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ORIGINAL RESEARCH
published: 20 May 2022
doi: 10.3389/fnrgo.2022.806485
Frontiers in Neuroergonomics | www.frontiersin.org 1May 2022 | Volume 3 | Article 806485
Edited by:
Wei-Peng Teo,
Nanyang Technological
University, Singapore
Reviewed by:
Christos Frantzidis,
Aristotle University of
Thessaloniki, Greece
Dale Michael Harris,
Inspire Institute of Sport (IIS), India
*Correspondence:
James Crum
james.crum.16@ucl.ac.uk
Specialty section:
This article was submitted to
Augmented and Synthetic
Neuroergonomics,
a section of the journal
Frontiers in Neuroergonomics
Received: 31 October 2021
Accepted: 27 April 2022
Published: 20 May 2022
Citation:
Crum J, Ronca F, Herbert G, Funk S,
Carmona E, Hakim U, Jones I,
Hamer M, Hirsch J, Hamilton A,
Tachtsidis I and Burgess PW (2022)
Decreased Exercise-Induced Changes
in Prefrontal Cortex Hemodynamics
Are Associated With Depressive
Symptoms.
Front. Neuroergon. 3:806485.
doi: 10.3389/fnrgo.2022.806485
Decreased Exercise-Induced
Changes in Prefrontal Cortex
Hemodynamics Are Associated With
Depressive Symptoms
James Crum 1
*, Flaminia Ronca 2, George Herbert 1, Sabina Funk 1, Estela Carmona 2,
Uzair Hakim 3, Isla Jones 1, Mark Hamer 2, Joy Hirsch 3,4,5, 6, Antonia Hamilton 1,
Ilias Tachtsidis 3and Paul W. Burgess 1
1Institute of Cognitive Neuroscience, Faculty of Brain Sciences, University College London, London, United Kingdom,
2Institute of Sport Exercise and Health, Faculty of Medical Sciences, University College London, London, United Kingdom,
3Department of Medical Physics and Biomedical Engineering, Faculty of Engineering Sciences, University College London,
London, United Kingdom, 4Department of Comparative Medicine, School of Medicine, Yale University, New Haven, CT,
United States, 5Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, United States, 6Department
of Neuroscience, School of Medicine, Yale University, New Haven, CT, United States
People with a depressed mood tend to perform poorly on executive function tasks,
which require much of the prefrontal cortex (PFC), an area of the brain which has also
been shown to be hypo-active in this population. Recent research has suggested that
these aspects of cognition might be improved through physical activity and cognitive
training. However, whether the acute effects of exercise on PFC activation during
executive function tasks vary with depressive symptoms remains unclear. To investigate
these effects, 106 participants were given a cardiopulmonary exercise test (CPET) and
were administered a set of executive function tests directly before and after the CPET
assessment. The composite effects of exercise on the PFC (all experimental blocks)
showed bilateral activation changes in dorsolateral (BA46/9) and ventrolateral (BA44/45)
PFC, with the greatest changes occurring in rostral PFC (BA10). The effects observed
in right ventrolateral PFC varied depending on level of depressive symptoms (13%
variance explained); the changes in activation were less for higher levels. There was
also a positive relationship between CPET scores (VO2peak) and right rostral PFC, in
that greater activation changes in right BA10 were predictive of higher levels of aerobic
fitness (9% variance explained). Since acute exercise ipsilaterally affected this PFC
subregion and the inferior frontal gyrus during executive function tasks, this suggests
physical activity might benefit the executive functions these subregions support. And
because physical fitness and depressive symptoms explained some degree of cerebral
upregulation to these subregions, physical activity might more specifically facilitate the
engagement of executive functions that are typically associated with hypoactivation
in depressed populations. Future research might investigate this possibility in clinical
populations, particularly the neural effects of physical activity used in combination with
mental health interventions.
Keywords: depression, aerobic fitness (VO2max), exercise neuroscience, fNIRS (functional near infrared
spectroscopy), frontal lobe, executive functions
Crum et al. Depression & Exercise in PFC
INTRODUCTION
There appears to be a link between performance on executive
function tasks and psychopathological symptomology (see
Joormann and Vanderlind, 2014; Rock et al., 2014, for reviews).
For example, in the case of depression, greater symptom severity
and maladaptive strategies for downregulating negative emotion
are associated with worse performance on tasks requiring
response inhibition (e.g., Joormann and Gotlib, 2010; Joormann
et al., 2011), dynamic updating (e.g., Meiran et al., 2011),
and attentional switching (e.g., Malooly et al., 2013). The
most prevalent maladaptive strategy is rumination, a trait-
like proclivity to think repetitively about goal-incongruent and
mood-congruent information (Nolen-Hoeksema, 1991; Nolen-
Hoeksema et al., 2008). Whether rumination and similar
deleterious tendencies (e.g., forms of attentional suppression;
Campbell-Sills et al., 2006) are integral to the pathogenesis of
psychopathological symptoms (Wells and Matthews, 2014) or a
product of them, such propensities are nonetheless concurrent
with diminished mental health, and present a challenge to
treatment. One reason why maladaptive emotion regulation
strategies impede the cultivation of mental health might be
that they place particular demands on executive functions,
leaving fewer cognitive resources available for engaging in
adaptive strategies that also require executive functions, such
as reappraisal (see Joormann and Siemer, 2014, for review).
The clinical implication is that deficits in executive functions
might limit the effectiveness of mental health interventions such
as psychotherapy (Roiser and Sahakian, 2013). This is because
the neurocognitive mechanisms potentially mediating the effects
of non-pharmacological interventions (e.g., recogitation; Crum,
2021a,b), which also likely drive explicit, conscious cognitive
strategies to downregulate negative emotion (see Braunstein
et al., 2017, for review), are predominately executive in nature.
This raises the interesting question of whether improving
performance of the executive operations localized within the
prefrontal cortex (PFC; see Knight and Stuss, 2013; Shallice
and Cooper, for reviews) might augment the effects of these
mechanisms on mental health.
Meta-analyses of studies aiming to improve cognition in
this way (e.g., attention bias modification) generally support
their effectiveness in reducing symptoms common to anxiety
and mood disorders (e.g., Hakamata et al., 2010; Beard et al.,
2012; Cristea et al., 2015; Liu et al., 2017; see Siegle et al.,
2007; Keshavan et al., 2014, for reviews). Such paradigms
target executive functions directly and, therefore, adopt a “top-
down” approach to improving mental health. There is also
some evidence for the effectiveness of transcranial direct current
stimulation in reducing depressive symptoms (e.g., Katz et al.,
2017; Ruf et al., 2017), which represents a more “bottom-
up” approach. However, the findings of cognitive training
paradigms are often mixed in the sense that there are marked
individual differences within samples; training works differently
for different people. Accounting for these differences likely
requires training programs to be customized to the individual
rather than to a particular group. Moreover, such interventions
have not yet reached the point at which they are practical for
people to do in their everyday lives. Thus, there is a growing
interest in whether cognitive functions can be improved through
top-down training approaches, and although the evidence
crossing into the clinical domain is promising, it is still marginal
and further research is necessary. Such approaches should only be
considered as a complement rather than a replacement to mental
health interventions that have long been established as efficacious
(e.g., McArdle et al., 2012).
It is plausible that some bottom-up approaches to improving
cognition might be more practical and able to circumvent the
challenges of targeting specific cognitive functions in the brain.
For example, one potential approach is medication; however,
evidence for the effectiveness of medication in improving
cognition in clinical populations is not strong (Halahakoon and
Roiser, 2016; Shilyansky et al., 2016). Another possibility is one
of the most predominant means by which to improve wellbeing
in everyday life: physical activity. Physical activity combined
with cognitive training appears to benefit brain function (e.g.,
Zhu et al., 2016). These improvements to “cold” cognition
might benefit psychological wellbeing in turn. Indeed, habitual
exercise which places cardiorespiratory demands on the body
(e.g., running, long walks, strength training, yoga, etc.) has been
associated with mental health improvements (Teychenne et al.,
2008; Harvey et al., 2010; Song et al., 2012; Mammen and
Faulkner, 2013; Hallgren et al., 2016), and it appears that both low
and high levels of cardiorespiratory intensity work to engender
mood changes (Helgadóttir et al., 2016). Unsurprisingly, then,
exercise has been explored as an alternative treatment for
mild to moderate depression (Parker and Crawford, 2007), as
well as other disorders (see Stathopoulou et al., 2006). More
appropriately, using exercise in combination with cognitive–
behavioral therapy (CBT) has shown improvements in outcome
measures relative to CBT with no exercise program (e.g.,
McArdle et al., 2012).
However, this raises some theoretical issues. Because cognitive
training techniques such as attention bias modification target the
“attentional deployment” step of the emotion regulation model
(Gross, 1998, 2014), which essentially cultivates the marginally
effective strategy of distraction rather than that of “cognitive
change”, dysfunctional appraisal processes are not targeted as
they are in CBT. This is why such cognitive training paradigms
might not act as a substitute for this form of psychotherapy:
They might target important aspects of attention and memory,
but they do not explicitly train the systems uniquely engaged
during CBT. And, even if techniques were developed to train the
systems underpinning cognitive restructuring and which act on
maladaptive schemas and appraisals, they should probably still
be used in combination with psychotherapy, since they would
lack other important factors that contribute to mental health (e.g.,
interpersonal interactions that build the therapeutic alliance).
Whatever the optimal approach to cultivating mental health,
the particular means by which exercise accomplishes its role
is unclear. That physical activity facilitates the release of
endorphins and dopamine (e.g., “runner’s high”) is well-
recognized, but also is the transient nature of these effects
(see Dishman and O’Connor, 2009). Although these low-level
neurobiological effects might be useful in boosting mood
Frontiers in Neuroergonomics | www.frontiersin.org 2May 2022 | Volume 3 | Article 806485
Crum et al. Depression & Exercise in PFC
and decreasing anxiety, they might have little impact on
sustained changes in mental health. Instead, any sustained
effects might be due to changes in executive functions. In other
words, positive affect from low-, state-level effects relating to
exercise or otherwise is potentially not what drives current
or future applications of cognitive strategies to downregulate
negative emotion: Executive functions largely underpin this
downregulation (see Gross, 2014). Therefore, profound changes
in long-term mental health might be more closely related to
the acute (functional) and chronic (structural) effects of exercise
on the brain systems supporting executive functions. Much
neuroimaging and neuropsychological research has localized
executive functions in the frontal lobe, particularly the PFC (see
Shallice and Cooper, 2011; Knight and Stuss, 2013 for reviews).
For example, one executive function that might be critical to
emotion regulation is the ability to regulate attention between
stimulus-independent and –dependent information, a system
which has been consistently localized within rostral PFC (BA10;
see Burgess et al., 2007). Another important feature of executive
functions that might be important is the general processing speed
with these cognitive operations can be carried out.
However, what remains to be seen is whether
psychopathological symptoms such as depressed mood relate to
the acute effects of exercise on PFC functional activation during
executive function tasks. The present work therefore aimed
to investigate this question, as well as whether one’s level of
physical fitness, as measured by VO2peak, impacts the reactivity
of the PFC to exercise. Because of the link between depressive
symptoms and deficits in executive functions, and because
exercise positively affects executive functions, there might also
be a link between depressed people’s neural reaction to exercise
in the PFC. Thus, it was hypothesized that people with greater
depressive symptoms might show weaker effects of exercise on
the PFC, but that greater levels of cardiorespiratory fitness would
show a stronger upregulation of the PFC as a function of exercise.
METHOD
Participants
Law enforcement officers were voluntarily recruited from UK-
based forces and randomly allocated to an exercise group (n
=106; 73% male; age: 39 ±9 years; weight 84.0 ±19.7 kg;
height 173.6 ±20.2 cm), and a control group (n=27; 97%
male; age: 43 ±6; weight 89.4 ±18.6 kg; height 177.7 ±9.4 cm).
This sample of officers was part of a larger study looking at
health and wellbeing in law enforcement and was not chosen
for any specific characteristics (e.g., depression scores; fitness,
age etc.) relating to this study. All participants provided written
informed consent prior to participating in the study (Ethics
number: 13985/004). All participants completed a physical
activity readiness questionnaire (PAR-Q; Pescatello et al., 2014)
to screen for eligibility to undergo maximal exercise testing and
provided written informed consent prior to participating in the
study. Participants were excluded from the study if they were
not law enforcement officers, if they presented any injury or
illness that prevented them from exercising to exhaustion, if
they had a neurological condition or if they responded “yes”
to any of the questions on the PAR-Q. Ethical approval was
granted by the University College London Research Ethics
Committee. An a priori power analysis of a medium effect size,
with alpha set at (α=0.05) (one-tailed) and beta 1–β(power)
=0.80, determined that n=27 is adequate for within-subjects
comparisons of exercise effects; however, a similar analysis
suggested that between-subjects comparisons would require at
least n=46 for comparison with the experimental group.
Procedure
Participants completed the Mood and Feelings Questionnaire
(MFQ; Angold et al., 1995), a widely used self-report measure
of depressive symptomology that has high internal reliability
(Cronbach’s alpha =0.85). The experimental group completed
neurocognitive testing before and after exercise, whilst the
control group completed neurocognitive testing before and
after resting (passively watching a television program), and
then underwent exercise testing to assess their cardiorespiratory
fitness. More specifically, participants completed a set of
cognitive tasks on a computer screen, which were created
in PsychToolbox, MATLAB (Mathworks, Natick, MA), to test
executive functions such as inhibition and attention and,
importantly, the general speed of processing across them (i.e.,
Speed). There were three blocks for inhibition that were
adaptations of typical go/no go tasks (Donders, 1969), varying
from low, moderate, to high inhibition. The low inhibition
condition was a simple reaction time task. The moderate
inhibition condition required participants to not respond to
specific images (e.g., kittens). The high inhibition condition
was the same as the moderate one, with the exception that a
loud auditory noise would randomly occur (e.g., a gunshot).
The last three blocks regarded mode of attending. These tasks
required participants to respond in particular ways depending on
whether they were attending to stimuli on the computer screen
(i.e., stimulus-oriented thought: SOT) or independent of it (i.e.,
stimulus-independent thought: SIT) See Burgess et al. (2007) for
review of these types of tasks. The first condition was SOT, the
second was SIT, and the third was SIT with visual distractors
(Figure 1).
The exercise group completed a VO2max test on a treadmill
(h/p/cosmos, Nussdorf, Germany) using the Bruce protocol. The
step protocol begins with a 3-min warm up, walking at 2.6 km/h
with no incline, every 3 min thereafter the speed and incline of
the treadmill increase, starting with a 10% incline at 2.7 km/h
followed by incremental increases in both incline and speed
every 3 min, pushing the participant to eventually running uphill,
if their fitness allows. Throughout the test, participants were
encouraged to continue exercising until volitional exhaustion,
at which point the test was terminated. The treadmill was
returned to level at walking pace, the participant was instructed
to walk slowly (2.6 km/h) for 3 min to recover fully. Breath-by-
breath gas analysis and heart rate were gathered through the
Vyntus CPX Metabolic Cart (Vyaire Medical, Chicago, USA)
throughout the test. The anaerobic threshold was determined
through the v-slope method (Wasserman et al., 1994). VO2max
(ml/kg/min) was determined as the highest recorded VO2value.
VO2max was identified as a true maximal value if the gas analysis
Frontiers in Neuroergonomics | www.frontiersin.org 3May 2022 | Volume 3 | Article 806485
Crum et al. Depression & Exercise in PFC
FIGURE 1 | (A) Channel-specific locations of the 22-channel (eight sources & eight detectors) configuration overlaid onto a model brain mesh of the PFC. (B)
Neurocognitive testing before and after exercise. (C) A 15-min bleep test of aerobic fitness to measure VO2max.(D) Example of trials of the SOT (upper row) and SIT
(lower row) tasks.
showed a plateau in the VO2values, respiratory exchange ratio
(RER) exceeded 1.13, and heart rate max reached ∼220-age. The
exercise group included in the neuroimaging analysis reached
true max (e.g., not quitting too early). After a recovery walk
(3 min), they returned to the testing room, resulting in a ∼10 min
time delay between reaching maximal exertion and starting the
second round of cognitive tests. To maximize data collection,
the no-exercise group completed these protocols after the second
round of cognitive tests.
Physiological Measures
Participants were fitted with a continuous-wave functional near-
infrared spectroscopy (fNIRS) system (LIGHTNIRS, Shimadzu
Corp., Kyoto, Japan) to measure changes in hemodynamics,
as well as with a physiological monitor to record heart
and respiration rates (HR & RR, respectively). fNIRS signal
acquisition used 16-fibers (22-channel configuration: 8 sources &
8 detectors), with a sampling rate of 13.33 Hz at three wavelengths
of light (780, 805, and 830 nm). Digitization was based on a single
subject due to the large sample size (n=106) and need for rapid
testing; the researchers were carefully trained to place the cap the
same way for each participant. Anatomical locations of optodes
in relation to standard head landmarks, including inion and
top center (Cz) and left and right tragi, were determined using
a Patriot 3D Digitizer (Polhemus, Colchester, VT). Montreal
Neurological Institute (MNI) coordinates (Mazziotta et al., 2001)
for each channel were obtained using NIRS-SPM software
(Ye et al., 2009; https://www.nitrc.org/projects/nirs_spm/) with
MATLAB (Mathworks, Natick, MA). The anatomical coverage of
the channel configuration was over three bilateral ROIs (Table 1):
rostral PFC (BA10), dorsolateral PFC (BA46/9), and ventrolateral
PFC (BA44/ 45/47). These ROIs were specified a priori based
on neuroimaging and neuropsychological research on frontal
lobe functions (see Shallice and Cooper, 2011; Knight and Stuss,
2013, for reviews). ECG signals were continuously collected at
256 Hz using two Equivital “eq02+LifeMonitors” (https://www.
equivital.com/heart-rate-and-breathing-rate-monitor).
Data analysis of the fNIRS data was completed in line with
the quality control standards suggested by Yücel et al. (2021).
Errors during data collection resulted in smaller sample sizes
for the exercise (n=92) and control (n=18) groups. For
example, participants were excluded if they did not have enough
behavioral data to match the fNIRS data (i.e., for convolution
of a stimulus design with a hemodynamic response function),
Frontiers in Neuroergonomics | www.frontiersin.org 4May 2022 | Volume 3 | Article 806485
Crum et al. Depression & Exercise in PFC
TABLE 1 | Channels, coordinates, and anatomical regions.
Channel # Anatomical region BAaCoordinatesb
1 Right Superior Frontal Gyrus 9 53, 26, 30
2 Right Middle Frontal Gyrus 46 41, 49, 23
3 Right Rostral PFC 10 25, 62, 21
4 Right Rostral PFC 10 4, 65, 21
5 Left Rostral PFC 10 -19, 63, 21
6 Left Middle Frontal Gyrus 46 -37, 52, 22
7 Left Superior Frontal Gyrus 9 -51, 28, 29
8 Right Inferior Frontal Gyrus 44 60, 15, 16
9 Right Inferior Frontal Gyrus 45 51, 43, 7
10 Right Rostral PFC 10 36, 60, 5
11 Right Rostral PFC 10 17, 68, 5
12 Left Rostral PFC 10 -8, 68, 5
13 Left Rostral PFC 10 -32, 62, 4
14 Left Inferior Frontal Gyrus 45 -47, 46, 7
15 Left Inferior Frontal Gyrus 44 -58, 17, 17
16 Right Inferior Frontal Gyrus 47 54, 30, -6
17 Right Rostral PFC 10 45, 51, -8
18 Right Rostral PFC 10 28, 64, -7
19 Right Rostral PFC 10 3, 67, -7
20 Left Rostral PFC 10 -22, 66, -8
21 Left Rostral PFC 10 -41, 54, -7
22 Inferior Frontal Gyrus 47 -51, 36, -3
aBA, Brodmann’s Area.
bCoordinates are based on the MNI system and (–) indicates left hemisphere.
or if their fNIRS data were too noisy or compromised in some
way. The pre-processing of raw fNIRS signals was carried out on
these data in accordance with Pinti et al. (2019). Namely, the raw
voltage intensities were converted from.OMM format into.NIRS
format. These data were then converted into optical density (OD)
signals. Next, motion-artifact correction was completed using
wavelet convolution (iqr =1.5), with a differential pathlength
factor (DPF) that is typically used for continuous-wave fNIRS
[6, 6, 6]. These signals were temporally smoothed using a band-
pass filter (FIR: order 1,000) [.01 .4 Hz]) to remove extracerebral,
systemic effects. The cleaned OD signals were then converted into
changes in concentrations of oxygenated hemoglobin (HbO2),
deoxygenated hemoglobin (HbR), and total hemoglobin (HbO2
+HbR) using the modified Beer-Lampert Law (see Dirnagl and
Villringer, 1997). Channels that were faulty or remained poor in
signal-to-noise ratio were removed from the analysis.
HR (n=56) and RR (n=52) were included as additional
parameters in the single-subject design matrices (see Tachtsidis
and Scholkmann, 2016) to address variance due to physiological
confounds in the predicted signals. Specifically, waveform
analysis calculated RR from the ECG data (Charlton et al.,
2016). HR was computed using the intervals between R-wave
peaks of QRS complexes. Most of the physiological data were
accounted for in the fNIRS sample (HR: 61%, RR: 57%), but
not all. A comparison of the results with and without these
physiological variables showed that accounting for the majority
of physiological variance in the fNIRS sample was sufficient.
FIGURE 2 | HbR changes in the PFC as an acute effect of exercise (n=92)
collapsed across all executive function conditions. Greatest activation changes
are represented in bright yellow and white, with little to no effects represented
in dark red and black, respectively (t-values of the images are scaled from 0 to
5+).
Next, onsets and durations of the epochs of each trial of each
block were extracted to generate a stimulus design for each
participant, with which a canonical hemodynamic response
function (HRF) was then convolved. The HR and RR parameters
as well as the predicted HRFs (HbO2and HbR) for each block
were then down-sampled to 1 Hz using spline interpolation
(Cohen, 2017) and a general-linear model analysis fitted these
models to the observed data. The second-level analysis of
the group data used a random-effects approach via summary
statistics (Friston et al., 2007; Poldrack et al., 2011). The group
effects of each HbO2and HbR contrast for each channel were
then projected onto a 3-D brain mesh via linear interpolation
after false-discovery rate (FDR) correction (q<0.05; Singh and
Dan, 2006) was carried out. Finally, although both HbO2and
HbR signals were analyzed, the interpretation of the results was
based on research suggesting that HbR signals are less affected
by systemic confounds (Dravida et al., 2017), especially in fNIRS
paradigms involving marked changes in arterial CO2due to
changes in respiration (e.g., exercise, speaking, etc.), because such
changes alter the HbO2signal to a greater degree than HbR in
these cases (Scholkmann et al., 2013a,b).
RESULTS
Changes in PFC activation from contrasting the pre- and post-
exercise (post >pre) tasks of the experimental group (n=
92) showed bilateral activation changes in dorsolateral (BA46/9),
ventrolateral (BA44/45), and rostral (BA10) PFC (Figure 2), with
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Crum et al. Depression & Exercise in PFC
FIGURE 3 | Higher depression scores on the MFQ (y-axis) predicted smaller changes in levels of activation in right IFG (BA44/45/47) as an effect of exercise (r=0.36,
p<0.001, 95% CI [−0.07, −0.02]; 13% variance explained). The red line depicts the regression line, with black lines as confidence intervals.
the greatest changes occurring in right BA10 and BA46 (p’s<
0.05, FDR corrected).
To investigate whether the effects observed in these
PFC subregions varied depending on level of depression
symptomology (MFQ scores; M=4.04, SD =4.25), a multiple
linear regression analysis resulted in three channels (8, 9, & 16)
that explained the most variance in depression scores, R2=
0.14, F(2,89) =4.59, p=0.005. Together, these channels form a
spatial cluster approximately over right inferior frontal gyrus
(IFG: BA44/45/47, respectively), so the values for these channels
were transformed into Z-scores and summed to create an “IFG”
variable. Although the IFG data were normally distributed, a
Shapiro-Wilk test showed that the depression scores were not
normally distributed, W=.80, p<0.001 (Skewness =2.01,
Kurtosis =5.37). Therefore, the IFG effects were regressed onto
a normalized distribution of depression scores (Skewness =
0.21, Kurtosis = −0.64), yielding a more statistically robust
model, R2=0.13, F(1,89) =12.91, p<0.001, of right IFG as
a predictor variable, t(89) = −3.59, p<0.001, 95% CI [−0.07,
−0.02] (Figure 3).
Thus, there was a negative relationship between depression
scores and the PFC activity that was due to exercise-elicited,
processing-speed changes, particularly in right inferior frontal
gyrus (BA44/45/47). That is, people with greater symptoms of
depression showed lower levels of PFC activation across all tasks
after exercise.
Following the same procedures for VO2peak scores (M=
37.25, SD =8.24) to investigate whether physical fitness predicted
the PFC effects of exercise, since these data were also not
normally distributed, W=0.94, p<0.001 (Skewness = −1.14,
Kurtosis =3.97), a one channel model, R2=0.09, F(1,89) =
8.81, p=0.004, 95% CI [0.79, 3.97], containing channel 10
(right rostral PFC; BA10) emerged as a significant predictor
of a normalized distribution of VO2peak scores (Figure 4). So,
there was a positive relationship between VO2peak and exercise-
elicited changes in PFC activity in right rostral PFC (BA10), in
that people with greater aerobic fitness showed greater levels
of activation in this region after exercise. However, there was
no association between VO2peak and depressive scores, r(90) =
−0.05, p>0.05.
DISCUSSION
Our results show some relationships between symptoms of
depression and exercise-elicited changes in PFC activity, as
well as between this activity and level of fitness. Specifically,
there was a negative relationship between symptom severity
and activity in right inferior frontal gyrus (BA44/45/47), in that
greater activation changes in these subregions were associated
with lower depression scores. Right inferior frontal gyrus (i.e.,
ventrolateral PFC) has been consistently implicated in the
controlled downregulation of negative emotion (Zilverstand
et al., 2017) and is an area that is relatively hypoactive during
emotion regulation in depressed populations (Rive et al., 2013).
So, the evidenced negative relationship is consistent with the
idea that this area of the PFC is underactive during executive
function tasks in people with depressive symptoms (see Wang
et al., 2008). Although this relationship was not found in rostral
PFC, it does not mean that there is no link between this subregion
and mood in relation to exercise. A stronger relationship might
be evidenced should alternative self-report measures be used
that index not only mood and negative affect but also the
dysfunctional cognitions that underpin them (e.g., the shorter
Attitudes and Belief Scale 2; DiGiuseppe et al., 2021), as well
Frontiers in Neuroergonomics | www.frontiersin.org 6May 2022 | Volume 3 | Article 806485
Crum et al. Depression & Exercise in PFC
FIGURE 4 | Higher levels of aerobic fitness (y-axis) predicted greater changes in the level of activation in right rostral PFC (BA10) as an effect of exercise (r=0.30, p
=0.004, 95% CI [0.79, 3.97]; 9% variance explained). The red line depicts the regression line, with black lines as confidence intervals.
as people’s tendency to downregulate negative affect and mood
from a ’top-down’ approach (i.e., reappraisal), such as with the
Emotion Regulation Questionnaire (Gross and John, 2003). Such
measure might mediate the relationship between PFC reactivity
and depressive symptoms.
In addition, there was a positive relationship between aerobic
fitness (VO2peak) and a different area of right PFC (BA10),
in that greater fitness was predicted greater activation changes
in right rostral PFC. While decreased activation of the PFC
appears to be the rule in depression (see Hariri, 2015),
there are some exceptions: For example, one study recently
showed that pessimistic future-thinking in people with major
depressive disorder exhibited greater activity in right rostral
PFC compared to healthy individuals (Katayama et al., 2019).
Given the cognitive operations for which this brain region is
largely functionally specialized (i.e., regulating thought that is
dependent or independent of the external world; Burgess et al.,
2007), it makes sense that dysfunctional, prospective appraisals
would be supported by the biasing of stimulus-independent
thought—that, here, there would be hyperactivity in depressed
individuals. Equally supported by this orientation of attention
are the hypothesized cognitive operations of “recogitation”
(Crum, 2021b)—executive functions in which depressed people
appear to have deficits—and, therefore, hypo-activity in BA10
might be present during their implementation. Thus, rostral
PFC is potentially as much involved in the pathogenesis of
psychopathological symptoms as it is in facilitating the cognitive
change mechanisms that ameliorate them. So, it is plausible
that the relative hypo- or hyper-activation of this brain region
might depend on the particular type of executive function task
in which depressed individuals engage. For example, collapsing
across different executive function tasks might result in BA10
activation that explains little variability in depression, as was the
case in the present study, but that the exercise effect in this PFC
subregion was sensitive to how aerobically fit people were might
suggest an important role of fitness in treating depression. That
is, it is plausible that physical fitness works to correct issues of
abnormal activity in rostral PFC (e.g., Saanijoki et al., 2022).
Future investigations might further elucidate this possibility, but
the present findings represent a starting point for highlighting the
potential interrelations between the PFC, physical activity, and
depressive symptoms, as well as between physical activity, rostral
PFC, and aerobic fitness.
A limitation of the present work was that long-term changes in
cognition, behavior, brain, fitness, and mood were not measured.
This constrains the type of inferences that can be made about
their interrelations, so future research investigating the chronic
effects of exercise on the brain, particularly the PFC, might
examine how functional changes in ventrolateral and rostral
PFC related to executive function tasks vary with changes in
psychopathological symptoms. Another possibility for future
research is to examine how much and what kind of physical
activity are sufficient to facilitate marked mental health changes.
For example, are a few acute bouts of exercise enough to cultivate
these changes or do overall fitness levels need to be increased,
which is achieved through more repeated, habitual activity?
Another limitation was that post-test measures in mood were not
taken, so it was not possible to assess the acute effects of exercise
on mood. However, this is not a significant limitation given the
current theoretical presuppositions about how exercise improves
mood over time. Namely, although physical activity tends to
indeed improve positive affect due to low-level neurobiological
Frontiers in Neuroergonomics | www.frontiersin.org 7May 2022 | Volume 3 | Article 806485
Crum et al. Depression & Exercise in PFC
changes (e.g., runners’ high), such effects are typically transient
(Dishman and O’Connor, 2009) and do not constitute mood.
Therefore, it is perhaps to the potential effects of exercise on top-
down cognitive strategies within the PFC to which researchers
ought to look for explaining lasting improvements to mood and
the ability to downregulate negative emotion.
Such mediating effects of the PFC might explain the lack of
a negative relationship between physical fitness and depressive
symptoms and, more broadly, why there are many people who
are depressed despite being physically fit. Indeed, the relationship
between increases in aerobic fitness and decreases in depressive
symptoms is relatively weak (Martinsen et al., 1989). So, it
is perhaps not enough to be fit: The benefits of exercising
on cerebral oxygenation in the brain ought also to be taken
advantage of in order to augment the facilitation of regulation
strategies (i.e., the mind needs to also play an active role
in cultivating mental health). Interestingly, improvements to
executive functions during and after exercise are optimized to
the extent that these functions are a part of the task demands
of a physical activity (e.g., hunting was a cognitively demanding
exercise task for early humans; see Raichlen and Alexander,
2017). Therefore, it could be the case that the influence of exercise
on decreasing psychopathological symptoms is optimized to
the extent that an exercise also requires of the individual the
executive functions that are integral to the cognitive change
strategies that drive future efforts to downregulate the onset of
negative affect. This raises the interesting question of whether
the physical activities of extremely fit, yet depressed individuals
are not sufficiently enriched, cognitively. At this stage, however,
these must remain speculations, but the results presented here
are consistent with the possibility that there may be a unifying
neural mechanism that links the effects of physical activity
upon the brain, consequent changes in cognitive processing, and
depression-like symptoms. The potential clinical implications for
the role of physical activity and fitness in treatment seem clear,
so it would be highly valuable to investigate these results in a
clinical population.
DATA AVAILABILITY STATEMENT
The raw data supporting the conclusions of this article will be
made available by the authors, without undue reservation.
ETHICS STATEMENT
The studies involving human participants were reviewed
and approved by University College London Research Ethics
Committee. The patients/participants provided their written
informed consent to participate in this study.
AUTHOR CONTRIBUTIONS
JC, FR, and PB designed the experiment. JC, GH, SF,
and EC collected the data. JC analyzed the data and
wrote the manuscript. FR, GH, SF, EC, UH, IJ, MH, JH,
AH, IT, and PB reviewed and suggested revisions to it.
All authors contributed to the article and approved the
submitted version.
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Conflict of Interest: The authors declare that the research was conducted in the
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