Setting the scene with two examples and a summary of models
In yesterday’s post, we looked at the admittedly rather obvious question of why a pacing strategy exists. It’s a question that is often dismissed as non-sensical and irrelevant with an obvious answer, but hopefully, it’s possible to recognize that in fact, this question has profound implications for exercise physiology. First of all, it has no explanation according to the prevailing theory for fatigue. Secondly, it stimulates one to think a little more deeply about why such an obvious thing exists. In otherwords, is it conscious or sub-conscious, or perhaps even “pre-conscious”? Is it simply a function of training and experience? But then, how does training help you understand how to pace yourself? What is the mechanism?
In any event, the next step to take is to delve a little more into the issue, and I thought that two examples of fatigue-models might help to explain some lingering questions. Once again, I must stress that I have no definitive answer here – no one does. But it’s a stimulating discussion, and we’re working towards a model for fatigue which will be evidence-based (promise!)
So the two examples for today are the “leaky calcium channel” theory and the model of exercise in the heat.
The leaky calcium channel theory
Yesterday’s post also introduced a theory that hit the news earlier this year, when scientists discovered that a possible cause for fatigue might be what they called “leaky calcium channels“. The one sentence summary of this theory is that exercised muscle becomes fatigued due to calcium channels which become progressively more and more “leaky”, causing the force of contraction to go down. It was a landmark study, and caused much excitement in the field, thanks to a somewhat sensationalized article in the New York Times. (This is, incidentally, a great example of how people will find “silver bullet” explanations for complex issues. Fatigue is not a problem waiting to be “solved”, but it’s reported this way, for admittedly understandable reasons. We certainly would not claim to have any answer so exciting and definitive!)
Consider for a moment the implications of this theory for endurance exercise – the best example is if you are doing interval training on the track. Let’s say you’re doing 5 x 800m repeats. If you ran without a watch, and your goal was to run the TOTAL SESSION as hard as possible, and you were running alone (very important – we’ll look at how “social factors” influence pacing later in the series!), then I can almost guarantee that your pace will go FAST-SLOWER-SLOWER-SAME-FASTEST for the five repeats. It’s the same pattern as we saw yesterday from Haile Gebrselassie and just about any other athlete doing self-paced exercise.
But the leaky calcium theory is saying that the reason you slow down and develop fatigue is that your muscles becomes less and less able to exert their normal force. Now, the key requirement for this to be true, which I hope is obvious to people, is that all the muscle has to be active. Because if there is any muscle that is INACTIVE, then that muscle would surely not be affected by “leaky calcium channels”? The inactive muscle could simply be activated and the pace would be maintained.
“Ah”, you say, “but that’s not an intelligent pacing strategy!”. To which my response is “Yes, but please tell me how the body knows this, when the problem is a leaky calcium channel in the muscle? How is it even remotely possible in this explanation that you can be aware of the fact that your slow down is being caused by a tiny channel in the muscle?” The point is, in this system, there is no allowance for your perception or “intelligence”, and surely intelligent pacing requires that you somehow KNOW what is going on with your body?
Therefore, pacing during endurance exercise is also incompatible with the calcium channel theory. Note that this DOES NOT mean calcium channels are not somehow involved, for a I believe they are. I said in the first post of this series, the trick is to balance the extremes, and we’ll hopefully manage to integrate all the information moving forward.
So here’s the thing – we know that muscle is not 100% active during your 10km race. In fact, even when you do your best to exert maximal force for FIVE SECONDS, there is evidence that you still keep some “reserve” capacity. We know that because if someone is doing a maximal 5 second contraction, and you stimulate the muscle using an electric current, the force can go up, so clearly what the person thought was “everything” was actually still sub-maximal! So a reserve is a universal feature of any voluntary effort, regardless of how hard you try. Now, given that fact, one can appreciate that it is impossible to explain how any biochemical change – lactate, hydrogen, leaky calcium – can force you to slow down, either consciously (intelligent pacing) or unconsciously (acting on the muscle).
Exercise and pacing in the heatThe best comparison between “limitations” and “regulation”
To illustrate this point before we move onto Part II, perhaps the best example of how the pacing strategy comes into play is during exercise in the heat. This is a topic we’ll devote an entire week to later on, because the heat is the best example of a “homeostatic failure” model compared to a model for “anticipatory regulation”, because it changes the INPUTS, as we spoke about yesterday. Perhaps this example should have been used instead of the “endspurt” question, because it’s a lot more logical to work through.
Basically, there are two lines of thought for why exercise performance in the heat is compromised:
The “Peripheral” model for fatigue in the heat – failure causes fatigue
This theory says that fatigue in the heat is the result of a failure to keep the body temperature down. When the body temperature rises, it causes fatigue because the overheated brain is less capable of activating muscle to keep exercise going. This theory was first developed through a series of very novel research studies by scientists in Denmark – Savard, Nybo & Nielsen are the common names, for those who are interested.
Basically, what they have done is find that once the body temperature hits 40 degrees, the athlete:
- Stops exercise – fatigue co-incides with this “limiting” temperature, hence the name “critical core temperature hypothesis for fatigue in the heat”
- Activates less muscle – muscle must be stimulated to contract, and what Nybo and Nielsen showed is that the activation of muscle by the “hot” brain is lower than that by the “cool” brain after exercise
- Has altered brain function – they measured brain waves during exercise and found that certain waves are altered, which suggests “reduced arousal” levels.
Their conclusion? Exercise is impaired in the heat because the body temperature rises until it reaches limiting values. At this point, the brain fails to activate the required muscle, and the athlete can no longer continue exercise.
A couple of key points: Firstly, there are a few details in the explanation of why the brain fails to activate muscle that we’ll get into later. However, what is key to realise is that these studies, while excellent and crucial to our understanding of the heat, have failed to recognize that during any form of exercise, it is possible to slow down long before you stop! In other words, because these studies force people to exercise at a fixed power output until exhaustion, the conclusion they make is that fatigue is caused by some “failure”. They then extend this finding to say that “impaired performance” is caused by the same thing, when in fact, they don’t measure what happens BEFORE the limiting temperature is reached!
An anticipatory regulation model for exercise in the heat
The alternative model is that performance is regulated well before the limiting temperature is reached. For this to be true, it would require that the athlete slow down at sub-maximal body temperatures. And there is evidence for this – Frank Marino from Australia found it in runners, Stephen Cheung of Canada found it for small muscle groups, and I found it a couple of times in the heat in studies that have all been published (If you’d like these references, please let me know – I’m not going to include them in the text because it breaks the flow – there are some below, however)
Thus, the athlete should start slowing down even though the body temperature is not different from that in the cool condition. As a result of slowing down, the athlete would be producing less heat, and so the fall in work rate will ultimately produce body temperatures that are not different to those measured in the cool conditions! In otherwords, you don’t slow down BECAUSE you are hot, you slow down in order to prevent yourself from getting hot!
Perhaps most interestingly, we’ve actually measured that LESS MUSCLE is activated during cycling in the heat than in the cool conditions. This was a study I did in 2004, and it will be discussed in detail later, but the key point was that cyclists in the heat slowed down very early on, when nothing measurable was different, and they did so by activating less muscle. That’s completely incompatible with the “peripheral fatigue” model.
This will, I’m sure, be dismissed as obvious by many, but again, the crucial question is HOW is this achieved? To refer to yesterday’s post, what are the inputs, how are they interpreted, and what is the output in response? These, and many more questions, are on the way.
Summarizing the models: A platform to move forward
The two diagrams below are concise summaries of the last two posts. The first diagram, directly below, shows what I have called “The homeostatic limitation model”.
This model shows the following:
- Muscle contraction during exercise is responsible for producing changes, including biochemical ones (leaky channels, fall in pH, lactate, phosphates etc), as well as changes to the cardiovascular system, energy system (glycogen is depleted and blood glucose falls), and thermoregulatory (body temperature rises, as discussed). The figure shows, from top to bottom: A mitochondria, the liver for energy supply, the heart, and body temperature.
- These changes DIRECTLY inhibit exercise, either by:
- Causing the muscle to lose its force generating ability. This is the theory for lactate, phosphates, oxygen supply (the “anaerobic” limit to exercise) and calcium ions; or
- By acting on the brain to force the muscle activation levels down. This is the case with high body temperatures, as discussed briefly above.
The key to this model is that failure is responsible for fatigue. Something has gone “wrong”, either with oxygen delivery, biochemistry, blood supply, or body temperature, and this has impaired the athlete’s ability to exercise at the same pace, so they slow down. One very important point I must make is that this model makes absolutely no allowance for pacing – I’ve said this many times before, but there is no feedback from these systems that would allow the suggested “intelligent” pacing to take place!
The figure below shows the model for “Anticipatory regulation“.
In this model, which was introduced yesterday, there are INPUTS and OUTPUTS.
The INPUTS are provided by the heart, liver (or energy supply), body temperature or rate of heat storage, biochemistry, and then, very importantly, the brain itself!
These INPUTS provide what is called afferent feedback to the brain, informing it of the situation. This feedback provides information on things like “How hot is it?”, “How much energy is available today?”, “What is the pH of the tissues?”, “What is the heart doing?”, and basically “Is it safe to keep going at this pace?”.
In response, the brain integrates all this information, then evaluates it in the context of the exercise bout before enforcing some output on the system. Key to this evaluation is to know how far the athlete has gone, how far they still have to go, and a host of other inputs or “moderators”. We’ll discuss all these in turn. Regardless, the end result of this process is the OUTPUT – the activation or the inhibition of muscle. This is responsible for controlling the force output of the muscles, and hence the pacing strategy.
It’s important to recognize the presence of the brain as an INPUT in this model. That is, the brain informs the brain (pardon the creative licence!) of certain key inputs before and during exercise. These include memory (the hippocampus, presumably, is the part of the brain involved), experience/training, and then crucially, social factors, or social facilitation. One cannot ignore these “conscious” cues that must also impact heavily on performance.
Also bear in mind that what you all know as true is that when you’re in a race, you race with tactics and the presence of other athletes. There is no explanation for this, no mechanism, according to a “limitations” model…how would leaky calcium channels be integrated into racing? It can’t be, because tactics and “intelligence” requires that the brain be involved…so you might actually be closer to this model than you realise!
So that is the model, which at this stage is just a theory, I admit! In the coming posts, we have to back-track a little, and look at pacing strategies, and then we’ll move on to systematically evaluating and discussing each of the various INPUTS I’ve put forward. Importantly, we must gather the evidence, otherwise, this is all just conjecture! That evidence most definitely exists, and the next phase of this series will be to examine that evidence, logically and thoroughly. I’ll be breaking it up into much smaller pieces, however, so don’t worry, this is the last “mega-epic post” for a while!
Speaking of theory, we can now attempt to answer that most basic of questions that started this whole series: The “endspurt” is the result of an increase in muscle activation, controlled by the brain in response to numerous INPUTS during exercise. It occurs because the finish line is approaching, and the physiological changes are no longer deemed harmful or potentially limiting to continuing exercise. The reserve can thus be activated!
Stick with this, and hopefull that will evolve from being mere theory to fact!
Have a good weekend!
Some relevant references, for those interested:
- Savard et al (1988), J Appl Physiol 64: 649 – 657
- Nybo and Nielsen (2001), J Appl Physiol 91: 1055-1060
- Nybo and Nielsen (2001), J Apply Physiol 91: 2017-2023
- Nybo et al. (2002), J Physiol, 545: 697-704
- Marino et al. (2004), J Appl Physiol, 96: 124-130
- Marino (2004), Comp Biochem Physiol B Biochem Mol Biol 139, 561-569
- Tatterson (2000), . J Sci Med Sport 3, 186-193
- Tucker et al. (2006), J Physiol 574, 905-915
- Tucker et al. (2004), . Eur J Physiol 448, 422-430