Researched and Composed by
Jacob
Wilson and Gabriel "Venom" Wilson
Abstract
The purpose of
this paper was to review the control mechanisms which determine the
Specificity between any two tasks. Theoretical rationales covered
include Movement Chaining theories, Perceptual Trace theories, and Motor
Programming Theories. Finally a discussion of the current state of
control theories is introduced.
Introduction
The previous
article discussed theoretical rationales for the underlying elements
responsible for the Specificity of various tasks. However, Specificity
is not only a factor of what elements underlie a task, but also a factor
of the constructs which control the task. While there are numerous
theories addressing the control of human movement, they can be broadly
classified as Movement Chaining theories ( James, 1890, Guthrie, 1935,
Hull, 1943, 1952; Skinner, 1953), Perceptual Trace theories (Koffka,
1935; Adams, 1971), and Motor Programming Theories ( Henry and Rogers,
1960; Keele, 1968; Schmidt, 1975). The purpose of this paper was to
provide the basis of each theory and how it pertains to Specificity.
Movement
Chaining Theories
James (1890)
introduced one of the earliest explanations of learning motor skills,
when he proposed the Response-Chaining hypothesis. Chaining is a
concept in which a stimulus is said to initiate a response. Following,
the response is suggested to serve as the stimulus for a second
response. Early examples of chaining include learning the alphabet. In
this context, saying the word A is thought to stimulate the response of
saying B, and B is thought to serve as a stimulus to trigger the
response of saying C and so on. Each previous response automatically
triggers the next response (Guthrie, 1935). Clearly this is a
Connectionist’s theory, in which learning is thought to occur through
the formation of bonds between stimuli and responses.
S1-R1=S2-R2=S3-R3=S4=R4…
James took this chaining concept of learning and applied it to motor
control. James (1890) suggested that movement was initiated by an
external or internal stimulus leading to a response involving muscular
contractions. An example of a stimulus would be the sound of a gun
going off before the 100 meter dash. This would lead to contraction of
relevant musculature meant to propel the athlete forward. In this
context, the muscular contractions would be sensed by various muscle
receptors and therefore generate afferent feedback which was carried
back to the central nervous system. Not the contraction itself, but the
feedback it produced would serve as a second stimulus which would then
trigger a second set of muscular contractions. This would continue in
an automatic chaining sequence until completion of the movement.
Guthrie (1935) who advocated movement chaining summarizes by stating
that ‘One movement starts another, then a third, the third a fourth and
so on. Our movements form series, very often stereotyped in the form of
habit. These movements and their movement produced stimuli make
possible a far reaching extension of association or conditioning.’
Several important
features need to be delineated. First behavior scientists predominantly
suggested that stimuli literally automatically triggered responses, and
that this process did not require attention (Guthrie, 1935; Skinner,
1953; Thorndike, 1898; Watson and McDougal, 1929). This would explain
why well learned tasks appear to be able to be performed automatically
and without attention. James (1890) posited that previous contractions
ensured that the order of a skill remained stable. In other words
because the responses were chained together it ensured an orderly
sequence each time the movement was executed. A final concept that is
suggested to occur in well learned skills is that the timing between
movements appears to also occur at a stable rate. James proposed that
the latencies (delays) in processing of information were what ensured
the stability of the timing between sequences. To elaborate, the
Stretch Reflex can be analyzed. The stretch reflex is a reflex that
occurs in response to rapid lengthening of a muscle. Information from
the stretch is sent back to the spinal cord, which sends an automatic
command back to the muscle to contract. This process is extremely
stable and occurs in 40-50 milliseconds (see Wilson, 2004 for a more in
depth discussion). In this context, sensorimotor skill acquisition was
comprised of forming bonds between contractile generated afferent
feedback and subsequent triggered responses. Generally behavior
scientists believed that the more a response occurred to a given
stimulus, the stronger the bond became ( i.e. Aristotle’s law of
frequency, Thorndike’s law of practice). In the context of this
Specificity, the movement chaining Hypothesis would propose that
modifications of skilled movements were a function of forming specific
bonds to specific stimuli.
It is important to
clearly realize that this hypothesis is based on feedback mechanisms.
Meaning that feedback from muscular contraction is intimately involved
in control of movement. Early on, Sherrington (1906) provided great
support for this Hypothesis. In an investigation he cut the nerves
responsible for carrying feedback from muscular contractions to a
forelimb of a monkey (deafferentiation). If movement control was indeed
dependent on feedback then the organism would lose the ability to
control movement if it could not receive sensory feedback. After
deafferentiating the animal it ceased to use its forelimb and kept it
tucked against its body for the rest of its life. While this seemed to
support James (1890) theory overwhelmingly, evidence discussed further
on in the article demonstrates that Sherrington’s experiment may not
have truly reflected what the Monkey was actually capable of. For
example, if an individual falls asleep on their arm, causing it to go
numb, they become uncomfortable using it until it has been reoxygenated.
While this is true, the individual still could have moved the limb.
The most recent
theory, with similarity to the Chaining Hypothesis is the Dynamical
Systems Approach to movement control. This approach suggests that it is
an interaction between the internal and external environment of an
organism which causes movement (Kugler et al., 1982; Kelso, 1995). The
approach is also dependent on feedback mechanisms. A further important
concept in learning in the Dynamical Systems approach is a concept known
as degrees of freedom. Bernstein (1967), defined degrees of freedom as
independent states. An independent state of the elbow involves saggital
movements (i.e. flexion / extension), while the shoulder joint contains
three degrees of freedom in saggital, transverse, and frontal planes
(adduction, abduction, flexion, extension, internal and external
rotation). Further, when musculature crossing these joints are included
an almost infinite number of independent states exist. Bernstein (1967)
suggested that learning was not only comprised of associations between
various movements, but the freeing of independent states between limbs.
For example, when an individual is in the early stages of learning to
throw, the limbs appear to freeze up, to limit degrees of freedom. As
practice continues these independent states are freed up, allowing more
precision as well as flexibility.
Perceptual
Trace Theories of Human Movement
Perceptual Trace
theories of human movement have risen out of Cognitive Learning
Psychology. The group of scientists who first popularized the concept
are known as the Gestalt Theorists (Koffka, 1935; Hergenhahn and Olson,
2005; ). They suggested that a current experience gives rise to a
memory process, when it is terminated it gives rise to a memory trace
which remains in the brain. The trace was suggested to influence all
similar processes that occurred in the future. Thereafter similar
experiences result from the interaction between the current experience
and the memory trace. Each time a similar experience occurred it
modified the organism which again influenced future experiences. In
this context the trace becomes more and more influential until it could
dominate how an individual both views and reacts in a given situation.
This was an intricate way to explain how past experiences influenced
future situations. As an Illustration Brewer & Tryens (1981) gave
participants a picture of an office. After removing the picture they
asked them to write down what they saw. The office picture contained
items normally associated with an office such as pencils and paper.
However it also contained items not associated with an office such as a
wine bottle. The participants tended to remember items normally
associated with the office, while not recalling items not associated.
Further, they actually wrote down items which were not in the office
picture such as books. According to Gestalt Theory, this would suggest
that the past memory trace of similar situations in offices dominated
what participants actually saw in the picture, whether it was actually
there or not!
Building off of
the work of the Gestalt Theorists, Adams (1971) proposed the Closed Loop
Theory of motor control. The Closed Loop theory suggests that feedback
from movement generates a perceptual trace which is stored in the
learner. With continued practice several perceptual trace elements are
stored forming a Reference of Correctness, which is a representation of
feedback associated with correct movement. In this context, movement
was controlled by continually comparing feedback to the Reference of
Correctness. An illustration can be found in driving. The Reference of
Correctness would represent visual information associated with staying
within a proper lane, as well as the feedback associated with the
interaction between the car and outside terrain. Visual feedback could
be how the car looks when it is within the lines which designate a
proper lane, while mechanical feedback could be the smoothness of the
road. If feedback matched the reference of correctness than the learner
would continue driving in the same pattern, however if feedback did not
match, then an error signal would be produced causing the learner to
make a correction. For example, if the individual began to dose off and
moved outside of the lane boundaries, an error signal would be produced
causing the individual to straighten the car up. Or the individual may
have veered off slightly causing them to move onto an unpaved part of
the road. The feedback generated from driving over the bumpy terrain
would be carried back to the reference of correctness, which specified a
smooth feeling of driving on a paved road. This would again trigger an
error signal causing the individual to make an adjustment.
The evidence
supporting
Adams model
is fascinating. For example when we initiate a movement, impulses are
carried from our brain in an area called the motor cortex out toward the
relevant musculature. However, Evarts (1973) found evidence that this
same information which was sent via efferent pathways (out toward the
musculature) was also sent to areas in the brain associated with
afferent or sensory information. Schmidt and Lee (1999) suggest that
this was evidence that the sensory system was prepared with a Reference
of Correctness for movement at the same time that the impulses were sent
to the musculature. Other evidence comes from computer tracking and
mechanical models, in which a Reference of Correctness is programmed to
keep the computer simulated or real mechanical model within a type of
tracking task similar to driving (Wickens 1992). In this context, the
model behaves nearly identically to humans! Evidence highly supports
Adams model
for slow tracking tasks. There are several References of Correctness
type mechanisms in the human body. These mechanisms keep temperature,
ph, and hormone levels in line. However, these models have some
limitations, notably in that they rely on feedback, which takes in many
cases too much time to process in order to control fast, or ballistic
movements in nature (Sherwood and Lee, 2003). This is further discussed
in Motor Programming Theory.
The application of
Adams (1971) model to Specificity are clearly outlined in article four
of this series.
Motor
Programming Theories of Motor Control
Motor programming
theories require a clear understanding of the concept of Reaction Time (RT).
Sawyer (2005) defines RT as the interval between the onset of an
unanticipated stimulus and the initiation of a response. RT can be used
to infer that information processing is occurring between the onset of
the stimulus and the time it takes for the person to respond. Posner
(1978) denotes this as the chronometric method of inference. The
chronometric approach was used early on by Donders (1868) who proposed
that RT was comprised of a number of substages. Current research
suggests that three stages exist (Schmidt and Lee, 1999, Sawyer, 2005).
The first is known as the stimulus identification stage, in which the
participant identifies the stimulus. The second stage is denoted
Response Selection stage, in which the individual compares the stimulus
to past experiences, and from those experiences selects out a response
(Sawyer, 2005, Hicks, 1952, Hyman, 1953). Finally, the third stage is
denoted Response Programming, in which most of the work has been done by
Henry and Rogers (1960).
Using the
chronometric method, researchers often investigate the effect of adding
stimuli to the environment on RT. In this context stimulus examinations
can be grossly divided into Simple RT and Choice RT. Henry and Rogers
(1960) suggested that ‘if the situation for a particular response
involves no discrimination as between two or more stimuli, and no choice
(at the time of reaction) between which of two or more movements is to
be made, the RT is simple, regardless of the complexity of the movement
itself.’ As an illustration, participants may be instructed to press
one button when a light turns green. Choice RT can be defined as the
possibility of two or more stimuli being presented to the participant
within an RT paradigm. An example would include a red and a blue button
each corresponding to the flashing of a red or blue light respectively.
Once one of the lights flashes the participant must press the
corresponding button. It has been found that as the number of choices
increases, RT increases (Klapp, 2003). This is known as the Hick’s
(1952) and Hyman’s (1953) Law ( the law is actually mathematical, and
quantitatively describes increases in RT) and is suggested to reflect
the extra time needed to process information in the Response Selection
Stage.
Henry (1960)
summarizes research on RT by suggesting that “ the simplest voluntary
response to a stimulus (simple RT) requires 0.15 sec. under the most
favorable circumstances; 0.20 to 0.25 sec. may be considered more
typical.”
The above
information is critical in the context that both the Chaining Hypothesis
and Closed Loop models of movement control are dependent on feedback.
However most ballistic sports movements are far too fast to be
controlled by feedback mechanisms (Schmidt, 2003, Sherwood and Lee,
2003, Shea and Wulf, 2005). For example a boxing jab can be thrown in
40 ms! However what occurs when a movement is too rapid to be
controlled by higher order correction mechanisms? Enter the Father of
Motor Learning, Franklin Henry. With his mind so akin to breaking old
traditions, as well as introducing completely new concepts to the world
of science he proposed the Memory Drum Theory of Motor Control.
The theory is
currently known as the Motor Programming Theory, and is defined by Henry
and Rogers (1960) as ‘ a rich unconscious store of motor memory
available for the performance of acts of neuromotor skill.’ More
recently Sawyer (2005) posits that the motor program ‘contains the
spatial and temporal elements within an individual, that when initiated
allows for the expression of complex movement behavior or skill.’ This
construct is suggested to be utilized in a feed forward fashion, and is
therefore not reliant on higher order feedback mechanisms.
In this context
Henry (1960) proposed that a complicated movement necessarily involves
more extensive use of learned and stored neuromotor patterns to initiate
the overt motor action. He therefore hypothesized that with richer and
more complicated patterns involved, a longer latent period would be
required to channel existing nervous impulses from brain waves and
general afferent stimuli into the appropriate neuromotor coordination
centers, subcenters, and efferent nerves to cause the desired movement.
In short, the more complex the Motor Program, the longer it will take to
retrieve and initiate it. Henry and Rogers (1960) investigated this
phenomenon in a three condition experiment. Participants in each
condition all began by lifting their finger from a key when a light
flashed from a button in front of them. Condition one consisted solely
of the finger lift. In condition two, the participants lifted their
finger from the key and grasped a tennis ball in front of them, while
condition three involved the finger lift, ball grasp, and an additional
striking of a ball to the right of the participant. Though each
condition began with the same key lift, the reaction time increased as
task complexity increased.
What is important
to understand is that the prediction of increased reaction time to
increased movement complexity ran against the prevailing view at the
time. For example, Paul Fitts (1950), one of the most dominant leaders
in the field, and indeed of all time in exercise science suggested that
‘ the latent time is independent of the rate, extent or direction of the
specific movement required by the stimulus.’ However, it was indeed
found that as movement complexity increased, RT increased, supporting
Henry’s theory!
There are numerous
other lines of evidence. Schmidt (2003) suggests that the most dominant
evidence can be found in limb blocking studies. First however, it needs
to be understood that the Motor Programming theory predicts exactly the
opposite of the Dynamical Systems approach to learning. Programming
theory posits that ballistic tasks are controlled in a feed forward
fashion, where as Dynamical systems approach posits that it is the
interaction between limb dynamics that cause complex movement patterns.
In this context
Wadman et al. (1979) investigated rapid elbow extension movements, while
monitoring electrical activity ( Electromyography or EMG) in the
extensor and flexor musculature. During rapid extension it was found
that EMG increased in the triceps, followed by extension of the elbow.
Presumably to prevent hyperextension, EMG in the biceps increased after
extension. Schmidt (2003) summarizes by stating: ‘people in a cognitive
camp would argue that the motor program was responsible, with these
things being a part of the "script" that runs off when the program is
activated. The "other camp," however, would argue that the dynamics of
the limb's movement and the sensory effects generated by the contracting
muscles are received centrally by the spinal cord and initiate the next
contractions (Feldman, 1986; Kelso, 1995); these patterns aren't
programmed at all but rather emerge from the dynamics.’ An example of
an interaction between limbs can be found in the stretch reflex
phenomenon discussed previously. In this context, rapid elbow extension
could initiate rapid lengthening of the biceps, and therefore increase
their EMG activity.
To examine which
prediction was supported, Wadman et al. (1979) blocked the limbs of
participants on unanticipated trials. In short, the participants
thought they were going to perform the normal action, but instead could
not move as their limbs were blocked. The findings supported the Motor
Programming theory as the EMG tracing remained almost identical! First
the triceps EMG rose, followed by a biceps burst. Schmidt (2003)
summarizes the results by stating that ‘From the dynamical perspective,
this would radically alter the dynamics of the moving limb and, hence,
would be expected to alter the EMG patterning. In fact, if the system
depended on the joint reaching some angular position before the muscles
were switched from agonist to antagonist action, then the muscles would
never be switched if the movement never left the starting position… This
clearly contradicts a dynamical viewpoint in which these patterns
emerged from the limb dynamics. And, these results clearly support a
preprogrammed view in which the script is stored in advance and run off
open-loop, without being affected by the momentary changes in the limb's
dynamics.’
Schmidt further
concludes that ‘my questions to people in the dynamical systems camp
(both in personal conversations and in public presentations) referring
to my interpretations of Wadman et al. (1979) has never yielded a
satisfactory answer about where this patterning arises or why it is not
disrupted when the limb is blocked. To say that it "emerged from the
brain dynamics," as one researcher claimed in response, is just nonsense
to me and seems to be just another vague attempt to prevent any
"retreat" toward admitting that something was stored in advance as
program theory would have it. And, how can a general theory of motor
control be developed without having some way to account for phenomena in
fast movements? If I am wrong, and the dynamical perspective does have
away to account for this, I would certainly love to hear it, but at this
writing I view this evidence as devastating to their view.’
While the limb
blocking evidence is certainly devastating, Sawyer (2005) suggests that
perhaps the most convincing evidence can be found in deafferentiated
studies. As a clear example, Taub and Berman (1968) found that
deafferentiation of monkeys’ forelimbs did not hinder them from
performing complex movement patterns such as climbing and swinging,
which runs contrary to Sherrington’s (1906) findings. This suggests
that Sherrington’s (1906) results were caused by discomfort rather than
ability. Further Deafferentiated studies in both animals and humans
have been replicated with continually similar results (Schmidt and Lee,
1999).
In the context of
specificity Sherwood and Lee (2003) summarize by stating that ‘The core
concept of Henry's view of motor programming was specificity--that motor
learning was specific to a particular skill. As such, individuals with
well developed motor programs might perform that skill well but would
not necessarily perform another skill well, even if it was closely
related. In this context, the idea that motor programs were the
underlying representations of motor skill was specific to the task that
had been practiced.
Schema Theory
of Motor Learning
Building off the
work of Henry (1961) Schmidt (1975) proposed the Schema theory of motor
learning to primarily explain the acquisition of discrete motor skills.
Over the past 30 years the theory has generated much research, being
referenced in over 700 journal articles, and achieving the ‘citation
classic’ award by the Institute for Scientific Information (Sherwood and
Lee, 2003, Shea and Wulf, 2005). There are two important concepts
involved in the theory. The first concerns the acquisition of a
Generalized Motor Program. Like Henry’s Motor Program the GPM contains
the spatial and temporal elements of a task. The difference is that the
program is adaptable to the environment. In this context it contains
invariant features and variant features or parameters. The invariant
features include the order of action, relative force, and relative
timing or phasing. The parameters include absolute force and absolute
duration.
An example would
include an individuals signature. The signature can be written in large
letters or small letters (see Merton, 1972; and Raibert, 1977).
Schmidt’s (1975) theory predicts that the same GPM would be utilized to
write both. To simplify assume that two muscle groups are involved in
writing the signature. When the signature is written in small letters
muscle A elicits 1 unit of force, while muscle B elicits 2 units of
force. However, when the signature is written in large letters muscle A
may utilize 2 units of force, while muscle B elicits 4 units of force.
In this context the parameter known as absolute force has increased.
Note however that the ratio of force remained the same or relative
between both signatures. The same concept occurs to phasing. If muscle
A speeds up, then muscle B speeds up in such a way to keep the ratio
between muscle groups constant. The order of action would concern the
sequence of letters written.
The ‘Schema’ is
the second critical concept of the theory. The term Schema has its
roots in learning psychology, and was first used by Piaget (1926) and
later developed and in large part credited to
Bartlett
(1932, 1958). The Schema can be thought of as a rule, framework or
structure of knowledge about how the world works. Piaget (1926)
suggested that learning occurred through the development and
modification of Schemas. An example is a grasping Schema. Individuals
are thought to have a Schema for ‘things they can grasp with one hand.’
The Schema is based on past experiences of what the individual has
grasped with one hand, and when they come across an object which fits
this Schema they attempt to grasp the object with one hand. If however,
they reach to grasp the object and have miscalculated and cannot grasp
it with one hand, then their Schema is updated with the new information
and the Rule is refined. Therefore the more variations in experience an
individual has the more predictive and useful their schema will be.
Bartlett (1932) developed the theory after he noticed that individuals
remembered events which did not actually occur. In this context the
Schema Theory serves as alternative explanation to the office example
used above that was previously explained by the Gestalt theorists
perceptual trace theory. In this context, individuals are said to have
a rule about things which belong in an office. When participants were
asked about what they saw in the office, their office Schema was aroused
causing them to recall objects which in actuality were not there.
Again, the more experiences the participant has had with offices the
more refined their schema would become.
The idea of a
schema did not have a significant impact on Motor learning research
until Schmidt (1975). He suggested that along with a GMP, individuals
learned two forms of Schemata. The first is known as Recall Schema and
is responsible for ‘scaling’ the program to the environment, while the
second known as Recognition Schema is responsible for error recognition
following completion of a movement. Recall Schema learning is suggested
to be comprised of forming relationships between the initial conditions,
and parameters selected to movement outcomes. This is analogous to
forming a regression line. Parameters would be represented on the Y
axis, while movement outcomes would be presented on the X axis. Each
time a participant performs a skill a data point is added. Therefore
the regression line is continually refined with experience. In this
context, striking a baseball, such that it travels 30 or 60 feet would
require the same General Motor Program. However the Recall Schema would
be utilized to select out differing force parameters.
The Recognition
Schema would act similarly to Adams (1971) reference of correctness;
however, afferent feedback would only be compared to Recognition Schema
after completion of the task. An advanced error detection mechanism is
suggested to inform the participant of his or her errors without
knowledge of results. Examples include the basketball player who
realizes that he or she has made a three point shot after taking it, but
before it has actually reached the basket, and the baseball player who
is informed of a homerun prior to its exit from the park. The
Recognition Schema is formed in a similar manner. The difference is
that the relationship is formed between feedback produced by a movement
and the movement outcome.
Schmidt (1975)
felt that the theory addressed two problems associated with Henry’s
(1960) view of the Motor Program. The first arguable problem is that
Henry proposed a very strict viewpoint, which suggested that each
movement and variation of movement was controlled by a separate Motor
Program. However, Schmidt (1975, 1999, and 2003) suggests that there
are literally an endless combination of variations possible for any
program, causing the need for an equally endless store of motor
programs. The second issue Schmidt (1975) had was the novelty problem,
summed by Bartlett (1932) who suggested that ‘ When I make the stroke
(tennis) I do not, as a matter of fact, produce something absolutely
new, and I never repeat something old.’ Schmidt also uses the example
of a tennis stroke, stating that if an individual makes 50 shots in
tennis, examining the fine detail of the movement it would most likely
be found that no two movements were exactly the same. Further, he
suggests that the ball never has the same velocity, or location. In
this context each stroke could be considered new or novel and that
unless the program for the stroke was innate it should be not be
possible to produce it in such a coordinated fashion.
The Schema Theory
attempts to solve the problem by allowing for variation. By scaling the
program to the environment, both the Storage and Novelty issues are
handled. Schmidt’s approach also has several predictions. For the
purposes of Specificity however, the main predictions this article are
concerned with are those concerning variation. According to the theory,
variation will strengthen the predictive value of the recall Schema.
Shea and Kohl (1991) investigated the effect of variation within a force
requiring task on learning. Three experimental conditions were used.
Condition one squeezed a force transducer with 150 Newtons (N),
condition 2 had the same number of trials with 150 N with additional
practice with +/- 25 N and +/- 5- N. Condition three practiced
additional trials on the criterion task of 150 N to match the number of
trials for condition two, to control for practice effects. Results
indicated that the criterion + variable practice condition performed
better on the 150 Newton retention test than both other conditions that
only practiced the 150 Newton test! This suggests that participants
learned a rule, which was strengthened by the acquisition of more data
points.
Phasing also
appears to have great support (Heuer, 1988, 1991, Heuer & Schmidt,
1988). In one study Shapiro (1977) had participants practice a pattern
of nine wrist twisting movements. After considerable practice
participants were asked to speed the movement to various degrees. It
was found that, though the overall duration of movement decreased, that
the proportion of relative segments of twists remained almost
identical. In terms of relative force a classic study was conduced by
Hollerback (1978). Participants were to write the word ‘Hell’ twice,
with one condition being twice the letter size as the other. It was
found that the size of the letters remained proportional to each other
even though the absolute size had increased. Because, the amplitude of
the letters is a function of the underlying musculature controlling
those letters it is assumed that the relevant muscular contractions
controlling the amplitude also remained proportional.
In terms of
Specificity, the Schema theory suggests that variation is important
quantitatively. For example, in a review on periodized training verses
linear training Wilson and Wilson (2005) found an incredibly large
number of studies which attested to greater gains by varying the weight
and repetition scheme, as opposed to performing the same criterion lift
each workout. This certainly supports the Schema Theory well. Schema
theory still predicts low transfer between two differing tasks however.
A central tenet to
Schema theory is the existence of separate memory states. One which
represents the invariant features of the GPM, and one representing the
Schema which scales the program. This has been studied by looking at
statistical evidence which measures either relative force, timing, or
error associated with the GPM or measures of absolute error in terms of
force, timing, or error associated with parameter learning
(Shea, Wulf
2005). Consistently studies have demonstrated that practice variables
differentially effect the GPM and the ability to scale the GPM,
supporting the two memory state construct.
Current Motor
Programming State
While the Schema
Theory has much experimental evidence, it also contains problems. One
such is that the concept of relative force does not hold in all
conditions. Schmidt summarizes by suggesting that relative force ‘
cannot account for actions involving gravity. One example is walking
normally versus walking with a load, such as a backpack. Here, the
extensor muscles and those involved in the stance phase must operate
differently as a function of the load; however, the flexor muscles and
those involved with the swing phase can operate essentially
independently of the load. Simply scaling all the muscles
proportionately will not accomplish this.’
Another problem
concerns the fact that it appears that while rule learning has
substantial support, that specific practice at criterion parameters also
produces specific learning at those parameters. Young and Schmidt
(1990) investigated the specificity of parameter learning by having
basketball players shoot from numerous distances. The mid distance was
15 feet, which is the free throw line, and is assumed to have been
practiced the greatest number of trials. They then plotted a regression
line, with the point of predicting the proportion of shots made against
the distance the shot was taken at. It was found that while the
regression line could predict the outcome of the other distances, it did
not predict the number of correct trials in the free throw shot, which
had a higher proportion of shots made. This suggests that both rule
learning, and specificity to well practiced parameters are also learned.
In this context,
Sawyer (2005) suggests that the true explanation for how the Motor
Program functions and is structured lies between Henry’s (1960) and
Schmidt’s (1975) theories.
Creation and
Modification of Motor Programs
Another issue
which needs further research concerns how a Motor Program is created and
modified. Originally Henry and Rogers (1960) suggested that originally
without a stored program that an unlearned complex task is carried out
under conscious control in an awkward, step by step, poorly coordinated
manner. However, with continual practice the elements of the program
are stored and eventually take over control. One of the long term
notions in learning Psychology proposed by Bartlett (1932) was that
memory was reconstructive in nature. This means that the elements
forming long term memory had to be recombined before the memory was
represented. Each time it was reconstructed it could be modified by
present experiences. This notion has been supported by several lines of
evidence in Motor learning, leading Wulf and Lee (1993) to propose that
modification of the Motor Program is dependent upon its reconstruction.
Therefore practice should optimize Motor Program reconstruction. This
is covered in the ‘Conditions of Practice’ aspect of this series.
Cognitive
Effort Theory of Motor Program Learning
Recently, Sherwood
and Lee (2003) made a critical review of the Schema Theory. They
suggested that while it explains learning to a great extent in motor
tasks, it is still rooted in a behavioral framework, and does little to
address the cognitive processes which underlie skill acquisition.
It is important to
understand that behavioral scientists were wholly against mentalistic
processes of learning. They suggested that learning occurred
automatically through experience. For example Thorndike (1898)
suggested that learning was incremental and not ‘insightful.’ He
further stated that we should ‘clear our way of one popular explanation,
that learning was due to ‘reasoning ( Thorndike, 1911).’ The father of
Behaviorism, John Watson suggested that consciousness could not be
objectively studied, and therefore should not be studied at all. This
reasoning is found in a quote by Watson and McDougal ( 1929) which
suggests that ‘ the behaviorist cannot find consciousness in the test
tube of his science. He finds no evidence anywhere for a stream of
consciousness…’ Sherwood and Lee (2003) summarize by stating that ‘The
mechanistic approach to motor learning--as increments in response
strength due to movement repetitions--is a remnant of the behaviorist
tradition inconsistent with research that has been conducted in the past
quarter century.’
There are numerous
lines of evidence for cognitive processes in motor learning. For
example, several studies have shown that observational learning can
occur, and that learning can be improved from imagery in motor tasks (Badets
& Blandin, 2004; Black & Wright, 2000; Blandin et al., 1999; Lai, Shea,
& Little, 2000; Shea, Wulf, Park, & Gaunt, 2001 ). In this context,
Lee, Swinnen, & Serrien (1994) propose the Cognitive Effort theory of
motor learning. Cognitive effort is defined as "the mental work
involved in making decisions" (Lee, Swinnen, & Serrien, 1994, p. 329).’
More recently Sherwood and Lee (2003) define it as ‘those decisions that
result in perceptual and motor processes involved in movement control.
For example, an ice hockey goalie needs to learn how to anticipate where
a shot will go to by using perceptual and decision-making processes.’
Because Motor learning requires both Cognitive and Motor processes
(Sawyer, 2005), Sherwood and Lee (2003) suggest that practice must
encourage both the execution of skill described extensively by Schmidt,
as well as the underlying cognitive processes which also underlie the
task. An illustration of this can be found in the development of error
detection mechanisms. Guadagnoli and Kohl (2001), had participants
perform a force replication task in which they were given 100 %
knowledge of results. Knowledge of Results refers to a practice
variable in which participants are told the outcome of a movement upon
its completion. There were two 100 % conditions. The first were given
100 % KR for each trial, while the second condition was first asked to
estimate their error and then given 100 % KR. It was found that the 100
% KR condition with a hypothesized difference had greater performance in
retention than the other 100 % KR condition. The theoretical rationale
is the guidance hypothesis, which suggests that 100 % KR causes
participants to become reliant on KR to make adjustments in their
errors, instead of the underlying cognitive processes, therefore
negating learning effects.
This theory can
easily be incorporated into the reconstructive theory. For example, as
stated Henry proposed that originally tasks were performed consciously.
The current authors posit that perhaps a portion of modifications to
motor programs begin cognitively, before being integrated into
unconscious motor memory. This suggestion is explored further in the
Conditions of practice article.
The Stringing
Theory of Motor Program Construction
Keele suggests
that Motor programs may be generated by stringing together smaller
programmed units of behavior so that eventually this string of behavior
is controllable as a single unit. For example assume there are 9
elements in an entire sequence and these are controlled at first one at
a time each by a separate motor program. With practice the first two
may be linked together, the next three act as another element and the
last four a third. Finally with a greater amount of experience the
entire sequence may be controlled as one program.
Complexity Effect on Response Programming Stage
One
of the more fascinating postulations is that the programming stage
itself can be fractionated into various subcomponents. Klapp (1995,
1996, 2003) of
California Hayward State University suggests that response programming
can be fractionated into an INT and SEQ stages. In the INT ‘ the
internal structure of each chunk is programmed, whereas the other
process, SEQ, relates to the overall sequence of chunks.’ Therefore
stored information is first constructed, recalled, or programmed, then
the information is properly sequenced. Based on Pews (1966) suggestion,
Klapp posits that the structure itself can change with practice.
Briefly, his theory explains the linking theory of motor programming.
It suggests that a number of chunks can be linked together, therefore
lowering RT.
Klapp (1995, 1996, 2003) has examined this through the use of Choice
Reaction Time studies and Simple Reaction Time studies. Briefly, in RT
paradigmns the participant is first readied with a precue stimulus
(denoted initial stimulus). Once the precue stimulus occurs a timer is
turned, and once the time ends the second stimulus, such as a light
occurs, this leads to the response (known as the implicit stimulus).
Task complexity can be increased one of two ways. First, if the
individual is only asked to load one chunk or sequence of information,
RT will be effected by the complexity of the chunk. For example, it is
suggested that motor programs run our speech. In this context, the
greater the number of syllables in a word the greater the complexity of
a chunk (i.e. saying ‘lift’ is less complex than saying ‘Barbell). The
second way to increase complexity is to add sequences or chunks. An
example of this was found in the Henry and
Rogers
(1960) study, in which they added sequences.
It
is positited that INT ( the programming stage) can be separated from the
SEQ ( sequencing stage). In simple RT, the individual already knows
what response to initiate, in this context if there is only onc chunk of
information, then the complexity of that chunk should not effect RT,
because the response is thought to be preloaded. Evidence supports
this, as increasing complexity of a chunk does not increase simple RT!
However in choice RT, the individual does not know what chunk to load
until the implicit stimulus. Evidence supports this as for example
increasing the number of syllables in a word increases choice RT. One
of the phenomenal aspects in regards to sequencing is that the elements
are suggested to be able to be linked together. In experimentation
Klapp had participants perform morris code pressing sequences. It was
found that as the numer of sequences increased from 1 to 4 that simple
RT increased. However, by session 9 the differences had disappeared.
Klapp summarizes by stating ‘The interpretation of that result was that,
whereas the presses were each coded as single chunks initially, an
entire sequence of four presses was recoded into one chunk after
extensive practice According to the analysis of process SEQ, simple RT
depends on the number of chunks. Thus, after extensive practice, simple
RT did not depend on number of presses because both one-press and
four-press responses were composed of one chunk..’
The
implications of this on specificity are huge and will be discussed in
conditions of practice. However, briefly one of the major benefits of
specific practice is the linking together of chunks, deviations from
this are suggested by the current authors to hinder chunking.
Slow Verses
Fast Movement Control Mechanisms
Finally, it should
be noted that it is currently thought that slow and fast movements are
controlled by differing mechanisms. Adams (1971) theory for example
does an excellent job explaining the control of slow tracking movements,
while Henrys open loop mechanism explains the control of fast tracking
movements.
Conclusion
Chaining,
perceptual trace, and programming theories were discussed. Chaining
theories view motor learning as a series of acquired associations
between muscular contraction produced stimuli and automatic responses
leading to a stable movement pattern. The perceptual trace theories
explain slow tracking movements well. In this context it is thought
that practicing a criterion skill generates feedback specific to that
movement, which leads to the formation of a reference of correctness.
Movement is said to be controlled by a chaining of comparisons between
movement generated feedback and the reference of correctness, leading to
no change when movements are correct, and a correction when incorrect
feedback is detected. Programming theories primarily explain tasks
which are ballistic in nature. It is postulated that such movements are
controlled by a rich unconscious store of motor memory. In this
context, practicing a different task requires a different program to
control the task, resulting in little transfer.
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