Motor Behavior: Connecting Mind and Body for Optimal Performance
Chapter 5
Movement Models
Jeffrey C. Ives
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Objectives and Questions
1. What is motor abundance and the degrees of freedom
problem?
2. What is the purpose of movement models?
3. What are open- and closed-loop systems, and what models
fit within these systems?
4. What do the terms generalized motor program, central
pattern generator, schema, reflex model, and internal
model all mean?
5. What are synergies and coordinative structures?
6. What are similarities among old and new models?
7. What are the systems model, constraints, affordances, and
perception–action coupling?
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The Need for Models
• For any given movement, there are numerous ways the
movement could be done.
– This situation is called motor redundancy, which
enables a wide range of options.
– Redundancy also poses a problem in selecting just one
solution, called the degrees of freedom problem.
• Determining what and how the brain and body are trying to
control movement is theorized using models.
• Models provide a “big picture” framework to explain how
the CNS and neuromuscular systems work to make
movement.
Objectives 1, 2
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Models
• Models provide a general framework of the processes and
physiological systems contributing to the formation and
execution of motor acts.
• Movement models serve two main purposes.
– Provide a conceptual framework by which to
understand how movements are formulated and
executed, and this enables prediction of change
following interventions.
– Provide a framework for practical use to devise more
effective programs for rehabilitation, practice, and
training
Objective 2
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Feedforward Versus Feedback Models
• Traditional models of motor control have been broadly
described as open loop or closed loop.
– Closed-loop models explain movement as an outcome of
feedback-initiated reflex actions and prepatterned neural
systems.
• Does not require sophisticated commands from
higher brain centers
– Open-loop models suggest a strict top–down hierarchy
across CNS and neuromuscular structures in planning,
executing, and initiating movement.
• The role of feedback in movement initiation and
execution is minimized.
Objective 3
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Feedforward Versus Feedback Models
(cont.)
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Objective 3
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Contemporary Hierarchical Versus
Heterarchical Models
• Hierarchical
models are
similar to open
loop,
describing a
systematic
command
structure from
top to bottom.
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Objectives 2, 3
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Contemporary Hierarchical Versus
Heterarchical Models (cont.)
•
Heterarchical
models are similar
to closed loop,
describing a
distributed and
balanced
command and
execution system.
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Objectives 2, 3
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Closed-Loop, Feedback-Based, and
Heterarchical Models
• The simplest models of motor control are reflex models.
– Movement stems from chaining together of reflex
actions that provide building blocks of complex
behavior.
– In many animals, basic acts such as chewing,
swallowing, and “fight or flight” actions are initiated by
sensory feedback and executed by reflex movements.
– Reflex models are based on the presence of hardwired
neural circuits and produce fixed movement patterns.
Objectives 3, 4
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Closed-Loop, Feedback-Based, and
Heterarchical Models (cont.)
• Hardwired circuits can also
produce more complex stereotyped
movements through central pattern
generators (CPGs).
• CPGs are built-in movements
initiated by CNS or sensory
systems.
• Because they can run without
complex commands or on sensory
input only, they are considered
closed loop.
Objectives 3, 4
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CPGs in Locust Flying
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Objectives 3, 4
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CPGs in the Spinal Cat
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Objectives 3, 4
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Human Limb CPGs
• Circumstantial
evidence for arm
CPGs suggests each
arm has its own
pattern generator.
• CPGs can be
reinforced by sensory
feedback, though
initiated and driven by
nominal supraspinal
commands.
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Objectives 3, 4
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Human CPGs for Walking
• Mounting evidence
suggests walking CPGs in
humans.
• CPGs may be exploited to
improve walking
performance in
hemiparetic patients.
• Body-weight supported
training is one therapeutic
tool to engage the CPG.
• PBS video moving
memories
Objectives 3, 4
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Complex Heterarchical Models
• Complex closed-loop models include involvement of
higher brain centers but still rely on feedback loops.
• Brain centers provide basic command to the next lower
level, which in turn modifies and “re-commands” the
signals and routes them out to the next lower levels.
– Modification via sensory feedback is essential to fulfill
the command signals at each level.
Objectives 3, 4
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Complex Heterarchical Models
(cont.)
• Theories of what constitutes the motor commands vary.
– Equilibrium point hypothesis suggests the commands
set stretch reflex thresholds.
– Uncontrolled manifold hypothesis posits that the brain
activates series of synergistic muscle actions.
– The brain may only offer “suggestions” to the next
lower levels.
Objectives 3, 4
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Complex Heterarchical Models and
Synergies
• New models often rely on synergistic muscle and limb
actions to simplify the CNS command structure.
– Synergies are ensembles or groupings of muscles and
limbs that work together as a functional unit.
– Actions of limbs or muscles constrain what actions can
happen at other limbs or muscles.
• Synergies involve inherent neural pathways, muscle and
limb biomechanical properties, and learned behaviors.
• Synergistic actions reduce degrees of freedom and
simplifies CNS planning.
Objectives 3, 4, 5
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Synergies and Coordinative Structures
• Synergies among opposite limbs during bilateral movements are called
coordinative structures.
• Synergies in muscle activation and timing are seen in wrist out-ofphase movements transitioning into in-phase movements during rapid
movements.
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Objectives 3, 4, 5
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Synergies and Coordinative Structures
(cont.)
• In this experiment, based on the work of Kelso and
colleagues, asymmetric movements assimilated the
timing of one another such that each arm arrived at the
target at the same time.
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Objectives 3, 4, 5
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Synergies and Coordinative Structures
(cont.)
• The experiment
demonstrated here
shows coupling among
arms and legs.
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Objectives 3, 4, 5
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Summary of Heterarchical Models and
the Need for Hierarchical Control
• There is evidence for distributed control of motor actions
from the CNS to peripheral systems such as CPGs and
synergies.
– Yet, heterarchical models do not explain nuances that
influence movement execution.
– Heterarchical models cannot easily explain the widely
distributed and highly complex actions of the brain that
accompany movement.
• Thus, the need for a centralized command system arising
out of brain structures: hierarchical control
Objectives 3, 4, 5
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Open-Loop and Hierarchical Models
• Hierarchical models suggest that motor skills arise from
comprehensive sets of CNS commands.
– Movements are considered centrally preprogrammed.
– Precise manipulation of movement characteristics
comes from a continually involved CNS controller.
• Feedback from sensory systems comes back into the
brain centers but is largely used to prepare or modify the
next movement.
• The initiation of movement is purely open loop because
there has been no preceding movement to provide
feedback.
Objectives 3, 4
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The Schema Theory
• The most long-standing hierarchical model is the schema
theory.
• Schema theory posits a generalized motor program
(GMP) and schemas.
– GMPs are a general representation of various motor
actions, or a class of actions.
– The schemas are separate memory components in
which movements are recognized and recalled,
essentially the decision-making and learning processes
for the GMP.
Objectives 3, 4
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The Schema Theory (cont.)
• Stored in the GMP and schemata are
invariant characteristics and
parameters.
– Invariant characteristics are
features of the GMP that do not
change, for example, relative
force, relative timing, and
sequencing.
– Parameters are features that
change within the GMP, for
example, overall force, overall
duration, and specific muscles.
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Objectives 3, 4
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Schema Theory Evidence
• Blocked
movement shows
similar movement
pattern as normal
movement.
• Suggests
preprogrammed
neural
commands not
influenced by
feedback
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Objectives 3, 4
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Schema Theory Evidence (cont.)
• Other evidence for motor programs is found in bimanual
transfer, for example, left and right handwriting similarities.
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Objectives 3, 4
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The Rise of Internal Models
• Schema theory criticized for:
– Implausibility of the brain being able to store so much
information
– GMPs do not explain how entirely novel movements
are created.
– GMPs rely on an executive controller making neverending rapid fire decisions.
– The concept of movement invariant characteristics may
not be so invariant.
• Newer hierarchical models center on internal models.
Objectives 3, 4
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Internal Hierarchical Models
• Internal model emphasize that the brain sends commands
to the PNS and itself through efference copy.
– Efference copy includes the movement plan and a
prediction of the sensory outcome.
– Planning and initiation of the motor command are
based on prediction of outcomes.
– Differences between the actual movement feedback
and the predicted feedback are used to refine
subsequent motor commands.
– Motor commands are thus based on understanding the
relationship between the original motor commands and
the actual output.
Objectives 3, 4
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Internal Model Schematic
• This forward internal
model shows the
planner (P)
somewhere in the
cortex sends a plan
to the controller (CT)
in the motor cortex.
• Plans are sent to the
to the controlled
object (CO), for
example, spinal
interneurons or motor
units.
Objectives 3, 4
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Internal Model Schematic (cont.)
• Efference copy goes to
the forward model (FM)
comparator, where it is
compared to sensory
feedback (FB).
– Difference relayed
back to the controller
• Visual cortex (VC)
information is relayed to
the controller.
• Plans are revised based
on comparator
differences.
Objectives 3, 4
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Model Consensus Points
• All the models find consensus on three points:
– The nervous system is most concerned with
movement outcomes or effects than specific muscle
actions.
– The nervous system must take into account
psychological, physiological, and biomechanical
properties of the body, the movement goals, and the
environmental context.
– There exists hardwired, preformed, and synergistic
movements that form building blocks for more complex
movements.
Objectives 3, 4, 6
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The Systems Model and Approach
• The systems model describes the production of skilled
movement as a natural outcome of the person interacting
with the environment.
– Task goals and characteristics of the individual interact
with the characteristics of the environment.
– Task requirements and the environmental context
cannot be separated from movement planning,
initiating, and executing.
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Objective 7
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The Systems Model and Approach
(cont.)
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Objective 7
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The Systems Model and Approach
(cont.)
• The individual, the task, and the environment are systems
that interact and each of these systems contain multiple
subsystems that also interact.
– Systems are assemblies or groups of components that
together have certain features or characteristics that
are task specific.
– The dynamic interplay among these systems identifies
them as dynamic systems.
Objective 7
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Systems Model and Constraints
• The features and characteristics of systems impose
constraints to movement.
– A constraint is a barrier or restriction that must be
used, avoided, or overcome for effective movement to
take place.
• Constraints may be task, environmental, or individual.
– Task constraints and environmental constraints are
considered external.
– Environmental constraints may be regulatory or
nonregulatory and physical or sociocultural.
– Individual systems produce internal constraints.
Objective 7
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Behavior of Biological Systems
• Dynamic systems, working as individual units and
interacting with other systems, have self-organizing
properties.
– The system tries to maintain a stable and patterned
state of operation, called an attractor state.
– The stable state is resistant to change but does
naturally fluctuate within the stable state.
– If knocked out of the stable state, the system will try
and find a new stable (attractor) state given the new set
of circumstances and dynamic properties.
Objective 7
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Behavior of Biological Systems
(cont.)
• Changing from one stable state to another is called a
transition phase.
– Example: Walking to running demonstrates that high
speeds or workloads destabilize the stable walking
pattern and forces a transition to running
– Speed is a control parameter, which are those factors
that when they change may cause a wholesale change
throughout the entire system.
– The rest of the system components that follow suit are
called order parameters.
• Coordination, gait repatterning, and vertical center of
mass movement are order parameters.
Objective 7
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Transitions in Dynamic Systems
• The walk to run
transition is marked by
changes in limb
velocity as a control
parameter.
• Characteristics such
as range of motion,
“flight phase,” and
center of mass
movement are order
parameters.
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Objective 7
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Destabilizing Dynamic Systems
• It is often necessary to destabilize the system in order to
promote better functioning at a new stable state.
– Example: Strength training aims to cause tissue
breakdown to promote new tissue growth.
• Destabilization does not always have positive outcomes.
– Changing one variable, even for the “better,” may have
a minimal impact on overall performance.
– Sometimes, such as in overtraining syndrome, the
system adapts to a poorly functioning stable state.
Objective 7
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Stabilizing Dynamic Systems with
Perception–Action Coupling
• Constraint-based information from the environment
continually merges with internal sensory information.
– Given a task, the system wants to find a stable
movement solution.
• Perceptual systems determine ways to take constraints
into account for movement planning and execution.
– This process is known as searching for affordances.
– Affordances link what is perceived and what action
may take place; a process termed perception–action
coupling.
Objective 7
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Perception–Action Coupling
• Perception–action
coupling makes precise
motor programs
unnecessary.
• Planning and action
information are part of the
environment and revealed
when interacting with the
environment.
• Consider the wall-climbing
actions afforded each
person in the picture.
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Objective 7
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Perception–Action Coupling (cont.)
•
•
This experimental setup could change the virtual reality
hallway “speed” to match or mismatch treadmill speed.
– Resulted in optic flow perceived by the person that he
were walking faster or slower than in reality.
Mismatched virtual reality hallway speed caused the person
to walk faster or slower to match the environment.
– Clear example of perception–action coupling
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Objective 7
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Perception–Action Coupling (cont.)
Permission from Mohler et al. (2007)
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Objective 7
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Applying the Systems Approach
• The systems approach provides a framework from which
to address movement-related problems.
– How individuals interact within the environment with
their own constraints and capabilities leads to
individual-specific assessments and interventions.
– Understanding environmental constraints enables the
practitioner to bring those situation-specific constraints
into the practice and training environment.
Objective 7
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Summary
• The benefit of motor abundance also brings on the
problem of degrees of freedom.
– Movement models attempt to explain the overarching
planning, initiation, and execution process.
• Models fall into open- (hierarchical) and closed-loop
(heterarchical) systems.
– Hierarchical models include the schema theory and
internal models.
– Heterarchical models range from reflex models to
dynamic systems.
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Summary (cont.)
• The systems theory and approach views movement from
the perspective of what factors influence movement
production.
– Involves dynamic systems interacting, including
individual, task, and environmental systems
– Dynamic systems include synergies and other
interacting components that set constraints upon one
another.
• Interactions among the human operator and the task and
the environment are worked out based on the ideas of
constraints, affordances, and perception–action coupling.
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