Instrumental learning is a fundamental process through which agents optimize their choices, taking into account various dimensions of available options such as the possible reward or punishment outcomes and the costs associated with potential actions. Although the implication of dopamine in learning from choice outcomes is well established, less is known about its role in learning the action costs such as effort. Here, we tested the ability of patients with Parkinson9s disease (PD) to maximize monetary rewards and minimize physical efforts in a probabilistic instrumental learning task. The implication of dopamine was assessed by comparing performance ON and OFF prodopaminergic medication. In a first sample of PD patients (n = 15), we observed that reward learning, but not effort learning, was selectively impaired in the absence of treatment, with a significant interaction between learning condition (reward vs effort) and medication status (OFF vs ON). These results were replicated in a second, independent sample of PD patients (n = 20) using a simplified version of the task. According to Bayesian model selection, the best account for medication effects in both studies was a specific amplification of reward magnitude in a Q-learning algorithm. These results suggest that learning to avoid physical effort is independent from dopaminergic circuits and strengthen the general idea that dopaminergic signaling amplifies the effects of reward expectation or obtainment on instrumental behavior. SIGNIFICANCE STATEMENT Theoretically, maximizing reward and minimizing effort could involve the same computations and therefore rely on the same brain circuits. Here, we tested whether dopamine, a key component of reward-related circuitry, is also implicated in effort learning. We found that patients suffering from dopamine depletion due to Parkinson9s disease were selectively impaired in reward learning, but not effort learning. Moreover, anti-parkinsonian medication restored the ability to maximize reward, but had no effect on effort minimization. This dissociation suggests that the brain has evolved separate, domain-specific systems for instrumental learning. These results help to disambiguate the motivational role of prodopaminergic medications: they amplify the impact of reward without affecting the integration of effort cost.

Local injections of botulinum toxin type A have been used to treat essential head tremor but have not been extensively studied in randomized trials. In a multicenter, double-blind, randomized trial, we assigned, in a 1:1 ratio, adult patients with essential or isolated head tremor to receive botulinum toxin type A or placebo. Botulinum toxin or placebo was injected under electromyographic guidance into each splenius capitis muscle on the day of randomization (day 0) and during week 12. The primary outcome was improvement by at least 2 points on the Clinical Global Impression of Change (CGI) scale at week 6 after the second injection (week 18 after randomization). The CGI scale was used to record the patient's assessment of the degree of improvement or worsening of head tremor since baseline; scores range from 3 (very much improved) to -3 (very much worse). Secondary outcomes included changes in tremor characteristics from baseline to weeks 6, 12, and 24. A total of 120 patients were enrolled; 3 patients were excluded during screening, and 117 patients were randomly assigned to receive botulinum toxin (62 patients) or placebo (55 patients) and were included in the intention-to-treat analysis. Twelve patients in the botulinum toxin group and 2 patients in the placebo group did not receive injections during week 12. The primary outcome - improvement by at least 2 points on the CGI scale at week 18 - was met by 31% of the patients in the botulinum toxin group as compared with 9% of those in the placebo group (relative risk, 3.37; 95% confidence interval, 1.35 to 8.42; P = 0.009). Analyses of secondary outcomes at 6 and 12 weeks but not at 24 weeks were generally supportive of the primary-outcome analysis. Adverse events occurred in approximately half the patients in the botulinum toxin group and included head and neck pain, posterior cervical weakness, and dysphagia. Injection of botulinum toxin into each splenius capitis muscle on day 0 and during week 12 was more effective than placebo in reducing the severity of isolated or essential head tremor at 18 weeks but not at 24 weeks, when the effects of injection might be expected to wane, and was associated with adverse events. (Funded by the French Ministry of Health; Btx-HT ClinicalTrials.gov number, NCT02555982.).

Background: The locus coeruleus/subcoeruleus complex (LC/LsC) is a structure comprising melanized noradrenergic neurons.Objective: To study the LC/LsC damage across Parkinson's disease (PD) and atypical parkinsonism in a large group of subjects.Methods: We studied 98 healthy control subjects, 47 patients with isolated rapid eye movement sleep behavior disorder (RBD), 75 patients with PD plus RBD, 142 patients with PD without RBD, 19 patients with progressive supranuclear palsy (PSP), and 19 patients with multiple system atrophy (MSA). Twelve patients with MSA had proven RBD. LC/LsC signal intensity was derived from neuromelanin magnetic resonance imaging using automated software.Results: The signal intensity was reduced in all parkinsonian syndromes compared with healthy control subjects, except in PD without RBD. The signal intensity decreased as age increased. Moreover, the signal intensity was lower in MSA than in isolated RBD and PD without RBD groups. In PD, the signal intensity correlated negatively with the percentage of REM sleep without atonia. There were no differences in signal intensity between PD plus RBD, PSP, and MSA.Conclusions: Neuromelanin signal intensity was reduced in all parkinsonian disorders, except in PD without RBD. The presence of RBD in parkinsonian disorders appears to be associated with lower neuromelanin signal intensity. Furthermore, lower LC/LsC signal changes in PSP could be partly caused by the effect of age. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Background: Among motor symptoms of Parkinson’s disease (PD), including rigidity and resting tremor, bradykinesia is a mandatory feature to define the parkinsonian syndrome. MDS-UPDRS III is the worldwide reference scale to evaluate the parkinsonian motor impairment, especially bradykinesia. However, MDS-UPDRS III is an agent-based score making reproducible measurements and follow-up challenging. Objective: Using a deep learning approach, we developed a tool to compute an objective score of bradykinesia based on the guidelines of the gold-standard MDS-UPDRS III. Methods: We adapted and applied two deep learning algorithms to detect a two-dimensional (2D) skeleton of the hand composed of 21 predefined points, and transposed it into a three-dimensional (3D) skeleton for a large database of videos of parkinsonian patients performing MDS-UPDRS III protocols acquired in the Movement Disorder unit of Avicenne University Hospital. Results: We developed a 2D and 3D automated analysis tool to study the evolution of several key parameters during the protocol repetitions of the MDS-UPDRS III. Scores from 2D automated analysis showed a significant correlation with gold-standard ratings of MDS-UPDRS III, measured with coefficients of determination for the tapping (0.609) and hand movements (0.701) protocols using decision tree algorithms. The individual correlations of the different parameters measured with MDS-UPDRS III scores carry meaningful information and are consistent with MDS-UPDRS III guidelines. Conclusion: We developed a deep learning-based tool to precisely analyze movement parameters allowing to reliably score bradykinesia for parkinsonian patients in a MDS-UPDRS manner.

Background: International clinical criteria are the reference for the diagnosis of degenerative parkinsonism in clinical research, but they may lack sensitivity and specificity in the early stages.Objectives: To determine whether magnetic resonance imaging (MRI) analysis, through visual reading or machine‐learning approaches, improves diagnostic accuracy compared with clinical diagnosis at an early stage in patients referred for suspected degenerative parkinsonism.Materials: Patients with initial diagnostic uncertainty between Parkinson's disease (PD), progressive supranuclear palsy (PSP), and multisystem atrophy (MSA), with brain MRI performed at the initial visit (V1) and available 2‐year follow‐up (V2), were included. We evaluated the accuracy of the diagnosis established based on: (1) the international clinical diagnostic criteria for PD, PSP, and MSA at V1 (“Clin1”); (2) MRI visual reading blinded to the clinical diagnosis (“MRI”); (3) both MRI visual reading and clinical criteria at V1 (“MRI and Clin1”), and (4) a machine‐learning algorithm (“Algorithm”). The gold standard diagnosis was established by expert consensus after a 2‐year follow‐up.Results: We recruited 113 patients (53 with PD, 31 with PSP, and 29 with MSA). Considering the whole population, compared with clinical criteria at the initial visit (“Clin1”: balanced accuracy, 66.2%), MRI visual reading showed a diagnostic gain of 14.3% (“MRI”: 80.5%; P = 0.01), increasing to 19.2% when combined with the clinical diagnosis at the initial visit (“MRI and Clin1”: 85.4%; P < 0.0001). The algorithm achieved a diagnostic gain of 9.9% (“Algorithm”: 76.1%; P = 0.08).Conclusion: Our study shows the use of MRI analysis, whether by visual reading or machine‐learning methods, for early differentiation of parkinsonism. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.