ArticlePDF Available

Abstract and Figures

Diffusion tensor imaging revealed that trait anxiety predicts the microstructural properties of a prespecified fiber tract between the amygdala and the perigenual anterior cingulate cortex. Besides this particular pathway, it is likely that other pathways are also affected. We investigated white matter differences in persons featuring an anxious or a nonanxious personality, taking into account all potential pathway connections between amygdala and anxiety-related regions of the prefrontal cortex (PFC). Diffusion-weighted images, measures of trait anxiety and of reappraisal use (an effective emotion-regulation style), were collected in 48 females. With probabilistic tractography, pathways between the amygdala and the dorsolateral PFC, dorsomedial PFC, ventromedial PFC, and orbitofrontal cortex (OFC) were delineated. The resulting network showed a direct ventral connection between amygdala and PFC and a second limbic connection following the fornix and the anterior limb of the internal capsule. Reappraisal use predicted the microstructure of pathways to all calculated PFC regions in the left hemisphere, indicating stronger pathways for persons with high reappraisal use. Trait anxiety predicted the microstructure in pathways to the ventromedial PFC and OFC, indexing weaker connections in trait-anxious persons. These effects appeared in the right hemisphere, supporting lateralization and top-down inhibition theories of emotion processing. Whereas a specific microstructure is associated with an anxious personality, a different structure subserves emotion regulation. Both are part of a broad fiber tract network between amygdala and PFC. Copyright © 2015 the authors 0270-6474/15/356020-08$15.00/0.
Content may be subject to copyright.
Behavioral/Cognitive
Emotion Regulation and Trait Anxiety Are Predicted by the
Microstructure of Fibers between Amygdala and Prefrontal
Cortex
Annuschka Salima Eden,
1
Jan Schreiber,
4
XAlfred Anwander,
4
XKatharina Keuper,
1,3
Inga Laeger,
2
Peter Zwanzger,
2
Pienie Zwitserlood,
5
XHarald Kugel,
6
and Christian Dobel
1,3
1
Institute for Biomagnetism and Biosignalanalysis and
2
Department of Psychiatry, University Hospital, 48149 Mu¨nster, Germany,
3
Otto Creutzfeldt Center
for Cognitive and Behavioural Neuroscience, 48149 Mu¨nster, Germany,
4
Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig,
Germany,
5
Westfa¨lische Wilhelms-Universita¨t, 48149 Mu¨ nster, Germany, and
6
Center of Radiology, Faculty of Medicine, 48149 Mu¨nster, Germany
Diffusion tensor imaging revealed that trait anxiety predicts the microstructural properties of a prespecified fiber tract between the
amygdala and the perigenual anterior cingulate cortex. Besides this particular pathway, it is likely that other pathways are also affected.
We investigated white matter differences in persons featuring an anxious or a nonanxious personality, taking into account all potential
pathway connections between amygdala and anxiety-related regions of the prefrontal cortex (PFC). Diffusion-weighted images, measures
of trait anxiety and of reappraisal use (an effective emotion-regulation style), were collected in 48 females. With probabilistic tractogra-
phy, pathways between the amygdala and the dorsolateral PFC, dorsomedial PFC, ventromedial PFC, and orbitofrontal cortex (OFC) were
delineated. The resulting network showed a direct ventral connection between amygdala and PFC and a second limbic connection
following the fornix and the anterior limb of the internal capsule. Reappraisal use predicted the microstructure of pathways to all
calculated PFC regions in the left hemisphere, indicating stronger pathways for persons with high reappraisal use. Trait anxiety predicted
the microstructure in pathways to the ventromedial PFC and OFC, indexing weaker connections in trait-anxious persons. These effects
appeared in the right hemisphere, supporting lateralization and top-down inhibition theories of emotion processing. Whereas a specific
microstructure is associated with an anxious personality, a different structure subserves emotion regulation. Both are part of a broad
fiber tract network between amygdala and PFC.
Key words: amygdala; DTI; PFC; reappraisal use; top-down inhibition; trait anxiety
Introduction
The interplay between amygdala and prefrontal cortex (PFC) is
central to the regulation of emotions. Crucial components of this
interplay are top-down inhibition processes manifesting them-
selves in downregulation of the amygdala by medial PFC (mPFC;
Bishop, 2007). A greater functional connectivity between the
amygdala and the mPFC was reported in persons with low anxi-
ety (Pezawas et al., 2005). Investigating fiber connections in white
matter, Kim and Whalen (2009) applied diffusion tensor imaging
(DTI) and found that trait anxiety, a stable tendency to respond
with anxiety, predicted the microstructure of a ventral amygdala–
PFC pathway. Persons high in trait anxiety showed lower values
of fractional anisotropy (FA; Basser and Pierpaoli, 1996) on this
tract to the perigenual anterior cingulate cortex, i.e., weaker con-
nections. It is likely that a larger network of amygdala–PFC con-
nections is affected in trait anxiety (for review, see Ray and Zald,
2012). Data by Kim and Whalen (2009) support the idea that
anxiety is associated with ineffective top-down inhibition. These
dysfunctional processes might be attributable to an attenuated
use of reappraisal, a coping strategy involving reinterpretation of
the emotional meaning of stimuli. Low reappraisal results in low
activity in PFC regions and in high amygdala activity (Ochsner et
al., 2002,2004;Kim and Hamann, 2007). In women, the micro-
structural foundation for this interplay is related to the integrity
of white matter pathways between amygdala and PFC (Zuurbier
et al., 2013).
Anatomical knowledge about amygdala–PFC connections
mostly derives from primates. Because of close cytoarchitectural
homology between primates and humans (Petrides and Mackey,
2006;Jbabdi et al., 2013), a transfer of findings seems reasonable
but awaits further support. The mPFC and the orbitofrontal cor-
tex (OFC) receive direct input from the amygdala (for an over-
view, see Barbas and Zikopoulos, 2006), whereas the lateral PFC
receives less, and mostly indirect, input via the cingulate or pos-
terior OFC (Ray and Zald, 2012). Studies investigating amygda-
la–PFC connections in relation to anxiety have mostly focused on
Received July 26, 2014; revised Jan. 31, 2015; accepted Feb. 3, 2015.
Authorcontributions: A.S.E.,K.K., I.L.,Pe.Z., Pi.Z.,and C.D.designed research;A.S.E. andH.K. performedresearch;
J.S., A.A., H.K., and C.D. contributed unpublished reagents/analytic tools; A.S.E., J.S., and A.A. analyzed data; A.S.E.,
J.S., A.A., K.K., I.L., Pe.Z., Pi.Z., H.K., and C.D. wrote the paper.
This work was supported by the Interdisciplinary Center for Clinical Research (Grant Do3/021/10).
The authors declare no competing financial interests.
Correspondenceshouldbeaddressedto AnnuschkaSalima Eden,Institute forBiomagnetism andBiosignalanaly-
sis, Malmedyweg 15, 48143 Mu¨nster, Germany. E-mail: Annuschka.Eden@uni-muenster.de.
DOI:10.1523/JNEUROSCI.3659-14.2015
Copyright © 2015 the authors 0270-6474/15/356020-08$15.00/0
6020 The Journal of Neuroscience, April 15, 2015 35(15):6020 – 6027
specific and direct connections, such as to the insula or via the
uncinate fasciculus. They neglected indirect routes via long asso-
ciation fibers (Modi et al., 2013;Baur et al., 2013a,b).
Our aim was to investigate white matter alterations in persons
with high and low trait anxiety, along multiple pathways connect-
ing amygdala and PFC. We collected diffusion-weighted mag-
netic resonance images and applied probabilistic tractography
(Behrens et al., 2007) to reconstruct all potential pathways be-
tween the amygdala and PFC regions associated with anxiety-
related processes. A rather large body of literature established an
association of anxiety with right-hemispheric activity (Davidson
et al., 1990), and thus we hypothesized trait anxiety to be associ-
ated with weaker right-hemispheric connections. Mechanisms of
reappraisal are less investigated, but there is some evidence for
left-hemispheric lateralization of reappraisal (Ochsner et al.,
2002) as well as higher metabolic activity in left frontal regions in
reappraisal users (Kim et al., 2012). Consequently, reappraisal
was expected to be associated with stronger left-hemispheric con-
nections brought forth by intensive use.
Materials and Methods
Subjects
Three hundred ten nonclinical volunteers completed an on-line version
of the Spielberger Trait Anxiety Inventory (Spielberger et al., 1983). On
the basis of individual trait scores, right-handed (according to the Edin-
burgh Handedness Inventory; Oldfield, 1971) female participants were
selected if they scored 30 or 50. In a next step, they were matched for
age. This established two groups of participants (n24 each), one with
low anxiety [LA; mean trait score, 27.08 (SD, 2.43); mean age, 25.38 (SD,
3.679)] and one with high anxiety [HA; mean trait score, 27.08 (SD,
2.43); mean age, 25.38 (SD, 3.67)], that did not differ for age (df 46,
T1.414, p0.166) nor years of schooling. All group members were
medically healthy and had no history of psychiatric medication or mental
disorders, as verified by the Mini International Neuropsychiatric Inter-
view (version 5.0.0) of the Diagnostic Statistical Manual–IV (Ackenheil
et al., 1999). The participants that were excluded from the two groups did
not fulfill one or more of the required inclusion criteria. All procedures
were cleared by the ethical review board of the A
¨rztekammer Westfalen-
Lippe, and subjects gave informed consent for their participation.
Procedure
To control for intelligence differences between groups, the Wechsler
Adult Intelligence Scale (German version of the WAIS-III; Von Aster et
al., 2006) was administered individually to every subject 2 d before image
acquisition. No significant differences were found between the HA and
LA groups (HA: mean, 107.00; SD, 25.11; LA: mean, 115.17; SD, 13.06;
T1.414, p0.164). Participants completed the German version of the
Emotion Regulation Questionnaire (Gross and John, 2003), which mea-
sures reappraisal use. The two groups displayed significant differences in
reappraisal use (HA: mean, 23.04; SD, 6.52; LA: mean, 27.75; SD, 6.03;
T2.598, p0.013; see Table 1 for means separated by group).
Image acquisition
Participants were instructed to lie still and stay awake throughout the
entire scanning procedure. Diffusion MRI (dMRI) and structural T1-
weighted images were acquired on a 3T MR scanner (Intera 3.0T; Philips
Medical Systems), with an inner bore diameter of 60 cm, equipped with
Quasar-Dual Gradients with two modes, either 40 mT/m gradient
strength and 200 mT/m/ms slew rate for general imaging or 80 mT/m
gradient strength and 100 mT/m/ms slew rate for diffusion imaging.
Diffusion MRI. High-angular resolution dMRI data were acquired us-
ing a six-channel head coil with a single-shot spin echo EPI sequence (TE,
55 ms; TR, 15,623 ms; image matrix, 128 128; FOV, 240 240 mm
2
),
providing 60 diffusion-encoding gradient directions with a bvalue of
1000 s/mm
2
and a single measurement without a diffusion-weighting
gradient (b0 s/mm
2
). Seventy-eight axial slices with 1.88 mm thick-
ness were acquired in an interleaved manner, covering the whole brain.
This resulted in cubic voxels of 1.88 mm edge length. Parallel image
acquisition was applied using SENSE with an acceleration factor of 2 and
a scan duration of 20 min.
Anatomical MRI. The T1-weighted images were acquired with a 3D
nonequilibrium gradient echo sequence (turbo field echo) with water-
selective excitation. Contrast preparation of magnetization consisted of a
nonselective inversion pulse every 1020 ms. Imaging parameters were as
follows: TR, 9.3 ms; final TE, 4.4 ms; pulse angle, 9°; FOV, 300 239
234 mm
3
(foot-head anterior-posterior right-left); cubic voxels of 1.17
mm edge length; SENSE acceleration factor 2scan duration, 8.43 min.
dMRI preprocessing
Before data processing, dMRI volumes that were corrupted by move-
ment of the participants were removed from the datasets. First, an auto-
matic method was used to remove volumes of low quality. The algorithm
is based on the fact that motion eliminates the signal in a slice when
motion occurs during its acquisition. Usually, the average voxel intensity
of two consecutive slices does not change much. Only when motion
extinguishes the signal in parts of a slice does its average voxel intensity
differ greatly from its neighbors’ and indicate corruption of the volume.
In a following control step, visual inspection of the datasets ensured the
satisfactory quality of the remaining data. The cleaned dMRIs were in-
terpolated to 1 mm isotropic resolution, aligned with the MNI template,
and corrected for motion and eddy-current effects in one step with a
single interpolation. The diffusion tensor and the FA maps were com-
puted by use of the FSL software package (http://fsl.fmrib.ox.ac.
uk/fsl/fsl-4.1.9;Smith et al., 2004;Woolrich et al., 2009;Jenkinson et al.,
2012).
Regions for connectivity analysis
Based on the literature, four regions in the PFC were defined: the ventro-
medial PFC (vmPFC; Buckholtz et al., 2008), the dorsomedial PFC
(dmPFC; Kim et al., 2011), the dorsolateral PFC (dlPFC; Stein et al.,
2007), and the OFC (Zald and Kim, 1996a,b;Rauch et al., 1997;Sladky et
al., 2012). Since the precise anatomical locations and boundaries of these
areas have not yet been defined beyond controversy (Roy et al., 2012),
there was no suitable ready-to-use atlas that comprised all four PFC areas
for our purposes. Thus, we manually created an atlas that included the
dmPFC, dlPFC, OFC, and vmPFC based on the atlas introduced by Oishi
(type II WMPM; Oishi et al., 2009). The ventral and dorsal regions were
separated by an axial cutting plane at z5 (MNI). The posterior end of
the ROIs was defined at y0 (MNI). This atlas was morphed on the
individual brains using nonlinear registration (Avants et al., 2008) ob-
tained from a registration of the FA template (FMRIB58_FA_1 mm sup-
plied with FSL) onto the individual FA map. Figure 1 illustrates the
defined PFC areas applied in this study. The amygdala regions were
obtained by registration of the combined population maps of the
amygdala parcellation (Solano-Castiella et al., 2010) to each individual
Table 1. Means and SDs of demographic, behavioral, and fractional anisotropy (in target regions) data, separately for both anxiety groups
FA
Trait anxiety group Trait anxiety score Reappraisal score Age Years of schooling IQ OFC vmPFC dmPFC dlPFC
Low 27.08 2.43 27.75 6.03 25.38 3.67 13 0 115.17 13.06 L: 0.533 0.017 L: 0.544 0.015 L: 0.553 0.015 L: 0.545 0.019
R: 0.541 0.017 R: 0.541 0.014 R: 0.554 0.012 R: 0.541 0.012
High 57.58 4.65 23.04 6.52 26.92 5.99 13 0 107.00 25.11 L: 0.522 0.030 L: 0.488 0.152 L: 0.505 0.157 L: 0.471 0.183
R: 0.527 0.017 R: 0.531 0.013 R: 0.519 0.112 R: 0.508 0.111
L, Left hemisphere; R, right hemisphere.
Eden et al. Fiber Microstructure Predicts Anxiety Traits J. Neurosci., April 15, 2015 35(15):6020 – 6027 • 6021
FA map, and they were thresholded at a value
of 3. The average volumes of the left and right
amygdala were 1478 and 1586 mm
3
,
respectively.
Analysis of white matter microstructure
Probabilistic tractography based on the ball-
and-stick model (Behrens et al., 2007) that is
implemented in the FSL software package was
used to create the connectivity maps between
amygdala and the PFC regions. These connec-
tivity maps indicate for every voxel by how
many probabilistic tracks it has been crossed.
One thousand tracks were started in every
voxel of the amygdala, but only those that
reached one of the prefrontal regions were con-
sidered. Starting a fixed number of tracks in
every voxel of the amygdala masks leads to a
different number of probabilistic tracks in ev-
ery subject, because of different sizes of indi-
vidual amygdalae. To compensate for this effect, all voxel values in the
connectivity maps were normalized by dividing them by the volume of
the individual amygdala. Tracks were only seeded in the amygdala and
not in the PFC regions, as pilot testing revealed that only a very small
fraction of the tracks seeded in the PFC areas reached the amygdala so
that the statistical power of this testing was not sufficient.
To evaluate differences in white matter coherence along the connect-
ing pathways, values of FA were compared between the groups. This was
achieved by a region-based analysis method (Snook et al., 2007;Faria et
al., 2010) that considered only voxels on the center line of the white
matter within the pathways defined by the connectivity maps. The central
line was defined by computing the skeleton of each individual’s FA map
as implemented in the tract-based spatial statistics software package
(TBSS, http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/TBSS;Smith et al., 2006), tak-
ing into account only voxels with an FA value higher than 0.4 (Fig. 1B,
green). To define the target-specific ROI, the connectivity maps were
thresholded at a specific level for every target region. These levels were
computed separately by averaging the 90% quantiles of all individual
normalized connectivity maps. The FA values on the skeleton within this
mask were averaged.
Amygdala–prefrontal pathways
The individual connectivity maps for each prefrontal connection were
normalized with the transformation obtained from the atlas registration,
averaged across participants, and thresholded at the target-specific level.
The anatomical locations of the fiber pathways were evaluated based on
the anatomical slices and a 3D volume rendering using the LIPSIA soft-
ware (Lohmann et al., 2001).
Statistical analysis
To test the influence of trait anxiety and reappraisal use on the pathway
strength between amygdala (seed) and PFC regions (targets), multiple
hierarchical regressions were calculated individually for both hemi-
spheres, with the factors trait anxiety (high trait anxiety vs low trait
anxiety, dummy coded), the individual reappraisal use score, and the
individual IQ score. The factor IQ was added to check the specificity of
the resultant pathways for emotion-related characteristics. There is evi-
dence for a positive correlation between FA and IQ (Schmithorst et al.,
2005). If the delineated microstructure is emotion specific, IQ should not
explain additional variance.
The FA values on the calculated pathways between seed and targets
(dmPFC, dlPFC, vmPFC, and OFC, respectively) served as dependent
variables. Note that because of a priori knowledge of asymmetric hemi-
spheric processing, we calculated hierarchical regressions and set up dif-
ferent hierarchies for both hemispheres. In the left hemisphere, the factor
reappraisal use was expected to explain most of the variance and thus was
the first variable to enter the regression, followed by the factor trait
anxiety and IQ as a third factor. To underline the hypothesis-driven
approach, we also tested the model where trait anxiety was the first factor.
Based on the literature, we expected no effects. In the right hemisphere,
we expected the factor trait anxiety to explain most of the variance.
Hence, trait anxiety was the first to enter this regression, followed by
reappraisal use and, finally, IQ. As above, we also tested the alternative
model with reappraisal use as the first factor.
Results
After an anatomical description of the fiber pathway connections
between seed and target regions, the results of the statistical anal-
yses of the FA values of these pathways will be reported.
Figure 2 shows the calculated pathways between the amygdala
and the four target regions of the prefrontal cortex: the OFC, the
vmPFC, the dmPFC, and the dlPFC, (see Table 1 for FA means
separated by group). The calculated pathways of both hemi-
spheres did not show qualitative differences, so that the connec-
tions are exemplarily shown in the right hemisphere. The ventral
PFC regions (Fig. 2A,B) are connected with the amygdala via a
direct ventral pathway following the uncinated fascicle. Addi-
tionally, a strong indirect limbic connection was found. This
pathway followed the fornix and the temporopulvinar tract to the
posterior thalamic nuclei, continuing through the anterior tha-
lamic radiation to the frontal lobe. The latter connection was also
observed for the dorsal PFC regions (Fig. 2C,D). The dorsal re-
gions and the vmPFC also showed a connection with the
amygdala via the cingulum.
Multiple hierarchical regressions
There are correlations between use of reappraisal and trait anxi-
ety (r⫽⫺0.377; p0.008), but both of these variables did not
correlate with IQ (reappraisal: r⫽⫺0.130, p0.379; trait anx-
iety: r⫽⫺0.182, p0.216; all Pearson correlations). The inter-
correlations between trait anxiety and “reappraisal use” stress the
use of methods that take this intercorrelation into account, such
as regression analysis.
The results of the multiple hierarchical regression analyses
with factor trait anxiety group as the first predictor (right hemi-
sphere) will be reported first, followed by the results of the mul-
tiple hierarchical regression analyses with the factor reappraisal
use as the first predictor (left hemisphere).
The factor trait anxiety group (high trait anxiety vs low trait
anxiety) significantly predicted the FA values on the white matter
microstructure between the amygdala and the vmPFC (r0.350,
df 47, F6.441, T⫽⫺2.538, p0.015) and between the
amygdala and the OFC (r0.395, df 47, F8.520, T
2.919, p0.005), both in the right hemisphere (see Table 2 for
a list of all statistical parameters for all multiple hierarchical re-
Figure 1. A, Illustration of the manually created atlas applied in this study. B, Axial slice of one subject with one exemplary
probabilistic track that connects the amygdala with the prefrontal cortex. Voxels selected for the analysis (red) are located within
the probabilistic track (green) and the individual skeleton and have FA values higher than 0.4.
6022 J. Neurosci., April 15, 2015 35(15):6020 – 6027 Eden et al. Fiber Microstructure Predicts Anxiety Traits
gressions). The FA values on the right-hemispheric white matter
microstructure between the amygdala and the dmPFC (r0.215,
df 47, F2.240, T⫽⫺1,497, p0.141) or the dlPFC (r
0.209, df 47, F2.097, T⫽⫺1,448, p0.154) could not
significantly be predicted. In line with our hypotheses, the factor
reappraisal did not explain additional variance in this hemisphere
(vmPFC: r0.377, df 47, F3.731, T1.009, p0.318;
OFC: r0.397, df 47, F4.209, T⫽⫺0.266, p0.792;
Figure 2. A–D, Left, Three-dimensional sagittal and superior views of tracts between amygdala and PFC regions: A, orbitofrontal cortex; B, ventromedial PFC; C, dorsomedial PFC; D, dorsolateral
PFC. Renderings show the normalized number of tracts through each voxel (red). Seed and target regions are displayed in blue. For normalization, each voxel was divided by the amygdala’s size. E,
Slices illustrating the tracts’ localization from medial to lateral. The distance between slices is 5 mm.
Eden et al. Fiber Microstructure Predicts Anxiety Traits J. Neurosci., April 15, 2015 35(15):6020 – 6027 • 6023
dmPFC: r0.242, df 47, F1.405, T0.769, p0.446;
dlPFC: r0.252, df 47, F1.530, T0.982, p0.331) and
IQ (vmPFC: r0.429, df 47, F3.308, T⫽⫺1.502, p
0.140; OFC: r0.408, df 47, F2.923, T0.674, p0.504;
dmPFC: r0.247, df 47, F0.953, T⫽⫺0.322, p0.749;
dlPFC: r0.253, df 47, F1.005, T⫽⫺0.148, p0.883). As
expected, the alternative model with reappraisal as first factor did
not become significant in any of the four (right-hemispheric)
analyses.
The factor reappraisal significantly predicted the FA values
on the calculated white matter microstructure between the
amygdala and all four predefined PFC regions in the left hemi-
sphere (dmPFC: r0.306, df 47, F4.741, T2.177, p
0.035; dlPFC: r0.336, df 47, F5.854, T2.419, p0.020;
vmPFC: r0.331, df 47, F5.652, T2.377, p0.022;
OFC: r0.301, df 47, F4.591, T2.143, p0.037). The
addition of the factor anxiety group did not significantly increase
the explanation of variance in any of the regions (dmPFC: r
0.327, df 47, F2.686, T⫽⫺0.816, p0.419; dlPFC: r
0.377, df 47, F3.727, T⫽⫺1.238, p0.222; vmPFC:
r0.361, df 47, F3.364, T⫽⫺1.033 p0.307; OFC: r
0.326, df 47, F2.678, T⫽⫺0.887, p0.380) or IQ (dmPFC:
r0.336, df 47, F1.870, T⫽⫺0.564, p0.576; dlPFC: r
0.383, df 47, F2.521, T⫽⫺0.485, p0.630; vmPFC: r
0.367, df 47, F2.285, T⫽⫺0.491, p0.626; OFC: r0.382,
df 47, F2.512, T⫽⫺1.433, p0.159). As hypothesized, the
alternative model with trait anxiety entering as first factor did not
reveal any effects.
Discussion
We investigated the microstructural properties of pathway con-
nections between the amygdala and PFC regions deemed relevant
for anxiety and emotion regulation. The results provide direct
evidence for stronger connectivity between amygdala and
vmPFC and OFC of the right hemisphere in persons with low
trait anxiety. Emotion regulation was expressed as stronger con-
nectivity between amygdala and vmPFC, OFC, dmPFC, and
dlPFC of the left hemisphere in persons with high reappraisal use.
We collected diffusion-weighted images (dMRI) and applied
probabilistic tractography to compute all tracks between
amygdala and PFC regions individually for both hemispheres.
The resulting white matter circuitry included (parts of) the unci-
nate fasciculus, cingulum, fornix, anterior thalamic radiation,
and inferior fronto-occipital fasciculus. Strong connectivity via
the uncinate fasciculus was observed for the pathways to vmPFC
and OFC, which was neither seen in the pathway network to
dlPFC nor to dmPFC. These connections, especially to vmPFC,
fit with findings from dMRI studies on humans and animals
(Croxson et al., 2005;Carlson et al., 2013;Jbabdi et al., 2013) and
with anatomical studies that reported extensive anatomical con-
nections between the amygdala and the PFC. For instance, in rats
and monkeys, it was shown that the amygdala is connected to
prefrontal cortex by direct amygdalo-cortical projections (Nauta,
1961;Krettek and Price, 1974,1977a), and indirectly via the thal-
amus (Nauta, 1962;Krettek and Price, 1974,1977a,b). In rhesus
monkeys, the ventromedial region of PFC receives both direct
and indirect tracts stemming from the amygdala, but the dorso-
lateral PFC does not get such input (Porrino et al., 1981). These
findings suggested that the ventromedial region may be regarded
as the “limbic portion of the frontal association cortex.” The
longer, presumably indirect routes found in our study have not
been focused on and rarely have been addressed in human dMRI
studies on emotion processing or anxiety. Reviewing the role of
the PFC in emotion– cognition interactions, Ray and Zald (2012)
emphasized that studies on nonhuman primates reveal large vari-
ability concerning direct projections between the amygdalae and
regions of the PFC and that direct projections between amygdala
and dlPFC are “extremely weak”. It may thus be surprising that
we find such strong connections between amygdala and prefron-
tal regions. However, there is ample evidence for indirect path-
ways, most notably through the thalamus, in both animals and
humans.
Recent research using tractography in humans provided fur-
ther evidence for strong connections between hippocampus/
amygdala and thalamus. The amygdala connects with the
anterior thalamus via the fornix and uncinate fasciculus and with
the pulvinar via the temporopulvinar tract (Zarei et al., 2010).
Similarly, Linke et al. (2012) reported indirect pathways from the
amygdala to the OFC, namely via the anterior and posterior thal-
ami. Note that these studies did not specifically target the con-
nection between the amygdala and prefrontal regions.
With multiple hierarchical regressions, we analyzed the rela-
tionship of these determined fiber connections with trait anxiety
and reappraisal use by means of hypothesis-driven, hemisphere-
specific models. Given accumulating evidence for an asymmetric
involvement of the PFC, with a right-hemispheric dominance for
anxiety and anxiety-related processes (Stewart et al., 1988;Her-
mann et al., 1992;Hellige, 1993;O’Carroll et al., 1993;Petruzzello
Table 2. Significant relationships between trait anxiety, reappraisal use, IQ, and
fractional anisotropy values of pathway microstructure between amygdala and
prefrontal cortex regions
ROI Model R
2
Cor. R
2
FTA
R
IQ
Right dmPFC TA 0.05 0.03 2.24 0.22
TA, R 0.06 0.02 1.41 0.17 0.12
TA, R, IQ 0.06 0.00 0.95 0.18 0.12 0.05
R 0.03 0.01 1.56 0.18
Right dlPFC TA 0.04 0.02 2.10 0.21
TA, R 0.06 0.02 1.53 0.16 0.15
TA, R, IQ 0.06 0.00 1.01 0.16 0.15 0.02
R 0.04 0.02 2.06 0.21
Right vmPFC TA 0.12 0.10 6.44* 0.35*
TA, R 0.14 0.10 3.73* 0.30 0.15
TA, R, IQ 0.18 0.13 3.31* 0.34* 0.16 0.21
R 0.07 0.05 3.21 0.26
Right OFC TA 0.16 0.14 8.52** 0.40**
TA, R 0.16 0.12 4.21* 0.41** 0.04
TA, R, IQ 0.17 0.11 2.92* 0.39* 0.04 0.10
R 0.01 0.01 0.54 0.11
Left dmPFC R 0.09 0.07 4.74* 0.31*
R, TA 0.11 0.07 2.69 0.12 0.26
R, TA, IQ 0.11 0.05 1.87 0.14 0.27 0.08
TA 0.05 0.03 2.27 0.22
Left dlPFC R 0.11 0.09 5.85* 0.34*
R, TA 0.14 0.10 3.73* 0.18 0.27
R, TA, IQ 0.15 0.09 2.52 0.20 0.28 0.07
TA 0.08 0.06 3.91 0.28
Left vmPFC R 0.11 0.09 5.65* 0.33*
R, TA 0.13 0.09 3.36* 0.15 0.28
R, TA, IQ 0.14 0.08 2.29 0.17 0.28 0.07
TA 0.06 0.04 3.13 0.25
Left OFC R 0.09 0.07 4.59* 0.30*
R, TA 0.11 0.07 2.68 0.13 0.25
R, TA, IQ 0.15 0.09 2.51 0.17 0.27 0.20
TA 0.05 0.03 2.44 0.22
Model parameters for each predictor variable for hierarchical regression analyses are shown. Dependent variables
are fractional anisotropy values of pathway microstructure between amygdala and prefrontal cortex regions. ROI,
Region of interest; TA, trait anxiety; R, reappraisal use. *p0.05; **p0.01.
6024 J. Neurosci., April 15, 2015 35(15):6020 – 6027 Eden et al. Fiber Microstructure Predicts Anxiety Traits
and Landers, 1994;Lucey et al., 1995;Stapleton et al., 1997;Brem-
ner et al., 1999;Nitschke et al., 1999;Wiedemann et al., 1999;
Davidson et al., 2000;Davidson, 2002;Pizzagalli et al., 2002;Smit
et al., 2007,Harmon-Jones et al., 2010), we expected our struc-
tural trait anxiety effects to be particularly visible in the right
hemisphere. Based on evidence for a left-hemispheric lateraliza-
tion of reappraisal use (Ochsner et al., 2002;Jackson et al., 2003;
Kim and Bell, 2006) and recently observed left-sided biases of
metabolic activity in the superior frontal gyrus in frequent reap-
praisers (Kim et al., 2012), we expected reappraisal use effects to
be most prominent in the left hemisphere. We set up the hierar-
chies of the multiple regression analysis accordingly, with trait
anxiety as the first factor in the analyses of the right hemisphere
and with reappraisal use as the first factor for the left hemisphere.
The following methodological details are important to con-
sider. First, we chose a hypothesis-based approach, analyzing the
microstructure of only those tracts to PFC regions that have con-
sistently been associated with emotion-related processes. Differ-
ent from prior studies, all tracks, including longer pathways
between the two structures, were considered. We calculated the
tracts for subsequent FA analysis on our sample, not relying on
data from thematically different experimental contexts. This is
more conservative than a whole-brain approach, where significant
regions are selected, analyzed, and interpreted post hoc. Second, we
also adopted the hypothesis-based approach in the statistical analy-
sis. As mentioned above, anxiety and use of reappraisal is related to
hemisphere-specific networks. Whereas anxiety is primarily (but not
exclusively) related to processes of right-hemispheric amygdala and
PFC (Reiman et al., 1984;Heller et al., 1995), emotion regulation is
primarily associated with left-hemispheric processing in these
structures (Wheeler et al., 1993;Jackson et al., 2003;Kim and Bell,
2006;Kim et al., 2012). This differential hemispheric involve-
ment in different aspects of emotion processing and regulation
supports the hypotheses by Davidson and colleagues (Davidson
et al., 1987,1990,2000;Davidson and Tomarken, 1989;David-
son, 1992,1995,2002;Sutton and Davidson, 1997). In low trait-
anxious persons, there was no higher FA in pathways to the
dorsomedial and the dorsolateral part of the PFC. One reason
might be that the amygdalar inhibition by these PFC regions
operates via general mechanisms, such as changes in the neu-
rotransmitter system. Such mechanisms might not be reflected in
FA values of connecting pathways (Ray and Zald, 2012). An al-
ternative explanation is that our atlas comprised comparably
wide boundaries around the dmPFC and the dlPFC. Although
this was deliberately done as not to miss potentially important
fibers, it could have led to an attenuation of the expected effect.
Some caveats and open questions should be addressed in fu-
ture studies. First, we probabilistically tracked fiber pathways
from amygdala to PFC within each hemisphere, focusing on non-
crossing fibers. However, animal studies have shown that a small
percentage of connecting fibers between the amygdala and the
PFC crosses the corpus callosum (Mascagni et al., 1993;McDon-
ald and Mascagni, 1996). A second caveat concerns the origin of
the calculated fibers within the amygdala. We mapped the
amygdala in each participant and treated the entire amygdala as
seed region. Yet, the amygdala is a heterogeneous structure, with
various substructures and nuclei (Sah et al., 2003), each with
different functions and connections with different areas in the
brain. It is thus a challenge for future DTI studies to differentiate
connections between amygdala substructures and regions of the
PFC. Third, because women are especially prone to develop anx-
iety disorders (see Somers et al., 2006) and to avoid additional
variance attributable to existing brain-activation differences be-
tween men and women (Gong et al., 2011), we included only
female persons. Studies revealed the sexually dimorphic nature of
the cortex, limbic structures, and connecting fibers and how such
sex differences might impact the development of affective disor-
ders (for review, see Cahill, 2006). Zuurbier et al. (2013) observed
correlations between reappraisal and FA values in the left frontal
part of uncinate fasciculus in women, but not in men. Thus, it is
likely that at least some of the connections between amygdala and
PFC reported here cannot easily be transferred to men.
Although our results have to be interpreted within the con-
straints of the above-mentioned limitations, we believe that our
data make an important contribution to the understanding of the
neuroanatomical basis of anxiety and emotion regulation. Our
findings provide strong support for theories of and (fMRI) stud-
ies on top-down inhibition, by offering a structural network that
might underlie the so far mostly theoretically, behaviorally, and
functionally argued/established network.
Our data show that different structural networks are respon-
sible for trait anxiety and reappraisal use. Neural models on the
generation and regulation of emotions stress the importance of
the interplay between automatic and voluntary processes (e.g.,
use of reappraisal; Ochsner and Gross, 2007;Phillips et al., 2008)
and emphasize the role of the amygdala and PFC regions (partic-
ularly OFC) for this interplay. The attempt to study voluntary
and automatic processes in separation may seem futile (Phillips et
al., 2008), especially in therapeutic settings. Nevertheless, we
identified a hemispherically specialized functional architecture
involved in the mediation of anxiety and reappraisal use, with
stronger connectivity between amygdala, OFC, and vmPFC in
each hemisphere. Given the correlational nature of these data, we
cannot make claims about the development of the relationship. It
is a challenge for future research to investigate how manipulating
one of these processes [e.g., using the anxiolytic effects of nonin-
vasive brain stimulation (Zwanzger et al., 2009)] impacts on the
other, especially on the microstructure involved. Such investiga-
tions might help to develop new strategies for the treatment of
anxiety disorders and to identify persons at risk.
References
Ackenheil M, Stotz G, Dietz-Bauer R, Vossen A (1999) Deutsche Fassung
des Mini-International Neuropsychiatric Interview. Mu¨nchen: Psychia-
trische Universita¨tsklinik Mu¨nchen.
Avants BB, Epstein CL, Grossman M, Gee JC (2008) Symmetric diffeomorphic
image registration with cross-correlation: evaluating automated labeling of
elderly and neurodegenerative brain. Med Image Anal 12:26–41. CrossRef
Medline
Barbas H, Zikopoulos B (2006) Sequential and parallel circuits for emo-
tional processing in primate orbitofrontal cortex. In: The orbitofrontal
cortex (Zald DH, Rauch SL, eds), pp 57–91. Oxford: Oxford UP.
Basser PJ, Pierpaoli C (1996) Microstructural and physiological features of
tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson
111:209–219.
Baur V, Ha¨nggi J, Langer N, Ja¨ncke L (2013a) Resting-state functional and
structural connectivity within an insula–amygdala route specifically in-
dex state and trait anxiety. Biol Psychiatry 73:85–92. CrossRef Medline
Baur V, Bru¨hl AB, Herwig U, Eberle T, Rufer M, Delsignore A, Ja¨ncke L,
Ha¨nggi J (2013b) Evidence of frontotemporal structural hypoconnec-
tivity in social anxiety disorder: a quantitative fiber tractography study.
Hum Brain Mapp 34:437–446. CrossRef Medline
Behrens TE, Berg HJ, Jbabdi S, Rushworth MF, Woolrich MW (2007) Prob-
abilistic diffusion tractography with multiple fibre orientations: what can
we gain? Neuroimage 34:144–155. CrossRef Medline
Bishop SJ (2007) Neurocognitive mechanisms of anxiety: an integrative ac-
count. Trends Cogn Sci 11:307–316. CrossRef Medline
Bremner JD, Staib LH, Kaloupek D, Southwick SM, Soufer R, Charney DS
(1999) Neural correlates of exposure to traumatic pictures and sound in
combat veterans with and without posttraumatic stress disorder: a posi-
Eden et al. Fiber Microstructure Predicts Anxiety Traits J. Neurosci., April 15, 2015 35(15):6020 – 6027 • 6025
tron emission tomography study. Biol Psychiatry 45:806–816. CrossRef
Medline
Buckholtz JW, Callicott JH, Kolachana B, Hariri AR, Goldberg TE, Gender-
son M, Egan MF, Mattay VS, Weinberger DR, Meyer-Lindenberg A
(2008) Genetic variation in MAOA modulates ventromedial prefrontal
circuitry mediating individual differences in human personality. Mol Psy-
chiatry 13:313–324. CrossRef Medline
Cahill L (2006) Why sex matters for neuroscience. Nat Rev Neurosci 7:477–
484. CrossRef Medline
Carlson JM, Cha J, Harmon-Jones E, Mujica-Parodi LR, Hajcak G (2013)
Influence of the BDNF genotype on amygdalo-prefrontal white matter
microstructure is linked to nonconscious attention bias to threat. Cereb
Cortex 24:2249–2257. CrossRef Medline
Croxson PL, Johansen-Berg H, Behrens TE, Robson MD, Pinsk MA, Gross
CG, Richter W, Richter MC, Kastner S, Rushworth MF (2005) Quanti-
tative investigation of connections of the prefrontal cortex in the human
and macaque using probabilistic diffusion tractography. J Neurosci 25:
8854–8866. CrossRef Medline
Davidson RJ (1992) Anterior cerebral asymmetry and the nature of emo-
tion. Brain Cogn 20:125–151. CrossRef Medline
Davidson RJ (1995) Cerebral asymmetry, emotion and affective style. In:
Brain asymmetry (Davidson RJ, Hugdahl K, eds), pp 361–387. Cam-
bridge, MA: MIT.
Davidson RJ (2002) Anxiety and affective style: role of prefrontal cortex and
amygdala. Biol Psychiatry 51:68–80. CrossRef Medline
Davidson RJ, Tomarken AJ (1989) Laterality and emotion: an electrophys-
iological approach. Handb Neuropsychol 3:419–441.
Davidson RJ, Mednick D, Moss E, Saron C, Schaffer CE (1987) Ratings of
emotion in faces are influenced by the visual field to which stimuli are
presented. Brain Cogn 6:403–411. CrossRef Medline
Davidson RJ, Ekman P, Saron CD, Senulis JA, Friesen WV (1990)
Approach-withdrawal and cerebral asymmetry: emotional expression
and brain physiology: I. J Pers Soc Psychol 58:330 –341. CrossRef Medline
Davidson RJ, Jackson DC, Kalin NH (2000) Emotion, plasticity, context,
and regulation: perspectives from affective neuroscience. Psychol Bull
126:890–909. CrossRef Medline
Faria AV, Zhang J, Oishi K, Li X, Jiang H, Akhter K, Hermoye L, Lee SK, Hoon
A, Stashinko E, Miller MI, van Zijl PC, Mori S (2010) Atlas-based anal-
ysis of neurodevelopment from infancy to adulthood using diffusion ten-
sor imaging and applications for automated abnormality detection.
Neuroimage 52:415–428. CrossRef Medline
Gong G, He Y, Evans AC (2011) Brain connectivity gender makes a differ-
ence. Neuroscientist 17:575–591. CrossRef Medline
Gross JJ, John OP (2003) Individual differences in two emotion regulation
processes: implications for affect, relationships, and well-being. J Pers Soc
Psychol 85:348–362. CrossRef Medline
Harmon-Jones E, Gable PA, Peterson CK (2010) The role of asymmetric
frontal cortical activity in emotion-related phenomena: a review and up-
date. Biol Psychol 84:451–462. CrossRef Medline
Heller W, Etienne MA, Miller GA (1995) Patterns of perceptual asymmetry
in depression and anxiety: implications for neuropsychological models of
emotion and psychopathology. J Abnorm Psychol 104:327–333. CrossRef
Medline
Hellige JB (1993) Hemispheric asymmetry: what’s right and what’s left.
Cambridge, MA: Harvard UP.
Hermann BP, Wyler AR, Blumer D, Richey ET (1992) Ictal fear: lateralizing
significance and implications for understanding the neurobiology of
pathological fear states. Neuropsychiatry Neuropsychol Behav Neurol
5:205–210.
Jackson DC, Mueller CJ, Dolski I, Dalton KM, Nitschke JB, Urry HL, Rosen-
kranz MA, Ryff CD, Singer BH, Davidson RJ (2003) Now you feel it,
now you don’t: frontal brain electrical asymmetry and individual differ-
ences in emotion regulation. Psychol Sci 14:612–617. CrossRef Medline
Jbabdi S, Lehman JF, Haber SN, Behrens TE (2013) Human and monkey
ventral prefrontal fibers use the same organizational principles to reach
their targets: tracing versus tractography. J Neurosci 33:3190–3201.
CrossRef Medline
Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM (2012)
FSL. Neuroimage 62:782–790. CrossRef Medline
Kim KJ, Bell MA (2006) Frontal EEG asymmetry and regulation during
childhood. Ann N Y Acad Sci 1094:308–312. CrossRef Medline
Kim MJ, Whalen PJ (2009) The structural integrity of an amygdala–pre-
frontal pathway predicts trait anxiety. J Neurosci 29:11614–11618.
CrossRef Medline
Kim MJ, Gee DG, Loucks RA, Davis FC, Whalen PJ (2010) Anxiety dissoci-
ates dorsal and ventral medial prefrontal cortex functional connectivity
with the amygdala at rest. Cereb Cortex 21:1667–1673. CrossRef Medline
Kim SH, Hamann S (2007) Neural correlates of positive and negative emo-
tion regulation. J Cogn Neurosci 19:776–798. CrossRef Medline
Kim SH, Cornwell B, Kim SE (2012) Individual differences in emotion reg-
ulation and hemispheric metabolic asymmetry. Biol Psychol 89:382–386.
CrossRef Medline
Krettek JE, Price JL (1974) A direct input from the amygdala to the thalamus
and the cerebral cortex. Brain Res 67:169–174. CrossRef Medline
Krettek JE, Price JL (1977a) The cortical projections of the mediodorsal
nucleus and adjacent thalamic nuclei in the rat. J Comp Neurol: 171:157–
191. CrossRef Medline
Krettek JE, Price JL (1977b) Projections from the amygdaloid complex to
the cerebral cortex and thalamus in the rat and cat. J Comp Neurol 172:
687–722. CrossRef Medline
Linke J, Witt SH, King AV, Nieratschker V, Poupon C, Gass A, Hennerici MG,
Rietschel M, Wessa M (2012) Genome-wide supported risk variant for
bipolar disorder alters anatomical connectivity in the human brain. Neu-
roimage, 59:3288–3296. CrossRef Medline
Lohmann G, Mueller K, Bosch V, Mentzel H, Hessler S, Chen L, Zysset S, von
Cramon DY (2001) Lipsia–a new software system for the evaluation of
functional magnetic resonance images of the human brain. Comput Med
Imaging Graph 25:449–457. CrossRef Medline
Lucey JV, Costa DC, Blanes T, Busatto GF, Pilowsky LS, Takei N, Marks IM,
Ell PJ, Kerwin RW (1995) Regional cerebral blood flow in obsessive-
compulsive disordered patients at rest. Differential correlates with
obsessive-compulsive and anxious-avoidant dimensions. Br J Psychiatry
167:629–634. CrossRef Medline
Mascagni F, McDonald AJ, Coleman JR (1993) Corticoamygdaloid and cor-
ticocortical projections of the rat temporal cortex: a Phaseolus vulgaris
leucoagglutinin study. Neuroscience 57:697–715. CrossRef Medline
McDonald AJ, Mascagni F (1996) Cortico-cortical and cortico-amygdaloid
projections of the rat occipital cortex: a Phaseolus vulgaris leucoaggluti-
nin study. Neuroscience 71:37–54. CrossRef Medline
Modi S, Trivedi R, Singh K, Kumar P, Rathore RK, Tripathi RP, Khushu S
(2013) Individual differences in trait anxiety are associated with white
matter tract integrity in fornix and uncinate fasciculus: preliminary evi-
dence from a DTI based tractography study. Behav Brain Res 238:188
192. CrossRef Medline
Nauta WJ (1961) Fibre degeneration following lesions of the amygdaloid
complex in the monkey. J Anat 95:515–531. Medline
Nauta WJ (1962) Neural associations of the amygdaloid complex in the
monkey. Brain 85:505–520. CrossRef Medline
Nitschke JB, Heller W, Palmieri PA, Miller GA (1999) Contrasting patterns
of brain activity in anxious apprehension and anxious arousal. Psycho-
physiology 36:628–637. CrossRef Medline
O’Carroll RE, Moffoot AP, Van Beck M, Dougall N, Murray C, Ebmeier KP,
Goodwin GM (1993) The effect of anxiety induction on the regional
uptake of 99mTc-Exametazime in simple phobia as shown by single pho-
ton emission tomography (SPET). J Affect Disord 28:203–210. CrossRef
Medline
Ochsner KN, Gross JJ (2007) The neural architecture of emotion regulation.
Handbook Emot Regul 1:87–109.
Ochsner KN, Bunge SA, Gross JJ, Gabrieli JDE (2002) Rethinking feelings:
an FMRI study of the cognitive regulation of emotion. J Neurosci 14:
1215–1229. CrossRef Medline
Ochsner KN, Ray RD, Cooper JC, Robertson ER, Chopra S, Gabrieli JD, Gross
JJ (2004) For better or for worse: neural systems supporting the cogni-
tive down- and up-regulation of negative emotion. Neuroimage 23:483–
499. CrossRef Medline
Oishi K, Faria A, Jiang H, Li X, Akhter K, Zhang J, Hsu JT, Miller MI, van Zijl
PC, Albert M, Lyketsos CG, Woods R, Toga AW, Pike GB, Rosa-Neto P,
Evans A, Mazziotta J, Mori S (2009) Atlas-based whole brain white mat-
ter analysis using large deformation diffeomorphic metric mapping: ap-
plication to normal elderly and Alzheimer’s disease participants.
Neuroimage 46:486–499. CrossRef Medline
Oldfield RC (1971) The assessment and analysis of handedness: The Edin-
burgh inventory. Neuropsychologia 9:97–113. CrossRef Medline
Petrides M, Mackey S (2006) The orbitofrontal cortex: sulcal and gyral mor-
6026 J. Neurosci., April 15, 2015 35(15):6020 – 6027 Eden et al. Fiber Microstructure Predicts Anxiety Traits
phology and architecture. In: The orbitofrontal cortex (Zald DH, Rauch
SL, eds), pp 19–37. Oxford: Oxford UP.
Petruzzello SJ, Landers DM (1994) State anxiety reduction and exercise:
does hemispheric activation reflect such changes? Med Sci Sports Exer
26:1028–1035. Medline
Pezawas L, Meyer-Lindenberg A, Drabant EM, Verchinski BA, Munoz KE,
Kolachana BS, Egan MF, Mattay VS, Hariri AR, Weinberger DR (2005)
5-HTTLPR polymorphism impacts human cingulate-amygdala interac-
tions: a genetic susceptibility mechanism for depression. Nat Neurosci
8:828–834. CrossRef Medline
Phillips ML, Ladouceur CD, Drevets WC (2008) A neural model of volun-
tary and automatic emotion regulation: implications for understanding
the pathophysiology and neurodevelopment of bipolar disorder. Mol
Psychiatry 13:833–857. CrossRef Medline
Pizzagalli DA, Nitschke JB, Oakes TR, Hendrick AM, Horras KA, Larson CL,
Abercrombie HC, Schaefer SM, Koger JV, Benca RM, Pascual-Marqui
RD, Davidson RJ (2002) Brain electrical tomography in depression: the
importance of symptom severity, anxiety and melancholic features. Biol
Psychiatry 52:73–85. CrossRef Medline
Porrino LJ, Crane AM, Goldman-Rakic PS (1981) Direct and indirect path-
ways from the amygdala to the frontal lobe in rhesus monkeys. J Comp
Neurol 198:121–136. CrossRef Medline
Rauch SL, Savage CR, Alpert NM, Fischman AJ, Jenike MA (1997) The
functional neuroanatomy of anxiety: a study of three disorders using
positron emission tomography and symptom provocation. Biol Psychia-
try 42:446–452. CrossRef Medline
Ray RD, Zald DH (2012) Anatomical insights into the interaction of emo-
tion and cognition in the prefrontal cortex. Neurosci Biobehav Rev 36:
479–501. CrossRef Medline
Reiman EM, Raichle ME, Butler FK, Herscovitch P, Robins E (1984) A focal
brain abnormality in panic disorder, a severe form of anxiety. Nature
310:683–685. CrossRef Medline
Roy M, Shohamy D, Wager TD (2012) Ventromedial prefrontal-subcortical
systems and the generation of affective meaning. Trends Cogn Sci 16:147–
156. CrossRef Medline
Sah P, Faber ES, Lopez De Armentia M, Power J (2003) The amygdaloid
complex: anatomy and physiology. Physiol Rev 83:803–834. CrossRef
Medline
Schmithorst VJ, Wilke M, Dardzinski BJ, Holland SK (2005) Cognitive
functions correlate with white matter architecture in a normal pediatric
population: a diffusion tensor MRI study. Hum Brain Mapp 26:139 –147.
CrossRef Medline
Sladky R, Ho¨ flich A, Atanelov J, Kraus C, Baldinger P, Moser E, Lanzenberger
R, Windischberger C (2012) Increased neural habituation in the
amygdala and orbitofrontal cortex in social anxiety disorder revealed by
fMRI. PLoS One 7:e50050. CrossRef Medline
Smit DJ, Posthuma D, Boomsma DI, De Geus EJ (2007) The relation be-
tween frontal EEG asymmetry and the risk for anxiety and depression.
Biol Psychol 74:26–33. CrossRef Medline
Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE,
Johansen-Berg H, Bannister PR, Luca M de, Drobnjak I, Flitney DE, Niazy
RK, Saunders J, Vickers J, Zhang Y, Stefano N de, Brady JM, Matthews PM
(2004) Advances in functional and structural MR image analysis and
implementation as FSL. Neuroimage 23 [Suppl 1]:S208–S219.
Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay
CE, Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TE
(2006) Tract-based spatial statistics: voxelwise analysis of multi-subject
diffusion data. Neuroimage 31:1487–1505. CrossRef Medline
Snook L, Plewes C, Beaulieu C (2007) Voxel based versus region of interest
analysis in diffusion tensor imaging of neurodevelopment. Neuroimage
34:243–252. CrossRef Medline
Solano-Castiella E, Anwander A, Lohmann G, Weiss M, Docherty C, Geyer S,
Reimer E, Friederici AD, Turner R (2010) Diffusion tensor imaging seg-
ments the human amygdala in vivo. Neuroimage, 49:2958–2965.
CrossRef Medline
Somers JM, Goldner EM, Waraich P, Hsu L (2006) Prevalence and inci-
dence studies of anxiety disorders: a systematic review of the literature.
Can J Psychiatry 51:100–113. Medline
Spielberger CD, Jacobs G, Russell S, Crane RS (1983) Assessment of anger:
the State-Trait Anger Scale. In: Advances in personality assessment, Vol 2
(Butcher JN, Spielberger CD, eds), pp 161–185. Mahwah, NJ: Lawrence
Erlbaum Associates.
Stapleton JM, Morgan MJ, Liu X, Yung BC, Phillips RL, Wong DF, Shaya EK,
Dannals RF, London ED (1997) Cerebral glucose utilization is reduced
in second test session. J Cereb Blood Flow Metab 17:704–712. Medline
Stein MB, Simmons AN, Feinstein JS, Paulus MP (2007) Increased
amygdala and insula activation during emotion processing in anxiety-
prone subjects. Am J Psychiatry 164:318–327. CrossRef Medline
Stewart RS, Devous MD Sr, Rush AJ, Lane L, Bonte FJ (1988) Cerebral blood
flow changes during sodium-lactate-induced panic attacks. Am J Psychi-
atry 145:442–449. CrossRef Medline
Sutton SK, Davidson RJ (1997) Prefrontal brain asymmetry: a biological
substrate of the behavioral approach and inhibition systems. Psychol Sci
8:204–210. CrossRef
Von Aster M, Neubauer A, Horn R (2006) Wechsler Intelligenztest fu¨r
Erwachsene (WIE). Deutschsprachige Bearbeitung und Adaptation des
WAIS-III von David Wechsler. Frankfurt/Main, Germany: Harcourt Test
Services.
Wheeler RE, Davidson RJ, Tomarken AJ (1993) Frontal brain asymmetry
and emotional reactivity: a biological substrate of affective style. Psycho-
physiology 30:82–89. Medline
Wiedemann G, Pauli P, Dengler W, Lutzenberger W, Birbaumer N, Buchkre-
mer G (1999) Frontal brain asymmetry as a biological substrate of emo-
tions in patients with panic disorders. Arch Gen Psychiatry 56:78–84.
CrossRef Medline
Woolrich MW, Jbabdi S, Patenaude B, Chappell M, Makni S, Behrens T,
Beckmann C, Jenkinson M, Smith SM (2009) Bayesian analysis of neu-
roimaging data in FSL. Neuroimage 45:S173–S186. CrossRef Medline
Zald DH, Kim SW (1996a) Anatomy and function of the orbital frontal
cortex: I. Anatomy, neurocircuitry, and obsessive-compulsive disorder.
J Neuropsychiatry Clin Neurosci 8:125–138. CrossRef Medline
Zald DH, Kim SW (1996b) Anatomy and function of the orbital frontal
cortex, II: Function and relevance to obsessive-compulsive disorder.
J Neuropsychiatry Clin Neurosci 8:249–261. CrossRef Medline
Zarei M, Patenaude B, Damoiseaux J, Morgese C, Smith S, Matthews PM,
Barkhof F, Rombouts SA, Sanz-Arigita E, Jenkinson M (2010) Combin-
ing shape and connectivity analysis: an MRI study of thalamic degenera-
tion in Alzheimer’s disease. Neuroimage 49:1–8. CrossRef Medline
Zuurbier LA, Nikolova YS, Åhs F, Hariri AR (2013) Uncinate fasciculus
fractional anisotropy correlates with typical use of reappraisal in women
but not men. Emotion 13:385–390. CrossRef Medline
Zwanzger P, Fallgatter AJ, Zavorotnyy M, Padberg F (2009) Anxiolytic ef-
fects of transcranial magnetic stimulation—an alternative treatment op-
tion in anxiety disorders? J Neural Transm 116:767–775. CrossRef
Medline
Eden et al. Fiber Microstructure Predicts Anxiety Traits J. Neurosci., April 15, 2015 35(15):6020 – 6027 • 6027
... We note that some other studies have failed to find a meaningful relationship between white matter integrity and the Big Five dimensions 54,58,70 or the BIS/BAS 71 . By contrast, the association between the habitual use of cognitive reappraisal and white matter integrity has been rather consistent, implicating the UNC [72][73][74][75] and the CNG 72,73 . Given the above-reported correlates for isolated personality characteristics, we expected the implication of these areas in our profile study, too. ...
... We note that some other studies have failed to find a meaningful relationship between white matter integrity and the Big Five dimensions 54,58,70 or the BIS/BAS 71 . By contrast, the association between the habitual use of cognitive reappraisal and white matter integrity has been rather consistent, implicating the UNC [72][73][74][75] and the CNG 72,73 . Given the above-reported correlates for isolated personality characteristics, we expected the implication of these areas in our profile study, too. ...
Article
Full-text available
We investigated the white matter correlates of personality profiles predictive of subjective well-being. Using principal component analysis to first determine the possible personality profiles onto which core personality measures would load, we subsequently searched for whole-brain white matter correlations with these profiles. We found three personality profiles that correlated with the integrity of white matter tracts. The correlates of an “optimistic” personality profile suggest (a) an intricate network for self-referential processing that helps regulate negative affect and maintain a positive outlook on life, (b) a sustained capacity for visually tracking rewards in the environment and (c) a motor readiness to act upon the conviction that desired rewards are imminent. The correlates of a “short-term approach behavior” profile was indicative of minimal loss of integrity in white matter tracts supportive of lifting certain behavioral barriers, possibly allowing individuals to act more outgoing and carefree in approaching people and rewards. Lastly, a “long-term approach behavior” profile’s association with white matter tracts suggests lowered sensitivity to transient updates of stimulus-based associations of rewards and setbacks, thus facilitating the successful long-term pursuit of goals. Together, our findings yield convincing evidence that subjective well-being has its manifestations in the brain.
... The amygdala and ventral prefrontal cortex-amygdala network play a key role in mood regulation in bipolar disorder 16 and the regulation of fear and anxiety. 17 However, studies on treatment for comorbid panic disorder and bipolar disorder are scarce, and treatment guidelines are based on a small number of studies with low levels of evidence. 18 The lack of effective interventions to manage anxiety symptoms may lead clinicians to prescribe more benzodiazepines or patients to self-medicate more (e.g., with alcohol). ...
Article
Anxiety disorders are the most common comorbid psychiatric disorders in patients with bipolar disorder. Managing anxiety symptoms in comorbid conditions is challenging and has received little research interest. The findings from preclinical research on fear conditioning, an animal model of anxiety disorder, have suggested that memory reconsolidation updating (exposure-based therapy) combined with valproate might facilitate the amelioration of fear memories. Here, three cases of successful amelioration of agoraphobia and panic symptoms through valproate adjuvant therapy for cognitive behavioral therapy in patients who failed to respond to two to three consecutive standard pharmacotherapy trials over several years are described. To the best of the author’s knowledge, this is the first attempt to combine CBT with valproate in patients with panic disorder, agoraphobia, and comorbid bipolar disorder. Additionally, the background preclinical research on this combination therapy based on the reconsolidation-updating mechanism, the inhibition of histone deacetylase 2, and critical period reopening, off-label use of valproate in panic disorder, plasticity-augmented psychotherapy, and how to combine valproate with CBT is discussed.
... Moreover, it has been argued how gender differences could impact on different brain structures development (Cahill, 2006), and could be reflected even in different neural activity linked to ER processes Gong et al., 2011). In addition, investigating psychological functioning among same-gender individuals is a well-established practice (e.g., see Harned et al., 2010;Gratz et al., 2015;Krause-Utz et al., 2019), even in neuroscientific literature (e.g., see Eden et al., 2015). Taken together, these evidences seem to confirm gender differences in different features of ER skills, thus supporting our choice in adopting a gender-homogenous sample. ...
Article
Emotion regulation (ER) is a core element for individual well-being, and dysregulated emotional states are prominent in several mental disorders. Moreover, dispositional use of adaptive ER strategies, such as cognitive reappraisal, is usually associated to better psychological outcomes and less emotional problems. Thus, identifying markers of emotion dysregulation could serve as a key point for developing treatments against risks of psychopathological outcomes. Neuroimaging techniques could represent a useful tool within these aims, focusing on neurobiological markers of psychopathological illness. Given the well known gender differences in using ER strategies, we examined behavioral and neuroimaging patterns associated with dispositional use of reappraisal among a non-clinical female sample. We found that the individual predisposition to use cognitive reappraisal as an emotion regulation strategy was associated with decreased levels of dysregulation. From a neurobiological perspective, difficulties in using reappraisal were associated with decreased resting-state functional connectivity (rs-FC) between the Middle Temporal Gyrus and occipito-parietal regions. Moreover, rs-FC between prefrontal and occipito-parietal brain regions was negatively associated with emotion dysregulation levels. Microstructural anomalies across white matter tracts connecting temporal, parietal, and occipital brain regions were associated to difficulties in using reappraisal. Our findings suggest that specific behavioral and neurobiological substrates are linked to reappraising abilities. Furthermore, the ability to implement adaptive ER strategies could serve as protective factor against developing emotion dysregulation.
... While many studies have examined WM pathways in adults with high trait anxiety and ADs [13][14][15][16][17][18][19][20][21][22][23], considerably less work has examined WM in anxious youth [24][25][26][27][28][29]. Given evidence linking prefrontal-limbic pathways to anxiety [21,25,[30][31][32][33][34][35][36], our prior work focused on the uncinate fasciculus (UF), the major WM pathway linking prefrontal regions to temporal lobe structures, including the amygdala and anterior hippocampus [37,38]. These studies demonstrated anxiety-related reductions in UF fractional anisotropy (FA), a measure of WM microstructural integrity, in adults, preadolescent children, and preadolescent non-human primates (NHPs) [21,25,39]. ...
Article
Full-text available
Pathological anxiety typically emerges during preadolescence and has been linked to alterations in white matter (WM) pathways. Because myelination is critical for efficient neuronal communication, characterizing associations between WM microstructure and symptoms may provide insights into pathophysiological mechanisms associated with childhood pathological anxiety. This longitudinal study examined 182 girls enrolled between the ages of 9–11 that were treatment-naïve at study entry: healthy controls (n = 49), subthreshold-anxiety disorders (AD) (n = 82), or meeting DSM-5 criteria for generalized, social, and/or separation ADs (n = 51), as determined through structured clinical interview. Anxiety severity was assessed with the Clinical Global Impression Scale and Screen for Child Anxiety and Related Emotional Disorders (SCARED). Participants (n = 182) underwent clinical, behavioral, and diffusion tensor imaging (DTI) assessments at study entry, and those with pathological anxiety (subthreshold-AD and AD, n = 133) were followed longitudinally for up to 3 additional years. Cross-sectional ANCOVAs (182 scans) examining control, subthreshold-AD, and AD participants found no significant relations between anxiety and DTI measurements. However, in longitudinal analyses of girls with pathological anxiety (343 scans), linear mixed-effects models demonstrated that increases in anxiety symptoms (SCARED scores) were associated with reductions in whole-brain fractional anisotropy, independent of age (Std. β (95% CI) = −0.06 (−0.09 to −0.03), F(1, 46.24) = 11.90, P = 0.001). Using a longitudinal approach, this study identified a dynamic, within-participant relation between whole-brain WM microstructural integrity and anxiety in girls with pathological anxiety. Given the importance of WM microstructure in modulating neural communication, this finding suggests the possibility that WM development could be a viable target in the treatment of anxiety-related psychopathology.
... While greater myelination in High anxiety could explain the elevated FA values, a reduction in intermixing factors such as merging, kissing, branching, and/or crossing along the insular portion of the tract would also result in increased FA values, but the investigation of these possibilities are beyond the scope of this work. If greater uncinate FA values in High relative to Low anxiety groups are indeed the result of "increased structural integrity", rather than a reflection of decreased local intermixing, then one possible interpretation would be that clinical anxiety in this population is associated with greater availability of emotionally valenced information resulting from more efficient amygdaloid-frontal connectivity via uncinate projections (Heide et al., 2013;Eden et al., 2015;Baur et al., 2012). To find convergence with the extant literature, then, it is possible that myelination could subsequently be affected in later pubertal development, resulting in the typically observed negative correlation of uncinate FA values and anxiety, possibly due to the adverse effects of hypercortisolaemia on myelination (Piasecka et al., 2020;Wong et al., 2013;Garg and Mittal, 2020;Jamieson et al., 2021), but this is conjecture. ...
Article
Full-text available
Statistical models employed to test for group differences in quantized diffusion-weighted MRI white matter tracts often fail to account for the large number of data points per tract in addition to the distribution, type, and interdependence of the data. To address these issues, we propose the use of Generalized Additive Models (GAMs) and supply code and examples to aid in their implementation. Specifically, using diffusion data from 73 periadolescent clinically anxious and no-psychiatric-diagnosis control participants, we tested for group tract differences and show that a GAM allows for the identification of differences within a tract while accounting for the nature of the data as well as covariates and group factors. Further, we then used these tract differences to investigate their association with performance on a memory test. When comparing our high versus low anxiety groups, we observed a positive association between the left uncinate fasciculus and memory overgeneralization for negatively valenced stimuli. This same association was not evident in the right uncinate or anterior forceps. These findings illustrate that GAMs are well-suited for modeling diffusion data while accounting for various aspects of the data, and suggest that the adoption of GAMs will be a powerful investigatory tool for diffusion-weighted analyses.
... While many studies have examined WM pathways in adults with high trait anxiety and ADs [13][14][15][16][17][18][19][20][21][22][23], considerably less work has examined WM in anxious youth [24][25][26][27][28][29]. Given evidence linking prefrontal-limbic pathways to anxiety [21,25,[30][31][32][33][34][35][36], our prior work focused on the uncinate fasciculus (UF), the major WM pathway linking prefrontal regions to temporal lobe structures, including the amygdala and anterior hippocampus [37,38]. These studies demonstrated anxiety-related reductions in UF fractional anisotropy (FA), a measure of WM microstructural integrity, in adults, preadolescent children, and preadolescent non-human primates (NHPs) [21,25,39]. ...
Preprint
Full-text available
Pathological anxiety typically emerges during preadolescence and has been linked to alterations in white matter (WM) pathways. Because myelination is critical for efficient neuronal communication, characterizing associations between WM microstructure and symptoms may provide insights into pathophysiological mechanisms associated with childhood pathological anxiety. This longitudinal study examined 182 girls enrolled between the ages of 9–11 that were treatment-naïve at study entry: healthy controls (n = 49), subthreshold-anxiety disorders (AD) (n = 82), or meeting DSM-5 criteria for generalized, social, and/or separation ADs (n = 51), as determined through structured clinical interview. Anxiety severity was assessed with the Clinical Global Impression Scale and Screen for Child Anxiety and Related Emotional Disorders (SCARED). Participants (n = 182) underwent clinical, behavioral, and diffusion tensor imaging (DTI) assessments at study entry, and those with pathological anxiety (subthreshold-AD and AD, n = 133) were followed longitudinally for up to 3 additional years. Cross-sectional ANCOVAs (182 scans) examining control, subthreshold-AD, and AD participants found no significant relations between anxiety and DTI measurements. However, in longitudinal analyses of girls with pathological anxiety (343 scans), linear mixed-effects models demonstrated that increases in anxiety symptoms (SCARED scores) were associated with reductions in whole-brain fractional anisotropy, independent of age (Std. β (95% CI)=-0.06 (-0.09 to -0.03), F (1,46.24) = 11.90, P = 0.001). Using a longitudinal approach, this study identified a dynamic, within-participant relation between whole-brain WM microstructural integrity and anxiety in girls with pathological anxiety. Given the importance of WM microstructure in modulating neural communication, this finding suggests the possibility that WM development could be a viable target in the treatment of anxiety-related psychopathology.
... More recently, studies using very large samples (i.e., the UK Biobank), as well as meta-analyses combining both published and unpublished data (i.e., the ENIGMA consortium), have observed widespread and replicable reductions in FA (Shen et al., 2017;van Velzen et al., 2020). Notably, white matter integrity in identified regions has been shown to correlate with the cognitive processes disrupted in depression, including processing speed (Chopra et al., 2018;Penke et al., 2010), emotion regulation (Eden et al., 2015;Welton et al., 2020), and reward learning (de Boer et al., 2020). ...
Article
Full-text available
The association between depressive disorders and measures reflecting myelin content is underexplored, despite growing evidence of associations with white matter tract integrity. We characterized the T1w/T2w ratio using the Glasser atlas in 39 UD and 47 HC participants (ages=19-44, 75% female). A logistic elastic net regularized regression with nested cross-validation and a subsequent linear discriminant analysis conducted on held-out samples were used to select brain regions and classify patients vs. healthy controls (HC). True-label model performance was compared against permuted-label model performance. The T1w/T2w ratio distinguished patients from HC with 68% accuracy (p<0.001; sensitivity=63.8%, specificity=71.5%). Brain regions contributing to this classification performance were located in the orbitofrontal cortex, anterior cingulate, extended visual, and auditory cortices, and showed statistically significant differences in the T1w/T2w ratio for patients vs. HC. As the T1w/T2w ratio is thought to characterize cortical myelin, patterns of cortical myelin in these regions may be a biomarker distinguishing individuals with depressive disorders from HC.
Article
Full-text available
Neurobiological research on anxiety has shown that trait-anxious individuals may be characterized by weaker structural connectivity of the amygdala-prefrontal circuitry, representing a reduced capacity for efficient communication between the two brain regions. However, comparison of available studies has been inconsistent, possibly related to factors such as aging that influences both trait anxiety and structural connectivity of the brain. To help clarify the nature of brain-anxiety relationship, we applied a connectome-based predictive modeling framework on 148 diffusion-weighted imaging data from the Leipzig Study for Mind-Body Emotion Interactions dataset and identified multivariate patterns of whole-brain structural connectivity that predicted trait anxiety. Results showed that networks predictive of trait anxiety differed across age groups. Specifically, an isolated negative network, which shared overlapping features with the amygdala-prefrontal circuitry, was found in younger adults (20–30 years of age), whereas a widespread positive network highlighted by frontotemporal and frontolimbic connectivity was identified when both younger and older adults (20–80 years of age) were examined. No predictive network was observed when only older adults (30–80 years of age) were considered. Our findings highlight an important age-dependent effect on the structural connectome-based prediction of trait anxiety, supporting ongoing efforts to develop potential neural biomarkers of anxiety.
Article
Full-text available
Background Models of anxiety disorders and the rationale of exposure therapy (ET) are grounded on classical fear conditioning. Yet, it is unclear whether lower fear ratings of conditioned safety versus threat cues and corresponding neural markers of safety-learning and/or fear inhibition assessed before treatment would predict better outcomes of behavioral exposure. Methods Sixty-six patients with spider phobia completed pre-treatment clinical and experimental fear conditioning assessments, one session of virtual reality ET, a post-treatment clinical assessment, and a 6-month follow-up assessment. Tilted Gabor gratings served as conditioned stimuli (CS) that were either paired (CS+) or remained unpaired (CS-) with an aversive phobia-related and phobia-unrelated unconditioned stimulus (UCS). CS+/CS- differences in fear ratings and magnetoencephalographic event-related fields (ERFs) were related to percentual symptom reductions from pre- to post-treatment, as assessed via spider phobia questionnaire (SPQ), behavioral avoidance test (BAT), and remission status at 6-month follow-up. Results We observed no associations between pre-treatment CS+/CS- differences in fear ratings and any treatment outcome. CS+/CS- differences in source estimations of ERFs revealed that higher CS- activity in bilateral dorsolateral prefrontal cortex (dlPFC) was related with SPQ- and BAT-reductions. Associations between CS+/CS- differences and treatment outcomes were also observed in left ventromedial prefrontal cortex (vmPFC) regions, which additionally revealed associations with the follow-up remission status. Conclusions Results provide initial evidence that neural pre-treatment CS+/CS- differences may hold predictive information regarding outcomes of behavioral exposure. Our findings highlight a key role of neural responses to safety cues with potentially inhibitory effects on affect-generating structures during fear conditioning.
Article
Irritability is a prevalent, impairing transdiagnostic symptom, especially during adolescence, yet little is known about irritability's neural mechanisms. A few studies examined the integrity of white matter tracts that facilitate neural communication in irritability, but only with extreme, disorder-related symptom presentations. In this preliminary study, we used a group connectometry approach to identify white matter tracts correlated with transdiagnostic irritability in a community/clinic-based sample of 35 adolescents (mean age=14 years, SD=2.0). We found positive and negative associations with irritability in local white matter tract bundles including sections of the longitudinal fasciculus; frontoparietal, parolfactory, and parahippocampal cingulum; corticostriatal and thalamocortical radiations; and vertical occipital fasciculus. Our findings support functional neuroimaging studies that implicate widespread neural pathways, particularly emotion and reward networks, in irritability. Our findings of positive and negative associations reveal a complex picture of what is “good” white matter connectivity. By characterizing irritability's neural underpinnings, targeted interventions may be developed.
Article
Full-text available
This article is a comparative study of white matter projections from ventral prefrontal cortex (vPFC) between human and macaque brains. We test whether the organizational rules that vPFC connections follow in macaques are preserved in humans. These rules concern the trajectories of some of the white matter projections from vPFC and how the position of regions in the vPFC dictate the trajectories of their projections in the white matter. To address this question, we present a novel approach that combines direct tracer measurements of entire white matter trajectories in macaque monkeys with diffusion MRI tractography of both macaques and humans. The approach allows us to provide explicit validation of diffusion tractography and transfer tractography strategies across species to test the extent to which inferences from macaques can be applied to human neuroanatomy. Apart from one exception, we found a remarkable overlap between the two techniques in the macaque. Furthermore, the organizational principles followed by vPFC tracts in macaques are preserved in humans.
Article
Full-text available
Emotion regulation refers to strategies through which individuals influence their experience and expression of emotions. Two typical strategies are reappraisal, a cognitive strategy for reframing the context of an emotional experience, and suppression, a behavioral strategy for inhibiting emotional responses. Functional neuroimaging studies have revealed that regions of the prefrontal cortex modulate amygdala reactivity during both strategies, but relatively greater downregulation of the amygdala occurs during reappraisal. Moreover, these studies demonstrated that engagement of this modulatory circuitry varies as a function of gender. The uncinate fasciculus is a major structural pathway connecting regions of the anterior temporal lobe, including the amygdala to inferior frontal regions, especially the orbitofrontal cortex. The objective of the current study was to map variability in the structural integrity of the uncinate fasciculus onto individual differences in self-reported typical use of reappraisal and suppression. Diffusion tensor imaging was used in 194 young adults to derive regional fractional anisotropy values for the right and left uncinate fasciculus. All participants also completed the Emotion Regulation Questionnaire. In women but not men, self-reported typical reappraisal use was positively correlated with fractional anisotropy values in a region of the left uncinate fasciculus within the orbitofrontal cortex. In contrast, typical use of suppression was not significantly correlated with fractional anisotropy in any region of the uncinate fasciculus in either men or women. Our data suggest that in women typical reappraisal use is specifically related to the integrity of white matter pathways linking the amygdala and prefrontal cortex. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
Article
Full-text available
A characterizing symptom of social anxiety disorder (SAD) is increased emotional reactivity towards potential social threat in combination with impaired emotion and stress regulation. While several neuroimaging studies have linked SAD with hyperreactivity in limbic brain regions when exposed to emotional faces, little is known about habituation in both the amygdala and neocortical regulation areas. 15 untreated SAD patients and 15 age- and gender-matched healthy controls underwent functional magnetic resonance imaging during repeated blocks of facial emotion ([Formula: see text]) and object discrimination tasks ([Formula: see text]). Emotion processing networks were defined by a task-related contrast ([Formula: see text]). Linear regression was employed for assessing habituation effects in these regions. In both groups, the employed paradigm robustly activated the emotion processing and regulation network, including the amygdalae and orbitofrontal cortex (OFC). Statistically significant habituation effects were found in the amygdalae, OFC, and pulvinar thalamus of SAD patients. No such habituation was found in healthy controls. Concurrent habituation in the medial OFC and the amygdalae of SAD patients as shown in this study suggests intact functional integrity and successful short-term down-regulation of neural activation in brain areas responsible for emotion processing. Initial hyperactivation may be explained by an insufficient habituation to new stimuli during the first seconds of exposure. In addition, our results highlight the relevance of the orbitofrontal cortex in social anxiety disorders.
Article
Resting anterior brain electrical activity, self-report measures of Behavioral Approach and Inhibition System (BAS and BIS) strength, and general levels of positive and negative affect (PA and NA) were collected from 46 unselected undergraduates on two separate occasions Electroencephalogram (EEG) measures of prefrontal asymmetry and the self-report measures showed excellent internal consistency reliability and adequate test-retest stability Aggregate measures across the two assessments were computed for all indices Subjects with greater relative left prefrontal activation reported higher levels of BAS strength, whereas those with greater relative right prefrontal activation reported higher levels of BIS strength Prefrontal EEG asymmetry accounted for more than 25% of the variance in the self-report measure of relative BAS-BIS strength Prefrontal EEG, however, was not significantly correlated with PA or NA, or the relative strength of PA versus NA Posterior asymmetry was unrelated to the self-report measures
Article
Trait anxiety, a personality dimension that measures an individual's higher disposition to anxiety, has been found to be associated with many functional consequences viz. increased distractibility, attentional bias in favor of threat-related information etc. Similarly, volumetric studies have reported morphological changes viz. a decrease in the volume of left uncinate fasciculus (fiber connecting anterior temporal areas including the amygdala with prefrontal-/orbitofrontal cortices) and an increase in the volume of the left amygdala and right hippocampus, to be associated with trait anxiety. The functional and morphological changes associated with trait anxiety might also be associated with the changes in the integrity of WM tracts in relation with the trait anxiety levels of the subjects. Therefore, in the present diffusion tensor tractography (DTT) study, we investigated the possible relationship between the diffusion tensor imaging (DTI) derived indices of a wide array of fiber tracts and the trait anxiety scores in our subject group. A positive correlation between trait anxiety scores and the mean fractional anisotropy (FA) value was obtained in fornix and left uncinate fasciculus. The study provides first account of a positive relation between sub-clinical anxiety levels of subjects and the FA of fornix thereby providing interesting insights into the biological foundation of sub-clinical anxiety.
Article
Fear is a well-known aura of partial seizures and is believed to be of mesial temporal lobe origin, but previous investigations using interictal electroencephalogram (EEG) and electrical brain stimulation have not found ictal fear to be of lateralizing significance. We report a consecutive series of 15 patients with idiopathic complex partial seizures who experienced ictal fear. All patients underwent monitoring of ictal events with scalp EEG, and 13 patients also underwent invasive EEG monitoring. In 13 of the 15 cases (87%) the seizures originated from the right (nondominant) temporal lobe. There are significant similarities between these data and recently published findings that have demonstrated right temporal lobe pathology in panic disorder. A growing understanding of the contribution of the nondominant temporal lobe and limbic system to pathologic fear states in humans appears to be developing. (C) Lippincott-Raven Publishers.
Article
Background: Conjoint activity of the insula and amygdala has frequently been reported during emotional stimulation in general and in anxiety-related contexts in particular. However, direct connectivity between the insula and amygdala in this framework has received little attention so far. Studying whether inter-individual differences in anxiety reflect variation in insula-amygdala connectivity is a way to push forward the understanding of network-related aspects underlying anxious behavior. Methods: To investigate functional and structural connectivity, we applied resting-state functional magnetic resonance imaging and diffusion tensor imaging in a group of 32 healthy subjects. Specific measures of connectivity between subregions of the insula and amygdala were related to subjects' anxiety levels. Results: Resting-state functional connectivity between the anterior insula and the basolateral amygdala was strongly related to state anxiety, explaining 40% of behavioral variance across subjects. This was substantiated by applying tractography, yielding a relationship between trait anxiety and axial diffusivity for a direct pathway between anterior insula and basolateral amygdala. Conclusions: Our results indicate that anterior insula and basolateral amygdala constitute a network part that is prominently linked to anxiety. Within this route, state and trait behavioral impacts seem to be specifically linked to dynamic functional and more static structural neural aspects, respectively. Insula-amygdala resting-state functional connectivity can be assessed in an easy and straightforward way and has high potential to serve as a biomarker for anxiety.
Article
Conceptual and empirical approaches to the study of the role of asymmetric frontal cortical activity in emotional processes are reviewed. Although early research suggested that greater left than right frontal cortical activity was associated with positive affect, more recent research, primarily on anger, suggests that greater left than right frontal cortical activity is associated with approach motivation, which can be positive (e.g., enthusiasm) or negative in valence (e.g., anger). In addition to reviewing this research on anger, research on guilt, bipolar disorder, and various types of positive affect is reviewed with relation to their association with asymmetric frontal cortical activity. The reviewed research not only contributes to a more complete understanding of the emotive functions of asymmetric frontal cortical activity, but it also points to the importance of considering motivational direction as separate from affective valence in psychological models of emotional space.