Eur J Neurosci. 2020;51:850–865.
Received: 3 July 2019
Revised: 18 August 2019
Accepted: 27 August 2019
REGISTERED REPORT STAGE 2
The relationship between individual differences in gray matter
volume and religiosity and mystical experiences: A preregistered
voxel‐based morphometry study
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original
work is properly cited.
© 2019 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Edited by EJN Registered Reports Editors.
Abbreviations: DWI, diffusion‐weighted imaging; GLM, general linear model; IPL, inferior parietal lobe; MRI, magnetic resonance imaging; MTL, middle
temporal lobe; OFC, orbitofrontal cortex; ROI, region‐of‐interest; SPL, superior parietal lobe; ToM, theory of mind; VBM, voxel‐based morphometry;
VMPC, ventromedial prefrontal cortex.
1Department of Psychology,University of
Amsterdam, Amsterdam, The Netherlands
2Amsterdam Brain and Cognition
Center,University of Amsterdam,
Amsterdam, The Netherlands
3Spinoza Center for Neuroimaging,Royal
Netherlands Academy of Arts and Sciences,
Amsterdam, The Netherlands
Michiel van Elk, Department of
Psychology, University of Amsterdam,
Nieuwe Achtergracht 129B, 1018WT
Amsterdam, The Netherlands.
John Templeton Foundation, Grant/Award
Number: # 60663
The neural substrates of religious belief and experience are an intriguing though con-
tentious topic. Here, we had the unique opportunity to establish the relation between
validated measures of religiosity and gray matter volume in a large sample of partici-
pants (N=211). In this registered report, we conducted a confirmatory voxel‐based
morphometry analysis to test three central hypotheses regarding the relationship be-
tween religiosity and mystical experiences and gray matter volume. The preregister-
ered hypotheses, analysis plan, preprocessing and analysis code and statistical brain
maps are all available from online repositories. By using a region‐of‐interest analy-
sis, we found no evidence that religiosity is associated with a reduced volume of the
orbito‐frontal cortex and changes in the structure of the bilateral inferior parietal
lobes. Neither did we find support for the notion that mystical experiences are as-
sociated with a reduced volume of the hippocampus, the right middle temporal gyrus
or with the inferior parietal lobes. A whole‐brain analysis furthermore indicated that
no structural brain differences were found in association with religiosity and mys-
tical experiences. We believe that the search for the neural correlates of religious
beliefs and experiences should therefore shift focus from studying structural brain
differences to a functional and multivariate approach.
gray matter volume, mystical experience, religiosity, structural brain differences, voxel‐based
The peer review history for this article is
available at https ://publo ns.com/publo
van ELK and SnOEK
In the early 2000s, several newspapers headlined a study that
had found the God‐spot—a brain region that could be con-
sidered the basis of the widespread belief in an omniscient
omnipresent and powerful being. This news was based on
pioneering work by Andrew Newberg, who identified the
neural correlates of the unitary peak experience of monks
(Newberg, Alavi, et al., 2001; Newberg & Iversen, 2003).
One of their key findings was that the superior parietal lobe
(SPL)—a brain region that has been associated with spatial
attention and temporal processing—showed a reduced activ-
ity during meditative peak experiences compared to baseline.
This finding made sense in light of the phenomenological re-
ports that often referred to feelings of a loss of sense of space
and time and the awareness of a presence that was bigger
than the self. These initial results inspired many neuroscien-
tists, philosophers and theologians to reflect on the poten-
tial implications. While some argued that these brain regions
could be considered a mechanism to perceive ultimate reality
(Beauregard & O'Leary, 2007; Newberg, d'Aquili, & Rause,
2001), other researchers gave a more reductionist interpreta-
tion according to which religious belief and mystical experi-
ence could be considered a by‐product of the way our brains
evolved (Boyer, 2003). In this manuscript, we define religios-
ity as the belief in an invisible supernatural agent (i.e., God)
that is typically based on tradition (as united in a community
of believers) and is manifested by overt behavior such as vis-
iting a church or religious meeting and praying on a daily
basis. Mystical experiences are characterized by a reduced
awareness of the self, the loss of sense of space and time and
the feeling of a strong connection with the surrounding world
The debate on the neural correlates of religious belief and
mystical experience has been fueled by other studies that pro-
vided more in‐depth insight in the brain mechanisms at play
in religion. For instance, the observation that religious partic-
ipants recruit brain areas involved in social cognition during
prayer (Schjoedt, Stdkilde‐Jorgensen, Geertz, & Roepstorff,
2009) has led to an impressive literature on the role of hy-
permentalizing as a cognitive bias predisposing people to
become religious (for recent critical review, see: Maij, van
Harreveld, et al., 2017). Similarly, the observation that re-
ligious believers show a reduced brain response to errors
(Inzlicht, McGregor, Hirsh, & Nash, 2009; Inzlicht & Tullett,
2010) has led to the idea that reduced error monitoring and
prefrontal cortex functioning could be associated with the ac-
ceptance of religious ideas. In line with this suggestion, it has
been found that patients with damage to the orbitofrontal cor-
tex (OFC) have a higher likelihood of having encountered a
mystical experience (Cristofori etal., 2016). Thus, the initial
steps toward unraveling the neural substrates of religiosity
At the same time, the neuroscientific study of religion has
been haunted by a lack of methodological rigor (Schjoedt,
2009). Many studies suffer from small sample sizes, a lack
of well‐validated tasks, and conceptual confusion about the
constructs that are measured. As a consequence, it remains
unclear to what extent theories about the neural substrates
underlying religiosity are actually supported by the data (van
Elk & Aleman, 2017). For instance, although several studies
have suggested the involvement of structural temporal lobe
abnormalities in religiosity, the findings are inconclusive: on
the one hand, temporal lobe atrophy has been associated with
increased religiosity by using a region‐of‐interest (ROI) anal-
ysis (Chan etal., 2009; Owen, Hayward, Koenig, Steffens, &
Payne, 2011), while another study found that higher religios-
ity was associated with an increased volume of the temporal
lobe, also by using an ROI voxel‐based morphometry (VBM)
analysis (Kapogiannis, Barbey, Su, Krueger, & Grafman,
2009). Similarly, whereas several neuropsychological le-
sion‐based studies have shown that damage to the inferior
parietal lobe (IPL) is associated with increased spiritual-
ity (Johnstone, Bodling, Cohen, Christ, & Wegrzyn, 2012;
Johnstone & Glass, 2008; Johnstone et al., 2014; Urgesi,
Aglioti, Skrap, & Fabbro, 2010), another VBM study found
that an increased IPL volume was associated with higher
spirituality (Van Schuerbeek, Baeken, De Raedt, De Mey,
& Luypaert, 2011). Thus, the debate on the precise neural
mechanisms involved in religiosity is far from settled.
In the present registered report, we had the unique op-
portunity to assess the relation between well‐validated mea-
surements of religiosity and structural brain differences in a
high‐powered (N=224) study. This allowed us to empirically
test some of the most prominent hypotheses that have been
put forward regarding the neurocognitive basis of religiosity.
The MRI and religiosity data for this project were already col-
lected as part of a larger collaborative research project, but
had not been analyzed in conjunction. Our religiosity scale
included questions related to religious beliefs and practices.
These questions have been used before in previous studies
on religious beliefs and the relation with mentalizing and
agency detection (Maij, van Harreveld etal., 2017; van Elk,
Rutjens, & van Harreveld, 2017). We also included questions
about mystical experiences, including key items taken from
the mysticism scale (Hood, 1975) and the Tellegen absorption
scale (Tellegen & Atkinson, 1974). By using structural brain
scans and voxel‐based morphometry (Ashburner & Friston,
2000), we investigated whether increased religiosity is associ-
ated with structural differences in gray matter volume, both in
a confirmatory approach using ROI analyses of brain regions
suggested by the literature as well using a whole‐brain anal-
ysis. Given the large number of participants in our study, we
were able to draw more robust and precise inferences about the
relation between religiosity and gray and white matter volume
than in previous studies (Cremers, Wager, & Yarkoni, 2017).
van ELK and SnOEK
The specific hypotheses that we tested were based on a
review of the existing literature on the neurocognitive mech-
anisms involved in religion and spirituality (for detailed re-
view, see: van Elk & Aleman, 2017).
First, we tested whether a reduced volume of the bilateral
orbitofrontal cortex is associated with a stronger endorse-
ment of religious beliefs. This hypothesis follows from the
theoretical framework of predictive processing (van Elk &
Aleman, 2017), as well as from the cognitive resource deple-
tion model (Schjoedt etal., 2013). Central to these theories is
the notion that a process of reduced error monitoring is at the
basis of willingness to accept and believe religious doctrines.
Some neuropsychological studies have indeed shown that
fronto‐temporal dementia and atrophy of the OFC is asso-
ciated with changes in religiosity (Hayward, Owen, Koenig,
Steffens, & Payne, 2011; Miller, Mychack, Seeley, Rosen, &
Boone, 2001). One study found in a small subset of patients
with fronto‐temporal dementia that some of these patients
experienced significant changes in their personality, includ-
ing an increased interest in religiosity (Miller etal., 2001).
In a longitudinal study using structural brain data from 302
participants, it was found that life‐changing religious experi-
ences were associated with a reduction in atrophy of the left
OFC (Hayward etal., 2011). In contrast, in the same study
more frequent participation in public religious worship was
associated with a stronger atrophy of the left OFC—thereby
painting a more complicated picture of the relationship be-
tween the frontal lobes and religiosity. In a small study in-
volving data from 40 participants, it was found that increased
fear of God was associated with a reduced volume of the left
OFC (Kapogiannis, Barbey, Su, Krueger, etal., 2009). And a
clinical study involving data from 103 participants at low or
high risk for depression found that increased importance of
religion and spirituality were associated with increased corti-
cal thickness of the mesial frontal lobe (Miller etal., 2014). A
study with data from 116 patients with traumatic brain injury
found that lesions to the dorsolateral prefrontal cortex and
the middle/superior temporal cortex were associated with in-
creased mysticism (Cristofori etal., 2016). Similarly, it was
found in 119 patients with traumatic brain injury that lesions
of the ventromedial prefrontal cortex (VMPFC, which is ana-
tomically synonymous with the OFC; Phillips, MacPherson,
& Della Sala, 2002) were associated with an increase in reli-
gious fundamentalism (Zhong, Cristofori, Bulbulia, Krueger,
& Grafman, 2017). Finally, a study using data from 40 par-
ticipants with and without non‐clinical psychosis also found
that increased intrinsic religiosity was associated with a re-
duced volume of the OFC (Pelletier‐Baldelli etal., 2014).
Functional brain imaging studies corroborate the notion
that changes in prefrontal cortex functioning are associated
with an increased acceptance of religious ideas. It has been
found for instance that believers compared to skeptics show
a reduced neural response to errors—which was localized to
the anterior cingulate cortex (Inzlicht & Tullett, 2010; Inzlicht
etal., 2009). Furthermore, it has been found that paranormal
believers compared to skeptics showed a reduced activation
of the right inferior frontal gyrus when inferring meaning
in random pictures (Lindeman, Svedholm, Riekki, Raij, &
Hari, 2013) and that religious believers compared to skeptics
showed a stronger reduction in the medial and dorsolateral
prefrontal cortex when listening to a prayer by a charismatic
faith healer (Schjoedt, Stodkilde‐Jorgensen, Geertz, Lund, &
Roepstorff, 2011). On the other hand, it has also been found
that personalized prayer to God by charismatic Christians, ac-
tivates the medial prefrontal cortex (MPFC)—which is con-
sidered to be part of the theory‐of‐mind‐network (Schjoedt
etal., 2009). Similarly, reflecting on God's perceived level
of involvement in the world has also been associated with an
increased activation of the MPFC (Kapogiannis, Barbey, Su,
Zamboni, etal., 2009). However, the apparent inconsistency
between these findings is probably related to differences in
the experimental paradigms that were used to study religi-
osity (i.e., prayer and reflection on traits by definition acti-
vate the theory‐of‐mind‐network). We should also bear in
mind that there is not a one‐to‐one correspondence between
changes in structural brain volume and functional brain data.
In fact, network analysis approaches of functional brain data
(e.g., by using functional or effective connectivity) may be
better suited for capturing the cognitive processes underly-
ing religiosity and mystical experience—as they tap more
directly into the efficiency by which neural networks process
information (Bullmore & Sporns, 2009).
Thus—although there are variable and conflicting find-
ings—overall these studies suggest that a reduced volume
of the frontal cortex—most notably the OFC is associated
with an increase in religiosity. This leads to our first hypoth-
esis that reduced volume in the OFC is associated with an
increase in religious beliefs.
Second, traditionally, abnormalities in temporal lobe
anatomy or function, for example, as observed in patients
with temporal lobe epilepsy, have been associated with in-
creased religiosity (for historical overview, see: Devinsky &
Lai, 2008). It has been reported that patients with temporal
lobe epilepsy can have profound religious experiences, which
have been attributed to spontaneous epileptic spikes in tem-
poral brain areas (Joseph, 2001; Saver & Rabin, 1997). For
instance, a patient suffering from temporal epileptic seizures
reported a conversion experience and receiving messianic
messages (Arzy & Schurr, 2016). Furthermore, as discussed
above, structural changes in the temporal lobe, for example,
due to atrophy, have also been associated with an increase in
religiosity (Chan et al., 2009; Owen et al., 2011). Already
in an early study involving structural brain scans from 33
epilepsy patients, a negative relation was found between
increased religiosity and the volume of the right hippocam-
pus (Wuerfel etal., 2004). Furthermore, some patients with
van ELK and SnOEK
right temporal lobe atrophy—next to experiencing the usual
symptoms associated with temporal lobe atrophy, such as
semantic dementia—showed hyperreligiosity as well (Chan
et al., 2009). In another study, using neuroanatomical data
from 268 adults it was found that having had a life‐chang-
ing religious experience was associated with a stronger at-
rophy of the hippocampus, as shown by using a VBM ROI
analysis (Owen etal., 2011). In a dataset from 80 healthy
volunteers, increases in the character trait of self‐transcen-
dence have been associated with an increased volume of the
middle temporal gyrus, as well as the inferior parietal gyrus
(Van Schuerbeek etal., 2011). Similarly, data from a study
with 42 healthy older adults showed that higher scores on
the personality trait of self‐transcendence were associated
with a reduced volume of the left fronto‐temporal and pa-
rieto‐temporal cortex (Kaasinen, Maguire, Kurki, Bruck, &
Together these findings suggest that temporal lobe re-
gions may be specifically involved in the experiential aspects
of religiosity, such as mystical experiences and feelings of
self‐transcendence (Grill‐Spector & Malach, 2004). Thus, in
the present study we tested whether items specifically per-
taining to the experiential aspects of religion (i.e., mystical
experiences that are typically characterized by a loss of sense
of space and time) are related to a reduced volume of tem-
poral brain regions, most notably the hippocampus (Owen
etal., 2011) and the right middle temporal gyrus (Chan etal.,
Thirdly, we tested whether an increased or decreased
volume of gray matter in the bilateral SPL and inferior pa-
rietal lobes (IPL) is associated with a stronger religiosity
and a higher proneness to having had a mystical‐like expe-
rience. This hypothesis partly follows from the initial work
by Newberg by using functional neuroimaging data to es-
tablish the neural correlates of peak meditative experiences
(Newberg, Alavi etal., 2001; Newberg & Iversen, 2003). He
found that peak experiences of absolute unity are associated
with a reduced blood flow to the superior parietal lobes and
an increased activation of prefrontal areas, which he inter-
preted as being associated with a stronger focused attention.
Other studies have used neuropsychological assessment
techniques as an indirect proxy for superior parietal lobe
functioning to establish a relationship between parietal lobe
atrophy and religiosity (Johnstone & Glass, 2008; Johnstone
etal., 2012, 2014; Urgesi etal., 2010). These studies indi-
cate that a reduced activation or an impaired functioning of
the parietal lobes (including the bilateral SPL and the IPL) is
associated with a higher sensitivity for having spiritual expe-
riences and increased religiosity. The supposed underlying
mechanism is that the parietal lobes support a process of
multi‐sensory integration and are at the basis of bodily self‐
awareness (Blanke, 2012). A disruption of this process could
result in changes in self‐awareness, for example, as observed
during self‐transcendent and out‐of‐body experiences, as
has been frequently observed in the neuropsychological lit-
erature (Blanke, Slater, & Serino, 2015). Only a few neuro-
anatomical studies have been conducted on the relationship
between parietal lobe volume and mystical experience.
Damage to the inferior parietal cortex has been associated
with an increase in the personality trait of self‐transcen-
dence in a group of 48 patients undergoing neurosurgery
(Urgesi etal., 2010). This finding fits well with other studies
on “religion‐by‐proxy” phenomena, such as the feeling of a
presence, that have also been associated with damage to the
inferior parietal lobe (for review, see: Blanke etal., 2015).
On the other hand, several studies also indicate that an
increased volume of the parietal lobes is positively associ-
ated with religion and spirituality. One study, using data from
103 participants, found that increased importance of religios-
ity was associated with an increased volume of the left and
right parietal cortices as well as the left precuneus (Miller
etal., 2014). A different study showed that an increased IPL
volume was associated with higher ratings of spirituality in
a sample of 80 healthy participants (Van Schuerbeek etal.,
2011). Also, doubting God's existence has been associated
with a reduced volume of the right precuneus (Kapogiannis,
Barbey, Su, Krueger etal., 2009)—although the sample size
of this study was small. Thus, the relation between pari-
etal lobe volume and religiosity and mystical experience is
mixed. Therefore, we tested a direction‐unspecific hypothe-
sis, by testing the relation between religious beliefs and mys-
tical experiences in relation to either an increase or a decrease
volume of the inferior parietal lobe.
We note that our theoretical predictions were quite ge-
neric and that the directionality of the expected effects is
open to discussion. Still, we argue that—if there is any value
in the neurocognitive mechanisms outlined above—this
should have become visible in the present analysis, which
could also serve to make more fine‐grained predictions for
future studies. We are well aware that by relating religiosity
to differences in gray matter volume, we somehow regress
to the highly controversial phrenology approach (Jones,
Alfaro‐Almagro, & Jbabdi, 2018). Rather than focusing
on structural brain differences, it might make more sense
to use network measures of brain activity and interaction
between different brain regions, such as functional connec-
tivity (Van Den Heuvel & Pol, 2010). We are very much in
favor of using these techniques in association with religion
and spirituality measures—and we definitely intend to use
them in future studies. But our primary aim here was to
establish the (absence of the) relation between religiosity
and structural brain differences at a level of methodological
and statistical rigor that we hope will set a new standard for
van ELK and SnOEK
Thus, the specific hypotheses that we set out to test were
the following: (a) a stronger acceptance of general religious
beliefs is associated with a reduced volume of the bilateral
orbitofrontal cortex; (b) a higher prevalence of mystical ex-
periences is associated with a reduced volume of the right
middle temporal gyrus and the hippocampus; (c) a higher
prevalence of religious beliefs and mystical experiences is
associated with an altered volume of the bilateral IPL. To test
these predictions, we estimated gray matter volume through-
out the entire brain using VBM and subsequently run both
confirmatory ROI analyses of the relation between ROI‐av-
erage gray matter volume and religiosity and mystical ex-
periences as well as a whole‐brain analysis of the relation
between voxel‐wise gray matter volume and religiosity. The
VBM procedure we used includes standard processing steps
of the T1‐weighted scans, including bias‐correction, skull-
stripping, segregation of gray and white matter, non‐linear
normalization to standard MNI space, and a Jacobian mod-
ulation step to correct for local expansion (or contraction)
due to the non‐linear component of the spatial transforma-
tion (Douaud etal., 2007). The ROIs were defined using the
Harvard–Oxford (sub)cortical probabilistic atlas (Craddock,
James, Holtzheimer, Hu, & Mayberg, 2012; for more details
on the ROI definition, see the Methods section).
The reason for doing ROI analyses on prespecified regions
of interest was to obtain a high‐powered confirmatory test of
the hypotheses derived from the literature. Typically, more
restricted ROI analyses (relative to whole‐brain, voxel‐wise
analyses) increase the statistical power to detect a potential
effect (Cremers etal., 2017). Conducting confirmatory ROI
analyses also allowed us to use Bayesian statistics on ROI‐av-
erage gray matter volume estimates, which provides the op-
portunity to quantify the relative evidence for the presence or
absence of a relationship between religiosity and gray matter
volume, which is not possible in the context of whole‐brain
analyses because no standard software packages for VBM
analyses offer Bayesian statistical tests. The ROI analyses
focused on the following hypotheses which were primarily
derived from the structural brain imaging studies (i.e., rather
than the functional studies) discussed above: (a) a stronger
acceptance of general religious beliefs is associated with a
reduced volume of the orbitofrontal cortex; (b) a higher prev-
alence of mystical experiences is associated with a reduced
volume of the right middle temporal gyrus and the hippocam-
pus; (c) a higher prevalence of mystical experiences is associ-
ated with an altered volume of the inferior parietal lobe.
Next to conducting ROI analyses of prespecified brain re-
gions forwarded by the literature, we also conducted a whole‐
brain, voxel‐wise analysis. We believe this type of analysis is
warranted given the quite unspecific nature of our hypothe-
ses (e.g., next to the orbitofrontal lobe, other prefrontal areas
such as the DLPFC have also been implicated in religiosity).
An overview of the data collection and analysis procedure is
presented in Figure1. The data collection was already com-
pleted before the start of this project, and the structural MRI
data have been checked visually using established quality
metrics using the MRIQC tool (Esteban etal., 2017a; version
0.10.3) and preprocessed using FMRIPREP (Esteban etal.,
2017b; version 1.0.15). For the present project, we analyzed
the religiosity data to test the specific hypotheses by conduct-
ing an ROI and whole‐brain VBM analysis, focusing on the
relation with religiosity and with mystical experiences.
Participants were recruited at the University of Amsterdam
and consisted of students. In total 244 participants were
tested, but 33 participants could not be used for the final
analysis because of incomplete (MRI or behavioral) data
or scanner artifacts (dropout rate = 8.2%), yielding a total
sample size of N=211. The age range for participants was
FIGURE 1 Overview of data
acquisition and analysis strategy. Boxes
marked in gray had already been completed
prior to commencing this registered report.
Boxes marked in black represent the
analysis plan that was used for the present
van ELK and SnOEK
20–28 years (mean = 24.18, SD = 1.92). The sample for
this study consisted of 118 female participants and 93 male
participants. All participants provided written informed con-
sent before participating in the study and the experimental
procedure was approved by the local ethics committee at the
Psychology Department at the University of Amsterdam.
Outcome neutral criterion
As an outcome neutral criterion, we used the effect of (self‐
reported) gender on gray matter volume in a separate VBM
analysis. It is well established that there are structural differ-
ences in local and global gray matter structure between the
brains of men of women (Good etal., 2001; Smith, Chebrolu,
Wekstein, Schmitt, & Markesbery, 2007). Note that multi-
variate predictive analyses of the same VBM data have al-
ready shown that gender can be “decoded” from whole‐brain
patterns of gray matter volume (Snoek, Miletic, & Scholte,
2018). While this multivariate analysis is different than the
intended univariate analysis for this outcome neutral crite-
rion, we believe that it demonstrates the validity of the pro-
posed neutral criterion. By testing the main effect of gender
on gray matter volume (by using a whole‐brain, voxel‐wise
analysis on the same VBM data that was used for the re-
ligiosity analysis), we were thus able to show that our data
are suitable for the intended main analysis. We expected to
find widespread gender differences in gray matter volume
throughout the brain (see e.g., Takahashi, Ishii, Kakigi, &
In this project, we first conducted a set of ROI analyses based
on prespecified brain areas that have been implicated in reli-
gious beliefs and mystical experiences. Next, given the rather
broad and unspecific nature of the suggestions in the litera-
ture, we also conducted a whole‐brain analysis (of which the
results were corrected for multiple comparisons).
There are multiple ways in which a power analysis could
be conducted. Here, we based the estimated effect size on
the reported effects in neuroanatomical studies on religios-
ity and mystical experience (Cristofori etal., 2016; Hayward
etal., 2011; Owen etal., 2011; Van Schuerbeek etal., 2011).
Although these papers did not always provide sufficient de-
tail to obtain a standardized effect size, overall the reported
effects were small, that is, β‐values ranged from .12 to .22
(Hayward etal., 2011; Owen et al., 2011), and η2 ranged
from .01 to .07 (Cristofori etal., 2016; Zhong etal., 2017).
Assuming a small effect size for our analysis of r =.20, a
sample size of N=224 and an alpha‐level of p<.05, the
achieved power of our analysis was 1 − β = .92, meaning
that there was 92% chance of correctly rejecting the null hy-
pothesis that there was no relation between religiosity and
brain volume (note, however, that strictly speaking our in-
tended Bayesian analyses do not employ the null‐hypothesis
testing framework assumed by power analyses). This crite-
rion exceeds the critical threshold of at least 80% statistical
power (Cohen, 1992), and we note that our sample size far
exceeds that of most previous studies on this topic. Thereby,
we aimed to provide a more precise estimate of the effect size
regarding the relation between structural brain differences
Population imaging project
The data for this study were collected as part of the Population
Imaging of Psychology project (PIoP1), which was conducted
at the Spinoza Center for Neuroimaging at the University of
Amsterdam. The aim of the PIoP was to offer researchers the
opportunity to collect brain imaging data from a large sam-
ple of participants (intended N =250), in association with
their individual difference measure of interest. The data were
collected between May 2015 and April 2016. The MRI data
have been preprocessed by LS and have been used already
for a project to identify multivariate structural brain differ-
ences in association with gender (Snoek et al., 2018). The
behavioral data (i.e., religiosity questionnaires) have been ac-
quired by MvE but had not been subjected to any analysis so
far. Both authors have confirmed that the MRI data have not
been associated in any way to the behavioral data and that all
hypotheses and the processing pipeline were developed and
defined prior to data inspection.
Standard MRI measurements that were collected for each
participant included a structural T1‐weighted scan, task‐free
resting state fMRI (6 min), a diffusion‐weighted imaging
(DWI) scan, and different functional localizer scans that
were collected using gradient‐echo EPI sequences, including
the Gender Stroop Task, an emotional matching task (Hariri,
Bookheimer, & Mazziotta, 2000), a working memory task
(Pessoa, Gutierrez, Bandettini, & Ungerleider, 2002) and
the anticipation of negative emotional vs. neutral scenes
(Oosterwijk, 2017). In addition, for each participant back-
ground demographic variables were recorded (gender, age,
socio‐economic status), as well as the NEO‐FFI personality
questionnaire (Costa & MacCrae, 1992) and an intelligence
test (Raven's matrices; Raven, 2000). For the present study,
we included measures related to religiosity and mystical ex-
periences (for description, see below).
For this study, we selected 7 items to measure religiosity,
which were completed using a 5‐point Likert scale ranging
from 1= not at all to 5= very much (see Table1). Six out
of these seven questions were directly based on the items
that are used to measure religiosity in the world value survey
van ELK and SnOEK
(Freese, 2004): three items assessed people's religious be-
liefs (i.e., religiosity, belief in God, belief in afterlife), two
items assessed the importance of people's faith for their lives,
and two items assessed participants’ religious practices (i.e.,
prayer and church visit). Although these questions are not
part of a standardized and validated scale to measure religios-
ity, the face validity of the items is high (e.g., church visit and
prayer refer to easily identifiable behaviors) and the construct
validity can be further guaranteed based on other items that
were included. Next to the religiosity items, we also asked
whether participants considered themselves to be a member
of a church or a religious organization, and if so whether they
could indicate their religious denomination (open response).
In this way, we could establish whether participants who in-
dicate religious membership indeed scored higher on the re-
We also asked three questions about the religious beliefs
(religiosity) and practices (church visit and lifestyle) of the
participants’ parents. Previous studies have shown that one's
parents’ religiosity, specifically the extent to which they
show credibility enhancing displays of their beliefs (e.g.,
wearing religious clothing, going to religious meetings), is
a strong predictor of endorsing religious beliefs (Lanman &
Buhrmester, 2017; Maij, van Harreveld etal., 2017). As such,
determining one's parents’ religiosity provides a good way
to further establish the construct validity of our religiosity
scale. Thus, for the VBM analysis we used the seven religi-
osity questions as presented in Table1 as predictor variables.
In addition, we included 6 items to measure mystical‐like
experiences, which were completed using a 5‐point Likert
scale ranging from “1=not at all” to “5=very much” (see
Table2). These items were items related to mystical expe-
riences from the Tellegen absorption scale (Tellegen &
Atkinson, 1974) and items from the mysticism scale (Hood,
1975). In several studies, it has been found that one's scores
on these items are strongly predictive of self‐induced mys-
tical experiences (van Elk, 2015; Maij & van Elk, 2018;
Maij, van Elk, & Schjoedt, 2017), self‐transcendent feelings
of awe (van Elk, Karinen, Specker, Stamkou, & Baas, 2016)
and hearing the voice of God (Luhrmann, 2011; Luhrmann,
Nusbaum, & Thisted, 2013). Accordingly, for the VBM anal-
ysis of mystical experiences, we used the sumscore of the
six items in Table2 as predictor variables. Next to the ques-
tions that were included in the present analysis, we also asked
questions about the participants’ spirituality, paranormal be-
liefs, conspiracy beliefs, and their level of absorption.
It could well be that average ratings of religiosity and
mystical experiences are non‐normally distributed, as data
were mainly collected from secularized students. However,
we note that this is not an issue for the statistical assumptions
of the analyses on the VBM data, which are based on the gen-
eral linear model (GLM) that assumes normality of the mod-
el's residuals, but not normality of its predictors. Moreover,
given results from earlier studies (see for instance: van Elk,
Rutjens, van der Pligt, & Van Harreveld, 2016) and the fact
that this study's sample consistent of university students, rel-
atively few participants scored high on religiosity and mys-
tical experiences. However, while potential low variance in
the predictor‐of‐interest (i.e., religiosity and mystical expe-
riences) may reduce power (Poldrack, Mumford, & Nichols,
2011), this study's relatively large sample size compensates
for this statistical inefficiency.
VBM processing pipeline
The T1‐weighted scans with a voxel size of 1.0×1.0×1.0mm
were acquired using 3D fast field echo (TR: 8.1 ms, TE:
3.7 ms, flip angle: 8°, FOV: 240 × 188 mm, 220 slices).
The T1‐weighted anatomical scan was bias‐corrected, skull-
stripped and segmented using the FMRIPREP package (ver-
sion 1.0.0; Esteban etal., 2017b)—a Nipype (Gorgolewski
etal., 2011) based tool. Each T1 weighted volume was cor-
rected for bias field using N4BiasFieldCorrection (v2.1.0;
Tustison etal., 2010) and skullstripped using antsBrainEx-
traction.sh v2.1.0 (using the OASIS template). Three tissue
classes were extracted from T1w images using FSL FAST
(v5.0.9; Jenkinson, 2003). From here on, we followed the
TABLE 1 Items included to measure religiosity. All items were
completed by using a 5‐point scale ranging from 1=not at all to
To what extent do you consider yourself to be religious?
To what extent do you believe in God or a supernatural being?
To what extent do you believe in life after death?
My faith is important to me
My faith affects my thinking and practice in daily life
I pray daily
I visit a church or religious meeting on a weekly basis
TABLE 2 Items included to measure mystical experiences. All
items were completed by using a 5‐point scale ranging from 1=not at
all to 5=very much
I have had an experience which was both timeless and spaceless
I have had an experience in which something greater than myself
seemed to absorb me
I have had an experience in which I felt myself to be absorbed as
one with all things
I have had an experience, of which I was incapable of being ex-
pressed in words
I have had an experience in which I realized the oneness of myself
with all things
I think I really know what some people mean when they talk about
van ELK and SnOEK
“FSL‐VBM” protocol (Douaud et al., 2007) from the FSL
software package (version 5.0.9; Smith et al., 2004). The
gray matter maps were registered to the MNI 152 standard
space using non‐linear registration (Andersson, Jenkinson,
& Smith, 2007). The resulting images were averaged and
flipped along the x‐axis to create a left‐right symmetric,
study‐specific gray matter template. Second, all native gray
matter images were non‐linearly registered to this study‐spe-
cific template and “modulated” to correct for local expan-
sion (or contraction) due to the non‐linear component of the
spatial transformation. The modulated gray matter images
were then smoothed with an isotropic Gaussian kernel with
a sigma of 3mm.
We used a volume‐based approach rather than a surface‐
based approach, to preserve consistency with previous stud-
ies on this topic (Cristofori etal., 2016; Kapogiannis, Barbey,
Su, Krueger etal., 2009; Van Schuerbeek etal., 2011).
The ROI analyses focused on the following hypotheses: (a)
a stronger acceptance of general religious beliefs is associ-
ated with a reduced volume of the orbitofrontal cortex; (b) a
higher prevalence of mystical experiences is associated with
a reduced volume of the right middle temporal gyrus and the
hippocampus; (c) a higher prevalence of mystical experi-
ences and religiosity is associated with an altered volume of
the bilateral IPL (which we define as the combination of the
angular gyrus and the supramarginal gyrus). ROIs for these
brain areas were identified using the probabilistic Harvard–
Oxford (sub)cortical atlas (see Table3). To create a binary
mask, we thresholded the probabilistic ROIs at 0 (i.e., any
voxel with a non‐zero probability of belonging to that brain
area were included in the binary mask). For each participant,
we averaged the voxel‐wise gray matter volume estimates
within each ROI separately, which served as the dependent
measure for our ROI analyses.
For our ROI analyses, we used a Bayesian ANCOVA
model. We used a Bayesian ANCOVA instead of Bayesian
regression because the statistical program we used, JASP
(Marsman & Wagenmakers, 2017; version 0.9.2), does not
allow for categorical independent variables in their Bayesian
regression implementation, which prevents us from includ-
ing gender as independent (“nuisance”) variable. Next to
gender, we included age and intelligence (operationalized
as the sumscore on the Raven's matrices test) as “nuisance”
variables. The rationale for including these measures as
dummy variables in our analysis is to control for the poten-
tial confound that any religiosity effect might be driven by
other individual differences that are known to be associated
with religiosity: typically females are more religious than
males (Miller & Hoffmann, 1995); older participants tend
to be more religious (Argue, Johnson, & White, 1999); and
people scoring high on intelligence are on average less reli-
gious (Zuckerman, Silberman, & Hall, 2013).
As our main independent variables of interest, we included
our two religiosity measures of interest (i.e., religiosity and
mystical experiences). We reported the Bayes factors for the
model including the main independent variables of interest
compared to the null model containing the nuisance variables
(gender, level of education, intelligence, and age). We ran the
Bayesian ANCOVA analysis for each ROI separately.
For the whole‐brain analysis, we used a non‐parametric,
permutation‐based (frequentist) GLM (using 10,000 ran-
dom permutations) with threshold‐free cluster enhancement
(TFCE; Smith & Nichols, 2009) using FSL's “randomize”
tool. Using TFCE‐based statistics instead of regular cluster‐
based statistics allows us to draw inferences on the voxel‐
level, which affords more detailed conclusions of the location
of potential significant correlations with religiosity (Smith &
Nichols, 2009). The TFCE‐values were corrected for mul-
tiple comparisons using the maximum statistic approach in
which voxels were only be considered significant if the ob-
served TFCE test statistic falls within the highest or lowest
2.5th percentile of the distribution of the permuted maximum
statistic values (i.e., voxel‐wise α=.025).
Similar to the ROI analyses, we included gender, age and
intelligence as covariates in our whole‐brain analysis. For
this analysis, we specified two contrasts, one for each main
independent variable of interest, which represent tests of
whether regression coefficients differ from zero. Because the
literature reports both positive and negative correlations be-
tween religiosity measures and gray matter volume, we tested
the contrasts in both directions and adjust the significance
level accordingly (i.e., use an alpha of 0.025 instead of the
conventional 0.05; Chen etal., 2019). Thresholded (i.e., sig-
nificant) results were visualized using the MNI152 (2mm)
TABLE 3 Regions of interest for the ROI analysis to assess the
relation between religious beliefs and mystical experiences and gray
Religious beliefs ROIs
Sub‐regions (from Harvard‐
(1) Orbitofrontal cortex —
(3) Bilateral inferior parietal
Bilateral angular gyrus
Bilateral supramarginal gyrus
Mystical experiences ROIs
(1) Hippocampus Bilateral hippocampus
(2) Right middle temporal
Right anterior MTL
Right posterior MTL
(3) Bilateral inferior parietal
Bilateral angular gyrus
Bilateral supramarginal gyrus
van ELK and SnOEK
template with different colors indicating positive versus neg-
To include religiosity and mystical experiences as regres-
sors in our model, first for each scale we calculated the reli-
ability by using Cronbach's α. Next, the sumscores for each
scale were calculated, which were used as predictors in the
statistical model (from both the ROI analyses and whole‐
Data and code availability
Most data and all code for this study are deposited in publicly
available online repositories. All analysis code and code to re-
produce the figures of this manuscript are available from the
project's GitHub repository: https ://github.com/lukas snoek/
Relig iosit yVBM. This repository also contains a csv‐file with
the data to reproduce the ROI analyses (i.e., the ROI‐average
gray matter volume, nuisance variables and religious belief/
mystical experience variables). Unthresholded brain maps
from the whole‐brain analysis of both the outcome neutral test
and main analysis can be viewed and downloaded from this
project's Neurovault repository: https ://ident ifiers.org/neuro
vault.colle ction :5380. Lastly, the project was preregistered on
the open‐science framework (OSF) at https ://osf.io/qzkmh/ .
Below, we describe the results from both the outcome
neutral analyses and the main analyses. The unthresholded
brain maps from the whole‐brain analyses for both the out-
come neutral and main analyses can be found in this study's
neurovault repository and the data for the ROI analyses (i.e.,
the ROI‐average gray matter volume and covariates) can be
found in this study's GitHub repository (see Data and Code
Deviations from preregistration
Although we planned to use data from N=224 participants
in our analysis, in the end we were only able to include data
from N=211 participants. This was the result of participants
that were missing either MRI data or religiosity data.
For the final analysis, 211 participants (118 females) were
retained. The descriptive variables, including religiosity
and personality characteristics, are presented in Tables 4
and 5. Both the religiosity and the mystical experience
scale showed a good reliability, Cronbach's α=.880 and
α=.877, respectively. As can be seen in the correlation
table, religiosity was negatively correlated with intelli-
gence, and mystical experiences were positively correlated
TABLE 4 Descriptive statistics for the participants included in the VBM analysis (N=211)
Age Raven Religiosity Mystical A C E N O
Mean 24.18 24.47 1.725 2.475 43.93 43.27 44.47 30.79 41.64
Std. deviation 1.924 4.997 0.8093 1.139 5.012 6.900 5.257 7.527 6.072
Minimum 20.00 3.000 1.000 1.000 27.00 22.00 31.00 13.00 28.00
Maximum 28.00 35.00 5.000 5.000 56.00 59.00 56.00 58.00 58.00
Abbreviations: A, agreeableness; C, conscientiousness; E, extraversion; N, neuroticism; O, openness to experience (scores on the NFFI personality questionnaire).
TABLE 5 Correlations between the different variables included in this study
Age Raven Religiosity Mystical A C E N O
Raven −0.001 —
Religiosity 0.013 −0.141* —
Mystical −0.107 −0.032 0.232*** —
A −0.040 0.102 0.095 0.003 —
C 0.044 −0.071 0.086 0.107 0.198** —
E 0.059 0.012 0.042 −0.019 0.207** 0.121 —
N 0.070 −0.115 0.130 0.044 0.002 −0.209** −0.297*** —
O −0.022 −0.021 0.061 0.029 0.093 −0.176* −0.059 0.201** —
Abbreviations: A, agreeableness; C, conscientiousness; E, extraversion; N, neuroticism; O, openness to experience (scores on the NFFI personality questionnaire).
van ELK and SnOEK
to religiosity—although overall correlations were small. As
expected, participants who indicated to be a member of a
church scored higher on the religiosity scale (mean=3.38,
SE=0.30) than those who did not (mean=1.73, SE=0.05),
Females in our study were slightly older than males
(mean=24.53, SE= 0.16, and mean = 23.74, SE =0.21,
respectively), t(209) = 2.99, p=.003. There was no effect
of gender on religiosity, but females tended to score lower on
mystical experiences (mean= 2.21, SE =0.10) than males
(mean=2.81, SE=0.12), t(209)=−3.90, p<.001. No dif-
ferences were found between males and females on the NNFI
personality traits, t(209)<1.36, p>.174.
Outcome neutral results
For the outcome neutral test, we investigated the effect of
(self‐reported) gender on gray matter volume in a whole‐
brain non‐parametric voxel‐wise analysis using the rand-
omize function from the FSL software package. In Figure2,
we plot the significantly different voxels (two‐sided t test)
resulting from this analysis.
Our ROI analyses for religious belief were done on the bilat-
eral OFC and the bilateral IPL, while the ROI analyses for
mystical experience were done on the bilateral hippocampus,
right MTL and bilateral IPL (see Figure3).
The ROI analyses are based on average gray matter
volume within a particular ROI. We used the Bayesian
ANCOVA module in the statistical software package “JASP”
for our ROI analyses (Love etal., 2015; Morey & Rouder,
2015; Rouder, Morey, Speckman, & Province, 2012). In the
Bayesian ANCOVA analysis, we used the ROI‐average gray
matter volume as dependent variable, gender as fixed factor,
and intelligence, age, and religious belief or mystical expe-
rience as covariates. The variables gender, intelligence and
age were added to the “null model,” which we compared to
our “religious belief model,” in which we include the reli-
gious belief covariate or “mystical experience model,” in
which we include the mystical experience covariate.
For both the OFC and IPL, there was more evidence for the
null model than for the “religious belief” model, with Bayes
factors (BF10) of 0.357 (OFC) and 0.414 (IPL), suggesting
that the data under the null model is more plausible than
under the religious belief model.
Similar to the religious belief analyses, for all three ROIs
(IPL, rMTL and hippocampus) there was weak evidence for
the null model, with Bayes factors (BF10) of 0.283 (IPL),
0.357 (rMTL) and 0.328 (hippocampus), again suggesting
that the data under the null model is more plausible than
under the mystical experience model.
In addition to the ROI analyses of religious belief and mysti-
cal experience, we also conducted a whole‐brain voxel‐wise
FIGURE 2 Whole‐brain significant (ɑ=0.025) voxel‐wise t‐statistics of the effect of gender computed with a (non‐parametric) general
linear model on the threshold‐free cluster enhancement‐transformed and thresholded voxel‐based morphometry data. Red‐yellow voxels represent
a significantly higher local gray matter volume for male than for female participants, while blue voxels represent a significantly higher local
gray matter volume for female than for male participants. Unthresholded statistical brain maps (t‐values and 1−p maps) can be viewed at and
downloaded from https ://ident ifiers.org/neuro vault.colle ction :5380. [Colour figure can be viewed at wileyonlinelibrary.com]
FIGURE 3 Outline of region‐of‐interests (ROIs) used in this study (Hippoc., hippocampus; IPL, inferior parietal lobe; MTL,
mediotemporal lobe; OFC, orbitofrontal cortex). All ROIs were bilateral, except for the (right hemisphere) MTL. [Colour figure can be viewed at
van ELK and SnOEK
analysis with religious belief and mystical experience as co-
variates (with identical settings as the outcome neutral whole‐
brain analysis). We used a significance level of 0.025 as we
conducted a two‐sided test (i.e., we tested both for positive
and negative associations of our covariates of interest with the
VBM data; cf., Chen etal., 2019). As can be seen in Figure4,
no voxels were found to be significant after multiple com-
parison correction. Unthresholded whole‐brain maps can be
found in the neurovault repository belonging to this study.
In addition to the preregistered analyses, in an exploratory
analysis we found hippocampus gray matter volume was
positively associated with religious belief (after adjusting for
age, intelligence and gender), as indicated by a Bayes factor
(BF10) of 3.512 in favor of the model including religious be-
lief. Although this Bayes factor suggests a moderate amount
of evidence for the observed effect (Jeffreys, 1961), we stress
that the reader should interpret this effect with care as this
analysis was not preregistered. To aid the interpretation of
the strength of the effect, Figure5 shows a partial (frequen-
tist) regression plot, showing the effect of religiosity on hip-
pocampal gray matter volume after partialling out the effects
of age, intelligence and gender.
In this registered report, we investigated whether religios-
ity and mystical experiences were associated with struc-
tural brain differences in gray matter volume. By using an
FIGURE 4 Whole‐brain results of religious belief and mystical experience contrasts. After multiple comparison correct, no voxels showed
a significant difference from zero. Unthresholded statistical brain maps (t‐values and 1−p maps) can be viewed at and downloaded from https ://
ident ifiers.org/neuro vault.colle ction :5380
FIGURE 5 The regression line
describes the effect of religious belief
on hippocampal gray matter volume
after partialling out the effects of gender,
intelligence and age, indicating a Bayes
factor (BF10) of 3.512 in favor of the model
including religious belief. The partial
regression analysis was performed using the
statsmodels Python package. [Colour figure
can be viewed at wileyonlinelibrary.com]
van ELK and SnOEK
outcome neutral criterion, we were able to show the validity
of our experimental and analytical approach, by identify-
ing clear gender differences in gray matter volume between
men and women (Takahashi etal., 2011). However, we did
not observe structural brain differences in association with
self‐reported religiosity or mystical experiences, neither
using an ROI analysis, nor using a whole‐brain analysis.
Overall, we observed moderate evidence for the null model
according to which gray matter volume in the OFC, the
bilateral IPL, the rMTL and the hippocampus are best ex-
plained by gender, age and intelligence, rather than religi-
osity or mystical experiences.
These findings cast new light on the claim that religion
is hardwired in the brain. Many previous studies in the field
of the neuroscience of religion have suffered from method-
ological problems, such as the lack of experimental control,
problems with ecological validity and low statistical power
(Schjødt & van Elk, 2019). The current replication study
comprised a relatively large sample and we used well‐vali-
dated measures of religiosity and mysticism, thereby over-
coming the limitations of previous research. Based on a
thorough literature review, we also used an ROI‐based anal-
ysis, resulting in a relatively high statistical power. Still,
the outcomes were not promising: religiosity and mystical
experiences were not consistently related to gray matter
volume differences. We note that in our exploratory analy-
sis a positive correlation was found between hippocampal
gray matter volume and religiosity. This finding needs to
be interpreted with caution as it was not preregistered and
the correlation is also contrary to the effects that have been
observed in earlier studies, indicating that hippocampal at-
rophy was related to an increased religiosity, that is, a neg-
ative correlation between hippocampal gray matter volume
and religiosity (Chan etal., 2009; Owen etal., 2011). Still,
a future independent replication study could take this unex-
pected finding into account, by conducting a confirmatory
ROI analysis of this relationship.
The absence of a clear and consistent relation between
religiosity and structural brain differences may not appear
surprising in the light of the recent replication crisis that
has haunted psychology and neuroscience as well (Zwaan,
Etz, Lucas, & Donnellan, 2017). Previous replications at-
tempts have shown that correlations between structural
brain properties and behavior and personality measures in
general are notoriously difficult to replicate (Boekel etal.,
2015; Melonakos etal., 2011). The field of neuroscience is
plagued with many low‐powered studies and accordingly the
literature abounds with many false‐positive findings, result-
ing in an overall inconsistent and scattered pattern of results
(Button etal., 2013). Another problem related with identify-
ing the structural brain correlates of religiosity is that other
confounding factors tend to covary with religion, such as gen-
der, age, schizotypy but also mental and physical health (e.g.,
living a healthier lifestyle by adhering to one's religious pre-
scriptions; cf., Maltby, Garner, Lewis, & Day, 2000; Miller
& Hoffmann, 1995; Stavrova, Fetchenhauer, & Schlösser,
2013). These factors in turn also directly have an effect on
gray matter volume (Goodkind etal., 2015; Modinos etal.,
2010), thereby further obscuring an eventual effect.
On a more positive note, a promising alternative to study-
ing structural brain differences is the use of multivariate
pattern recognition (Calhoun, Lawrie, Mourao‐Miranda, &
Stephan, 2017) and network analysis techniques (Sporns,
2014). These methods provide an increased sensitivity, as-
suming that confounds are properly controlled for (Snoek,
Miletić, & Scholte, 2019), because they allow identify-
ing multidimensional spatially distributed representations,
which is beyond the reach of classic univariate approaches
(Jimura & Poldrack, 2012). Relatedly, as already outlined in
the Introduction, several functional neurocognitive mecha-
nisms have been proposed to underlie a general propensity
for religiosity and religious experiences, such as for instance
a reduced error monitoring mechanism (van Elk & Aleman,
2017). Putting these ideas to the test would require setting
up carefully designed functional neuroimaging studies. These
would need to do justice to both the requirement to study au-
thentic religious beliefs and practices, while also providing
sufficient experimental control (Schjødt & van Elk, 2019).
We note that we currently have two studies underway in
line with this approach: in one study, we assess the effects
of source credibility in believers vs. non‐believers (Schjoedt
etal., 2011), and while in the other, we assess the relationship
between neurocognitive conflict detection in a Stroop task
and religiosity (Hoogeveen, Snoek & van Elk, in prep.). An
alternative and complementary approach is to deconstruct re-
ligion in its constitutive components, such as rituals, morality
and belief in minimally counterintuitive concepts (McKay &
Whitehouse, 2015). Each of these topics could be related to
the extant literature in social and cognitive neuroscience.
In this study, we found no evidence that religiosity is as-
sociated with a reduced volume of the orbito‐frontal cortex
and changes in the structure of the bilateral inferior parietal
lobes. Neither did we find support for the notion that mys-
tical experiences are associated with a reduced volume of
the hippocampus, the right middle temporal gyrus or with
the inferior parietal lobes. A whole‐brain analysis further-
more indicated that no structural brain differences were
found in association with religiosity and mystical experi-
ences. The search for the neural correlates of religious be-
liefs and experiences should therefore probably shift focus
from studying structural brain differences, to a functional
and multivariate approach.
van ELK and SnOEK
This study was supported by a grant from the John Templeton
Foundation (grant # 60663).
CONFLICT OF INTEREST
The authors declare to have no conflict of interest.
MvE designed the study; MvE & LS wrote the RR; LS super-
vised data collection; LS analyzed the data with input from
DATA AVAILABILITY STATEMENT
All analysis code and code to reproduce the figures of this
manuscript are available from the project's GitHub reposi-
tory: https ://github.com/lukas snoek/ Relig iosit yVBM. This
repository also contains a csv‐file with the data to reproduce
the ROI analyses (i.e., the ROI‐average gray matter volume,
nuisance variables and religious belief/mystical experience
variables). Unthresholded brain maps from the whole‐brain
analysis of both the outcome neutral test and main analysis
can be viewed and downloaded from this project's Neurovault
repository: https ://ident ifiers.org/neuro vault.colle ction :5380.
The project was preregistered on the open‐science frame-
work (OSF) at https ://osf.io/qzkmh/ .
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How to cite this article: van Elk M, Snoek L. The
relationship between individual differences in gray
matter volume and religiosity and mystical
experiences: A preregistered voxel‐based
morphometry study. Eur J Neurosci. 2020;51:850–
865. https ://doi.org/10.1111/ejn.14563