We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the alternating serial reaction time task, exhibited good test-retest reliability in measures of learning and performance. However, the learning measures did not correlate between the two tasks, arguing against a shared process for implicit motor learning.

Objective: To evaluate the feasibility of a smartphone remote patient monitoring approach in a real-life Parkinson's disease (PD) cohort during the Italian COVID-19 lockdown. Methods: Fifty-four non-demented PD patients who were supposed to attend the outpatient March clinic were recruited for a prospective study. All patients had a known UPDRS-III and a modified Hoehn and Yahr (H&Y) score and were provided with a smartphone application capable of providing indicators of gait, tapping, tremor, memory and executive functions. Different questionnaires exploring non-motor symptoms and quality of life were administered through phone-calls. Patients were asked to run the app at least twice per week (i.e., full compliance). Subjects were phone-checked weekly throughout a 3-week period for compliance and final satisfaction questionnaires. Results: Forty-five patients (83.3%) ran the app at least once; Twenty-nine (53.7%) subjects were half-compliant, while 16 (29.6%) were fully compliant. Adherence was hindered by technical issues or digital illiteracy (38.7%), demotivation (24%) and health-related issues (7.4%). Ten patients (18.5%) underwent PD therapy changes. The main factors related to lack of compliance included loss of interest, sadness, anxiety, the absence of a caregiver, the presence of falls and higher H&Y. Gait, tapping, tremor and cognitive application outcomes were correlated to disease duration, UPDRS-III and H&Y. Discussion: The majority of patients were compliant and satisfied by the provided monitoring program. Some of the application outcomes were statistically correlated to clinical parameters, but further validation is required. Our pilot study suggested that the available technologies could be readily implemented even with the current population's technical and intellectual resources.

BackgroundMood disorders are dynamic disorders characterized by multimodal symptoms. Clinical assessment of symptoms is currently limited to relatively sparse, routine clinic visits, requiring retrospective recollection of symptoms present in the weeks preceding the visit. Novel advances in mobile tools now support ecological momentary assessment of mood, conducted frequently using mobile devices, outside the clinical setting. Such mood assessment may help circumvent problems associated with infrequent reporting and better characterize the dynamic presentation of mood symptoms, informing the delivery of novel treatment options.ObjectivesThe aim of our study was to validate the Immediate Mood Scaler (IMS), a newly developed, iPad-deliverable 22-item self-report tool designed to capture current mood states.MethodsA total of 110 individuals completed standardized questionnaires (Patient Health Questionnaire, 9-item [PHQ-9]; generalized anxiety disorder, 7-Item [GAD-7]; and rumination scale) and IMS at baseline. Of the total, 56 completed at least one additional session of IMS, and 17 completed one additional administration of PHQ-9 and GAD-7. We conducted exploratory Principal Axis Factor Analysis to assess dimensionality of IMS, and computed zero-order correlations to investigate associations between IMS and standardized scales. Linear Mixed Model (LMM) was used to assess IMS stability across time and to test predictability of PHQ-9 and GAD-7 score by IMS.ResultsStrong correlations were found between standard mood scales and the IMS at baseline (r=.57-.59, P<.001). A factor analysis revealed a 12-item IMS (“IMS-12”) with two factors: a “depression” factor and an “anxiety” factor. IMS-12 depression subscale was more strongly correlated with PHQ-9 than with GAD-7 (z=1.88, P=.03), but the reverse pattern was not found for IMS-12 anxiety subscale. IMS-12 showed less stability over time compared with PHQ-9 and GAD-7 (.65 vs .91), potentially reflecting more sensitivity to mood dynamics. In addition, IMS-12 ratings indicated that individuals with mild to moderate depression had greater mood fluctuations compared with individuals with severe depression (.42 vs .79; P=.04). Finally, IMS-12 significantly contributed to the prediction of subsequent PHQ-9 (beta=1.03, P=.02) and GAD-7 scores (beta =.93, P=.01).ConclusionsCollectively, these data suggest that the 12-item IMS (IMS-12) is a valid tool to assess momentary mood symptoms related to anxiety and depression. Although IMS-12 shows good correlation with standardized scales, it further captures mood fluctuations better and significantly adds to the prediction of the scales. Results are discussed in the context of providing continuous symptom quantification that may inform novel treatment options and support personalized treatment plans.

Background: Transcranial direct current stimulation (tDCS) can enhance cognitive function in healthy individuals, with promising applications as a therapeutic intervention. Despite this potential, variability in the efficacy of tDCS has been a considerable concern.Objective/Hypothesis: Given that tDCS is always applied at a set intensity, we examined whether individual differences in sensitivity to brain stimulation might be one variable that modulates the efficacy of tDCS in a motor learning task. Methods:In the first part of the experiment, single-pulse transcranial magnetic stimulation (TMS) over primary motor cortex (M1) was used to determine each participant's resting motor threshold (rMT). This measure was used as a proxy of individual sensitivity to brain stimulation. In an experimental group of 28 participants, 2 mA tDCS was then applied during a motor learning task with the anodal electrode positioned over left M1. Another 14 participants received sham stimulation.Results: M1-Anodal tDCS facilitated learning relative to participants who received sham stimulation. Of primary interest was a within-group analysis of the experimental group, showing that the rate of learning was positively correlated with rMT: Participants who were more sensitive to brain stimulation as operationalized by our TMS proxy (low rMT), showed faster adaptation. Conclusions:Methodologically, the results indicate that TMS sensitivity can predict tDCS efficacy in a behavioral task, providing insight into one source of variability that may contribute to replication problems with tDCS. Theoretically, the results provide further evidence of a role of sensorimotor cortex in adaptation, with the boost from tDCS observed during acquisition.

Cognitive models of depression suggest that depressed individuals exhibit a tendency to attribute negative meaning to neutral stimuli, and enhanced processing of mood-congruent stimuli. However, evidence thus far has been inconsistent. In this study, we sought to identify both differential interpretation of neutral information and emotion processing biases associated with depression. Fifty adult participants completed standardized mood-related questionnaires, a novel immediate mood scale questionnaire (IMS-12), and a novel task, Emotion Matcher, in which participants were required to indicate whether pairs of emotional faces show the same expression or not. We found that overall success rate and reaction time did not differ as a function of level of depression. However, more depressed participants had significantly worse performance when presented with sad-neutral pairs, as well as increased reaction times to happy-happy pairs. In addition, accuracy of the sad-neutral pairs was found to be significantly associated with depression severity in a regression model. Our study provides partial support to the mood-congruent *