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Friedman, J., & Korman, M. (2012). Kinematic Strategies Underlying Improvement in the Acquisition of a Sequential Finger Task with Self-Generated vs. Cued Repetition Training. PLoS One, 7(12), e52063.
Abstract: Many motor skills, such as typing, consist of articulating simple movements into novel sequences that are executed faster and smoother with practice. Dynamics of re-organization of these movement sequences with multi-session training and its dependence on the amount of self-regulation of pace during training is not yet fully understood. In this study, participants practiced a sequence of key presses. Training sessions consisted of either externally (Cued) or self-initiated (Uncued) training. Long-term improvements in performance speed were mainly due to reducing gaps between finger movements in both groups, but Uncued training induced higher gains. The underlying kinematic strategies producing these changes and the representation of the trained sequence differed significantly across subjects, although net gains in speed were similar. The differences in long-term memory due to the type of training and the variation in strategies between subjects, suggest that the different neural mechanisms may subserve the improvements observed in overall performance.
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Frenkel-Toledo, S., Bentin, S., Perry, A., Liebermann, D. G., & Soroker, N. (2013). Dynamics of the EEG Power in the Frequency and Spatial Domains During Observation and Execution of Manual Movements. Brain Res, 1509, 43–57.
Abstract: Mu suppression is the attenuation of EEG power in the alpha frequency range (8-12Hz) while executing or observing a motor action. Whereas typically observed at central scalp sites, there are diverging reports about the extent of the attenuation over the cortical mantle, its exact frequency range and the specificity of this phenomenon. We investigated the modulation of EEG oscillations in frequency-bands from 4 to 12Hz at frontal, central, parietal and occipital sites during the execution of manual movements and during observation of similar actions from allocentric (i.e., facing the actor) and egocentric (i.e., seeing the actor from behind) viewpoints. Suppression was determined relative to observation of a non-biological movement. Action observation elicited greater suppression in the lower (8-10Hz) compared to the higher mu range (10-12Hz), and greater suppression in the entire 4-12Hz range at frontal and central sites compared to parietal and occipital sites. In addition, suppression tended to be greater during observation of a motor action from allocentric compared to egocentric viewpoints. During execution of movement, suppression of the EEG occurred primarily in the higher alpha range and was absent at occipital sites. In the theta range (4-8Hz), the EEG amplitude was suppressed during action observation and execution. The results suggest a functional distinction between modulation of mu and alpha rhythms, and between the higher and lower ranges of the mu rhythms. The activity of the presumed human mirror neuron system seems primarily evident in the lower mu range and in the theta range.
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Merdler, T., Liebermann, D. G., Levin, M. F., & Berman, S. (2013). Arm-plane representation of shoulder compensation during pointing movements in patients with stroke. J Electromyogr Kinesiol, 23(4), 938–947.
Abstract: Improvements in functional motor activities are often accompanied by motor compensations to overcome persistent motor impairment in the upper limb. Kinematic analysis is used to objectively quantify movement patterns including common motor compensations such as excessive trunk displacement during reaching. However, a common motor compensation to assist reaching, shoulder abduction, is not adequately characterized by current motion analysis approaches. We apply the arm-plane representation that accounts for the co-variation between movements of the whole arm, and investigate its ability to identify and quantify compensatory arm movements in stroke subjects when making forward arm reaches. This method has not been previously applied to the analysis of motion deficits. Sixteen adults with right post-stroke hemiparesis and eight healthy age-matched controls reached in three target directions (14 trials/target; sampling rate: 100Hz). Arm-plane movement was validated against endpoint, joint, and trunk kinematics and compared between groups. In stroke subjects, arm-plane measures were correlated with arm impairment (Fugl-Meyer Assessment) and ability (Box and Blocks) scores and were more sensitive than clinical measures to detect mild motor impairment. Arm-plane motion analysis provides new information about motor compensations involving the co-variation of shoulder and elbow movements that may help to understand the underlying motor deficits in patients with stroke.
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Berman, S., Liebermann, D. G., & McIntyre, J. (2014). Constrained Motion Control on a Hemispherical Surface – Path Planning. J Neurophysiol, 111(5), 954–968.
Abstract: Surface-constrained motion, i.e., motion constraint by a rigid surface, is commonly found in daily activities. The current work investigates the choice of hand paths constrained to a concave hemispherical surface. To gain insight regarding the paths and their relationship with task dynamics, we simulated various control policies. The simulations demonstrated that following a geodesic path is advantageous not only in terms of path length, but also in terms of motor planning and sensitivity to motor command errors. These stem from the fact that the applied forces lie in a single plane (that of the geodesic path itself). To test whether human subjects indeed follow the geodesic, and to see how such motion compares to other paths, we recorded movements in a virtual haptic-visual environment from eleven healthy subjects. The task was comprised of point-to-point motion between targets at two elevations (30 degrees and 60 degrees ). Three typical choices of paths were observed from a frontal plane projection of the paths: circular arcs, straight lines, and arcs close to the geodesic path for each elevation. Based on the measured hand paths, we applied k-means blind separation to divide the subjects into three groups and compared performance indicators. The analysis confirmed that subjects who followed paths closest to the geodesic produced faster and smoother movements, compared to the others. The 'better' performance reflects the dynamical advantages of following the geodesic path, as shown by the simulations, and may also reflect invariant features of the control policies used to produce such a surface-constrained motion.
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Noy, L., Alon, U., & Friedman, J. (2015). Corrective jitter motion shows similar individual frequencies for the arm and the finger. Exp Brain Res, 233(4), 1307–1320.
Abstract: A characteristic of visuomotor tracking of non-regular oscillating stimuli are high-frequency jittery corrective motions, oscillating around the tracked stimuli. However, the properties of these corrective jitter responses are not well understood. For example, does the jitter response show an idiosyncratic signature? What is the relationship between stimuli properties and jitter properties? Is the jitter response similar across effectors with different inertial properties? To answer these questions, we measured participants' jitter frequencies in two tracking tasks in the arm and the finger. Thirty participants tracked the same set of eleven non-regular oscillating stimuli, vertically moving on a screen, once with forward-backward arm movements (holding a tablet stylus) and once with upward-downward index finger movements (with a motion tracker attached). Participants' jitter frequencies and tracking errors varied systematically as a function of stimuli frequency and amplitude. Additionally, there were clear individual differences in average jitter frequencies between participants, ranging from 0.7 to 1.15 Hz, similar to values reported previously. A comparison of individual jitter frequencies in the two tasks showed a strong correlation between participants' jitter frequencies in the finger and the arm, despite the very different inertial properties of the two effectors. This result suggests that the corrective jitter response stems from common neural processes.
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