Kinematic features of continuous hand reaching movements under simple and complex rhythmical constraints
Introduction
Body motion can be described in terms of spatial and temporal features that result from the interaction with the forces in the surroundings. When one feature is modified the other is expected to change accordingly. Such spatiotemporal interaction has been internalized in humans to the extent that it seems to have cognitive, motor and perceptual brain representations (Schubotz et al., 2000). Wertheimer, for example, noted long ago that when two light spots located at a constant distance flash intermittently at a gradually faster rate, the two spots seem to move closer to each other (‘Tau’ effect; Coren et al., 1979). That is, spatiotemporal coupling is more than just a physical fact. It may be regarded as an expression of normal sensorimotor processes.
During discrete hand movements, Kelso et al. (1979) showed that under Fitt’s law paradigm, movement time is roughly constant for both hands moving simultaneously in opposite directions towards equidistant visual targets across obstacles of different heights. In such case, the brain keeps an invariant temporal boundary for the two homologous hands, while each moves along a different path; i.e., speed is adjusted independently for the left and the right hand to meet the specific spatial constraints.
For continuous movements, a clear synchronization was reported between up–down finger movements during simple unconstrained tasks. This synchronization pattern was significantly modified when subjects followed an auditory rhythmical cue (Balasubramaniam et al., 2004). In the same vein, Patel et al. (2005) showed that synchronizing actions to isochronous rhythms (rhythms with constant inter-tone intervals) was easier when people performed finger tapping to a beat. Similarly, this has been reported for the upper limbs during continuous elbow flexion–extension movements (Wiegner and Wierzbicka, 1992), as well as for the lower limbs during locomotion whereas changes in rhythm caused changes in stride length (Thaut et al., 1999a).
Implicitly, temporal cues seem to set boundaries for the control of spatial aspects of movement in healthy people, therefore providing a basis for the use of rhythmical cues in clinical populations as a non-verbal way to convey movement-related information. For example, simple rhythmic isochronous cues had significant effects in guiding movements of people with proprioceptive deficits (LaRue et al., 1995, Stenneken et al., 2006), in patients undergoing motor rehabilitation after a stroke (Thaut et al., 2007, Malcolm et al., 2009) or in Parkinson’s disease (Freedland et al., 2002, Nieuwboer et al., 2007). However, complex rhythmical cues have not been investigated to the same extent.
A main difference between simple and complex rhythms is in their metrical structure. ‘Meter’ is defined as number of pulses between regularly recurring accents (Cooper and Meyer, 1963). Simple rhythms are characterized by an isochronous metric with equally-spaced accents, while non-isochronous metrics are more complex since accentuated beats are non-equally spaced. In general, humans seem to be better tuned to simple rhythms, which are more frequently used.
Simple and complex rhythms differ to such an extent that it has been suggested that each may be represented by different neural substrates in the brain (Sakai et al., 1999). The observation that non-isochronous rhythms are more difficult to follow can in part be attributed to early conditioning. Phillips-Silver and Trainor (2005) showed that seven-month-old babies could differentiate an isochronous duple meter (“March”) from a non-isochronous triple meter (“Waltz”), and had a clear preference for one of them after being swung to either rhythmic meter. This suggests that, to some extent, the association of temporal cues with movement may be based on early experience. Tempo and movement may become so strongly associated that at some stage spatiotemporal integration may seem to be a spontaneous process. It is not known, however, how the different rhythmical components affect the coupling of spatial and temporal aspects of movement.
The goal of this study was therefore to examine the effect of rhythmical constraints on spatial and temporal components of hand movement kinematics under the assumption that spatial and temporal features are processed separately but become integrated later. It is hypothesized that various rhythmical constraints (changes in pace and/or meter) would differently affect the geometrics of movement (hand path) and its temporal evolution (hand speed).
Section snippets
Subjects
Ten right-handed healthy subjects with no history of neurological, cognitive or orthopedic impairment participated in the experiment (7 females and 3 males, mean age = 27.4 ± 3.5 years, age range = 24–34 years). They were required to read an explanation sheet and sign a consent form as required by the institutional ethics review board.
Apparatus
The apparatus consisted of an inverted pendulum with a fixed center of rotation and a handle at its extreme (Fig. 1). This setup enabled free translations and rotations
Results
In total, 808 forward reaching movements were detected during the automatic pre-processing stage. The multivariate outlier analysis showed that 42 cases were outside a 95% probability in all dependent measures. Thus, such cases were eliminated. The remaining 766 movements (duple – 1 Hz: N = 141; triple – 1 Hz: N = 144; duple – 2 Hz: N = 233; triple – 2 Hz: N = 248) were used for the following analyses. Descriptive data are shown in Table 1.
The results of RM-ANOVAs performed on the temporal and spatial
Discussion
This study investigated point-to-point reaching movements to assess the effect of rhythmical constraints (pace and meter) on spatial and temporal kinematic features. Effects of increasing pace on movement performance are generally known (Wiegner and Wierzbicka, 1992, Isenberg and Conrad, 1994) but the influence of meter on motion has not been reported in the literature. This study offers some preliminary insights into the effects of meter on movement under simple and more complex rhythmical
Tal Krasovsky is a PhD candidate in rehabilitation science at the School of Physical and Occupational Therapy at McGill University. She had earned a BSc in Computer Science from Tel-Aviv University in 2004 and an MSc in Physical Therapy (honors) from Tel-Aviv University in 2006. Tal is a recipient of a CIHR (Multidisciplinary Team in Locomotor Rehabilitation) doctoral award. Her primary research interests include normal and disrupted human motor control, locomotor coordination and stability of
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Tal Krasovsky is a PhD candidate in rehabilitation science at the School of Physical and Occupational Therapy at McGill University. She had earned a BSc in Computer Science from Tel-Aviv University in 2004 and an MSc in Physical Therapy (honors) from Tel-Aviv University in 2006. Tal is a recipient of a CIHR (Multidisciplinary Team in Locomotor Rehabilitation) doctoral award. Her primary research interests include normal and disrupted human motor control, locomotor coordination and stability of gait.
Sigal Berman is the Head of the Intelligent Systems Program and a lecturer in the Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer-Sheva. She has a PhD in Industrial Engineering & Management, Ben-Gurion University, and a BSc in Electrical and Computer Engineering, The Technion, Israel. She held a research assistant position at the Center for Autonomous Control Engineering (ACE), Department of Electrical & Computer Engineering, The University of New Mexico and was a post doctoral fellow at the Department of Computer Science & Applied Mathematics, Weizmann Institute of Science, Israel. Her research interests include human motor control, robotics and telerobotics.
Dario G. Liebermann earned a M.Sc. degree in motor control from the School of Kinesiology at the Simon Fraser University, Canada, and his Ph.D. from the Department of Applied Mathematics and Computer Sciences at the Weizmann Institute, Israel. His post-doc work included movement research in clinical neurosciences at the Faculty of Medicine of the University of Calgary, Canada. Since 2000 he is with the Department of Physical Therapy at the Sackler Faculty of Medicine of the Tel Aviv University, Israel, where he lectures undergraduate and graduate level kinesiology, motor learning and control, and investigates the control of arm motion in healthy and clinical populations among several other movement science issues.