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On analysing and interpreting variability in motor output

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Abstract

A recent article in the Journal of Science and Medicine in Sport by Chapman et al.1 reported data from an empirical investigation comparing lower extremity joint motions, joint coordination and muscle recruitment in expert and novice cyclists. 3D kinematic and intramuscular electromyographic (EMG) analyses revealed no differences between expert and novice cyclists for normalised joint angles and velocities of the pelvis, hip, knee and ankle. However, significant differences in the strength of sagittal plane kinematics for hip–ankle and knee–ankle joint couplings were reported, with expert cyclists displaying tighter coupling relationships than novice cyclists. Furthermore, significant differences between expert and novice cyclists for all muscle recruitment parameters, except timing of peak EMG amplitude, were also reported.
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Journal of Science and Medicine in Sport 12 (2009) e2–e3
Letter to the Editor
On analysing and interpreting variability in motor output
A recent article in the Journal of Science and Medicine
in Sport by Chapman et al.1reported data from an empirical
investigation comparing lower extremity joint motions, joint
coordination and muscle recruitment in expert and novice
cyclists. 3D kinematic and intramuscular electromyographic
(EMG) analyses revealed no differences between expert and
novice cyclists for normalised joint angles and velocities of
the pelvis, hip, knee and ankle. However, significant dif-
ferences in the strength of sagittal plane kinematics for
hip–ankle and knee–ankle joint couplings were reported, with
expert cyclists displaying tighter coupling relationships than
novice cyclists. Furthermore, significant differences between
expert and novice cyclists for all muscle recruitment param-
eters, except timing of peak EMG amplitude, were also
reported.
Perhaps the most theoretically interesting finding to
emerge from this study was that novice cyclists exhibited
significantly greater variability in hip–ankle and knee–ankle
joint couplings than expert cyclists. From an information pro-
cessing theoretical perspective, it could be argued that these
results, taken at face value, support the proposition that motor
learning is characterised by progression towards invariance
in motor output2and that movement variability might be a
negative by-product of noise in the central nervous system
that should be minimised or eliminated.3–5 However, from
a dynamical systems theoretical perspective, observed vari-
ability in motor output in both novice and expert cyclists
may not necessarily be a reflection of system noise. As
motor learning from a dynamical systems theoretical perspec-
tive is considered to be the search for stable and functional
states of coordination,6it is possible that the greater variabil-
ity displayed by novice cyclists in the relative motion plots
of Fig. 1(b) of Chapman et al.1may represent exploratory
behaviour as the system attempts to discover stable regions
of the ‘perceptual-motor workspace’ or attractor states7that
subserve the production of functional, possibly optimal, coor-
dination solutions. The much narrower bandwidth of motor
variability exhibited by the expert cyclists could also be con-
sidered functional as it may represent subtle adaptations to
continuously fluctuating constraints on action, or ‘control-
lable chaos’ as Kelso and Ding8described it.
There are a number of theoretical and methodological
issues that need to be considered when attempting to estab-
lish the functionality and role of movement variability in
motor control and learning. First, operational analyses, such
as the one conducted by Chapman et al.,1need to be under-
pinned by a scientifically rigorous theoretical rationale that
should form the basis for hypothesis testing and experi-
mentation. Second, the theoretical framework adopted must
also have the scope to consider alternative interpretations
of motor variability, rather than making the default assump-
tion that it is an artefact of noise in the system.9Third, the
inverse relationship between movement variability and skill
level is not universally supported in the literature with some
studies actually showing reduced variability in less skilled
performers compared to their more highly skilled counter-
parts [e.g., 10,11]. Similarly, the clinical literature has shown
that patients exhibiting injury or disease, in some cases,
exhibit less variability than healthy controls12,13 although
there can be an increase or decrease of variability depending
on the intrinsic dynamics of the system and the constraints
on action.14,15 Finally, the recent introduction of non-linear
measurement tools16 in empirical studies have revealed that
it is the structure, rather than the magnitude, of movement
variability that appears to be of greater significance in under-
standing normal and pathological human perceptual-motor
functioning.17,18
To summarise, it is proposed that observations of motor
variability require careful consideration to establish its func-
tionality and role during goal-directed movement. Clearly,
the default interpretation that movement variability is syn-
onymous with noise is no longer tenable. However, this is not
to say that all motor variability is functional, but rather, that
not all variability is dysfunctional. Empirical research should
be firmly based on a theoretical framework, such as dynami-
cal systems theory, that can underpin hypothesis testing and
experimentation. Importantly, it is the structure, rather than
the magnitude, of variability that is important in uncovering
the functionality of this ubiquitous feature of human motor
behaviour.
1440-2440/$ – see front matter © 2009 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
doi:10.1016/j.jsams.2009.03.010
Letter to the Editor / Journal of Science and Medicine in Sport 12 (2009) e2–e3 e3
References
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Paul S. Glazier
Centre for Sport and Exercise Science, Sheffield Hallam
University, Collegiate Campus, Sheffield, UK
Keith Davids
School of Human Movement Studies, Queensland
University of Technology, Australia
Corresponding author.
E-mail address: paul@longdrivegolf.co.uk (P.S. Glazier)
13 February 2009
... It is proposed that, in becoming skilled, the system consolidates an 'attractor state' ensuring that the movement is performed consistently well while also developing the ability to adapt to changes in the constraints (Davids, Glazier, Araujo, & Bartlett, 2003;Glazier & Davids, 2009a;Seifert, Komar, Araújo, & Davids, 2016). ...
... Indeed, researchers have rejected the historic notion that the presence of variability in the motor patterns of skilled movers reduces the performance level. Rather, variability acts as a functional aid to performance in terms of offering different motor solutions to optimise kinematic patterns (Bartlett, Wheat, & Robins, 2007;Glazier & Davids, 2009a;Langdown, Bridge, & Li, 2012). For example, in the case of a basketball shot, the segmental rotations and positions of the shoulder, elbow, and wrist vary across trials, and yet they interact successfully to optimise the endpoint movement pattern (i.e. the trajectory of the hand: Button, Macleod, Sanders, & Coleman, 2003). ...
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This is an upper-level undergraduate or graduate textbook for courses in human movement and skill acquisition. A professional reference for movement practitioners and scientists, including teachers, coaches, physical educators, physical therapists, rehabilitation specialists, sport scientists, psychologists, biomechanists, and physiologists. The book provides a comprehensive analysis of the evolution of the constraints-led perspective, a recognized theory in motor learning and control. It outlines the development of a conceptual model of coordination and control within a multidisciplinary framework, capturing the various interlocking scales of analysis (e.g., neural, behavioral, psychological) and the many subsystems (e.g., perceptual and movement) involved in producing behavior. A conceptual model of coordination and control is important not just for designing learning environments, but it is also important for ensuring that learners gain positive experiences when acquiring motor skills. Practitioners and students will appreciate the applied focus which outlines a model of human movement with specific constraints-led approach strategies that address skill acquisition across a variety of professions, including teaching, coaching, and rehabilitation. By learning both the theoretical origins and applications for implementing a constraints-led approach to movement skill acquisition, readers will gain insight into how the informed organization of learning and rehabilitation environments produces more effective and efficient use of practice and therapy time. Contents: Traditional theories of skill acquisition -- Physical constraints on coordination : dynamical systems theory -- Informational constraints on coordination : an ecological perspective -- Redefining learning : a constraints-led approach -- Understanding the dynamics of skill acquisition -- Dealing with individual differences : implications for a nonlinear pedagogy -- Organizing practice to optimize learning -- Using verbal guidance as an informational constraint on learners -- Observational learning as directed search -- Implementing the constraints-led approach: case studies.
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