Even though there is a clear immediate effect of exercise during running, the effect of intensity remained somewhat unclear (no posthoc differences between low and moderate intensity) and in addition to that it should also be taken into consideration that the CCPT test takes 14 minutes and is therefore not able to depict an instant reflection of brain activity but rather gives a summary over 14min, which suggested an immediate, impairing effect of exercise right at the onset of exercising, most likely due to the immediate, consistent computational demand of running that is not-changing as indicated by no dose (intensity) effect (in the implicit system) and therefore requires a shift of resources from the prefrontal networks involved in executive and attentional control to the primary motor cortex, secondary motor cortices (i.e. premotor and SMA), basal ganglia, the motor thalamus, cerebellum, red nucleus, substantia nigra, the massive pathway systems, and the motor neurons all along the spinal cord, among many others involving sensory motor integration (Dietrich 2003).
When looking at differences within the duration (14min) of the CCPT differences in intensity became clearer. The analysis of changes during the time course of 14min points towards an involvement of the reticular activating systems at beginning of running but only during low intensity running.It could be shown that on the one hand both, commission errors and reaction time during low intensity decreased from the first three blocks to the last three blocks at ISIs of 1sec, and 1 and 2sec, respectively whereas on the other hand, during moderate intensity, commission errors and reaction time increased from the first three blocks to the last three blocks at ISIs of 2 and 4sec, and 2sec, respectively. This in-depth analyses of single block values during the time course of running and the CCPT test (14min) add more details to the hypofrontality theory and imply a facilitating effect for both, reaction time and inhibitory control (commission errors) on low intensity exercising, most likely due to a involvement of the reticular-activating system (Dietrich 2011). This effect was then shown to be overwritten/overshadowed by moderate intensity running, which led to a increase in both, reaction time and commission errors, most likely due to a higher metabolic demand put up by a higher intensity, and not by higher computational challenges.
As suggested by the reaction time summary results of the 14min the computational demand is not likely to be very different in treadmill running on low and moderate intensity and may furthermore not change very much in prolonged treadmill running. Therefore we suggest that, in addition to the spatially localized challenges of running (termed “computational demand”), which immediately caused impaired performance on average when compared to baseline, the metabolic demand will further play a role in triggering a shift of activity away from the executive and attentional networks embedded in the prefrontal cortex by means of the running intensity, which therefore intensifies activity spatially in the already exercise-type-dependent active brain networks. Even though intensity effects have been detected before (Del Giorno et al. 2010) it has never been suggested that exercise
Chapter 4 – Discussion 79
intensity stresses the activity/metabolic demand of neuronal networks encoding the mode of exercise in an intensity dependent fashion as the results of intensity-dependent impairment of response inhibition during running suggest. However, a very recent study was the first to actually give direct evidence for brain glycogen supercompensation in astrocytes following exhaustive exercise, which was correlated with the glycogen decrease during exercise (Matsui et al. 2012) showing that the extend of supercompensation was dependent on the glycogen decrease during exercise. The similarity of skeletal muscle and brain dynamics in these glycogen mechanisms lead therefore to the conclusion that higher intensities require higher turn-over rates of glycogen in the networks active and responsible for the type of movement. The threshold for this shift to become and stay evident in the cognitive measures of this study was between 40% and 60% VO2max for a exercise bout of 14min but might be
different for longer bouts of running since the energy supply might be limited in extreme cases or changes its energy transfer from the main metabolic resource to optimally supply the sustained metabolic needs and for trained people since they have optimized energy transfer system to satisfy a prolonged bout of exercise. In this regard enzyme activity level might explain the transient component of the cognitive decrease. Next to carbohydrate it has been repeatedly shown that neurons are also able to utilize lactic acid, produced by astrocytes, especially upon energy tightness (Suzuki et al. 2011). Since untrained people produce relatively more lactate that untrained, there might be a metabolic advantage for them. However, Hu & Wilson (1997) showed in a in vivo rat model that elevated lactic acid in the brain extracellular fluid could be depleted rapidly (up to 28%) in as little as 10-12sec of large neuronal activity. Instead, glutamate stimulated astrocytic glycolysis might account for neuronal substrate in longer activity. Since brain derived neurotrophic factors (BDNF) play a crucial role in cognitive performance it is worth mentioning that there is evidence that the BDNF response to exercise is not only dependent on the intensity protocol (Knaepen et al. 2010) but also on participant´s level of training (Castellano & White 2008; Zoladz et al. 2008). In more detail, higher intensity exercising leads to larger increase in BDNF and BDNF release is moderated in well-trained compared to less trained people, both evidences pointing towards a receptor desensitization.
Hence, in terms of metabolic supply athletes might achieve hypofrontality later because of larger glycogen stores. They might also stimulate the RAS less as a response to training (chronic adaptation) or have more desensitized receptors for its projections. Moreover, it should be considered that athletes are better able to oxidize fat. This might unbind tryptophan from its fatty acids and allow it to cross the blood brain barrier as a precursor for 5-HT. The computational demand is debatable, too. Athletes familiar with running would be expected to address a smaller amount of brain capacity to sustain running, which is evidenced by their economical running style. On the one side this would mean that they require higher metabolic demands to compensate for the reduced computational challenge in order to achieve a state of hypofrontality. On the other side, according to this rationale inexperienced runners would be expected to achieve a state of hypofrontality faster. However, a methodological
problem for the assessment of a hypofrontality state with cognitive tests is that with inexperienced runners there might be a dual task interference as a consequence of overloading the working memory. The present study involved young, healthy people that were familiar with treadmill running.