Meditation leads to reduced default mode network activity beyond an active task

Abstract

Meditation has been associated with relatively reduced activity in the default mode network, a brain network implicated in self-related thinking and mind wandering. However, previous imaging studies have typically compared meditation to rest, despite other studies having reported differences in brain activation patterns between meditators and controls at rest. Moreover, rest is associated with a range of brain activation patterns across individuals that has only recently begun to be better characterized. Therefore, in this study we compared meditation to another active cognitive task, both to replicate the findings that meditation is associated with relatively reduced default mode network activity and to extend these findings by testing whether default mode activity was reduced during meditation, beyond the typical reductions observed during effortful tasks. In addition, prior studies had used small groups, whereas in the present study we tested these hypotheses in a larger group. The results indicated that meditation is associated with reduced activations in the default mode network, relative to an active task, for meditators as compared to controls. Regions of the default mode network showing a Group × Task interaction included the posterior cingulate/precuneus and anterior cingulate cortex. These findings replicate and extend prior work indicating that the suppression of default mode processing may represent a central neural process in long-term meditation, and they suggest that meditation leads to relatively reduced default mode processing beyond that observed during another active cognitive task.

Full text

Meditation leads to reduced default mode network activity
beyond an active task
Kathleen A. Garrison
1
&Thomas A. Zeffiro
2
&Dustin Scheinost
3
&R. Todd Constable
3
&
Judson A. Brewer
1,4
#Psychonomic Society, Inc. 2015
Abstract Meditation has been associated with relatively re-
duced activity in the default mode network, a brain network
implicated in self-related thinking and mind wandering. How-
ever, previous imaging studies have typically compared med-
itation to rest, despite other studies having reported differences
in brain activation patterns between meditators and controls at
rest. Moreover, rest is associated with a range of brain activa-
tion patterns across individuals that has only recently begun to
be better characterized. Therefore, in this study we compared
meditation to another active cognitive task, both to replicate
the findings that meditation is associated with relatively re-
duced default mode network activity and to extend these find-
ings by testing whether default mode activity was reduced
during meditation, beyond the typical reductions observed
during effortful tasks. In addition, prior studies had used small
groups, whereas in the present study we tested these hypoth-
eses in a larger group. The results indicated that meditation is
associated with reduced activations in the default mode net-
work, relative to an active task, for meditators as compared to
controls. Regions of the default mode network showing a
Group × Task interaction included the posterior cingulate/
precuneus and anterior cingulate cortex. These findings repli-
cate and extend prior work indicating that the suppression of
default mode processing may represent a central neural pro-
cess in long-term meditation, and they suggest that meditation
leads to relatively reduced default mode processing beyond
that observed during another active cognitive task.
Keywords Meditation .Default mode network .Mind
wandering .Self-related thinking
Meditation involves maintaining attention on immediate ex-
perience and away from distractions such as self-referential
thinking and mind wandering (Bishop et al., 2004). Consistent
with this idea, meditation has been associated with relatively
reduced activity in a network of brain regions implicated in
self-referential processing, known as the default mode net-
work (DMN), in experienced meditators relative to
nonmeditators (Brewer et al., 2011b). Likewise, mind wander-
ing has been associated with activity in the DMN (Mason
et al., 2007), and reduced DMN activity during meditation
has been associated with improved sustained attention outside
of the scanner (Pagnoni, 2012). These findings suggest a role
for reduced DMN processing during meditation.
Reduced DMN activity during meditation appears to be
consistent across different meditation practices. A recent
meta-analysis showed that DMN activity was consistently re-
duced during meditation, relative to control conditions, across
neuroimaging studies of meditation that involved either fo-
cused attention or the repetition of phrases (Tomasino,
Fregona, Skrap, & Fabbro, 2012). The same study by our
research group revealed that DMN activity was reduced in
meditators as compared to controls across three standard
mindfulness meditations: focused concentration, loving
Electronic supplementary material The online version of this article
(doi:10.3758/s13415-015-0358-3) contains supplementary material,
which is available to authorized users.
*Judson A. Brewer
judson.brewer@umassmed.edu
1
Department of Psychiatry, Yale School of Medicine, New Haven, CT,
USA
2
Neurometrika, Potomac, MD, USA
3
Department of DiagnosticRadiology, Yale School of Medicine, New
Haven, CT, USA
4
Department of Medicine, University of Massachusetts Medical
School, 55 Lake Avenue North, Worcester, MA 01655, USA
Cogn Affect Behav Neurosci
DOI 10.3758/s13415-015-0358-3

kindness, and choiceless awareness (Brewer et al., 2011b).
Determining that some neural mechanisms are common
across meditation practices may inform the generalizability
and potential clinical applications of these techniques.
The DMN has been found to be most highly active when
individuals are left to think to themselves undisturbed or dur-
ing tasks involving self-related processing, and less active
during tasks requiring cognitive effort (Buckner, Andrews-
Hanna, & Schacter, 2008; Raichle et al., 2001). This network
is composed of a midline core, including the anterior medial
prefrontal cortex and posterior cingulate cortex/precuneus; a
dorsal medial prefrontal cortex subsystem including the tem-
poral pole, lateral temporal cortex, and temporoparietal junc-
tion; and a medial temporal lobe subsystem including the ven-
tral medial prefrontal cortex, posterior inferior parietal lobule,
retrosplenial cortex, parahippocampal complex, and hippo-
campal formation (Andrews-Hanna, Reidler, Sepulcre,
Poulin, & Buckner, 2010). Several of these brain regions,
including the angular gyrus, middle temporal gyrus, and
precuneus (Tomasino et al., 2012), have been shown across
neuroimaging studies to have relatively reduced activity dur-
ing meditation relative to control conditions, suggesting
that increased cognitive effort and decreased self-related
thinking are associated with meditation. In our prior
study meditators showed lower activity during medita-
tion than during rest in the posterior cingulate cortex
and precuneus, relative to controls (Brewer et al.,
2011b). Therefore, in the present study we aimed to
replicate this finding with a larger sample, given that
most neuroimaging studies of meditation—in particular,
those involving experienced meditators—have used
small groups (mean = 11.7, range = 4–31; Tomasino
et al., 2012).
Previous studies have also reported that meditators, rel-
ative to controls, show differences in DMN activity not
only during meditation, but also in functional connectivity
at rest (Brewer et al., 2011b; Jang et al., 2011). These
findings introduce a potential confound to studies of med-
itators that compare meditation to rest, because meditation
may transform the resting state into a more meditative
state. The choice of a control condition is a critical prob-
lem in cognitive neuroimaging studies and is fundamental
for interpreting changes in brain activation patterns
(Gusnard & Raichle, 2001;Marxetal.,2004). The resting
brain state is expected to be highly variable across indi-
viduals, and therefore may be a poorer choice for compar-
ison. To mitigate this confound, some studies have found
it useful to compare meditation to active control tasks,
such as mental arithmetic (e.g., Hölzel et al., 2007).
Therefore, in this study we aimed to compare meditation
to another active cognitive task, in order to test the hy-
pothesis that meditation leads to reduced activity in the
DMN beyond that found in another active cognitive task.
Method
Participants
All participants provided written informed consent in accor-
dance with the Human Investigations Committee of the Yale
School of Medicine. A total of 20 experienced meditators and
26 nonmeditators (controls) took part in the study. Of these
participants, six meditators and three controls had participated
in our previous study (Brewer et al., 2011b). All results re-
ported here showed similar effects if the analyses were re-
stricted to the new participants only. The meditators were re-
cruited by advertisements and word of mouth and were all
from the Insight meditation (Theravada) tradition. They re-
ported a mean of 9,676 ± 1,586 practice hours over 14 ± 2
years, including daily practice and retreats. Controls reported
no prior meditation experience. The groups were matched on
sex, race, age, and years of education (Table 1).
fMRI protocol
Just before scanning, participants were instructed in three
standard mindfulness meditation practices (as in previous
studies: Brewer et al., 2011b; Gunaratana, 2002).
(a) Concentration:BPlease pay attention to the physical sen-
sation of the breath wherever you feel it most strongly in
the body. Follow the natural and spontaneous movement
of the breath, not trying to change it in any way. Just pay
attention to it. If you find that your attention has wan-
dered to something else, gently but firmly bring it back to
the physical sensation of the breath.^
(b) Loving kindness:BPlease think of a time when you gen-
uinely wished someone well (pause). Using this feeling
as a focus, silently wish all beings well, by repeating a
few short phrases of your choosing over and over. For
example: May all beings be happy, may all beings be
healthy, may all beings be safe from harm.^
(c) Choiceless awareness:BPlease pay attention to whatever
comes into your awareness, whether it is a thought, emo-
tion, or body sensation. Just follow it until something else
comes into your awareness, not trying to hold onto it or
change it in any way. When something else comes into
your awareness, just pay attention to it until the next
thing comes along.^
Participants practiced each meditation condition outside of
the scanner prior to fMRI and confirmed that they understood
and could follow the instructions.
Each run began with a 30-s eyes-open rest period, during
which participants were instructed to look at the fixation cross
and not think of anything in particular. This was followed by
an 8-s display of the instructions for the active cognitive task
Cogn Affect Behav Neurosci

and by the 90-s active cognitive task itself. For the active task,
participants were asked to make judgments about adjectives in
response to a cue indicating that they should judge the word in
terms of Bself^(BDoes the word describe you?^)orBcase^
(BIs the word in uppercase letters?^) and to indicate Byes^or
Bno^using a button box (Kelley et al., 2002). Adjectives were
presented using E-Prime 1.2 (www.pstnet.com/eprime.cfm)for
2.5 s, with a 1- to 3-s interstimulus fixation interval for 30 trials
per run, for a total of 180 trials. A total of 60 unique adjectives
were drawn from the Anderson (1968) word list and were
counterbalanced for valence. Participants practiced the active
task to proficiency outside of the scanner prior to scanning. The
active task was followed by a 30-s eyes-closed rest period. The
eyes-closed condition was followed by a 30-s recorded medi-
tation instruction (as above) and by a 180-s meditation period.
At the end of the meditation period, subjects heard an audio
prompt to open their eyes and rest until the sound of the scan-
ner stopped, for an additional 20-s eyes-open rest period. Each
meditation condition was performed twice, for a total of six
runs. Meditation conditions were randomized, but the second
instance of each meditation was blocked (i.e., AABBCC). Af-
ter each run, participants were asked to rate how well they were
able to follow the instructions and how much their mind wan-
dered during meditation, on a scale from 0 to 10.
fMRI imaging parameters
Scanning was conducted using a Siemens 1.5-T Sonata MRI
(Siemens AG, Erlangen, Germany) with an eight-channel re-
ceive-only head coil. High-resolution T1-weighted 3-D ana-
tomical images were acquired using a magnetization-prepared
rapid gradient echo (MPRAGE) sequence (TR = 2,530 ms, TE
= 3.34 ms, field of view = 220 mm, matrix size = 192 × 192,
slice thickness = 1.2 mm, flip angle = 8°, 160 slices). Low-
resolution T1-weighted anatomical images were also acquired
(TR = 500 ms, TE = 11 ms, field of view = 220 mm, slice
thickness = 4 mm, gap = 1 mm, 25 AC–PC-aligned axial–
oblique slices). Functional image acquisition began at the
same slice location as in the T1 scan. Functional images were
acquired using a T2*-weighted gradient-recalled single-shot
echo-planar sequence (TR = 2,000 ms, TE = 35 ms, flip angle
= 90°, bandwidth = 1446 Hz/pixel, matrix size = 64× 64, field
of view = 220 mm, voxel size = 3.5 mm, interleaved, 210
volumes; two volumes were acquired at the beginning of the
run and discarded).
fMRI data preprocessing
Images were preprocessed using SPM8 (www.fil.ion.ucl.ac.
uk/spm). The functional images were realigned for motion
correction, and the resultant parameters were used as
regressors of no interest in the fMRI model. In addition,
Artifact Detection Tools (ART; www.nitrc.org/projects/
artifact_detect) was used to identify global mean intensity
and motion outliers in the fMRI time series (outlier
thresholds: global signal > 3 standard deviations, motion > 1
mm). Any detected outliers were included as regressors of no
interest in the model. A generative model of tissue
classification, bias correction, and segmentation (Ashburner
& Friston, 2005) was used to estimate the spatial normaliza-
tion parameters to Montreal Neurological Institute (MNI)
space. The estimates were then applied to all structural and
functional images, and all images were smoothed using a 6-
mm full-width-at-half-maximum Gaussian kernel.
Although motion outliers were modeled as regressors of no
interest using ART, nonequivalent motion correction might
result in bias when modeling group differences. Therefore,
the mean outliers detected by ART across six runs were com-
pared between groups using an independent ttest. No signif-
icant difference in mean outliers was found between medita-
tors and controls (meditators = 45, SEM = 6.3; controls = 38,
SEM =5.8),t(44) = 0.79, p= .43. Outliers were detected in all
controls and in all but one meditator. Motion outliers in the
first and last runs (Runs 1 and 6) were compared between the
groups using a repeated measures analysis of variance. A sig-
nificant effect of time was found (F=4.34,p= .04), but no
Tabl e 1 Participant demographics
Meditators (n= 20) Controls (n=26) χ
2
p
n%n%
Sex 0.03 .85
Male 11 55 15 55
Female 9 45 11 45
Race n/a n/a
White (Non-Hispanic) 20 100 26 100
Mean SD Mean SD t p
Age 45.6 11.1 42.2 13.3 –0.92 .36
Years of education 17.6 4.8 17.2 3.0 –0.36 .72
Cogn Affect Behav Neurosci

significant Group × Time interaction (F=0.01,p= .91), such
that the mean motion outliers increased from Runs 1 to 6
comparably in meditators (Run 1 = 5.1, Run 6 = 7.8) and
controls (Run 1 = 5.9, Run 6 = 8.3).
fMRI data analysis
The blood oxygen level-dependent (BOLD) signal was
modeled using separate regressors for the conditions: active
task instructions, active task, meditation instructions, and
meditation task. Rest periods were combined to form the im-
plicit baseline. The meditation task included the three distinct
meditation practices collapsed as blocks for the analysis. The
active task included Bself,^Bcase,^and fixation trials col-
lapsed as blocks for the analysis. The conditions were
modeled using a boxcar function convolved with a canonical
hemodynamic response function, and the regressors were fit
using SPM8’s implementation of the general linear model. To
accommodate the long mediation conditions, the high-pass
filter cutoff was 360 s. A first-level model was specified to
estimate the parameter for each condition for each subject. A
second-level model was specified to estimate the parameter
for the main effects of task (meditation, active task) and group
(meditation, control), and the interaction effect. A two-
by-two interaction effect was tested using a repeated
measures analysis of variance for groups (meditators,
controls) by tasks (meditation, active task) and was ex-
clusively masked with the group effect (meditation vs.
control), in order to show the voxels in which the in-
teraction was not driven by the main effect of group.
All findings were significant at p≤.05 family-wise
error (FWE) cluster-corrected, using a p≤.01 cluster-
forming threshold and an extent threshold of 250
voxels, unless a more conservative threshold was
indicated.
Statistics
The statistical analysis was conducted using SPSS 19 (http://
www-01.ibm.com/software/analytic). For participant
demographics, paired ttestswereusedtodetermine
differences between the groups in age, and χ
2
tests were
used to determine differences between the groups in sex.
Repeated measures analyses of variance were used to
determine differences between the groups in self-reported
mind wandering. For the active task, independent ttests were
used to compare reaction times between the groups, and χ
2
tests were used to compare error rates between the groups,
with an error defined as an incorrect response to Bcase^or
no response to Bself.^All statistical tests were two-tailed and
are reported as means ± standard deviations.
Results
Behavioral results
In line with the assumption that meditators and controls per-
formed the active task similarly, no significant difference in
reaction times was found between meditators (1.25 ± 0.38 s)
and controls (1.26 ± 0.42 s), t=1.46,p= .15. Meditators made
significantly fewer errors in the Bcase^condition (1.7%) than
did controls (3.5%), χ
2
=13.2,p< .001, whereas no signifi-
cant difference was found in errors in the Bself^condition
between groups (meditators = 1.7%, controls = 1.3%), χ
2
=
1.1, p=.31.
As expected, meditators reported less mind wandering dur-
ing meditation than did controls, F(1, 44) = 7.57, p=.009.
This finding was apparent for concentration (controls, 4.5 ±
2.1; meditators, 3.5 ± 1.4), loving kindness (controls, 3.8 ±
1.8; meditators, 2.8 ± 1.4), and choicelessawareness (controls,
4.4 ± 2.3; meditators, 2.7 ± 1.6) meditation. Both meditators
and controls reported being able to follow the instructions to a
high degree for concentration (controls, 8.6 ± 1.4; meditators,
8.5 ± 1.4), loving kindness (controls, 8.6 ± 1.4; meditators, 8.8
± 1.2), and choiceless awareness (controls, 9.0 ± 1.4; medita-
tors, 8.9 ± 0.9) meditation. No effect of time was found on
mind wandering (meditators: Run 1, 3.0 ± 1.6; Run 6, 2.9 ±
2.0; controls: Run 1, 4.1 ± 2.0; Run 6, 4.3 ± 2.5), F(1, 44) =
0.003, p= .96, and likewise no Group × Time interaction was
found for mind wandering, F(1, 44) = 0.19, p= .67. Similarly,
no effect of time was found on the ability to follow instruc-
tions (meditators: Run 1, 8.7 ± 1.3; Run 6, 8.9 ± 1.4; controls:
Run 1, 8.6 ± 1.2; Run 6, 8.7 ± 1.6), F(1, 44) = 1.14, p=.29,
nor was a Group × Time interaction found for the ability to
follow instructions, F(1, 44) = 0.57, p=.45.
fMRI results
For meditators and controls combined, meditation was asso-
ciated with activity increases in the bilateral rectal gyrus and
orbitofrontal cortex, relative to the implicit baseline (Fig. 1top
left, Table 2). The same brain regions showed an activity de-
crease during the active task relative to the implicit baseline in
meditators and controls combined (Fig. 1bottom right,
Tab le 2).
A between-group difference was found for meditation in
comparison to the implicit baseline. Relative to controls, med-
itators showed reduced activity in the anterior cingulate cortex
and the dorsal and ventral precuneus/posterior cingulate cor-
tex during meditation, as compared to the implicit baseline
(Fig. 2, supplementary Fig. S1).
A significant Group (meditators, controls) × Task (medita-
tion, active task) interaction, exclusively masked by the effects
of group, was identified in the middle temporal gyrus, fusi-
form and hippocampal gyri, anterior cingulate cortex, and
Cogn Affect Behav Neurosci

precuneus (Fig. 3, Table 3). Plots of the parameter estimates
for the anterior cingulate cortex and precuneus demonstrated
that activity in these brain regions decreased during medita-
tion and increased during the active control task in meditators,
whereas controls did not show this dissociation (Fig. 3,
insets).
Discussion
In this study, meditation was found to be associated with rel-
atively lower activity in regions of the DMN in meditators
than in controls, as compared to during another active cogni-
tive task, indicated by a significant Group × Task interaction.
Fig. 1 Effects of task in the combined meditator and control groups.
Meditation, as compared to the implicit baseline, is associated with
activity increases bilaterally in the orbitofrontal cortex (top left). The
same areas show an activity decrease during the active task, as
compared to the implicit baseline (bottom right). Images are displayed
in neurological convention, with critical thresholds at p< .001,
uncorrected for multiple tests, to show the subthreshold extents of the
effects.
Tabl e 2 Brain region peaks showing increased activity with meditation
as compared to the implicit baseline in both meditators and controls
Side Label Peak p(FWE-corr) Peak Zx y z
L Rectal gyrus .00024 7.52 –10 14 –18
R Rectal gyrus .00024 7.08 –14 28 –22
L Orbitofrontal cortex .011 6.80 –12 26 –22
R Rectal gyrus .00020 6.29 6 26 –20
R Orbitofrontal cortex .0055 6.28 16 16 –18
L Orbitofrontal cortex .022 6.09 –22 20 –20
All peaks are significant at p< .05, FWE-corrected.
Cogn Affect Behav Neurosci

Brain regions showing relatively reduced activity during med-
itation in meditators included the anterior cingulate cortex,
fusiform gyrus, middle temporal gyrus, and precuneus. Med-
itators also showed relatively lower activity in DMN regions
than did controls during meditation as compared to rest.
As we described above, the DMN is typically active during
task-free resting states (Raichle et al., 2001), and this activity
is thought to represent neural processing related to self-related
thinking or mind wandering (Buckner et al., 2008). The DMN
is further characterized by decreased activity during effortful,
goal-directed tasks (Fox et al., 2005; Greicius, Krasnow,
Reiss, & Menon, 2003). A recent meta-analysis reported that
neuroimaging studies of meditation consistently report re-
duced DMN activity during meditation relative to control con-
ditions in both meditators and nonmeditator controls
(Tomasino et al., 2012). Although the meta-analysis did not
find a difference in DMN activity associated with long-term
experience, our prior study did show reduced activity in re-
gions of the DMN during meditation relative to rest in expe-
rienced meditators compared with nonmeditators (Brewer
et al., 2011b). This study replicated the results of that
previous study in a larger sample (meditators, 20 vs. 12;
controls, 26 vs. 12).
However, functional connectivity in regions of the DMN, a
measure of the temporal correlation of the BOLD signal be-
tween these regions, has also been found to differ between
meditators and controls, not only during meditation but also
at rest (Brewer et al., 2011b; Pagnoni, 2012; Taylor et al.,
2013). This suggests that meditation training may alter the
behavioral state that individuals enter when given the standard
resting-state instructions. Meditators and controls appear to
differ in their resting-state DMN processing. Therefore, we
compared meditation to another active cognitive task. Other
studies have reported similar utility in comparing meditation
with an active task (e.g., Hölzel et al., 2007; Tomasino et al.,
2012). The present findings add to this work by providing
evidence that meditation is associated with relatively reduced
DMN activity during meditation as compared to a judgment-
Fig. 2 A between-group contrast of meditation versus the implicit base-
line revealed effects in the anterior cingulate cortex (ACC) and the dorsal
(dPCu) and ventral precuneus (vPCu)/posterior cingulate cortex (M =
meditators, C = controls). All three clusters are significant at p<.05
FWE-corrected, p≤.01 cluster-forming threshold, and extent threshold
250 voxels. Images are displayed in neurological convention, with critical
thresholds at p< .01, uncorrected for multiple tests, to show the sub-
threshold extents of the effects.
Fig. 3 A Group × Task interaction exclusively masked with the main
effect of group revealed effects in the anterior cingulate cortex (ACC) and
the dorsal precuneus (PCu) across groups and task conditions. Both
clusters are significant at p< .05, FWE-corrected. Images are
displayed in neurological convention, with critical thresholds of p<
.01, uncorrected for multiple tests, to show the subthreshold extents of
the effects. MM, meditators meditating; MA, meditators performing
the active task; CM, controls meditating; CA, controls performing the
active task.
Cogn Affect Behav Neurosci

of-adjectives task in meditators versus controls. This finding
suggests that meditation by experienced meditators leads to
relatively reduced activity in the DMN, beyond that expected
by general task-based deactivation.
Consistent with other prior findings (Kelley et al., 2002),
our controls showed a pattern of reduced precuneus/posterior
cingulate cortex activity during both the judgment-of-
adjectives task and the meditation task (see the parameter
estimate plots in the Figs. 2and 3insets). It is possible that
for controls, reduced activity in this hub of the DMN during
meditation and the active task reflects reduced self-related
processing and mind wandering during these tasks in compar-
ison with the implicit baseline, which was composed of rest-
ing periods. In support of this, task engagement has been
shown to reduce activity in the precuneus/posterior cingulate
cortex relative to rest (Fox et al., 2005). Other studies have
reported a high incidence of mind wandering in healthy indi-
viduals (Killingsworth & Gilbert, 2010; Whitfield-Gabrieli
et al., 2011) and a high incidence of precuneus/posterior cin-
gulate cortex activity associated with mind wandering
(Pagnoni, 2012). In contrast, meditators showed increased ac-
tivity in the precuneus during the judgment-of-adjectives task
(Fig. 2), possibly reflecting increased self-related processing
relative to the implicit baseline. This interpretation would be
consistent with our prior finding that meditators showed al-
tered DMN functional connectivity at rest as compared to
nonmeditators (Brewer et al., 2011b). Related to this, we used
real-time fMRI neurofeedback, in which individuals were pro-
vided with dynamic visual feedback about their ongoing brain
activity in real time, to demonstrate that the changes in activity
in the posterior cingulate cortex corresponded to experienced
meditators’subjective reports of focused attention and mind
wandering (Garrison et al., 2013a;Garrisonetal.,2013b). The
present findings further suggest that long-term meditation ex-
perience may lead to changes in DMN activity beyond typical
task-engagement-related reductions, because meditators
showed reduced DMN activity during meditation not only as
compared to rest, but also as compared to another active cog-
nitive task. For meditators, this is consistent with the hypoth-
esis that meditation may reduce self-related thinking and mind
wandering more than does another active task.
This study has several limitations. The use of a mixed de-
sign and the comparison of task blocks of different lengths
may have reduced the design’s efficiency. Comparing blocks
of different lengths can lead to poorer estimates of the shape of
the hemodynamic response to a given stimulus block (Wager,
Vazquez, Hernandez, & Noll, 2005). Block length was deter-
mined in consideration of both the task requirements and scan
time limitations. To improve statistical power, the event-
related active task (judgment of adjectives) was analyzed as
a block. This might have combined events that increased (e.g.,
Bself^) and decreased (e.g., Bcase^) DMN processing, thereby
reducing power to detect DMN changes during this active task
relative to meditation. Likewise, the meditation conditions
(concentration, loving kindness, and choiceless awareness)
were collapsed to improve power. This design could be opti-
mized to directly compare the components of the active task
and the different meditation practices in a future study. A
Tabl e 3 Brain regions identified by a Group (meditators, controls) × Task (meditation, active task) interaction
Side Label Cluster p(FWE-corr.) Cluster kPeak Z xyz
R Middle temporal gyrus .007 481 4.60 66 –18 –8
3.90 58 –4–10
3.25 50 –20 –10
L Middle temporal gyrus 3.228E–05 999 4.36 –48 –30 –16
4.22 –60 –28 –10
3.86 –48 –18 –22
L Fusiform and hippocampal gyri .005 505 4.29 –20 –50 –10
3.62 –26 –60 –10
3.38 –38 –52 –20
R Anterior cingulate cortex .01 458 4.09 12 44 12
3.94 10 40 26
3.51 6 44 36
R Middle temporal gyrus .0002 783 4.09 46 –56 20
3.59 56 –36 18
3.56 42 –40 20
L Precuneus .0369 350 3.63 –2–48 46
3.48 –14 –44 52
3.13 –18 –36 40
Cluster-forming threshold p< .005; extent threshold 250. All clusters are significant at p< .05, FWE-corrected.
Cogn Affect Behav Neurosci

related limitation was that the meditation and active tasks were
not counterbalanced; the active task always preceded the med-
itation task. Although the fixed order was used to avoid spe-
cific effects of state-based meditation on brain activity patterns
during the active task, this approach did not account for po-
tential trait-based effects. Finally, interpretation of our results
is limited to meditation in the research setting. Traditional or
cultural meditation practices typically involve contextual
components, such as intentions for practice, background con-
ceptual beliefs, and the support of a community, among
others. In the present study, meditation was performed in an
fMRI scanner, and thus decontextualized. Despite these draw-
backs, since the meditators were long-term practitioners with
significant commitments to practice, we cannot rule out that
larger components of the practice or memory of other contexts
were active even during the decontextualized meditation
tasks. Due to these empirical differences, further studies will
be necessary to interpret our findings within the broader field
of meditation research. Overall, despite the design limitations,
this study showed reliable group differences in DMN activity
across the different experimental conditions.
These findings provide evidence that reduced DMN process-
ing may represent a central neural process in long-term medita-
tion. This may have clinical implications. Previous work sug-
gested that increased DMN activity may interfere with cognitive
performance and that decreased DMN activity is associated with
improved performance (for a review, see Anticevic et al., 2012).
Likewise, increased DMN activity has been associated with de-
pression (Sheline et al., 2009), anxiety (Zhao et al., 2007), and
addiction(Garavanetal.,2000), among other disorders. Mind
wandering and self-related processing contribute to ruminative
thinking, which may be a feature of these disorders and has also
been associated with decreased well-being (e.g., Killingsworth &
Gilbert, 2010). In contrast, meditation, which appears to be asso-
ciated with reduced activity in the DMN, has been shown to
improve attention and working memory performance (Pagnoni,
2012) and promote positive health outcomes (Keng, Smoski, &
Robins, 2011). Because mindfulness training has shown utility
for addiction (Brewer et al., 2011a), as well as for pain, anxiety,
and depression (Goyal et al., 2014), these studies together sug-
gest that the neural mechanism by which meditation results in
clinical benefits may be through reducing DMN activity.
Author note This work was supported by awards from the National
Institutes of Health, National Institute on Drug Abuse (Grant No. K12-
DA00167 to J.A.B... and K.A.G.); from the US Veterans Affairs New
England Mental Illness Research, Education, and Clinical Center; and
from the American Heart Association (Grant No. 14CRP18200010 to
K.A.G.), and by private donations from Jeffrey C. Walker, Austin Hearst,
and the 1440 Foundation. We thank our participants for their time and
effort, Joseph Goldstein and Ginny Morgan for input on the meditation
instructions, Hedy Kober for input on the study design, Thomas Thornhill
IV for study coordination, and Hedy Sarofin and the staff of the Yale
Magnetic Resonance Research Center for help with scanning.
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