From catastrophe to complexity: A novel model of integrative central neural regulation of effort and fatigue during exercise in humans: Summary and conclusions

Research Unit for Exercise Science and Sports Medicine, University of Cape Town, Sports Science of South Africa, PO Box 115, Newlands 7725, South Africa.
British Journal of Sports Medicine (Impact Factor: 5.03). 03/2005; 39(2):120-4. DOI: 10.1136/bjsm.2003.010330
Source: PubMed


It is hypothesised that physical activity is controlled by a central governor in the brain and that the human body functions as a complex system during exercise. Using feed forward control in response to afferent feedback from different physiological systems, the extent of skeletal muscle recruitment is controlled as part of a continuously altering pacing strategy, with the sensation of fatigue being the conscious interpretation of these homoeostatic, central governor control mechanisms.

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Available from: Timothy Noakes, Sep 03, 2014
    • "According to the corollary discharge model (Marcora 2009), the perception of effort is determined by a feedforward mechanism, where increases in RPE over time are the result of a " … conscious awareness of the central motor commands to the locomotor and respiratory muscles " (Marcora 2009, p 2061). In contrast, the central governor model proposes that exercise responses are predetermined by an unconscious " governor " and that these responses are independent of any efferent or afferent inputs (Noakes et al. 2005). The exercise pressor reflex model suggests that group III and IV afferent fibers in the working muscle (leg, thigh, or respiratory muscles) respond to mechanical (group III) and metabolic (group IV) stimuli and provide feedback that contributes to ventilatory, cardiovascular, and perceptual responses (Amann et al. 2010; Kaufman et al. 1983; St. Croix et al. 2000). "
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    ABSTRACT: This study examined: (1) the sustainability of the critical heart rate (CHR) minus 5 b min(-1) (CHR - 5) and CHR plus 5 b min(-1) (CHR + 5); (2) the ratings of perceived exertion (RPE), velocity, [Formula: see text], minute ventilation ([Formula: see text]), breathing frequency (f b ), and electromyographic amplitude (EMG AMP) and EMG mean power frequency (MPF) responses during treadmill running at CHR - 5 and CHR + 5 to determine what factors underlie the perception of effort when heart rate (HR) is held constant; and (3) the relationships among RPE, [Formula: see text], and HR, to determine which variable(s) reflect exhaustion during exercise performed at a constant HR. The CHR was determined in eight runners (mean ± SD; age = 24 ± 3 years) from a series of four exhaustive, constant velocity runs. The RPE, velocity, [Formula: see text], [Formula: see text], f b , EMG AMP, and EMG MPF responses were recorded during runs at the CHR - 5 and CHR + 5. At CHR - 5, RPE, f b, and EMG MPF increased, while velocity, [Formula: see text], [Formula: see text], and EMG AMP decreased. At CHR + 5, RPE and f b increased, velocity, [Formula: see text], [Formula: see text], and EMG AMP decreased, and EMG MPF remained constant. The close association between f b and RPE throughout the run at CHR - 5 and during the last 50 % of the run at CHR + 5 indicated that muscle afferents may have provided feedback from metabolic and mechanical stimuli that contributed to the perceptual responses. In addition, only RPE consistently indicated exhaustion and the current findings supported its use to monitor exercise performed at a constant HR.
    Arbeitsphysiologie 06/2015; 115(10). DOI:10.1007/s00421-015-3204-y · 2.19 Impact Factor
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    • "Subsequently, steplike (1–3 min) increases in intensity were typically used (McArdle et al. 1973) followed by the development of the ramp protocol (RAMP) (Whipp et al. 1981), which is characterized by gradual increases in intensity until volitional exhaustion, with test duration typically lasting 8–12 min (Astorino et al. 2004; Midgley et al. 2006). In the last 20+ years, this protocol has been widely used to assess V ˙ O 2max , yet has also been identified (Noakes et al. 2005) as an unnatural form of exercise in that the exerciser has no idea when the test ends and moreover, the exerciser is not in control of effort and must merely respond to the workload placed on the ergometer. This growing criticism serves to question the "
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    ABSTRACT: Recently, a self-paced protocol demonstrated higher maximal oxygen uptake versus the traditional ramp protocol. The primary aim of the current study was to further explore potential differences in maximal oxygen uptake between the ramp and self-paced protocols using simultaneous measurement of cardiac output. Active men and women of various fitness levels (N = 30, mean age = 26.0 ± 5.0 years) completed 3 graded exercise tests separated by a minimum of 48 h. Participants initially completed progressive ramp exercise to exhaustion to determine maximal oxygen uptake followed by a verification test to confirm maximal oxygen uptake attainment. Over the next 2 sessions, they performed a self-paced and an additional ramp protocol. During exercise, gas exchange data were obtained using indirect calorimetry, and thoracic impedance was utilized to estimate hemodynamic function (stroke volume and cardiac output). One-way ANOVA with repeated measures was used to determine differences in maximal oxygen uptake and cardiac output between ramp and self-paced testing. Results demonstrated lower (p < 0.001) maximal oxygen uptake via the ramp (47.2 ± 10.2 mL·kg(-1)·min(-1)) versus the self-paced (50.2 ± 9.6 mL·kg(-1)·min(-1)) protocol, with no interaction (p = 0.06) seen for fitness level. Maximal heart rate and cardiac output (p = 0.02) were higher in the self-paced protocol versus ramp exercise. In conclusion, data show that the traditional ramp protocol may underestimate maximal oxygen uptake compared with a newly developed self-paced protocol, with a greater cardiac output potentially responsible for this outcome.
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    • "The aim of this study was to explore the possible implications of circadian rhythms in CBF (indexed from MCAv), BP, and cerebrovascular control on maximal exercise performance. The focus was on trained athletes, as such changes may be a critical factor in maximal performance limitations where greater motor unit recruitment may enhance central fatigue (Noakes et al., 2005). Rowing was chosen because (a) this rhythmic whole-body exercise seems to challenge CBF control (Pott et al., 1997) and is thus potentially susceptible to time-of-day alterations in its control, and (b) performance is highly reliable in trained rowers performing the standard 2000-m ergometer test (Schabort et al., 1999). "
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    ABSTRACT: The purpose of this study was to characterize cerebrovascular responses to rowing exercise, investigating whether their diurnal variation might explain performance differences across a day. Twelve male rowers completed incremental rowing exercise and a 2000-m ergometer time trial at 07:00 h and 16:00 h, 1 week apart, while middle cerebral artery velocity (MCAv), cerebral (prefrontal), and muscular (vastus lateralis) tissue oxygenation and hemoglobin volume (via near-infrared spectroscopy), heart rate, and pressure of end-tidal CO2 (PET CO2 ) were recorded. MCAv was 20-25% above resting levels (68 ± 12 cm/s) during submaximal and maximal exercise intensities, despite PET CO2 being reduced during maximal efforts (down ∼ 0.5-0.8 kPa); thus revealing a different perfusion profile to the inverted-U observed in other exercise modes. The afternoon time trial was 3.4 s faster (95% confidence interval 0.9-5.8 s) and mean power output 3.2% higher (337 vs 347 W; P = 0.04), in conjunction with similar exercise-induced elevations in MCAv (P = 0.60) and reductions in cerebral oxygenation (TOI) (P = 0.12). At the muscle, afternoon trials involved similar oxygen extraction (HHb volume and TOI) albeit from a relatively lower total Hb volume (P < 0.01). In conclusion, rowing performance was better in the afternoon, but not in conjunction with differences in MCAv or exercise-induced differences in cerebral oxygenation.
    Scandinavian Journal of Medicine and Science in Sports 06/2014; 25(4). DOI:10.1111/sms.12273 · 2.90 Impact Factor
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