Which of the following theories attempts to describe how motor skills develop and are coordinated

We can classify theories of how the nervous system controls coordinated movement in terms of the relative importance given to movement instructions specified by central components of the control system or by information arising from interactions among the performer, the task, and the environment. Theories that give prominence to movement instructions specified by the central nervous system in the control process have in common some form of memory representation, such as a motor program, that provides the basis for organizing, initiating, and carrying out intended actions. We will discuss a motor program–based theory as an example of this type of theory. In contrast, other theories give more influence to information specified by the environment and to the dynamic interaction of this information with information from the task and the body, limbs, and nervous system. We will discuss the dynamical systems theory as an example of this type of theory.

Motor Program–Based Theory

At the heart of central control–oriented theories is the motor program, a memory-based construct that controls coordinated movement. Various theoretical viewpoints attribute different degrees of control to the motor program. Undoubtedly, the view that best characterizes present-day thinking about the motor program comes from the work of Richard Schmidt (1988, 2003; Schmidt & Lee, 2011). In his "schema theory," Schmidt (1975) proposed that a serious problem with previous views was that they limited the motor program to controlling specific movements or sequences of movements. To overcome this limitation, Schmidt hypothesized the generalized motor program (GMP) as a mechanism that could account for the adaptive and flexible qualities of human coordinated-movement behavior.

Schmidt's generalized motor program. Schmidt proposed that a GMP controls a class of actions, rather than specific movements or sequences. He defined a class of actions as a set of different actions having a common but unique set of features. For Schmidt, these features, which he called invariant features, are the "signature" of a GMP and form the basis of what is stored in memory. These movement-related features form the basis of what Schmidt (2003) referred to as the fundamental pattern of the class of actions. These features remain consistent from one performance of an action to another. In order for a person to produce a specific action to meet the demands of a performance situation, the person must retrieve the appropriate program from memory and then add movement-specific parameters. These are movement-related features of the performances of an action that can be varied from one performance to another.

An analogy that can help you understand the distinction between invariant features and parameters of a GMP is the distinction between rhythm and tempo in music and dance. A piece of music has a rhythmic structure that is specified by the time signature, or meter, which is indicated on the written music score, such as 3/4 or 4/4. The first number (which would be the top number on the music score) indicates the number of beats with equal proportions of time intervals per measure of music. This number establishes the music's rhythmic structure. The second, or bottom, number specifies which type of note receives one beat, which in the case of the two examples would be the quarter note—that is, the 1/4 note. For the 3/4 meter there are three beats with equal proportions of time intervals in every measure (i.e., the equivalent of three quarter notes in each measure); for the 4/4 there are four beats to every measure. In dance, a waltz, for example, has a 3/4 meter, which means it has three beats to every measure and gives it its familiar 1-2-3 sequence of steps. Note, however, that for the waltz, the three beats are not of equal length; the first is long, the second and third are shorter but equal in time. Tempo refers to the speed at which the music is performed. The same rhythmic structure can be played slowly or fast. You can try this by clapping your hands with one clap for each beat. Try a consistent series of three claps with equal proportions of time intervals between claps, which establishes the rhythmic structure of your clapping. Then clap the same way but faster. Notice that the rhythmic structure doesn't change even though you increase the speed of the clapping. In this analogy, rhythm in music is analogous to an invariant feature of the GMP; tempo is analogous to a parameter.

Invariant features and parameters. Although many possible characteristics could be invariant features of the GMP, one that Schmidt (2003) considered to be the most likely is the relative time (which is analogous to rhythm in music) of the components of the skill. Another is the order, or sequence, of the components. The term relative in relative time indicates that what is invariant are the percentages, or proportions, of the overall duration, or movement time of the components of a skill.

motor program a memory representation that stores information needed to perform an action.

generalized motor program (GMP) the memory representation of a class of actions that share common invariant characteristics; it provides the basis for controlling a specific action within the class of actions.

invariant features a unique set of characteristics that defines a GMP and does not vary from one performance of the action to another.

parameters features of the GMP that can be varied from one performance of a skill to another; the features of a skill that must be added to the invariant features of a GMP before a person can perform a skill to meet the specific movement demands of a situation.

relative time the proportion, or percentage, of the total amount of time required by each component of a skill during the performance of that skill.

Which of the following theories attempts to describe how motor skills develop and are coordinated
A CLOSER LOOK Defining the Motor Program: A Memory Representation versus a Plan of Action Prepared Just Prior to Moving

A problem that has arisen over the years has led to difficulties in understanding what the motor program is and how it functions. The problem is that the term motor program has been used to describe different functional constructs. In some discussions, the motor program refers to the memory representation of a movement or action. The generalized motor program (GMP) construct in Schmidt's schema theory is a good example. The theoretical arguments about the memory-representation type of motor program focus on which characteristics of a movement or action are stored in memory as a part of the motor program. We use the term this way in the present chapter.

The other use of the term motor program refers to what is constructed or prepared just prior to movement initiation, but following an intention to act. This use of the term, sometimes referred to as motor programming, is the focus of chapter 8, although we do make some reference to this preparation aspect of motor program–based control in the present chapter.

Figure 5.4 presents an illustration of how to interpret the concept of invariant relative time. Suppose you move the index finger of your hand as quickly as possible to press five keys on a keyboard in sequence. Now, suppose that the four components of this task (the time intervals between the keys: keys 1-2, 2-3, 3-4, 4-5) yield the following movement time (MT) proportions: component 1 takes up 30 percent of the total MT (component % = component MT/total MT); component 2, 20 percent; component 3, 40 percent; and component 4, 10 percent. If the performance of this skill under typical conditions has an overall duration of 10 sec [represented in part (a) of the figure], then regardless of how much you speed up or slow down this overall duration, the actual amount of movement time for each component changes proportionately. In figure 5.4, parts (b) and (c) represent this proportional component change for speeding up the skill [part (b)] and slowing it down [part (c)]. Thus, if you typically perform this skill in 10 sec, then the amount of time you spend performing each component is 3, 2, 4, and 1 sec, respectively. If you performed the skill twice as fast, in 5 sec, then each component would change proportionately to be 1.5, 1, 2, and 0.5 sec, respectively. If you slowed down your overall movement time to 15 sec, then each component would change to 4.5, 3, 6, and 1.5 sec, respectively.

FIGURE 5.4

An illustration of invariant relative time for a hypothetical four-component motor skill when it is performed normally at a 10 sec duration (a), speeded up to a 5 sec duration (b), and slowed down to a 15 sec duration (c).

Which of the following theories attempts to describe how motor skills develop and are coordinated

Although motor program theory proposes that the invariant features of a GMP are rather fixed from one performance of a skill to another, it also holds that there are other features, called parameters, that can be varied. Examples include the overall duration and the muscles used to perform the skill. Skilled performers can easily change these from one performance situation to another, readily adapting them to the specific requirements of each situation.

The following two examples illustrate the relationship between invariant features and parameters. One relates to figure 5.4, which, as just discussed, portrays relative time as an invariant feature. This figure also illustrates the parameter of overall duration. The normal, faster, and slower speeds in the figure show that a person can change the overall amount of time taken to move without altering the relative time structure of the components of the movement. This type of situation occurs, for example, when a person walks faster or slower than his or her typical speed.

The second example concerns muscles as parameters. Research evidence shows that whether you sign your name with a pen held in your preferred hand, in the opposite hand, between your toes, or with your teeth, the two signatures have distinct invariant spatial as well as relative time features (see Wright, 1990 for an excellent review of this research). These results suggest that you can change the muscles involved in writing your signature without altering the invariant features represented in the generalized motor program. Interestingly, Rijntjes et al. (1999) provided neurological evidence for muscles as a movement parameter related to the signing of one's name by comparing brain regions activated by people signing their name with the finger of the preferred hand and with the big toe. Additional evidence and examples of muscles as parameters will be discussed in chapter 13, when we consider the topic of bilateral transfer.

Schmidt's schema theory. A formalized theory of how the GMP operates to control coordinated movement is Schmidt's schema theory (Schmidt, 1975, 1988, 2003). A schema is a rule or set of rules that serves to provide the basis for a decision. It is developed by abstracting important pieces of information from related experiences and combining them into a type of rule. For example, your concept of dog is the result of seeing many different types of dogs and developing a set of rules that will allow you to identify correctly as a "dog" an animal you have never seen before.

schema a rule or set of rules that serves to provide the basis for a decision; in Schmidt's schema theory, an abstract representation of rules governing movement.

Schmidt used the schema concept to describe two control components involved in the learning and control of skills. Both are characterized as based on abstract rules. The first is the GMP, which, as just described, is the control mechanism responsible for controlling the movement coordination patterns of classes of actions, such as throwing, kicking, walking, and running. The second component is the motor response schema, which is responsible for providing the specific rules governing the performance of a skill in a given situation. Thus, the motor response schema provides parameters to the GMP.

The schema theory provides an explanation for how well a person can adapt to new situations or environmental contexts. People can successfully perform a skill requiring movements that have not been made in that same way before. For example, when you walk in a crowded mall or return a tennis serve, characteristics of the situation change in ways that you have not previously experienced. It is possible to perform the skill successfully in these situations because you can use the rules from the motor response schema to generate appropriate parameter characteristics; you add these to the GMP to perform the skill.

Schmidt's schema theory claims to solve the degrees of freedom problem in movement coordination through an executive control operation that organizes motor programs and schemas. An important emphasis in this approach is the abstract, or general, nature of what is stored in the control center. The GMP and motor response schema work together to provide the specific movement characteristics needed to initiate an action in a given situation. The action initiation is an open-loop control process. However, once movement is initiated, feedback can influence its course if there is sufficient time to process the feedback and alter the movement in progress.

Testing the invariant relative time feature. Researchers have attempted to provide empirical support for motor program–based control by investigating Schmidt's claim that a generalized motor program controls a class of actions defined by specific invariant features. Of the proposed invariant features, relative time has generated the most research interest. Support for the invariance of this feature has come from many experiments investigating several different skills, such as typing, gait, handwriting, prehension, and sequences of key presses, among others. (For reviews of this evidence, see Heuer, 1991; Schmidt, 1985, 1988, 2003; Shea & Wulf, 2005.)

Researchers typically have investigated relative time invariance by observing changes in relative time across a range of values of an associated parameter, such as overall duration or speed. The most commonly cited research example in this regard is a study by Shapiro, Zernicke, Gregor, and Diestel (1981) in which people walked and ran at different speeds on a treadmill. The researchers were interested in the percentages of the total step cycle time (i.e., relative time) that would characterize the four components, or phases, of the step cycle at each treadmill speed (i.e., the overall duration parameter). Their hypothesis was that if relative time is invariant for the generalized motor program involved in controlling walking and/or running gait patterns, then the percentages for a specific gait component should remain constant across the different speeds.

The results were consistent with the hypothesis of relative time invariance (see figure 5.5). As gait sped up or slowed down (at least up to 6 km/hr and beyond 8 km/hr), the percentage of time accounted for by each step cycle component remained essentially the same for different speeds. The differences between the relative time characteristics of walking and running are especially notable in the pie charts in the (b) section of figure 5.5. The pie charts show the relative time percentages for the average of the walking speeds and the running speeds for each of the four step cycle phases. Because the relative time percentages differed between walking and running, the authors concluded that two different motor programs control walking and running gaits. Within each gait pattern, the overall duration (i.e., speed) parameter could be increased or slowed down while the relative timing among the components of the step cycle was maintained.

FIGURE 5.5

Results of the experiment by Shapiro et al. (a) The relative time percentage of total step cycle time for each of the four step cycle phases (Phillipson step cycle) at different speeds of walking and running. F = Flexion phase (from toeoff to beginning of knee extension); E1 = Extension phase 1 (from beginning of knee extension to heelstrike); E2 = Extension phase 2 (from heelstrike to maximum knee-angle flexion); E3 = Extension phase 3 (from maximum knee-angle flexion to toeoff). (b) The average (of the four speeds) relative time percentages of total step cycle time for each of the four step cycle phases for walking and running. [From Shapiro, D. C. et al. (1981). Evidence for generalized motor programs using gait pattern analysis. Journal of Motor Behavior, 13, 33–47. Copyright © 1981 Heldref Publication, Inc. Washington, DC.]

Which of the following theories attempts to describe how motor skills develop and are coordinated

Which of the following theories attempts to describe how motor skills develop and are coordinated
A CLOSER LOOK Two Views about the Source of Relative Time Invariance

Relative time invariance is a common component of both the generalized motor program and dynamical systems views of motor control. However, one of the important differences between these views is the source of the invariance.

  • The generalized motor program view emphasizes that relative time, as an invariant feature of the GMP, is included in the movement commands sent to the musculature. Because of this, the resulting set of movements that comprise an action is obligated to perform according to this time constraint. Relative time invariance across variations of a parameter is an indicator of a class of movements that are controlled by the same GMP.

  • The dynamical systems view prefers to use the term "temporal pattern" rather than relative time invariance. Although different with respect to some specific characteristics, temporal pattern is an analogous concept to relative time invariance. More important, the invariance seen in relative time for many actions is an emergent characteristic, which is the result of the person interacting with characteristics of the task and/or environment, or the mechanical dynamics involved in the body and limb movements. Relative time invariance across variations of a control parameter is an indicator of coordination pattern stability.

Dynamical Systems Theory

In sharp contrast to the motor program–based theory of motor control is an approach commonly referred to as dynamical systems theory (sometimes referred to as dynamic pattern theory, coordination dynamics theory, ecological theory, and action theory). The basis for this theoretical viewpoint is a multidisciplinary perspective involving physics, biology, chemistry, and mathematics. Proponents of this theory see human movement control as a complex system that behaves in ways similar to those of any complex biological or physical system. As a complex system, human motor control is seen from the perspective of nonlinear dynamics; this means that behavioral changes over time do not follow a continuous, linear progression, but make sudden abrupt changes. For example, in the physical world, when the temperature of water is increased gradually there is a specific temperature (100°C) at which the water boils; its behavior abruptly changes. This type of change represents a nonlinear behavior.

Those who study dynamical systems theory are particularly interested in how a system changes over time from one stable state to another because of the influence of a particular variable. In addition, they are interested in identifying physical and mathematical laws that govern such behavior. Although this approach has been used to model many complex systems in the physical world (see Gleick, 1987), only since the 1980s has it captured the attention of scientists interested in understanding and explaining human movement control.

Nonlinear changes in movement behavior. A series of experiments by Scott Kelso and his colleagues established for movement scientists that a systematic change in the level of one variable can cause a nonlinear behavioral change in human coordinated movement (e.g., Kelso, 1984; Kelso & Scholz, 1985). In these experiments participants began moving their right and left index fingers at a specified rate of speed in one stable coordination state, or pattern, described as an antiphase relationship (sometimes referred to as an out-of-phase relationship). This means that the muscle groups controlling the right and left fingers were operating simultaneously but in opposite ways: when the right finger was flexed, the left finger was extended, similar to the motion of windshield wipers in some vehicles. Quantitatively, the fingers were 180° out of phase with each other throughout the movement cycle. The participants systematically increased the speed of their finger movements by keeping their finger speed consistent with that of a metronome controlled by the experimenters. The result was that at a specific speed the finger movements spontaneously shifted to a second stable coordination state, or pattern, described as an in-phase relationship between the two fingers, where both were flexed or extended at the same time (i.e., 0 or 360° in phase with each other).

You can experience this spontaneous, nonlinear coordination change yourself by making two fists with your hands and putting them on your desk or tabletop so that the little finger side of your fist rests on the desktop. Extend your two index fingers so that they face forward. Then begin to move them side-to-side (keep them parallel to the desktop) in the same way that was done in the Kelso experiment.

The shift to the in-phase coordination state occurred during the transition between the stable antiphase and in-phase states. The transition was a mixture of both antiphase and in-phase coordination patterns. But at slower speeds, only an antiphase pattern occurred, whereas at faster speeds, only an in-phase pattern occurred. Thus, a linear increase in movement speed led to a nonlinear change in the fundamental coordination pattern of movement between the two index fingers.

When viewed from the perspective of coordination patterns, these experiments established that distinct coordination patterns can spontaneously develop as a function of a change in one specific variable; which in this case was movement speed. In the finger-movement task used in the Kelso experiments, the antiphase and in-phase finger-movement relationships represent stable coordination patterns. The importance of these experiments is that they provided an initial step in the investigation of coordination changes that can occur without resorting to a mechanism such as a motor program to specify movement characteristics for each coordination pattern.

These spontaneous coordination pattern changes are not limited to laboratory tasks. They also have been found for motor skills involved in sports and daily activities. For example, front-crawl strokes in swimming exhibit spontaneous arm coordination pattern changes at a specific swimming speed (Seifert, Chollet, & Bardy, 2004; Seifert et al., 2015). Another example is the change from a walking to a running coordination pattern that spontaneously occurs at a specific speed. The experiment by Shapiro et al. (1981), which was discussed earlier in this chapter, was an early demonstration of this spontaneous gait pattern change. Since that experiment, the walk-to-run and, conversely, the run-to-walk gait changes that occur as a function of speed have been demonstrated numerous times and have become the basis for an increasing amount of research (e.g., Abdolvahab & Carello, 2015; Diedrich & Warren, 1995, 1998; Farinatti & Monteiro, 2010; Wagenaar & van Emmerik, 1994). We will discuss this spontaneous gait change phenomenon in more detail in chapter 7.

Stability and Attractors

At the heart of the dynamical systems view is the concept of stability. In dynamic terms, stability refers to the behavioral steady state of a system. It is important to note that this use of this term is different from the concept of invariance. As used here, stability incorporates the notion of variability by noting that when a system is slightly perturbed, it will return spontaneously to a stable state.

dynamical systems theory an approach to describing and explaining the control of coordinated movement that emphasizes the role of information in the environment and the dynamic properties of the body and limbs; it is also known as the dynamic pattern theory.

nonlinear behavior a behavior that changes in abrupt, nonlinear ways in response to systematic linear increases in the value of a specific variable (e.g., the change from smooth to turbulent water flow in a tube at a specific increase in water velocity; the change from a walking to a running gait at a specific increase in gait velocity).

stability a behavioral steady state of a system that represents a preferred behavioral state and incorporates the notion of invariance by noting that a stable system will spontaneously return to a stable state after it is slightly perturbed.

Which of the following theories attempts to describe how motor skills develop and are coordinated
A CLOSER LOOK Spontaneous Coordination Pattern Changes due to Speed in the Front-Crawl Strokes of Elite Swimmers

A change in the arm coordination pattern of the front-crawl stroke in swimming is a sports skill example of the type of spontaneous coordination pattern development originally reported by Kelso (1984) for the finger-movement task. In an experiment in France by Seifert, Chollet, and Bardy (2004), fourteen elite male sprint swimmers performed eight swim trials at a specified distance. The trials began at a speed that was similar to the pace for a 3,000 m distance. On succeeding trials swimmers were required to increase their speed by a specified amount, which was based on paces that would be used for 1,500, 800, 400, 200, 100, and 50 m; the eighth trial was at the swimmers' maximum speed. Arm coordination was quantified for each trial. The analysis of arm coordination revealed two distinct coordination patterns: a catch-up pattern, in which there was a lag time between the propulsive phases of each arm, and a relative opposition pattern, in which the propulsive phase of one arm ended when the propulsive phase of the other arm began. Analysis of the arm strokes showed that all the swimmers used a catch-up pattern during the first trial. But as they increased their swimming speeds on successive trials, there was a critical speed at which they all began to use a relative opposition pattern for their arm strokes.

By observing characteristics of a stable state, scientists can gain understanding of the variables that influence a system to behave as it does. For example, in the reciprocal rhythmic finger movements in the Kelso experiment just described, the researchers observed behavioral stability when the fingers were in antiphase and in-phase relationships with each other. These two stable states indicate two patterns of coordinated movement. Between these states, as finger speed increased, a phase transition occurred during which instability characterized the behavioral patterns. The instability continued until finger speed reached a point at which a new stable state spontaneously occurred.

The stable behavioral steady states of systems are known as attractors (or attractor states). In terms of human coordinated movement, attractors are preferred behavioral states, such as the in-phase and antiphase states for rhythmic finger movements in the Kelso experiment. Attractors represent stable regions of operation around which behavior typically occurs when a system is allowed to operate in its preferred manner.

Consider two examples of the presence of attractors for common motor skills. When people locomote at a speed of 3 mi/hr (i.e., 4.8 km/hr), the arms and legs are "attracted to" a coordination relationship that produces a walking gait. This gait pattern represents the preferred behavioral state for engaging in a locomotion action at this particular speed. But when people locomote at a speed of 10 mi/hr (16 km/hr), the walking gait is not the preferred locomotion state. At this speed, most people run, which, as you saw in figure 5.5, involves a coordination pattern that is different from a walking gait pattern.

The second example is postural coordination patterns. According to Bardy and his colleagues (e.g., Bardy, Ouiller, Lagarde, & Stoffregen, 2007) there are two stable patterns of postural coordination, as determined by the relationship between the movements of the hips (i.e., the joints that influence trunk movement) and ankles: an in-phase and antiphase pattern. These two patterns are analogous to the rhythmic finger-movement patterns described earlier, which means that the hips and ankles both exhibit flexion in the in-phase pattern, but one joint extends while the other flexes during the antiphase pattern. Each of these patterns characterize standing postural control coordination in situations in which a person is trying to maintain standing balance on an unstable surface, as would occur when you are standing in a moving bus. From a dynamical systems theory perspective, the transition from one coordination pattern to the other (in response to the movement of the bus) occurs automatically and spontaneously because the in-phase and antiphase modes of the postural coordination components (the hips and ankles) establish the "preferred" pattern.

Finally, attractor states are not only stable states of coordinated movement, but also optimally energy-efficient states. This means that when a person is moving at a preferred rate or using a preferred coordination pattern, that person uses less energy than he or she would if moving at a nonpreferred rate.

Order and Control Parameters

Proponents of the dynamical systems view place a priority on developing formal nonlinear equations of motion that specify the stability and loss of stability of movement coordination patterns during motor control, learning, and development. To develop these equations, scientists must identify the variables responsible for and associated with coordination. Primary among these variables are order parameters (sometimes the term collective variables is used). These are variables that define the overall behavior of a system. The order parameters enable a coordinated pattern of movement that can be reproduced and distinguished from other patterns.

Because order parameters define a movement pattern, it is essential to identify specific types. The most prominent of the order parameters identified by researchers is relative phase for rhythmic movements. Relative phase, which we briefly discussed in chapter 2, refers to a quantified value that represents the movement relationship between two movement segments. For the rhythmic finger-movement task in the Kelso (1984) experiment, the relative phase for the in-phase movement relationship was 360° (which is the same as 0°); the relative phase for the antiphase movement relationship was 180°. These two relative phases were determined by establishing that the maximum adduction of a finger had a phase value of 360° (i.e., 0°), and the maximum abduction had a phase value of 180°. On the basis of a common starting point, the relative phase was then calculated as the difference between the phase values of the two fingers at any point during the movement.

To apply the description from chapter 2 of the calculation of relative phase to this rhythmic finger-movement task, consider the following. For the in-phase movement, both fingers had a common starting point of maximum adduction (i.e., 360°). The fingers moved together to a maximum abduction position (180°) and then returned to the initial maximum adduction position. At any time during the fingers' movement, they had a relative phase of 360°, indicating that both fingers are at the same abduction position. The opposite holds for the antiphase pattern. At any point, the one finger is abducting the same amount as the other is adducting, which means the two fingers have a relative phase of 180°.

Another way to consider this phase relationship is from the perspective of the amount of simultaneous adduction and/or abduction movement. When moving in-phase with each other, both fingers abduct or adduct the same amount at the same time; when moving antiphase, both fingers move the same amount simultaneously, but one is adducting while the other is abducting.

The control parameter represents the variable that when increased or decreased will influence the stability and character of the order parameter. For example, in the Kelso experiment, movement frequency (i.e., speed) was the control parameter. As the movement frequency was systematically increased by the metronome, the phase relationship between the two fingers underwent distinct changes. That is, the in-phase relationship was maintained through several frequencies, but then began to destabilize as frequency continued to increase. During an intermediate period neither an in-phase nor an antiphase relationship was detectable. However, as the frequency continued to increase, there was a critical frequency at which the new antiphase relationship emerged and became stable. The shift from one stable pattern to another stable pattern is known as a phase transition.

attractors the stable behavioral steady states of systems. In terms of human coordinated movement, attractors characterize preferred behavioral states, such as the in-phase and antiphase states for rhythmic bimanual finger movements.

order parameters functionally specific variables that define the overall behavior of a system; they enable a coordinated pattern of movement to be reproduced and distinguished from other patterns (e.g., relative phase); known also as collective variables.

control parameters coordinated movement control variables (e.g., tempo, or speed, and force) that freely change according to the characteristics of an action situation. Under certain conditions, they can shift a system's behavior from one coordination pattern to another coordination pattern. According to the dynamical systems view of motor control when a control parameter is systematically varied (e.g., speed is increased from slow to fast), an order parameter may remain stable or change its stable state characteristic at a certain level of change of the control parameter.

From an experimental point of view, the control parameter is important to identify because it becomes the basis for assessing the stability of a pattern of coordination and for shifting a pattern of coordination from one stable state to another. From an applied perspective, the control parameter may provide insights into a person's coordination characteristics that might not otherwise be observed.

An example of a situation in which a practitioner could vary the control parameter was reported in a study by van Emmerik and Wagenaar (1996). They demonstrated that Parkinson's disease patients had more difficulty than healthy age-matched control participants in adapting a specific coordination pattern while walking to gradually increasing speeds (i.e., the control parameter) on a treadmill. In this study, the relative phase (i.e., the order parameter) of interest was based on the relationship between the arm and leg swings while walking. The researchers concluded from their results that the assessment of the stability of the phase relationship for the arm and leg swings at various walking speeds provides a sensitive technique to diagnose and detect early stages of Parkinson's disease.

Self-organization. An important element of the dynamical systems perspective is the concept of self-organization. This means that when certain conditions characterize a situation, a specific stable pattern of behavior emerges. Many examples of self-organization exist within the physical world that illustrate applications of this concept to the human movement domain. For example, there is no hurricane program in the universe, but hurricanes commonly occur. However, they occur only when certain wind and water temperature conditions exist. When these variables achieve certain characteristics, a hurricane will self-organize in an identifiable pattern that distinguishes it from a tropical depression or any other weather system.

When applied to human movement coordination, the concept of self-organization means that when certain conditions characterize a situation, a specific pattern of limb movement emerges. Thus, rather than being specified by a motor program, the coordinated pattern of movement self-organizes within the framework of the characteristics of environmental conditions, the task demands, and limb dynamics. For example, in the bimanual finger-movement task performed in the Kelso experiments, the in-phase coordination pattern self-organized as a function of the movement speed (i.e., the control parameter). This same type of self-organization is seen for the walk-to-run, or run-to-walk, gait transitions that occur as gait speed increases or decreases and for the arm coordination change that occurs as swim speed increases (see, for example, Seifert, Chollet, & Bardy, 2004).

Coordinative Structures; Muscle Synergies

Another important aspect of the dynamical systems view relates to the unit of behavior that is controlled. Proponents of the view assert that skilled action results when a person's nervous system constrains functionally specific collections of muscles and joints to act cooperatively, so that the person can achieve an action goal according to the dictates of the situation. An individual may develop these performance synergies, called coordinative structures, through practice or experience, or they may exist naturally.

One example of a coordinative structure is the muscles and joints (the degrees of freedom to be controlled) involved in the action of reaching and grasping an object. The groups of muscles and joints that must act together to enable a person to successfully reach and grasp an object are "converted" through practice into a task-specific ensemble.

Which of the following theories attempts to describe how motor skills develop and are coordinated
A CLOSER LOOK Evidence for Relative Time in Brain Activity and Coordinated Movement

In an excellent discussion comparing and contrasting the motor programming and dynamical systems views of motor control, Kelso (1997) addressed various issues related to relative time, which is a key variable common to both views. One of the issues that motor control researchers have struggled with over the years is determining the relationship between brain activity and observable performance characteristics associated with movement. A possible breakthrough in this struggle appears possible through the use of functional brain imaging technology, which enables researchers to observe brain activity while a person engages in performing a motor skill.

Below are two key findings from research by Kelso and his colleagues in which they used this technology to investigate the issue of relative time. In these experiments, participants performed bimanual coordination skills to produce either in-phase or out-of-phase (antiphase) movement coordination patterns to a signal that specified movement speed, which was systematically increased.

  • At low speeds, relative time remained stable (i.e., invariant) across a range of speeds for both in- and out-of-phase coordination patterns.

  • Spontaneous transitions from out-of-phase to in-phase coordination patterns occurred (i.e., a new coordination pattern self-organized) at a critical movement speed.

The results indicated that in terms of the relative time characteristic of the patterns, the brain produced essentially the same pattern of activity as the movements produced during the performance of a motor skill. Kelso stated that an important implication of these results for the motor control theory controversy is that the dynamical systems view predicts these results, whereas the motor programming view does not because the motor programming view would regard the patterns as controlled by two independent GMPs, which would not predict a spontaneous transition from one to the other as movement speed increased.

An analogy here may help. The term "task-specific ensemble" can be thought of as analogous to singing groups, commonly called "ensembles," in which many individuals sing specific parts of a specific song; all the individual singers work together cooperatively (i.e., synergistically) to achieve a specific goal. Similarly, coordinative structures are ensembles of muscles and joints that work cooperatively to allow a person to achieve a specific action goal, such as grasping an object.

For the motor control system the existence of coordinative structures reduces the degrees of freedom that the system must control. Rather than having to control the many degrees of freedom represented by the many muscles and joints involved in performing an action, the motor control system can control one ensemble of muscles and joints. In this sense, the control system for a specific movement can be less complex than would be suggested by the number of degrees of freedom that need to be controlled. For the reach-and-grasp action the activation of the coordinative structure begins when a person has the intention to reach and grasp a cup and the environmental conditions specify that this action should occur. Then, in accordance with the characteristics of the limb and of the environmental constraints, the coordinative structure self-organizes to carry out the action.

self-organization the emergence of a specific stable pattern of behavior due to certain conditions characterizing a situation rather than to a specific control mechanism organizing the behavior; for example, in the physical world hurricanes self-organize when certain wind and water temperature conditions exist.

coordinative structures functionally specific collections of muscles and joints that are constrained by the nervous system to act cooperatively to produce an action; sometimes referred to as muscle, or motor, synergies.

The coordination characteristics of hitting a tennis serve provide a good example of a coordinative structure that is acquired as a result of extensive practice.

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Which of the following theories attempts to describe how motor skills develop and are coordinated

An important behavioral benefit of coordinative structures is that they allow a person to achieve an action goal even when a muscle or joint that is a part of the structure is not able to function normally. For example, if you have a cast on your leg that keeps your knee from bending, you are able to walk up or down the stairs. This is possible because some of the muscles in the ensemble of muscles and joints (i.e., the coordinative structure) associated with walking up and down the stairs will activate in a way that compensates for the lack of involvement by muscles that can't normally function because of the cast. Consider this compensatory activity as similar to what occurs in sports teams when one of the players is not able to perform at his or her best, but the team performs well because players "step up" and perform at a higher level than they typically perform.

Coordinative structures can be intrinsic or developed through practice. Intrinsic coordinative structures are involved in actions such as walking, running, and bimanual coordination. When we perform these actions, the muscles and joints of the limbs involved have a natural tendency to demonstrate interlimb coordination patterns that have characterized our performance of them since early in life. For example, when performing a skill involving bimanual coordination, which requires the simultaneous use of both arms and hands, both infants (see, for example, Corbetta & Thelen, 1996) and adults (see Kelso, Southard, & Goodman, 1979, for instance) typically demonstrate a similar natural tendency to move the arms and hands in synchrony—that is, simultaneously both spatially and temporally. This means that when people first learn to perform a tennis serve, which requires each arm to simultaneously move in different ways, their initial tendency is to move their arms in the same way at the same time.

In contrast, coordinative structures developed through practice become new combinations of muscles and joints that act together to produce a coordination pattern that will allow the achievement of an action goal. The tennis serve just described is a good example of the development of a new coordinative structure as a result of extensive practice. Another example was described by Seifert, Chollet, and Allard (2004) for swimmers. As front-crawl swimmers achieved elite status, they began to demonstrate a stroke speed and length relationship with breathing frequency that allowed them to adapt to race situation demands more successfully than less skilled swimmers. Similar development of coordinative structures was found for skilled drummers as a result of practicing asymmetric bimanual coordination patterns (Fuji, Kudo, Ohtsuki, & Oda, 2010).

For the learning of certain skills, the intrinsic coordinative structures can lead to initial performance difficulties, as in the case of learning a tennis serve. However, after overcoming these initial difficulties, the person's performance of the skill will benefit from the newly developed coordinative structure, because it will allow him or her to achieve an action goal even though some slight perturbation occurs during the action. For example, if a tennis player is serving, and during the serve a gust of wind makes the ball deviate from its intended path, the player can quickly and easily adjust the movements involved in his or her serving action and achieve a successful serve. Similarly, if a person is jogging on a sidewalk and must step over a curb, the jogger can quickly and easily adjust movement characteristics of his or her gait pattern to avoid tripping while maintaining the jogging coordination pattern.

Perception and action coupling. Proponents of the dynamical systems view emphasize the interaction of the performer and the physical environment in which the skill is performed. From a motor control perspective, this interaction involves perception and movement variables that must be taken into account in any attempt to explain the mechanisms involved in the control of motor skills. The dynamical systems theory proposes that this interaction, which is referred to as perception-action coupling, is an essential element in accounting for skillful performance. The perception part of the interaction detects and uses critical invariant information in an environment (e.g., the amount of time until an object contacts the person, or vice versa); the action part involves the setting and regulating of movement control features that enable the person to achieve the action goal (e.g., kinematic and kinetic components of movements).2

An example of a perceptual variable involved in this type of coupling process is known by the Greek letter tau (τ), which is related to the time to contact between an object and a person's eye. (We will discuss tau further in chapters 6 and 8.) Researchers have demonstrated that tau guides actions such as steering a car, catching a ball, hitting a ball, jumping from a platform, and performing the long jump (Lee, 2009; Lee et al., 2009). As a person gains experience, the perceptual variable couples with the dynamics of movement so that a distinct coordination pattern can be reproduced and modified as needed.

Some additional examples of perception-action coupling include the coordination pattern people use to get on or over an obstacle, climb stairs, and go through a doorway. Researchers have found that obstacles in a person's pathway, stairs, and door openings specify size-related information that a person perceives in terms of an invariant relationship between an object's size and her or his own leg length (in the case of obstacles and stairs) or body size (in the case of door openings). Thus the person will step or climb over the obstacle on the basis of this perceived relationship, choose one of various stair-climbing options, and walk through a doorway sideways or face-forward depending on this perceived relationship between the environmental feature and his or her own body size–related feature. The reciprocal fit between the characteristics of a person and the characteristics of the environment that permit specific actions, such as stairs having the physical characteristics to permit stair climbing, are referred to as affordances in the perception-action coupling literature (Gibson, 1979). Learning to detect affordances is central to motor control and learning from this perspective.

perception-action coupling the spatial and temporal coordination of vision and the hands or feet that enables people to perform eye-hand and eye-foot coordination skills; that is, the coordination of the visual perception of the object and the limb movement required to achieve the action goal.

affordance the reciprocal fit between the characteristics of a person and the characteristics of the environment that permit a specific action to occur, such as stairs having the physical characteristics to permit stair climbing.

Which of the following theories attempts to describe how motor skills develop and are coordinated
A CLOSER LOOK An Example of How Motor Program Theory and Dynamical Systems Theory Differ in Explaining the Motor Control of a Behavior: The Walk-to-Run Gait Change

People spontaneously change from a walk to a run gait pattern at a certain speed of locomotion. Although individuals vary in terms of the actual speed at which this change occurs, the shift appears to be common to all people. The motor program and dynamical systems theories differ in their explanations of why this coordination change occurs.

  • Motor Program Theory The relative time structure of a coordination pattern distinguishes one generalized motor program from another. Because walking and running gaits are characterized by different relative time structures, they are controlled by different generalized motor programs. The walk-to-run gait pattern change occurs at a certain speed because the person chooses to change from the program that controls walking to the program that controls running.

  • Dynamical Systems Theory Interlimb and body coordination patterns self-organize as a function of specific control parameter values and environmental conditions. For walking and running gait patterns, speed is a critical control parameter. The walk-to-run gait transition involves a competition between two attractors. At slow speeds, the primary attractor state is a walking coordination pattern. But as walking speed increases, there is a certain range of speeds at which this attractor state loses stability, which means that for this range of speeds, the walking pattern undergoes some change as a running coordination pattern self-organizes and eventually becomes the stable attractor state for gait at a certain speed.

Interpreting the Shapiro et al. (1981) Experiment Results

Motor program theory (Figure 5.5). Gait is controlled by one generalized motor program when walking gait is observed (3–6 km/hr) and by a different generalized motor program when the running gait is observed (8–12 km/hr).

Dynamical systems theory. The walking and running gaits represent two attractor states that remain stable within the speed ranges of 3–6 km/hr and 10–12 km/hr. But for gait speeds of 7–9 km/hr, the order parameter becomes unstable during a transition period in which a new gait pattern (running) self-organizes and becomes stable for a certain range of speeds.

Which of the following defines motor development?

Motor development means the physical growth and strengthening of a child's bones, muscles and ability to move and touch his/her surroundings.

What development refers to growth and change in intellectual capabilities?

Cognitive or intellectual development means the growth of a child's ability to think and reason.

Which principle does motor development in infancy follow?

The cephalocaudal principle refers to the general pattern of physical and motoric development followed from infancy into toddlerhood and even early childhood whereby development follows a head-to-toe progression.

Which principle of motor development describes the fact that infants tend to gain motor control over the upper part of their bodies before the lower part of their bodies?

According to the cephalocaudal principle, A. upper body parts develop before lower parts.