Dominic Stone
Muscle synergies are neural coordinative structures that function to alleviate the computational burden associated with the control of movement and posture. The muscle synergy hypothesis suggests that the central nervous system (CNS) produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles. The identification of muscle synergies has strong implications for the organization and structure of the nervous system, providing a mechanism by which task-level motor intentions are translated into detailed, low-level muscle activation patterns.
| Characteristics | Values |
|---|---|
| Definition | Muscle synergy is a vector specifying relative levels of muscle activation. |
| Function | Muscle synergies are neural coordinative structures that function to alleviate the computational burden associated with the control of movement and posture. |
| Origin | Muscle synergies are hypothesised to have a neural origin. |
| Measurement | Muscle synergy recruitment signals cannot be measured directly in the brain or CNS. However, muscle activation can be measured, and the signals can be estimated from this data. |
| Variability | Muscle synergy theory suggests that the CNS produces a small number of stable signals, but some variability is present. |
| Clinical Applications | Muscle synergy analysis may offer clinicians a better view of the neural structure underlying motor behaviours, which could inform diagnostic tools and interventions. |
| Plasticity | Muscle synergies exhibit plasticity during child-to-adult development and adult training, with specific synergy-merging patterns correlating with enhanced or reduced efficiency. |
| Structure | Muscle synergies are like building blocks, defining characteristic patterns of activation across multiple muscles that may be unique to each individual but perform similar functions. |
| Hierarchy | Muscle synergies may represent the bottom of a hierarchical neural control structure, with higher neural centres operating on increasingly conceptual variables related to task-level motor performance. |
| Neural Abnormalities | Altered behavioural or kinematic outcomes could be the result of multiple distinct neural abnormalities with different muscle coordination patterns. |
| Computational Procedures | Muscle synergy structures can be retrieved using computational procedures such as the non-negative matrix factorization algorithm (NMF). |
| Motor Control | Muscle synergies are activated in varying combinations to produce motor behaviour and are essential for tasks such as maintaining balance. |
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What You'll Learn
Muscle synergies are neural coordinative structures
The muscle synergy hypothesis is a long-withstanding proposition on the underlying neural constraints that produce coordinated movement. It suggests that the complexity of human movement is offset by the allocation of computational resources to the spinal level in the form of motor primitives. These motor primitives modularly activate functional groups of muscles that are flexibly combined for efficient control. The muscle synergy concept describes the role of common neural drives to functional muscle groupings working redundantly towards a common task goal.
Muscle synergies are like building blocks, defining characteristic patterns of activation across multiple muscles that may be unique to each individual but perform similar functions. They are the elements from which complex muscle activation patterns are constructed to produce a wide range of motor behaviors. The absolute level of activation of each muscle synergy is presumed to be modulated by a single neural command signal. For a given motor task, several muscle synergies are activated in varying combinations to produce the motor behavior.
Muscle synergy analysis may offer clinicians a better view of the neural structure underlying motor behaviors and how they change in motor deficits and rehabilitation. Such information could inform diagnostic tools and evidence-based interventions specifically targeted to a patient’s deficits.
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Muscle synergy theory and the central nervous system
Muscle synergy theory suggests that the central nervous system (CNS) produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles. The CNS processes a relatively small amount of information about the environment outside the human body and sends signals to the muscles that, in turn, move the highly redundant musculo-skeletal structure.
The CNS produces and sends signals to the muscles to effect movement, but the exact nature of these signals is not entirely understood. Muscle synergy theory attempts to explain this process. The theory posits that the CNS produces a small number of signals that are then distributed through a network that combines these signals and sends them to the muscles. These signals are called synergies.
Synergies are neural coordinative structures that function to reduce the computational burden associated with controlling movement and posture. When the CNS generates voluntary movement, many muscles, each comprising thousands of motor units, are simultaneously activated and coordinated. This is a complex task, and muscle synergies are thought to simplify this process by reducing the number of variables that the CNS needs to process.
Muscle synergy analysis is a method that can offer clinicians insight into the underlying neural strategies for movement and the functional outcomes of muscle activity. This analysis can be particularly useful in understanding the neural structure underlying motor behaviors and how they change in motor deficits and rehabilitation. For example, differences in the number of muscle synergies exhibited by hemiparetic stroke patients may reflect disruptions in descending neural pathways and are correlated to deficits in motor function.
The concept of muscle synergies has also been used in the development of assistive technologies, such as myoelectric controlled assistive technologies (AT) for upper extremities. By using a modular organization based on muscle synergies, the computational burden for the controller is reduced, improving the ease of use of these technologies.
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Muscle synergy hypothesis and human movement
Muscle synergy theory suggests that the central nervous system (CNS) produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles. The CNS produces and sends signals to the muscles to effect movement, but the exact mechanisms are not entirely understood. The muscle synergy hypothesis provides a framework to identify the functional significance of individual muscle activity and muscle coordination. This hypothesis suggests that the CNS produces a small set of modules, or muscle synergies, to simplify motor control. These modules are the functional building blocks of movement as they can explain the neurophysiological characteristics of movements.
Muscle synergies are neural coordinative structures that function to alleviate the computational burden associated with the control of movement and posture. When the CNS generates voluntary movement, many muscles, each comprising thousands of motor units, are simultaneously activated and coordinated. This is a complex task, and muscle synergies are thought to reduce the CNS's burden to a much smaller set of variables. Muscle synergy analysis has been used to study motor behaviour and understand the underlying neural strategies for movement. This analysis can be performed using linear decomposition algorithms such as principal component analysis (PCA) and non-negative matrix factorization (NMF). NMF, for example, identifies synergies that are time-invariant non-negative vectors whose linear combination minimises the error of EMG reconstruction.
The muscle synergy hypothesis has important implications for clinical evaluation and rehabilitation of movement. Muscle synergy analysis may offer clinicians a better view of the neural structure underlying motor behaviours and how they change in motor deficits and rehabilitation. For example, hemiparetic stroke patients exhibit differences in the number of muscle synergies, which may reflect disruptions in descending neural pathways and are correlated to deficits in motor function. Understanding the degree of plasticity in muscle coordination could allow for more targeted interventions.
Furthermore, muscle synergy analysis is robust enough to reveal an underlying neural organisation even when there are competing influences on muscle activity, such as local circuits. This analysis can help identify and extract muscle synergies from electromyographic (EMG) signals. While it is possible to measure muscle activity during movements using EMG, it is difficult to interpret the functional implications of these signals during motor tasks due to their variability. The same motor behaviour can be executed by a variety of muscular patterns due to the overabundant musculature of the body. This can result in highly variable EMG patterns between repeated measurements, even in single-muscle recordings. However, this variability does not necessarily indicate dysfunction, as EMG patterns can normally vary due to factors such as attention, body configuration, and emotional state.
In summary, the muscle synergy hypothesis and human movement are closely related. The hypothesis suggests that the CNS simplifies motor control by activating a small set of muscle synergy modules. Muscle synergy analysis provides a tool to study motor behaviour and understand the underlying neural organisation of movement. This analysis has important applications in clinical evaluation and rehabilitation, offering insights into motor deficits and the flexibility and adaptability of motor patterns.
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Muscle synergy analysis and clinical evaluation
Muscle synergy analysis can be used to gain insight into the underlying neural strategies for movement and the functional outcomes of muscle activity. This is because muscle synergies are neural coordinative structures that function to alleviate the computational burden associated with the control of movement and posture.
The central nervous system (CNS) produces and sends signals to the muscles to effect movement. Muscle synergy theory suggests that the CNS produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles. This results in a complex electromyographic (EMG) pattern in the limb's muscles. Muscle synergy analysis can be used to extract muscle synergies from such datasets, revealing underlying patterns that may reflect different levels of neural function.
The technique reveals the underlying coordination patterns within a highly variable set of muscle activation patterns. For example, hemiparetic stroke patients exhibit differences in the number of muscle synergies, which may reflect disruptions in descending neural pathways and are correlated to deficits in motor function. Muscle synergy analysis may thus offer clinicians a better view of the neural structure underlying motor behaviours and how they change in motor deficits and rehabilitation. This information could inform diagnostic tools and evidence-based interventions specifically targeted to a patient’s deficits.
By regularly assessing a patient’s muscle synergy profile, it may be possible to identify a patient’s functional deficit, track rehabilitation results, and adjust treatments. This could allow clinicians to more effectively treat motor dysfunctions by organizing patients into subclasses and tailoring the treatment to the specific patient’s deficit.
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Muscle synergies and human locomotion
Muscle synergies are neural coordinative structures that function to reduce the computational burden associated with controlling movement and posture. They are the result of the simultaneous activation of a few muscle synergies via descending or afferent pathways, producing a complex electromyographic (EMG) pattern in the limb's muscles. The muscle synergy hypothesis suggests that the central nervous system (CNS) produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles.
Muscle synergy theory has been used to explain locomotion in cats and humans. Studies have shown that locomotion in these species can be explained by a small number of muscle synergies, with five to seven hindlimb/leg muscle synergies in cats and humans. These muscle synergies are maintained at different speeds, although new synergies can be added during running as additional muscles are recruited. The concept of muscle synergies is supported by the identification of similar synergies in different species, suggesting that they are organized at lower levels of the CNS.
The application of muscle synergy analysis (MSA) has provided further insights into muscle synergies and locomotion. MSA, a quantitative method, utilizes matrix factorization algorithms to quantify muscle synergies. Results from MSA studies suggest that muscle synergies may be the basic building blocks that, in specific combinations, can produce a variety of movements such as locomotion.
Furthermore, muscle synergies play a role in task-specific locomotor behaviors. For example, during downhill or downstairs walking, the primary goal is to control the descent of the body with caution. The muscle synergies involved in this task are different from other motor tasks, reflecting the unique requirements of this specific behavior.
In summary, muscle synergies are essential for human locomotion, providing a simplified neural control system for muscle groups. These synergies are coordinated by the CNS and are adaptable to different locomotor tasks and speeds. MSA has been a valuable tool in understanding the role of muscle synergies in locomotion, with potential applications in clinical evaluation and rehabilitation.
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Frequently asked questions
Muscle synergies are neural coordinative structures that function to alleviate the computational burden associated with the control of movement and posture. They are the result of the simultaneous activation of a few muscle synergies via descending or afferent pathways.
The central nervous system (CNS) produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles. These signals are called synergies. Most muscles work in groups, and the muscle activation signals are related to each other, so they can be represented by a smaller number of signals.
Muscle synergies allow for the translation of task-level neural commands into execution-level muscle activation patterns. They also provide insight into the underlying neural structure of muscle activation, which can inform diagnostic tools and interventions for motor deficits.
Muscle synergies are identified through muscle synergy analysis, which involves measuring muscle activity during movements and interpreting the electromyographic (EMG) signals. This can be done using computational procedures such as non-negative matrix factorization (NMF) or independent component analysis (ICA).
Yes, muscle synergies can be modified through development and training. During development, synergies are fractionated into units with fewer muscles, while specific synergies may coalesce and merge during adult training to meet changing biomechanical and efficiency demands.
