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In practicing a new task, the initial performance gains, across consecutive trials, decrease; in the following phase, performance tends to plateau. However, after a long delay additional performance improvements may emerge (delayed/ "offline" gains). It has been suggested that the attainment of the plateau phase is a necessary condition for the triggering of skill consolidation processes that lead to the expression of delayed gains. Here we compared the effect of a long-delay (24-48 h) interval following each of the two within-session phases, on performance in a simple motor task, the finger-tapping sequence learning (FTSL), and in a conceptually complex task, the Tower of Hanoi puzzle (TOHP). In Experiment 1 we determined the amount of practice leading to the plateau phase within a single practice session (long practice), in each task. Experiment 2 consisted of three consecutive sessions with long-delay intervals in between; in the first session, participants underwent a short practice without attaining the plateau phase, but in the next two sessions, participants received long practice, attaining the plateau phase. In the FTSL, short practice resulted in no delayed gains after the long delay, but after 24-48 h following long practice, task performance was further improved. In contrast, no delayed gains evolved in the TOHP during the 24- to 48-h delay following long practice. We propose that the attainment of a plateau phase can indicate either the attainment of a comprehensive task solution routine (achievable for simple tasks) or a preservation of work-in-progress task solution routine (complex tasks); performance after a long post-practice interval can differentiate these two states.

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OBJECTIVES: Personal Assistive RObot (PARO) interventions have been used to treat agitation and mood symptoms of dementia effectively. However, the effects of a PARO intervention on physiological and cognitive function are unclear. To examine the effects of a group-based PARO intervention for older adults with mild dementia. DESIGN: Using a group-based PARO intervention randomized controlled trial with 2-arm parallel groups. SETTING AND PARTICIPANTS: Older adults with mild dementia aged 65 years or older from 4 dementia day care centers were recruited. METHODS: Physiological parameters were assessed using the finger tapping test (FTT) and heart rate variability (HRV). The Mini-Mental State Examination (MMSE), Geriatric Depression Scale-Short Form (GDS-SF), University of California Los Angeles loneliness scale-version 3 (UCLA-3), and Warwick-Edinburgh Mental Well-being Scale (WEMWBS) were assessed before the intervention, end of the intervention, and 1-month after the intervention. RESULTS: Using a repeated-measures generalized linear model, significant time × group interactions were found in the MMSE [F(2, 115) = 19.54, P < .001], FTT [F(2, 115) = 4.87, P = .01], HRV high-frequency [F(2, 115) = 3.57, P = .03], and high-frequency/low-frequency ratio [F(2, 115) = 0.96, P = .01], UCLA-3 [F(2, 115) = 54.7, P < .001], GDS-SF [F(2, 115) = 3.36, P = .04], and WEMWBS [F(2, 115) = 5.93, P < .001]. Furthermore, psychological parameters improved significantly and continuously even 1 month after the PARO intervention was finished. Physiological parameters significantly improved at week 6, but the effects had diminished by week 10. CONCLUSIONS AND IMPLICATIONS: A PARO intervention may effectively improve the physiological and psychological responses of people with mild dementia.

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OBJECTIVE: This study aimed to explore the relationships between potential neurophysiological biomarkers and upper limb motor function recovery in stroke patients, specifically focusing on combining two neurophysiological markers: electroencephalography (EEG) and transcranial magnetic stimulation (TMS). METHODS: This cross-sectional study analyzed neurophysiological, clinical, and demographical data from 102 stroke patients from the DEFINE cohort. We searched for correlations of EEG and TMS measurements combined to build a prediction model for upper limb motor functionality, assessed by five outcomes, across five assessments: Fugl-Meyer Assessment (FMA), Handgrip Strength Test (HST), Finger Tapping Test (FTT), Nine-Hole Peg Test (9HPT), and Pinch Strength Test (PST). RESULTS: Our multivariate models agreed on a specific neural signature: higher EEG Theta/Alpha ratio in the frontal region of the lesioned hemisphere is associated with poorer motor outcomes, while increased MEP amplitude in the non-lesioned hemisphere correlates with improved motor function. These relationships are held across all five motor assessments, suggesting the potential of these neurophysiological measures as recovery biomarkers. CONCLUSION: Our findings indicate a potential neural signature of brain compensation in which lower frequencies of EEG power are increased in the lesioned hemisphere, and lower corticospinal excitability is also increased in the non-lesioned hemisphere. We discuss the meaning of these findings in the context of motor recovery in stroke.

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BACKGROUND: Finger tapping impairment and frailty share overlapping pathophysiology and symptoms in older adults, however, the relationship between each other has not been previously studied. OBJECTIVES: To investigate how finger tapping movements correlate with frail status in older Japanese adults. DESIGN, SETTING, AND PARTICIPANTS: Data were from a cross-sectional study called the Cognition and Activity in Rural Environment of Hokkaido Senior Survey 2018. A total of 244 community-dwelling older adults (mean age 75.3 years) were included. MEASUREMENTS: Participants underwent physical examinations, gait and finger tapping tests, and completed self-administered questionnaires. Frailty was assessed using Fried's frailty phenotype, and factor analysis was conducted to extract relevant finger tapping factors. Multinomial logistic regression was employed to analyze associations, generating adjusted odds ratios. RESULTS: Of the participants, 18 were frail, and 145 pre-frail. Analysis identified three distinct finger tapping patterns: "Range of Motion - Nondominant Hand," "Variability - Dominant Hand - Anti," and "Variability - Nondominant Hand - Anti." These patterns showed significant associations with aspects of Fried's frailty phenotype, particularly low physical activity (P = 0.002), weakness (P = 0.003), and slowness (P = 0.004). A larger range of motion in the nondominant hand correlated with a lower frailty risk (Odds Ratio: 0.09, 95% CI: 0.02-0.46), while higher variability in the same hand increased the risk of pre-frailty (Odds Ratio: 2.19, 95% CI: 1.09-4.39). CONCLUSION: Finger tapping movements are significantly associated with frailty status as determined by Fried's phenotype. The findings underscore the importance of further longitudinal studies to understand the relationship between motor function and frailty.

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Portable and flexible administration of manual dexterity assessments is necessary to monitor recovery from brain injury and the effects of interventions across clinic and home settings, especially when in-person testing is not possible or convenient. This paper aims to assess the concurrent validity and test-retest reliability of a new suite of touchscreen-based manual dexterity tests (called EDNA™MoTap) that are designed for portable and efficient administration. A minimum sample of 49 healthy young adults will be conveniently recruited. The EDNA™MoTap tasks will be assessed for concurrent validity against standardized tools (the Box and Block Test [BBT] and the Purdue Pegboard Test) and for test-retest reliability over a 1- to 2-week interval. Correlation coefficients of r > .6 will indicate acceptable validity, and intraclass correlation coefficient (ICC) values > .75 will indicate acceptable reliability for healthy adults. The sample were primarily right-handed (91%) adults aged 19 and 34 years (M = 24.93, SD = 4.21, 50% female). The MoTap tasks did not demonstrate acceptable validity, with tasks showing weak-to-moderate associations with the criterion assessments. Some outcomes demonstrated acceptable test-retest reliability; however, this was not consistent. Touchscreen-based assessments of dexterity remain relevant; however, there is a need for further development of the EDNA™MoTap task administration.

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Introduction: Bradykinesia is an essential diagnostic criterion for Parkinson's disease (PD) but is frequently observed in many non-parkinsonian movement disorders, complicating differential diagnosis, particularly in disorders featuring tremors. The presence of bradykinetic features in the subset of dystonic tremors (DT), either "pure" dystonic tremors or tremors associated with dystonia, remains currently unexplored. The aim of the current study was to evaluate upper limb bradykinesia in DT patients, comparing them with healthy controls (HC) and patients with PD by observing repetitive finger tapping (FT). Methods: The protocol consisted of two main parts. Initially, the kinematic recording of repetitive FT was performed using optical hand tracking system (Leap Motion Controller). The values of amplitude, amplitude decrement, frequency, frequency decrement, speed, acceleration and number of halts of FT were calculated. Subsequently, three independent movement disorder specialists from different movement disorders centres, blinded to the diagnosis, rated the presence of FT bradykinesia based on video recordings. Results: Thirty-six subjects participated in the study (12 DT, 12 HC and 12 early-stage PD). Kinematic analysis revealed no significant difference in the selected parameters of FT bradykinesia between DT patients and HC. In comparisons between DT and PD patients, PD patients exhibited bigger amplitude decrement and slower FT performance. In the blinded clinical assessment, bradykinesia was rated, on average, as being present in 41.6% of DT patients, 27.7% of HC, and 91.7% of PD patients. While overall inter-rater agreement was moderate, weak agreement was noted within the DT group. Discussion: Clinical ratings indicated signs of bradykinesia in almost half of DT patients. The objective kinematic analysis confirmed comparable parameters between DT and HC individuals, with more pronounced abnormalities in PD across various kinematic parameters. Interpretation of bradykinesia signs in tremor patients with DT should be approached cautiously and objective motion analysis might complement the diagnostic process and serve as a decision support system in the choice of clinical entities.

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Introduction: Even simple tapping tasks require cognitive processes. Some variants of the Finger Tapping Test (FTT) may reveal cognitive aspects associated with frontal processing, including executive functions such as inhibition, or emotional aspects such as anxiety. A context of particular interest for the application of cognitive-motor-anxiety interactions is sports. Although athletes generally exhibit better anxiety levels, they may experience heightened anxiety before important competitions. The problem lies in determining whether the application of anxiety control techniques can be useful in pre-competition situations, given the lack of quick and easy methods to detect if an athlete is experiencing anxiety at a particular moment. Methods: This exploratory study evaluated anxiety using online versions of questionnaires (ISRA, the Competitive State Anxiety Inventory-2, and STAI) and applied a variant of the FTT to 204 participants, both athletes and non-athletes. The scores were compared and correlated. Results: Athletes exhibited lower general anxiety and greater cognitive resistance to interference (better cognitive inhibition). Non-athletes displayed a particular parameter in the FTT variant that differed from the one obtained by athletes and exhibited higher anxiety levels. In the athletes' group only, anxiety was correlated with a specific parameter of the FTT task. Discussion: Our conclusion is that this parameter holds potential relevance in elite sports performance to detect if an athlete is experiencing anxiety. It could be of particular interest in psychological interventions in sports. Further investigation is warranted to fully explore this potential.

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Parkinson's disease (PD) is characterized by the disruption of repetitive, concurrent and sequential motor actions due to compromised timing-functions principally located in cortex-basal ganglia (BG) circuits. Increasing evidence suggests that motor impairments in untreated PD patients are linked to an excessive synchronization of cortex-BG activity at beta frequencies (13-30 Hz). Levodopa and subthalamic nucleus deep brain stimulation (STN-DBS) suppress pathological beta-band reverberation and improve the motor symptoms in PD. Yet a dynamic tuning of beta oscillations in BG-cortical loops is fundamental for movement-timing and synchronization, and the impact of PD therapies on sensorimotor functions relying on neural transmission in the beta frequency-range remains controversial. Here, we set out to determine the differential effects of network neuromodulation through dopaminergic medication (ON and OFF levodopa) and STN-DBS (ON-DBS, OFF-DBS) on tapping synchronization and accompanying cortical activities. To this end, we conducted a rhythmic finger-tapping study with high-density EEG-recordings in 12 PD patients before and after surgery for STN-DBS and in 12 healthy controls. STN-DBS significantly ameliorated tapping parameters as frequency, amplitude and synchrony to the given auditory rhythms. Aberrant neurophysiologic signatures of sensorimotor feedback in the beta-range were found in PD patients: their neural modulation was weaker, temporally sluggish and less distributed over the right cortex in comparison to controls. Levodopa and STN-DBS boosted the dynamics of beta-band modulation over the right hemisphere, hinting to an improved timing of movements relying on tactile feedback. The strength of the post-event beta rebound over the supplementary motor area correlated significantly with the tapping asynchrony in patients, thus indexing the sensorimotor match between the external auditory pacing signals and the performed taps. PD patients showed an excessive interhemispheric coherence in the beta-frequency range during the finger-tapping task, while under DBS-ON the cortico-cortical connectivity in the beta-band was normalized. Ultimately, therapeutic DBS significantly ameliorated the auditory-motor coupling of PD patients, enhancing the electrophysiological processing of sensorimotor feedback-information related to beta-band activity, and thus allowing a more precise cued-tapping performance.

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Malnutrition remains a pressing health concern in developing nations, contributing to growth delay (stunting) and psychomotor impairments among the youth. Tanzania has the highest prevalence of stunting, yet the psychomotor status of its population has not been previously studied. To address this gap, we gathered anthropometric, nutritional, and psychomotor data from 211 children with the aim of assessing the reliability of digital tools as indicators of psychomotor performance in relation to the nutritional status. Collected anthropometric measures included middle-upper arm circumference (MUAC), triceps skinfold thickness (TST), and handgrip strength, while psychomotor variables were assessed using digital finger tapping test (DFTT), eye-tracking test (ETT), and nine-hole peg test (9HPT). Statistical analysis revealed significant associations between age and both MUAC and handgrip strength (R = 0.5, p < 0.001). Moreover, DFTT and 9HPT demonstrated a correlation with each other (p = 0.026) and with MUAC, handgrip strength, and age (p < 0.001). Notably, lower stature was independently linked to slower horizontal eye movements (p < 0.001). Findings underscores the crucial link between nutrition and psychomotor skills in Tanzanian children. Digital tests like DFTT, ETT, and the 9HPT show promise for assessing psychomotor performance. Addressing malnutrition requires comprehensive interventions. Future research should explore long-term effects of interventions in resource-limited settings.

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Introduction: Neurofeedback using near-infrared spectroscopy (NIRS) has been used in patients with stroke and other patients, but few studies have included older people or patients with cognitive impairment. Methods: We constructed a NIRS-based neurofeedback system and used finger tapping to investigate whether neurofeedback can be implemented in older adults while finger tapping and whether brain activity improves in older adults and healthy participants. Our simple neurofeedback system was constructed using a portable wearable optical topography (WOT-HS) device. Brain activity was evaluated in 10 older and 31 healthy young individuals by measuring oxygenated hemoglobin concentration during finger tapping and neurofeedback implementation. Results: During neurofeedback, the concentration of oxygenated hemoglobin increased in the prefrontal regions in both the young and older participants. Discussion: The results of this study demonstrate the usefulness of neurofeedback using simple NIRS devices for older adults and its potential to mitigate cognitive decline.

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BACKGROUND: Knowing how impaired manual dexterity and finger proprioception affect upper limb activity capacity is important for delineating targeted post-stroke interventions for upper limb recovery. OBJECTIVES: To investigate whether impaired manual dexterity and finger proprioception explain variance in post-stroke activity capacity, and whether they explain more variance than conventional clinical assessments of upper limb sensorimotor impairments. METHODS: Activity capacity and hand sensorimotor impairments were assessed using clinical measures in N = 42 late subacute/chronic hemiparetic stroke patients. Dexterity was evaluated using the Dextrain Manipulandum to quantify accuracy of visuomotor finger force-tracking (N = 36), timing of rhythmic tapping (N = 36), and finger individuation (N = 24), as well as proprioception (N = 27). Stepwise multivariate and hierarchical linear regression models were used to identify impairments best explaining activity capacity. RESULTS: Dexterity and proprioceptive components significantly increased the variance explained in activity capacity: (i) Box and Block Test was best explained by baseline tonic force during force-tracking and tapping frequency (adjusted R2 = .51); (ii) Motor Activity Log was best explained by success rate in finger individuation (adjusted R2 = .46); (iii) Action Research Arm Test was best explained by release of finger force and proprioceptive measures (improved reaction time related to use of proprioception; adjusted R2 = .52); and (iv) Moberg Pick-Up test was best explained by proprioceptive function (adjusted R2 = .18). Models excluding dexterity and proprioception variables explained up to 19% less variance. CONCLUSIONS: Manual dexterity and finger proprioception explain unique variance in activity capacity not captured by conventional impairment measures and should be assessed when considering the underlying causes of post-stroke activity capacity limitations.URL: https://www.clinicaltrials.gov. Unique identifier: NCT03934073.

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When applied over the primary motor cortex (M1), anodal transcranial direct current stimulation (a-tDCS) could enhance the effects of a single motor imagery training (MIt) session on the learning of a sequential finger-tapping task (SFTT). This study aimed to investigate the effect of a-tDCS on the learning of an SFTT during multiple MIt sessions. Two groups of 16 healthy young adults participated in three consecutive MIt sessions over 3 days, followed by a retention test 1 week later. They received active or sham a-tDCS during a MIt session in which they mentally rehearsed an eight-item complex finger sequence with their left hand. Before and after each session, and during the retention test, they physically repeated the sequence as quickly and accurately as possible. Both groups (i) improved their performance during the first two sessions, showing online learning; (ii) stabilised the level they reached during all training sessions, reflecting offline consolidation; and (iii) maintained their performance level one week later, showing retention. However, no significant difference was found between the groups, regardless of the MSL stage. These results emphasise the importance of performing several MIt sessions to maximise performance gains, but they do not support the additional effects of a-tDCS.

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BACKGROUND: Dementia prevalence is predicted to triple to 152 million globally by 2050. Alzheimer's disease (AD) constitutes 70% of cases. There is an urgent need to identify individuals with preclinical AD, a 10-20-year period of progressive brain pathology without noticeable cognitive symptoms, for targeted risk reduction. Current tests of AD pathology are either too invasive, specialised or expensive for population-level assessments. Cognitive tests are normal in preclinical AD. Emerging evidence demonstrates that movement analysis is sensitive to AD across the disease continuum, including preclinical AD. Our new smartphone test, TapTalk, combines analysis of hand and speech-like movements to detect AD risk. This study aims to [1] determine which combinations of hand-speech movement data most accurately predict preclinical AD [2], determine usability, reliability, and validity of TapTalk in cognitively asymptomatic older adults and [3], prospectively validate TapTalk in older adults who have cognitive symptoms against cognitive tests and clinical diagnoses of Mild Cognitive Impairment and AD dementia. METHODS: Aim 1 will be addressed in a cross-sectional study of at least 500 cognitively asymptomatic older adults who will complete computerised tests comprising measures of hand motor control (finger tapping) and oro-motor control (syllabic diadochokinesis). So far, 1382 adults, mean (SD) age 66.20 (7.65) years, range 50-92 (72.07% female) have been recruited. Motor measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 to develop an algorithm that classifies preclinical AD risk. Aim 2 comprises three sub-studies in cognitively asymptomatic adults: (i) a cross-sectional study of 30-40 adults to determine the validity of data collection from different types of smartphones, (ii) a prospective cohort study of 50-100 adults ≥ 50 years old to determine usability and test-retest reliability, and (iii) a prospective cohort study of ~1,000 adults ≥ 50 years old to validate against cognitive measures. Aim 3 will be addressed in a cross-sectional study of ~200 participants with cognitive symptoms to validate TapTalk against Montreal Cognitive Assessment and interdisciplinary consensus diagnosis. DISCUSSION: This study will establish the precision of TapTalk to identify preclinical AD and estimate risk of cognitive decline. If accurate, this innovative smartphone app will enable low-cost, accessible screening of individuals for AD risk. This will have wide applications in public health initiatives and clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06114914, 29 October 2023. Retrospectively registered.

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The finger tapping test (FTT) is a tool to evaluate the motor performance of the hand and fingers and eye-hand coordination with applicability in people with multiple sclerosis (pwMS). The aim of this study was to evaluate the intra- and inter-rater reliability of the TappingPro® mobile app and the construct validity between this app and validated clinical scales for motor performance in healthy subjects and pwMS. 42 healthy subjects (mean age 25.05) and 13 pwMS (mean age 51.69, EDSS between 3 and 7.5E) participated. FTT was performed with the TappingPro® mobile app. All participants were examined twice, with a one-week interval between the two appointments. For the analysis of construct validity, the Jamar® hydraulic hand dynamometer, Box and Blocks Test (BBT), and Nine Hole Peg Test (NHPT) were used. The intra-rater reliability showed a good correlation (Intraclass Correlation Coefficient, ICC > 0.787) for both upper limbs and both times of FTT for healthy subjects, and an excellent correlation (ICC > 0.956) for upper limbs and both times of FTT for pwMS. The ICC for the inter-rater reliability was good (ICC = 0.869) for the non-dominant upper limb in the FTT 10 s of the healthy subjects, and excellent (ICC > 0.904) for all the other measurements of the healthy subjects and pwMS. However, the Bland-Altman plots showed disagreement between observers and measurements that should be considered in the interpretation of clinical evaluations. The correlation analysis for healthy subjects showed poor associations between all variables, except for the association between hand grip strength and the FTT 60 s in the non-dominant upper limb, which had a moderate coefficient. For pwMS, there were moderate to excellent associations between BBT and the NHPT and FTT for both upper limbs. The correlations between hand grip strength and FFT were poor. This mobile app could be a useful and low-cost assessment tool in pwMS, allowing a simple evaluation and follow-up that has excellent correlation with clinical scales validated in this pathology.

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Bradykinesia is a behavioral manifestation that contributes to functional dependencies in later life. However, the current state of bradykinesia indexing primarily relies on subjective, time-averaged categorizations of motor deficits, which often yield poor reliability. Herein, we used time-resolved analyses of accelerometer recordings during standardized movements, data-driven factor analyses, and linear mixed effects models (LMEs) to quantitatively characterize general, task- and therapy-specific indices of motor impairment in people with Parkinson's disease (PwP) currently undergoing treatment for bradykinesia. Our results demonstrate that single-trial, accelerometer-based features of finger-tapping and rotational hand movements were significantly modulated by divergent therapeutic regimens. Further, these features corresponded well to current gold standards for symptom monitoring, with more precise predictive capacities of bradykinesia-specific declines achieved when considering kinematic features from diverse movement types together, rather than in isolation. Herein, we report data-driven, sample-specific kinematic profiles of diverse movement types along a continuous spectrum of motor impairment, which importantly, preserves the temporal scale for which biomechanical fluctuations in motor deficits evolve in humans. Therefore, this approach may prove useful for tracking bradykinesia-induced motor decline in aging populations the future.

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Parkinson's disease (PD) is a progressive neurodegenerative disorder whose prevalence has steadily been rising over the years. Specialist neurologists across the world assess and diagnose patients with PD, although the diagnostic process is time-consuming and various symptoms take years to appear, which means that the diagnosis is prone to human error. The partial automatization of PD assessment and diagnosis through computational processes has therefore been considered for some time. One well-known tool for PD assessment is finger tapping (FT), which can now be assessed through computer vision (CV). Artificial intelligence and related advances over recent decades, more specifically in the area of CV, have made it possible to develop computer systems that can help specialists assess and diagnose PD. The aim of this study is to review some advances related to CV techniques and FT so as to offer insight into future research lines that technological advances are now opening up.

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Although implicated in unsuccessful treatment, psychomotor deficits and their neurobiological underpinnings in bipolar (BD) and unipolar (UD) depression remain poorly investigated. Here, we hypothesized that motor performance deficits in depressed patients would relate to basal functional coupling of the hand primary motor cortex (M1) and the posterior cingulate cortex (PCC) with the supplementary motor area (SMA). We performed a longitudinal, naturalistic study in BD, UD and matched healthy controls comprising of two resting-state functional MRI measurements five weeks apart and accompanying assessments of motor performance using a finger tapping task (FTT). A subject-specific seed-based analysis describing functional connectivity between PCC-SMA as well as M1-SMA was conducted. The basal relationships with motor performance were investigated using linear regression models and all measures were compared across groups. Performance in FTT was impaired in BD in comparison to HC in both sessions. Behavioral performance across groups correlated significantly with resting state functional coupling of PCC-SMA, but not of M1-SMA regions. This relationship was partially reflected in a reduced PCC-SMA connectivity in BD vs HC in the second session. Exploratory evaluation of large-scale networks coupling (SMN-DMN) exhibited no correlation to motor performance. Our results shed new light on the association between the degree of disruption in the SMA-PCC anticorrelation and the level of motor impairment in BD.

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Synchronizing movement with external stimuli is important in musicians and athletes. This study investigated the effects of sound characteristics, including sound with harmonics (square wave) and without harmonics (sine wave) and levels of expertise in sports and music on rhythmic ability. Thirty-two university students participated in the study. The participants were divided into sixteen music education (ME) and sixteen physical education (PE) majors. They were asked to perform finger tapping tasks with 1,2 and 3 Hz beat rates, tapping in time with the sine and square wave beat produced by a metronome. The relative phase angle of finger tapping and the onset time of metronome sound were calculated using circular statistics. The results showed that type of wave and music experience affected the rhythmic ability of participants. Our study highlights the importance of types of waves on rhythmic ability, especially for participants with no background in music. The square wave is recommended for athletes to learn to synchronize their movement with beats.

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The utilization of Artificial Intelligence (AI) for assessing motor performance in Parkinson's Disease (PD) offers substantial potential, particularly if the results can be integrated into clinical decision-making processes. However, the precise quantification of PD symptoms remains a persistent challenge. The current standard Unified Parkinson's Disease Rating Scale (UPDRS) and its variations serve as the primary clinical tools for evaluating motor symptoms in PD, but are time-intensive and prone to inter-rater variability. Recent work has applied data-driven machine learning techniques to analyze videos of PD patients performing motor tasks, such as finger tapping, a UPDRS task to assess bradykinesia. However, these methods often use abstract features that are not closely related to clinical experience. In this paper, we introduce a customized machine learning approach for the automated scoring of UPDRS bradykinesia using single-view RGB videos of finger tapping, based on the extraction of detailed features that rigorously conform to the established UPDRS guidelines. We applied the method to 75 videos from 50 PD patients collected in both a laboratory and a realistic clinic environment. The classification performance agreed well with expert assessors, and the features selected by the Decision Tree aligned with clinical knowledge. Our proposed framework was designed to remain relevant amid ongoing patient recruitment and technological progress. The proposed approach incorporates features that closely resonate with clinical reasoning and shows promise for clinical implementation in the foreseeable future.

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In neuroscience, clarifying the functional localization of the cerebrum using functional near-infrared spectroscopy (fNIRS) is one of the important works. To better understand and trust fNIRS data, neuroscientists formulate hypothesis about the underlying neural processes. However, visualizing and validating these hypotheses is not easy due to the complex nature of brain activity and the limitations of fNIRS measurements. In this paper, we suggest the novel Monte Carlo tool designed to assist fNIRS study for neuroscientists and to deal with these problems. The tool provides a user-friendly interface for generating realistic virtual brain activity patterns based on a specified hypothesis. By setting up a region of interest in the standard brain based on the hypothesis, the simulation models the propagation of light through the brain accurately and mimics the hemodynamic response observed in fNIRS measurements. By visually displaying simulation data and identifying the major activation point, neuroscientists can validate and refine hypothesis and obtain a better understanding of the neural mechanisms underlying the fNIRS signals.•A Monte Carlo simulation method reflecting the functional localization of the cerebrum for fNIRS measurements.•Method for setting ROI corresponding to the functional localization of the cerebrum in the standard brain.•Visualization of Monte Carlo simulation results and anatomical evaluation method of activation points.