ORIGINAL RESEARCH
published: 18 October 2021
doi: 10.3389/fpsyt.2021.739356
Twelve-Week Yoga vs. Aerobic
Cycling Initiation in Sedentary
Healthy Subjects: A Behavioral and
Multiparametric Interventional
PET/MR Study
June van Aalst 1 , Lise Jennen 1 , Koen Demyttenaere 2,3 , Stefan Sunaert 4,5 , Michel Koole 1 ,
Jenny Ceccarini 1 and Koen Van Laere 1,6*
1
Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium, 2 Research
Group Psychiatry, Neurosciences, University Psychiatric Center KU Leuven, Leuven, Belgium, 3 Adult Psychiatry, University
Hospitals Leuven, Leuven, Belgium, 4 Translational MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium,
5
Radiology, University Hospitals Leuven, Leuven, Belgium, 6 Division of Nuclear Medicine, University Hospitals Leuven,
Leuven, Belgium
Edited by:
Anne M. Landau,
Aarhus University, Denmark
Reviewed by:
Caroline Cristiano Real,
Aarhus University, Denmark
Kiyotaka Nemoto,
University of Tsukuba, Japan
David Matuskey,
Yale University, United States
*Correspondence:
Koen Van Laere
koen.vanlaere@uzleuven.be
Specialty section:
This article was submitted to
Neuroimaging and Stimulation,
a section of the journal
Frontiers in Psychiatry
Received: 10 July 2021
Accepted: 16 September 2021
Published: 18 October 2021
Citation:
van Aalst J, Jennen L,
Demyttenaere K, Sunaert S, Koole M,
Ceccarini J and Van Laere K (2021)
Twelve-Week Yoga vs. Aerobic Cycling
Initiation in Sedentary Healthy
Subjects: A Behavioral and
Multiparametric Interventional PET/MR
Study. Front. Psychiatry 12:739356.
doi: 10.3389/fpsyt.2021.739356
Frontiers in Psychiatry | www.frontiersin.org
Interventional yoga studies with an active control group remain scarce and are
important to clarify the underlying neurobiology. We conducted an interventional study in
healthy controls using simultaneous positron emission tomography/magnetic resonance
(PET/MR) imaging and psychometric scales. Thirty healthy, female volunteers (28.4 ±
8.4 years) participated and were randomly assigned to a 12-week yoga or indoor
cycling intervention. Before and after the intervention, [18 F]FDG and [11 C]UCB-J PET was
performed on a simultaneous GE Signa PET/MR with volumetric imaging. Psychometric
scales were evaluated on affect, mindfulness, stress, worrying, self-compassion, and
interoceptive awareness. Yoga subjects scored higher on interoceptive awareness
compared to baseline (p < 0.001). Cognitive (P = 0.009) and overall cognitive functioning
(P = 0.01) improved after the yoga intervention compared to the cycling group. We
did not observe significant differences in glucose metabolism, synaptic density, or gray
matter (GM) volume. The indoor cycling group did not show changes in psychometric
variables, but significant increases in relative glucose metabolism were observed in
the parahippocampal/fusiform gyrus and cerebellum (P < 0.001). In conclusion, 12
weeks of yoga practice has significant effects on interoceptive awareness and perceived
cognitive function in starters. Longer interventions and/or higher frequency of yoga
practice may be needed to detect cerebral metabolic and/or morphologic effects on
the macroscopic level.
Keywords: yoga, longitudinal interventional study, PET/MR imaging, FDG, synaptic density, indoor cycling
INTRODUCTION
Yoga combines meditation (dhyana), physical postures (asana), and focused breathing
(pranayama). It has become increasingly popular in the Western world as an approach to improve
health and well-being (1) and has received more and more interest from a research perspective.
Behavioral studies have shown that yoga can be an effective multi-component health intervention
1
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van Aalst et al.
PET/MR Study in Yoga Subjects
neuropsychological endpoints as well as longitudinal positron
emission tomography/magnetic resonance (PET/MR) imaging
of glucose metabolism, synaptic density and structural imaging.
This was performed in yoga-naïve sedentary individuals to
exclude effects of previous training.
to reduce stress, increase physical fitness, and improve general
well-being and quality of life (2, 3). Psychological dimensions
improved by yoga include self and body awareness, coping
capacity, stress, mindfulness, and self-compassion (2, 3). Besides
behavioral studies, a limited number of imaging studies have
investigated the effects of yoga on objective biomarkers in
the brain. Different advanced neuroimaging techniques such as
positron emission tomography (PET) and magnetic resonance
(MR) imaging allow to investigate the biochemical, functional,
and structural effects of yoga in a non-invasive way (4). However,
since most studies so far have focused specifically on the
meditational dimension of yoga, evidence for the combined
tripartite effects is scarce. Based on imaging and physiological
data, a leading hypothesis of an underlying neurobiological
mechanism of yoga is that breathing exercises, meditation, and
baroreflex-promoting poses induce a shift in the parasympathetic
nervous system through activation of gamma aminobutyric acid
(GABA) release through the vagal nerve (5, 6).
In cross-sectional studies, structural effects on gray matter
(GM) volume have been described by MR imaging, with
increased GM volume in the insular cortex and hippocampus
as most consistently reported findings in (experienced) yoga
practitioners (7, 8). It has been postulated that changes in
GM volume might be the result of neuroplasticity (9). Few
functional or molecular PET studies have been conducted
in yoga practitioners. [18 F]Fluorodeoxyglucose (FDG)
PET imaging enables measurement of regional neuronal
activity. In a recent [18 F]FDG PET study in experienced yoga
practitioners, we found a significant decrease in the limbic
system compared to physically active but yoga-naive subjects
(10). Such downregulation in metabolic activity could be
due to GABA-mediated inhibition, development of more
efficient brain metabolism, or a pre-existing phenotype in yoga
practitioners. Therefore, a longitudinal study is warranted to
clarify possible underlying mechanisms. Glucose metabolism
is majorly determined by glutamate neurotransmission and
neuron-astrocyte interactions (11). Furthermore, recently
imaging of synaptic density has become available by means of
PET radiotracers such as [11 C]UCB-J. This ligand binds to the
presynaptic vesicle protein 2A (SV2A) with high affinity and
specificity, and is altered in several neuropsychiatric conditions
(12–16). For the first time, this opens the possibility to investigate
whether an intervention can induce neuroplasticity by axon
sprouting and neurogenesis (9). Combined measurement of
synaptic activity and synaptic density could therefore offer
complimentary measures of brain function (17).
As the choice of an appropriate control group is critical
to disentangle the impact of yoga practice on brain function
without confounding factors (4, 18), we have chosen to use
moderate-intensity indoor cycling as control intervention. Both
interventions are practiced in group, can be guided by a
skilled teacher, are of similar duration per exercise unit and
can be metabolically matched. Also aerobic exercise induces
beneficial psychological effects, such as increased self-esteem,
self-satisfaction, confidence, and improved turmoil (19).
The aim of this study was to compare a 12-week yoga
intervention vs. aerobic moderate intensity exercise with
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MATERIALS AND METHODS
Subjects
In total, 30 right-handed healthy sedentary female volunteers
[n = 30; age: 28.4 ± 8.4 (SD) years] participated in the
study. Subjects were in good health according to their medical
history, physical examination, general laboratory test (blood
and urine) screening, and general neuropsychological evaluation
[Symptoms Checklist (SCL90), Beck’s depression inventory
(BDI) (20), and mini-mental state examination (MMSE)]. The
main exclusion criteria consisted of a history of major internal
disease, previous severe head trauma, a psychiatric disorder, and
use of centrally acting drugs. All subjects were required to have
a sedentary lifestyle, defined as doing <1 h of exercise a week
the year prior to study participation. The study was approved by
the local University Ethics committee (study number S59792—
Belgian Registration Number B32220173162) and was conducted
in full accordance with the latest version of the Declaration
of Helsinki. All participants provided written informed consent
before inclusion in the study.
Study Design
The study design is reported in Supplementary Figure 1. All
subjects underwent up to two PET/MR scans ([18 F]FDG in all
and [11 C]UCB-J for most participants) at baseline and after 12
weeks of intervention. After the baseline scan, subjects were
randomly assigned to either the yoga intervention group (n =
15) or an indoor cycling intervention group (n = 15) (physical
blinded number picking by the subjects). The yoga group was
planned to attend yoga classes for 12 weeks, twice a week with
60-min sessions. In addition, their regular exercise regimen (<1
h/per week) was allowed. All yoga sessions took place in the
same studio in Leuven (Flowing Yoga, Mrs. K. Marent). Different
yoga styles for beginners were allowed to the participant’s choice,
including easy flow, prana vinyasa easy flow, ashtanga basics, and
Yin and Yang yoga. These yoga styles all included approximately
the same time ratio of physical postures (±70%), breathing
exercises (±25%, in between the different postures) and guided
meditation (±5%).
Participants assigned to the cycling group had to attend 60 min
of indoor cycling classes for 12 weeks, also twice a week (with
regular exercise routine (<1 h of exercise/per week) allowed).
At their first training, cycling group subjects had to perform
an individual power level test, to determine their individual
threshold power defined as 90% of their peak power. The cycling
subjects then received the instruction to keep the mean power
below 80% of their individually determined threshold during the
cycling classes, in order to stay within aerobic conditions and to
match the physical intensity level with the yoga intervention.
Both yoga and cycling sessions were registered by the yoga
studio and sport center, respectively. Moreover, participants had
2
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van Aalst et al.
PET/MR Study in Yoga Subjects
UZ Leuven, Belgium) was produced in-house according to an
approved manufacturing authorization, with a radiochemical
purity >95%. After the [18 F]FDG PET acquisition, a single
venous blood sample was collected to measure blood glucose
concentration and the remaining [18 F]FDG radioactivity to
calculate a simplified measure of absolute glucose consumption
(Hunter method) as validated previously against absolute arterial
spin labeling (10, 32).
Additionally, a subset of participants (n = 20; 10 in each
group) received an additional SV2A PET scan using [11 C]UCBJ. This subset was chosen randomly, and only based on the
logistics (availability) of the [11 C]UCB-J tracer production. The
precursor was obtained from UCB and labeled on site under
GMP standards with a radiochemical purity >95%, as described
previously (33). Subjects received a bolus injection of 270 ±
60 MBq (specific activity 239 ± 133 GBq/µmol) and of 262
± 61 MBq (specific activity 187 ± 73 GBq/µmol) at baseline
and post-intervention, respectively. This bolus was administered
at least 100 min prior to the [18 F]FDG injection (with 20 min
physical half-life the [11 C]UCB-J activity was mostly decayed
before [18 F]FDG PET). Sixty minutes post-injection, a 30-min
static [11 C]UCB-J scan was acquired to be quantified using a
reference tissue approach (33).
PET data were rebinned in six frames of 5 min, corrected
for dead time, randoms, scatter, and time-offset (34). An MRbased attenuation correction (MRAC), based on zero-echo time
(ZTE) MR images (3D radial acquisition; Flip Angle: 0.8◦ ;
Bandwidth: 62.5 kHz), was used for attenuation correction (35).
Positron emission tomography images were reconstructed using
OSEM (ordered subset expectation maximization; 28 subsets; 4
iterations) algorithm, including time of flight (TOF) information,
resolution modeling, and an in-plane Gaussian post-smoothing
with a FWHM (full width at half maximum) of 4.5 mm.
Simultaneous with the PET data acquisition, the following MR
sequences were acquired [using an eight-channel high-resolution
receiver head coil (GE Healthcare)]: 3D volumetric T1-weighted
BRAVO (plane: sagittal; TE: 3.2 ms; TR: 8.5 ms; TI: 450 ms; flip
angle: 12◦ ; receiver bandwidth: 31.25 kHz; voxel size: 1 × 1
× 1 mm) and fluid-attenuated inversion recovery (FLAIR) 3D
CUBE (TR: 8,500 ms, TE 130 ms, voxel size: 1 × 1 × 1.4 mm).
to keep a diary to track their lessons. For both groups a minimum
of 20 lessons was required to complete the study.
Psychometric Evaluation
All participants completed a battery of psychometric
questionnaires at baseline and post intervention. In line
with the previously observed psychological effects of yoga (3),
the following dimensions were sampled: affect (21), mindfulness
(22–24), stress (2, 22), worrying (22), self-compassion (23), and
interoceptive awareness (25). The specific scales sampled in this
study included:
– Multi-assessment interoceptive awareness (MAIA) scale. The
MAIA questionnaire measures interoceptive awareness,
defined as the awareness of signals from the inside of the
body and higher-order top down processes. In total eight
subdimensions are measured: noticing, not-distracting,
not-worrying, attention regulation, emotional awareness,
self-regulation, body listening, and trust (26).
– Leuven Affect and Pleasure Scale (LAPS) (27). This scale
offers a comprehensive assessment of negative and positive
affect, hedonic tone, and independent variables on cognitive
and overall functioning, evaluation of a meaningful live,
and happiness.
– Five-Facet Mindfulness Questionnaire (FFMQ) (28).
Mindfulness is defined as “paying attention in a particular way:
on purpose, in the present moment, and non-judgmentally.”
This questionnaire includes five factors that represent
elements of mindfulness, including observing, describing,
acting with awareness, non-judging of inner experience, and
non-reactivity to inner experience.
– Perceived Stress Scale (PSS) (29). This psychological
instrument is used to measure perception of stress.
– Penn State Worry Questionnaire (PSWQ) (30) to measure the
trait of worry.
– Self-Compassion Scale (SCS) (31). Self-compassion is described
as “being open to and moved by one’s own suffering,
experiencing feelings of caring and kindness toward oneself,
taking an understanding, non-judgmental attitude toward
one’s inadequacies and failures, and recognizing that one’s
own experience is part of the common human experience.”
This scale is a psychometrical measure of self-compassion and
includes six subscales: self-kindness, self-judgment, common
humanity, isolation, mindfulness, and over-identification.
Image Data Analysis
Both [18 F]FDG and [11 C]UCB-J PET data were analyzed on a
voxelwise basis, using SPM12 (Statistical Parametric Mapping,
Wellcome Department of Imaging Neuroscience, London, UK),
and using a predefined volume-of-interest (VOI) approach
(PMOD software v3.9, PMOD Inc., Zurich, Switzerland).
Reconstructed PET data were corrected for motion.
Parametric standardized uptake value ratio (SUVR) images
for [11 C]UCB-J were generated, using the centrum semiovale
(CS) as validated reference region in healthy volunteers
(33, 36). For [18 F]FDG PET regional cerebral metabolic rate
of glucose (rCMRGlc) (mmol/l/min) maps, first blood glucose
concentration was measured at the end of the scan and a
venous blood sample was centrifuged for 5 min (4,000 rpm,
4◦ C) to measure the remaining tracer concentration in plasma
(gamma counter; Perkin Elmer, 1480 WIZARD). A lumped
Image Acquisition
All PET and MR data were acquired on a simultaneous Signa
time-of-flight (TOF) PET/MR scanner with fast Silicon
photomultiplier detectors inside a 3T MR magnet (GE
Healthcare, Chicago, IL, USA). Subjects fasted at least 3 h
prior to [18 F]FDG injection. Subjects received an intravenous
bolus injection of [18 F]FDG (at baseline: 118 ± 12 MBq and
post-intervention: 119 ± 9 MBq) in supine position with a 20min accumulation period in a quiet and dimly lit environment.
During the accumulation period, subjects were asked to close
their eyes but remain awake. Subsequently, a static 30-min
[18 F]FDG PET/MR scan was acquired. [18 F]FDG (GlucogastTM ,
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van Aalst et al.
PET/MR Study in Yoga Subjects
constant of 0.65 was applied for all regions to calculate rCMRGlc
values (32, 37). For two subjects (both in the yoga group at
post-intervention), these maps could not be generated due to
technical errors in plasma analysis and blood sample withdrawal,
respectively. These two subjects were therefore excluded from
the rCMRGLc data analysis.
All post-intervention [18 F]FDG and [11 C]UCB-J parametric
PET maps were first co-registered to their respective baseline
images. Subsequently, all PET images were co-registered to the
subject’s own T1-weighted MR image and spatially normalized to
the Montreal Neurological Institute (MNI) space using a nonlinear normalization with a DARTEL algorithm (SPM12). To
reduce noise at the voxel level and account for gyral variations,
PET images were additionally smoothed using a Gaussian
FWHM of 8 mm. To exclude extracerebral activity, a relative
threshold of 80% of the mean and an implicit CSF and GM mask
was used.
Voxel-based findings were corroborated with a predefined
VOI analysis using the N30R83 Hammers probabilistic atlas and
AAL-merged in PMOD (38, 39), as the AAL-atlas allows for a
more detailed delineation of the entire brainstem (VOIs for the
medulla, pons, and midbrain). To reduce dimensionality and
avoid type II errors, the standard 83 VOIs were merged into
12 larger, bilateral VOIs: FCx, frontal cortex; ACCx, anterior
cingulate cortex; PCCx, posterior cingulate cortex; LTL, lateral
temporal lobe; MTL, medial temporal lobe; PCx, parietal cortex;
OCx, occipital cortex; Str, striatum; Thal, thalamus; ICx, insular
cortex; Cbl, cerebellum; Bs, brainstem.
For the voxel-based morphometry (VBM) analysis, the
Computational Anatomy Toolbox (CAT12) (40) implemented
in SPM12 was used. All individual T1-weighted MR images
were segmented into GM, white matter (WM), and cerebrospinal
fluid (CSF), spatially normalized using the DARTEL algorithm
and modulated with the Jacobian warp parameters. After preprocessing, GM images were smoothed with a Gaussian kernel of
8 mm. An absolute threshold masking of 0.1 to avoid edge effects
around borders between GM, WM, and CSF was used.
TABLE 1 | Subject demographics and study-related variables.
Age
Sex (F/M)
Cycling group
(n = 15)
(n = 15)
31.8 ± 9.8
24.9 ± 5.1
15/0
15/0
P-value
0.02
Activity level (hrs/wk)
0.5 ± 0.4
0.6 ± 0.5
0.98
Pre-PET scan sober
glycaemia (mg/dl)
86.5 ± 6.1
85.5 ± 6.1
0.68
BMI (kg/m2 )
23.4 ± 2.3
22.5 ± 2.4
Educational level
0.30
0.66
High school
2 (13.3%)
Bachelor degree
8 (53.3%)
7 (46.7%)
Master degree
5 (13.3%)
4 (26.7%)
BDI
4 (26.7%)
3 (0–8)
1 (0–8)
0.32
MMSE
30 (29,30)
29 (29,30)
0.07
Nr of attended classes (out
of max 24)
21.1 ± 1.2
21.4 ± 1.4
0.49
BDI, beck depression inventory; BMI, body mass index; F, female; M, male; MMSE,
mini-mental state examination. Data are presented as mean ± standard deviation for
continuous variables, median (min-max) for integer variables and frequency (%).
data were analyzed at a voxel-level Pheight < 0.001, cluster
extent threshold kE = 237 voxels (corresponding to a size
of 0.8 cm3 ; applied voxel size = 1.5 × 1.5 × 1.5 mm), and
cluster-level PFWE < 0.05. Total intracranial volume was used as
covariate for the VBM SPM group analysis. Correlations between
significant effects on brain regions and the psychometric scores
were explored.
RESULTS
Subject Characteristics
In total 33 subjects were initially included and scanned at
baseline. Two subjects withdrew and one was excluded after the
baseline scan due to significant WM lesions due to a delivery
trauma at birth. After randomization (paper picking of numbers
1 or 2 by the subjects), a small but significant age difference [31.8
± 9.8 years (yoga, range 22–51 years) vs. 24.9 ± 5.1 years (cycling,
range 19–38 years), P = 0.02] was present between both groups.
This difference was neglected as for FDG PET, SV2A PET density
and structural MR imaging no significant age effect between 20
and 50 years is known (41–45). Also, although both female and
male subjects were eligible in the study, only female subjects were
included (Table 1). In the yoga group, the average number of
lessons attended was 21.1 ± 1.2 (range 20–24); similar to the
cycling group: 21.4 ± 1.4 (range 20–24), P = 0.49.
Statistical Analyses
Statistical analyses were conducted using Prism (v5, GraphPad,
San Diego, USA) or SPSS (v26, IBM, Corporation, Chicago,
Illinois). P-values were considered significant at an alpha level
of 0.05. For the psychometric questionnaires, data were analyzed
in a repeated ANOVA design (interaction effect group × time),
followed by post-hoc between-group unpaired t-tests (yoga vs.
indoor cycling, at baseline and post-intervention) and withingroup paired t-tests (baseline vs. post-intervention, in the yoga
and indoor cycling group). In SPM, both PET targets and the
T1-weighted images (VBM) were explored in a flexible factorial
design to investigate interaction effects and in a 2 × 2 design;
post-hoc between-group unpaired t-tests (yoga vs. indoor cycling,
at baseline and post-intervention) and within-group paired ttests (baseline vs. post-intervention, in the yoga and indoor
cycling group). Both absolute (parametric rCMRGlc images and
SUVR [11 C]UCB-J images) and relative ([18 F]FDG uptake and
[11 C]UCB-J, normalized to global [18 F]FDG uptake and global
[11 C]UCB-J binding in GM, respectively) were analyzed. SPM
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Yoga group
Psychometric Scales
For the psychometric scales, no significant interaction effect
(group × timing) was found. However, a significant increase
after yoga intervention was observed in the MAIA interoceptive
awareness total score compared to baseline (26.2 ± 5.2 vs.
23.9 ± 4.7, P = 0.001 (uncorrected), remaining significant
after Bonferroni correction for the number of scales) (Figure 1;
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PET/MR Study in Yoga Subjects
FIGURE 1 | Results of the multidimensional assessment of interoceptive awareness (MAIA) scale and subscales of both groups (yoga and cycling), at baseline (BL)
and post-intervention (POST). Significant results of the paired tests are indicated with * (P < 0.05, uncorrected) and ** (P < 0.005, uncorrected).
functioning” (P = 0.009, uncorrected) and “overall functioning”
(P = 0.01, uncorrected) subscales of the LAPS affect and pleasure
scale in the yoga group compared to the cycling group.
Table 2). For the MAIA subscores, this increase was also reflected
in the subdimensions “noticing” (P = 0.02 (uncorrected),
Bonferroni uncorrected), “emotional awareness” (P = 0.009,
uncorrected), “self-regulation” (P = 0.015, uncorrected), and
“body listening” (P = 0.007, uncorrected). For the cycling group,
a significant (P = 0.04, uncorrected) increase in the emotional
awareness score was observed, but no overall effect on the global
MAIA score.
Furthermore, in the yoga subjects, scores on the “observe
items” of the mindfulness FFMQ questionnaire increased
significantly (P = 0.04, uncorrected) compared to baseline
(Table 2). No significant intervention differences were observed
for the PSS, PSWQ, and SCS.
For the between group analysis at baseline, both groups
did not score significantly different on the psychometric scales.
A significant difference between groups was observed after
the intervention however, showing higher scores on “cognitive
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Glucose Metabolism and Intervention
Effects
No significant interaction effects were found. No significant
differences in absolute glucose metabolism were found between
both groups (at baseline and post-intervention), nor within
groups (comparing the baseline vs. post-intervention condition).
The mean absolute glucose metabolism values in the different
composite VOIs are shown in Figure 2A. For relative glucose
metabolism, normalized on total GM, no differences were found
between groups Figure 2B. Within-group analyses showed no
significant differences after the yoga intervention. However,
for the indoor cycling group, the paired within-group showed
significant increases in relative glucose metabolism in the
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Yoga
Scale
Cycling
Repeated
ANOVA
P-value
Within groups (paired)
(intervention effect)
Between groups (unpaired)
(group effect)
Baseline
Post
Baseline
Post
Group × Time
Yoga
Cycling
Baseline
Post
Positive affect
7.8(1.1)
7.9(1.3)
7.2(1.4)
7.3(1.2)
0.94
0.78
0.87
0.23
0.22
Negative affect
1.2(1.0)
2.0(1.6)
1.6(0.9)
2.2(1.5)
0.73
0.07
0.15
0.23
0.69
Hedonic tone
8.8(1.0)
8.6(1.1)
8.5(0.9)
8.1(1.1)
0.64
0.35
0.06
0.34
0.22
Cognitive functioning
8.1(1.7)
8.6(1.1)
7.9(1.5)
7.3(1.4)
0.06
0.20
0.18
0.66
0.009a
Overall functioning
8.7(1.3)
8.8(0.9)
8.2(1.3)
7.7(1.3)
0.26
0.84
0.19
0.28
0.01a
Meaningful life
8.5(1.0)
8.1(1.2)
7.4(2.2)
7.9(1.2)
0.30
0.21
0.52
0.10
0.56
Happiness
8.5(1.1)
8.3(1.2)
7.5(1.6)
7.7(1.5)
0.33
0.30
0.63
0.04
0.23
van Aalst et al.
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TABLE 2 | Psychometric results of the between and within group analyses.
LAPS
Independent variables:
FFMQ
6
138.9(18.9)
139.4(13.3)
140.9(13.9)
0.97
0.51
0.55
0.71
0.74
24.5(5.4)
26.8(5.8)
25.9(4.4)
27.5(5.0)
0.54
0.04a
0.07
0.42
0.74
Describe items
28.67(5.4)
28.5(5.3)
30.1(5.5)
30.0(6.3)
0.96
0.81
0.90
0.47
0.48
Awareness items
29.7(5.4)
28.0(5.8)
29.3(4.7)
29.1(5.4)
0.35
0.09
0.87
0.86
0.59
Non-judge items
30.8(4.7)
30.9(4.9)
32.5(3.4)
32.4(4.0)
0.91
0.93
0.95
0.27
0.36
Non-react items
23.9(4.2)
24.7(3.5)
21.5(4.9)
21.9(4.5)
0.71
0.41
0.59
0.17
0.07
PSS
12.1(6.3)
12.6(5.4)
12.1(5.8)
12.9(5.4)
0.86
0.80
0.49
0.98
0.87
PSWQ
31.0(13.2)
30.1(14.9)
33.2(14.8)
36.6(15.2)
0.50
0.83
0.48
0.67
0.25
SCS
28.1(7.5)
27.2(6.0)
29.9(4.4)
28.0(4.3)
0.51
0.30
0.06
0.41
0.69
MAIA
23.9(4.7)
26.2(5.2)
24.8(4.4)
25.8(3.2)
0.18
0.001b
0.21
0.61
0.78
Noticing
3.0(1.0)
3.6(1.0)
3.5(0.8)
3.6(0.4)
0.07
0.02a
0.58
0.20
0.81
Not-distracting
2.1(0.8)
2.1(0.9)
2.4(0.5)
2.2(0.7)
0.39
0.88
0.17
0.25
0.72
Not-worrying
4.0(0.8)
3.8(0.9)
3.7(0.9)
3.6(0.9)
0.78
0.29
0.41
0.40
0.55
Attention regulation
3.2(0.6)
3.2(0.9)
3.0(0.8)
3.3(0.5)
0.45
0.68
0.14
0.52
0.94
Emotional awareness
3.4(0.9)
3.8(0.9)
3.3(0.9)
3.6(0.6)
0.90
0.009a
0.04a
0.69
0.56
Self-regulation
2.6(1.2)
3.3(0.9)
2.7(1.1)
3.0(0.6)
0.28
0.015a
0.40
0.82
0.40
Body listening
1.8(1.1)
2.5(1.2)
2.2(0.8)
2.5(1.1)
0.20
0.007a
0.10
0.33
0.96
Trusting
3.8(0.6)
4.0(0.8)
4.0(0.7)
4.0(0.7)
0.52
0.13
0.93
0.33
0.81
BL, baseline; FFMQ, five facet mindfulness questionnaire; LAPS, Leuven affect and pleasure scale; MAIA, multi-assessment interoceptive awareness; PSS, perceived stress scale; PSWQ, Penn state worrying questionnaire; SCS,
self-compassion scale.
a (significant) uncorrected, b remains significant after Bonferroni correction.
PET/MR Study in Yoga Subjects
October 2021 | Volume 12 | Article 739356
137.5(15.2)
Observe items
van Aalst et al.
PET/MR Study in Yoga Subjects
FIGURE 2 | Regional mean (A) absolute glucose metabolism (rCMRGlu), (B) relative glucose metabolism, (C) SUVR [11 C]UCB-J, and (D) relative synaptic density in
the composite VOIs (FCx, frontal cortex; ACCx, anterior cingulate cortex; PCCx, posterior cingulate cortex; LTL, lateral temporal lobe; MTL, medial temporal lobe; PCx,
parietal cortex; OCx, occipital cortex; Str, striatum; Thal, thalamus; ICx, insular cortex; Cbl, cerebellum; Bs, brainstem). Error bars represent one standard deviation.
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FIGURE 3 | Within-groups analysis of relative glucose metabolism. (A) Voxel-based paired t-statistical map for the cycling group showing increased relative glucose
metabolism post intervention compared to baseline. Evaluation at PFWE < 0.05 corrected at cluster level, Pheight < 0.001 uncorrected at voxel level, K ext >0.8 cm3 .
The results are projected on the group’s average 3D T1-weighted MR. (B) Regional relative glucose metabolism in the parahippocampus (+2.2%; P = 0.0002) and
fusiform gyrus (+2.2%; P = 0.006), paired t-tests. **: P < 0.005.
volume after the 12-week yoga intervention nor after the
cycling intervention.
cerebellum (region 4, 5, 6, and 10), fusiform gyrus, and
parahippocampus with a peak effect in the right and left upper
cerebellar gyrus (region 4/5), of +4.3 and +5.7%, respectively
(Figure 3A; Supplementary Table 1). The VOI-based analysis
confirmed this significant relative increased glucose metabolism
in the parahippocampus (+2.2%; P = 0.0002) and fusiform
gyrus (+2.2%; P = 0.006) (Figure 3B). Regional average relative
glucose metabolism values in the different composite VOIs
are given in Figure 2B. No significant correlations were found
between the psychometric scores and increased regional relative
glucose metabolism in the indoor cycling group.
DISCUSSION
Several cross-sectional imaging studies have shown that
long-term yoga practice may lead to both structural and
functional/metabolic alterations (7, 46). The objective of this
(current) study was to determine in a longitudinal study whether
behavioral and multimodal imaging biomarker change in
sedentary healthy subjects starting either a yoga intervention
vs. a physical matched intervention. Whereas, a clear effect on
relevant behavioral changes was present, including interoceptive
awareness and cognition scores, no significant imaging-based
changes were found after this 12-week intervention.
For the psychometric scales, especially interoceptive
awareness increased significantly after successful completion
of a 12-week yoga intervention with more than 20 sessions.
Previous studies have shown similar behavioral effects after
mindfulness interventions, accompanied by increases in the
MAIA subscales as well (26, 47). After a mindfulness intervention
of 3 months, Bornemann et al. found significant overall increase
in interoceptive awareness in healthy volunteers, with significant
changes on self-regulation, attention regulation, emotional
awareness, body listening, and trusting subscales. Also de Jong
et al., investigating patients with chronic pain and comorbid
Synaptic Density and Intervention Effects
No significant interaction effects were found. The groups did
not differ in synaptic density (n = 10 each), both in absolute
(SUVR) as well as in relative terms. Neither intervention resulted
in a demonstrable effect on regional synaptic density. The mean
[11 C]UCB-J SUVR and relative synaptic density VOI-based
values for the baseline and post intervention conditions are
shown in Figures 2C,D.
Gray Matter Volume and Intervention
Effects
No significant interaction effects were found. At baseline, no
differences in GM volume values were found between both
groups. Also, VBM did not show significant changes in GM
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from the frequency and duration of the current study where
yoga-naive participants practiced yoga only twice a week for
12 weeks with on average 21 sessions, which may have been
too short or too infrequent to instigate measurable metabolic
effects. The intervention duration for the current study was
chosen as a practically achievable time scale, so new designs
will have to take longer durations and/or more frequent sessions
into consideration.
After the indoor cycling intervention, significant clusters of
increased resting glucose metabolism were found in cognitive
and motor brain areas: parahippocampal gyrus, fusiform gyrus,
and upper cerebellum. The parahippocampal gyrus is associated
with many cognitive processes, including visuospatial processing
and episodic memory, but also emotion processing (51).
Extensive involvement of the parahippocampal gyrus has been
found in the majority of animal and human studies investigating
neuronal activity in relation to physical activity (52), and was
associated with positive effects on memory (53, 54). This is
supported by evidence of increased levels of serum brain derived
neurotrophic factor (BDNF) after exercise interventions (55–
57). Brain derived neurotrophic factor is an important molecule
for synaptic plasticity and known to play a crucial role in
learning and memory (58). Increased levels of BDNF have been
repeatedly reported in the hippocampal regions of rodents after
physical activity (59, 60). Similarly, elderly healthy subjects that
were more physically active showed higher glucose metabolism
in the parahippocampus and fusiform gyrus (61). The link
between physical activity and increased glucose metabolism in
the fusiform gyrus remains speculative as the fusiform gyrus
is mainly known for its involvement in functionally specialized
computations of higher-order visual features such as object
recognition and face perception (62, 63). In line with the
observed increased glucose metabolism in the upper cerebellum,
Talukdar et al. found that general aerobic fitness was significantly
associated with increased brain activity in the upper cerebellum
in addition to sensory, motor, and memory processing regions
(64). The connections of the upper cerebellum with the primary
motor cortex and a somatotopic organization of both lower and
upper limbs, play a pivotal role in motor functioning, which
is heavily interrogated during indoor cycling or aerobic activity
(more than in slow, postural changes in yoga) and could therefore
explain this association.
It can be hypothesized that alterations in glucose metabolism,
a main determinant of synaptic activity, may after time lead to
strengthening of synapses (65). Therefore, only after long enough
metabolic activation, more synaptic connections (hence synaptic
density) and ultimately microstructural increases in GM volume
can be expected. Concerning effects of yoga on macroscopic
structure, to the best of our knowledge only two studies have
been published in a longitudinal interventional setting. Also here,
despite daily practicing yoga (mindfulness based stress reduction
including yoga postures and yogic meditation) over a period of
8–12 weeks, no increased GM volume was found (66, 67), (which
is) in line with our data. In addition, interventional longitudinal
imaging studies investigating physical activity in healthy subjects
are limited as well. Erickson et al. found that in healthy
elderly individuals hippocampal volumes increased after regular
depression, reported significant effects of an 8-week mindfulness
intervention, on self-regulation, emotional awareness, and
not-distracting subscales (26, 47). Effects on the self-regulation
and emotional awareness subscales, also found in our study,
thus show an overlapping effect of mindfulness and yoga-based
interventions. Of interest, in our study specific “formal” guided
meditation components represent only a minor part of the whole
yoga lesson. During yoga practice, interoceptive awareness is
addressed by drawing attention, feeling emotions, and bodily
sensations to the present moment. This indicates that adding the
dimensions of breathing techniques and meditation are needed
to alter interoceptive awareness, as only exercise as shown in
the control arm with indoor cycling, was unable to change
this. In contrast, the FFMQ, a particular scale oriented toward
mindfulness did not change significantly in our study. This is in
contrast to previous interventional studies that had a stronger
focus on additional mindfulness or yoga philosophy components
such as Kripalu yoga emphasizing the cultivation of “witness
consciousness” and compassion, and a combination of yin yoga
and mindfulness (22, 24), compared to the yoga styles practiced
in this study. Specific mindfulness-based interventions may
be needed to improve self-compassion (48). Also, a significant
relationship between class frequency or practice experience with
mindfulness scores and self-compassion levels has been found
previously, suggesting that the frequency and length of a yoga
intervention plays a crucial role in achieving optimal changes in
mindfulness and self-compassion scores (23).
Mind-body interventions such as yoga are increasingly used
for stress reduction, often investigated with the perceived stress
scale (22, 24, 49). In a systematic review addressing the effects
of yoga on stress in healthy individuals, yoga was beneficial on
reducing stress levels in the majority of the included studies
(50). However, here we did not observe a decrease in perceived
stress. Some participants mentioned at the end of the study that
introducing the intervention in their daily life schedule was even
stressful at times. Other studies have found even increased stress
levels at the end of a yoga intervention that could be related
to a too overwhelming class schedule on top of daily activities
and/or that the expectations were not in line with reality (49).
As previous research has addressed a beneficial effect of yoga in
mood disorder (depression and anxiety), we also explored the
effects of yoga on affect in healthy subjects. In this study, we
found increased scores on cognitive and overall functioning with
the LAPS in the yoga group compared to the controls after the
intervention. Although no differences were found on positive
affect, increases in cognitive functioning may precede effects
on positive affect, as a link between cognitive functioning and
positive affect has been described previously (27).
Regarding the three neuroimaging markers (i.e., glucose
metabolism, synaptic density, and GM volume), we did not
observe significant differences in any of these markers after the
yoga intervention compared to baseline. In our previous crosssectional study, a strong and highly significant decrease in the
medial temporal cortex, striatum, and brainstem was observed
in experienced yoga subjects, with an average of 4.8 years of
yoga experience and at least four practices per week, totaling
at least 150 sessions per year (10). This is markedly different
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aerobic exercise at moderate-intensity for 1 year (68). Another
interventional study in healthy elderly individuals before and
after 6 months of aerobic training found increased volumes in
the anterior cingulate cortex, supplementary motor association
cortex, inferior frontal gyrus, and left superior temporal gyrus
(69). Thus, only in studies conducted over a longer time span
and higher cumulated activity levels compared to our study,
significant effects were found.
Additionally, no changes in synaptic density were found using
[11 C]UCB-J PET imaging in the subcohort. Even a more liberal
threshold up to 0.01 did not result in significant clusters. As the
field of in vivo synaptic density imaging is still very young (12), no
other studies investigating the effects of any behavioral/physical
interventions on synaptic density in humans have been published
so far. Therefore, it is difficult to speculate on the intensity of
a behavioral intervention that would be needed for detection of
a macroscopic difference combined to the test sensitivity (T-RT
values about 5%) (70). In rodents, aerobic exercise (treadmill
running), 5 days a week for 4 or 12 weeks resulted in increased
hippocampal synaptic density (60.6–75.1% higher number of
synapses per cubic micron of tissue in treadmill training vs.
sedentary), using post-mortem immunofluorescent staining and
electron microscopy (71, 72).
A few study limitations should be addressed. First, the
group size in this academic interventional trial was relatively
small and the duration and frequency of the intervention was
limited, because the feasibility of the study for the subjects was
considered. However, previous studies investigating effects of
yoga on the brain used similar study designs in terms of study
duration and frequency (4, 66, 67, 73–75). The study length and
frequency were considered as an optimal balance between study
feasibility, duration, cost, and potential drop-out rate. Secondly,
as no significant differences in GM volume between both groups,
nor between the baseline vs. the post- intervention condition,
were found, we did not apply partial volume correction on the
PET data. Thirdly, the participants were randomly assigned to
either the yoga intervention or the indoor cycling intervention.
As subjects may have showed preference toward one specific
intervention, and preference of the participant may influence
the outcome (76), a chance of underperforming in the control
group may have occurred. However, based on the number of
sessions followed and the detailed, consistent information in
self-reporting logs of the participants in both groups, we expect
no systematic bias from this aspect. Finally, the yoga group
could attend classes of four different yoga styles, each having
a different emphasis. Although the relative composition of the
yoga classes (postures/breathing/meditation) remained stable,
there is still debate about which component of yoga causes
the most substantial behavioral or physical benefits (7). Thus,
a different ratio between the components could be necessary
to detect stronger neuronal effects. Furthermore, these types
of comprehensive changes may require longer time before
macroscopic effects become evident.
In conclusion, we found that a yoga intervention of 12 weeks
increases interoceptive awareness. However, we were not yet able
to observe metabolic, synaptic density or volumetric correlates
of this behavioral finding after this short intervention. Therefore,
in line with previous results, longer interventions and/or higher
frequency of yoga practice may be needed to objectivate cerebral
metabolic and/or structural brain effects. Furthermore, indoor
12 weeks of cycling did significantly increase regional glucose
metabolism in brain regions important for motor functioning
and cognition, but did not result into interoceptive or measurable
cognitive improvements.
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 local University Ethics Committee of Leuven. The
patients/participants provided their written informed consent to
participate in this study.
AUTHOR CONTRIBUTIONS
JvA, KVL, and KD contributed to conception and design of the
study. JvA, LJ, and KVL collected the data. JvA, LJ, JC, SS, MK,
and KVL performed the (statistical) analysis. JvA wrote the first
draft of the manuscript. JvA, LJ, JC, KD, SS, and KVL wrote
sections of the manuscript. All authors contributed to manuscript
revision, read, and approved the submitted version.
FUNDING
KVL is senior clinical research fellow for the Research
Foundation-Flanders (FWO), JC is post-doctoral fellow
for FWO.
ACKNOWLEDGMENTS
We acknowledge the skilled help of the local PET/MR
technologists and radiopharmacy staff.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fpsyt.
2021.739356/full#supplementary-material
REFERENCES
survey. Am J Prev Med. (2016) 50:230–5. doi: 10.1016/j.amepre.2015.
07.037
2. Riley KE, Park CL. How does yoga reduce stress? A systematic
review of mechanisms of change and guide to future inquiry.
1. Cramer H, Ward L, Steel A, Lauche R, Dobos G. Zhang Y. Prevalence,
patterns, and predictors of yoga use: results of a us nationally representative
Frontiers in Psychiatry | www.frontiersin.org
10
October 2021 | Volume 12 | Article 739356
van Aalst et al.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
PET/MR Study in Yoga Subjects
20. Beck AT, Steer RA, Carbin MG. Psychometric properties of the Beck
Depression Inventory: twenty-five years of evaluation. Clin Psychol Rev. (1988)
8:77–100. doi: 10.1016/0272-7358(88)90050-5
21. Cramer H, Anheyer D, Lauche R, Dobos G. A systematic review of
yoga for major depressive disorder. J Affect Disord. (2017) 213:70–7.
doi: 10.1016/j.jad.2017.02.006
22. Hylander F, Johansson M, Daukantaite D, Ruggeri K. Yin yoga and
mindfulness: a five week randomized controlled study evaluating the effects
of the YOMI program on stress and worry. Anxiety Stress Coping. (2017)
30:365–78. doi: 10.1080/10615806.2017.1301189
23. Snaith N, Schultz T, Proeve M, Rasmussen P. Mindfulness, self-compassion,
anxiety and depression measures in South Australian yoga participants:
implications for designing a yoga intervention. Complement Ther Clin Pract.
(2018) 32:92–9. doi: 10.1016/j.ctcp.2018.05.009
24. Gard T, Brach N, Hölzel BK, Noggle JJ, Conboy LA, Lazar SW. Effects
of a yoga-based intervention for young adults on quality of life and
perceived stress: the potential mediating roles of mindfulness and selfcompassion. J Posit Psychol. (2012) 7:165–75. doi: 10.1080/17439760.2012.
667144
25. Neukirch N, Reid S, Shires A. Yoga for PTSD and the role of
interoceptive awareness: a preliminary mixed-methods case series study.
Eur J Trauma Dissociation. (2019) 3:7–15. doi: 10.1016/j.ejtd.2018.
10.003
26. Bornemann B, Herbert BM, Mehling WE, Singer T. Differential
changes in self-reported aspects of interoceptive awareness through
3 months of contemplative training. Front Psychol. (2015) 5:1504.
doi: 10.3389/fpsyg.2014.01504
27. Demyttenaere K, Mortier P, Kiekens G, Bruffaerts R. Is there enough “interest
in and pleasure in” the concept of depression? The development of the
Leuven Affect and Pleasure Scale (LAPS). CNS Spectr. (2019) 24:265–74.
doi: 10.1017/s1092852917000578
28. Baer RA, Smith GT, Hopkins J, Krietemeyer J, Toney L. Using self-report
assessment methods to explore facets of mindfulness. Assessment. (2006)
13:27–45. doi: 10.1177/1073191105283504
29. Cohen S, Kamarck T, Mermelstein R. A Global measure of perceived stress. J
Health Soc Behav. (1983) 24:385–96. doi: 10.2307/2136404
30. Meyer TJ, Miller ML, Metzger RL, Borkovec TD. Development and validation
of the penn state worry questionnaire. Behav Res Ther. (1990) 28:487–95.
doi: 10.1016/0005-7967(90)90135-6
31. Neff KD, Kinney S, Kirkpatrick K, Schmitt LT, Hsieh Y-P, Chen W-C, et al.
The development and validation of a scale to measure self-compassion. Self
Identity. (2003) 2:223–50. doi: 10.1080/15298860390209035
32. Hunter GJ, Hamberg LM, Alpert NM, Choi NC. Fischman AJ. Simplified
measurement of deoxyglucose utilization rate. J Nucl Med. (1996) 37:950–5.
33. Koole M, van Aalst J, Devrome M, Mertens N, Serdons K, Lacroix
B, et al. Quantifying SV2A density and drug occupancy in the human
brain using [11C]UCB-J PET imaging and subcortical white matter
as reference tissue. Eur J Nucl Med Mol Imaging. (2018) 46:396–406.
doi: 10.1007/s00259-018-4119-8
34. Rezaei A, Schramm G, Willekens SM, Delso G, Van Laere K, Nuyts J. A
quantitative evaluation of joint activity and attenuation reconstruction
in TOF-PET/MR brain imaging. J Nucl Med. (2019) 60:1649–55.
doi: 10.2967/jnumed.118.220871
35. Schramm G, Koole M, Willekens SMA, Rezaei A, Van Weehaeghe D, Delso
G, et al. Regional accuracy of ZTE-based attenuation correction in static and
dynamic brain PET/MR. Physics. (2018) arXiv:1806.03481v1.
36. Rossano S, Toyonaga T, Finnema SJ, Naganawa M, Lu Y, Nabulsi N,
et al. Assessment of a white matter reference region for 11C-UCBJ PET quantification. J Cereb Blood Flow Metab. (2019) 40:1890–901.
doi: 10.1177/0271678X19879230
37. Wu HM, Bergsneider M, Glenn TC, Yeh E, Hovda DA, Phelps ME,
et al. Measurement of the global lumped constant for 2-deoxy-2[18F]fluoro-D-glucose in normal human brain using [15O]water
and 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography
imaging: a method with validation based on multiple methodologies.
Mol Imaging Biol. (2003) 5:32–41. doi: 10.1016/S1536-1632(02)
00122-1
Health Psychol Rev. (2015) 7199:1–18. doi: 10.1080/17437199.2014.
981778
Cartwright T, Mason H, Porter A, Pilkington K. Yoga practice in
the UK: a cross-sectional survey of motivation, health benefits and
behaviours. BMJ Open. (2020) 10:e031848. doi: 10.1136/bmjopen-2019-0
31848
van Aalst J, Ceccarini J, Demyttenaere K, Sunaert S, Van Laere K.
What has neuroimaging taught us on the neurobiology of yoga? A
review. Front Integr Neurosci. (2020) 14:34. doi: 10.3389/fnint.2020.
00034
Critchley HD, Nicotra A, Chiesa PA, Nagai Y, Gray MA, Minati L,
et al. Slow breathing and hypoxic challenge: cardiorespiratory consequences
and their central neural substrates. PLoS ONE. (2015) 10:e0127082.
doi: 10.1371/journal.pone.0127082
Streeter CC, Jensen JE, Perlmutter RM, Cabral HJ, Tian H, Terhune
DB, et al. Yoga asana sessions increase brain GABA levels: a pilot
study. J Altern Complement Med. (2007) 13:419–26. doi: 10.1089/acm.20
07.6338
Villemure C, Ceko M, Cotton VA, Bushnell MC. Neuroprotective
effects of yoga practice: age-, experience-, and frequency-dependent
plasticity. Front Hum Neurosci. (2015) 9:281. doi: 10.3389/fnhum.2015.
00281
Elías Hernández S, Suero J, Barros A, Luis González-Mora J, Rubia K.
Increased grey matter associated with long-term sahaja yoga meditation:
a voxel-based morphometry study. PLoS ONE. (2016) 11:e0150757.
doi: 10.1371/journal.pone.0150757
Phillips C. Lifestyle modulators of neuroplasticity: how physical activity,
mental engagement, and diet promote cognitive health during aging. Neural
Plast. (2017) 2017:3589271. doi: 10.1155/2017/3589271
van Aalst J, Ceccarini J, Schramm G, Van Weehaeghe D, Rezaei A,
Demyttenaere K, et al. Long-term Ashtanga yoga practice decreases
medial temporal and brainstem glucose metabolism in relation to years
of experience. EJNMMI Res. (2020) 10:50. doi: 10.1186/s13550-02000636-y
Zimmer ER, Parent MJ, Souza DG, Leuzy A, Lecrux C, Kim HI, et al.
[18F]FDG PET signal is driven by astroglial glutamate transport. Nat Neurosci.
(2017) 20:393–5. doi: 10.1038/nn.4492
Finnema SJ, Nabulsi NB, Eid T, Detyniecki K, Lin SF, Chen MK, et al. Imaging
synaptic density in the living human brain. Sci Transl Med. (2016) 8:1–10.
doi: 10.1126/scitranslmed.aaf6667
Nabulsi NB, Mercier J, Holden D, Carre S, Najafzadeh S, Vandergeten M-C,
et al. Synthesis and preclinical evaluation of 11C-UCB-J as a PET tracer for
imaging the synaptic vesicle glycoprotein 2A in the brain. J Nucl Med. (2016)
57:777–84. doi: 10.2967/jnumed.115.168179
Holmes SE, Scheinost D, Finnema SJ, Naganawa M, Davis MT,
DellaGioia N, et al. Lower synaptic density is associated with depression
severity and network alterations. Nat Commun. (2019) 10:1–10.
doi: 10.1038/s41467-019-09562-7
Chen M-K, Mecca AP, Naganawa M, Finnema SJ, Toyonaga T, Lin S,
et al. Assessing synaptic density in alzheimer disease with synaptic vesicle
glycoprotein 2A positron emission tomographic imaging. JAMA Neurol.
(2018) 75:1215–24. doi: 10.1001/jamaneurol.2018.1836
Vanhaute H, Ceccarini J, Michiels L, Koole M, Sunaert S, Lemmens
R, et al. In vivo synaptic density loss is related to tau deposition
in amnestic mild cognitive impairment. Neurology. (2020) 95:e545–53.
doi: 10.1212/wnl.0000000000009818
van Aalst J, Ceccarini J, Sunaert S, Dupont P, Koole M, Van Laere K. In vivo
synaptic density relates to glucose metabolism at rest in healthy subjects, but is
strongly modulated by regional differences. J Cereb Blood Flow Metab. (2021)
41:1978–87. doi: 10.1177/0271678X20981502
Park C, Groessl E, Maiya M, Sarkin A, Eisen S V, Riley K, et al.
Comparison groups in yoga research: a systematic review and critical
evaluation of the literature. Complement Ther Med. (2014) 22:920–9.
doi: 10.1016/j.ctim.2014.08.008
Gilani SRM, Feizabad AK. The effects of aerobic exercise training on mental
health and self-esteem of type 2 diabetes mellitus patients. Heal Psychol Res.
(2019) 7:6576. doi: 10.4081/hpr.2019.6576
Frontiers in Psychiatry | www.frontiersin.org
11
October 2021 | Volume 12 | Article 739356
van Aalst et al.
PET/MR Study in Yoga Subjects
38. Hammers A, Allom R, Koepp MJ, Free SL, Myers R, Lemieux L, et al.
Three-dimensional maximum probability atlas of the human brain, with
particular reference to the temporal lobe. Hum Brain Mapp. (2003) 19:224–47.
doi: 10.1002/hbm.10123
39. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard
O, Delcroix N, et al. Automated anatomical labeling of activations in
SPM using a macroscopic anatomical parcellation of the MNI MRI
single-subject brain. Neuroimage. (2002) 15:273–89. doi: 10.1006/nimg.20
01.0978
40. Farokhian F, Beheshti I, Sone D, Matsuda H. Comparing CAT12 and
VBM8 for detecting brain morphological abnormalities in temporal
lobe epilepsy. Front Neurol. (2017) 8:428. doi: 10.3389/fneur.2017.
00428
41. Michiels L, Delva A, van Aalst J, Ceccarini J, Vandenberghe W, Vandenbulcke
M, et al. Synaptic density in healthy human aging is not influenced by
age or sex: a 11C-UCB-J PET study. Neuroimage. (2021) 2021:117877.
doi: 10.1016/j.neuroimage.2021.117877
42. DeCarli C, Massaro J, Harvey D, Hald J, Tullberg M, Au R, et al.
Measures of brain morphology and infarction in the framingham heart
study: establishing what is normal. Neurobiol Aging. (2005) 26:491–510.
doi: 10.1016/j.neurobiolaging.2004.05.004
43. Walhovd KB, Westlye LT, Amlien I, Espeseth T, Reinvang I, Raz
N, et al. Consistent neuroanatomical age-related volume differences
across multiple samples. Neurobiol Aging. (2011) 32:916–32.
doi: 10.1016/j.neurobiolaging.2009.05.013
44. Kakimoto A, Ito S, Okada H, Nishizawa S, Minoshima S, Ouchi Y. Age-related
sex-specific changes in brain metabolism and morphology. J Nucl Med. (2016)
57:221–5. doi: 10.2967/jnumed.115.166439
45. Malpetti M, Ballarini T, Presotto L, Garibotto V, Tettamanti M, Perani D.
Gender differences in healthy aging and Alzheimer’s dementia: a 18 F-FDGPET study of brain and cognitive reserve. Hum Brain Mapp. (2017) 38:4212–
27. doi: 10.1002/hbm.23659
46. Hernández SE, Barros-Loscertales A, Xiao Y, González-Mora JL, Rubia K.
Gray matter and functional connectivity in anterior cingulate cortex are
associated with the state of mental silence during sahaja yoga meditation.
Neuroscience. (2018) 371:395–406. doi: 10.1016/j.neuroscience.2017.
12.017
47. de Jong M, Lazar SW, Hug K, Mehling WE, Hölzel BK, Sack AT, et al.
Effects of mindfulness-based cognitive therapy on body awareness in patients
with chronic pain and comorbid depression. Front Psychol. (2016) 7:967.
doi: 10.3389/fpsyg.2016.00967
48. Wasson RS, Barratt C, O’Brien WH. Effects of mindfulness-based
interventions on self-compassion in health care professionals: a metaanalysis. Mindfulness (N Y). (2020) 11:1914–34. doi: 10.1007/s12671-02001342-5
49. Kinchen E, Loerzel V, Portoghese T. Yoga and perceived stress,
self-compassion, and quality of life in undergraduate nursing
students. J Educ Health Promot. (2020) 9:292. doi: 10.4103/jehp.jehp_
463_20
50. Chong C, Tsunaka M, Tsang H, Chan E, Cheung W. Effects of yoga on stress
management in healthy adults: a systematic review. Altern Ther Health Med.
(2011) 17:32–8.
51. Aminoff EM, Kveraga K, Bar M. The role of the parahippocampal cortex in
cognition. Trends Cogn Sci. (2013) 17:379–90. doi: 10.1016/j.tics.2013.06.009
52. Loprinzi PD. The effects of physical exercise on parahippocampal
function. Physiol Int. (2019) 106:114–27. doi: 10.1556/2060.106.2
019.10
53. Ruscheweyh R, Willemer C, Krüger K, Duning T, Warnecke T, Sommer
J, et al. Physical activity and memory functions: an interventional study.
Neurobiol Aging. (2011) 32:1304–19. doi: 10.1016/j.neurobiolaging.2009.
08.001
54. Hötting K, Reich B, Holzschneider K, Kauschke K, Schmidt T, Reer R, et al.
Differential cognitive effects of cycling versus stretching/coordination training
in middle-aged adults. Heal Psychol. (2012) 31:145–55. doi: 10.1037/a00
25371
55. Ferris LT, Williams JS, Shen CL. The effect of acute exercise on
serum brain-derived neurotrophic factor levels and cognitive function.
Frontiers in Psychiatry | www.frontiersin.org
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
74.
12
Med Sci Sports Exerc. (2007) 39:728–34. doi: 10.1249/mss.0b013e31802
f04c7
Håkansson K, Ledreux A, Daffner K, Terjestam Y, Bergman P, Carlsson
R, et al. Responses in healthy older persons to 35 minutes of physical
exercise, cognitive training, and mindfulness: associations with working
memory function. J Alzheimer’s Dis. (2017) 55:645–57. doi: 10.3233/JAD160593
Griffin ÉW, Mullally S, Foley C, Warmington SA, O’Mara SM, Kelly
ÁM. Aerobic exercise improves hippocampal function and increases BDNF
in the serum of young adult males. Physiol Behav. (2011) 104:934–41.
doi: 10.1016/j.physbeh.2011.06.005
Cunha C, Brambilla R, Thomas KL. A simple role for BDNF in learning and
memory? Front Mol Neurosci. (2010) 3:1. doi: 10.3389/neuro.02.001.2010
Vaynman S, Ying Z, Gomez-Pinilla F. Hippocampal BDNF mediates the
efficacy of exercise on synaptic plasticity and cognition. Eur J Neurosci. (2004)
20:2580–90. doi: 10.1111/j.1460-9568.2004.03720.x
Liu PZ, Nusslock R. Exercise-mediated neurogenesis in the hippocampus via
BDNF. Front Neurosci. (2018) 12:52. doi: 10.3389/fnins.2018.00052
Matthews DC, Davies M, Murray J, Williams S, Tsui WH Li Y, Andrews RD,
et al. Physical activity, mediterranean diet and biomarkers-assessed risk of
Alzheimer’s: a multi-modality brain imaging study NIH public access. Adv J
Mol Imaging. (2014) 4:43–57. doi: 10.4236/ami.2014.44006
Suwabe K, Byun K, Hyodo K, Reagh ZM, Roberts JM, Matsushita A, et al.
Rapid stimulation of human dentate gyrus function with acute mild exercise.
Proc Natl Acad Sci USA. (2018) 115:10487–92. doi: 10.1073/pnas.1805668115
Aguirre-Loaiza H, Arenas J, Arias I, Franco-Jímenez A, Barbosa-Granados
S, Ramos-Bermúdez S, et al. Effect of acute physical exercise on executive
functions and emotional recognition: analysis of moderate to high intensity
in young adults. Front Psychol. (2019) 10:2774. doi: 10.3389/fpsyg.2019.02774
Talukdar T, Nikolaidis A, Zwilling CE, Paul EJ, Hillman CH, Cohen NJ,
et al. Aerobic fitness explains individual differences in the functional brain
connectome of healthy young adults. Cereb Cortex. (2018) 28:3600–9.
doi: 10.1093/cercor/bhx232
Mainardi M, Fusco S, Grassi C. Modulation of hippocampal neural
plasticity by glucose-related signaling. Neural Plast. (2015) 2015:657928.
doi: 10.1155/2015/657928
Hölzel BK, Carmody J, Evans KC, Hoge EA, Dusek JA, Morgan L, et al. Stress
reduction correlates with structural changes in the amygdala. Soc Cogn Affect
Neurosci. (2009) 5:11–7. doi: 10.1093/scan/nsp034
Yang H, Leaver AM, Siddarth P, Paholpak P, Ercoli L, St. Cyr NM, et al.
Neurochemical and neuroanatomical plasticity following memory training
and yoga interventions in older adults with mild cognitive impairment Front
Aging Neurosci. (2016) 8:277. doi: 10.3389/fnagi.2016.00277
Erickson KI, Voss MW, Prakash RS, Basak C, Szabo A, Chaddock L, et al.
Exercise training increases size of hippocampus and improves memory. Proc
Natl Acad Sci USA. (2011) 108:3017–22. doi: 10.1073/pnas.1015950108
Colcombe SJ, Erickson KI, Scalf PE, Kim JS, Prakash R, McAuley E, et al.
Aerobic exercise training increases brain volume in aging humans. J Gerontol
A Biol Sci Med Sci. (2006) 61:1166–70. doi: 10.1093/gerona/61.11.1166
Finnema SJ, Nabulsi NB, Mercier J, Lin S, Chen M-K, Matuskey D, et al.
Kinetic evaluation and test–retest reproducibility of [11 C]UCB-J, a novel
radioligand for positron emission tomography imaging of synaptic vesicle
glycoprotein 2A in humans. J Cereb Blood Flow Metab. (2018) 38:2041–52.
doi: 10.1177/0271678X17724947
Fattoretti P, Malatesta M, Cisterna B, Milanese C, Zancanaro C.
Modulatory effect of aerobic physical activity on synaptic ultrastructure
in the old mouse hippocampus. Front Aging Neurosci. (2018) 10:141.
doi: 10.3389/fnagi.2018.00141
Li Y, Zhao L, Gu B, Cai J, Lv Y, Yu L. Aerobic exercise regulates Rho/cofilin
pathways to rescue synaptic loss in aged rats. PLoS ONE. (2017) 12:e0171491.
doi: 10.1371/journal.pone.0171491
Dodich A, Zollo M, Crespi C, Cappa SF, Laureiro Martinez D, Falini A, et al.
Short-term Sahaja Yoga meditation training modulates brain structure and
spontaneous activity in the executive control network. Brain Behav. (2019)
9:e01159. doi: 10.1002/brb3.1159
Eyre HA, Acevedo B, Yang H, Siddarth P, Van Dyk K, Ercoli L, et al.
Changes in neural connectivity and memory following a yoga intervention
October 2021 | Volume 12 | Article 739356
van Aalst et al.
PET/MR Study in Yoga Subjects
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for older adults: a pilot study. J Alzheimer’s Dis. (2016) 52:673–84.
doi: 10.3233/JAD-150653
75. Streeter C, Gerbarg PL, Nielsen GH, Brown RP, Jensen JE, Silveri M, et al.
Effects of yoga on thalamic gamma-aminobutyric acid, mood and depression:
analysis of two randomized controlled trials. Neuropsychiatry (London).
(2018) 8:1923–39. doi: 10.4172/Neuropsychiatry.1000535
76. Kwan BM, Dimidjian S, Rizvi SL. Treatment preference,
engagement, and clinical improvement in pharmacotherapy versus
psychotherapy for depression. Behav Res Ther. (2010) 48:799–804.
doi: 10.1016/j.brat.2010.04.003
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