What do we mean when we say that a muscle fiber contracts strongly?

What do we mean when we say that a muscle fiber contracts strongly?

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Sounds dumb but anyway, i heard that superfast fibers contract more strongly than fast twitch fibers. And i never thought of muscle contraction as something that has a magnitude (i thought of it as "1 or 0" meaning either contracted or not). So lets say we have two fibers, the same length and thickness, if one contracts more than the other does that simply mean that it becomes shorter ?

Fast-Twitch Vs. Slow-Twitch Muscle Fiber Types + Training Tips

Looking to build endurance? What about power? Do dreams of being an all-star hitter or marathon runner need to be dashed if twitch ratios aren’t ideal? Not necessarily. The types of muscle fibers targeted in different types of training programs can impact athletic performance goals.

In this article, we explore the two types of muscle fibers in detail and discuss how to train each type according to athletic goals.

Velocity and Duration of Muscle Contraction

The shortening velocity affects the amount of force generated by a muscle.

Learning Objectives

Explain the interaction of velocity and duration in muscle contraction

Key Takeaways

Key Points

  • Twitch contractions, which are short in duration, do not reach peak force.
  • Tetanic contractions, which are long in duration, reach peak force and plateau.
  • The shortening velocity is the speed at which a muscle changes length during a contraction.
  • The force of a muscle contraction declines with increasing velocity.

Key Terms

  • Force-Velocity Relationship: The relationship between the speed and force of muscle contraction, outputted as power.
  • summation.: The occurrence of another twitch contraction before complete relaxation of the prior twitch has occurred.
  • tetanic: A longer contraction of a muscle which reaches peak force.
  • twitch: A short contraction of a muscle which does not reach peak force.

Muscle Contraction Velocity

Skeletal muscle contractions can be broadly separated into twitch and tetanic contractions. In a twitch contraction, a short burst of stimulation causes the muscle to contract, but the duration is so brief that the muscle begins relaxing before reaching peak force. If another contraction occurs before complete relaxation of a muscle twitch, then the next twitch will simply sum onto the previous twitch, a phenomenon called summation. If the stimulation is long enough, the muscle reaches peak force and plateaus at this level, resulting in a tetanic contraction.

Force-Velocity Relationship

Force-Velocity Relationship: As velocity increases force and power produced is reduced. Although force increases due to stretching with no velocity, zero power is produced. Maximum power is generated at one-third of maximum shortening velocity.

The force-velocity relationship in muscle relates the speed at which a muscle changes length to the force of this contraction and the resultant power output (force x velocity = power). The force generated by a muscle depends on the number of actin and myosin cross-bridges formed a larger number of cross-bridges results in a larger amount of force. However, cross-bridge formation is not immediate and if myofilaments slide over each other at a faster rate, their ability to form cross-bridges and subsequent force are both reduced.

At a maximum velocity no cross-bridges can form so no force is generated, resulting in the production of zero power (right edge of graph). The reverse is true for stretching of muscle although the force of the muscle is increased, there is no velocity of contraction and zero power is generated (left edge of graph). Maximum power is generated at approximately one-third of maximum shortening velocity.

Twitch contractions are short in duration. Though they have high velocity, they begin resting before reaching peak force. Tetanic contractions, which are long in duration, reach peak force and plateau.

What Is a Graded Muscle Response?

A graded muscle response occurs when a muscle contracts with different degrees of force based on certain circumstances, according to Dr. Gary Ritchison from the Department of Biological Sciences at Eastern Kentucky University. Two types of graded muscle responses are motor unit summations and wave summations.

A motor unit summation relies on the number of motor units stimulated within a skeletal muscle to cause contractions. When more motor units are stimulated, the greater the contraction within the muscle, notes Dr. Ritchison. A motor unit consists of a single motor neuron and all of the muscle fibers attached to it. A wave summation that increases the frequency of muscle stimulation also increases muscle strength. Rapid stimulation prevents calcium levels in muscles from decreasing, therefore a stronger contraction occurs because calcium creates more active neuron-muscle fiber interactions.

A motor unit summation increases the electrical stimulation of motor unit cells, states lecturer Jim Swan from the Department of Biology at University of New Mexico. When more electricity is applied, more muscles contract. This is also called quantal summation. A wave summation can lead to tetanization, a process that sustains a contraction after the muscle stimuli reach a high enough frequency. When wave after wave of muscle contractions reach a maximum point, the muscle remains contracted rather than relaxing. A treppe is similar to a motor unit summation, only this time the muscle gradually increases stimuli as the fibers warm up from a previously relaxed position. The strength of muscles remain the same in a treppe, whereas muscle contractions increase during a quantal summation.

Spinal Cord and Brain Stem

A sensory pathway that carries peripheral sensations to the brain is referred to as an ascending pathway, or ascending tract. The various sensory modalities each follow specific pathways through the CNS. Tactile and other somatosensory stimuli activate receptors in the skin, muscles, tendons, and joints throughout the entire body. However, the somatosensory pathways are divided into two separate systems on the basis of the location of the receptor neurons. Somatosensory stimuli from below the neck pass along the sensory pathways of the spinal cord, whereas somatosensory stimuli from the head and neck travel through the cranial nerves—specifically, the trigeminal system.

The dorsal column system (sometimes referred to as the dorsal column–medial lemniscus) and the spinothalamic tract are two major pathways that bring sensory information to the brain (Figure 14.5.1). The sensory pathways in each of these systems are composed of three successive neurons.

The dorsal column system begins with the axon of a dorsal root ganglion neuron entering the dorsal root and joining the dorsal column white matter in the spinal cord. As axons of this pathway enter the dorsal column, they take on a positional arrangement so that axons from lower levels of the body position themselves medially, whereas axons from upper levels of the body position themselves laterally. The dorsal column is separated into two component tracts, the fasciculus gracilis that contains axons from the legs and lower body, and the fasciculus cuneatus that contains axons from the upper body and arms.

The axons in the dorsal column terminate in the nuclei of the medulla, where each synapses with the second neuron in their respective pathway. The nucleus gracilis is the target of fibers in the fasciculus gracilis, whereas the nucleus cuneatus is the target of fibers in the fasciculus cuneatus. The second neuron in the system projects from one of the two nuclei and then decussates, or crosses the midline of the medulla. These axons then continue to ascend the brain stem as a bundle called the medial lemniscus. These axons terminate in the thalamus, where each synapses with the third neuron in their respective pathway. The third neuron in the system projects its axons to the postcentral gyrus of the cerebral cortex, where somatosensory stimuli are initially processed and the conscious perception of the stimulus occurs.

The spinothalamic tract also begins with neurons in a dorsal root ganglion. These neurons extend their axons to the dorsal horn, where they synapse with the second neuron in their respective pathway. The name “spinothalamic” comes from this second neuron, which has its cell body in the spinal cord gray matter and connects to the thalamus. Axons from these second neurons then decussate within the spinal cord and ascend to the brain and enter the thalamus, where each synapses with the third neuron in its respective pathway. The neurons in the thalamus then project their axons to the spinothalamic tract, which synapses in the postcentral gyrus of the cerebral cortex.

These two systems are similar in that they both begin with dorsal root ganglion cells, as with most general sensory information. The dorsal column system is primarily responsible for touch sensations and proprioception, whereas the spinothalamic tract pathway is primarily responsible for pain and temperature sensations. Another similarity is that the second neurons in both of these pathways are contralateral, because they project across the midline to the other side of the brain or spinal cord. In the dorsal column system, this decussation takes place in the brain stem in the spinothalamic pathway, it takes place in the spinal cord at the same spinal cord level at which the information entered. The third neurons in the two pathways are essentially the same. In both, the second neuron synapses in the thalamus, and the thalamic neuron projects to the somatosensory cortex.

Figure 14.5.1 – Ascending Sensory Pathways of the Spinal Cord: The dorsal column system and spinothalamic tract are the major ascending pathways that connect the periphery with the brain.

The trigeminal pathway carries somatosensory information from the face, head, mouth, and nasal cavity. As with the previously discussed nerve tracts, the sensory pathways of the trigeminal pathway each involve three successive neurons. First, axons from the trigeminal ganglion enter the brain stem at the level of the pons. These axons project to one of three locations. The spinal trigeminal nucleus of the medulla receives information similar to that carried by spinothalamic tract, such as pain and temperature sensations. Other axons go to either the chief sensory nucleus in the pons or the mesencephalic nuclei in the midbrain. These nuclei receive information like that carried by the dorsal column system, such as touch, pressure, vibration, and proprioception. Axons from the second neuron decussate and ascend to the thalamus along the trigeminothalamic tract. In the thalamus, each axon synapses with the third neuron in its respective pathway. Axons from the third neuron then project from the thalamus to the primary somatosensory cortex of the cerebrum.


The diencephalon is beneath the cerebrum and includes the thalamus and hypothalamus. In the somatic nervous system, the thalamus is an important relay for communication between the cerebrum and the rest of the nervous system. The hypothalamus has both somatic and autonomic functions. In addition, the hypothalamus communicates with the limbic system, which controls emotions and memory functions.

Sensory input to the thalamus comes from most of the special senses and ascending somatosensory tracts. Each sensory system is relayed through a particular nucleus in the thalamus. The thalamus is a required transfer point for most sensory tracts that reach the cerebral cortex, where conscious sensory perception begins. The one exception to this rule is the olfactory system. The olfactory tract axons from the olfactory bulb project directly to the cerebral cortex, along with the limbic system and hypothalamus.

The thalamus is a collection of several nuclei that can be categorized into three anatomical groups. White matter running through the thalamus defines the three major regions of the thalamus, which are an anterior nucleus, a medial nucleus, and a lateral group of nuclei. The anterior nucleus serves as a relay between the hypothalamus and the emotion and memory-producing limbic system. The medial nuclei serve as a relay for information from the limbic system and basal ganglia to the cerebral cortex. This allows memory creation during learning, but also determines alertness. The special and somatic senses connect to the lateral nuclei, where their information is relayed to the appropriate sensory cortex of the cerebrum.

Effects of strength training on muscle fiber types and size consequences for athletes training for high-intensity sport

Training toward improving performance in sports involving high intense exercise can and is done in many different ways based on a mixture of tradition in the specific sport, coaches' experience and scientific recommendations. Strength training is a form of training that now-a-days have found its way into almost all sports in which high intense work is conducted. In this review we will focus on a few selected aspects and consequences of strength training namely what effects do strength training have of muscle fiber type composition, and how may these effects change the contractile properties of the muscle and finally how will this affect the performance of the athlete. In addition, the review will deal with muscle hypertrophy and how it develops with strength training. Overall, it is not the purpose of this review to give a comprehensive up-date of the area, but to pin-point a few issues from which functional training advises can be made. Thus, more than a review in the traditional context this review should be viewed upon as an attempt to bring sports-physiologists and coaches or others working directly with the athletes together for a mutual discussion on how recently acquired physiological knowledge are put into practise.

When watching athletes in action, it is obvious even for the untrained eye that some athletes are “faster” or more “explosive” than others. Likewise, it is evident that some athletes manage to perform certain movements quicker than others. No doubt much of this can be attributed to superior technical skills achieved through many hours of practice, but any coach will tell you that “fast” and “explosive” are qualities the athlete had already before he or she was molded through endless training sessions he/she had “talent.” Thus, both coaches and scientists know that it is not possible to turn a donkey into a racehorse by means of exercise and training. Hard work will, at the most, turn the donkey into a fast and explosive donkey! With this in mind, a number of fundamental questions can be asked. What and how much can we improve through training, and what are the factors that matter? These questions are unfortunately extremely complex and difficult to answer. Nevertheless, a number of crucial physical parameters can be identified.

We know that the ability of a muscle to conduct a fast and forceful contraction contribute positively to performance in certain athletic advents. Within muscle physiology it has been know for many years that the maximum speed at which a muscle can contract is to a high extent explained by the its composition of fast and slow muscle fibers ( Harridge et al., 1996 Bottinelli & Reggiani, 2000 ). Likewise, the maximum force and power produced by the single muscle fiber is strongly positively related to its content of fast myosin ( Bottinelli et al., 1999 ), which can also be observed during in vivo muscle contraction in the intact human ( Aagaard & Andersen, 1998 ). The purpose of this review is to look at what happens with human skeletal fiber type composition and fiber size when exposed to strength training, and how these changes might affect athletic performance. It should be emphasize that the aim of this paper is not to give an extensive review of the literature within the area, but to pin-point a few selected aspects and issues that are of relevance in the exercise planning for elite athletes.

Defining the terms “strength training” or “resistance training” may be a little more difficult than it seems at first glimpse. A number of variables such as type of exercise, order of exercises, load or intensity, total volume of exercises and rest are obvious parameters that can be regulated in a training regimen ( Fleck & Kraemer, 2004 ). On top of this we can add other variables such as speed of contraction, the choice between exercising in machines or with free weights and overall periodization principals ( Fry, 2004 ). Thus, there is no doubt that the end-result will be influenced by how these variables are combined ( Fry, 2004 ). For the purpose of this review we will define strength training as “Training that in a efficient manner induces a measurable increase in muscle strength or/and hypertrophy.” Thus, this review will focus on training that typically engage relatively heavy loads (e.g. 70–100% of 1 RM), performed in series of relative few repetitions (e.g. ≤12), as this loading modality appears to be highly efficient of producing muscle hypertrophy ( Fry, 2004 ).

Skeletal muscle fibers contain a large number of different proteins facilitating contraction some are purely structural, with the sole purpose of maintaining the physical structure of the fiber as force is produced, whereas others have their main function in the actual contractile process ( Schiaffino & Reggiani, 1996 ). Although several contractile proteins play important roles when a muscle fiber contracts, the two main players are myosin (the thick filament) and actin (the thin filament). When a contraction is initiated the two proteins couple, change conformation, one slides past the other as they move in opposite directions, uncouple, reload while preparing for coupling with the next actin/myosin that passes by, constantly repeating the cycle. In the human skeletal muscle actin exists in a singular form only ( Schiaffino & Reggiani, 1994 ). Myosin (or to be more exact the heavy chain of the myosin molecule MyHC), on the other hand, exists in three different forms (know as isoforms essentially different versions of the same protein taking care of the same task) in human skeletal muscle ( Schiaffino & Reggiani, 1994 ). Each of these MyHC isoforms do, when present in a muscle fiber endow the fiber with specific functional characteristics, the most important being the velocity of contraction. A number of other proteins contribute to or modulate the outcome but the absolute governing element in the equation is the MyHC isoform present. Thus, muscle fibers can be readily separated into different fiber types with specific contraction characteristics via identification of the MyHC isoform(s) present in the individual fibers. Obviously, other criteria for fiber type differentiation can be set up, e.g. metabolic characteristics ( Essén et al., 1975 ), however these are beyond the scope of this review. The three different MyHC isoforms should in principle leave us with three different major muscle fiber types. In human skeletal muscle, however, one often find that two MHC isoforms are present alongside each other in the same fiber, which depending on the degree of details could expand the number of different fiber types from three to five or even into a continuum of slow-to-fast fiber types. The three MyHC isoforms present are MyHC I, MyHC IIA and MyHC IIX [in older literature often refereed to as “IIB,” ( Smerdu et al., 1994 )] ( Schiaffino & Reggiani, 1996 ). Fibers containing only MyHC I, MyHC IIA and MyHC IIX constitute the “pure” fiber types, but also “hybrid fibers” co-expressing MyHC I and MyHC IIA as well as MyHC IIA and MyHC IIX are commonly found ( Andersen et al., 1994 ).

It is possible to determine the maximum contraction velocity of single human skeletal muscle fibers through relative simple but time-consuming experiments. When doing that a clear pattern emerges fibers containing MyHC I are the slowest and fibers containing MyHC IIX are the fastest, and a relative solid rule of thumb says that the order of contraction velocity for the different fiber types is, MyHC I<MyHC I/IIA hybrids<MyHC IIA<MyHC IIA/IIX hybrid <MyHC IIX ( Harridge et al., 1996 Bottinelli, 2001 ). The difference in maximum shortening speed, when determined in single fibers between fibers containing only one of the three MyHC isoforms (MyHC I:MyHC IIA:MyHC IIX) is in the order of magnitude of 1:3:8 or 1:4:10, where co-expression hybrid fibers are placed nicely in-between fibers containing only one MyHC isoform ( Fitts & Widrick, 1996 Harridge, 2007 ). These data are results of experiments conducted at relatively low temperature (15–18 °C). While this is substantially below the temperature in the intact muscle, recent data conducted at 35 °C indicate that the fiber type difference at more physiological relevant temperature is much less and in the magnitude of 1:2 between MyHC I and MyHC II fibers ( Lionikas et al., 2006 ).

The next question that arrives is if this difference in shortening velocity between “slow” and “fast” fibers can be observed in the intact muscle. The question asked could be is there a correlation between fiber type composition of a muscle and the velocity properties of the intact muscle? A number of studies have exploited this question, and strong relationship have been demonstrated both in different muscles with different fiber type composition in the same individual ( Harridge, 1996 Harridge et al., 1996 ) and in the same muscle between different individuals with different fiber type composition ( Tihanyi et al., 1982 Yates & Kamon, 1983 Aagaard & Andersen, 1998 ). The relationship between fiber type composition and muscle contractile velocity does not emerge at slow contraction velocities, because slow fibers in this case have ample time to build up force to more or less to the same level as the fast fibers ( Aagaard & Andersen, 1998 ). Consequently, the close relationship between maximal concentric muscle strength and the percentage of MyHC II in intact human skeletal muscle first becomes readily apparent at high contraction velocities ( Aagaard & Andersen, 1998 ). Translated to functional terms this mean that a person with a relative large proportion of fast fibers will be able to achieve higher muscle force and power output during fast movements including the early acceleration phase than a person with a low relative proportion of fast fibers. Likewise, muscles characterized by a large proportion of fast muscle fibers (high relative MyHC II content) are substantially more “explosive” [i.e. demonstrating a greater rate of force development (RFD)] than muscles with fewer fast fibers (low relative MyHC II content), as reflected by an elevated contractile RFD ( Harridge et al., 1996 ), hence demonstrating an enhanced capacity for rapid force production.

Thus, as it is established that that a person with high relative amount of fast fibers, all other things equal, will be more suited for sports in which fast, explosive-type movements performed over shorter periods of time is crucial, another question raises “Can we change the fiber type composition of our muscles through training?” The short (disappointing) answer is “Not really” ( Andersen et al., 2000 ). The long answer has some uplifting nuances. Animal studies have shown that exposing a muscle with predominantly fast muscles fibers to huge amounts of low-frequency electrical stimulation, similar to what is received by slow muscles fibers, over time will gradually change the MyHC composition from fast to slow. Likewise a complete removal of the nerve impulse to a slow muscle, e.g. by cutting the motor nerve, will over time induce a switch from slow to fast MyHC ( Pette & Staron, 2000 ). Similar findings were demonstrated some 50 years ago in animal studies in which fast and slow motor nerves were switched between a fast and slow muscle leading to a switch in contraction velocity characteristics between the two muscles ( Buller et al., 1960 ). Later it has been shown that these shifts were the consequence of a change in MyHC isoforms expression from fast to slow and vice versa in the muscles ( Pette, 2001 ).

Likewise, in humans a number of critical conditions can introduce large changes in MyHC compositions in skeletal muscle, e.g. after a spinal cord injury leading to paralysis. This condition will after a while leads to an almost complete abolishment of the slow MyHC isoforms in the affected muscles, leaving the muscle to exclusively express the two fast MyHC isoforms ( Andersen et al., 1996 ). Thus, these experiment and observations tells us that a more or less complete switch between expression of fast and slow MyHC isoforms is possible in most skeletal muscles. Nevertheless, the above described scenario of a complete change in expression from slow to fast MyHC after a spinal cord injury and other similar situations are highly un-physiological, and not within the frame of physical training.

What are the limits of fiber type changes that we can introduce with physical training, and in our case strength training? Numerous studies have shown that heavy resistance exercise training will decrease the expression of MyHC IIX in human skeletal muscle and simultaneously increase the expression of MyHC IIA, whereas the expression of MHC I is much more unaffected by the resistance exercise ( Hather et al., 1991 Adams et al., 1993 Andersen & Aagaard, 2000 ). This is a highly solid observation and a general consensus on this point exists among people working in the field ( Fry, 2004 Folland & Williams, 2007 ). Likewise, cessation of resistance training will induce, or re-induce MyHC IIX at the expense of MyHC IIA ( Andersen & Aagaard, 2000 Andersen et al., 2005 ). Whether or not the number of fibers expressing MyHC I is increased or decreased after strength training is debateable, but most likely, there is no or only very subtle changes in the number of fibers expressing MyHC I ( Andersen & Aagaard, 2000 Fry, 2004 ). Thus, the general rule of MyHC isoform plasticity in human skeletal muscle appears to be: introduction of or increase in the amount of resistance training lead to decrease in MyHC IIX and increase in MyHC IIA, while a withdrawal or decrease in resistance training lead to increase in MyHC IIX and decrease in MyHC IIA, leaving MyHC I relatively unaffected ( Andersen & Aagaard, 2000 Fry, 2004 ).

From a functional point of view the disappearance of MyHC IIX with strength training may seem somewhat unfavorable since this MyHC isoform has the fastest contraction velocity and highest power production, and removal from the muscle should lead to a slowing and reduced power output of the muscle. Theoretically that is the case when looking at the individual fiber, but when looking at the capacity of the whole and intact muscle this apparent slowing is, in most athletic settings, more than out-weighted by the increase in contractile strength, power and RFD of the trained muscle ( Aagaard, 2004 ). In consequence, maximal unloaded limb movement speed is observed to increase ( Schmidtbleicher & Haralambie, 1981 Aagaard et al., 2003 ) or remain unaltered ( Andersen et al., 2005 ) following 3–4 months of heavy-resistance strength training. The enhancement in muscle force, power and RFD observed following heavy-resistance strength training to a large extent is caused by the fast fibers demonstrating a twofold greater hypertrophy than the slow fibers in response to heavy-resistance strength training ( Aagaard et al., 2001 Kosek et al., 2006 ). Moreover, a differentiated hypertrophy of the fast and slow fibers with heavy resistance training, in favor of the fast fibers will eventually give rise to not only a bigger muscle but also a muscle in which a relatively lager proportion of the cross-sectional area is being occupied by fast fibers ( Andersen & Aagaard, 2000 Aagaard, 2004 ).

Data from our lab indicate that heavy resistance training followed by detraining can evoke a boosting in proportions of the MyHC IIX isoform. In a strength training study involving a group of young healthy male subjects is was observed that the MyHC IIX percentage in the vastus lateralis muscle of the subjects decreased from 9% to only 2% in a 3 months training period, but somewhat more remarkable the MyHC IIX percentage subsequently increased to 17% after a additional period of 3 months of detraining ( Andersen & Aagaard, 2000 ). The MyHC IIX level at the end of the study were significantly higher than both the level after training, but also the level before the resistance training period ( Andersen & Aagaard, 2000 ). In a similar study, we found that the MyHC IIX boosting after detraining were accompanied by a parallel increase in RFD in the trained muscles of the subjects ( Andersen et al., 2005 ), however detraining also resulted in a loss in muscle mass that returned to levels comparable to that observed before the training period. This apparent boosting of the MyHC IIX isoform with detraining (and potentially also by tapering) is highly interesting if the goal of a long-term training program is to increase the relative amount of MyHC IIX in the muscle of a specific athlete, typically an athlete competing in an athletic event in which no endurance type of work is necessary, and contractile speed, power and/or explosiveness (RFD) is dominantly favored (e.g. a high- or long jumper). At this point in time we do not know how the muscle will react beyond the experimental period of 3 months, but it can be expected that the level of MyHC IIX will eventually return to the original pre-training value. A least one study with a somewhat different design seems to indicate that this is a likely scenario ( Staron et al., 1991 ).

The question remains, however, if a high relative amount of MyHC IIX in the major skeletal muscles is interesting to other than athlete's participation in very specialised compositions? The fact is that muscle fibers containing predominantly MyHC IIX are also fibers that relay on a metabolism that enables them to produce very high amounts of energy in short time (i.e. exerting very high power), but only over a very limited period of time (seconds) ( Harridge, 1996 Harridge et al., 1996 ). Consequently, the IIX fibers need to rest to avoid exhaustion. Sufficient rest they will not get in any of the major ball sports, or other sports in which continues work over longer periods are need. Thus, fibers containing MyHC IIA might be preferable to athletes that compete in events in which a relative fast but also somewhat enduring muscle is desirable i.e. in 400–1500 m runners, rowers, kayakers, cycling events like sprint and team pursuit etc. Training to meet these conditions is much “easier” to plan than training to provoke fibers to express exclusively MyHC IIX. However, if the intention is to produce a very fast 100 or 200 m sprinter (i.e. targeting the latter training regime) the scheme would roughly be: avoid training involving hours of continues work at a moderate aerobic level, as this type of exercise may lead to an increased number of fibers expressing MyHC I ( Schaub et al., 1989 ) and/or fibers co-expressing MyHC I and MyHC IIA. Further, aerobic exercise may fully or partially blunt the hypertrophic muscle response from concurrent resistance training ( Glowacki et al., 2004 Baar, 2006 Nader, 2006 Coffey et al., 2009 ). Training exercises should comprise high-intensity intermittent work along with substantial amounts of resistance exercise (strength training), the former giving rise to an improved short-term endurance of the type IIA fibers, and the latter giving rise to a preferential hypertrophy in the type II muscle fibers. The end-result will be a muscle with is optimized toward the highest possible relative amount of MyHC IIA at the expense of both MyHC I and MyHC IIX. Needless to say, this scenario favors athletes that have a relatively high amount of type II fibers to begin with. Whether or not these type II fibers contain MyHC IIA or MyHC IIX to begin with is of less importance, since the transformation MyHC IIX→MyHC IIA inherently will be introduced through training.

In many ways it seems trivial to repeat that the training-induced increase in muscle strength and muscle hypertrophy go hand in hand. This have been observed in many long-term studies conducted on human subjects, especially involving subjects with no or limited prior history of heavy load resistance exercise training ( Staron et al., 1991 Adams et al., 1993 Andersen & Aagaard, 2000 Aagaard et al., 2001 ). An interesting aspect of muscle adaptation to strength training, that is sometimes overlooked or toned down, is the background of the individual who is exposed to the training. When planning strength training for a given athlete it is important to know and take into account the training background of the athlete: A certain amount/volume of training might introduce significant muscle hypertrophy in one athlete with no prior strength training experience, whereas another athlete having conducted large amounts of resistance training may experience regular atrophy of his/her muscles if conducting the same amount and type of resistance training that is prescribed for a more inexperienced athlete, simply because the stimulus to his/her muscles and nervous system are less intense than the muscle-CNS signaling that they normally receive. The point here is that we should bear in mind that a very hypertrophied muscle is not in “equilibrium,” and will strive toward a less hypertrophied status if the stimulus to the muscle is lowered or removed.

For muscular hypertrophy to occur a number of things have to happen. After the initial stimuli, being the resistance training, several cellular and hormonal signal pathways will be activated ( Bickel et al., 2005 Bamman et al., 2007 Coffey & Hawley, 2007 ), descriptions of which are beyond the scope of this review. Essentially these signal-pathways govern the processes leading to hypertrophy. Two of the major processes evidentially leading to hypertrophy are (i) increase in muscle protein synthesis ( Kumar et al., 2009 ) and (ii) myogenic satellite cell proliferation ( Kadi et al., 2005 ). Even though hypertrophy only is manifested, or more rightly so measurable, after 4–6 weeks of intensive resistance training from the untrained state ( Seynnes et al., 2007 ), the processes leading to hypertrophy commence already within the first exercise session ( Atherton et al., 2005 ). Although the two processes will be initiated directly after the training session, one will contribute much more to the increase in muscle mass than the other. The increase in protein synthesis is the immediate response of the muscle fibers to the training stimulus received, whereas the activation (proliferation) of satellite cells are trailing somewhat behind, as if the muscle fibers are “waiting” to see if this stimulus are withheld over a longer period, before the costly affair of incorporating new nuclei into the fibers are implemented ( Kadi et al., 2005 Kosek et al., 2006 Seynnes et al., 2007 ).

The muscle mass, or CSA of the individual fibers, is maintained when protein synthesis and muscle protein degradation is in equilibrium. A disturbance in this balance will lead to either muscle hypertrophy or muscle atrophy ( Tang et al., 2008 Kumar et al., 2009 ). Since one of the main the purposes of resistance training frequently is to increase muscle mass obviously it is unfavorable when muscle protein degradation exceeds muscle protein synthesis, as this eventually will result in muscle atrophy. As a matter of fact, muscle protein degradation is increased right after a resistance training session, and the magnitude of degradation may even be bigger than the degree of protein synthesis in the first short period after the training session (a few hours), but provided that the subjects are not in a fasting state the net protein balance (synthesis minus degradation) subsequently becomes positive during the following hours of recovery ( Kumar et al., 2009 ), hence facilitating a hypertrophy response. Furthermore, the increase in synthesis is withheld for a longer period than the increase in protein degradation ( Biolo et al., 1995 ). Thus, the muscle fibers are prepared and will react to resistance training by increasing the net synthesis of contractile (and cytoskeletal) proteins. This is not an inexpensive process, but on the other hand not expensive either in sense that the cellular regulatory machinery is already present and can be set into action right away.

With the onset of fiber hypertrophy the individual muscle fiber increase the myonuclear domain i.e. each nucleus has to serve a lager cytoplasm volume ( Kadi et al., 2004 Petrella et al., 2008 ). It seems that the myonuclei are fully capable of doing this – at least until a certain limit. At some point in the hypertropic process new myonuclei have to be added for cellular hypertrophy to commence, this point in often referred to as the myonuclear domain ceiling ( Kadi et al., 2004 Petrella et al., 2008 ). Although it is probably individual for different muscles, fiber types and persons this myonuclear domain ceiling has been suggested to arrive around a ∼25% hypertrophy of CSA of the muscle fibers ( Kadi et al., 2004 ). At this point new myonuclei, from the pool of quiescent satellite cells, will be added to the muscle fiber to ensure that the hypertropic process can continue. Thus, the muscle seems to have two gears a first reactive gear with an expansion limit, and a second blunt gear with fewer limitations. In the late stage of the hypertropic process the muscle fibers will drive in both gears simultaneously. The interesting part is that the proliferation for the later differentiation of the satellite cells appears to start early in the initiation phase of the resistance-training program, hence preparing the muscle fiber for the situation that may arrive in the future ( Petrella et al., 2008 ).

The plateau in muscle size increase that an athlete often meet typically is around 25% muscle expansion in a intensive hypertropic inducing training program. This plateau or ceiling effect may be related to the individuals ability to activate his/her second “gear-shift,” i.e. to activate the pool of myogenic satellite cells. Thus, in a recent study extreme responders, moderate responders and non-responders were identified according to the hypertrophic effect of a 16-week resistance training program, after which extreme responders (cellular hypertrophy of ∼50%) showed a markedly higher activation (proliferation) of their satellite cells and greater myonuclei addition compared with moderate responders (∼25% hypertrophy) and non-responders (0% hypertrophy) ( Petrella et al., 2008 ). Results as these give us strong hints as to why some athletes may react promptly and strongly to resistance training whereas others don't.

In summary, the MyHC composition of human skeletal muscle seems to be modulated when subjected to resistance training and subsequent detraining. Most pronounced is the significant decrease in the expression of the fastest human skeletal muscle MyHC isoform IIX, with a corresponding increase in the MyHC IIA isoform. It is speculated that the increase in the relative amount of MyHC IIA along with a documented twofold greater hypertrophy of the fast fibers, compared with the slow fibers, as well as the training-induced increase in maximal muscle strength are highly beneficial in a wide range of sports. Likewise, the apparent boosting in MyHC IIX isoform content that seems to occur with detraining following strength training is a phenomenon that should be further examined if the intention is to create a very fast, explosive (albeit non-endurant) type of muscle. In relation to the choice of investing time and efforts in resistance training for a given athlete it is important to closely examine the athletes training background and take into account whether or not the athlete respond with extensive muscle hypertrophy or with almost no hypertrophy. Very recent data indicate that a great deal of difference may exist among different individuals in terms of this particular response, which means that the type and amount of resistance training should be modified accordingly.


The analysis presented here offers lessons both encouraging and cautionary for the use of EMG as an indicator of the timing and magnitude of muscle force. The r-EMD in the turkey LG is relatively constant over a range of running speeds (2–4 m s −1 ), suggesting that for a given muscle EMG timing variables can be constant for a relatively wide range of activities. However, the relatively large difference between the r-EMD for slow walking compared with running suggests that assuming this value to be fixed for a given muscle may be problematic. Our measurements of the relationship between mean EMG amplitude and average muscle force in the LG also indicate that an assumption of a linear relationship between these two variables is justified under some, but not all conditions. When the entire range of swing phase and stance phase forces are considered together, the relationship between mean EMG amplitude and force is nonlinear.

R-EMD—determinants and trends

Because the EMG is the only available measure of muscle activity in many studies, there has been considerable interest in the magnitude of the electromechanical delay and the factors that contribute to it. Most of this work has focused on human subjects, and most of it has investigated the delay between the onset of EMG and the beginning of force development [the activation electromechanical delay (a-EMD)]. Several steps between the depolarization of the sarcolemma (the event measured by EMG) and the production of measurable force by actomyosin cross-bridges can potentially contribute to the a-EMD. It has been suggested that the process of “taking up slack” in the series elastic component represents the majority of the delay, as processes such as the propagation of muscle action potentials and the release of Ca 2+ from the sarcoplasmic reticulum are expected to be quite rapid relative to the EMD typically measured (Cavanagh and Komi 1979). This idea is supported by recent work showing a correlation between a-EMD and the degree of initial strain in the tendon of human triceps surae (Muraoka et al. 2004), and by lower measured a-EMD in the relatively stiff muscles of patients with cerebral palsy (Granata et al. 2000). Similarly, Cavanagh and Komi ( 1979) studied the a-EMD in forearm muscles of human subjects and found it was significantly longer for concentric contractions compared with eccentric or isometric contractions.

Fewer studies have examined the EMD for relaxation. As would be expected from the relatively shorter activation times compared with relaxation times for typical muscle, measured r-EMDs are typically longer than the EMDs for activation (Vos et al. 1990 Ferris-Hood et al. 1996). For example, Ferris-Hood and coworkers (1996) reported r-EMDs ranging from 239 to 300 ms for human knee extensors, much longer than the typically reported values for activation EMDs for voluntary contractions of 35–80 ms.

Comparative studies report a wide range of electromechanical delays for relaxation. Biewener and coworkers (1992) found an r-EMD of 17 ms in starling pectoralis during flight at 13.7 m s −1 . Values for Tamar wallabies’ r-EMD are also slightly shorter than are those of the turkey LG, ranging from ∼32 ms in the plantaris to 43 ms in the LG [based on Fig. 8, (Biewener et al. 2004)]. Values for the ankle extensors of guinea fowl appear to be similar to those of turkeys (∼60 ms, based on reported offset times and stride times for running at 1.3 m s −1 , (Daley and Biewener 2003). The r-EMD for a guinea fowl digital flexor appears to be shorter, ∼30 ms (Daley and Biewener 2003).

What explains the variation in measured r-EMD in different species, and what explains the variation in r-EMD across speed in the turkey LG? The variation in r-EMD within the turkey LG could be simply an artifact resulting from a limited ability to detect very low-level EMG signals. EMG amplitude is lowest at the slowest speeds. Very low-level EMG signals that occur late in force production at the slowest speeds could fall below our threshold for detection, resulting in an overestimate of the r-EMD. If this is the explanation for the trend observed here, our results may be most relevant as a caution for assumptions about a single EMD for EMG signals across a range of activities. Without measurements of force, our measurements of EMG would have led to either an overestimation of the duration of force at fast speeds, or an underestimate of the duration of force at slow speeds, depending on the value for r-EMD that was assumed.

It is also possible that the observed relationship between r-EMD and speed has a physiological basis. Just as shortening velocity (as in taking up slack) can likely influence the EMD for muscle activation, it might be expected that muscle velocity could influence the electromechanical delay for muscle relaxation. A relationship between changes in muscle length and timing of force development could result from the influence of muscle velocity on force output, and/or from the interaction between activation/relaxation processes and changes in muscle length that have been observed in vitro (Gordon et al. 2000). However, our results suggest that the variation in r-EMD with locomotor speed is not explained by variation in the pattern of shortening or lengthening of the muscle, because there is no correlation between fascicle velocity and r-EMD.

Changes in the pattern of muscle fiber recruitment might explain the observed correlation between r-EMD and locomotor speed. A longer r-EMD would be expected for slower types of fibers, as they have lower rates of Ca 2+ cycling and longer relaxation times (Close 1972). This influence of excitation–contraction kinetics likely explains much of the variation in r-EMD between different muscles and different species. For example, during fast flight a starling's entire downstroke phase is <40 ms, a time course that undoubtedly requires fast fibers with very rapid rates of force onset and decay (Biewener et al. 1992). These rapid rates are apparent not only in the Starling's very short r-EMD, but also in the very short activation EMD (∼3 ms for rapid flight, Biewener et al. 1992). Within humans, fiber type has been implicated as one of the factors influencing EMD (Norman and Komi 1979). Slow fibers recruited in the turkey LG at slow walking speeds would be expected to have slower rates of relaxation (and therefore longer r-EMD) than the fast fibers that are added to the recruited pool at faster speeds. The problem with this possible explanation for the pattern of r-EMD observed here is that it would seem to violate Henneman's size principle for the order of recruitment of motor units (Henneman et al. 1974). According to the size principle, slow fibers recruited at slow speeds should continue to be recruited at fast speeds that is, slow fibers are not derecruited as additional fast fibers are recruited. Thus, one would expect that the time from the offset of EMG activity to the offset of force would be dominated by the slow relaxation time course of slower motor units at all speeds. Other studies using arguably more refined methods for inferring motor unit recruitment from EMG signals have found evidence that the order of motor unit recruitment does not always follow the size principle (Wakeling et al. 2002 Hodson-Tole and Wakeling 2007). Further study in this area is warranted.

Integrated EMG area and force

Measures of mean amplitude or area of EMG signals are often reported in studies of muscle function during locomotion (Gillis and Biewener 2002 Konow et al. 2008 McGowan et al. 2006). It is generally assumed that EMG intensity provides a reliable estimate of the volume of recruited muscle, but not necessarily of the developed force. The difficulty in relating amplitude of EMG to amplitude of force lies in the fact that although EMG may give a reliable measure of the volume of active motor units, many factors, including muscle length, velocity, and activation/deactivation kinetics will influence the force an active motor unit produces (Hof 1984 Gabaldón et al. 2008). Indeed, even the assumption that EMG amplitude is related to the volume of muscle recruited has been challenged (Farina et al. 2004). In isometric contractions, the relationship between force and EMG amplitude is usually linear or close to linear and predictable in systems that have been measured, including mammalian masseter (Hylander and Johnson 1989) and human knee extensors (Alkner et al. 2000).

The relationship between average EMG and force during locomotion can be evaluated from comparative studies that provide direct measurements of force from individual muscles. Hedrick and coworkers (2003) reported a strong correlation (R 2 = 0.91) between mean EMG and force for the cockatiel pectoralis over a range of flight speeds. In guinea fowl ankle extensor and toe flexors, the relationship between magnitude of force and EMG during running is more variable (Daley and Biewener 2003). The relationship between EMG and force was found to be significant across running speeds (R 2 = 0.65 and 0.58 for level and incline running, respectively) for the LG, but weak (R 2 = 0.33, level running) or not significant (incline running) for digital flexor IV (Daley and Biewener 2003). One of the determinants of the relationship between EMG and force is the contractile condition of the muscle (Hof 1984). For example, force output should be reduced for a given EMG signal in a muscle when it shortens relative to when it is isometric. This may explain some of the variability in the EMG versus force relationship in, for example, muscles during uphill versus level running (Roberts et al. 1997 Gabaldón et al. 2008).

The results presented here reinforce the challenges associated with estimating force production from the amplitude of the EMG signal. In the turkey LG, the relationship between the amplitude of EMG and the developed force is linear across the range of forces developed during the stance phase of walking and running. However, there is a clear nonlinearity when the relatively low forces and EMG levels produced during swing are included ( Fig. 4). This result illustrates two points relevant to the interpretation of the amplitude of EMG signals.

Given the very low, and in many cases absent ( Fig. 4) EMG trace during the swing phase, measurement of EMG only in this muscle would likely lead to the conclusion that either no or negligible force was developed in the LG during swing phase. Because the amplitude of force for a given level of EMG is much higher during the swing phase as compared with stance, the EMG is not a reliable indicator of the relative force developed during different periods of the stride cycle. The explanation for the relatively high amplitude of force for a given EMG amplitude during swing phase is not fully established, but we hypothesize that it is due to development of passive force by the LG (Roberts et al. 1997). To the extent that muscles develop forces passively during locomotion (in muscle connective tissue elements and sarcomeric spring-like proteins, such as titin), the relation between EMG and force production is further obscured. The pattern of the EMG–force relationship shown in Fig. 5 demonstrates that the conclusion that the muscle develops force passively is not necessarily well-supported by EMG data alone. Because the stance-phase force–EMG relationship during stance phase has a positive y-intercept, the force–EMG relationship must presumably depart from the observed regression at very low levels of force and EMG (as zero force is expected at zero EMG). Thus, based on EMG data alone, an alternative explanation for the very low EMG signals during the swing phase is that the force–EMG relationship at the lowest forces and activities departs from the linear relationship for force and EMG observed for stance phase. A full understanding of the mechanisms underlying these relationships will require further study.


Muscle Contraction Involves the Sliding of the Thick and Thin Filaments Relative to Each Other in the Sarcomere

Measurements of sarcomere and A and I band lengths from electron micrographs of contracted and resting muscle firmly established the mechanism of muscle contraction: The sliding of actin thin and myosin thick filaments passed each other within the sarcomere unit. These measurements demonstrated that the lengths of the individual filaments do not change as a muscle contracts yet, the distance between two adjacent Z disks becomes shortened in contracted muscle relative to relaxed muscle. When the length of a sarcomere decreases in contracted muscle, the I band region shortens, whereas the length of the A band remains unchanged ( Fig. 3-10 ).

Figure 3-10 . Sliding filament model of muscle contraction. Muscle contraction occurs by the sliding of the myofilaments relative to each other in the sarcomere. A: In relaxed muscle, the thin filaments do not completely overlap the myosin thick filaments, and a prominent I band exists. B: With contraction, movement of the thin filaments toward the center of the sarcomere occurs, and because the thin filaments are anchored to the Z disks, their movement causes shortening of the sarcomere. The sliding of thin filaments is facilitated by contacts with the globular head domains of the bipolar myosin thick filaments.

Because the lengths of the thick and thin filaments do not change, the change in length of the I band could occur only if the thin filaments were to slide past the thick filaments. Therefore, the reversed polarity of the thick and thin filaments relative to the center line of the sarcomere (defined by the M line) would cause a shortening of the sarcomere during contraction by the sliding of thin actin filaments, which are attached to the Z disk, past the thick myosin filaments toward the center of the sarcomere. This model of muscle contraction, called the sliding filament model, was first proposed in 1954 and led to the dissection of molecular mechanisms of contraction.

Stretch Reflexes Laboratory Methods

Stretch reflexes are protective reflexes that ensue to avoid damage due to over-stretching a muscle.

Stretch reflexes occur in response to the activation of special sensory receptors in the muscle called &ldquomuscle spindles&rdquo or &ldquostretch receptors.&rdquo

In this lab, students will determine the response time, conduction velocity (speed), and amplitude (strength) of two stretch reflexes: the Achilles reflex at the ankle and the patellar (knee-jerk) reflex.

The velocity of a reflex informs us about the health of the receptors, neurons, and muscles involved in a reflex and can help to diagnose neuromuscular damage or disease.

Equipment Required

  • IXTA data acquisition unit,
  • iWire-B3G ECG cable and electrode lead wires,
  • alcohol swabs,
  • disposable EMG electrodes,
  • PRH 200 reflex hammer with BNC connector

Experimental Set-Up: Start the Software

  • Turn on the iWorx hardware with the switch on the back of the unit.
  • Double click the Week6 StretchReflex settings file from the p-drive.

EMG Cable and Reflex Hammer Setup

  • Use an alcohol swab to clean and abrade three regions on the lower portion of the left leg for electrode attachment. One area is posterolateral near the knee (see Methods Figure 1), the second is posterolateral on the calf muscles, and the third area is on the lateral side of the ankle that functions as the ground. Let the areas dry.
  • Remove the plastic disk from a disposable electrode and apply it to one of the abraded areas. Repeat for the other two areas.
  • The RED (+1) lead wire is attached to the electrode laterally, near the back of the knee. Flex your calf muscle to make sure the electrode is placed on the muscle.
  • The BLACK (-1) lead wire is attached to the electrode in on the lateral aspect of the gastrocnemius (calf) muscle. Flex your calf muscle to make sure the electrode is placed on the muscle.
  • The GREEN(C) lead wire is attached to the electrode on the lateral side of the ankle that functions as the ground. Make sure the electrode is placed laterally as you will strike the calcaneal tendon (Achilles Tendon).

What Are Muscles?

The muscular system consists of all the muscles of the body. Muscles are organs composed mainly of muscle cells, which are also called muscle fibers. Each muscle fiber is a very long, thin cell that can do something no other cell can do. It can contract, or shorten. Muscle contractions are responsible for virtually all the movements of the body, both inside and out. There are three types of muscle tissues in the human body: cardiac, smooth, and skeletal muscle tissues. They are shown in Figure below and described below.

Types of Muscle Tissue. Both skeletal and cardiac muscles appear striated, or striped, because their cells are arranged in bundles. Smooth muscles are not striated because their cells are arranged in sheets instead of bundles.

Smooth Muscle

Muscle tissue in the walls of internal organs such as the stomach and intestines is smooth muscle. When smooth muscle contracts, it helps the organs carry out their functions. For example, when smooth muscle in the stomach contracts, it squeezes the food inside the stomach, which helps break the food into smaller pieces. Contractions of smooth muscle are involuntary. This means they are not under conscious control.

Skeletal Muscle

Muscle tissue that is attached to bone is skeletal muscle. Whether you are blinking your eyes or running a marathon, you are using skeletal muscle. Contractions of skeletal muscle are voluntary, or under conscious control. When skeletal muscle contracts, bones move. Skeletal muscle is the most common type of muscle in the human body.

Cardiac Muscle

Cardiac muscle is found only in the walls of the heart. When cardiac muscle contracts, the heart beats and pumps blood. Cardiac muscle contains a great many mitochondria, which produce ATP for energy. This helps the heart resist fatigue. Contractions of cardiac muscle are involuntary, like those of smooth muscle. Cardiac muscle, like skeletal muscle, is arranged in bundles, so it appears striated, or striped.