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Sensory processing sensitivity and childhood quality’s effects on neural responses to emotional stimuli

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Objective: This study examined the neural correlates of adult sensory processing sensitivity (SPS) and its interaction with subjective ratings of quality of childhood parenting (QCP). Method: Fourteen women (ages 18-25) underwent fMRI while viewing positive, negative and neutral images from the standard International Affective Picture System (IAPS) and completed the Highly Sensitive Person (HSP) Scale. (HSP) Scale, a neuroticism scale, and measures of quality of recalled childhood parenting. Results: In response to emotional (versus neutral) IAPS images, the SPS x QCP interaction (and also of SPS directly controlling for neuroticism) showed significant positive neural correlations in the hippocampus, entorhinal area, hypothalamus, and temporal/parietal areas, which process emotional memory, learning, physiological homeostasis, awareness, reflective thinking, and integration of information. For positive stimuli only, SPS showed significant correlations with areas involved in reward processing (VTA, SN, caudate), self-other integration (insula and IFG), calm (PAG), and satiation (subcallosal AC); and to a greater extent with increasing QCP. For negative images, the SPS x QCP interaction showed significant activation in the amygdala and PFC (involved in emotion and self-control), without diminished reward activity. Conclusions: SPS (and its interaction with childhood environment) is positively associated with activation of brain regions associated with depth of processing, memory, and physiological regulation in response to emotional stimuli. Results support differential susceptibility, vantage sensitivity and HSP models suggesting that SPS is associated with environmental sensitivity so that positive environments (such as high QCP) may provide benefits, such as adaptive responsivity (with awareness, arousal, self-control and calm) to emotionally evocative stimuli.
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Clinical Neuropsychiatry (2017) 14, 6, 359-373
SENSORY PROCESSING SENSITIVITY AND CHILDHOOD QUALITY’S EFFECTS ON NEURAL
RESPONSES TO EMOTIONAL STIMULI
Bianca P. Acevedo, Jadzia Jagiellowicz, Elaine Aron, Robert Marhenke, Arthur Aron
Abstract
Objective: This study examined the neural correlates of adult sensory processing sensitivity (SPS) and its interaction
with subjective ratings of quality of childhood parenting (QCP).
Method: Fourteen women (ages 18-25) underwent fMRI while viewing positive, negative and neutral images from the
standard International Affective Picture System (IAPS) and completed the Highly Sensitive Person (HSP) Scale. (HSP)
Scale, a neuroticism scale, and measures of quality of recalled childhood parenting.
Results: In response to emotional (versus neutral) IAPS images, the SPS x QCP interaction (and also of SPS
directly controlling for neuroticism) showed signicant positive neural correlations in the hippocampus, entorhinal area,
hypothalamus, and temporal/parietal areas, which process emotional memory, learning, physiological homeostasis,
awareness, reective thinking, and integration of information. For positive stimuli only, SPS showed signicant correlations
with areas involved in reward processing (VTA, SN, caudate), self-other integration (insula and IFG), calm (PAG), and
satiation (subcallosal AC); and to a greater extent with increasing QCP. For negative images, the SPS x QCP interaction
showed signicant activation in the amygdala and PFC (involved in emotion and self-control), without diminished reward
activity.
Conclusions: SPS (and its interaction with childhood environment) is positively associated with activation of brain
regions associated with depth of processing, memory, and physiological regulation in response to emotional stimuli.
Results support differential susceptibility, vantage sensitivity and HSP models suggesting that SPS is associated with
environmental sensitivity so that positive environments (such as high QCP) may provide benets, such as adaptive
responsivity (with awareness, arousal, self-control and calm) to emotionally evocative stimuli.
Key words: sensory processing sensitivity, fMRI, childhood environment, emotions, reward, self-regulation
Declaration of interest: all of the authors declare no nancial interests or potential conicts of interest.
Bianca P. Acevedo1, Jadzia Jagiellowicz2, Elaine Aron2, Robert Marhenke3, Arthur Aron2
1 University of California, Santa Barbara, Neuroscience Research Institute, Santa Barbara, CA, 93106-5060, USA.
2 Stony Brook University, Stony Brook, NY, 11794-2500, USA.
3 Leopold-Franzens University of Innsbruck, Innsbruck, Austria
Corresponding author
Bianca Acevedo,
University of California, Santa Barbara, Neuroscience Research Institute,
Santa Barbara, CA 93106-5060.
Contact: bianca.acevedo@lifesci.ucsb.edu
Submitted September 2017, Accepted November 2017
© 2017 Giovanni Fioriti Editore s.r.l. 359
Sensory processing sensitivity (SPS) is thought to
be a genetically-based trait found in humans and in over
100 other species (Wolf et al. 2008). It is characterized
by greater environmental sensitivity (Pluess 2015),
including social stimuli (Acevedo et al. 2014, Wolf et
al. 2008), and behaviorally it is typically associated with
reactivity to salient stimuli and greater cautiousness in
approaching novel situations and objects (Aron et al.
2012; Gartstein et al. 2016, review). It appears to be
a survival strategy found across species in only in a
signicant minority within each species, probably due to
negative frequency dependence (Wolf et al. 2008). The
trait bestows the advantage (as long as most individuals
do not possess it) of being more aware than others of
opportunities and threats. Interpersonal sensitivity would
also allow them to select mates, parent, empathize and
form alliances more effectively resulting in survival
advantages (Acevedo et al. 2017).
SPS has a unique avor in humans, and is generally
measured with the Highly Sensitive Person (HSP)
scale (Aron et al. 1997). Its items include sensitivity to
bright lights, loud noises, others’ moods, violent stimuli,
caffeine, and hunger as well as having “a rich, complex
inner life” greater conscientiousness, and “being deeply
moved by arts or music. SPS is thought to be mediated
by deep and connective cognitive processing (Mesulam
1998), as well as emotion responsivity, which enhances
memory, attention and learning (Baumeister et al. 2007).
Research on differential susceptibility (Belsky et al.
2009) suggests that greater sensitivity leads to more
vulnerability to negative environments and greater
vantage sensitivity in positive ones (Belsky et al.
2009, Boyce et al. 2005, Pluess et al. 2013). Similarly,
studies of SPS in adults, using the standard HSP scale
Bianca P. Acevedo et al.
360 Clinical Neuropsychiatry (2017) 14, 6
including the 27-item HSP Scale (M = 4.26, SD = 0.99),
Cronbach’s alpha = 0.87 (as in previous studies Aron
et al. 2005, Benham 2006); and a measure of quality of
childhood parenting (QCP), calculated as a weighted sum
(computed from the larger sample initially surveyed) of
7 inter-correlated scales. The weights were based on
contributions to the rst principal component, positively
or negatively assigned to represent high-quality
parenting: (a-d) the care and overprotection subscales
of the Parental Bonding Inventory (Parker et al. 1979),
completed for both mother and father (Cronbach’s alphas:
care, 0.94 and 0.92 for mother and father, respectively;
overprotection, 0.88 and 0.90, respectively; weights:
-.307, -265, .286, 301); (e and f) the abuse subscale of
the Measure of Parenting Style (Parker et al. 1997): for
mother, (Cronbach’s alpha =0.86; weight: 0.12); and for
father (Cronbach’s alpha = 0.87, weight: 0.09); and (g)
an eight-item scale (e.g., “Would you characterize your
childhood as troubled?”) used in previous SPS studies
(e.g. Aron EN et al. 2005; Cronbach’s alpha = 0.74,
weight = 0.22). In addition a measure of neuroticism (M
= 3.96; SD = 1.58) was included, with two items “Are
you prone to depression?” and “Are you prone to fears?”
(Cronbach’s alpha = 0.51). As in previous studies, SPS
and neuroticism were highly correlated (r = 0.66, p =
0.01) thus we followed standard procedures (e.g. Aron A
et al. 2005), and controlled for neuroticism for the basic
correlations of SPS with brain responsivity (results are
shown in tables 1 and 2). For the SPS X QCP interaction
we did not control for neuroticism as the parenting
interaction also predicts neuroticism.
Experimental Procedure
Stimuli and MRI protocol. Stimuli consisted of
pictures from the IAPS, which were specically selected
for wide use and have been shown to correspond with the
elicitation of emotions in normative and clinical samples
(Bradley et al. 2007). The fMRI protocol (modied from
Canli et al. 2001 and Ribeiro et al. 2007) consisted of an
8-minute session where participants viewed 6 alternating
blocks of four pictures, each of the same valence
(positive, negative, or neutral); and with 3 practice-trials
at the beginning of the entire sequence. Each picture was
presented for 6,000 ms, with an interstimulus interval (a
xation cross) of 1,125 ms. The initial block (after the
practice trials) consisted of neutral pictures. The order of
subsequent blocks was alternated across participants.
Post-scan anxiety ratings. Post-scan, participants
were asked to indicate their level of anxiety while in the
scanner on a Likert scale from 1 to 7, with 1 representing
“not at all” and 7 representing “extremely.” The mean
anxiety rating was 2.62.
Data Acquisition and Analysis
To collect brain imaging data, we used a 3.0 T
MAGNETOM TrioTim magnetic resonance imaging
scanner at the SCAN Center of Stony Brook University.
A T2-weighted gradient-echo echo-planar sequence
(repetition time 2,000 ms, echo time 30 ms, 80˚ ip
angle, eld of view 240 X 240 mm, 64 X 64 matrix) was
used to acquire functional scans. The pictures consisted
of 30 contiguous axial slices, with no gap between slices,
voxel size was 3.8 X 3.8 X 4.0 mm. Anatomical scans
were also acquired (axial T1-weighted scans; repetition
time 300 ms, echo time ms, 256 X 256 matrix, 80˚ ip
angle, 240 mm X 240 mm eld of view, slice thickness
4 mm) in the same session. Voxel size for the anatomical
scans was 0.9 X 0.9 X 4 mm.
(Aron et al. 1997), found that high SPS individuals with
negative childhood environments had more anxiety and
depression as adults compared to their less sensitive
counterparts (Aron et al. 2005, Liss et al. 2005). Also
in support of vantage sensitivity, another study found
that high (vs. low) SPS adults with positive recalled
childhoods showed especially greater arousal to positive
(versus neutral) images (Jagiellowicz et al. 2016).
Although heightened emotional arousal may provide
some explanation for the differential susceptibility
associated with the trait, it has mostly been reported in
behavioral studies. The three fMRI studies of SPS to date
(all using the HSP scale) found that it is associated with
overall greater expression in (a) visual areas associated
with making ne visual distinctions (Jagiellowicz et
al. 2011); (b) regions associated with attention and
working memory in response to a task involving
attending to context to visual scenery (Aron et al.
2010); and (c) regions involved in empathy, awareness,
sensory integration, self-referential processing and
action in response to others’ emotional expressions
(Acevedo et al. 2014). Moreover, a review of the brain
structures involved in SPS versus seemingly related
clinical disorders (i.e., autism) suggests that it is largely
differentiated by neural processing in regions associated
with physiological homeostasis, self-regulation, self-
other processing, empathy and awareness (Acevedo et
al. 2017).
The present study used functional MRI (as did the
three previous studies) to measure the neural correlates
of SPS in response to standardized emotional pictures
from the International Affective Picture System (IAPS).
It also used seven well-established childhood measures
of perceived quality of childhood environment. Our two
questions were: (1) whether participants with high SPS
would show evidence of greater emotional, memory,
awareness and self-referential processing to affective
images; and (2) whether this would vary with degree of
positive childhood quality. Thus, we specically focused
on brain regions shown in previous neuroimaging studies
of SPS as well as the amygdala a main site of emotion
processing, especially to aversive stimuli (Canli et
al. 2000; Ochsner et al. 2004, 2009; Phan et al. 2004)
whose role in emotional SPS processing has been
inconclusive.
Method
Participants
Participants were undergraduate student females
recruited from Stony Brook University, with scores at
the top and bottom quartile of the HSP scale (eliminating
the top and bottom 2.5% of scorers). Sample selection
was consistent with conditions delineated by previous
studies (Preacher et al. 2005), such as recruitment of only
one gender (females), as studies have shown signicant
gender differences for the IAPS emotion task (Blair
2002, Velderman et al. 2006). Our resulting sample
consisted of 14 right-handed females, ages 18-25 (M age
= 19.00 years, SD = 1.84), with an ethnic composition of
50% Caucasian, 40% Asian and 11% reporting “other”.
Of these 14, 7 were in the top SPS quartile and 7 in the
bottom quartile. All participants met criteria for fMRI
contraindications (e.g., no severe alcohol or drug use,
claustrophobia, etc.).
Questionnaires
Participants completed a battery of questionnaires
Table 1. Correlations of Adult Sensory Processing Sensitivity (controlling for Neuroticism) with Neural Response
to Positive versus Neutral Images
Brain Region Left Right
x y z T p k x y z T p k
ROI Activations
VTA/SN 8 -16 -16 1.91 0.04a3
Caudal cingulate -20 -8 36 2.55 0.01a8 12 -20 28 3.11 0.004a15
Caudate tail -28 -60 12 2.87 0.02a9
Hippocampus/
Entorhinal area
-36 -8 -28 3.64 0.002abc 22 36 -8 -28 3.62 0.002abc 22
Hypothalamus -4 -8 -8 2.25 0.02abc 3
Periacqueductal gray -4 -36 -32 2.05 0.03a9 4 -36 -32 1.86 0.04a9
Anterior cingulate,
subcallosal
8 32 4 3.21 .004a3
Insula -40 12 12 2.77 0.01a5
Fusiform gyrus -36 -32 -16 2.65 0.01b9
Tempoparietal junction 47 -66 24 2.61 0.01a24
Precuneus/parietal area -16 -48 52 2.46 0.03a21 7 -49 56 3.13 0.01 16
Superior/middle
temporal gyrus
68 -44 4 3.70 0.002abc 6
Inferior temporal gyrus -52 -4 -24 3.04 0.01 abc 16
Medial PFC 21 40 -8 2.37 0.02a8
Whole-brain Deactivations
Dorsomedial PFC 12 40 28 4.04 < .001 88
Inferior parietal lobule 40 -76 44 4.20 < .001ac 22
Inferior parietal cortex 52 -36 56 4.15 < .001ac 262
Anterior cingulate cortex -12 48 -4 3.86 < .001 79
Note. Results are for regions showing signicant brain response in association with the Highly Sensitive Person (HSP) Scale
scores moderated by Positive Childhood scale scores. MNI coordinates (x,y,z) are at the maximum value for the cluster,
which may be elongated in any direction. Legend: a overlapping area for Positive Conditions; b overlapping with the Negative
condition (controlling for Neuroticism); and coverlapping with Negative condition x Childhood.
Sensory processing sensitivity, the brain, and emotions
Clinical Neuropsychiatry (2017) 14, 6 361
.05 (Genovese et al. 2002) to correct for multiple
comparisons. ROIs were derived from previous fMRI
studies of SPS (Aron et al. 2010, Jagiellowicz et al. 2011),
a meta-analysis on human brain responses to emotional
stimuli (Morelli et al. 2015), and close inspection of the
amygdala (Costafreda et al. 2008, Phan et al. 2004). All
ROIs occupied a 3-mm radius (minimum) and anatomic
regions were conrmed with the Atlas of the Human
Brain (Mai et al. 2008).
Results
SPS (controlling for Neuroticism) Correlations
with Human Brain Activity
Positive versus Neutral Contrast. As shown
in table 1, signicant regional brain correlations
were shown for SPS (controlling for Neuroticism) in
response to positive (vs. neutral) IAPS images in the
ventral tegmental area (VTA)/ substantia nigra (SN),
caudate, hippocampus, periaqueductal gray (PAG),
anterior cingulate (AC), insula, fusiform gyrus (FG),
temporoparietal junction (TPJ), precuneus, temporal
gyrus, and medial PFC.
Negative versus Neutral Contrast. As shown
in table 2, signicant regional brain correlations
were shown for SPS (controlling for Neuroticism) in
response to negative versus neutral IAPS images in the
amygdala, hippocampus/entorhinal area, hypothalamus,
Stimuli were shown using E-Prime software (Version
2.0, Psychology Software Tools, Pittsburgh, PA) and
were projected on a screen placed directly outside the
MRI tube, and viewed via an angled mirror mounted on
the RF coil of the scanner.
Data were analyzed using SPM5 (http://www.l.
ion.ucl.ac.uk/spm). For preprocessing, functional EPI
volumes were realigned to the rst volume, smoothed
with a Gaussian kernel of 6mm, and then normalized
to the T1.nii image template. No participant showed
movement greater than 3 mm (whole-voxel). After
preprocessing, contrasts were created (e.g., positive vs.
neutral) followed by regression analyses examining
the associations between each contrast (positive vs.
neutral and negative vs. neutral). For SPS controlling
for Neuroticism, rst we calculated SPS residual scores
controlling for the interaction of SPS with Neuroticism.
The residuals were used to carry out a mixed-effects
general linear model, with participants as the random-
effects factor and conditions as the xed effect. For
the SPS x QCP interaction, regression analyses were
conducted estimating group brain activity in association
with SPS and QCP scores which produced an interaction
term controlling for the independent contribution of each
of the variables.
We conducted exploratory, whole-brain analyses
using a threshold of p < .001 (uncorrected) and a spatial
extent of > 15 contiguous voxels. We also examined,
a priori regions of interest (ROIs) applying a standard
false discovery rate (FDR) with a threshold of p <
Table 3. Correlations of Adult Sensory Processing Sensitivity and Childhood Environment with Neural Response
to Positive versus Neutral Images
Brain Region
Left Right
x y z T p k x y z T p k
VTA/SN -4 -8 -16 2.6 0.01 15 8 -16 -16 2.10 0.03a43
Caudate tail/posterior
cingulate -28 -64 12 3.31 0.005a95
Caudate cingulate -20 -8 36 3.24 0.01a20 16 -20 28 3.20 0.02 a 35
Hippocampus/
entorhinal area -36 -8 -28 1.93 0.04abc
45
36 -8 -28 4.38 0.01abc 23
Hypothalamus -4 -8 -12 3.09 0.01abc 15 4 -8 -12 2.68 0.02 15
Periacqueductal gray -4 -36 -32 2.79 0.01a11 4 -36 -32 2.50 0.02a11
Anterior cingulate,
subcallosal 8 32 4 2.63 0.01a4
Insula -40 12 12 3.77 < .001a21
Inferior frontal gyrus -44 24 4 3.29 0.01 24
Fusiform gyrus 36 -24 -12 2.31 0.02bc 45
Tempoparietal junction 48 -68 28 2.84 0.01a114
Precuneus/parietal area -12 -60 52 3.23 0.01 84
Superior/middle
temporal gyrus 68 -48 4 1.90 0.01abc 19
Inferior temporal
gyrus -52 -4 -29 1.85 0.01abc 16
Medial PFC -20 32 -12 3.04 0.01 16 24 40 -8 3.12 0.01 a 6
PFC -40 44 32 3.53 0.003 37
Deactivations
Inferior parietal area 40 -72 48 4.77 < .001ac37
Note. Results are for regions showing signicant brain response in association with the Highly Sensitive Person (HSP)
Scale scores moderated by Positive Childhood scale scores. MNI coordinates (x,y,z) are at the maximum value for the
cluster, which may be elongated in any direction. Legend: a overlapping area for Positive conditions; b overlapping with the
Negative condition (controlling for Neuroticism); and c overlapping with Negative x Childhood.
Bianca P. Acevedo et al.
362 Clinical Neuropsychiatry (2017) 14, 6
that for positive (vs. neutral) pictures, the SPS x QCP
interaction showed signicant neural activations that
were not shown for the SPS correlation in the left VTA,
IFG, dorsomedial and ventromedial PFC; and the right
hypothalamus. These areas are well-known for their
role in reward, self-other processing, cognitive control,
and physiological homeostasis.
Negative versus Neutral Contrast. As shown in
table 4, the interaction of SPS x QCP in response to
negative (vs. neutral) images resulted in signicant
activation of the bilateral amygdala, hippocampus,
precuneus/parietal area, temporal pole, middle
frontal gyrus (MFG), ventromedial PFC, secondary
somatosensory cortex (SII), and the supplementary
motor area (SMA); the left hypothalamus, PC, TPJ,
dorsomedial PFC, sensorimotor cortex; and the right
STG, MTG, ITG, occipital/FG, precentral gyrus, and
frontal pole.
In general, the pattern of results for the SPS x
QCP interaction in response to negative images was
similar to those seen for the SPS correlation (denoted
by superscript “a” in tables 2 and 4). However, a few
important differences emerged. In response to negative
stimuli, SPS showed signicant deactivation in the VTA,
SN, caudate (gure 3), and IFG (indicating less reward
and self/other processing). This pattern did not emerge
for the SPS x QCP interaction. In contrast, the SPS x
QCP interaction for negative (versus neural) images
showed signicant brain activations in the dorsomedial
AC, posterior cingulate (PC), precuneus/parietal area,
TPJ, temporal gyrus, FG, frontal gyri, ventromedial
PFC, SII, and premotor cortex (PMC).
SPS x Quality of Childhood Parenting (QCP)
Activations in the Human Brain
Positive versus Neutral Contrast. As shown
in table 3, the interaction of SPS x QCP in response
to positive (vs. neutral) IAPS images resulted in
signicant neural activity in the bilateral VTA/
SN, caudal cingulate, hippocampus/entorhinal area,
hypothalamus, PAG, and medial PFC; right AC, FG,
TPJ, and superior/middle temporal gyrus (STG, MTG);
and the left caudate tail/PC, insula, inferior frontal
gyrus (IFG), insula, precuneus/parietal area, inferior
temporal gyrus (ITG), and PFC. The pattern of the SPS
x QCP interaction for positive (vs. neutral) images was
such that the combination of greater HSP and QCP
scores resulted in stronger brain activation for most of
the regions, compared to lower HSP and QCP (gure
1). In other words, subjects with low SPS did not show
large differences in the strength of neural signals as a
function of QCP.
Many of the results shown for the SPS x QCP
interaction (positive versus neutral condition) were
also shown for the SPS correlation as denoted by
superscripts “a”. However, it’s interesting to note
Sensory processing sensitivity, the brain, and emotions
Clinical Neuropsychiatry (2017) 14, 6 363
4
5
C
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E
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F
B
Activation intensity
for the Caudate tail
(-29,-20,12)
Activation intensity
for VTA
(8,-16,-16)
Activation intensity
for the Hippocampus/Entorhinal area
(36,-8,-28)
Figure 1. Sensory processing sensitivity (SPS) and subjective quality of childhood parenting (QCP) interaction
is associated with adults’ brain responsivity to positive (vs. neutral) images in the: A) ventral tegmental area
(VTA)/substantia nigra (SN) and hypothalamus; C) the caudate tail and insula; and E) the hippocampus/
entorhinal area. Plots show that subjective positive childhood moderates the response intensity in the
B) R. VTA/SN, and D) the L. caudate tail, and F) the R. hippocampus/entorhinal area
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for the Caudate tail
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for VTA
(8,-16,-16)
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for the Hippocampus/Entorhinal area
(36,-8,-28)
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-0.125
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D
F
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Activation intensity
for the Caudate tail
(-29,-20,12)
Activation intensity
for VTA
(8,-16,-16)
Activation intensity
for the Hippocampus/Entorhinal area
(36,-8,-28)
B
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E
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-0.125
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B
Activation intensity
for the Caudate tail
(-29,-20,12)
Activation intensity
for VTA
(8,-16,-16)
Activation intensity
for the Hippocampus/Entorhinal area
(36,-8,-28)
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5
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E
Hippocampus/Entorhinal area
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-0.125
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0
0.125
0.25
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LoHSP HiHSP
-0.125
0
0.125
0.25
0.375
0.5
NegPar
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LoHSP HiHSP
D
F
B
Activation intensity
for the Caudate tail
(-29,-20,12)
Activation intensity
for VTA
(8,-16,-16)
Activation intensity
for the Hippocampus/Entorhinal area
(36,-8,-28)
4
5
C
0
1
2
3
Caudate tail Insula
E
Hippocampus/Entorhinal area
0
1
2
3
4
5
A
0
1
2
3
4
5
VTA Hypothalamus
-0.125
0
0.125
0.25
0.375
0.5
NegPar
PosPar
LoHSP HiHSP
-0.125
0
0.125
0.25
0.375
0.5
NegPar
PosPar
LoHSP HiHSP
-0.125
0
0.125
0.25
0.375
0.5
NegPar
PosPar
LoHSP HiHSP
D
F
B
Activation intensity
for the Caudate tail
(-29,-20,12)
Activation intensity
for VTA
(8,-16,-16)
Activation intensity
for the Hippocampus/Entorhinal area
(36,-8,-28)
Bianca P. Acevedo et al.
364 Clinical Neuropsychiatry (2017) 14, 6
Discussion
This was the rst neuroimaging study to investigate
the neural correlates of SPS in response to standard
emotional images from the IAPS, with the addition of
examination of the effects of self-reported quality of
childhood parenting (QCP). Our results, along with
those from previous empirical studies, suggest that in
response to both positive and negative visual stimuli,
SPS evokes brain activation in regions that mediate: (a)
memory, attention, awareness, and reective thinking
in response to both positive and negative emotional
stimuli; and (b) reward processing (VTA, SN, caudate),
self-other integration (insula and IFG), calm (PAG),
and satiation (subcallosal AC) to positive stimuli only.
This pattern of results was also shown for the SPS
x QCP interaction. However, the interaction resulted
in overall stronger brain activation of regions that
mediate emotions, memory, physiological homeostasis,
attention and cognitive processes specically in the
PFC, occipital/FG, precentral gyrus, frontal pole, and
sensorimotor cortex areas involved in cognitive
emotion processing, visual processing, decision-making
and self-regulation (Buhle et al. 2014, Sabatinelli et al.
2011); while these areas were not shown for the SPS
correlation. These results highlight the role that QCP
may play for SPS in adaptive response to negative
stimuli ‒ namely through enhanced cognitive and self-
regulatory processing without diminished reward.
Commonalities for All SPS Conditions
Across all SPS conditions (that is, in response to
both positive and negative images, when controlling for
Neuroticism, and for the SPS x QCP interaction), SPS
showed signicant positive correlations with activation
in the hippocampus, entorhinal area, hypothalamus, and
temporal gyri; and deactivation of the inferior parietal
area.
Table 2. Correlations of Adult Sensory Processing Sensitivity (controlling for Neuroticism) with Neural Response
to Negative versus Neutral Images
Brain Region
Left Right
x y z T p k x y z T p k
ROI Activations
Amygdala -20 -12 -24 2.41 0.02a4
Hippocampus/
entorhinal area -36 -8 -28 3.64 0.002abc 22 36 -8 -28 3.62 0.002abc 22
Hypothalamus 0 -4 -8 3.02 0.01abc 5
Anterior cingulate 0 44 20 2.58 0.01 19
Posterior cingulate/
precuneus 8 -56 28 1.82 0.05a292
Precuneus/parietal area -12 -68 28 2.77 0.01a292 16 -56 36 4.53 0.004a292
Tempoparietal junction -40 -52 24 2.86 0.01a36 36 -60 32 2.16 0.001 36
Middle/inferior
temporal gyrus -52 -24 -16 4.00 < .001abc 203 52 -32 -16 4.24 < .001
abc 69
MTG/temporal pole -52 -4 -12 4.04 < .001abc 203
Fusiform gyrus -36 -32 -16 4.56 < .001b203 36 -32 -16 2.29 0.02ac 31
Superior/middle frontal
gyrus -28 52 12 4.17 < .001a53 24 52 4 2.45 0.01ac 87
Middle frontal gyrus 32 24 56 2.81 0.01a50
Ventromedial PFC 0 56 -4 2.67 0.01a13
SII -40 -24 16 2.23 0.05a3
Premotor cortex 8 -28 56 4.19 < .001a52
Deactivations
VTA 4 -12 -8 2.00 0.03 3
SN 12 -8 -12 2.48 0.01 6
Caudate, head 20 24 0 2.13 0.03 4
Inferior frontal gyrus -30 28 -12 1.88 0.04 9
Posterior orbital/
frontomarginal gyrus -28 48 -12 2.33 0.02 6
Note. Results are for regions showing brain responses associated with the Highly Sensitive Person (HSP) Scale scores
controlling for Neuroticism. MNI coordinates (x,y,z) are at the maximum value for the cluster, which may be elongated in
any direction. Legend: a overlapping area for Negative conditions; b overlapping with the Positive condition (controlling for
Neuroticism); and c overlapping with Positive condition (x Childhood)
Sensory processing sensitivity, the brain, and emotions
Clinical Neuropsychiatry (2017) 14, 6 365
at least one approach that may over-ride the effects
of negative experiences and stress. Other techniques
include behavioral interventions as shown by at least
one study with pre adolescent females (Pluess et al.
2015), in which only the third of girls highest in SPS
beneted one year later from the procedures designed
to reduce adolescent depression.
Sensory Processing Sensitivity, Emotions,
Memory and Homoeostasis
Across every condition examined in the present
study, SPS, as well as the interaction of high SPS
with QCP, was associated with signicant neural
response in regions associated with emotional memory
(hippocampus/entorhinal area), and physiological
homeostasis and energy balance (hypothalamus).
These ndings are in line with previous fMRI studies
of SPS examining response to emotionally evocative
social stimuli (Acevedo et al. 2014) and behavioral and
self-reports of SPS suggesting its cardinal features of
depth of processing, attention to detail, and awareness
of subtleties in the environment and other people’s
moods (Aron et al. 1997). Such processing would also
require greater emotional memory, through activation
of the hippocampus, in order to compare the meaning of
present details with those observed in the past.
TPJ, precuneus/parietal lobe, and PFC areas that
are involved in reective thinking, present-moment
awareness, and self-regulation in response to both
positive and negative stimuli. For positive images
only, the SPS x QCP interaction conferred increases
activation in brain regions for reward and self-other
processing (i.e., VTA, caudate, IFG, and FG) with
better QCP. In response to negative (versus neutral)
images, the interaction of SPS x QCP showed unique
signicant activations in ventromedial and dorsal parts
of the PFC, but without the diminishment of reward
signals (VTA, SN, caudate; table 2), that was seen for
the SPS correlation for negative stimuli without the
interaction with QCP (gures 2 and 3).
These results provide support for differential
susceptibility models, in particular the positive effects
of good environments, which propose that some
individuals are highly sensitive to the effects of their
environment (Belsky et al. 2009). These ndings
also elucidate the neural mechanisms by which SPS
and environmental conditions (such as the quality of
childhood parenting) affect long-term outcomes
namely via circuits that mediate mood (reward), higher-
order cognitive processing, self-regulation, reective-
thinking, self/other elaboration and awareness.
Promisingly, these circuits are the main targets for
mindfulness, yoga and meditative practices (for review
see Acevedo et al. 2016, Tang et al. 2015), thus providing
Table 4. Correlations of Adult Sensory Processing Sensitivity and Childhood Environment with Neural Response
to Negative versus Neutral Images
Brain Region
Left Right
x y z T p k x y z T p k
ROI Activations
Amygdala/
hippocampus -28 -8 -28 2.19 0.02a32 20 0 -24 3.09 0.01 32
Hippocampus/
entorhinal -20 -12 -20 4.01 0.002a32 32 -4 -24 2.55 0.02abc 32
Hypothalamus 0 -4 -8 4.91 .001abc 10
Posterior cingulate -24 -64 12 4.91 < .001 23
Precuneus/parietal area -12 -72 36 2.14 0.03a15 16 -60 44 4.64 < .001a154
Tempoparietal junction -56 -64 24 3.33 0.001a22
Superior/middle/
inferior temporal
gyrus
-40 16 -28 7.14 0.001 abc 253 52 -32 -8 6.67 0.001abc 151
Occipital/fusform
gyrus 40 -56 -12 2.08 0.01ac 5
Pre-central gyrus 44 0 44 3.22 0.001 21
Middle frontal gyrus -28 52 32 4.34 < .001 a 11 24 44 48 4.28 < .001 40
Frontal pole 32 60 -8 4.03 < .001 89
Ventromedial PFC -12 56 -8 2.52 0.02 a 7 12 56 -8 3.51 0.02 89
Dorsomedial PFC -8 48 40 2.75 0.01 4
Sensorimotor cortex -16 -32 56 2.19 0.03 19
SII -44 -24 28 1.90 0.04a17 44 -24 28 1.85 0.02 16
SMA -4 -16 72 2.29 < .001 5 4 -9 68 2.01 0.01a4
Deactivations
Inferior parietal area 52 -40 60 4.20 < .001c19
Note. Results are for regions showing brain responses associated with the Highly Sensitive Person (HSP) Scale scores
moderated by Positive Childhood. MNI coordinates (x,y,z) are at the maximum value for the cluster, which may be elongated
in any direction. Legend: a overlapping area for Negative conditions; b overlapping with the Positive condition (controlling
for Neuroticism); and c overlapping with Positive x Childhood.
Bianca P. Acevedo et al.
366 Clinical Neuropsychiatry (2017) 14, 6
integrate information from the limbic, visual, auditory,
and somatosensory systems (van Overwalle et al.
2009). Several meta-analyses have suggested that the
TPJ plays a major role in attention, inferring others’
intentions, making self/other distinctions, and detecting
and reorienting attention to unexpected changes
(Decety et al. 2007, Krall et al. 2015, Saxe et al. 2006,
van Overwalle et al. 2009). In sum, it can be thought of
as processing information from multisensory systems
to “make sense” of the present moment and relevant
stimuli.
Results from the present study of SPS x QCP response
to emotional images also showed large activation
clusters in temporal areas, which are associated with
language, semantic memory processing, and visual
perception (Cabeza et al. 2000, Jagiellowicz et al.
2011, Olson et al. 2013, Tek et al. 2002). In addition,
the temporal, parietal, and TPJ regions are consistently
found in a wide range of meditation studies of the
human, including those with active-based meditation
(that involve postures, breath-work, chanting) and
mindful practices where the focus is on present-moment
awareness (Acevedo et al. 2016, Brewer et al. 2011,
Holzel et al. 2011, Yang et al. 2016).
Positive Environments and SPS: Reward,
Calm, and Self-Control
The effects of positive environments and positive
stimuli have been largely understudied in research
on SPS, differential susceptibility and biological
sensitivity to context. However, the present study
examined the effects of perceived positive childhood
environments on brain response to positive stimuli in
association with SPS. Our ndings showed greater
reward response (namely in the VTA, SN, and caudate)
as a function of SPS, and also with its interaction
with QCP such that more postive childhoods showed
stronger reward activation to positive images. These
results are particularly striking because both the VTA
and SN are major dopamine sites involved in reward
and motivation (Ikemoto 2007), and that serve basic
motivational drives for survival of the species such
as feeding and mating, and that may also be used for
pleasure such as addictive substances Robinson et
al. 2016). Also, the caudate processes object-reward
associations and mediates reward-related actions
(White et al. 2016). These results add to the conjecture
that SPS is one of several diverse strategies that may
help to promote survival of the species by deeper
processing of environmental stimuli, to learn and
memorize associations, so that decisions and behaviors
may be enacted readily upon subsequent presentations.
Certainly in the case of positive stimuli this may be
observed as greater approach behaviors and there is at
least some evidence in the present study and a previous
fMRI study of such markers in numerous motor and
premotor areas (Acevedo et al. 2014). Moreover,
a behavioral study showed that high (versus low)
SPS individuals rated positive and negative pictures,
considered together, more quickly (Jagiellowicz et al.
2016).
Additional results for positive conditions only were
shown in the PAG, an area that is well-known for its
role in pain-control and the regulation of anxiety (Bittar
et al. 2005). It is also a major site of opioid release in
the brain (Sims-Williams et al. 2016) and facilitates
fear-conditioning/extinction to stimuli (McNally et al.
2004). Also, activation of the PAG for the interaction
of SPS x QCP, was greater with increasing QCP. Again,
Hippocampal activation as a function of SPS is
especially interesting because it plays a role in memory,
associative learning (Nees et al. 2014), and is closely
situated near the entorhinal cortex (EC), a region which
plays a key role in cognitive processing of salient
emotional information (Etkin 2010). The EC is the
gateway between the hippocampus and the neocortex
(Curtis et al. 2004) and has been associated with memory
(Eichenbaum 2008) and spatial navigation (Hafting et
al. 2005). Research has shown that patients with EC
lesions experience greater spontaneous confabulations
and greater defective memory retrieval (Schnider et al.
1999). Also, the EC is affected early in Alzheimer’s
disease (AD) and mild cognitive impairment (Khan et
al. 2014, Markesbery 2010).
The hypothalamus is also notable in the context
of SPS processing as it is the center of autonomic
and physiological response regulation; with its
neurons playing essential roles in controlling stress,
metabolism, growth, reproduction, sexual behaviors,
immune response, as well as more traditional autonomic
functions such as gastrointestinal functioning,
breathing, and sleep (Carter 2014, Frodl et al. 2013). As
part of its stress-control function, it releases cortisol to
enhance emotional memory consolidation (Wingenfeld
et al. 2014, Wolf 2009). The hypothalamus also
shows increased connectivity with the hippocampus,
thalamus, amygdala, and the striatum in response to
joyful music (Koelsch 2014, Koelsch et al. 2014), as
well as other emotionally evocative stimuli. These
results support behavioral evidence that emotional
arousal, in conjunction with memory, may facilitate
deep processing of relevant incoming information,
again, the cardinal features of SPS (Aron et al. 1997).
Moreover, we see indications of how high-SPS is
expressed neurally to emotional stimuli through areas
that mediate calm, which may facilitate memory, and
adaptive SPS responsivity to emotional stimuli.
Additionally, interaction results showed that SPS
and QCP, together, evoked increased activation of
memory, emotion, physiological regulatory areas
(hippocampus, EC, and hypothalamus). Specically,
the pattern of the interaction was such that high SPS
with high QCP showed the strongest activations in
the hippocampus, EC and hypothalamus in response
to both positive (gures 1A, E, and F) and negative
(gures 2A and B) stimuli. These results substantiate
behavioral evidence that positive environments (such
as high QCP) may enhance the positive effects of SPS
through greater memory, emotion, and physiological
homeostasis.
Depth of Processing and Sensory Sensitivity
The present fMRI study of SPS also showed
activation across all conditions in areas of the default
mode network (DMN) including the precuneus,
parietal, TPJ, and temporal regions ‒ which are involved
in self/other elaboration, semantic representations, and
perceptual and present-moment awareness (Andrews-
Hanna et al. 2014, Schilbach et al. 2012, Spreng et
al. 2009, Utevsky et al. 2014). It’s interesting to note
that previous fMRI studies showed activation of the
DMN when using non-emotional stimuli ‒ such as a
change detection task using landscape photos and
when making judgments about line lengths (Aron et al.
2010, Jagiellowicz et al. 2011) ‒ as well as in response
to emotionally evocative face images (Acevedo et
al. 2014). The TPJ is an area where the temporal and
parietal lobes meet, and thus, it is well-situated to
Sensory processing sensitivity, the brain, and emotions
Clinical Neuropsychiatry (2017) 14, 6 367
awareness elicited both from internal (e.g., visceral
sensations) and external/environmental inputs (Fan et
al. 2011, Kandylaki et al. 2015, Kanwisher et al. 2000,
Maceeld et al. 2016, Simmons et al. 2013). In fact,
the insula showed signicant activation as a function of
increasing QCP (gure1C), and it replicated activations
these results suggest some of the vehicles by which
differential susceptibility exerts its effects on behavior
in positive contexts.
Other results unique to the positive condition
appeared in the insula, known for its role in self-other
processing, awareness, theory of mind, and emotional
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
FIGURE 2
A
Amygalda Hippocampus
0
1
2
3
4
B
Amygdala response intensity
at (28,-8,-12)
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
NegPar PosPar
LoHSP HiHSP
-0.3
-0.2
0
0.6
NegPar PosPar
LoHSP HiHSP
D
mPFC response intensity
at (0, 50, 40)
0.5
0.4
0.3
0.2
0.1
-0.1
C
0
1
2
3
4
medial PFC
medial PFC
Figure 2. SPS X QCP interaction is associated with adults’ brain responsivity to negative (vs. neutral) images
in the: A) amygdala and hippocampus and C) the medial PFC. Plots show that subjective positive childhood
moderates the response intensity in the B) R. amygdala and D) the L. medial PFC
Bianca P. Acevedo et al.
368 Clinical Neuropsychiatry (2017) 14, 6
response in brain areas associated with emotion
regulation. This arousal to potentially frightening or
threatening stimuli, and coupled with increased medial
PFC activation, it indicates a normal range of emotion
response (Kim et al. 2011). The results are consistent
with theories highlighting connectivity between limbic/
emotion centers and self-control areas for adaptive
inhibition of negative emotion (Lee et al. 2012). That is,
if we could hope that high quality parenting is simply
“good-enough” parenting, or normal parenting, these
results would suggest that “normal” behavior for those
high in SPS is to regulate emotions effectively and
calmly.
Other novel evidence of the mechanisms by
which high-quality childhood may promote more
adaptive responsivity to negative stimuli for high SPS
individuals also emerged. Individuals with high SPS
and high quality childhoods did not show reduced
activation of reward areas to negative stimuli (as they
did with the correlation of SPS directly controlling for
SPS). Instead they showed robust activation of regions
implicated in cognitive and emotional self-regulation.
These results are consistent with vantage sensitivity
models suggesting that highly sensitive individuals
with positive childhood environments show greater
resiliency to adverse events (Pluess et al. 2013). They are
also consistent with Rothbart’s model which highlights
reactivity and self-regulation to account for individual
differences in temperament across the lifespan (Rothbart
et al. 1981) that may ultimately impact well-being. For
example, greater impulse control to positive stimuli
(or among individuals with high reward sensitivity),
is associated with a lower risk-taking, addiction,
and lower likelihood of divorce (Jocklin et al. 1996,
Stephens et al. 2010). Here we expand on these models
by describing some potential neural mechanisms that
may be underlying these behavioral effects.
These results are promising for highly sensitive
individuals, as they suggest that high quality childhood
environment is key in promoting adaptive functioning.
Hence parenting interventions for parents of children
with high SPS may be a key for future intervention.
As adults, sensitive individuals’ apparently built-in
capacity for self-regulation may help those who have
had low quality childhoods to have better control over
their responses to incoming stimuli, so that strategies
focusing on enhancement of self-regulatory abilities
may also prove helpful for high SPS individuals. For
example, yoga and meditation have been shown to
impact areas involved in self-regulation and have
also shown enhancements in cognitive functioning in
both normative and clinical samples (Acevedo et al.
2016). Active-based meditations that involve chanting,
body and hand postures, and visualizations have
been shown to specically target areas of the brain
associated with self-regulation and the integration of
emotional, internal and external stimuli to produce
movement. Also the restfulness-focused transcendental
meditation (Yamamoto et al. 2006) might be helpful,
than mindfulness based meditations, which focus on
clearing the mind of thoughts. But all meditation types
show deactivation of the amygdala (Acevedo et al.
2016). Thus, any of these techniques may be useful
for the enhancement of self-control and diminished
emotional reactivity.
Another useful technique may be cognitive
reappraisal an emotion regulation strategy that
involves changing ones’ interpretation of a negative
situation or object so that the emotional pattern
associated with it is altered, and one may experience
more adaptive emotional responses to incoming stimuli
shown in a previous studies of response to emotional
faces (Acevedo et al. 2014, Kanwisher et al. 2000).
The present results highlight the strong effects
of positive stimuli and environments (QCP) for
individuals with high SPS and suggest that they may
be particularly susceptible to the reward, calm, arousal,
and sensory pleasures that may be evoked by positive
stimuli in key areas of the brain including the VTA/SN,
hypothalamus, and the insula (gure 1).
SPS Response to Negative Stimuli: Threat,
Diminished Reward, and the Buffering Role of
Positive Environments
One of our main targets of examination was the
amygdala, as it is a major site of emotion processing,
especially to aversive stimuli (Canli et al. 2000,
Ochsner et al. 2004, Ochsner et al. 2009, Phan et al.
2004). It failed to show signicant activation in a
prior fMRI study of SPS examining response to sad
faces (Acevedo et al. 2014). The present study showed
prominent activation of the amygdala in response to
aversive and threat-related stimuli such as pictures of
snakes and res in association with SPS by itself, and
also for the SPS x QCP interaction. Our results are in-
line with models suggesting that the amygdala seems to
be especially sensitive to threat or fear-inducing stimuli
(Phelps et al. 2005), as well as models suggesting that
emotion may play a role for SPS.
Other notable results shown for the negative condition
only, were seen in the secondary somatosensory cortex
(SII), which is involved in sensorimotor integration,
attention, learning and memory, self-perception of the
body, and afferent nociceptors (Chen et al. 2008, Lin et
al. 2002); as well as temporal areas, which are involved
in social and emotional processing, and the integration
of perceptual inputs from the environment to visceral,
auditory, olfactory and visual responses (Olson et
al. 2007). Although speculative, this may represent
readiness to act in response to threat or fear inducing
stimuli.
However, it’s interesting to note that for the SPS
x QCP interaction (compared with the simple SPS
correlation), brain signals were stronger in the dorsal
and ventral parts of the medial PFC areas involved
in cognitive self-regulation and executive control
that are classically known for their role in cognitive
processing, memory, and decision-making to support
learning adaptive emotional responses (Euston et al.
2012). Research on addiction and mood disorders has
established the mPFC’s role in self-control (Goldstein
et al. 2011). The dorsal area is thought to play a more
prominent role in understanding others’ intentions
and reective thinking (Gallagher et al. 2003, Waytz
et al. 2012) while the ventral region is more involved
in emotion-demanding tasks (Gusnard et al. 2001,
Silvers et al. 2016). Anatomically, the vmPFC is
well-positioned to receive sensory inputs from the
environment through its connections with limbic
structures, including the amygdala and hypothalamus
(e.g., Haber et al. 1995), and thus it seems to play a role
in integrating emotional signals into decision-making
processes via connections with other processing in
other limbic structures (LeDoux 2000). Also, according
to a meta-analysis of 48 emotion studies the vmPFC
appears to play a major role in cognitive reappraisal of
emotion and fear extinction (Buhle et al. 2014).
It is interesting to note that adults with high SPS
and high QCP showed enhanced amygdala activity in
response to negative stimuli, in addition to stronger
Sensory processing sensitivity, the brain, and emotions
Clinical Neuropsychiatry (2017) 14, 6 369
Figure 3. SPS (controlling for Neuroticism) is associated with decreased reward response to negative (vs. neutral)
images in the: A) VTA and C) caudate, head. Plots show decreased reward response with greater SPS in the: B) R.
VTA and D) the R. caudate, head
FIGURE 3
A
VTA
0
1
2
3
B
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.4
−0.3
−0.2
−0.1
0
0.1
0.2
0.3
0.4
HSP (controlling for Neuroticism) scores
VTA response intensity
at (0,-16,-8)
C
0
1
2
3
4
Caudate head
D
Caudate response intensity
at (20, 24, 0)
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.1
−0.08
−0.06
−0.04
−0.02
0
0.02
0.04
0.06
0.08
0.1
response at [20, 24, 0]
HSP (controlling for Neuroticism) scores
FIGURE 3
A
VTA
0
1
2
3
B
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.4
−0.3
−0.2
−0.1
0
0.1
0.2
0.3
0.4
HSP (controlling for Neuroticism) scores
VTA response intensity
at (0,-16,-8)
C
0
1
2
3
4
Caudate head
D
Caudate response intensity
at (20, 24, 0)
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.1
−0.08
−0.06
−0.04
−0.02
0
0.02
0.04
0.06
0.08
0.1
response at [20, 24, 0]
HSP (controlling for Neuroticism) scores
FIGURE 3
A
VTA
0
1
2
3
B
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.4
−0.3
−0.2
−0.1
0
0.1
0.2
0.3
0.4
HSP (controlling for Neuroticism) scores
VTA response intensity
at (0,-16,-8)
C
0
1
2
3
4
Caudate head
D
Caudate response intensity
at (20, 24, 0)
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.1
−0.08
−0.06
−0.04
−0.02
0
0.02
0.04
0.06
0.08
0.1
response at [20, 24, 0]
HSP (controlling for Neuroticism) scores
FIGURE 3
A
VTA
0
1
2
3
B
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.4
−0.3
−0.2
−0.1
0
0.1
0.2
0.3
0.4
HSP (controlling for Neuroticism) scores
VTA response intensity
at (0,-16,-8)
C
0
1
2
3
4
Caudate head
D
Caudate response intensity
at (20, 24, 0)
−2 −1.5 −1 −0.5 0 0.5 1 1.5 2
−0.1
−0.08
−0.06
−0.04
−0.02
0
0.02
0.04
0.06
0.08
0.1
response at [20, 24, 0]
HSP (controlling for Neuroticism) scores
(Boden et al. 2012, Gross 1998). A few meta-analyses
to date have shown that cognitive reappraisal exerts
its effects via brain regions associated with cognitive
control (the dmPFC, vmPFC, dlPFC, and vlPFC), self-
reection (posterior parietal areas), and modulation of
emotion in the bilateral amygdala (Buhle et al. 2014,
Diekhof et al. 2011).
Finally, an intervention designed to develop
resilience and thereby prevent depression in adolescent
girls had a similar positive effect, but only on those
high in SPS (Pluess et al. 2015). Thus it may be most
important to continue to test whether highly sensitive
individuals seem to respond particularly well to positive
interventions in general.
Limitations and Future Directions
This is now the fourth study investigating the neural
correlates of SPS that may provide a foundation for
determining the biological underpinnings of this trait.
Although our sample size was small and comprised
of women only, we implemented several techniques
to increase effect sizes including selecting the top and
bottom quartile HSP scorers and only women. The
power was sufcient to reveal signicant a-priori and
meaningful unexpected ndings. Nevertheless, it will
be important to conrm these results with a larger and
more diverse sample, including males, to examine
potential gender differences. Also considering that
measures of reported childhood environment were
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retrospective, it is possible that individuals who recall
their childhoods as more positive may have a general
tendency to see the “silver lining”. Thus, it may not
be that they had more positive childhoods, but that
their ability to respond positively arose in some other
way, still reecting the overall pattern of enhanced
cortical activations associated with self-control and the
attenuation of diminished reward activity. However,
this would seem unlikely for high SPS individuals,
who appear to have deeply integrated information from
their childhoods and family life (even if challenging)
to create a coherent narrative. Longitudinal studies
measuring childhood environment with subsequent
brain responses will be useful to clarify this issue.
Conclusions
This study provides evidence of the neural
correlates underlying SPS that demonstrate the greater
emotional responsiveness associated with it, and
accounting for the effects of the recollected quality of
one’s childhood environment (QCP). Results showed
signicant involvement of subcortical and cortical
circuits associated with emotion, memory, reective
thinking, awareness and regulation of physiological
homeostasis supporting basic tenets of SPS suggesting
that it is mediated via emotion and depth of processing.
Results also support differential susceptibility models,
in that neural signals were generally amplied for those
with high QCP in these regions, as well as in major
reward circuits (the VTA, SN, and caudate) in response
to positive (but not negative) images. Further, in those
high in SPS, high QCP may promote adaptive responses
to emotional stimuli via higher order cortical systems
involved in awareness, reective thinking, and self-
regulation (the TPJ, precuneus/parietal lobe, and PFC);
and specically to negative stimuli via the attenuation
of diminished brain reward response.
Acknowledgements
Manuscript based on data used in a doctoral
dissertation by Jadzia Jagiellowicz. We thank Turhan
Canli, Anne Moyer, Nelly Alia-Klein, Everett Waters,
and Hoi-chung Leung for providing assistance and
support that made this research possible. We also
thank all our research assistants, for their assistance
with data collection, data organization, and running
of experiments including Dana Jessen, and Lauren
Espejo, Rachel Han, Aja Macias, Miriam Magana, Kate
Matyjaszek, and Kelly Yu.
Author Contributions
J.J. and A.A. designed the fMRI experiment and
collected the fMRI data. E.A. provided guidance
on measures and theoretical constructs. B.A. and
R.M. analyzed and organized the fMRI data. B.P.A.
interpreted the data and wrote the manuscript with
contributions from all authors.
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... These studies investigated SPS-related brain activity during resting states with different methods. For example, one fMRI study examined neural correlates of SPS in response to emotional versus neutral pictures (Acevedo et al., 2017). In this study, participants' neural activity was recorded while and after they viewed six alternating blocks of respectively four pictures with the same valence (positive, negative) and a block of four neutral pictures at the beginning of the scanning session. ...
... Previously described fMRI research on SPS consistently demonstrated that positive as well as negative emotional (vs. neutral) stimuli evoked greater hippocampal activity as a function of SPS (e.g., Acevedo et al., 2017). Thus, in contrast to previously described studies on introversioneextraversion, SPS seems to generally support memory processing for emotional material, independent of its valence. ...
... As was discussed in the previous section, the majority of fMRI studies on SPS reported increased hippocampal activity as a function of SPS during resting states (Acevedo et al., 2017). Even though this activity does not necessarily indicate neural replay, it still suggests a more prevalent depth in memory postprocessing as a function of SPS. ...
Chapter
The idea that individual differences in sensitivity to the environment interact with an individual’s ability to encode, store and retrieve information in memory is not new. In fact, since the very beginning of psychological research, scientists quickly noted that more sensitive, introverted individuals were faster to form conditioned responses and learned differently well under various conditions. These individual variations in conditioning laid the bases for modern differential psychology and concepts like introversion and sensory processing sensitivity. Yet, through declining interest in conditioning research and the increasing institutional and methodological separation of experimental and differential psychology, the highly important investigation of temperament-memory interactions only plays a minor role in the current scientific debate. However, the tendency of more sensitive individuals to inhibit behavior when facing novel information, in order to allow for deeper information processing and reflection are highly related to memory consolidation and the formation of habits. In this chapter, I will review previous advances in introversion, anxiety and other related research and will integrate this knowledge with new evidence from neuropsychological and behavioral research in the field of sensory processing sensitivity. I will discuss how the greater effort that higher sensitive individuals exert to process and consolidate information, affects their ability to maintain those information. Based on this review I will present a new model, describing the interaction of individual differences in SPS with learning and memory. This model explains new findings, indicating that the activity after learning is especially important for the highly sensitive. While, highly sensitive individuals are more prone to the detrimental effects of retroactive interference, they demonstrate better memory retention if they have the time to rest after learning new information.
... En la década de los noventa, la psicóloga Elaine Aron definió la Alta Sensibilidad como un rasgo de personalidad (Pardo, 2018) cuya prevalencia está en torno al 15-20% de la población mundial (Aron, 1996). Sin embargo, hay otros autores que hacen referencia a la misma realidad con diferentes nomenclaturas como Sensibilidad del Procesamiento Sensorial (SPS) (Acevedo et al., 2017), Sensibilidad Ambiental (Pluess, 2015;Bridges y Schendan, 2018) o sobreexcitabilidad (Dabrowski, 1964). Dicho autor, psiquiatra, es previo a Elaine Aron, pero desde su teoría de la personalidad ya atisbaba que esta forma de ser la presentaban algunas personas y no implicaba ninguna patología. ...
... Finalmente, el hallazgo de esta investigación va dirigido a las diferencias encontradas en cuanto al sexo, donde, a pesar de los estudios de Elaine Aron (1999), Acevedo (2017), Pluess (2015) e, incluso, Chacón et al. (2021), se ha podido observar que existen diferencias estadísticamente significativas en cuanto a la sensibilidad en población española, siendo estas diferencias a favor de las mujeres (ellas son más sensibles). ...
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El presente estudio pretende probar las propiedades psicométricas de la adaptación transcultural realizada por Chacón et al. (2020) de la escala HSP de Aron (1996). Para ello, se procedió en primer lugar a comprobar la fiabilidad y validez de constructo del instrumento a través de un análisis factorial confirmatorio para datos categóricos (CFA). En concreto, se usó un procedimiento de ajuste a los datos ordinales utilizando la matriz de correlación policórica combinada con el estimador DWLS (Diagonally Weighted Least Squares). Para la consistencia interna se calcularon el coeficiente alfa ordinal y el coeficiente Omega de McDonald's cuyos resultados confirmaron las puntuaciones obtenidas por Chacón et al. (2020). Las personas que participaron en el estudio fueron estudiantes de la Universidad Rey Juan Carlos y lo hicieron de manera anónima y voluntaria. Finalmente se quiso cotejar si existían diferencias en cuanto al sexo respecto a la sensibilidad y obtuvimos la existencia de diferencias estadísticamente significativas en todas las dimensiones (sensibilidad a la sobreestimulación (SOS), sensibilidad estética (AES), umbral sensorial bajo (LST), discriminación psicofisiológica fina (FPD) y (HA) evitación al daño). Concluimos, por tanto, que la escala HSP validada para población española es eficaz, pero se recomienda replicar estudios con muestras más amplias y comprobar si en España contamos con diferencias significativas en la sensibilidad ligada al sexo.
... This higher average SPS level among teacher population potentially suggests that highly sensitive individuals may be more predispose to look for meaningful professions, particularly in education and helping roles. Additionally, the greater empathy characteristic of highly sensitive people could influence their choice of an educational profession, which implies relationships based on care and growth (Acevedo et al., 2017;Aron et al., 2012;Black & Kern, 2020). This result could also due to the fact that highly sensitive teacher are more likely to be stressed and the higher average SPS could be driven by higher scores in items related to the ease of excitation SPS aspect. ...
Article
School teachers are among workers most exposed to stress and burnout—a relevant occupational phenomenon leading to psychological and economic costs. The Environmental Sensitivity individual trait—as captured by the psychological marker of sensory processing sensitivity (SPS)—has been found to have a relevant role in stress and emotional exhaustion at work. Yet, little is still known about heightened SPS in the educational field and on underlying mechanisms occurring in the relationship between SPS, stress and burnout. The current work aimed to explore the association between SPS and burnout among teachers as well as the moderating role of perceived stress and school climate in this association. One hundred and ninety eight teachers (44.3 years; SD = 9.7, 94% F) reported on their levels of SPS, occupational burnout, perceived stress and school climate quality. In line with a vulnerability effect, we found heightened SPS largely associated with burnout. This was particularly evident in a context of high‐perceived stress, suggesting that teachers high on SPS may experience more challenges in the face of elevated stress with the need of more support. When exposed to positive and supportive school climate, highly sensitive teachers showed a decrease in burnout, suggesting high SPS as a valuable strength for benefiting from positive experiences. Findings have the potential to inform the customisation of support programs, assisting both schools and work agencies in increasing their awareness of the role of individual differences in responding to both work‐demand‐related stress and to positive work environments.
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This study investigated whether sensory processing sensitivity (SPS) is associated with a perceptual advantage, above just heightened brain, emotional and behavioural reactivity. Participants (N = 222) were tested on detection and identification of visually degraded words at three levels of difficulty, and completed the Highly Sensitive Person Scale (HSPS) and the Big Five Inventory. The positive subscale of the HSPS predicted both the detection and identification of visually degraded stimuli, beyond the Big Five traits. This contradicts claims that SPS is solely a combination of Big Five traits. Importantly, the perceptual advantage for highly sensitives may balance the disadvantages of being easily overwhelmed by stimuli and indicates separate evolutionary advantages and strategies for high and low SPS humans and other mammals.
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This study examined the relation between interparental conflict and cortisol recovery, with child temperamental negative affectivity as the moderator. Children ( n = 118) ages 9–11 years observed an argument between their parents in the lab and provided saliva samples for cortisol assays. Children also reported levels of interparental conflict, and mothers reported their child's negative affectivity. Results showed that youths with high levels of negative affectivity experienced less cortisol recovery as interparental conflict levels increased. Further, demonstrating some support for differential susceptibility, youths with higher levels of negative affectivity exhibited less recovery at high levels of parental conflict but greater recovery at low levels of parental conflict, compared to peers with lower scores on negative affectivity. We also found that children with low levels of negative affectivity exhibited greater recovery as rates of interparental conflict increased. In summary, this study sheds light on sources of variability in cortisol recovery as it relates to interparental disharmony.
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The main aim of this review article is to describe the sensory processing sensitivity trait (SPS). People with this trait are highly sensitive individuals and the pertinent literature states that they make up 20% to 30% of the general population. The paper outlines the theories that originally explained the high sensitivity of a certain segment of the population, the results of the studies that explored the discriminant validity of the Highly Sensitive Person Scale, the studies that examined the relationships between the SPS trait and personality dimensions, and the studies on the quality of mental health of highly sensitive individuals. Although there is an increasing number of studies on highly sensitive people worldwide, this has not been the case in our region. Consequently, experts (psychologists, psychotherapists and psychiatrists) in Serbia and the region are largely unfamiliar with this trait. Hence, it is possible to confuse the SPS trait with a personality dimension (neuroticism, introversion, shyness, etc.) or to diagnose a disorder in highly sensitive individuals (autism, attention deficit hyperactivity disorder, etc.). In addition, a very large number of newspaper articles on various internet portals about highly sensitive people may imply that high sensitivity in our region is only described through the lens of popular psychology. All this can lead to a misunderstanding of this scientific construct. Considering that the literature indicates that approximately a quarter of the general population is highly sensitive, it is extremely important that professionals become more familiar with the sensory processing sensitivity trait.
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With high rates of violence exposure among justice‐involved youth, it is critical to identify factors that might impact the likelihood of youth engaging in violence themselves. One such factor is sensitivity to context, which describes how sensitive youth are to experiences in their environment. Using an ethnically diverse sample of justice‐involved male adolescents (47% Latino, 38% Black/African American, 15% White) aged 13‐17 at the time of their first arrest, the results of this study indicate that exposure to violence was related to increased violent behavior six months later, and this effect was strongest among youth who were low in sensitivity to context. These findings may help practitioners identify which youth are at greatest risk for violence in a policy‐relevant population.
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During the past decade, research on the biological basis of sensory processing sensitivity (SPS)—a genetically based trait associated with greater sensitivity and responsivity to environmental and social stimuli—has burgeoned. As researchers try to characterize this trait, it is still unclear how SPS is distinct from seemingly related clinical disorders that have overlapping symptoms, such as sensitivity to the environment and hyper-responsiveness to incoming stimuli. Thus, in this review, we compare the neural regions implicated in SPS with those found in fMRI studies of—Autism Spectrum Disorder (ASD), Schizophrenia (SZ) and Post-Traumatic Stress Disorder (PTSD) to elucidate the neural markers and cardinal features of SPS versus these seemingly related clinical disorders. We propose that SPS is a stable trait that is characterized by greater empathy, awareness, responsivity and depth of processing to salient stimuli. We conclude that SPS is distinct from ASD, SZ and PTSD in that in response to social and emotional stimuli, SPS differentially engages brain regions involved in reward processing, memory, physiological homeostasis, self-other processing, empathy and awareness. We suggest that this serves species survival via deep integration and memory for environmental and social information that may subserve well-being and cooperation. This article is part of the theme issue ‘Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences’.
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and Keywords This chapter provides an overview of theory and research addressing temperament and personality, particularly as these are relevant to clinical applications. Our review begins with a brief history of influential frameworks and foundational constructs, including aspects they share in common and others engendering disagreement. Measurement approaches, development of temperament/personality, the biological underpinnings, and studies addressing cross-cultural and gender differences, are also noted in this review. The chapter concludes with problems in adaptation associated with temperament, focusing on ameliorating those difficulties through clinical applications of temperament and personality constructs with children and adults. Importantly, a developmental, empirically focused perspective informed this chapter, and as a result, this work includes references to developmental periods from early childhood to adulthood, emphasizing approaches that have received empirical support.
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Objectives Meditation has been shown to have physical, cognitive, and psychological health benefits that can be used to promote healthy aging. However, the common and specific mechanisms of response remain elusive due to the diverse nature of mind–body practices. Methods In this review, we aim to compare the neural circuits implicated in focused-attention meditative practices that focus on present-moment awareness to those involved in active-type meditative practices (e.g., yoga) that combine movement, including chanting, with breath practices and meditation. Recent FindingsRecent meta-analyses and individual studies demonstrated common brain effects for attention-based meditative practices and active-based meditations in areas involved in reward processing and learning, attention and memory, awareness and sensory integration, and self-referential processing and emotional control, while deactivation was seen in the amygdala, an area implicated in emotion processing. Unique effects for mindfulness practices were found in brain regions involved in body awareness, attention, and the integration of emotion and sensory processing. Effects specific to active-based meditations appeared in brain areas involved in self-control, social cognition, language, speech, tactile stimulation, sensorimotor integration, and motor function. SummaryThis review suggests that mind–body practices can target different brain systems that are involved in the regulation of attention, emotional control, mood, and executive cognition that can be used to treat or prevent mood and cognitive disorders of aging, such as depression and caregiver stress, or serve as “brain fitness” exercise. Benefits may include improving brain functional connectivity in brain systems that generally degenerate with Alzheimer’s disease, Parkinson’s disease, and other aging-related diseases.
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To learn, obtain reward and survive, humans and other animals must monitor, approach and act on objects that are associated with variable or unknown rewards. However, the neuronal mechanisms that mediate behaviours aimed at uncertain objects are poorly understood. Here we demonstrate that a set of neurons in an internal-capsule bordering regions of the primate dorsal striatum, within the putamen and caudate nucleus, signal the uncertainty of object-reward associations. Their uncertainty responses depend on the presence of objects associated with reward uncertainty and evolve rapidly as monkeys learn novel object-reward associations. Therefore, beyond its established role in mediating actions aimed at known or certain rewards, the dorsal striatum also participates in behaviours aimed at reward-uncertain objects.
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The fourth edition of Atlas of the Human Brain presents the anatomy of the brain at macroscopic and microscopic levels, featuring different aspects of brain morphology and topography. This greatly enlarged new edition provides the most detailed and accurate delineations of brain structure available. It includes features which assist in the new fields of neuroscience – functional imaging, resting state imaging and tractography. Atlas of the Human Brain is an essential guide to those working with human brain imaging or attempting to relate their observations on experimental animals to humans. Totally new in this edition is the inclusion of Nissl plates with delineation of cortical areas (Brodmann’s areas), the first time that these areas have been presented in serial histological sections.
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Emotion regulation is a critical life skill that develops throughout childhood and adolescence. Despite this development in emotional processes, little is known about how the underlying brain systems develop with age. This study examined emotion regulation in 112 individuals (aged 6–23 years) as they viewed aversive and neutral images using a reappraisal task. On “reappraisal” trials, participants were instructed to view the images as distant, a strategy that has been previously shown to reduce negative affect. On “reactivity” trials, participants were instructed to view the images without regulating emotions to assess baseline emotional responding. During reappraisal, age predicted less negative affect, reduced amygdala responses and inverse coupling between the ventromedial prefrontal cortex (vmPFC) and amygdala. Moreover, left ventrolateral prefrontal (vlPFC) recruitment mediated the relationship between increasing age and diminishing amygdala responses. This negative vlPFC–amygdala association was stronger for individuals with inverse coupling between the amygdala and vmPFC. These data provide evidence that vmPFC–amygdala connectivity facilitates vlPFC-related amygdala modulation across development.