(2 points) Briefly discuss 2 things you learned after reading Guyton’s chapters on Muscle
and Motor Control (include any necessary illustrations).
a.There are three levels at which human motor control can function. The most
basic of these is the spinal level where reflex reactions and other sorts of
instinctive behavior are embedded. For example, the quick withdrawal
from a source of sharp pain is a spinal-controlled reaction. Similarly,
highly coordinated, involuntary movements, such as those associated with
walking or crawling, are spinally-controlled. Since it is the lowest level of
brain-function, spinal responses are often the fastest responses. This level
seems to have evolved as a set of default reflex actions that the body
performs under an elevated threat level while the higher brain levels
attempt to consciously figure out how best to deal with the threat. The
next-highest level is the hindbrain, which controls movements that are
required to maintain a given posture or continuous set of movements.
Maintaining balance while standing on a flat surface is an example of a
hindbrain-level movement. The hindbrain level seem to have evolved as a
closed-loop control system with a high response-time which is principally
intentioned to maintain balance, stability and posture without having to
consciously think about it. The highest level of brain function is the
corticospinal level, which controls learned responses (as opposed to the
instinctive responses controlled by the lower levels). This is by far the
most complex of the levels of motor control and is responsible, in many
cases, for triggering the hindbrain and spinal controls. Similarly, the
corticospinal level can inhibit other levels and thus prevent them from
operating. Since the corticospinal level is farther removed from most part
of the body than the spinal or hindbrain levels, there is usually a larger
time lag between stimulus and corticospinal response than there is
between a spinal or hindbrain response.
b. Like bones, muscles are continuously undergoing a remodeling process to
match their structure to their function. For muscles, this process occurs on
the order of a few weeks (as opposed to on the order of decades for
bones). Therefore, muscular atrophy will result very quickly if a specific
muscle is not used very often. In the space environment, this often means
that muscles that are used for antigravity, such as most of the leg muscles,
will be too weak to in an Earth-normal environment after a long period in
microgravity. On the other hand, muscular hypertrophy, which tends to
increase muscle size or length, can be achieved by stretching and
contracting muscle fibers at their maximum loading levels. This implies
that the nocive effects of the space environment on muscle tone can be
counteracted by strenuous exercise during and after a stint in the
microgravity environment.
4.1The innervation ratio is the number of muscle fibers activated by a single alpha
motoneuron. Consider a simplified muscle model that consists of 1000 fibers with
the following distribution:
500 slow fibers, 300 fast fatigue resistant fibers, 200 fast fatigable fibers
driven by 3 alpha motoneurons. How can you implement this in the simulink
model?
This is already implemented in the Simulink model. Since the gain, G, can equal 1
without loss of generality, it can also be 1000/3 or any other number. This implies
that the Figure of Merit for the innervation ratio is the percentage of each type of
fiber. Thus, setting the number of slow fibers to 0.5, the number of fast fatigue
resistant fibers to 0.3 and the number of fast fatigable to 0.2 will accomplish this
implementation. Scope 1 overlays these 3 twitch responses on to the same graph. See
Printout 1 for this output.
4.2 Consider all fibers activated and in a fused tetanus state. To do so with the
Simulink model, simply replace the “pulse generators” by a step... Now the output
is the sum of the tensions produced by the 3 types of fibers. Run the simulation
and discuss the force output.
The sum of the three force outputs is visible in scope 2, which acts to add all three
step responses. There is a very slight overshoot in this response which is the result of
the fast fibers achieving their maximum value before the slow fibers do. The longer,
more sustained climb of the slow muscle fibers acts to smooth the overall response.
This is evident from the fact that the peak time of the slow fiber response is equal to
the peak time of the overall response. A result of this action is that the slope of the
response curve approaches the slope of the fast curve for the start of the step
response. After 0.2 seconds the slope becomes much more similar to that of the slow
response curve. Overall, the response seems to approach steady-state relatively after
about 0.5 seconds. The steady state magnitude of this output is eqal to the sum of the
magnitudes of the individual steady states, i.e. 1.7 N. Printouts of the inidviudal and
summed step responses are available on prinouts 2 and 3 respectively.
4.3Consider this result to be the overall maximum force generated by the lower limbs
of a person in a 1G environment during an intense physical effort (i.e. All fibers
activated)...During a normal stance with only the slow fibers activated, what is the
maximum force generated by the lower limbs?
According to the previous model, the maximum force is that encountered by the slow
fibers at their peak time. Since the other fibers are not activated, we only need to
consider the lowermost graph in printout 2. This graph, when analysed more closely
with the zoom tool shows that maximum force is just under 0.53 and occurs at 0.38
seconds after the initial step, as per the MATLAB graph. Printout 4 shows this peak.
What is the activation pattern?
The activation pattern is therefore [alpha = 1, beta = 0, gamma = 0]. Since Matilda
weighs 480N, this implies that steady-state slow-muscle force is equal to 480 N.
Therefore, the maximum force exerted by the muscle at its peak is 480*(0.53/0.5) =
508.8 N. Furthermore, the overall maximum steady-state force she can generate if she
uses all of her muscle fibers is 480*(1.7/0.5) =1632 N.
4.4After spending several days onboard the space shuttle, Matilda returns with
noticeable atrophy of her lower limbs...assume that 150 fast fibers were damaged,,
120 fast fatigue-resistant fivers and 100 slow fibers were damaged. How can you
implement these changes into the Simulink model?
The above statement implies that 400 slow, 180 fast fatigue-resistant, and 50 fast
fibers are still healthy. Dividing each one of these by 1000 yields the values that
should be changed in the Simulink model. Thus the associated innervation ratios are:
Slow = 0.4,
Fast fatigue-resistant = 0.18
Fast = 0.05
Upon return to Earth, can Matilda stand up under her nominal activation pattern?
What is her force output in this case?
Upon her return to Earth, Matilda can put out 8/10 of her previous slow muscle force.
This translates to a peak of 407.04 N with a steady state of 384 N. She cannot stand
up. The minimum activation pattern for her to stand requires that she generate an
additional 96 N of force in steady state. Since she is not using her fast fibers, this
additional force must come from her fatigue-resistant fibers, which put out
480*0.6/0.5 = 576 N before the Shuttle Mission. Now, she can put out a maximum of
576 * 0.18/ 0.3 = 345.6 N, which corresponds to her maximum of beta = 2. For her to
put out 96 N, beta must therefore equal 0.56. Therefore, her minimal activation
pattern is [alpha = 1, beta = 0.56, gamma = 0].