Pietro Mazzoni

The corticospinal (CST) and corticoreticulospinal (CReST) tracts are two major descending motor pathways. We examined their relationships to motor behaviors in paretic arm and hand muscles in chronic stroke. Stronger ipsilesional CST projections related to better motor control, whereas stronger contralesional CReST projections related to better muscle strength. Stronger CST projections are also uniquely related to better biceps individuation. These findings support the notion of specialized but complementary contributions of these pathways to human motor function.

In this study, we examined different components of bradykinesia in patients with Parkinson’s disease (PD). We identified different components through signal processing techniques and their response to deep brain stimulation (DBS). We found that some components of bradykinesia respond to stimulation, whereas others do not. This knowledge advances our understanding of brain mechanisms that control movement speed and amplitude.

Freezing of gait (FOG) is a debilitating symptom of Parkinson’s disease (PD) that remains difficult to assess. Wearable movement sensors and associated algorithms can be used to quantify FOG in laboratory settings, but the utility of such methods for real world use is unclear. We aimed to determine the suitability of our wearable sensor-based FOG assessment method for real world use by assessing its performance during in-clinic simulated real world activities. Accuracy of the sensor-based method during simulated real-world tasks was calculated using expert rated video as the gold standard. To determine feasibility for unsupervised home use, we also determined correlations between the percent of active time spent freezing (%ATSF) during unsupervised home use and in-clinic activities. Nineteen people with PD and FOG participated in this study. Results from our sensor-based method demonstrated an accuracy above 90% compared to gold-standard expert review during simulated real-world tasks. Additionally, %ATSF from our sensor-based method during unsupervised home use correlated strongly with %ATSF from our sensor-based method during in-clinic simulated real-world activities (ρ = 0.73). Accuracy values and correlation patterns suggest our method may be useful for FOG assessment in the real world.

Aim: To determine the effectiveness of a targeted dance intervention to improve walking speed for people with Parkinson disease (PD) by increasing motor motivation. Materials & methods: 11 particip...

Background: Postural stepping is an important strategy for recovery of balance in response to postural perturbations. It is disrupted by Parkinson’s disease (PD) and other conditions. The nature of this disruption remains poorly understood. Understanding the motor control nature of this impairment can guide the development of novel interventions. Objectives: To identify the motor control abnormalities responsible for parkinsonian impairment of postural stepping. Methods: We studied four groups of participants: control, aged, PD, and normal-pressure hydrocephalus (NPH). We performed kinematic analysis of postural stepping by recording participants’ body motion during a modified version of the clinical pull test, which was performed multiple times with different amounts of pulling forcefulness. Results: Successful postural stepping in the control group was accompanied by linear scaling of their first step’s length and latency to the body’s initial motion: more forceful pulls caused larger initial body acceleration, which resulted in longer steps that began earlier. PD patients exhibited reduced scaling of step length: they maintained normal reaction time but took steps that were inadequately short. Reduced step length scaling was present, but less severe, in aged individuals, and was more severe in NPH patients. Aged individuals and PD patients exhibited partial compensation for reduced step length scaling: their step length included a component that was independent of initial body acceleration, which was absent in control and NPH groups. Conclusions: the impairment of postural stepping caused by PD and related conditions is due to inadequate scaling of movement amplitude and is thus a form of hypokinesia.

It has been debated whether kinematic features, such as the number of peaks or decomposed submovements in a velocity profile, indicate the number of discrete motor impulses or result from a continuous control process. The debate is particularly relevant for tasks involving target perturbation, which can alter movement kinematics. To simulate such tasks, finite-horizon models require two preset movement durations to compute two control policies before and after the perturbation. Another model employs infinite- and finite-horizon formulations to determine, respectively, movement durations and control policies, which are updated every time step. We adopted an infinite-horizon optimal feedback control model that, unlike previous approaches, does not preset movement durations or use multiple control policies. It contains both control-dependent and independent noises in system dynamics, state-dependent and independent noises in sensory feedbacks, and different delays and noise levels for visual and proprioceptive feedbacks. We analytically derived an optimal solution that can be applied continuously to move an effector toward a target regardless of whether, when, or where the target jumps. This single policy produces different numbers of peaks and “submovements” in velocity profiles for different conditions and trials. Movements that are slower or perturbed later appear to have more submovements. The model is also consistent with the observation that subjects can perform the perturbation task even without detecting the target jump or seeing their hands during reaching. Finally, because the model incorporates Weber's law via a state representation relative to the target, it explains why initial and terminal visual feedback are, respectively, less and more effective in improving end-point accuracy. Our work suggests that the number of peaks or submovements in a velocity profile does not necessarily reflect the number of motor impulses and that the difference between initial and terminal feedback does not necessarily imply a transition between open- and closed-loop strategies.

It has been difficult to link synaptic modification to overt behavioral changes. Rodent models of DYT1 dystonia, a motor disorder caused by a single gene mutation, demonstrate increased long-term potentiation and decreased long-term depression in corticostriatal synapses. Computationally, such asymmetric learning predicts risk taking in probabilistic tasks. Here we demonstrate abnormal risk taking in DYT1 dystonia patients, which is correlated with disease severity, thereby supporting striatal plasticity in shaping choice behavior in humans.

There is a great need to develop new approaches for rehabilitation of the upper limb after stroke. Robotic therapy is a promising form of neurorehabilitation that can be delivered in higher doses than conventional therapy. Here we sought to determine whether the reported effects of robotic therapy, which have been based on clinical measures of impairment and function, are accompanied by improved motor control. Patients with chronic hemiparesis were trained for 3 wk, 3 days a week, with titrated assistive robotic therapy in two and three dimensions. Motor control improvements (i.e., skill) in both arms were assessed with a separate untrained visually guided reaching task. We devised a novel PCA-based analysis of arm trajectories that is sensitive to changes in the quality of entire movement trajectories without needing to prespecify particular kinematic features. Robotic therapy led to skill improvements in the contralesional arm. These changes were not accompanied by changes in clinical measures of impairment or function. There are two possible interpretations of these results. One is that robotic therapy only leads to small task-specific improvements in motor control via normal skill-learning mechanisms. The other is that kinematic assays are more sensitive than clinical measures to a small general improvement in motor control.

When movements are perturbed in adaptation tasks, humans and other animals show incomplete compensation, tolerating small but sustained residual errors that persist despite repeated trials. State-space models explain this residual asymptotic error as interplay between learning from error and reversion to baseline, a form of forgetting. Previous work using zero-error-clamp trials has shown that reversion to baseline is not obligatory and can be overcome by manipulating feedback. We posited that novel error-clamp trials, in which feedback is constrained but has nonzero error and variance, might serve as a contextual cue for recruitment of other learning mechanisms that would then close the residual error. When error clamps were nonzero and had zero variance, human subjects changed their learning policy, using exploration in response to the residual error, despite their willingness to sustain such an error during the training block. In contrast, when the distribution of feedback in clamp trials was naturalistic, with persistent mean error but also with variance, a state-space model accounted for behavior in clamps, even in the absence of task success. Therefore, when the distribution of errors matched those during training, state-space models captured behavior during both adaptation and error-clamp trials because error-based learning dominated; when the distribution of feedback was altered, other forms of learning were triggered that did not follow the state-space model dynamics exhibited during training. The residual error during adaptation appears attributable to an error-dependent learning process that has the property of reversion toward baseline and that can suppress other forms of learning.

We recently defined a component of motor skill learning as “motor acuity,” quantified as a shift in the speed-accuracy trade-off function for a task. These shifts are primarily driven by reductions in movement variability. To determine the neural correlates of improvement in motor acuity, we devised a motor task compatible with magnetic resonance brain imaging that required subjects to make finely controlled wrist movements under visual guidance. Subjects were imaged on day 1 and day 5 while they performed this task and were trained outside the scanner on intervening days 2, 3, and 4. The potential confound of performance changes between days 1 and 5 was avoided by constraining movement time to a fixed duration. After training, subjects showed a marked increase in success rate and a reduction in trial-by-trial variability for the trained task but not for an untrained control task, without changes in mean trajectory. The decrease in variability for the trained task was associated with increased activation in contralateral primary motor and premotor cortical areas and in ipsilateral cerebellum. A global nonlocalizing multivariate analysis confirmed that learning was associated with increased overall brain activation. We suggest that motor acuity is acquired through increases in the number of neurons recruited in contralateral motor cortical areas and in ipsilateral cerebellum, which could reflect increased signal-to-noise ratio in motor output and improved state estimation for feedback corrections, respectively.