Design and Validation of a MR-compatible Pneumatic Manipulandum

The combination of functional MR imaging and novel robotic tools may provide unique opportunities to probe the neural systems underlying motor control and learning. Here, we describe the design and validation of a MR-compatible, 1 degree-of-freedom pneumatic manipulandum along with experiments demonstrating its safety and efficacy. We first validated the robot\u27s ability to apply computer-controlled loads about the wrist, demonstrating that it possesses sufficient bandwidth to simulate torsional spring-like loads during point-to-point flexion movements. Next, we verified the MR-compatibility of the device by imaging a head phantom during robot operation. We observed no systematic differences in two measures of MRI signal quality (signal/noise and field homogeneity) when the robot was introduced into the scanner environment. Likewise, measurements of joint angle and actuator pressure were not adversely affected by scanning. Finally, we verified device efficacy by scanning 20 healthy human subjects performing rapid wrist flexions against a wide range of spring-like loads. We observed a linear relationship between joint torque at peak movement extent and perturbation magnitude, thus demonstrating the robot\u27s ability to simulate spring-like loads in situ. fMRI revealed task-related activation in regions known to contribute to the control of movement including the left primary sensorimotor cortex and right cerebellum

Remembering Forward: Neural Correlates of Memory and Prediction in Human Motor Adaptation

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions – including prefrontal, parietal and hippocampal cortices – exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or “states” important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancelation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures

Capability of 2 Gait Measures for Detecting Response to Gait Training in Stroke Survivors: Gait Assessment and Intervention Tool and The Tinetti Gait Scale

Zimbelman J, Daly JJ, Roenigk KL, Butler K, Burdsall R, Holcomb JP. Capability of 2 gait measures for detecting response to gait training in stroke survivors: Gait Assessment and Intervention Tool and the Tinetti Gait Scale. Objective:To characterize the performance of 2 observational gait measures, the Tinetti Gait Scale (TGS) and the Gait Assessment and Intervention Tool (G.A.I.T.), in identifying improvement in gait in response to gait training. Design: In secondary analysis from a larger study of multimodal gait training for stroke survivors, we measured gait at pre-, mid-, and posttreatment according to G.A.I.T. and TGS, assessing their capability to capture recovery of coordinated gait components. Setting: Large medical center. Participants: Cohort of stroke survivors (N=44) greater than 6 months after stroke. Interventions: All subjects received 48 sessions of a multimodal gait-training protocol. Treatment consisted of 1.5 hours per session, 4 sessions per week for 12 weeks, receiving these 3 treatment aspects: (1) coordination exercise, (2) body weight–supported treadmill training, and (3) overground gait training, with 46% of subjects receiving functional electrical stimulation. Main Outcome Measures: All subjects were evaluated with the G.A.I.T. and TGS before and after completing the 48-session intervention. An additional evaluation was performed at midtreatment (after session 24). Results: For the total subject sample, there were significant pre-/post-, pre-/mid-, and mid-/posttreatment gains for both the G.A.I.T. and the TGS. According to the G.A.I.T., 40 subjects (91%) showed improved scores, 2 (4%) no change, and 2 (4%) a worsening score. According to the TGS, only 26 subjects (59%) showed improved scores, 16 (36%) no change, and 1 (2%) a worsening score. For 1 treatment group of chronic stroke survivors, the TGS failed to identify a significant treatment response to gait training, whereas the G.A.I.T. measure was successful. Conclusions: The G.A.I.T. is more sensitive than the TGS for individual patients and group treatment response in identifying recovery of volitional control of gait components in response to gait training

Neural modulation of temporal encoding, maintenance, and decision processes.

Time perception emerges from an interaction among multiple processes that are normally intertwined. Therefore, a challenge has been to disentangle timekeeping from other processes. Though the striatum has been implicated in interval timing, it also modulates nontemporal processes such as working memory. To distinguish these processes, we separated neural activation associated with encoding, working-memory maintenance, and decision phases of a time-perception task. We also asked whether neuronal processing of duration (i.e., pure tone) was distinct from the processing of identity (i.e., pitch perception) or sensorimotor features (i.e., control task). Striatal activation was greater when encoding the duration than the pitch or basic sensory features, which did not differentially engage the striatum. During the maintenance phase, striatal activation was similar for duration and pitch but at baseline in the control task. In the decision phase, a stepwise reduction in striatal activation was found across the 3 tasks, with activation greatest in the timing task and weakest in the control task. Task-related striatal activations in different cognitive phases were distinguished from those of the supplementary motor area, inferior frontal gyrus, thalamus, frontoparietal cortices, and the cerebellum. Our results were consistent with a model in which timing emerges from context-dependent corticostriatal interactions

Neural Modulation of Temporal Encoding, Maintenance, and Decision Processes

Time perception emerges from an interaction among multiple processes that are normally intertwined. Therefore, a challenge has been to disentangle timekeeping from other processes. Though the striatum has been implicated in interval timing, it also modulates nontemporal processes such as working memory. To distinguish these processes, we separated neural activation associated with encoding, working-memory maintenance, and decision phases of a time-perception task. We also asked whether neuronal processing of duration (i.e., pure tone) was distinct from the processing of identity (i.e., pitch perception) or sensorimotor features (i.e., control task). Striatal activation was greater when encoding the duration than the pitch or basic sensory features, which did not differentially engage the striatum. During the maintenance phase, striatal activation was similar for duration and pitch but at baseline in the control task. In the decision phase, a stepwise reduction in striatal activation was found across the 3 tasks, with activation greatest in the timing task and weakest in the control task. Task-related striatal activations in different cognitive phases were distinguished from those of the supplementary motor area, inferior frontal gyrus, thalamus, frontoparietal cortices, and the cerebellum. Our results were consistent with a model in which timing emerges from context-dependent corticostriatal interactions

Capability of 2 Gait Measures for Detecting Response to Gait Training in Stroke Survivors: Gait Assessment and Intervention Tool and The Tinetti Gait Scale

Zimbelman J, Daly JJ, Roenigk KL, Butler K, Burdsall R, Holcomb JP. Capability of 2 gait measures for detecting response to gait training in stroke survivors: Gait Assessment and Intervention Tool and the Tinetti Gait Scale. Objective:To characterize the performance of 2 observational gait measures, the Tinetti Gait Scale (TGS) and the Gait Assessment and Intervention Tool (G.A.I.T.), in identifying improvement in gait in response to gait training. Design: In secondary analysis from a larger study of multimodal gait training for stroke survivors, we measured gait at pre-, mid-, and posttreatment according to G.A.I.T. and TGS, assessing their capability to capture recovery of coordinated gait components. Setting: Large medical center. Participants: Cohort of stroke survivors (N=44) greater than 6 months after stroke. Interventions: All subjects received 48 sessions of a multimodal gait-training protocol. Treatment consisted of 1.5 hours per session, 4 sessions per week for 12 weeks, receiving these 3 treatment aspects: (1) coordination exercise, (2) body weight–supported treadmill training, and (3) overground gait training, with 46% of subjects receiving functional electrical stimulation. Main Outcome Measures: All subjects were evaluated with the G.A.I.T. and TGS before and after completing the 48-session intervention. An additional evaluation was performed at midtreatment (after session 24). Results: For the total subject sample, there were significant pre-/post-, pre-/mid-, and mid-/posttreatment gains for both the G.A.I.T. and the TGS. According to the G.A.I.T., 40 subjects (91%) showed improved scores, 2 (4%) no change, and 2 (4%) a worsening score. According to the TGS, only 26 subjects (59%) showed improved scores, 16 (36%) no change, and 1 (2%) a worsening score. For 1 treatment group of chronic stroke survivors, the TGS failed to identify a significant treatment response to gait training, whereas the G.A.I.T. measure was successful. Conclusions: The G.A.I.T. is more sensitive than the TGS for individual patients and group treatment response in identifying recovery of volitional control of gait components in response to gait training

Recovery of Coordinated Gait: Randomized Controlled Stroke Trial of Functional Electrical Stimulation (FES) Versus No FES, With Weight-Supported Treadmill and Over-Ground Training

Background. No single intervention restores the coordinated components of gait after stroke. Objective. The authors tested the multimodal Gait Training Protocol, with or without functional electrical stimulation (FES), to improve volitional walking (without FES) in patients with persistent (\u3e6 months) dyscoordinated gait. Methods. A total of 53 subjects were stratified and randomly allocated to either FES with intramuscular (IM) electrodes (FES-IM) or No-FES. Both groups received 1.5-hour training sessions 4 times a week for 12 weeks of coordination exercises, body weight–supported treadmill training (BWSTT), and over-ground walking, provided with FES-IM or No-FES. The primary outcome was the Gait Assessment and Intervention Tool (G.A.I.T.) of coordinated movement components, with secondary measures, including manual muscle testing, isolated leg movements (Fugl-Meyer scale), 6-Minute Walk Test, and Locomotion/Mobility subscale of the Functional Independence Measure (FIM). Results. No baseline differences in subject characteristics and measures were found. The G.A.I.T. showed an additive advantage with FES-IM versus No-FES (parameter statistic 1.10; P = .045, 95% CI = 0.023-2.179) at the end of training. For both FES-IM and No-FES, a within-group, pre/posttreatment gain was present for all measures (P \u3c .05), and a continued benefit from mid- to posttreatment (P \u3c .05) was present. For FES-IM, recovered coordinated gait persisted at 6-month follow-up but not for No-FES. Conclusion. Improved gait coordination and function were produced by the multimodal Gait Training Protocol. FES-IM added significant gains that were maintained for 6 months after the completion of training

Recovery of Coordinated Gait: Randomized Controlled Stroke Trial of Functional Electrical Stimulation (FES) Versus No FES, With Weight-Supported Treadmill and Over-Ground Training

Background. No single intervention restores the coordinated components of gait after stroke. Objective. The authors tested the multimodal Gait Training Protocol, with or without functional electrical stimulation (FES), to improve volitional walking (without FES) in patients with persistent (\u3e6 months) dyscoordinated gait. Methods. A total of 53 subjects were stratified and randomly allocated to either FES with intramuscular (IM) electrodes (FES-IM) or No-FES. Both groups received 1.5-hour training sessions 4 times a week for 12 weeks of coordination exercises, body weight–supported treadmill training (BWSTT), and over-ground walking, provided with FES-IM or No-FES. The primary outcome was the Gait Assessment and Intervention Tool (G.A.I.T.) of coordinated movement components, with secondary measures, including manual muscle testing, isolated leg movements (Fugl-Meyer scale), 6-Minute Walk Test, and Locomotion/Mobility subscale of the Functional Independence Measure (FIM). Results. No baseline differences in subject characteristics and measures were found. The G.A.I.T. showed an additive advantage with FES-IM versus No-FES (parameter statistic 1.10; P = .045, 95% CI = 0.023-2.179) at the end of training. For both FES-IM and No-FES, a within-group, pre/posttreatment gain was present for all measures (P \u3c .05), and a continued benefit from mid- to posttreatment (P \u3c .05) was present. For FES-IM, recovered coordinated gait persisted at 6-month follow-up but not for No-FES. Conclusion. Improved gait coordination and function were produced by the multimodal Gait Training Protocol. FES-IM added significant gains that were maintained for 6 months after the completion of training