations in ipsilateral areas across the visuomotor hierarchy are active during unilateral movements. We show that fMRI response patterns in the motor cortices are similar for both arms if the movement direction is mirror-reversed across the midline. This suggests that in both ipsilateral and contralateral motor cortices, neural populations have effector-invariant coding of movements in intrinsic coordinates. This not only affects our understanding of motor control, it may serve in the development of brain machine interfaces that also use ipsilateral neural activity.

Done in 100 ms: path-dependent visuomotor transformation in the human upper limb.

A core assumption underlying mental chronometry is that more complex tasks increase cortical processing, prolonging reaction times. In this study we show that increases in task complexity alter the magnitude, rather than the latency, of the output for a circuit that rapidly transforms visual information into motor actions. We quantified visual stimulus-locked responses (SLRs), which are changes in upper limb muscle recruitment that evolve at a fixed latency ~100 ms after novel visual stimulus onset. First, we studied the underlying reference frame of the SLR by dissociating the initial eye and hand position. Despite its quick latency, we found that the SLR was expressed in a hand-centric reference frame, suggesting that the circuit mediating the SLR integrated retinotopic visual information with body configuration. Next, we studied the influence of planned movement trajectory, requiring participants to prepare and generate either curved or straight reaches in the presence of obstacles to attain the same visual stimulus location. We found that SLR magnitude was influenced by the planned movement trajectory to the same visual stimulus. On the basis of these results, we suggest that the circuit mediating the SLR lies in parallel to other well-studied corticospinal pathways. Although the fixed latency of the SLR precludes extensive cortical processing, inputs conveying information relating to task complexity, such as body configuration and planned movement trajectory, can preset nodes within the circuit underlying the SLR to modulate its magnitude. NEW & NOTEWORTHY We studied stimulus-locked responses (SLRs), which are changes in human upper limb muscle recruitment that evolve at a fixed latency ~100 ms after novel visual stimulus onset. We showed that despite its quick latency, the circuitry mediating the SLR transformed a retinotopic visual signal into a hand-centric motor command that is modulated by the planned movement trajectory. We suggest that the circuit generating the SLR is mediated through a tectoreticulospinal, rather than a corticospinal, pathway.

Light localization with low-contrast targets in a patient implanted with a suprachoroidal-transretinal stimulation retinal prosthesis.

PURPOSE: To evaluate the improvement in targeted reaching movements toward targets of various contrasts in a patient implanted with a suprachoroidal-transretinal stimulation (STS) retinal prosthesis. METHODS: An STS retinal prosthesis was implanted in the right eye of a 42-year-old man with advanced Stargardt disease (visual acuity: right eye, light perception; left eye, hand motion). In localization tests during the 1-year follow-up period, the patient attempted to touch the center of a white square target (visual angle, 10°; contrast, 96, 85, or 74%) displayed at a random position on a monitor. The distance between the touched point and the center of the target (the absolute deviation) was averaged over 20 trials with the STS system on or off. RESULTS: With the left eye occluded, the absolute deviation was not consistently lower with the system on than off for high-contrast (96%) targets, but was consistently lower with the system on for low-contrast (74%) targets. With both eyes open, the absolute deviation was consistently lower with the system on than off for 85%-contrast targets. With the system on and 96%-contrast targets, we detected a shorter response time while covering the right eye, which was being implanted with the STS, compared to covering the left eye (2.41 ± 2.52 vs 8.45 ± 3.78 s, p < 0.01). CONCLUSIONS: Performance of a reaching movement improved in a patient with an STS retinal prosthesis implanted in an eye with residual natural vision. Patients with a retinal prosthesis may be able to improve their visual performance by using both artificial vision and their residual natural vision. CLINICAL TRIAL REGISTRATION: Beginning date of the trial: Feb. 20, 2014 Date of registration: Jan. 4, 2014 Trial registration number: UMIN000012754 Registration site: UMIN Clinical Trials Registry (UMIN-CTR) http://www.umin.ac.jp/ctr/index.htm.

Rapid visuomotor feedback gains are tuned to the task dynamics.

Adaptation to novel dynamics requires learning a motor memory, or a new pattern of predictive feedforward motor commands. Recently, we demonstrated the upregulation of rapid visuomotor feedback gains early in curl force field learning, which decrease once a predictive motor memory is learned. However, even after learning is complete, these feedback gains are higher than those observed in the null field trials. Interestingly, these upregulated feedback gains in the curl field were not observed in a constant force field. Therefore, we suggest that adaptation also involves selectively tuning the feedback sensitivity of the sensorimotor control system to the environment. Here, we test this hypothesis by measuring the rapid visuomotor feedback gains after subjects adapt to a variety of novel dynamics generated by a robotic manipulandum in three experiments. To probe the feedback gains, we measured the magnitude of the motor response to rapid shifts in the visual location of the hand during reaching. While the feedback gain magnitude remained similar over a larger than a fourfold increase in constant background load, the feedback gains scaled with increasing lateral resistance and increasing instability. The third experiment demonstrated that the feedback gains could also be independently tuned to perturbations to the left and right, depending on the lateral resistance, demonstrating the fractionation of feedback gains to environmental dynamics. Our results show that the sensorimotor control system regulates the gain of the feedback system as part of the adaptation process to novel dynamics, appropriately tuning them to the environment.NEW & NOTEWORTHY Here, we test whether rapid visuomotor feedback responses are selectively tuned to the task dynamics. The responses do not exhibit gain scaling, but they do vary with the level and stability of task dynamics. Moreover, these feedback gains are independently tuned to perturbations to the left and right, depending on these dynamics. Our results demonstrate that the sensorimotor control system regulates the feedback gain as part of the adaptation process, tuning them appropriately to the environment.

Variance in exposed perturbations impairs retention of visuomotor adaptation.

Sensorimotor control requires an accurate estimate of the state of the body. The brain optimizes state estimation by combining sensory signals with predictions of the sensory consequences of motor commands using a forward model. Given that both sensory signals and predictions are uncertain (i.e., noisy), the brain optimally weights the relative reliance on each source of information during adaptation. In support, it is known that uncertainty in the sensory predictions influences the rate and generalization of visuomotor adaptation. We investigated whether uncertainty in the sensory predictions affects the retention of a new visuomotor relationship. This was done by exposing three separate groups to a visuomotor rotation whose mean was common at 15° counterclockwise but whose variance around the mean differed (i.e., SD of 0°, 3.2°, or 4.5°). Retention was assessed by measuring the persistence of the adapted behavior in a no-vision phase. Results revealed that mean reach direction late in adaptation was similar across groups, suggesting it depended mainly on the mean of exposed rotations and was robust to differences in variance. However, retention differed across groups, with higher levels of variance being associated with a more rapid reversion toward nonadapted behavior. A control experiment ruled out the possibility that differences in retention were accounted for by differences in success rates. Exposure to variable rotations may have increased the uncertainty in sensory predictions, making the adapted forward model more labile and susceptible to change or decay.NEW & NOTEWORTHY The brain predicts the sensory consequences of motor commands through a forward model. These predictions are subject to uncertainty. We use visuomotor adaptation and modulate uncertainty in the sensory predictions by manipulating the variance in exposed rotations. Results reveal that variance does not influence the final extent of adaptation but selectively impairs the retention of motor memories. These results suggest that a more uncertain forward model is more susceptible to change or decay.

Visuomotor signals for reaching movements in the rostro-dorsal sector of the monkey thalamic reticular nucleus.

The thalamic reticular nucleus (TRN) collects inputs from the cerebral cortex and thalamus and, in turn, sends inhibitory outputs to the thalamic relay nuclei. This unique connectivity suggests that the TRN plays a pivotal role in regulating information flow through the thalamus. Here, we analyzed the roles of TRN neurons in visually guided reaching movements. We first used retrograde transneuronal labeling with rabies virus, and showed that the rostro-dorsal sector of the TRN (TRNrd) projected disynaptically to the ventral premotor cortex (PMv). In other experiments, we recorded neurons from the TRNrd or PMv while monkeys performed a visuomotor task. We found that neurons in the TRNrd and PMv showed visual-, set-, and movement-related activity modulation. These results indicate that the TRNrd, as well as the PMv, is involved in the reception of visual signals and in the preparation and execution of reaching movements. The fraction of neurons that were non-selective for the location of visual signals or the direction of reaching movements was greater in the TRNrd than in the PMv. Furthermore, the fraction of neurons whose activity increased from the baseline was greater in the TRNrd than in the PMv. The timing of activity modulation of visual-related and movement-related neurons was similar in TRNrd and PMv neurons. Overall, our data suggest that TRNrd neurons provide motor thalamic nuclei with inhibitory inputs that are predominantly devoid of spatial selectivity, and that these signals modulate how these nuclei engage in both sensory processing and motor output during visually guided reaching behavior.