Laurie Rauch

The Role of Information Processing Between the Brain and Peripheral Physiological Systems in Pacing and Perception of Effort

This article examines how pacing strategies during exercise are controlled by information processing between the brain and peripheral physiological systems. It is suggested that, although several different pacing strategies can be used by athletes for events of different distance or duration, the underlying principle of how these different overall pacing strategies are controlled is similar. Perhaps the most important factor allowing the establishment of a pacing strategy is knowledge of the endpoint of a particular event. The brain centre controlling pace incorporates knowledge of the endpoint into an algorithm, together with memory of prior events of similar distance or duration, and knowledge of external (environmental) and internal (metabolic) conditions to set a particular optimal pacing strategy for a particular exercise bout. It is proposed that an internal clock, which appears to use scalar rather than absolute time scales, is used by the brain to generate knowledge of the duration or distance still to be covered, so that power output and metabolic rate can be altered appropriately throughout an event of a particular duration or distance. Although the initial pace is set at the beginning of an event in a feedforward manner, no event or internal physiological state will be identical to what has occurred previously. Therefore, continuous adjustments to the power output in the context of the overall pacing strategy occur throughout the exercise bout using feedback information from internal and external receptors. These continuous adjustments in power output require a specific length of time for afferent information to be assessed by the brain’s pace control algorithm, and for efferent neural commands to be generated, and we suggest that it is this time lag that crates the fluctuations in power output that occur during an exercise bout. These non-monotonic changes in power output during exercise, associated with information processing between the brain and peripheral physiological systems, are crucial to maintain the overall pacing strategy chosen by the brain algorithm of each athlete at the start of the exercise bout.

Fuel utilisation during prolonged low-to-moderate intensity exercise when ingesting water or carbohydrate

AbstractPreviously, we examined the effects of carbohydrate (CHO) ingestion on glucose kinetics during exercise at 70% of maximum O2 uptake (

Methylphenidate Enhances Grip Force and Alters Brain Connectivity.

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Modelling techniques for analysis of human activity patterns

O2,max). Here we repeat those studies in heavier cyclists (n=6 per group) cycling for 3 h at a similar absolute O2 uptake but at a lower (55% of

Methylphenidate alters brain connectivity after enhanced physical performance

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Impaired exercise performance in the heat is associated with an anticipatory reduction in skeletal muscle recruitment

O2,max) relative exercise intensity. During exercise, the cyclists were infused with a 2-3H-glucose tracer and ingested U-14C glucoselabelled solutions of either flavoured water (H2O) or 10 g/100 ml glucose polymer, at a rate of 600 ml/h. Two subjects in the H2O trial fatigued after 2.5 h of exercise. Their rates of glucose appearance (Ra) declined from 2.9±0.6 to 2.0±0.1 mmol/min (mean ± SEM) and, as their plasma glucose concentration [Glu] declined from 4.7±0.2 to below 3.5±0.2 mM, their rates of glucose oxidation (Rox) and fat oxidation plateaued at 2.7±0.4 and 1.7±0.1 mmol/min respectively. In contrast, all subjects completed the CHO trial. Although CHO ingestion during exercise reduced the final endogenousRa from 3.4±0.6 to 0.9±0.3 mmol/min at the end of exercise, it increased totalRa to 5.5±0.5 mmol/min (P<0.05). A higher totalRa with CHO ingestion raised [Glu] from 4.3±0.3 to 5.3±0.1 mM and acceleratedRox from 3.5±0.2 to 5.9±0.2 mmol/min after 180 min of exercise (P<0.05). The increased contribution to total energy production from glucose oxidation (34±1 vs. 20±1 %) decreased energy production from fat oxidation from 51±2 to 40±5% (P=0.08) and produced patterns of glucose, muscle glycogen (plus lactate) and fat utilisation similar to those during exercise at 70% of (