Effects of transcranial alternating current stimulation on repetitive finger movements in healthy humans

Transcranial alternating current stimulation (tACS) is a noninvasive neurophysiological technique that can entrain brain oscillations. Only few studies have investigated the effects of tACS on voluntary movements. We aimed to verify whether tACS, delivered over M1 at beta and gamma frequencies, has any effect on repetitive finger tapping as assessed by means of kinematic analysis. Eighteen healthy subjects were enrolled. Objective measurements of repetitive finger tapping were obtained by using a motion analysis system. M1 excitability was assessed by using single-pulse TMS and measuring the amplitude of motor-evoked potentials (MEPs). Movement kinematic measures and MEPs were collected during beta, gamma, and sham tACS and when the stimulation was off. Beta tACS led to an amplitude decrement (i.e., progressive reduction in amplitude) across the first ten movements of the motor sequence while gamma tACS had the opposite effect. The results did not reveal any significant effect of tACS on other movement parameters, nor any changes in MEPs. These findings demonstrate that tACS modulates finger tapping in a frequency-dependent manner with no concurrent changes in corticospinal excitability. The results suggest that cortical beta and gamma oscillations are involved in the motor control of repetitive finger movements

Spectral parameters for finger tapping quantification

A miniature inertial sensor placed on fingertip of index finger while performing finger tapping test can be used for an objective quantification of finger tapping motion. Temporal and spatial parameters such as cadence, tapping duration, and tapping angle can be extracted for detailed analysis. However, the mentioned parameters, although intuitive and simple to interpret, do not always provide all the necessary information regarding the subject's motor performance. Analysis of frequency content of the finger tapping movement can provide crucial information about the patient's condition. In this paper, we present parameters extracted from spectral analysis that we found to be significant for finger tapping assessment. With these parameters, tapping's intra-variability, movement smoothness and anomalies that may occur within the tapping performance can be detected and described, providing significant information for further diagnostics and monitoring progress of the disease or response to therapy

Vertical finger displacement is reduced in index finger tapping during repeated bout rate enhancement

The present study analyzed (a) whether a recently reported phenomenon of repeated bout rate enhancement in finger tapping (i.e., a cumulating increase in freely chosen finger tapping frequency following submaximal muscle activation in the form of externally unloaded voluntary tapping) could be replicated and (b) the hypotheses that the faster tapping was accompanied by changed vertical displacement of the fingertip and changed peak force during tapping. Right-handed, healthy, and recreationally active individuals (n = 24) performed two 3-min index finger tapping bouts at freely chosen tapping frequency, separated by 10-min rest. The recently reported phenomenon of repeated bout rate enhancement was replicated. The faster tapping (8.8 ± 18.7 taps/min, corresponding to 6.0 ± 11.0%, p = .033) was accompanied by reduced vertical displacement (1.6 ± 2.9 mm, corresponding to 6.3 ± 14.9%, p = .012) of the fingertip. Concurrently, peak force was unchanged. The present study points at separate control mechanisms governing kinematics and kinetics during finger tapping.</jats:p

A Comparative of Finger Tapping Test Scores Elite Athletes, Art, Foreign Languages and Computer- Instructional Technology Students

Fine motor skill is ability to control and coordinate the small muscles in the hand for precise movements. Fine motor skill have been associated with several other cognitive abilities, including processing speed executive functions and scholastic skills. Fine motor skill in the early years have also been shown to predict later academic achievement, especially in reading and mathematics and to predict underachievement in able students at school. In this aspect our objective in this study was to compare finger tapping test scores between students of art, foreign languages, computer-instructional technologies and elite athletes. A significant difference was found between elite athletes and all groups in finger tapping test scores. Elite athletes performed more finger taps than other groups in the same period. In conclusion, the more importance of fine motor skill in terms of sporting success also explains the difference of the finger tapping test performances between the groups. Keywords: education, motor skills, finger tapping, elite athlete

Slowing fastest finger movements of the dominant hand with low-frequency rTMS of the hand area of the primary motor cortex

Neuroimaging studies suggest that the primary hand motor area and the cerebellum play a pivotal role in the control of finger tapping, but their differential contribution in this task is unknown. We used therefore repetitive transcranial magnetic stimulation (rTMS) in its virtual lesion mode (1Hz, 10min, 90% of motor threshold) to study the effects of transient disruption of the right lateral cerebellum (CB), the left primary hand motor area (M1), and the right brachial plexus (PL, control site) on various finger tapping tasks (paced finger tapping task: PFT; tapping with maximum speed: TAPMAX, and tapping with convenient speed: TAPCON) in healthy right-handed subjects. RTMS of the left M1 slowed finger tapping speed of the right hand in the TAPMAX task. This effect eliminated the right hand superiority in the TAPMAX task. In addition, rTMS of the left M1 resulted in slower tapping speeds for both hands during TAPCON. There were no other effects of rTMS on tapping speed or tapping variability. Findings indicate that M1 is essential for generating fastest finger movement

Differential responses of spinal motoneurons to fatigue induced by short-lasting repetitive and isometric tasks

[Abstract] Compared to isometric activities, the neural basis of fatigue induced by repetitive tasks has been scarcely studied. Recently, we showed that during short-lasting repetitive tasks at the maximal possible rate (finger tapping for 10 and 30 s), tapping rate and maximal voluntary contraction (MVC) force decrease at the end of finger tapping. We also observed larger silent periods (SP) induced by transcranial magnetic stimulation during MVC post finger tapping. However, if SP were induced by cervicomedullary stimulation (CMS) they remained unchanged. This suggested a supraspinal origin of fatigue for repetitive tasks. Nevertheless, CMS SP only partially explore spinal excitability; therefore, to evaluate a spinal origin of fatigue it is essential to know the features of the CMS-evoked potentials (CMEP). Herein, we evaluated (n = 15) the amplitude of the CMEP during MVC executed immediately (no gap) after a short-lasting finger tapping task; we also evaluated the compound muscle action potential (CMAP) so that the amplitude of the CMEP was expressed as a function of the CMAP amplitude. Indices of fatigue obtained during finger tapping were compared with those obtained during short-lasting maximal isometric tasks. While indices of excitability increased initially in both tasks, they decreased with the isometric task only when the task was prolonged to 30 s. We suggest that the inability to maintain increased levels of spinal excitability during task execution is a neurophysiological mark of fatigue. Our results suggest that the origin of fatigue induced by brief and fast repetitive tasks is not spinal.Galicia. Consellería de Educación; 2007/000140-

Motion Capture System for Finger Movement Measurement in Parkinson Disease

Parkinson’s disease (PD) is a chronic neurodegenerative disorder that affects almost 1% of the population in the age group above 60 years. The key symptom in PD is the restriction of mobility. The progress of PD is typically documented using the Unified Parkinson’s Disease Rating Scale (UPDRS), which includes a finger-tapping test. We created a measurement tool and a methodology for the objective measurement of the finger-tapping test. We built a contactless three-dimensional (3D) capture system using two cameras and light-passive (wireless) reflexive markers. We proposed and implemented an algorithm for extracting, matching, and tracing markers. The system provides the 3D position of spherical or hemispherical markers in real time. The system’s functionality was verified with the commercial motion capture system OptiTrack. Our motion capture system is easy to use, saves space, is transportable, and needs only a personal computer for data processing—the ideal solution for an outpatient clinic. Its features were successfully tested on 22 patients with PD and 22 healthy control subjects

Measurement and Evaluation of Finger Tapping Movements Using Log-linearized Gaussian Mixture Networks

This paper proposes a method to quantitatively measure and evaluate finger tapping movements for the assessment of motor function using log-linearized Gaussian mixture networks (LLGMNs). First, finger tapping movements are measured using magnetic sensors, and eleven indices are computed for evaluation. After standardizing these indices based on those of normal subjects, they are input to LLGMNs to assess motor function. Then, motor ability is probabilistically discriminated to determine whether it is normal or not using a classifier combined with the output of multiple LLGMNs based on bagging and entropy. This paper reports on evaluation and discrimination experiments performed on finger tapping movements in 33 Parkinson’s disease (PD) patients and 32 normal elderly subjects. The results showed that the patients could be classified correctly in terms of their impairment status with a high degree of accuracy (average rate: 93.1 ± 3.69%) using 12 LLGMNs, which was about 5% higher than the results obtained using a single LLGMN

The discerning eye of computer vision: can it measure Parkinson's finger tap bradykinesia?

Objective: The worldwide prevalence of Parkinson's disease is increasing. There is urgent need for new tools to objectively measure the condition. Existing methods to record the cardinal motor feature of the condition, bradykinesia, using wearable sensors or smartphone apps have not reached large-scale, routine use. We evaluate new computer vision (artificial intelligence) technology, DeepLabCut, as a contactless method to quantify measures related to Parkinson's bradykinesia from smartphone videos of finger tapping. Methods: Standard smartphone video recordings of 133 hands performing finger tapping (39 idiopathic Parkinson's patients and 30 controls) were tracked on a frame-by-frame basis with DeepLabCut. Objective computer measures of tapping speed, amplitude and rhythm were correlated with clinical ratings made by 22 movement disorder neurologists using the Modified Bradykinesia Rating Scale (MBRS) and Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Results: DeepLabCut reliably tracked and measured finger tapping in standard smartphone video. Computer measures correlated well with clinical ratings of bradykinesia (Spearman coefficients): -0.74 speed, 0.66 amplitude, -0.65 rhythm for MBRS; -0.56 speed, 0.61 amplitude, -0.50 rhythm for MDS-UPDRS; -0.69 combined for MDS-UPDRS. All p Conclusion: New computer vision software, DeepLabCut, can quantify three measures related to Parkinson's bradykinesia from smartphone videos of finger tapping. Objective 'contactless' measures of standard clinical examinations were not previously possible with wearable sensors (accelerometers, gyroscopes, infrared markers). DeepLabCut requires only conventional video recording of clinical examination and is entirely 'contactless'. This next generation technology holds potential for Parkinson's and other neurological disorders with altered movements