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Brain activity during self-paced vs. fixed protocols in graded exercise testing

DOI:10.1007/s00221-019-05669-x
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Rachel Dykstra at Nebraska Wesleyan University
Rachel Dykstra
Nicholas J. Hanson at Western Michigan University
Nicholas J. Hanson
Mike Miller at Western Michigan University
Mike Miller
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Abstract and Figures

Electroencephalography research surrounding maximal exercise testing has been limited to male subjects. Additionally, studies have used open-looped protocols, meaning individuals do not know the exercise endpoint. Closed-loop protocols are often shown to result in optimal performance as self-pacing is permitted. The purpose of this study was to compare brain activity during open- and closed-loop maximal exercise protocols, and to determine if any sex differences are present. Twenty-seven subjects (12 males, ages 22.0 ± 2.5 years) participated in this study. A pre-assembled EEG sensor strip was used to collect brain activity from specific electrodes (F3/F4: dorsolateral prefrontal cortex, or dlPFC; and C3/Cz/C4: motor cortex, or MC). Alpha (8–12 Hz) and beta (12–30 Hz) frequency bands were analyzed. Subjects completed two maximal exercise tests on a cycle ergometer, separated by at least 48 h: a traditional, open-loop graded exercise test (GXT) and a closed-loop self-paced VO2max (SPV) test. Mixed model ANOVAs were performed to compare power spectral density (PSD) between test protocols and sexes. A significant interaction of time and sex was shown in the dlPFC for males, during the GXT only (p = 001), where a peak was reached and then a decrease was shown. A continuous increase was shown in the SPV. Sex differences in brain activity during exercise could be associated with inhibitory control, which is a function of the dlPFC. Knowledge of an exercise endpoint could be influential towards cessation of exercise and changes in cortical brain activity.
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Experimental Brain Research (2019) 237:3273–3279
https://doi.org/10.1007/s00221-019-05669-x
RESEARCH ARTICLE
Brain activity duringself‑paced vs. xed protocols ingraded exercise
testing
RachelM.Dykstra1 · NicholasJ.Hanson1· MichaelG.Miller1
Received: 27 August 2019 / Accepted: 5 October 2019 / Published online: 24 October 2019
© Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract
Electroencephalography research surrounding maximal exercise testing has been limited to male subjects. Additionally,
studies have used open-looped protocols, meaning individuals do not know the exercise endpoint. Closed-loop protocols are
often shown to result in optimal performance as self-pacing is permitted. The purpose of this study was to compare brain
activity during open- and closed-loop maximal exercise protocols, and to determine if any sex differences are present. Twenty-
seven subjects (12 males, ages 22.0 ± 2.5years) participated in this study. A pre-assembled EEG sensor strip was used to
collect brain activity from specific electrodes (F3/F4: dorsolateral prefrontal cortex, or dlPFC; and C3/Cz/C4: motor cortex,
or MC). Alpha (8–12Hz) and beta (12–30Hz) frequency bands were analyzed. Subjects completed two maximal exercise
tests on a cycle ergometer, separated by at least 48h: a traditional, open-loop graded exercise test (GXT) and a closed-loop
self-paced VO2max (SPV) test. Mixed model ANOVAs were performed to compare power spectral density (PSD) between
test protocols and sexes. A significant interaction of time and sex was shown in the dlPFC for males, during the GXT only
(p = 001), where a peak was reached and then a decrease was shown. A continuous increase was shown in the SPV. Sex
differences in brain activity during exercise could be associated with inhibitory control, which is a function of the dlPFC.
Knowledge of an exercise endpoint could be influential towards cessation of exercise and changes in cortical brain activity.
Keywords Electroencephalography· GXT· Perceptual regulation· Inhibitory control
Introduction
Exercise performance within an individual is manipulated
based on feedback by various physiological systems con-
trolled by the brain (Brümmer etal. 2011b). For example,
growing evidence has suggested that the onset of fatigue
leading to exercise termination is linked to afferent feed-
back, a neural factor that is controlled and interpreted by
the brain (Robertson and Marino 2015b); specifically, this
afferent feedback relates to sensory information recognizing
unpleasant stimuli such as lactate accumulation in working
muscles (Ishii and Nishida 2013), peripheral locomotor mus-
cle fatigue (Amann 2011) or an increase in core temperature
(Thompson 2006), to which the brain initiates a response
(Robertson and Marino 2015b). There is evidence that the
prefrontal cortex (PFC) plays an important role in cessation
of exercise by inhibiting activity within the motor cortex
(Noakes 2012; Robertson and Marino 2015b). Afferent feed-
back from periphery is sent to the PFC, where it is then inter-
preted and influences the decision to stop (Amann 2011).
Therefore, monitoring changes in brain activity during exer-
cise could be highly advantageous (Bailey etal. 2008) and
help researchers and practitioners understand more about
the relationship between exercise duration, modality, and
intensity (Bailey etal. 2008). With this, electroencephalog-
raphy (EEG) has been proposed as a pragmatic, noninvasive
method of providing useful information surrounding changes
in brain activity during rest and exercise.
EEG measures cortical brain activity, which is sepa-
rated into frequency ranges (e.g., alpha: 8–12Hz and beta:
12–30Hz), each associated with different actions or reac-
tions regulated by the brain (Schneider etal. 2009). Alpha
is a low-frequency band associated with perceptual aware-
ness and inhibition of non-essential processing, which
Communicated by Francesco Laquaniti.
* Rachel M. Dykstra
rachel.m.dykstra@wmich.edu
1 Department ofHuman Performance andHealth Education,
Western Michigan University, 1903W. Michigan Ave,
Kalamazoo, MI49008, USA
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... This pertains also for the concurrent assessment of only HRV and EEG. Thus, an interaction may only be inferred indirectly from results of previous studies investigating brain (Abeln et al., 2015;Bailey et al., 2008;Brümmer et al., 2011;di Fronso et al., 2019;Dykstra et al., 2019;Edwards et al., 2016;Gutmann et al., 2018;Jung et al., 2015;Mechau et al., 1998;Moraes et al., 2007;Robertson and Marino, 2015;Schneider et al., 2013), HRV (Banach et al., 2004;Candido et al., 2015;Cruz et al., 2017;da Silva et al., 2017;Duarte et al., 2014;Michael et al., 2017;Shiraishi et al., 2018;Yamamoto et al., 1992) and RPE (Duarte et al., 2014;Faulkner and Eston, 2007;Moraes et al., 2007) effects separately. Therefore, research interest rises to simultaneously study the reaction of the (neuro-) physiological system as well as the perceived exertion to a GXT execution. ...
... frontopolar, frontal, central, temporal, parietal or occipital lobe). Further studies (Dykstra et al., 2019;Mechau et al., 1998;Robertson and Marino, 2015) reported a decline of brain activity over the whole cortex, especially in the temporal and prefrontal cortex (PFC) at high intensities. Although several studies provided evidence for common tendencies, a concrete reproduction of results is according to the methodological differences (e.g. ...
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... Indeed, tissue hemoglobin index and oxygen extraction increased during the last 2 km when participants were informed about performance information and remaining distance [122], which was associated with more important PO, HR, MC, and parietal lobe EEG activity. Therefore, the changes in PFC activity when phenomena such as deception, preconditioning, and the knowledge of performance information happened [19] suggest the alteration of the perception of sensory signals by PFC, which contributes to impact performance. It would be interesting to investigate whether virtual environment exposure could counteract deception during cycling and therefore improve performance. ...
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