Download Distinguishing intrinsic from extrinsic factors underlying firing rate

J Neurophysiol 113: 1310 –1322, 2015.
First published December 4, 2014; doi:10.1152/jn.00777.2014.
Distinguishing intrinsic from extrinsic factors underlying firing rate saturation
in human motor units
Andrew J. Fuglevand, Rosemary A. Lester, and Richard K. Johns
Department of Physiology, College of Medicine, University of Arizona, Tucson, Arizona
Submitted 6 October 2014; accepted in final form 1 December 2014
firing rate; force; motor neuron; motor unit; saturation
(MNs) represent the final processing stage
within the mammalian central nervous system, the site at which
synaptic signals are ultimately transformed into overt motor
behaviors. MNs receive a complex array of synaptic inputs and
have long been thought to generate action potentials at firing
rates proportional to the net excitatory synaptic drive (Granit et
al. 1966; Heckman and Binder 1991a; Kernell 1969; Kernell
and Sjöholm 1973; Powers et al. 1992; Schwindt and Calvin
1973). Each action potential generated by a MN is replicated
with near perfect fidelity in the hundreds of skeletal muscle
fibers innervated by each MN, causing these muscle fibers to
contract as a group. The MN and its innervated muscle fibers
therefore comprise a functional entity called a motor unit
(MU). The contractile force exerted by a MU, in turn, varies
precisely as a function of the firing rate of the MN. In this way,
the intensity of neural activity delivered synaptically to MNs is
transduced into the constituent mechanical signals that operate
on tendon and bone.
MOTOR NEURONS
Address for reprint requests and other correspondence: A. J. Fuglevand,
Dept. of Physiology, PO Box 210093, Univ. of Arizona, Tucson, AZ 857210093 (e-mail: [email protected]).
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Because it is relatively easy to record the discharge of MUs
(and hence, MNs) in awake human subjects, the relation
between naturally occurring synaptic input and firing rate
responses in MNs can be indirectly assessed. Furthermore,
detailed computer models of MU populations have shown
isometric muscle force to be a monotonically increasing function of the net excitatory synaptic drive (Fuglevand et al. 1993;
Heckman and Binder 1991a). This means that isometric muscle
force can serve as a coarse indicator of synaptic excitation
during voluntary muscle contraction. This in turn enables, at
least to a first approximation, assessment of the relation between natural synaptic input and spike-frequency output in an
unanesthetized, fully intact subject.
Interestingly, when MU activity is recorded during experiments in which human subjects progressively increase the
strength of an isometric contraction, a marked nonlinearity in
the relation between firing rate and synaptic drive (as inferred
from muscle force) is often exhibited. Specifically, firing rate
increases only modestly over a relatively narrow range of
isometric force beyond which little further increase in firing
rate is seen (Bailey et al. 2007; Bracchi et al. 1966; De Luca
and Contessa 2012; De Luca et al. 1982; Kiehn and Eken 1997;
McGill et al. 2005; Monster and Chan 1977; Moritz et al. 2005;
Mottram et al. 2009, 2014; Person and Kudina 1972). Such
saturation of firing rate with maximum rates often ⬍20 impulses/s (imp/s) in response to presumed increases in synaptic
drive is in contrast to that observed with intracellular current
injection during which, for example, cat hindlimb MNs increase firing rates linearly up to high levels (usually ⬎50
imp/s, occasionally ⬎100 imp/s) with increased current (Granit
et al. 1966; Kernell 1965; Schwindt 1973; Schwindt and Calvin
1972; Schwindt and Crill 1982).
From the broadest perspective, there are two categories of
factors that could account for such saturation associated with
natural activation of MNs. Extrinsic factors represent those
processes that might limit the net synaptic excitation acting on
MNs during voluntary contraction. As such, during voluntary
effort, the depolarizing current delivered synaptically may
simply be less than that needed to drive the MNs to high firing
rates. This might come about, in part, because of progressive
increases in concurrent inhibition tending to curb increases in
firing rate (Denny-Brown 1929; Granit 1958; Granit et al.
1960; Heckman and Binder 1993; Powers et al. 2012; Tansey
and Botterman 1996).
Alternatively, MNs themselves might be intrinsically less
able to respond with increases in firing rate as synaptic drive
increases. One candidate for such an intrinsic limitation in
firing rate is a progressive loss in driving potential at excitatory
synapses as the dendritic membrane depolarizes (Barrett and
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Fuglevand AJ, Lester RA, Johns RK. Distinguishing intrinsic
from extrinsic factors underlying firing rate saturation in human motor
units. J Neurophysiol 113: 1310 –1322, 2015. First published December 4, 2014; doi:10.1152/jn.00777.2014.—During voluntary contraction, firing rates of individual motor units (MUs) increase modestly
over a narrow force range beyond which little additional increase in
firing rate is seen. Such saturation of MU discharge may be a
consequence of extrinsic factors that limit net synaptic excitation
acting on motor neurons (MNs) or may be due to intrinsic properties
of the MNs. Two sets of experiments involving recording of human
biceps brachii MUs were carried out to evaluate saturation. In the first
set, the extent of saturation was quantified for 136 low-threshold MUs
during isometric ramp contractions. Firing rate-force data were best fit
by a saturating function for 90% of MUs recorded with a maximum
rate of 14.8 ⫾ 2.0 impulses/s. In the second set of experiments, to
distinguish extrinsic from intrinsic factors underlying saturation, we
artificially augmented descending excitatory drive to biceps MNs by
activation of muscle spindle afferents through tendon vibration. We
examined the change in firing rate caused by tendon vibration in 96
MUs that were voluntarily activated at rates below and at saturation.
Vibration had little effect on the discharge of MUs that were firing at
saturation frequencies but strongly increased firing rates of the same
units when active at lower frequencies. These results indicate that
saturation is likely caused by intrinsic mechanisms that prevent
further increases in firing rate in the presence of increasing synaptic
excitation. Possible intrinsic cellular mechanisms that limit firing rates
of motor units during voluntary effort are discussed.
FIRING RATE SATURATION
METHODS
position was used to maintain some degree of resting tension on the
force transducer. A vertically directed cord, supported by an overhead
pulley, was attached to a Velcro strap encircling the hand to help
support the weight of the hand and forearm. As a consequence of this
overall arrangement, elbow flexion force was largely exerted in the
horizontal plane. Force signals were amplified (gain 1,000) using a
World Precision Instruments Transbridge amplifier.
Motor Unit Recording
Motor unit action potentials were recorded using sterilized, lacquer-coated tungsten microelectrodes (diameter 250, impedance ⬃10
M⍀ before insertion; Frederick Haer) inserted through alcoholcleansed skin and into the lateral head of biceps brachii. A small
surface electrode (diameter 4 mm) was fixed to the skin over the
lateral epicondyle of the elbow to provide a reference signal for the
differentially amplified intramuscular electromyographic (IEMG) signal (gain 1,000, bandpass filter 0.3–3 kHz). The IEMG signal was
displayed on an oscilloscope and broadcast audibly to provide feedback of MU activity. Force and IEMG signals were digitally sampled
(1 and 20 kHz, respectively; Power 1401 Cambridge Electronics
Design), displayed on a computer monitor, and stored for subsequent
analysis.
Tendon Vibration
Mechanical oscillatory inputs (80 Hz) were applied to the distal
tendon of biceps brachii on the ventral aspect of the elbow using a
mechanical vibrator (Panasonic EV 297). The vibrator was stabilized
within a custom-built frame that allowed positioning of a 1-cmdiameter, 20-cm-long probe on and perpendicular to the distal portion
of the biceps tendon. A noncalibrated accelerometer was mounted on
the head of the vibrator and was simply used to monitor when
vibration was applied. The accelerometer signal was digitally sampled
(1 kHz) concurrently with force and EMG signals.
Protocol
Two sets of experiments were carried out, both involving the
recording of MU activity in the lateral (long) head of the biceps
brachii in healthy adult human subjects. In the first set of experiments
(13 experimental sessions involving 4 female and 6 male subjects) we
quantitatively characterized firing rate saturation in biceps MUs during voluntary contractions involving slow ramp increases in isometric
elbow flexion force. In the second set of experiments (12 experimental
sessions on 5 female and 5 male subjects) we applied vibration to the
distal biceps tendon while subjects held MU firing rates at different
steady levels. We selected biceps brachii as the test muscle because it
has been widely used in previous studies of human MU activity and,
based on preliminary studies, it was a muscle that could be readily
excited with tendon vibration, a prerequisite for the present experiments. The Institutional Human Investigation Committee approved
the procedures, and all subjects gave informed consent.
Experimental Setup
For both sets of experiments, subjects were seated comfortably in
a dental chair with their right arm supported on a horizontal platform.
The medial surface of the elbow rested on a padded, thermoplastic
support that held the shoulder abducted ⬃70° and flexed ⬃45°. A
thermoplastic cuff encircled the distal forearm just proximal to the
wrist joint and was molded to hold the forearm midway between fully
supinated and fully pronated positions. The cuff was connected to a
force transducer (Grass FT-10) by a small metal chain. The length of
the chain was adjusted so as to hold the elbow joint in a relatively
extended position (⬃20° from full extension). This extended elbow
Experiment 1. In the first set of experiments (carried out to
characterize firing rate saturation in biceps MUs), subjects first performed three brief (duration ⬃2 s) maximum voluntary contractions
(MVCs) of elbow flexion. MVCs were performed before insertion of
microelectrodes into biceps. To record the large forces associated with
this task, custom-built heavy-duty springs were inserted into the
housing of the Grass FT-10 force transducer, providing an overall
sensitivity of 0.072 mV/kg. Subjects were provided with about 1 min
of rest between MVCs. The greatest peak force recorded from any of
the three trials was taken as the MVC force.
After the MVCs were performed, the heavy-duty springs in the
FT-10 transducer were replaced with springs allowing more sensitive
measures of force (0.65 mV/kg). The microelectrode was inserted into
the lateral head of biceps, and the position of the electrode was
manually adjusted while the subject exerted weak isometric contractions until clear MU action potentials could be discerned. The subject
was then instructed to perform slow, smooth ramp increases in elbow
flexion force while MU activity was recorded. Subjects had visual
feedback of force and MU activity. Auditory feedback of MU activity
was also available to the subject. Subjects were instructed to increase
force in a very gradual ramp, but no other constraints were put on the
rate of rise of force. Force increased up to a level where recruitment
of other units made detection of target-unit activity difficult (as judged
by the experimenter), at which time the subject was instructed to
relax. A rest of 10 –20 s was provided between trials. The microelectrode position was then adjusted (which sometimes involved removal
of the electrode and reinsertion at a new location) to sample from
presumed different MUs, and the procedures were repeated.
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Crill 1974; Cushing et al. 2005; Powers and Binder 2000).
Such a loss in driving potential has been shown to markedly
reduce synaptic currents and thereby lessen the net current
transferred to the soma and spike-initiating zone (Cushing et al.
2005).
Another intrinsic factor is that associated with diminution of
cell input resistance as the quantity of open transmitter-gated
(and other type) channels increases (Binder et al. 1996; Burke
1967; Coombs et al. 1955; Destexhe and Paré 1999; Fuortes
1959; Kuhn et al. 2004; Llinas and Terzuolo 1964; Powers and
Binder 2000). Such a reduction in membrane input resistance
should lessen the effective change in membrane potential
caused by a given increment in synaptic current (due to Ohm’s
law) and also lead to an abbreviation in the time course of
postsynaptic potentials (due to the decrease in membrane time
constant). Theoretically, such decreases in membrane input
resistance and time constant should progressively erode the
efficacy by which excitatory synaptic inputs are transformed
into spiking output as synaptic activity increases.
Therefore, to help distinguish extrinsic from intrinsic factors
underlying firing rate saturation, we artificially augmented
descending excitatory drive to MNs by activation of muscle
spindle afferents through tendon vibration. We measured the
effects of tendon vibration on the change in firing rates of MUs
voluntarily activated at firing rates below saturation and when
saturated. We hypothesized that if MUs discharging at saturation increase their rate of firing with additional synaptic excitation provided by tendon vibration, then this would imply that
extrinsic limitations in voluntary synaptic drive underlie saturation. On the other hand, if tendon vibration does not increase
firing rate in otherwise saturated MUs, then this would imply
that intrinsic cellular mechanisms limit increases in firing rate.
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FIRING RATE SATURATION
rate. For each MU, we tested the hypothesis that such an exponential
(i.e., saturating) function provided a significantly better fit of firing
rate data than a simple linear function. As such, firing rate-force data
for each unit were also fit with linear regression. The sum of squared
errors (SSE) associated with linear regression was compared with that
of the exponential fit using the F statistic. The firing rate profile of a
unit was then designated as exponential only if the F statistic indicated
a significant (P ⬍ 0.01) improvement in fit over linear regression.
Otherwise, the firing rate relation was deemed to be linear. If neither
linear nor exponential regression provided a significant fit of the data,
then no designation was applied to the unit’s firing rate profile.
Regression analyses were also carried out to determine if there
existed significant associations between recruitment threshold (Fth)
and the maximum rate of spiking (Rmax), between recruitment threshold and the rate of spiking at threshold (Rmin), and between recruitment threshold and the initial firing rate gain (calculated as the ratio
of the change in firing rate from the minimum rate to that at the force
constant, divided by the force constant).
Experiment 2. For the second experiment involving tendon vibration, the firing rate of each unit was determined over a 2-s period
immediately preceding tendon vibration and for a 2-s period 0.5 s after
the onset of vibration. This was done for each of the holding-force
levels. For each holding-force level, the difference in firing rate
(⌬rate) between that measured during the superimposed vibration
(vibration rate) and that prior to vibration (initial rate) represented the
efficacy with which the supplemental excitation arising from peripheral receptors increased firing rate in the MU. Likewise, to obtain a
coarse index of the overall excitatory effect of vibration on the entire
MU pool, we measured the change in isometric muscle force averaged
over a 2-s window before vibration and over a 0.5-s window 2-s after
the onset of vibration. This delayed window for measuring vibrationevoked force was selected because force was relatively stable and
nearly fully developed during this period (e.g., see Fig. 6).
Regression analysis was performed on ⌬rate as a function of the
initial rate for all units and for all target levels to establish whether
there was a systematic change in firing rate responsiveness of MUs to
peripheral excitatory input as initial firing rates increased. Data are
reported as means ⫾ SD, and effects were considered statistically
significant when P ⬍ 0.01.
Data Analysis
Experiment 1: Firing Rate Saturation
In off-line analysis, MU action potentials detected in IEMG signals
were discriminated on the basis of waveform shape and amplitude
using a template-matching algorithm (Spike2; Cambridge Electronics
Design). From the discriminated spike trains, the firing rates of each
MU were calculated. Sporadic doublet discharges (interspike intervals
⬍15 ms) occurring at the outset of a contraction were excluded from
the analysis.
Experiment 1. For the first set of experiments to characterize firing
rate saturation, instantaneous firing rate was plotted as a function of
isometric force (% MVC). This was done only for the rising force
phase of the contractions. Based on previous work (e.g., De Luca and
Contessa 2012; De Luca et al. 1982; McGill et al. 2005; Monster and
Chan 1977), the profiles of these types of plots indicate that such data
can be reasonably fit by rising exponentials of the form (see Fig. 1)
The discharge patterns of 136 MUs were recorded from the
biceps brachii during slow, weak ramp contractions in 10
subjects. The average trial duration was 14.2 ⫾ 6.5 s with a
slow rate of rise of force (0.77 ⫾ 0.71 N/s or 0.40 ⫾ 0.36%
MVC/s). In 75 recordings, only 1 unit was analyzed; in 26
recordings, 2 units were identified and analyzed; and in 3
recordings, 3 units were identified and analyzed. Figure 1A
shows an example recording in which one unit was followed
throughout the ramp contraction. In this low-threshold unit,
firing rate initially increased with subtle increases in force but
then leveled off to an average rate of ⬃15 imp/s even though
force (and presumably, synaptic drive) continued to increase
(period between dashed vertical lines).
In Fig. 1B, the instantaneous firing rate of this unit is
replotted as a function of rising isometric force, normalized to
the MVC of the subject. It is evident in this representation that
firing rate was modulated over only a small increase in force
beyond which firing rate showed little further systematic increases. Nevertheless, linear regression performed on these
data was significant (P ⬍ 0.001, R2 ⫽ 0.35, SSE ⫽ 1,094). As
expected, the exponential fit (Eq. 1, METHODS) was also signif-
R共F兲 ⫽ Rmax共1 ⫺ e⫺共F⫺Fth兲⁄⌽兲 ⫹ Rmin ,
(1)
where R(F) represents the rate (R) of spiking as a function of muscle
force (F), Rmax is the maximum rate of spiking, e is the base of the
natural logarithms, F is normalized isometric force, Fth is the threshold force at which a unit begins to discharge, and Rmin is the minimum
rate of spiking at recruitment threshold. The parameter ⌽ can be
thought of as a force constant (akin to a time constant) and represents
the amount of force increase associated with a 63% increase in firing
RESULTS
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To relate MU firing rates to the mechanical properties of the lateral
biceps, additional experimental sessions were carried out in five of the
subjects who participated in experiment 1 during which we electrically stimulated the lateral biceps at different frequencies using the
intramuscular microelectrodes. The tip of the microelectrode was
inserted to a depth that was judged to be near the central core of the
lateral biceps. A small surface electrode attached over the lateral
epicondyle of the elbow served as the return pathway for stimulation.
Trains of monophasic, cathodic constant-current pulses (duration 0.5
ms) were delivered through the microelectrode using a Grass S88
stimulator and optical isolation unit. Initially, during stimulation at 1
Hz, the intensity of the pulses was increased up to a level that evoked
moderately strong twitches but without discomfort to the subject. The
stimulus intensity was then maintained at this level while trains of
stimuli (⬃2 s in duration and with ⬃5 s of rest between trains) were
delivered at frequencies of 5, 10, 15, 20, 30, 40, and 50 imp/s during
which the evoked isometric flexion force was recorded. Subjects were
instructed to relax the arm during stimulation.
Experiment 2. The procedures for the second set of experiments
involving tendon vibration were similar to those described above for
MU recording, with the following differences. Initially, the probe of
the tendon vibrator was applied to the biceps tendon with its position
and applied pressure optimized to elicit a consistent reflex contraction
in response to brief periods of vibration as judged by increased
isometric force. The microelectrode was then inserted into the lateral
biceps, and a target MU was identified during weak voluntary contractions. Subjects were then instructed to perform stepwise rampand-hold contractions beginning with a holding-force level just sufficient to activate the MU to fire tonically. Each hold phase consisted
of an initial ⬃4-s period of maintained isometric force followed by an
⬃3- to 5-s period during which tendon vibration was superimposed on
the voluntary contraction. Subjects were instructed to maintain the
same level of voluntary effort during the vibration as during the initial
holding period (Hagbarth et al. 1976). Subjects were then instructed to
increase force slightly to a new holding-force level and the procedures
were repeated. Such increasing force steps were continued until
activity of newly recruited units made identification of the target unit
difficult. The subject then relaxed for a period of 30 – 60 s, after which
the microelectrode position was adjusted to search for a different MU.
This process was repeated several times during an ⬃2-h experimental
session.
FIRING RATE SATURATION
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icant (P ⬍ 0.001, R2 ⫽ 0.58, SSE ⫽ 714). Using the F statistic
and accounting for differences in the number of parameters
used to fit the data, the reduction in SSE from linear to
exponential fits was highly significant (F ratio ⫽ 84.4, P ⬍
0.0001). As such, this unit was designated as having an
exponential (saturating) firing rate function, which is displayed
as a red trace in Fig. 1B. From this function, the following
parameters were identified (see Eq. 1): initial minimum spiking
rate (Rmin ⫽ 6.2 imp/s), maximum spiking rate (Rmax ⫽ 14.9
imp/s), threshold force (Fth ⫽ 0.20% MVC), and force constant
(⌽ ⫽ 0.17% MVC).
Despite the narrow force range (⬍1% MVC) over which this
unit modulated firing rate, the subject was still able to precisely
regulate firing of the unit within this range. As shown in Fig.
1A, the increase in firing rate played out over a relatively long
duration (⬎10 s). This prolonged period of rate modulation
presumably occurred because the subject was capable of finely
grading the net synaptic excitation driving the MN during this
time. As such, the unit did not exhibit an uncontrollable jump
from low to high firing rate; instead, firing rate was purposefully modulated despite the initial high gain. Indeed, the
subject was able to extend the initial period of rate modulation
of this unit over a period of ⬃5 min (data not shown) involving
a very gradual increase in force. Because we did not examine
this issue systematically in the present study, it is not possible
to say how prevalent this capability of controlled rate modulation is for biceps MUs.
The profile of firing rate vs. force for the unit depicted in Fig.
1A appeared different for the rising phase compared with the
falling phase of the contraction. We did not analyze the falling
phase in these experiments because subjects typically abruptly
ceased the contraction when instructed to relax (unlike the trial
shown in Fig. 1A). Nevertheless, such intriguing asymmetry in
firing rate modulation has been noted previously (e.g., Mottram
et al. 2014) and warrants dedicated further investigation.
Figure 2 shows an example recording in which the activities
of two units were clearly discernable during the ramp contraction. The first unit increased its firing rate over a period of
about 5 s up to a level of ⬃13 imp/s, after which no further
systematic increases in firing rate occurred. The second unit
was recruited at a time when the firing rate of the first unit had
leveled off. The firing rate of the second unit then increased
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Fig. 1. Example recording from biceps motor unit (MU). A:
isometric force exerted by biceps muscle (bottom trace), intramuscular electromyography (IEMG) signal recorded in biceps muscle depicting discharge of a single MU (middle trace),
and instantaneous (dots) and moving average (1-s window;
line) firing rate of recorded unit (top trace). Vertical dashed
lines indicate period during which force was increasing yet
MU firing rate had leveled off at a firing rate of ⬃15 impulses/s (imp/s). B: plot of instantaneous firing rate vs. muscle
force for the unit shown in A. Force was normalized to a
percentage of the maximum voluntary contraction (% MVC)
force. Data were fit with a rising exponential (red line) of the
form represented by Eq. 1. Parameters derived from this fit
were recruitment threshold force (Fth), firing rate at recruitment threshold (Rmin), maximum rate (Rmax), and force constant (⌽).
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FIRING RATE SATURATION
Fig. 2. Example recording depicting firing rate saturation in
2 MUs. Isometric force (bottom trace), IEMG signal (middle trace), and instantaneous firing rates of the 2 units
detected in the IEMG signal (top traces). The firing rates of
both units leveled off despite continued increase in muscle
force. In addition, unit 2 was recruited at a time when the
firing rate of unit 1 had saturated.
For the 123 units that were best fit by an exponential
function (and for which we could estimate the upper limit of
firing rate), the average maximum firing rate was 14.8 ⫾ 2.0
imp/s. This value is nearly identical to that (15.2 imp/s)
reported for biceps MUs in healthy control subjects by Mottram et al. (2014). There was no significant (P ⫽ 0.53) relation
Fig. 3. Firing rate-force relation for 133 biceps MUs. A: each trace indicates the
firing rate-force relation for an individual MU. Force is normalized as % MVC.
Black traces indicate MUs (n ⫽ 123) whose firing rate-force data were
significantly better fit by a rising exponential function (Eq. 1) than a linear
function. Red traces indicate MUs (n ⫽ 10) whose firing rate data were best fit
by a linear function. B: for improved clarity, firing rate-force relations shown
in A are redrawn for a force range up to 2.5% MVC.
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rapidly and with very modest changes in force up to a rate of
⬃14.5 imp/s, beyond which no further increases in firing rate
were observed. Such saturation in firing rate suggests that these
units were relatively impervious to further increases in synaptic
excitation delivered to the motor nucleus as a whole as evidenced by increased muscle force and recruitment of other
units. Furthermore, this example demonstrates that the period
over which a unit increased firing rate occurred relatively
independently of that occurring in other units within the same
muscle.
Of the 136 MUs recorded, 123 (90%) were best fit by the
exponential function, 10 were best fit with a linear function,
and 3 were not significantly fit by either exponential or linear
regression. For those units designated as linear, oftentimes they
too exhibited the initial steep increase in firing rate characteristic of saturating firing but with insufficient data points in the
initial high-gain region for the exponential fit to represent a
significant improvement over the linear fit.
Figure 3A shows a plot of the exponential and linear firingrate vs. force functions for all 133 MUs whose data were
significantly fit by one of those two relations. Cases that were
best fit by a linear function are shown in red. Virtually all the
MUs that we could record and reliably discriminate had recruitment thresholds ⬍10% MVC, and the majority of these
were recruited at forces ⬍5% MVC. For improved clarity at
the low force range where many units are represented, we have
replotted the firing-rate force relations over the initial 2.5%
MVC in Fig. 3B.
Most units depicted in Fig. 3 exhibited an initial steep rise in
firing rate and then leveled out at modest firing rates, usually
⬍20 imp/s. The average (SD) minimum firing rate across the
entire population of MUs depicted in Fig. 3A was 6.7 ⫾ 2.3
imp/s. The average recruitment threshold force of all units
sampled was 2.1 ⫾ 2.2% MVC. For this population of lowthreshold MUs, there was no significant (P ⫽ 0.89) relation
between recruitment threshold force and minimum firing rate.
FIRING RATE SATURATION
Experiment 2: Tendon Vibration
As described in the Introduction, saturation of MU discharge
may result from limitations in the net excitatory drive acting on
the MNs (an extrinsic factor), from intrinsic properties of the
MNs, or both. Excitatory drive to a MN pool can be augmented
artificially by activation of muscle spindle Ia afferents through
tendon vibration. Therefore, we examined the effects of tendon
vibration on the change in firing rate of individual biceps
brachii MUs that were voluntarily activated at various rates
below saturation and at saturation.
Figure 5 shows representative responses recorded in a single
MU. When weak voluntary drive brought the discharge of the
unit to ⬃10 imp/s (Fig. 5A), the addition of tendon vibration
Fig. 4. Relation between stimulus frequency and isometric force. A: mean (SD)
steady-state elbow flexion force exerted during submaximal stimulation of
biceps at different pulse frequencies using intramuscular electrodes. Force
increased as a sigmoid function of stimulus frequency with maximum force
attained at a stimulus frequency of ⬃30 imp/s. B: histogram depicting maximum firing rates recorded during ramp contractions in 123 MUs that exhibited
saturating firing rate responses (black traces in Fig. 3). Average maximum rate
(14.8 imp/s) is depicted as a vertical dashed line projecting to A. Based on the
force-stimulus frequency curve in A, MUs discharging at this average maximum rate would likely generate ⬃63% of their force capacity.
caused a marked increase in firing rate to ⬃15 imp/s. When the
subject slightly increased drive to the muscle and increased the
spike rate of the unit to ⬃11 imp/s (Fig. 5B), tendon vibration
again augmented firing rate, but the change in rate was not as
great as in the first case. Finally, when drive to the muscle was
increased so that the firing of the MU appeared to have
saturated at a rate of ⬃15 imp/s (Fig. 5C), tendon vibration had
virtually no effect on the discharge of the unit. Nevertheless,
tendon vibration remained an effective excitatory stimulus as it
led to an increase in muscle force (see bottom trace, Fig. 5C),
suggesting that other units were recruited or increased their
rates in response to vibration.
Immediately following the vibration trial shown in Fig. 5C,
the subject was asked to voluntarily increase isometric force
exerted by the biceps. Figure 5D redisplays the traces depicted
in Fig. 5C showing the responses to tendon vibration and is
extended to include the following period of increased voluntary
force. Firing rate remained stable at ⬃15 imp/s during both
maneuvers suggesting that the MU was relatively unresponsive
once saturated to increases in either peripheral or descending
sources of excitatory drive. Although average firing rate (as
shown in Fig. 5) rarely exceeded 15 imp/s when saturated, the
instantaneous rate did fluctuate with a similar variability (e.g.,
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between maximum firing rate and recruitment threshold force.
The average extent of firing rate modulation (maximum firing
rate minus minimum firing rate) was 8.0 ⫾ 2.9 imp/s.
Force constant ⌽ values were highly skewed to the right
(skewness ⫽ 3.6) with values ranging from 0.02 to 3.3% MVC,
an average value of 0.35 ⫾ 0.48% MVC, and a median value
of 0.19% MVC. Likewise, initial gain values were also broadly
distributed (range ⫽ 1–251 imp/s/% MVC) and rightward
skewed (skewness ⫽ 2.4), with a mean value of 37 ⫾ 38
imp/s/% MVC and a median value of 24 imp/s/% MVC. To
ascertain whether initial gain varied systematically with recruitment threshold, the data were first log transformed (due to
their lack of normality), and then linear regression was performed. Whereas the regression was significant (P ⬍ 0.01) and
negative (i.e., lower gains for higher threshold MUs), the
overall variance accounted for by the regression was small
(R2 ⫽ 0.08). As such, some degree of caution is warranted in
interpreting this result.
To understand whether firing rate saturation exhibited by
most biceps MUs might limit force output, it is important to
know the relation between MU firing rate and MU force. The
human biceps is not experimentally amenable to intraneural
microstimulation of single motor axons as are some distal
muscles. Therefore, we instead electrically stimulated the lateral head of the biceps with intramuscular electrodes by using
submaximal constant current pulses delivered at different stimulus frequencies in five of the subjects who participated in the
first experiment. Figure 4A shows the average (SD) peak force
exerted for each stimulus frequency normalized to the maximum evoked force. Maximum force was achieved at 50 imp/s
in 3 of the 5 subjects and at 40 imp/s in the other 2 subjects.
The average maximum evoked force for these experiments was
5.6 ⫾ 2.8% MVC. Isometric force increased most steeply in
the stimulus frequency range from 10 to 20 imp/s.
Figure 4B shows the distribution of the maximum firing rates
for the 123 exponentially designated MUs (depicted in Fig. 2)
plotted on an abscissa with the same scaling as for Fig. 4A. The
average maximum firing rate (14.8 imp/s) in Fig. 4B is indicated with a dashed vertical line projecting to the average
force-stimulus frequency relation shown in Fig. 4A. The isometric force that would be evoked with electrical stimuli
delivered at this frequency would only be about 63% of the
maximal evoked force. These results suggest that biceps MUs
discharging at saturation rates are unlikely to elicit their maximum force capacity. This issue will be more fully explored in
the DISCUSSION.
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FIRING RATE SATURATION
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Fig. 5. Response of single biceps MU to tendon vibration. Subject voluntarily increased firing of unit to different initial rates (indicated by horizontal dashed
lines): ⬃10 (A), ⬃11 (B), and ⬃15 imp/s (C). Vibration was then applied to the biceps tendon (vertical dashed lines). Traces from bottom to top show elbow
flexion force, intramuscular EMG signal, discriminated MU spikes, moving average (1-s window) MU firing rate, and noncalibrated acceleration signal indicating
application of vibration. There was a marked increase in firing rate with vibration in A and B but no detectable change in rate in C despite clear evidence of
vibration-mediated increase in muscle force. D: traces from C are redrawn and extended to show subsequent period of voluntary increase in muscle force. Once
the unit reached a discharge rate of ⬃15 imp/s, additional increases in firing rate were not observed in response to enhanced excitation mediated by tendon
vibration or voluntary drive.
Fig. 1A) as seen at lower rates. This indicates that firing rate
can momentarily exceed the saturation level. Such temporary
increases (and decreases) in firing rate likely reflect noisy
fluctuations in membrane potential rather than systematic
changes in the net driving current or intrinsic responsiveness of
MNs.
For each unit recorded in experiment 2, firing rate was
determined over a 2-s period immediately preceding tendon
vibration and for a 2-s period 0.5 s after the onset of vibration
(Fig. 6). These measurement windows were selected because
they were associated with relatively stable periods of firing rate
in response to tendon vibration. The difference in firing rate
(⌬rate) between that measured during vibration (vibration rate)
and that before vibration (initial rate) represents the efficacy
with which the supplemental excitation arising from peripheral
receptors drove firing rate in the MU.
J Neurophysiol • doi:10.1152/jn.00777.2014 • www.jn.org
FIRING RATE SATURATION
1317
Fig. 6. Quantification of vibration-mediated changes in firing rate. Example
recording of biceps MU responding to tendon vibration illustrates quantification. The initial rate was determined as the average spike rate in a 2-s window
(black vertical dashed lines) immediately before vibration. The vibration rate
was calculated as the average spike rate in a 2-s window (red vertical dashed
lines) 0.5 s after the onset of vibration. The difference in firing rate (⌬rate) was
calculated as the difference between the vibration rate and initial rate. Traces
from bottom to top show elbow flexion force, intramuscular EMG signal,
discriminated MU spikes, moving average (0.5-s window) MU firing rate, and
noncalibrated acceleration signal indicating application of vibration.
The vibration responses from a total of 96 MUs in 10
subjects were recorded and analyzed for this experiment.
Each unit’s response to vibration was evaluated, on average,
at 4 ⫾ 2 different initial firing rate levels. The changes in
firing rate evoked by vibration are plotted as a function of
firing rates immediately preceding vibration for all units and
firing rate levels in Fig. 7A. Linear regression indicated a
significant (P ⬍ 0.001, R2 ⫽ 0.28) negative relation between
these two variables. For example, for an initial firing rate of
⬃6 imp/s, vibration evoked on average about a 4 imp/s
increase in firing rate, whereas for units discharging close to
saturation frequencies (⬃14 imp/s), vibration evoked little
change in firing rate.
We were also interested to know whether the transient
increase in firing rate often seen often at the outset of vibration
(e.g., Fig. 6) was also diminished when units were discharging
at saturation rates. We therefore calculated the change in firing
rate in the 0.5-s window immediately following the onset of
vibration (to capture the transient) for all trials for which the
initial firing rate was ⱖ14 imp/s. These values were then
compared with the change in rate for the subsequent 2-s period.
Although the change in rate associated with the initial 0.5-s
period was slightly greater on average (0.60 ⫾ 0.86 imp/s) than
for the subsequent 2-s period (0.40 ⫾ 1.25 imp/s), these values
were not significantly different from one another (P ⫽ 0.80,
repeated-measures ANOVA). This implies that tendon vibration had little effect on MU discharge, either transiently or
longer lasting, when MUs were already active near saturation
rates.
Fig. 7. Vibration-mediated changes in firing rate as a function of initial rate. A:
⌬rate induced by tendon vibration for 362 total trials recorded in 96 MUs
plotted as a function of the initial (i.e., previbration) firing rate. The firing rate
change evoked by tendon vibration decreased as the initial rate on which the
vibration was superimposed increased. Line shows linear regression (P ⬍
0.001). B: average change in isometric force (⌬force) caused by tendon
vibration for the same 362 trials shown in A. Linear regression was not
significant (P ⫽ 0.16). Dashed line indicates average magnitude of vibrationinduced force.
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One interpretation of the results in Fig. 7A is that MUs
discharging at saturation frequencies are relatively unresponsive to additional synaptic excitation provided by tendon vibration, and as such, intrinsic cellular mechanisms likely limit
firing rates of MUs during voluntary effort. This interpretation
rests partially on the assumption that the vibratory stimulus
provided roughly equivalent levels of additional excitatory
synaptic input as initial firing rates (and associated contraction
levels) increased. Our measure of the efficacy of supplemental
excitatory drive provided to biceps MNs by vibration was the
magnitude of the reflex contraction force superimposed on the
voluntary force. The average magnitude of the vibrationinduced force was 0.96 ⫾ 0.92 N. Figure 7B shows a plot of
the change in force elicited by vibration as a function of the
initial firing rate for all 362 trials. Linear regression revealed
no significant (P ⫽ 0.16) relation between these two variables,
1318
FIRING RATE SATURATION
suggesting that the strength of the excitatory drive provided by
vibration did not vary systematically with the initial firing rate.
carried out within the same species will greatly aid in understanding the mechanisms underlying firing rate saturation.
Extrinsic Factors
DISCUSSION
Limitations
The major limitation of this study was that we were able to
follow the firing rates of only the lowest threshold MUs
(recruitment thresholds all ⬍10% MVC). Furthermore, once
recruited, we tracked subsequent changes in firing rates over
only a small range of the entire force capacity of biceps. This
was primarily due to the difficulty in isolating spikes of
individual MUs because activities in other MUs contaminated
the recordings as force increased. It is possible, therefore, that
saturation of MU activity at low firing rates may be a feature
of low-threshold MUs only. The recent development of highdensity multielectrode surface arrays (Lapatki et al. 2004;
Merletti et al. 2008; Nawab et al. 2010) using sophisticated
decomposition algorithms (Holobar and Zazula 2007; Holobar
et al. 2010; McGill et al. 2005) should enable reliable tracking
of higher threshold MUs over a wider force range (Holobar et
al. 2014). Indeed, using this approach, De Luca and Contessa
(2012) recently showed saturation at rates ⬍20 imp/s in vastus
lateralis motor units recruited as high as 50% MVC.
A more general limitation of this study is that implicit
comparisons between saturation firing rates generated in response to natural synaptic activation and those in response to
intracellular current injection are made across species. As far
as we are aware, no intracellular current injection studies have
been carried out in human MNs. Likewise, only a few studies
(e.g., Gorassini et al. 1999) have attempted to characterize MU
activity during voluntarily graded isometric contractions in
experimental animal models as is done so readily in human
subjects. Future work in which both types of assessments are
Our argument that firing rate saturation is most likely caused
by mechanisms intrinsic to individual MNs derives in part from
consideration as to how extrinsic sources of synaptic input to a
motor nucleus are organized. For example, anatomic and electrophysiological evidence suggests that individual muscle spindle Ia afferents arborize extensively to make excitatory synaptic connections on most alpha MNs of the homonymous motor
nucleus (Brown and Fyffe 1978; Lüscher and Vadar 1989;
Mendell and Henneman 1971). Likewise, individual corticospinal inputs (in primates) also appear to diverge extensively to
provide excitatory input across many members of a MN pool
(Lawrence et al. 1985; Mantel and Lemon 1987; Shinoda et al.
1981). Such broadly distributed excitation would seem unlikely to cause the restricted periods of firing rate increases in
individual MUs characteristic of firing rate saturation.
It also seems improbable that the leveling off in firing rate
seen to occur in different MUs at various time points and levels
of excitatory drive (e.g., Fig. 2) could come about due to
targeted increases in synaptic inhibition directed specifically to
those MNs exhibiting saturation. This is not to say that an
overall increase in synaptic inhibition may not occur as contraction strength increases. Indeed, recurrent inhibition, for
example, mediated by Renshaw cells is likely to increase in
intensity with increased MU activity. However, the distribution
of inhibitory synaptic contacts made by Renshaw cells is
widespread (Fyffe 1991) such that the overall degree of recurrent inhibition is more or less uniformly distributed across a
pool of MNs (Lindsay and Binder 1991). Similar findings have
also been reported for reciprocal inhibition mediated by Ia
inhibitory interneurons (Heckman and Binder 1991b). As such,
targeted inhibition from spinal interneurons to individual MNs
seems unlikely.
Rubrospinal inputs, however, do appear to have a nonuniform distribution across motor nuclei supplying cat
hindlimb muscles with such inputs tending to inhibit lowthreshold MNs while facilitating higher threshold MNs (Powers et al. 1993). If the degree of engagement of rubrospinal
inputs progressively increased with the intensity of muscle
contraction, then aspects of firing rate saturation (e.g., leveling
off of firing rate of low-threshold units while higher threshold
units are recruited and increasing firing rate) might be affected
(Heckman and Binder 1993). However, in humans, the rubrospinal tract is virtually absent (Massion 1988; Nathan and
Smith 1982; Yang et al. 2011), making such a divergent source
of synaptic input an unlikely cause of the saturation seen in the
present experiments. Collectively, therefore, it seems unlikely
that firing rate saturation in individual MUs could be due to a
selective reduction in excitatory input or a targeted increases in
inhibition.
Intrinsic Mechanisms
If, as we suggest, mechanisms intrinsic to individual MNs
are primarily responsible for the limitation in firing rates
observed in this and other studies of human MUs, then one
must account for the relative absence of clear-cut saturation in
studies involving current injection into individual MNs (e.g.,
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In this study we have characterized the firing rate properties
of low-threshold biceps MU during voluntarily graded isometric contractions. For most units recorded, firing rate initially
increased steeply as a function of force and then leveled off
(i.e., saturated) at relatively low rates, usually ⬍20 imp/s. This
result is qualitatively similar to that described previously by
other investigators for biceps (Mottram et al. 2009, 2014) and
in a variety of other human muscles (rectus abdominis, latissiumus dorsi, pectoralis major, triceps, and brachioradialis,
Bracchi et al. 1966; genioglossus, Bailey et al. 2007; vastus
lateralis, De Luca and Contessa 2012; deltoid, De Luca et al.
1982; soleus and tibialis anterior, Kiehn and Eken 1997;
medial gastrocnemius, McGill et al. 2005; extensor digitorum,
Monster and Chan 1977; first dorsal interosseus, Moritz et al.
2005; rectus femoris, Person and Kudina 1972). We have also
shown in this work that augmenting descending excitatory
drive to biceps MNs with peripheral excitation mediated by
tendon vibration had little effect on the discharge of MUs that
were firing at saturation frequencies but robustly increased
firing rates of the same units when active at lower frequencies.
These results suggests that firing rate saturation in human MNs
is likely caused by intrinsic mechanisms that curtail increases
in firing rate even in the presence of escalating synaptic
excitation. Although the specific mechanisms responsible for
saturation are presently unknown, we consider some possibilities below after first discussing limitations of this study.
FIRING RATE SATURATION
sively undercut synaptic excitation acting on a MN as a ramp
contraction progresses. However, the time constant for spikefrequency adaptation is typically found to be ⬎20 s (Gorman
et al. 2005; Kernell and Monster 1982; Sawczuk et al. 1995).
Such a slowly developing conductance would therefore seem
unlikely to account for the rapid transition into saturated states
that can be seen in MUs even during slowly graded contractions (e.g., Fig. 2).
A third possibility, as elegantly explored in computer simulation by Cushing et al. (2005), is that progressive diminution
of the electrochemical driving force at excitatory synapses
could severely reduce synaptic currents as dendritic membranes become depolarized. This would limit the overall current delivered to the soma and thereby tend to abate increases
in firing rate in the presence of increasing synaptic activity.
Furthermore, the time course of this effect would occur somewhat independently for different neurons because change in
membrane potential (and effect on driving potential) would
depend on properties, such as size-related input resistance,
specific to individual neurons.
A forth intrinsic factor that might underlie firing rate
saturation is that associated with activation of persistent
inward currents (PICs) (Heckman et al. 2008; Heckman and
Enoka 2012; Hornby et al. 2002). PICs are mediated by
intrinsic (i.e., nonsynaptic) voltage-gated conductances that
slowly inactivate. PICs likely become activated near the
recruitment threshold of MNs (Bennett et al. 1998) and then
provide an additional potent source of depolarizing current
to MNs (Bennett et al. 1998; Lee and Heckman 1998a,
2000). Such activation of PICs could contribute to a sharp
rise in depolarizing current at the outset of firing in MNs and
could contribute to the initial steep increase in firing rate
characteristic of firing-rate saturation (Heckman et al. 2008;
Hornby et al. 2002). Furthermore, because PICs primarily
originate in the dendrites, dendritic membrane potential
might shift rather abruptly into a depolarized state and
thereby diminish synaptic driving potential (Cushing et al.
2005). As such, the dendritic membrane might approach a
kind of voltage-clamp state and make the neuron relatively
indifferent to additional synaptic input. Indeed, Powers and
Binder (2000) demonstrated that synaptic excitation mediated by tendon vibration had virtually no effect on membrane potential when MNs were already exhibiting plateau
potentials associated with activation of PICs. That finding
closely parallels the absence of effect of tendon vibration on
firing rate when MUs were saturated as shown in the present
investigation. Similarly, under high-monoamine drive that
likely promotes PICs, MNs can exhibit bistable firing in
response to slow ramp increases of injected current (e.g.,
Lee and Heckman 1998b) that are not unlike the saturating
responses of motor units in the present study.
It should also be said that framing possible mechanisms for
saturation as a dichotomy between intrinsic and extrinsic factors may not be entirely constructive. Indeed, in an important
computational study, Powers et al. (2012) have accurately
simulated the type of firing rate saturation seen in human MUs
but only under conditions in which the model incorporated
some of the intrinsic properties described above combined with
the extrinsic factor of time-varying synaptic inhibition.
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Kernell 1965; Granit et al. 1966; Schwindt 1973; Schwindt and
Calvin 1972; Schwindt and Crill 1982). As mentioned above,
species differences might be an important consideration, because such current injection studies primarily involved cat
MNs, whereas firing rate saturation during voluntary activation
has mainly been reported for human MUs. As such, there could
simply be species differences in the capacity of MNs to
generate action potentials at high rates. However, substantial
evidence of firing rate saturation has also been reported for cat
MNs during synaptic activation mediated by reflex pathways
(Alvord and Fuortes 1953; Bracchi et al. 1966; Burke 1968;
Cordo and Rymer 1982; Denny-Brown 1929; Granit 1958;
Granit et al. 1960; Kernell and Sjöholm 1975; Prather et al.
2002) and in response to stimulation of descending pathways
(Brownstone et al. 1992; Kernell and Sjöholm 1975; Tansey
and Botterman 1996; Zajac and Young 1980).
Despite numerous arguments to the contrary (Granit et al.
1966; Heckman and Binder 1991a; Kernell 1969, 2006; Kernell and Sjöholm 1973; Powers et al. 1992; Schwindt and
Calvin 1973), some investigators have questioned the validity
of using focal intrasomatic current injection to represent the
complex processes by which neurons naturally integrate currents arising from hundreds of synaptic conductances distributed across elaborate dendritic arbors (Cushing et al. 2005;
Destexhe and Paré 1999; Destexhe et al. 2003; Kuhn et al.
2004; Paré et al. 1998). For example, several investigators have
pointed out that as synaptic activity increases, input resistance
of the target neuron will progressively diminish due to increased opening of transmitter-gated channels (Binder et al.
1996; Destexhe and Paré 1999; Destexhe et al. 2003; Granit et
al. 1966; Kernell 1969; Kuhn et al. 2004; Llinas and Terzuolo
1964; Paré et al. 1998; Powers and Binder 2000). Such a
decrease in input resistance should have two consequences on
neuron discharge. First, lowering of input resistance should
lessen the effective change in membrane potential caused by a
given increment in depolarizing current according to Ohm’s
law. Second, because membrane time constant is directly
proportional to input resistance, lowering of input resistance
will abbreviate the time course of postsynaptic potentials and
thereby reduce their temporal summation. Because abovethreshold changes in membrane potential are tightly linked to
increments in discharge rate (Granit et al. 1966), such input
resistance-related mitigation of membrane depolarization
should subdue increases in firing rate, which in theory, could
contribute to firing rate saturation.
One problem with this idea, however, is that the transitions
into saturated states occurred at distinct times for different
MUs. Because synaptic inputs are more or less uniformly
distributed across a pool of MNs (Binder et al. 1998), changes
in input resistance associated with increased synaptic activation should occur roughly in parallel, rather than independently, for members of an MU population.
Given the relatively discrete manifestation of saturation in
individual MUs, the contributing mechanisms might be linked
in some way to the extent of activity in each MN. For example,
the magnitude of a slowly activating potassium conductance
(Barraza et al. 2009; Partridge and Stevens 1976; Sawczuk et
al. 1997) underlying “late” spike-frequency adaptation appears
related to both the duration and intensity of MN activity
(Gorman et al. 2005; Kernell and Monster 1982; Sawczuk et al.
1995). As such, spike-frequency adaptation might progres-
1319
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FIRING RATE SATURATION
Functional Consequences
AUTHOR CONTRIBUTIONS
Regardless of the underlying mechanisms, saturation in MU
firing rate has functional consequences. The force exerted by a
MU increases as a sigmoidal function of firing rate. In this
study, we obtained an estimate of this relation by activating
biceps at different stimulus rates (Fig. 4A). The stimulus rate
needed to achieve near maximum force was ⬃30 imp/s. Dalton
et al. (2010) found somewhat higher stimulus rates (⬃50
imp/s) to achieve maximal force in human biceps brachii. This
difference may be due to the higher stimulus intensities or
more flexed elbow posture used in that study.
Such electrical stimulation, however, is not selective for
individual types of MUs. At best, the force-stimulus frequency
relation like that depicted in Fig. 4A represents a weighted
average of the subset of MUs whose axons were in the vicinity
of the stimulating electrode. Nevertheless, it provides a rough
indication of the firing rates needed to produce near maximum
force in biceps MUs (⬎30 imp/s). The saturation firing rates
recorded in this study and elsewhere (Mottram et al. 2014) for
biceps during voluntary contraction were about half that estimated to be needed to produce maximal force (Fig. 4B). The
firing rate needed to achieve maximum force, however, depends on the contractile properties of the MU, with slow units
requiring lower rates (Botterman et al. 1986; Kernell et al.
1983). All the MUs recorded in the present study were low
threshold and as such may have been slow twitch (cf. Fuglevand 2011) and therefore required somewhat lower activation
rates to achieve maximum force than that indicated in Fig. 4A.
Nevertheless, based on experiments involving intraneural microstimulation of single motor axons in humans, the stimulus
rate needed to elicit maximum force in the slowest contracting
MUs was never less than 30 imp/s (Thomas et al. 1991;
Fuglevand et al. 1999). Collectively, these findings imply that
muscle strength may be partially limited by an inability to drive
MUs voluntarily with the high firing rates needed to attain
maximum force (Enoka and Fuglevand 2001).
A.J.F. and R.K.J. conception and design of research; A.J.F., R.A.L., and
R.K.J. performed experiments; A.J.F., R.A.L., and R.K.J. analyzed data;
A.J.F., R.A.L., and R.K.J. interpreted results of experiments; A.J.F. prepared
figures; A.J.F. drafted manuscript; A.J.F., R.A.L., and R.K.J. edited and
revised manuscript; A.J.F., R.A.L., and R.K.J. approved final version of
manuscript.
Finally, because of their relative accessibility, MNs have
long played an important role in shaping ideas about how
neurons integrate synaptic information. In this regard, the
present findings imply that the spiking output of a MN does not
faithfully “report” the intensity of synaptic excitation received.
Instead, once brought to threshold and following a brief and
modest period of rate modulation, MNs seem to all but ignore
additional synaptic excitation. As such, MNs appear to respond
in an almost binary “on-off” fashion rather than as accurate
integrators. The degree to which other neurons in the central
nervous system respond in this way and the impact this might
have on notions of information processing in the brain remain
to be determined.
GRANTS
This work was supported by National Institutes of Health Grants NS079147
(to A. J. Fuglevand) and F31 DC012697 (to R. A. Lester).
DISCLOSURES
No conflicts of interest, financial or otherwise, are declared by the authors.
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