Differential Sensitivity Between a Virtual Reality Balance Module and Clinically Used Concussion Balance Modalities

Balance assessments are part of the recommended clinical concussion evaluation, along with computerized neuropsychological testing and self-reported symptoms checklists. New technology has allowed for the creation of virtual reality (VR) balance assessments to be used in concussion care, but there is little information on the sensitivity and specificity of these evaluations. The purpose of this study is to establish the sensitivity and specificity of a VR balance module for detecting lingering balance deficits clinical concussion care

Brain structure can mediate or moderate the relationship of behavior to brain function and transcriptome. A preliminary study

Abnormalities in motor-control behavior, which have been with concussion and head acceleration events (HAE), can be quantified using virtual reality (VR) technologies. Motor-control behavior has been consistently mapped to the brain's somatomotor network (SM) using both structural (sMRI) and functional MRI (fMRI). However, no studies habe integrated HAE, motor-control behavior, sMRI and fMRI measures. Here, brain networks important for motor-control were hypothesized to show changes in tractography-based diffusion weighted imaging [difference in fractional anisotropy (dFA)] and resting-state fMRI (rs-fMRI) measures in collegiate American football players across the season, and that these measures would relate to VR-based motor-control. We firther tested if nine inflammation-related miRNAs were associated with behavior-structure-function variables. Using permutation-based mediation and moderation methods, we found that across-season dFA from the SM structural connectome (SM-dFA) mediated the relationship between across-season VR-based Sensory-motor Reactivity (dSR) and rs-fMRI SM fingerprint similarity (p = 0.007 and Teff = 47%). The interaction between dSR and SM-dFA also predicted (pF = 0.036, pbeta3 = 0.058) across-season levels of dmiRNA-30d through permutation-based moderation analysis. These results suggest (1) that motor-control is in a feedback relationship with brain structure and function, (2) behavior-structure-function can be connected to HAE, and (3) behavior-structure might predict molecular biology measures.Comment: 62 pages, 4 figures, 2 table

Task-dependent activation of distinct fast and slow(er) motor pathways during motor imagery

Background: Motor imagery and actual movements share overlapping activation of brain areas but little is known about task-specific activation of distinct motor pathways during mental simulation of movements. For real contractions, it was demonstrated that the slow(er) motor pathways are activated differently in ballistic compared to tonic contractions but it is unknown if this also holds true for imagined contractions.Objective: The aim of the present study was to assess the activity of fast and slow(er) motor pathways during mentally simulated movements of ballistic and tonic contractions.Methods: H-reflexes were conditioned with transcranial magnetic stimulation at different interstimulus intervals to assess the excitability of fast and slow(er) motor pathways during a) the execution of tonic and ballistic contractions, b) motor imagery of these contraction types, and c) at rest.Results: In contrast to the fast motor pathways, the slow(er) pathways displayed a task-specific activation: for imagined ballistic as well as real ballistic contractions, the activation was reduced compared to rest whereas enhanced activation was found for imagined tonic and real tonic contractions.Conclusions: This study provides evidence that the excitability of fast and slow(er) motor pathways during motor imagery resembles the activation pattern observed during real contractions. The findings indicate that motor imagery results in task- and pathway-specific subliminal activation of distinct subsets of neurons in the primary motor cortex

Shannon and Renyi Entropies to Classify Effects of Mild Traumatic Brain Injury on Postural Sway

Background: Mild Traumatic Brain Injury (mTBI) has been identified as a major public and military health concern both in the United States and worldwide. Characterizing the effects of mTBI on postural sway could be an important tool for assessing recovery from the injury. Methodology/Principal Findings: We assess postural sway by motion of the center of pressure (COP). Methods for data reduction include calculation of area of COP and fractal analysis of COP motion time courses. We found that fractal scaling appears applicable to sway power above about 0.5 Hz, thus fractal characterization is only quantifying the secondary effects (a small fraction of total power) in the sway time series, and is not effective in quantifying long-term effects of mTBI on postural sway. We also found that the area of COP sensitively depends on the length of data series over which the COP is obtained. These weaknesses motivated us to use instead Shannon and Renyi entropies to assess postural instability following mTBI. These entropy measures have a number of appealing properties, including capacity for determination of the optimal length of the time series for analysis and a new interpretation of the area of COP. Conclusions: Entropy analysis can readily detect postural instability in athletes at least 10 days post-concussion so that it appears promising as a sensitive measure of effects of mTBI on postural sway

Complex hand dexterity: a review of biomechanical methods for measuring musical performance

Complex hand dexterity is fundamental to our interactions with the physical, social, and cultural environment. Dexterity can be an expression of creativity and precision in a range of activities, including musical performance. Little is understood about complex hand dexterity or how virtuoso expertise is acquired, due to the versatility of movement combinations available to complete any given task. This has historically limited progress of the field because of difficulties in measuring movements of the hand. Recent developments in methods of motion capture and analysis mean it is now possible to explore the intricate movements of the hand and fingers. These methods allow us insights into the neurophysiological mechanisms underpinning complex hand dexterity and motor learning. They also allow investigation into the key factors that contribute to injury, recovery and functional compensation. The application of such analytical techniques within musical performance provides a multidisciplinary framework for purposeful investigation into the process of learning and skill acquisition in instrumental performance. These highly skilled manual and cognitive tasks present the ultimate achievement in complex hand dexterity. This paper will review methods of assessing instrumental performance in music, focusing specifically on biomechanical measurement and the associated technical challenges faced when measuring highly dexterous activities

Rate Effects on Timing, Key Velocity, and Finger Kinematics in Piano Performance

We examined the effect of rate on finger kinematics in goal-directed actions of pianists. In addition, we evaluated whether movement kinematics can be treated as an indicator of personal identity. Pianists' finger movements were recorded with a motion capture system while they performed melodies from memory at different rates. Pianists' peak finger heights above the keys preceding keystrokes increased as tempo increased, and were attained about one tone before keypress. These rate effects were not simply due to a strategy to increase key velocity (associated with tone intensity) of the corresponding keystroke. Greater finger heights may compensate via greater tactile feedback for a speed-accuracy tradeoff that underlies the tendency toward larger temporal variability at faster tempi. This would allow pianists to maintain high temporal accuracy when playing at fast rates. In addition, finger velocity and accelerations as pianists' fingers approached keys were sufficiently unique to allow pianists' identification with a neural-network classifier. Classification success was higher in pianists with more extensive musical training. Pianists' movement “signatures” may reflect unique goal-directed movement kinematic patterns, leading to individualistic sound