Stress reduction correlates with structural
changes in the amygdala
Britta K. Ho ¨lzel,1,2James Carmody,3Karleyton C. Evans,1Elizabeth A. Hoge,4Jeffery A. Dusek,5,6
Lucas Morgan,1Roger K. Pitman,1and Sara W. Lazar1
1Massachusetts General Hospital, Charlestown, MA 02129, USA,2Bender Institute of Neuroimaging, Justus-Liebig Universita ¨t Giessen,
35394 Giessen, Germany,3University of Massachusetts Medical School, Worcester, MA 01605,4Massachusetts General Hospital, Boston,
MA 02114 and5Abbott Northwestern Hospital, Penny George Institute for Health and Healing, Minneapolis, MN 55407, USA,
6Benson-Henry Institute for Mind Body Medicine at Massachusetts General Hospital, Boston, MA 02114, USA
Stress has significant adverse effects on health and is a risk factor for many illnesses. Neurobiological studies have implicated
the amygdala as a brain structure crucial in stress responses. Whereas hyperactive amygdala function is often observed during
stress conditions, cross-sectional reports of differences in gray matter structure have been less consistent. We conducted a
longitudinal MRI study to investigate the relationship between changes in perceived stress with changes in amygdala gray matter
density following a stress-reduction intervention. Stressed but otherwise healthy individuals (N¼26) participated in an 8-week
mindfulness-based stress reduction intervention. Perceived stress was rated on the perceived stress scale (PSS) and anatomical
MR images were acquired pre- and post-intervention. PSS change was used as the predictive regressor for changes in gray matter
density within the bilateral amygdalae. Following the intervention, participants reported significantly reduced perceived stress.
Reductions in perceived stress correlated positively with decreases in right basolateral amygdala gray matter density. Whereas
prior studies found gray matter modifications resulting from acquisition of abstract information, motor and language skills, this
study demonstrates that neuroplastic changes are associated with improvements in a psychological state variable.
Keywords: stress; amygdala; gray matter; MRI; mindfulness
Acute stress initiates hormonal and behavioral responses that
enable an organism to make adaptations to environmental
demands (Chrousos, 2000). The amygdala has been impli-
cated in both human and animal studies as playing a crucial
role during stress responses, including the detection of
stressful and threatening stimuli and the initiation of adap-
tive coping responses (LeDoux, 2000; Hasler et al., 2007).
Amygdala-dependent cognition is facilitated during stressful
conditions?a useful function for fear-related learning (Shors
and Mathew, 1998; Sapolsky, 2003). However, prolonged
exposure to stress increases the risk of being affected by a
number of mental and physical illnesses (Johnson et al.,
1992; Chrousos, 2000; Sapolsky, Romero, & Munck, 2000).
Aberrant amygdala function has been consistently demon-
strated across several stress-related psychopathologies. For
example, exaggerated amygdala activation has been found
in trait anxiety (Stein et al., 2007), post-traumatic stress dis-
order (PTSD; Rauch et al., 2000; Shin et al., 2004, 2005),
social phobia (Birbaumer et al., 1998; Evans et al., 2008;
Phan et al., 2006), depression (Drevets et al., 1992;
Abercrombie et al., 1998; Sheline et al., 2001; Siegle et al.,
2002; Dougherty et al., 2004) and impulsive aggression
(Coccaro et al., 2007).
Reports of differences in gray matter structure of the
amygdala in pathologic stress conditions have been less
consistent (Drevets et al., 2008). While some studies found
enlarged amygdala volumes in subjects with affective disor-
ders (Altshuler et al., 1998; Strakowski et al., 1999; Frodl
et al., 2002; Lange and Irle, 2004; Weniger et al., 2006),
others did not find altered volumes or reported volume
reductions (Sheline et al., 1998; Mervaala et al., 2000;
Frodl et al., 2003; Frodl et al., 2008). Amygdala findings
for patients suffering from PTSD and other anxiety disorders
have also been mixed (Gurvits et al., 1996; De Bellis et al.,
2000; Gilbertson et al., 2002; Massana et al., 2003; Siegle
et al., 2003; Wignall et al., 2004; Milham et al., 2005;
Karl et al., 2006; Atmaca et al., 2008; Woon and Hedges,
2008; Hayano et al., 2009). One study with healthy
individuals failed to find a correlation between chronic life
stress and gray matter volume in the amygdala (Gianaros
et al., 2007). These inconsistencies in the literature might
result from a number of factors that can impact gray
matter measures, such as gender (Wilke et al., 2007), genetics
Received 17 December 2008; Accepted 6 August 2009
This research was funded by the National Institutes of Health-NCCAM (R21-AT003425-01A2) and the British
Broadcasting Company (BBC). B.K.H. is supported by a Marie Curie International Outgoing Fellowship within
the 7th European Community Framework Programme. S.W.L. was supported by National Institutes of Health
funding K01AT00694. The funders had no role in study design, data collection and analysis, decision to
publisher preparation of the manuscript. We thank C. Legro and the Center for Mindfulness for conducting the
MBSR intervention, J. Bates, L. Shin and C. Linnman for critical reading of the manuscript; and S. Yerramsetti,
N. Olendzki, C. Congleton, D. McCaffrey and A. McCallister for technical support.
Correspondence should be addressed to Britta K. Ho ¨lzel, Massachusetts General Hospital, 149 13th Street,
Charlestown, MA 02129, USA. E-mail: firstname.lastname@example.org
doi:10.1093/scan/nsp034SCAN (2010) 5,11^17
? TheAuthor (2009).PublishedbyOxfordUniversityPress.For Permissions,pleaseemail:email@example.com
(Meyer-Lindenberg et al., 2006) and volumetry method
(Doty et al., 2008).
In contrast to studies of humans, the stress literature with
animals is more consistent. Several studies have shown that
prolonged stress exposure leads to increases in measures
of amygdala structure in rodents (Vyas et al., 2002, 2003;
Mitra et al., 2005). Increased dendritic length and increased
arborization were reported within the basolateral complex of
the amygdala and in the extended amygdala as a result of
exposure to chronic immobilization stress (Vyas et al., 2002,
2003). Differences between the results from the human and
animal studies might be due to methodological differences.
First, the human studies have often investigated amygdaloid
volume using MRI, while animal studies have used invasive
techniques to look at specific cellular changes within this
structure. Second, while most human studies have been
cross-sectional investigations of pathologic conditions, the
animal studies have been longitudinal, with presumably
healthy animals undergoing a controlled chronic stress
manipulation. While individual differences are difficult to
control and can confound findings in cross-sectional studies,
in longitudinal studies these variables remain constant,
allowing researchers to selectively vary the factor of interest.
However, to our knowledge, no longitudinal neuroimaging
studies have examined the influence of stress on amygdala
morphology in healthy human beings.
Here, we report a longitudinal MRI study in humans that
investigated the correlation between changes in perceived
stress and changes in amygdaloid gray matter density follow-
ing a stress-reduction intervention. Mindfulness-based stress
reduction (MBSR; Kabat-Zinn, 1990) is a popular 8-week
program developed to help individuals reduce their stress
levels and increase psychological well-being. Mindfulness is
defined as the non-judgmental awareness of present moment
experiences (Kabat-Zinn, 1990). Participants practise medi-
tation techniques designed to increase awareness of present
moment experiences such as thoughts, emotions and phys-
ical sensations. They also learn to use this awareness in
responding more skillfully to stress in their everyday lives.
Numerous studies have demonstrated the efficacy of this
program in reducing subjective reports of stress and increas-
ing well-being (e.g. Chang et al., 2004; Carmody and Baer,
2008). However, the underlying neural mechanisms of these
changes are largely unknown. Since the amygdala has been
repeatedly shown to be involved in, and responsive to, an
individual’s experience of stress, we hypothesized that
changes in perceived stress would be associated with changes
in amygdala gray matter density. Correlations within the
whole brain were also explored on an exploratory basis.
METHODS AND MATERIALS
Twenty-seven participants (41% males; mean age 35.2 years;
SD 6.7 years) who reported high levels of stress during the
previous month were enrolled in the study. Individuals
were eligible if their score on the perceived stress scale
(PSS; Cohen and Williamson, 1988) was ?1 SD above the
population mean. The PSS is a validated self-report
questionnaire widely used for assessing an individual’s self-
perception of stress. The PSS has 14-, 10- and 4-item
versions and has been shown to yield adequate reliability
and validity (Cohen et al., 1983; Cohen and Williamson,
1988). In this study, the 4-item version was used to screen
potential subjects while the 10-item version was used to
assess change in perceived stress before and after the train-
ing. Participants gave their responses on a 5-point Likert
scale, ranging from never (0) to very often (4). Inclusion
criteria was based on the population means according to
Cohen et al. (1983; Cohen and Williamson, 1988), namely
4.2 (SD 2.8) for females and 4.7 (SD 3.1) for males.
Further exclusion criteria were: current psychiatric illness
or medical illness, ineligibility for MRI scanning (claustro-
phobia, metallic implants, pregnancy, etc.), or significant
previous meditation or yoga experience. The protocol
was approved by the Massachusetts General Hospital
Institutional Review Board. Written informed consent was
obtained from all study participants and they were compen-
sated for completion of assessment procedures.
All participants completed the 8-week MBSR program,
consisting of weekly group meetings and daily home mind-
fulness practises, including sitting meditation and yoga.
The sample described here includes participants from two
similar studies that both assess the effect of MBSR on brain
structure. Sixteen participants received the standard MBSR
class held at the Center for Mindfulness at the University of
Massachusetts Medical School. Eleven subjects received a
shorter version of the MBSR course held at Massachusetts
General Hospital that consisted of only 12 contact hours
(versus the standard 23h) and 20 min daily homework prac-
tise (versus the standard 40 min). The intervention has been
comprehensively described elsewhere (Kabat-Zinn, 1990).
Classes took place between April 2005 and June 2008 and
were led by several instructors. One enrolled participant was
excluded from the data analyses due to non-adherence to
home practise requirements (<4h total of home practise).
Data from 26 healthy, right-handed individuals (44% males;
mean age 35.7 years, SD 6.3 years) were included in the
analyses. Home practise logs demonstrated that participants
reported an average of 19.77h (SD 6.53h) of prescribed out-
of-class mindfulness practise over the 8-week study period.
To test whether the amount of practise had an influence on
the improvement in stress, a Pearson correlation between the
number of hours of mindfulness home practise and the
change in PSS scores was performed in SPSS (‘Statistical
Package for Social Sciences, Release 12.0.2.’, 2004).
Participants were scanned at the Martinos Center for
Biomedical Imaging in Charlestown, MA. Pre-intervention
scans were acquired approximately 1 week before the inter-
vention began and post-intervention scans were acquired
within the 2 weeks following the intervention. High-
resolution MRI data were acquired with a Siemens
12 SCAN (2010)B.K.Ho « lzeletal.
Magnetom Avanto 1.5 T scanner, using a T1-weighted,
magnetization-prepared rapid acquisition gradient echo
(MP-RAGE) sequence, consisting of 128 sagittal slices
(voxel size: 1.0?1.0?1.3mm, TI¼1000ms; TE¼3.39ms;
TR¼2730ms; flip angle 78 and matrix 256?256mm).
Anatomical MR images were compared for differences in
gray matter density using voxel-based morphometry (VBM;
Gaser, 2008), within the SPM5 neuroimaging statistical soft-
ware (www.fil.ion.ucl.ac.uk/spm/software/spm5/) based in
MATLAB 7.1, release 14 (Mathworks Inc., Natick, MA,
USA). VBM permits an automated voxel-wise whole-brain
statistical comparison of MRI scans. Images were first man-
ually aligned to the anterior commissure after which gray
matter, white matter and cerebral spinal fluid components
were segmented within native space. We analyzed unmodu-
lated images, which contain the probability within each voxel
for being gray matter, i.e. the proportion of gray matter to
other tissue types within a region (Good et al., 2001). For
each individual, the gray matter segmentations of the
post-intervention time-point were co-registered to the
image of the pre-intervention time-point. The normalization
parameters were calculated for the pre-intervention image
only and then applied to the post-intervention image to
make sure that regional differences between the images
were not removed because of scan-specific normalization.
Images were smoothed at 8-mm full width at half maximum
with an Isotropic Gaussian Kernel.
Improvement in PSS (post-intervention score minus pre-
intervention score; where negative values indicate decreases
in PSS scores and positive values indicate increases) was used
as the predictive regressor for changes in gray matter density
(post-intervention image minus pre-intervention image;
where negative values represent a decrease in gray matter
density and positive values indicate increases) in a regression
analysis. The significance threshold was defined as P<0.05,
corrected for multiple comparisons (false discovery rate)
within the search region (height threshold¼0.01, uncor-
rected). The region of interest was defined as the bilateral
amygdalae, according to Tzourio-Mazoyer et al. (2002).
Exploratory correlation with gray matter density in the
whole brain was performed at a significance threshold of
P<0.01 (uncorrected, 10 voxels).
PSS scores decreased pre- (mean 20.7; SD 5.6) to post-
P<0.001), indicating that the participants benefited from
the course. The internal consistency of the PSS was high
at boththe pre-and post-intervention
(Cronbach’s-? values 0.85 and 0.81, respectively), confirm-
ing an adequate reliability of the scale.
To assess whether the amount of individual meditation
home practise predicted the improvement in stress, the
number of minutes of meditation practise that participants
reported on daily logs was correlated with the magnitude of
their reduction in stress. With a Pearson correlation
coefficient of r¼0.35, the amount of training was mildly
correlated with the improvement in stress, though this
correlation did not reach statistical significance (P¼0.079;
Pre- to post-intervention analyses of the MRI data in SPM
confirmed a correlation between change in PSS scores and
change in gray matter density within the right amygdala
(cluster size: 10 voxels, MNI coordinates of peak voxel
x¼32, y¼0, z¼?26; voxel-level T¼3.18; P¼0.042,
multiple comparisons correction within the amygdala
search territory; Figure 1). Larger decreases in perceived
stress were associated with larger decreases in amygdaloid
gray matter density. The identified region appears to be
located in basolateral/lateral regions of the amygdala, based
on the atlas by Mai et al. (1997). The correlation of the
change in perceived stress and amygdala gray matter density
within the left amygdala was not significant.
Controlling for age and gender did not change the signif-
icance of the results in the right amygdala (cluster size:
9 voxels, MNI coordinates of peak voxel x¼32, y¼0,
z¼–26; T¼3.13; P¼0.045). There were no significant
correlations between change in gray matter density and
age, nor any group differences between males and females,
either in the amygdala or within the whole brain.
No other brain loci were significantly correlated with PSS
change scores when exploratory whole brain analyses were
performed in SPM, even at a liberal significance threshold of
P<0.01 (uncorrected, 10 voxels). There was also no corre-
lation between PSS values and gray matter density at the
pre-intervention time-point. Finally, there was no significant
pre- to post-intervention decrease in amygdala gray matter
density, i.e. no main effect of the MBSR intervention in the
amygdala; however, pre- to post-changes were identified in
other brain regions and are reported elsewhere (Ho ¨lzel et al.,
The present study investigates the potential relationship
between changes in perceived stress and morphological
changes in the amygdala. As predicted, there was a signifi-
cant correlation between changes in PSS scores and changes
in amygdaloid gray matter density. The more participants’
stress levels decreased, the greater the decrease of gray matter
density in the right amygdala.
The amygdala is widely regarded as one of the most
important limbic structures in prevailing models of stress
states and anxiety disorders. It receives information from
sensory modalities and projects to other subcortical
structures, thereby mediating stress-related behavioral and
physiological effects such as stress-hormone release, blood
pressure elevation and facial expression of fear (LeDoux,
2000). The cluster identified here appears to be located in
the lateral/basolateral region of the amygdala (Mai et al.,
1997). The basolateral region has been proposed to serve
Stress andamygdalaplasticitySCAN (2010) 13
as the site for the relay of sensory information from subcor-
tical and cortical sensory areas to the central nucleus of the
amygdala during anxiety responses (Campeau and Davis,
1995). Evidence of stress-related plasticity in these regions
has previously been found in animal studies, including
increased dendritic length and arborization within the baso-
lateral complex of the amygdala (Vyas et al., 2002; Mitra
et al., 2005).Strikingly,
sub-region identified in these rodent studies corresponds
to the region identified here. Cytoarchitectural modifications
such as those observed in rodent studies could potentially
contribute to the increased gray matter density observed in a
subset of the individuals in the present study. However,
studies designed to establish the cellular mechanisms under-
lying the observed differences in amygdaloid gray matter in
humans would require postmortem investigations.
Our results indicated an association between changes in
stress levels and morphometric changes in the right, but not
the left amygdala. It has been suggested that the right amyg-
dala mediates an initial, fast and perhaps automatic stimulus
detection, followed by a more evaluative and discriminative
response by the left amygdala (Morris et al., 1998; Wright
et al., 2001; Glascher and Adolphs, 2003; Costafreda et al.,
2008). Based on this model, our data suggest that this stress
reduction intervention may strongly impact the participants’
initial reaction to stimuli. This is consistent with a recent
study demonstrating decreased autonomic arousal (skin
conductance response) to affective stimuli following a
stress reduction course similar to the one in this study
(Ortner et al., 2007). However, further research will be
required to directly test any relationship between gray
matter changes and reactions to stimuli.
Previous longitudinal structural MRI studies in humans
have shown that repeated activation of a neural region, either
while learning new skills (Draganski et al., 2004; Ilg et al.,
2008) or through transcranial magnetic stimulation (May
et al., 2007), leads to an increase in the corresponding regio-
nal gray matter, whereas cessation of activation leads to a
decrease. It seems plausible that this pattern could apply to
the present findings?that changes in stress facilitate changes
in amygdala activity, which in turn mediate changes in
gray matter density. Interestingly, in rats, removal of
Fig. 1 (A–C) Location of positive correlation between gray matter density change in right amygdala and change in PSS score. Identified cluster overlaid on group-averaged
sagittal (A) (x¼32) and coronal (B) (y¼0) structural image. (C) The coronal glass brain image illustrates that no other brain regions were correlated even at a liberal statistical
threshold of uncorrected P<0.01. (D) Average percent change (post-intervention minus pre-intervention) in gray matter density within the identified cluster extracted from each
individual plotted against change in PSS scores. For illustrative purposes, voxel values within the identified cluster in the right amygdala were extracted and averaged using
Marsbar (Brett et al., 2002), and values on the x-axis were reversed.
14 SCAN (2010) B.K.Ho « lzeletal.
experimental stressors after a period of chronic exposure did
not lead to a reversal of the identified amygdaloid neuronal
hypertrophy, or to the reversal of the associated enhanced
anxiety-like behaviors within the observed time-frame of
21 days (Vyas et al., 2004). Our results suggest that amelior-
ating the subjective experience of stress through a behavioral
intervention may actually decrease amygdala gray matter
density in humans. This finding is particularly interesting
as it suggests that an active re-learning of emotional
responses to stress (such as taught in MBSR) can lead to
beneficial changes in neural structure and well-being even
when there is presumably no change in the person’s external
environment. Future research will be required to address
whether stress-induced alterations in the basolateral complex
of the amygdala might influence a person’s susceptibility to
anxiety and other affective disorders (Sajdyk et al., 1999;
Shekhar et al., 2003).
Gianaros et al. (2008) recently reported that lower gray
matter volume in the bilateral amygdala predicted greater
stressor-related amygdala activation, as well as greater
blood pressure reactivity. However, the complexity and
heterogeneity of amygdala subnuclei, in addition to the
low spatial resolution of neuroimaging methods, make inter-
preting this seemingly contradictory finding difficult.
As methods and technology improve, future studies could
consider how effects of stress may vary across the several
heterogeneous subregions of the amygdala. It should also
be noted that Gianaros et al. (2008) investigated gray
matter volume, which is distinct from gray matter density
examined in the present study. The biological differences
underlying these two neuroimaging techniques remain
Although a correlation was found between changes in
amygdaloid structure and perceived stress, the present
study did not show a significant overall main effect of the
training on amygdaloid gray matter density. Thus, the results
do not support the conclusion that MBSR training per se
leads to decreases in gray matter in this region. As reported
elsewhere (Ho ¨lzel et al., under review), main effect analyses
on a sub-cohort of the study participants did reveal signifi-
cant changes in hippocampal, inferior temporal lobe, poste-
rior cigulate, temporo-parietal and cerebellar gray matter
density, though these regions were not correlated with
changes in perceived stress.
The scatter plot (Figure 1D) illustrates that amygdaloid
gray matter density increased for some participants, though
it should be noted that a lot of those subjects also reported
increases in perceived stress following the MBSR program.
Some of the participants with improved perceived stress
scores appear to have slight increases in gray matter density,
but these small deviances may reflect noise. Alternatively,
changes in amygdala gray matter may be temporally delayed
relative to changes in perceived stress, perhaps requiring
habitual activation in this region to subside prior to
longer term structural changes. The results do support a
bidirectional correlation; further work will be required to
determine the precise relationship between the self-report
measure and cellular changes. PSS values and gray matter
density were not correlated at the pre-intervention time-
point. This is in line with previous findings (Gianaros
et al., 2007) and is not unexpected, as numerous factors
Lindenberg et al., 2006; Wilke et al., 2007). Importantly,
we assessed the relationship between the change in one
variable, namely perceived stress and changes in gray
matter density within the amygdala. By employing a
longitudinal design most within-subject variables were kept
relatively constant, while the factor of interest, perceived
stress, varied. Some behavioral variables, such as smoking,
diet or exercise, and psychological factors (e.g. neuroticism)
can also co-vary with changes in perceived stress, however,
and might mediate or drive the relationship between changes
in perceived stress and structural changes (cf., Gianaros
et al., 2007). These variables were not assessed in the current
study, and so it is unknown if the relationship between
perceived stress and gray matter observed here is direct or
Several previous cross-sectional studies have investigated
the impact of mindfulness meditation on brain morphology
by comparing groups of experienced mindfulness meditators
to nonmeditators (Lazar et al., 2005; Pagnoni and Cekic,
2007; Ho ¨lzel et al., 2008; Luders et al., 2009). These studies
identified several regions of altered brain morphology, but
none within the amygdalae. However, none of these studies
assessed the participants’ perceived stress levels. Again, these
data highlight the limitations of the cross-sectional study
design. The unique hypothesis-driven, focused analysis
employed in the present study revealed a novel link between
changes in amygdaloid gray matter density and decreases in
self-reported stress following stress-reduction
marking a significant advance in our understanding of the
association between both. Whereas previous studies have
demonstrated that gray matter modifications can result
from the acquisition of abstract information (Draganski
et al., 2006), motor skills (Draganski et al., 2004) and lan-
guage skills (Mechelli et al., 2004), this is the first study to
demonstrate neuroplastic changes associated with changes
in a measure of a psychological state.
Conflict of interest
Abercrombie, H.C., Schaefer, S.M., Larson, C.L., et al. (1998). Metabolic
rate in the right amygdala predicts negative affect in depressed patients.
Neuroreport, 9(14), 3301–7.
Altshuler, L.L., Bartzokis, G., Grieder, T., Curran, J., Mintz, J. (1998).
Amygdala enlargement in bipolar disorder and hippocampal reduction
in schizophrenia: an MRI study demonstrating neuroanatomic specificity.
Archives of General Psychiatry, 55(7), 663–4.
Stress andamygdalaplasticitySCAN (2010) 15
Atmaca, M., Yildirim, H., Ozdemir, H., et al. (2008). Hippocampus and
amygdalar volumes in patients with refractory obsessive-compulsive
disorder. Progress in neuro-psychopharmacology and Biological Psychiatry,
Birbaumer, N., Grodd, W., Diedrich, O., et al. (1998). fMRI reveals
amygdala activation to human faces in social phobics. Neuroreport,
Brett, M., Anton, J.-L., Valabregue, R., Poline, J.-B. (2002). Region of
interest analysis using an SPM toolbox [abstract]. In: 8th International
Conference on Functional Mapping of the Human Brain, 16(2), Sendai,
Campeau, S., Davis, M. (1995). Involvement of the central nucleus and
basolateral complex of the amygdala in fear conditioning measured
with fear-potentiated startle in rats trained concurrently with auditory
and visual conditioned stimuli. Journal of Neuroscience, 15(3 Pt 2),
Carmody, J., Baer, R.A. (2008). Relationships between mindfulness practice
and levels of mindfulness, medical and psychological symptoms and
well-being in a mindfulness-based stress reduction program. Journal of
Behavioral Medicine, 31(1), 23–33.
Chang, V.Y., Palesh, O., Caldwell, R., et al. (2004). The effects of a
mindfulness-based stress reduction program on stress, mindfulness self-
efficacy, and positive states of mind. Stress and Health: Journal of the
International Society for the Investigation of Stress, 20(3), 141–7.
Chrousos, G.P. (2000). The stress response and immune function: clinical
implications. The 1999 Novera H. Spector Lecture. Annals of the New York
Academy of Sciences, 917, 38–67.
Coccaro, E.F., McCloskey, M.S., Fitzgerald, D.A., Phan, K.L. (2007).
Amygdala and orbitofrontal reactivity to social threat in individuals
with impulsive aggression. Biological Psychiatry, 62(2), 168–78.
Cohen, S., Kamarck, T., Mermelstein, R. (1983). A global measure of
perceived stress. Journal of Health and Social Behavior, 24(4), 385–96.
Cohen, S., Williamson, G.M. (1988). Perceived stress in a probability sample
of the United States. In: Spacapan, S., Oskamp, S., editors. The Social
Psychology of Health. Newbury Park, CA: Sage, pp. 31–67.
Costafreda, S.G., Brammer, M.J., David, A.S., Fu, C.H. (2008). Predictors
of amygdala activation during the processing of emotional stimuli: a
meta-analysis of 385 PET and fMRI studies. Brain Research Reviews,
De Bellis, M.D., Casey, B.J., Dahl, R.E., et al. (2000). A pilot study of
amygdala volumes in pediatric generalized anxiety disorder. Biological
Psychiatry, 48(1), 51–7.
Doty, T.J., Payne, M.E., Steffens, D.C., Beyer, J.L., Krishnan, K.R.,
LaBar, K.S. (2008). Age-dependent reduction of amygdala volume in
bipolar disorder. Psychiatry Research, 163(1), 84–94.
Dougherty, D.D., Rauch, S.L., Deckersbach, T., et al. (2004). Ventromedial
prefrontal cortex and amygdala dysfunction during an anger induction
positron emission tomography study in patients with major depressive
disorder with anger attacks. Archives of General Psychiatry, 61(8),
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., May, A.
(2004). Changes in grey matter induced by training. Nature, 427, 311–12.
Draganski, B., Gaser, C., Kempermann, G., et al. (2006). Temporal and
spatial dynamics of brain structure changes during extensive learning.
Journal of Neuroscience, 26(23), 6314–7.
Drevets, W.C., Price, J.L., Furey, M.L. (2008). Brain structural and
functional abnormalities in mood disorders: implications for neuro-
circuitry models of depression. Brain Structure and Function, 213(1–2),
Drevets, W.C., Videen, T.O., Price, J.L., Preskorn, S.H., Carmichael, S.T.,
Raichle, M.E. (1992). A functional anatomical study of unipolar
depression. Journal of Neuroscience, 12(9), 3628–41.
Evans, K.C., Wright, C.I., Wedig, M.M., Gold, A.L., Pollack, M.H.,
Rauch, S.L. (2008). A functional MRI study of amygdala responses to
angry schematic faces in social anxiety disorder. Depress Anxiety, 25(6),
Frodl, T., Jager, M., Smajstrlova, I., et al. (2008). Effect of hippocampal and
amygdala volumes on clinical outcomes in major depression: a 3-year
prospective magnetic resonance imaging study. Journal of Psychiatry
Neuroscience, 33(5), 423–30.
Frodl, T., Meisenzahl, E., Zetzsche, T., et al. (2002). Enlargement of the
amygdala in patients with a first episode of major depression. Biological
Psychiatry, 51(9), 708–14.
Frodl, T., Meisenzahl, E. M., Zetzsche, T., et al. (2003). Larger amygdala
volumes in first depressive episode as compared to recurrent major
depression and healthy control subjects. Biological Psychiatry, 53(4),
Gaser, C. VBM5 (for SPM5). [Computer software]. Available at:
Gianaros, P.J., Jennings, J.R., Sheu, L.K., Greer, P.J., Kuller, L.H.,
Matthews, K. A. (2007). Prospective reports of chronic life stress predict
decreased grey matter volume in the hippocampus. Neuroimage, 35(2),
Gianaros, P.J., Sheu, L.K., Matthews, K.A., Jennings, J.R., Manuck, S.B.,
Hariri, A.R. (2008). Individual differences in stressor-evoked blood pres-
sure reactivity vary with activation, volume, and functional connectivity
of the amygdala. Journal of Neuroscience, 28(4), 990–9.
Gilbertson, M.W., Shenton, M.E., Ciszewski, A., et al. (2002). Smaller
hippocampal volume predicts pathologic vulnerability to psychological
trauma. Nature Neuroscience, 5(11), 1242–7.
Glascher, J., Adolphs, R. (2003). Processing of the arousal of subliminal and
supraliminal emotional stimuli by the human amygdala. Journal of
Neuroscience, 23(32), 10274–82.
Good, C.D., Johnsrude, I.S., Ashburner, J., Henson, R.N., Friston, K.J.,
Frackowiak, R.S. (2001). A voxel-based morphometric study of ageing
in 465 normal adult human brains. Neuroimage, 14(1 Pt 1), 21–36.
Gurvits, T.V., Shenton, M.E., Hokama, H., et al. (1996). Magnetic resonance
imaging study of hippocampal volume in chronic, combat-related
posttraumatic stress disorder. Biological Psychiatry, 40(11), 1091–9.
Hasler, G., Fromm, S., Alvarez, R.P., Luckenbaugh, D.A., Drevets, W.C.,
Grillon, C. (2007). Cerebral blood flow in immediate and sustained
anxiety. Journal of Neuroscience, 27(23), 6313–9.
Hayano, F., Nakamura, M., Asami, T., et al. (2009). Smaller amygdala is
associated with anxiety in patients with panic disorder. Psych Clin
Neurosci, 63(3), 266–76.
Ho ¨lzel, B.K., Carmody, J., Congleton, C., McCallister, A., Yerramsetti, S.M.,
Lazar, S. (under review). Meditation practice leads to increases in regional
brain gray matter concentration.
Ho ¨lzel, B.K., Ott, U., Gard, T., et al. (2008). Investigation of mindfulness
meditation practitioners with voxel-based morphometry. Social Cognitive
and Affective Neuroscience, 3(1), 55–61.
Ilg, R., Wohlschlager, A.M., Gaser, C., et al. (2008). Gray matter increase
induced by practice correlates with task-specific activation: a combined
functional and morphometric magnetic resonance Imaging study. Journal
of Neuroscience, 28(16), 4210–5.
Johnson, E.O., Kamilaris, T.C., Chrousos, G.P., Gold, P.W. (1992).
Mechanismsof stress:a dynamic
behavioral homeostasis. Neuroscience and Biobehavioral reviews, 16(2),
Kabat-Zinn, J. (1990). Full Catastrophe Living. New York: Delta Publishing.
Karl, A., Schaefer, M., Malta, L. S., Dorfel, D., Rohleder, N., Werner, A.
(2006). A meta-analysis of structural brain abnormalities in PTSD.
Neuroscience and Biobehavioral Reviews, 30(7), 1004–31.
Lange, C., Irle, E. (2004). Enlarged amygdala volume and reduced hippo-
campal volume in young women with major depression. Psychological
Medicine, 34(6), 1059–64.
Lazar, S.W., Kerr, C.E., Wasserman, R.H., et al. (2005). Meditation experi-
ence is associated with increased cortical thickness. Neuroreport, 16(17),
LeDoux, J.E. (2000). Emotion circuits in the brain. Annual Review of
Neuroscience, 23, 155–84.
16 SCAN (2010) B.K.Ho « lzeletal.
Luders, E., Toga, A.W., Lepore, N., Gaser, C. (2009). The underlying
anatomical correlates of long-term meditation: larger hippocampal and
frontal volumes of gray matter. Neuroimage, 45(3), 672–8.
Mai, J.K., Assheuer, J., Paxinos, G. (1997). Atlas of the Human Brain. San
Diego: Academic Press.
Massana, G., Serra-Grabulosa, J.M., Salgado-Pineda, P., et al. (2003).
Amygdalar atrophy in panic disorder patients detected by volumetric
magnetic resonance imaging. Neuroimage, 19(1), 80–90.
May, A., Hajak, G., Gaenssbauer, S., et al. (2007). Structural brain
alterations following 5 days of intervention: Dynamic aspects of neuro-
plasticity. Cerebral Cortex, 17, 205–10.
Mechelli, A., Crinion, J.T., Noppeney, U., et al. (2004). Structural plasticity
in the bilingual brain. Proficiency in a second language and age at
acquisition affect grey-matter density. Nature, 431, 757.
Mervaala, E., Fohr, J., Kononen, M., et al. (2000). Quantitative MRI of the
hippocampus and amygdala in severe depression. Psychological Medicine,
Meyer-Lindenberg, A., Buckholtz, J.W., Kolachana, B., et al. (2006). Neural
mechanisms of genetic risk for impulsivity and violence in humans.
Proceedings of the National Academy of Sciences of the United States of
America, 103(16), 6269–74.
Milham, M.P., Nugent, A.C., Drevets, W.C., et al. (2005). Selective
reduction in amygdala volume in pediatric anxiety disorders: a voxel-
based morphometry investigation. Biological Psychiatry, 57(9), 961–6.
Mitra, R., Jadhav, S., McEwen, B.S., Vyas, A., Chattarji, S. (2005). Stress
duration modulates the spatiotemporal patterns of spine formation in the
basolateral amygdala. Proceedings of the National Academy of Sciences of
the United States of America, 102(26), 9371–6.
Morris, J.S., Ohman, A., Dolan, R.J. (1998). Conscious and unconscious
emotional learning in the human amygdala. Nature, 393(6684), 467–470.
Ortner, C.N.M., Kilner, S.J., Zelazo, P.D. (2007). Mindfulness meditation
and reduced emotional interference on a cognitive task. Motivation and
Emotion, 31(4), 271–83.
Pagnoni, G., Cekic, M. (2007). Age effects on gray matter volume and
attentional performance in Zen meditation. Neurobiology of Aging,
Phan, K.L., Fitzgerald, D.A., Nathan, P.J., Tancer, M.E. (2006). Association
between amygdala hyperactivity to harsh faces and severity of social
anxiety in generalized social phobia. Biological Psychiatry, 59(5), 424–9.
Rauch, S.L., Whalen, P.J., Shin, L.M., et al. (2000). Exaggerated amygdala
response to masked facial stimuli in posttraumatic stress disorder: a
functional MRI study. Biological Psychiatry, 47(9), 769–76.
Sajdyk, T.J., Schober, D.A., Gehlert, D.R., Shekhar, A. (1999). Role of
corticotropin-releasing factor and urocortin within the basolateral
amygdala of rats in anxiety and panic responses. Behavioural Brain
Research, 100(1–2), 207–15.
Sapolsky, R.M. (2003). Stress and plasticity in the limbic system.
Neurochemical Research, 28(11), 1735–42.
Sapolsky, R.M., Romero, L.M., Munck, A.U. (2000). How do gluco-
corticoids influence stress responses? Integrating permissive, suppressive,
stimulatory, and preparative actions. Endocrine Reviews, 21(1), 55–89.
Shekhar, A., Sajdyk, T.J., Gehlert, D.R., Rainnie, D.G. (2003). The amygdala,
panic disorder, and cardiovascular responses. Annals of the New York
Academy of Sciences, 985, 308–25.
Sheline, Y.I., Barch, D.M., Donnelly, J.M., Ollinger, J.M., Snyder, A.Z.,
Mintun, M.A. (2001). Increased amygdala response to masked emotional
faces in depressed subjects resolves with antidepressant treatment: an
fMRI study. Biological Psychiatry, 50(9), 651–8.
Sheline, Y.I., Gado, M.H., Price, J.L. (1998). Amygdala core nuclei volumes
are decreased in recurrent major depression. Neuroreport, 9(9), 2023–8.
Shin, L.M., Orr, S.P., Carson, M.A., et al. (2004). Regional cerebral blood
flow in the amygdala and medial prefrontal cortex during traumatic
imagery in male and female Vietnam veterans with PTSD. Archives of
General Psychiatry, 61(2), 168–76.
Shin, L.M., Wright, C.I., Cannistraro, P.A., et al. (2005). A functional
magnetic resonance imaging study of amygdala and medial prefrontal
cortex responses to overtly presented fearful faces in posttraumatic
stress disorder. Archives of General Psychiatry, 62(3), 273–81.
Shors, T.J., Mathew, P.R. (1998). NMDA receptor antagonism in the lateral/
basolateral but not central nucleus of the amygdala prevents the
induction of facilitated learning in response to stress. Learning &
Memory, 5(3), 220–30.
Siegle, G.J., Konecky, R.O., Thase, M.E., Carter, C.S. (2003). Relationships
between amygdala volume and activity during emotional information
processing tasks in depressed and never-depressed individuals: an
fMRI investigation. Annals of the New York Academy of Sciences, 985,
Siegle, G.J., Steinhauer, S.R., Thase, M.E., Stenger, V.A., Carter, C.S. (2002).
Can’t shake that feeling: event-related fMRI assessment of sustained
amygdala activity in response to emotional information in depressed
individuals. Biological Psychiatry, 51(9), 693–707.
Statistical Package for Social Sciences, Release 12.0.2. (2004). Chicago:
Stein, M.B., Simmons, A.N., Feinstein, J.S., Paulus, M.P. (2007). Increased
amygdala and insula activation during emotion processing in anxiety-
prone subjects. The American Journal of Psychiatry, 164(2), 318–27.
Strakowski, S.M., DelBello, M.P., Sax, K.W., et al. (1999). Brain magnetic
resonance imaging of structural abnormalities in bipolar disorder.
Archives of General Psychiatry, 56(3), 254–60.
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., et al. (2002).
Automated anatomical labeling of activations in SPM using a macro-
scopic anatomical parcellation of the MNI MRI single-subject brain.
Neuroimage, 15(1), 273–89.
Vyas, A., Bernal, S., Chattarji, S. (2003). Effects of chronic stress on
dendritic arborization in the central and extended amygdala. Brain
Research, 965(1–2), 290–4.
Vyas, A., Mitra, R., Shankaranarayana Rao, B.S., Chattarji, S. (2002).
Chronic stress induces contrasting patterns of dendritic remodeling in
hippocampal and amygdaloid neurons. Journal of Neuroscience, 22(15),
Vyas, A., Pillai, A.G., Chattarji, S. (2004). Recovery after chronic stress fails
to reverse amygdaloid neuronal hypertrophy and enhanced anxiety-like
behavior. Neuroscience, 128(4), 667–3.
Weniger, G., Lange, C., Irle, E. (2006). Abnormal size of the amygdala
predicts impaired emotional memory in major depressive disorder.
Journal of Affective Disorders, 94(1–3), 219–29.
Wignall, E.L., Dickson, J.M., Vaughan, P., et al. (2004). Smaller hippocam-
pal volume in patients with recent-onset posttraumatic stress disorder.
Biological Psychiatry, 56(11), 832–6.
Wilke, M., Krageloh-Mann, I., Holland, S.K. (2007). Global and local
development of gray and white matter volume in normal children and
adolescents. Experimental Brain Research, 178(3), 296–307.
Woon, F.L., Hedges, D.W. (2008). Hippocampal and amygdala volumes in
children and adults with childhood maltreatment-related posttraumatic
stress disorder: a meta-analysis. Hippocampus, 18(8), 729–36.
Wright, C.I., Fischer, H., Whalen, P.J., McInerney, S.C., Shin, L.M.,
Rauch, S.L. (2001). Differential prefrontal cortex and amygdala habitua-
tion to repeatedly presented emotional stimuli. Neuroreport, 12(2),
Stress andamygdalaplasticity SCAN (2010)17