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Re: The end-spurt does not require a subconscious intelligent system, just our conscious brain

Dear Editor

I agree with Professor Tim Noakes that the presence of an end-spurt cannot be explained by either the traditional peripheral fatigue model, or the more recent negative feedback model proposed by Amann and Dempsey [1, 4]. However, I think that the presence of an end-spurt is also at odds with Noakes’ central governor model.

In fact, a subconscious intelligent system capable of regulating in anticipation the central neural drive to the locomotor muscles on the basis of a known end-point and afferent feedback from a variety of intero-and extero-receptors should not allow for an end-spurt. On the contrary, it should choose from the very start the maximum speed that can be sustained over 4 miles without dangerous homeostatic failure and, in stable environmental conditions, provide very small but frequent adjustments in central motor command/speed during the race in relation to unpredictable small changes in the physiological conditions of the body. This is the typical functioning of subconscious physiological control systems of homeostasis, and this principle should apply to the central governor as well.

On the other hand, the end-spurt is perfectly compatible with an effort-based decision-making model of exercise performance. When the exercise task is simple (constant-workload or incremental exercise tests to exhaustion), the goal is to last for as long as possible and the conscious decision to take is simple: do I keep going or do I stop? In these testing conditions anticipation is not necessary, and time to exhaustion is determined by two psychological factors: i) potential motivation (the maximum effort a person is willing to exert in order to satisfy a motive) and ii) perceived exertion [2-3, 5].

When the exercise task is more complex (time trials in the lab or actual endurance competitions such as the 4-mile races analysed by Noakes), the conscious decision to take is also more complex: at which speed do I run at the beginning, middle, and end* of the race? Again potential motivation and perception of effort play a major role. However, we need additional conscious information to allow for such complex decision-making process. These conscious information are iii) memory of perception of effort during previous exercise bouts of different intensities and duration, and in different environmental conditions, iv) knowledge of total distance to cover, v) knowledge of distance covered/remaining. Precise knowledge of running speed (or, in the field, running time over a certain distance) certainly helps conscious regulation of pacing, but it is not crucial because our kinaesthetic sense gives us good enough information. Conveniently, we also exclude tactical considerations and we assume that the goal (as in time trials) is to finish the race in the shortest time possible.

Because precise conscious anticipation of perceived exertion and running speed at the end of the race is not possible (and because finishing the race is paramount), athletes usually choose a slightly conservative pace for most of the race. Near the end of the race, when the information provided by the conscious sensation of effort at a certain running speed is more reliable, most “conservative” athletes realise that they can significantly increase running speed without reaching exhaustion before the finishing line, and decide to go for an end-spurt. No additional subconscious intelligent system needed, just our conscious brain.

* such simplistic tripartite subdivision is for illustration purposes only. Decisions about running speed may vary in frequency depending on tactical considerations and other factors

References

1. Marcora S. Is peripheral locomotor muscle fatigue during endurance exercise a variable carefully regulated by a negative feedback system? J Physiol. 2008; 586(7): 2027-8.

2. Marcora SM. Do we really need a central governor to explain brain regulation of exercise performance? Eur J Appl Physiol. 2008; DOI: 10.1007/s00421-008-0818-3.

3. Marcora SM, Bosio A, de Morree HM. Locomotor muscle fatigue increases cardiorespiratory responses and reduces performance during intense cycling exercise independently from metabolic stress. Am J Physiol Regul Integr Comp Physiol. 2008; 294(3): R874-83.

4. Noakes TD, Marino FE. Arterial oxygenation, central motor output and exercise performance in humans. J Physiol. 2007; 585(Pt 3): 919-21.

5. Wright RA. Refining the Prediction of Effort: Brehm's Distinction between Potential Motivation and Motivation Intensity. Soc Pers Psychol Compass. 2008; 2(2): 682-701.

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Re: The interpretation of mile world-record split times

Dear Editor,

In the recent article published online (18th April, 2008) Noakes et al. (2008) present some interesting data detailing lap-times recorded en- route to world record performances in the one mile run. These data show that, on average, the times for the second and third laps were significantly slower than those for the first and last lap. Subsequently, Noakes et al. (2008) interpret these data as being supportive of the Central Governor hypothesis; a complex anticipatory regulatory system in which running speed is dictated primarily by motor unit recruitment as determined by a central governor (the brain) (Noakes et al., 2004), rather than a catastrophe model, in which pacing strategy is dictated by the development of peripheral fatigue. Indeed, the increase in running speed (end-spurt) during the final lap is purported to be incompatible with a model in which pacing strategy is regulated by peripheral fatigue. However, these data, and their interpretation, raise a number of interesting questions.

Firstly, the observation that the running pace is reduced significantly after the first lap might alternatively be interpreted as indicative of the selection of a sub-optimal pacing strategy i.e. the anticipatory selection of a running speed that cannot be sustained for the entire race distance. Another explanation is that the pace of the first lap is influenced by the tactical requirement for a good position. Indeed, the impact of the presence of other athletes on the interpretation of the lap times does not appear to have been considered. In the majority of the races presented the record-breaking athlete will not have led the race from the start to the finish, while in many instances pace-makers will have been employed to dictate a pre-determined pace strategy for a portion of the race. Thus, the pacing strategy selected by the record breaking athlete may not be entirely autonomous for portions of the race, and consequently may not be optimal. The observation that in most instances the last lap of the race was the fastest might also support this interpretation. Alternatively, this competitive element may have played a role in the slower pace during the middle portion of the race, with the athletes ensuring a ‘reserve’ for the latter portion of the race. Regardless of the interpretation, it is clear that the competitive influences on the pacing strategy employed in a race situation should not be underestimated.

Noakes et al. (2008) also point out that if peripheral fatigue and the failure of the exercising limb to maintain homeostasis are the factors determining pacing strategy, then the pace would fall with each successive lap (with no end-spurt). However, this is precisely the pacing strategy consistently evident during the 800 m run (Tucker et al., 2006). Moreover, this pacing strategy is also evident during track cycling in both the 1 km time trial and 4 km individual pursuit (Corbett, 2008 unpublished observations); events which are less likely to be influenced by the pacing strategies of other competitors and require the athlete to complete a set distance in the fastest time possible. In addition, the 4 km individual pursuit is of a comparable duration to the one mile run (~4 min). This might suggest that either the pacing strategy is regulated by different mechanisms in these events, or that a sub-optimal pacing strategy is employed in one of these examples. Perhaps the end-spurt is an example of a sub-optimal pacing strategy?

That a pacing strategy is selected by some central mechanism in anticipation of an event appears undeniable; experienced athletes do not commence the mile race at the same speed as a 100 m race. However, the extent to which the pacing strategy predominating in the mile race (with the presence of an end-spurt), is optimal, remains unclear.

Jo Corbett
Martin Barwood

References

Noakes, TD, St Clair Gibson, A. Lambert EV. From catastrophe to complexity: a novel model of integrative central neural regulation of effort and fatigue during exercise in humans. Br. J. Sports Med. 2004;38:511-14.

Noakes, TD, Lambert, L, Human, R. Which lap is the slowest? An analysis of 32 world record performances. Br. J. Sports Med. 2008: Apr 18. [Epub ahead of print].

Tucker, R, Lambert, MI, Noakes, TD. An analysis of pacing strategies during men’s world-record performances in track athletics. Int. J. Sports Physiol. Perform. 2006;1:233-45.