It is often suggested that stretching-related changes in performance Behm et al. Indeed, although it has been extensively reported that muscle stretching induces several neuromuscular responses For review Budini and Tilp, , H-reflex and motor evoked potential return to baseline values within seconds Guissard et al.
However, this inhibition cannot be attributed to changes in the reflex loop, but rather to a thixotropy effect within the muscle spindles that reduces their sensitivity with a consequent decrease of Ia afferents activity Proske et al. Therefore, this long-lasting inhibition seems to have a mechano-morphological rather than a neural nature. Regardless of its nature, a decreased muscle spindle sensitivity does have neural implications. It has long been known, in fact, that afferents from muscle spindles contribute in various ways to different voluntary muscle contractions Vallbo, ; Burke et al.
A paper by Dietz et al. Another study by Meunier and Morin demonstrated that both homonymous and heteronymous Ia facilitations are markedly increased at the beginning of a voluntary isometric contraction Meunier and Morin, The contribution of spindles afferents to contraction is also in relation to agonist heteronymous decrease of presynaptic inhibition on Ia homonymous afferents, with simultaneous increase of presynaptic inhibition of Ia in the antagonist Hultborn et al.
Consequently, muscle stretching could be detrimental to muscle performance. Indeed several studies reported a decrease in maximal static and dynamic force following stretching for review Behm and Chaouachi, and in this respect a decreased contribution of spindle afferents to the contraction could be imputed as one of the possible underlying mechanisms.
However, the relevance to sport practice of these studies is limited because most research works have adopted stretching protocols of over 30 s duration Rosenbaum and Hennig, ; Weir et al. These procedures are very different to standard stretching practice in sport. Another element that cannot be fully elucidated and that would be relevant to sport performance is the duration of the effect.
It is known that even short duration stretching bouts 2 times 30 s inhibit tap reflex for several seconds Budini et al. Other studies reported a full recovery within 5—10 min following the stretching procedure Budini et al. In conclusion, to date it is not clear for how long muscle spindle sensitivity is reduced following a stretching exercise like those adopted commonly in sport practise around 30 s static stretching per muscle group.
Moreover, it is not known whether a voluntary muscle contraction is sufficient to fully restore muscle spindle sensitivity. On the other hand, dynamic contractions, in the form of counter movement jumps CMJs are already commonly adopted in warm up routines, and also in this case we could expect a similar reflex recovery based on the same mechanism.
However, both these assumptions have to be examined. Therefore, in the present work we investigate the effects of a single 30 s triceps surae stretching exercise on tap reflex inhibition and its recovery during the following 10 min in three different conditions: with an MVC following stretching, with three CMJs following stretching and without any contraction. Fifteen recreationally active students 7 male age Volunteers were required to abstain from any strenuous physical activity before the testing day and, due to the known effects of nicotine Ginzel et al.
The study was approved by the local research ethics board and written informed consent was obtained from all volunteers before the onset of the experimental procedures. Participants attended the laboratory on a single occasion lasting about 90 min. The experiment consisted of measuring the tap reflex before and after stretching of ankle plantar flexors with three different interventions isometric contraction, dynamic contraction and no contraction in between the before and after stretching assessments.
In this arrangement the backside and the heel of the tested foot were close fitting against fixed ends seatback and dynamometer footplate , consequently, being the knee fully extended, any slide in the sitting position was not possible. This placement allowed us to have the volunteer to stand up from the dynamometer chair and come back to the same testing position. By using a remote control, the volunteers were instructed to adjust the dorsiflexion isokinetic rotation operated by the dynamometer around the foot plate until the point of perceived maximal dorsiflexion.
Participants were asked to keep their knee extended and to relax during the procedures. Once the maximal individual dorsiflexion was defined, subjects left the dynamometer and were prepared for electromyographic recording EMG from soleus SOL and gastrocnemius medialis GM muscles.
Subsequently, the volunteers sat down again on the dynamometer chair position described above and were then instructed to relax completely and gaze horizontally at a point set 4 m distant.
After 30 s sitting in testing position the first tap reflex was evoked, further nine reflexes were induced with intervals of 30 s. Before the first tap reflex post-stretch was evoked, one of three interventions was introduced: control, 3 s maximal isometric contraction of the stretched plantar flexors, or three counter movement jumps. Thirty seconds after the intervention, the collection of tap reflexes started again and continued for 10 min with one reflex elicited every 30 s; in this way it was possible to collect data at 20 different time points.
The complete procedure was repeated a second and third time so to complete the remaining interventions. Between one complete pre-post stretch measurement and the next, the volunteers were asked to stand up for 2 min. The order of the interventions was randomized. A flow chart of the experimental sequence is presented in Figure 1.
Tendon tap reflex was elicited by a hammer driven by motor Type GDRX , Magnet-Schultz, Germany hitting the Achilles tendon about 3—4 cm above its insertion on the calcaneus. An electrical output from the motor provided information about its rotation allowing hammer hitting consistency to be monitored. Electromyography, foot displacement, torque and trigger signals were synchronized Dewetron 7.
Tap reflexes were estimated as reflex peak to peak amplitude of the raw EMG signal. Peak torque was evaluated as the peak in the torque response produced by the reflex.
Mean values and standard deviations of tap reflexes and peak torque data are reported. Sex differences at baseline before stretching were checked by 2-sample t -test. To account for the great individual variability of the reflex values, the individual mean values of all 21 measures within the subjects were subtracted from each value. Skip to content. Your knee jerks suddenly. Muscle spindles are skeletal muscle sensory receptors — a type of proprioceptor, which is a sensor that lets you do things like touch your finger to your nose when your eyes are closed, or play guitar without looking at the fretboard.
The work may alter long-established views of muscle spindles, how they work, and how they affect people with neurological challenges and other movement issues. In general, the idea established over the past 50 years or so, according to Ting, is that muscle spindles fire in response to, or encode, the length and velocity of the muscle. Developing a mechanistic framework for understanding how muscle spindle organs generate the complex sensory signals during natural movements is critical for understanding muscle spindle sensory signals and how they change under different behaviors, in neurological disorders, and during interactions with devices or interventions to improve motor impairments.
Existing computational models of muscle spindle afferent firing have largely been data-driven, with well-known experimental features represented phenomenologically Schaafsma et al. Such models have high fidelity under the conditions in which the data were collected, but generalize poorly to more naturalistic conditions. The anatomical arrangement of the muscle and muscle spindle have also been shown in simulation to affect the forces on the muscle spindle and alter muscle spindle firing properties Lin and Crago, The biomechanical properties of the intrafusal muscle fibers within the muscle spindle have also been implicated in determining muscle spindle receptor potentials Blum et al.
Here, we take a biophysical modeling approach to build a muscle spindle model based on first principles of intrafusal muscle contractile mechanics, along with its interaction with the muscle and tendon to predict both classic and seemingly paradoxical muscle spindle Ia afferent firing during passive and active conditions.
We first establish a relationship between muscle spindle firing characteristics and estimated intrafusal fiber force and its first time-derivative, yank Lin et al. We then build a generative model based on a simple representation of intrafusal muscle mechanics, revealing that several classic muscle spindle firing characteristics emerge from muscle cross-bridge population kinetics.
The independent effects of alpha and gamma drive on muscle spindle firing were then simulated based on mechanical interactions between the muscle spindle and the muscle-tendon unit. Highly variable muscle spindle activity observed during human voluntary isometric force generation and muscle stretch—from silent to highly active—could be explained by as a result of interactions between the muscle spindle and musculotendon unit, central activation of extrafusal alpha drive versus intrafusal muscle fibers gamma drive , and muscle length change.
These multiscale interactions may explain why muscle spindle activity may roughly approximate muscle force, length, velocity, acceleration, activation level, or other variables under different movement and experimental conditions. As such, our model establishes a biophysical framework to predict muscle spindle afferent activity during natural movements that can be extended to examine multiscale interactions at the level of cell, tissue, and limb mechanics.
We first demonstrated that in passive stretch of relaxed rat muscle, muscle spindle Ia afferent firing rates can be described in terms of extrafusal muscle fiber force and yank.
We recorded muscle spindle afferent axonal potentials and computed instantaneous firing rates IFRs in anesthetized rats while stretching the triceps surae muscles Figure 1. In the relaxed condition, that is in the absence of central drive to the muscles, we assumed that extrafusal muscle fiber forces provide a reasonable proxy for resistive forces of the intrafusal muscle fibers within the muscle spindle mechanosensory apparatus Figure 1.
We previously demonstrated that whole musculotendon force in rat experiments is not predictive of muscle spindle IFRs Blum et al. We modeled the extracellular tissue forces using a nonlinear elastic model and identified the parameters that minimized the prediction error of muscle spindle firing rates based on estimated extrafusal muscle fiber force and yank see Materials and methods.
The initial rise in extrafusal muscle fiber force at the onset of stretch Figure 1 , red trace manifests as a large, transient yank signal Figure 1 , blue trace and became more apparent once the extracellular tissue forces were subtracted from whole musculotendon force.
Ia afferent firing rates were recorded from dorsal rootlets during stretches of the triceps surae muscle in anesthetized rats.
Muscle fiber forces were estimated by subtracting noncontractile forces from measured whole musculotendon force. The exponential rise in force with stretch was assumed to arise from non-contractile tissue in parallel with the muscle-tendon unit with exponential stiffness Blum et al.
The remaining estimated muscle fiber force and yank exhibited similar temporal characteristics to the muscle spindle IFR. Intrafusal muscle fiber force and yank were then simulated using a cross-bridge based model to predict muscle spindle IFRs. Like in cats Blum et al. We assumed average extrafusal fiber force to be proportional to intrafusal muscle fiber force in the anesthetized, passive stretch condition only.
The notable features of muscle spindle Ia afferent firing reconstructions included initial bursts, dynamic responses during ramps, rate adaptation during holds, and movement history-dependent firing Figure 2A—C ; Figure 2—figure supplement 1.
The reconstructions revealed history-dependent initial bursts in Ia afferent firing coincide with large, history-dependent yank component in estimated extrafusal muscle fiber force Figure 2B. The dynamic Ia afferent firing response during ramp stretches was primarily reconstructed by the force component Figure 2C and was larger during the first stretch of a repeated sequence Figure 2B.
Rate adaptation during the hold period was reconstructed by the force component in both slow and fast stretches Figure 2C ; Matthews, A Estimated driving potentials were derived from linear combinations of muscle fiber force and yank, half-wave rectified, and compared against recorded muscle spindle Ia afferent firing rates.
Weights of each component were optimized to match recorded spiking dynamics. B Recorded muscle spindle Ia afferent firing rates gray dots in history-dependent conditions, having non-unique relationships to muscle length and velocity, were reproduced using muscle fiber force and yank black lines.
Notably, the initial burst and increased firing during ramp in the first stretch were attributed to increased muscle fiber yank and to greater force during the first stretch, respectively. C Likewise, muscle fiber force and yank could also account for the temporal dynamics of Ia afferent firing in response to both slow and fast stretches.
D This model permits independent manipulation of the force and yank contributions to muscle spindle firing rates. As such, we can explain the altered muscle spindle Ia afferent firing patterns in E oxaliplatin chemotherapy-induced sensory neuropathy as a loss of force sensitivity, and F after antidromic electrical stimulation of the axon as loss of yank sensitivity.
We then demonstrated that the sensitivity of Ia firing to passive muscle fiber force and yank was differentially affected by two types of perturbation to the muscle spindle afferent neuron. Estimated extrafusal muscle fiber force- and yank-based reconstruction of Ia firing rates was robust to experimental perturbations due to either oxaliplatin chemotherapy OX alone or intra-axonal antidromic stimulation of the afferent STIM.
While the mechanisms underlying these perturbations are undetermined, the effects on firing likely involve alterations in function of ion channels in the nerve terminal function as opposed to effects on properties of non-neural tissues, for example muscle. Bullinger et al. Accordingly, the characteristics of the estimated intrafusal muscle fiber force and yank were qualitatively similar in intact and OX rats, suggesting there was no change in muscle fiber force in the OX animals.
However, muscle spindles in healthy rats treated with OX maintain an initial burst and dynamic response, but lack sustained firing during the hold period Figure 2D vs Figure 2E ; Figure 2—figure supplement 2 ; Bullinger et al.
These OX Ia afferent firing phenotypes were primarily reconstructed by the yank component Figure 2D , blue trace , with a small contribution of the force component Figure 2D , red trace; Figure 2—figure supplement 2 , suggesting a reduced sensitivity of the muscle spindle afferent to intrafusal muscle fiber force.
Conversely, when we perturbed the Ia afferent in healthy rats through intra-axonal electrical stimulation STIM; ms duration, Hz train of 30nA pulses and applied muscle stretch immediately afterward Figure 2F ; Figure 2—figure supplement 3 , STIM Ia afferent firing phenotypes were primarily reproduced by the intrafusal fiber force, with reduced sensitivity to the intrafusal fiber yank Figure 2—figure supplement 3.
Overall, we were able to reproduce perturbed Ia afferent firing data by varying only the relative weighting of force and yank. Taken together, these data show that in the absence of changes in intrafusal or extrafusal muscle fiber force and yank signals, the sensitivity of the muscle spindle Ia afferent to force and yank can be decoupled and therefore may arise due to separate encoding or transduction mechanisms. The differential effects of oxaliplatin and axonal stimulation on spindle firing rates led us to hypothesize there is a degree of independence in the transduction of force and yank in the spindle.
We further tested this hypothesis by simulating Ia afferent firing arising from force- and yank-based receptor driving potentials Figure 3A ; see Materials and methods. Nominal sensitivities of the model receptor current closely related to driving potential were chosen to reproduce a typical recorded muscle spindle firing rate during passive stretch Figure 3B , green shaded box.
We then generated a family of muscle spindle firing phenotypes Figure 3B , blue dots by systematically varying the sensitivity of receptor currents Figure 3 , thin black lines to the same muscle fiber force Figure 3B , vertical axis and yank signals Figure 3B , horizontal axis during the same muscle stretch Figure 3B.
A Sensitivity to experimentally-derived force and yank was systematically varied for a single stretch and resultant driving potentials were input to a Connor-Stevens model neuron to generate firing patterns.
B Nominal force and yank weights were identified to recreate experimentally-recorded muscle spindle response to a representative stretch green box. Increasing sensitivity to yank left to right generated larger initial bursts and dynamic responses during the ramp, and resembled responses from oxaliplatin-treated specimens at the highest yank and lowest force sensitivities orange boxes, compare to Figure 2E. Increasing sensitivity to force top to bottom generated higher firing rates during the hold period and resembled Ia afferent firing responses after axonal stimulation at the lowest yank and highest force sensitivities red boxes, compare to Figure 2F.
Varying the weights of the force and yank sensitivities could recreate the spectrum of healthy muscle spindle firing profiles reported classically purple boxes. Varying force- and yank- sensitivity generated diverse muscle spindle firing phenotypes similar to those observed experimentally — including the OX and STIM phenotypes. The firing profiles with high yank and lowest force sensitivity resembled the OX firing phenotype Bullinger et al.
We concluded that independently varying Ia afferent sensitivity the input-output gain to force and yank explains a spectrum of spindle firing phenotypes. We next built a biophysical model of muscle spindle mechanics to more directly predict intrafusal fiber force and yank during muscle stretch conditions where experimental data are not readily available.
History-dependent muscle forces have been simulated previously based on muscle cross-bridge population cycling kinetics Campbell and Lakie, ; Campbell and Moss, ; Campbell, ; Campbell and Moss, , but no current muscle spindle model has incorporated these principles, and thus none simulate history dependence in muscles spindle Ia afferent firing Hasan, ; Lin and Crago, ; Mileusnic et al.
While different intrafusal muscle fibers vary morphologically and mechanically, as well as in their contributions to Ia firing patterns, their basic architectures are similar Banks et al.
Intrafusal muscle fibers are innervated by gamma motor neurons in two polar regions containing contractile muscle fibers, with an in-series non-contractile equatorial region around which the muscle spindle endings are wrapped and mechanotransduction occurs. Muscle spindle Ia receptor potentials and afferent firing are directly related to deformation of the equatorial regions Boyd, ; Boyd et al.
Our mechanistic muscle spindle model consists of a pair of half-sarcomere muscle models arranged in parallel, simulated using two-state actin-myosin population interactions Campbell, The dynamic fiber model was designed with slower myosin attachment rates Thornell et al.
Length changes to the spindle were applied to both fibers equally. We assumed the receptor driving potential of the Ia afferent receptor ending to be proportional to a weighted combination of force and yank of the intrafusal fibers based on visual inspection of intrafusal force recordings and our previous hypotheses of intrafusal force and yank encoding Blum et al.
This was based on the idea that the intrafusal mechanosensory nuclear regions stretch linearly with intrafusal force Matthews, ; Schaafsma et al. A The muscle spindle model consists of two muscle fibers in a parallel mechanical arrangement, loosely representing intrafusal bag and chain fibers. C A population of myosin cross-bridges and their relative displacement and velocity with respect to active actin binding sites was simulated during three consecutive ramp-stretch-release stretches.
The distribution of cross-bridge lengths relative to actin binding sites is shown at different timepoints of imposed kinematics numbered graphs and timepoints.
The length of the dynamic and static fibers lower trace and the stress in the dynamic and static fibers middle trace is shown. Deviations between applied length and muscle fiber length occur due to muscle fiber slack. Our mechanistic model predicted a spectrum of muscle spindle firing phenotypes identified in passive stretch conditions by varying the sensitivity gain of driving potentials to biophysically predicted intrafusal fiber force and yank Figure 4B.
The predicted muscle spindle firing phenotypes closely resembled biological firing phenotypes discussed earlier. As a result of our chosen kinetic scheme, history-dependent forces emerge within our simulated intrafusal muscle fibers from cross-bridge population dynamics Figure 4C.
When the muscle is at rest, the spontaneous formation and breakage of cross-bridges is at steady-state equilibrium Figure 4C , time 1. As soon as a stretch is applied, the population of attached cross-bridges is also stretched, resulting in a short period of high-stiffness force response, known as short-range stiffness Figure 4C , time 2; Lakie and Campbell, Once these cross-bridges are stretched to their limits, they break and a new attachment equilibrium is reached during the remainder of stretch Figure 4C , between times 2 and 3.
If the muscle is shortened back to the original length, the cross-bridges will shorten Figure 4C , time 4 — note the distributions shift leftward. In this case, the force in the fibers will decrease until the fibers are slack Figure 4C , time 5 , at which point the cross-bridges will shorten the muscle fibers against zero load until the slack length is reduced to zero, or another stretch is applied Figure 4C , time 6.
If the fibers are not given enough time to return to steady-state equilibrium e. Figure 4C , time 1 , a stretch will result in qualitatively different, history-dependent force and yank responses. A truly general model of a muscle spindle would predict firing properties across different experimental contexts without any fundamental changes to the model structure or parameters.
Using a single, nominal set of parameters in our muscle spindle model, we tested whether a variety of classical muscle spindle firing characteristics during passive stretch would emerge, including: fractional power relationship with stretch velocity Matthews, , history-dependence Haftel et al. To demonstrate the ability of the mechanical signals themselves to predict the properties observed in Ia afferent firing rates, we examined simulated driving potentials rather than creating additional degrees of freedom in our model with a spike generating process.
In our model, the scaling properties of muscle spindle dynamic responses and initial bursts with increasing velocity during passive muscle stretch arise from intrafusal cross-bridge kinetics. More specifically, the strain dependence of the cross-bridge detachment rates produces force profiles that contain linear increases in short-range stiffness and sublinear increases in force dynamic response as a function of stretch velocity.
In a series of constant velocity stretches relative to optimal muscle length, L 0 0. We predicted a sublinear increase in dynamic index with stretch velocity, emergent from intrafusal mechanics, resembling the classically reported fractional-power velocity relationship in muscle spindle firing rates Figure 5C ; Houk et al. Initial burst scaling was emergent from intrafusal muscle fiber yank at the onset of stretch due to the elasticity of attached cross-bridges that then detach rapidly after being stretched a small fraction of L 0 Hasan and Houk, ; Matthews and Stein, To our knowledge, neither of these phenomena has been previously demonstrated to arise from the same mechanistic model.
Simulations assume a low level of muscle cross-bridge cycling consistent with relaxed muscle. Length displacements were imposed on the muscle fiber.
A Predicted driving potentials upper traces during ramp stretches of varying velocity and acceleration lower traces. B Classical data showing Ia afferent firing modulation with different stretch velocity Matthews, C Dynamic index emergent from cross-bridge mechanisms. Dynamic index is defined classically as the ratio of firing rate at the end of the ramp phase and the firing rate 0.
The muscle spindle model exhibits a sublinear relationship between dynamic index and stretch velocity middle plot — colors correspond to A , similarly to classical findings bottom plot. E Linear acceleration scaling of initial burst emergent from cross-bridge mechanisms. Initial burst amplitude is defined as the difference between peak firing rate during initial burst and baseline.
These images are not covered by the CC-BY 4. Our biophysical model predicted history-dependent changes in the muscle spindle firing initial burst and dynamic response analogous to those previously reported in acute cat, rat, and toad experiments as well as in microneurographic recordings in awake humans Blum et al. In our model, these features emerged from the asymmetry present in strain-dependent cross-bridge detachment rates. In three consecutive, identical stretches, the biophysical muscle spindle model predicted an initial burst and elevated dynamic response on the first, but not second stretch Figure 6A.
In the third stretch, the amplitude of the simulated driving potentials recovered asymptotically as the time interval between stretches increased to 10 s Figure 6A , resembling the recovery of spike counts during the dynamic response in rats Figure 6B ; Haftel et al. Our model predicted an initial burst at the onset of sinusoidal muscle stretches Figure 6C , similar to that seen in microneurographic recordings from awake humans Figure 6C ; Day et al.
Although a cross-bridge mechanism has been proposed previously based on experimental findings Haftel et al. A When repeated stretch-shorten length cycles were applied, a larger response was predicted if the length was held constant prior to stretch bottom plot — all traces.
An abolished initial burst and reduced dynamic response were predicted in the second stretch, immediately applied after the length was returned to the initial value top plot — all traces. In the third stretch, recovery of the initial burst was dependent on the time interval between the second and third stretch, with the effect saturating between 5 and 10 s top plot, recovery from violet to red traces.
This finding predicts the results found by Haftel et al. Similarly, dynamic response recovered gradually with time interval between second and third stretch top plot, recovery from violet to red traces. This finding predicts the results found by Proske and Stuart, in toad muscle spindles. B Sinusoidal displacement imposed from rest elicited a history-dependent initial burst in the predicted muscle spindle driving potential at the onset of stretch, resembling data from C human muscle spindles recorded during the application of sinusoidal motion to the ankle in relaxed conditions Day et al.
Figure 6C is redrawn from Day et al. We tested whether previously-reported effects of gamma motor neuron activity on muscle spindle afferent firing characteristics during passive muscle stretch conditions were also emergent from our biophysical model.
Dynamic and static gamma motor neurons innervate the static and dynamic intrafusal muscle fibers within the muscle spindle, respectively. To simulate classic experiments in which dynamic and static gamma motor neurons were electrically stimulated in anesthetized animals, we independently increased the number of available actin-binding sites in simulated intrafusal static and dynamic muscle fibers Figure 7A. Consistent with many prior experimental findings, simulated dynamic gamma drive increased the force and yank of the dynamic fiber during stretch, predicting increased receptor driving potentials underlying initial burst and dynamic responses, with proportionately smaller increases in baseline muscle spindle driving potentials Boyd et al.
In contrast, simulated static gamma drive primarily increased baseline muscle spindle driving potentials, and had much smaller effects on driving potentials underlying the initial burst and dynamic response during stretch Figure 7A—B ; Crowe and Matthews, a ; Boyd et al. Even the previously reported increases and decreases in dynamic index as a result of dynamic versus static fiber stimulation, respectively, Figure 7C left plot; Crowe and Matthews, a ; Crowe and Matthews, b were predicted by our model Figure 7C right plot.
Fusimotor activity was imposed on either the dynamic or the static fiber by increasing the number of active actin binding sites in the appropriate fiber. A Simulated dynamic fiber activation increased the driving potential predominantly during the ramp, with smaller increases during the background and hold period top traces.
Simulated static fiber activation predominantly increases the driving potential rate during the background and hold period, with only modest increases in during the ramp. B Emergent scaling of the dynamic index with dynamic increase in dynamic index and static fiber activation decrease in dynamic index resembled trends reported previously in the literature with C dynamic index increasing with bag fiber activation, and dynamic index decreasing with chain fiber activation, respectively.
To simulate how alpha and gamma drive affect muscle spindle Ia afferent firing during voluntary movement, we simulated the peripheral mechanical interactions of the biophysical intrafusal muscle fiber above within extrafusal muscle-tendon dynamics.
We modeled the muscle spindle and extrafusal muscle-tendon dynamics while the total end-to-end length was held constant to simulate isometric muscle contractions Dimitriou, ; Edin and Vallbo, ; Figure 8. All the force on the tendon was generated by the extrafusal muscle fibers, as the intrafusal muscle fiber was assumed to generate negligible force.
We constrained the end-to-end lengths of the intrafusal and extrafusal muscle fibers to be the same. However, muscle fibers were allowed to go slack based on their own properties, meaning the true fiber lengths were not necessarily equal when slack was present in one or more fibers.
Alpha drive was simulated by activation of the extrafusal muscle fiber and gamma drive was simulated by activation of the intrafusal muscle fiber Figure 8A. In addition, experimental studies do not support the hypothesis that irregular sustained action potentials like EPSs be activated by peripheral nerve injury or irritation [ 10 , 11 , 12 ].
To discuss the origin of EPSs, we have to look at the physiological properties of the muscle spindle. Human muscle spindles are 7—10 mm long fusiform fluid-filled capsulated organs with equatorial A and polar B regions. The capsule of the muscle spindle is a lamellated structure, which prevents the diffusion of extrafusal substances into the intrafusal periaxial space [ 13 ].
The mean thickness of the capsule is 1. The periaxial space is between the outer and inner capsule of the spindle and it is full of highly viscous gel. This may contribute to the excitability of the intrafusal endings. There are three types of intrafusal muscle fibres such as nuclear bag 1, nuclear bag 2 and nuclear chain fibres. One spindle has usually one bag 1 fibre, one bag 2 fibre and 4—7 nuclear chain fibres [ 13 ]. The muscle spindles are mainly distributed at the region of nerve entry into the muscle and around the subdivisions of the intramuscular nerves [ 13 ].
The distribution is thus different from that of the end plate zone, which usually is a relatively narrow band around muscle belly [ 15 ]. The main spindle artery is separated from those supplying extrafusal muscles, and in intrafusal capillaries, there is a blood nervous system barrier in both endoneurial and periaxial spaces [ 13 ]. The extrafusal capillaries are different and have efficient perfusion when compared to the intrafusal ones. Removal of substances which accumulate into the gel-filled periaxial space of the muscle spindle is a slow process.
The sensory innervation of a muscle spindle consists of primary and secondary endings [ 13 ], and also III- and IV-afferents [ 16 , 17 , 18 , 19 ]. Also, autonomic innervation has been observed [ 19 , 20 ]. The motor innervation consists of fusimotor gamma and skeletofusimotor beta nerve axons, both of which also have dynamic and static components. They adjust the responses of the primary and secondary endings to the length and changes in the length of the muscle [ 21 ]. Dynamic gamma neurons innervate the bag 1 fibre by a p2 plate ending.
Static gamma neurons innervate the bag 2 fibre and chain fibres by the trail endings. Dynamic skeletofusimotor beta neurons innervate the bag 1 fibre and extrafusal slow oxidative type 1 muscle fibres by p1 plate endings.
Static beta neurons innervate the long chain fibres and extrafusal fast oxidative type 2 muscle fibres by p1 plate endings [ 13 ].
Each spindle receives about 7 motor axons, mean 3. The bag 1 fibre is almost always separately innervated by dynamic beta and gamma axons.
Static beta branches supply exclusively the long chain poles. The bag 2 and chain fibres may receive a completely or variously segregated input in each pole [ 13 ]. Where is the origin of EPSs if they are not nerve potentials or postsynaptic muscle fibre action potentials, activated by peripheral nerve injury? Partanen and Nousiainen [ 22 ] suggested that EPSs are action potentials of intrafusal muscle fibres such as small nuclear bag and nuclear chain muscle fibres inside the muscle spindles.
EPSs can also be observed in active sites after manoeuvres for activating the gamma and beta motor activity such as passive stretch of the muscle, voluntary effort and repetitive nerve stimulation [ 9 ].
If multichannel EMG recordings are used, there are also different propagation patterns of EPSs such as local junction potentials as those observed in nuclear bag fibres [ 23 ], propagation for a very short distance as in nuclear chain fibres and propagation like MUPS but with the EPS firing pattern, as in beta skeletofusimotor motor units [ 9 , 24 , 25 ].
EPSs were also conjectured to be confined to the end plate zone of a muscle [ 26 ]. In fact EPSs can be found far from the end plate zone [ 9 , 27 ]. It is a misconception that MEPPs are observed solely at the end plate zone, where the extrafusal neuromuscular junctions are situated [ 26 ]. Actually, MEPPs which are found far from the end plate zone, are mostly intrafusal representing synaptic activity of motor p2, p1 and trail endings.
Each pole of the muscle spindle receives 4—5 different motor axons and each gamma or beta axon innervates several spindles, but in a selective manner [ 13 ].
Thus junction and action potentials arise in several different spindles, when gamma and beta motor units are activated. This can also be seen in multichannel needle EMG recording. Synchronously firing EPSs may be found in remote active sites of a muscle, if these sites are innervated with the same gamma motor unit [ 27 ].
If EPSs in different remote active sites of a muscle are not innervated by the same gamma motor units, EPS firing is asynchronous. EPSs cannot be activated voluntarily, but voluntarily stopping of this activity is possible [ 27 , 29 ]. Active spots with EPSs can also be stimulated with the concentric needle electrode, using electric impulses. With such stimulation, a reflex response resembling a myotatic reflex can be recorded [ 27 ].
Stimulation of an active spot with very small electric stimuli yields a response on another active spot, and even late responses resembling F-waves. Thus, muscle spindles are electrically active structures in EMG, working in a network of gamma and beta motor units and having specific reflex responses [ 27 ].
In clinical EMG, EPSs may be confused with fibrillation potentials, which are spontaneous action potentials of muscle fibres, or pieces of muscle fibres, which have lost contact with their motor axons.
The development of fibrillation potentials needs time and there may be both rhythmic and irregular fibrillation sequences [ 30 ].
However, fibrillation potentials are distinctly different from EPSs both by the wave form and by the firing properties [ 9 ]. The essential difference between EPSs and fibrillation potentials is the fact that denervation causes prolongation of the refractory period of the muscle fibre and thus the fibrillation potential cannot recur as promptly as action potential in a normal muscle fibre [ 33 ].
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