Mirella Dapretto, PhD: Sensory Over-Responsivity in ASD: Insights from Neuroimaging

Sensory Over-Responsivity in ASD:
Insights form Neuroimaging
Mirella Dapretto, Ph.D.
Dept. of Psychiatry and Biobehavioral Sciences
Semel Institute for Neuroscience and Human Behavior
UCLA David Geffen School of Medicine
CART Symposium April 22, 2016

Acknowledgments
Funding Agencies
NICHD P50 HD055784
NIH T32 GM008042
NIH T32 MH073526
SFARI 345389
Trainees
Leanna Hernandez
Kathy Lawrence
Janele Liu
Aarti Nair
Jeff Rudie
Ashley Scott-Van Zeeland
Deanna Greene
Amy Hubbard
Jennifer Pfeifer
Ting Wang

Collaborators
Susan Bookheimer
Dan Geschwind
Pat Levitt
Marian Sigman
All Children Who Participated in Our Studies & Their Families!

Acknowledgments
Tawny Tsang

Shula Green

Outline
•  Sensory Over-Responsivity (SOR):
- Autism Spectrum Disorders
- Other Developmental Disorders
•  Mechanisms and Neural Correlates of SOR:
- Altered Brain Responsivity to Sensory Stimulation
- Altered Brain Connectivity in the Salience Network
•  Avenues for Future Research:
- SOR: Links to Early Social Attention
- Better Assessment Tools -> Targeted Interventions

Future Directions:
New Focus on Sensory Responsivity
CART Symposium January 31, 2014
Autistic traits are associated with diminished neural
response to affective touch
Avery C. Voos, Kevin A. Pelphrey, and Martha D. Kaiser
Yale Child Study Center, Yale University, New Haven, CT, USA
‘Social brain’ circuitry has recently been implicated in processing slow, gentle touch targeting a class of slow-conducting, unmyelinated nerves, CT
afferents, which are present only in the hairy skin of mammals. Given the importance of such ‘affective touch’ in social relationships, the current
functional magnetic resonance imaging (fMRI) study aimed to replicate the finding of ‘social brain’ involvement in processing CT-targeted touch and to
examine the relationship between the neural response and individuals’ social abilities. During an fMRI scan, 19 healthy adults received alternating
blocks of slow (CT-optimal) and fast (non-optimal) brushing to the forearm. Relative to fast touch, the slow touch activated contralateral insula, superior
temporal sulcus (STS), medial prefrontal cortex (mPFC), orbitofrontal cortex (OFC) and amygdala. Connectivity analyses revealed co-activation of
the mPFC, insula and amygdala during slow touch. Additionally, participants’ autistic traits negatively correlated with the response to slow touch in
the OFC and STS. The current study replicates and extends findings of the involvement of a network of ‘social brain’ regions in processing CT-targeted
affective touch, emphasizing the multimodal nature of this system. Variability in the brain response to such touch illustrates a tight coupling of
social behavior and social brain function in typical adults.
Keywords: affective touch; autistic traits; CT-afferent; fMRI; social brain
Touch enables us to navigate not only the physical world but also the
social world. This dual dimensionality of touch has been described
as being processed in the brain in a manner similar to pain, via two
dissociable dimensions categorized as, sensory-discriminative and
motivational-affective (Morrison et al., 2010). Although the perception
of discriminative touch, which allows us to perceive pressure, vibra-
tion, slip and texture has historically dominated the touch literature
(McGlone et al., 2007), neuroscientists have only recently begun to
study ‘affective’ or social touch (Francis et al, 1999; Olausson et al.,
2002, 2008; Rolls et al., 2003; McGlone et al., 2007; McCabe et al.,
2008; Loken et al., 2009; Keysers et al., 2010; Morrison et al., 2010,
2011;Gordon et al., 2011;). This type of pleasant, gentle touch has been
linked to a class of slow-conducting, unmyelinated nerves, CT affer-
ents, present only in the hairy skin of mammals, including humans
(Sugiura et al., 1986; Craig, 2003). Lamina I neurons continue through
the lamina I spinothalamical pathway and project to the insular cortex
(Olausson et al., 2002; Craig, 2003). For this reason, and because the
insular cortex has been considered a gateway from sensory systems to
the emotional system of the frontal lobe (Augustine, 1996; Craig,
2008), initial neuroimaging studies of the brain mechanisms involved
in processing CT-targeted affective touch focused on the posterior
insula (Olausson et al., 2002; McCabe et al., 2008). Recently, our
group (Gordon et al., 2011) used functional magnetic resonance ima-
ging (fMRI) to demonstrate the involvement of several key nodes of
the ‘social brain’ in processing such touch. The social brain describes a
circumscribed set of brain regions that have evolved to support social
cognition. In her seminal writing on this idea, Leslie Brothers (1990)
called this set of regions the social brain and included the amygdala,
doi:10.1093/scan/nss009 SCAN (2013) 8, 378^386
atUniversityofCalifornia,Lohttp://scan.oxfordjournals.org/Downloadedfrom
NEW RESEARCH
Overreactive Brain Responses to Sensory
Stimuli in Youth With Autism Spectrum
Disorders
Shulamite A. Green, M.A., Jeffrey D. Rudie, Ph.D., Natalie L. Colich, M.A.,
Jeffrey J. Wood, Ph.D., David Shirinyan, Ph.D., Leanna Hernandez, M.A.,
Nim Tottenham, Ph.D., Mirella Dapretto, Ph.D., Susan Y. Bookheimer, Ph.D.
Objectives: Sensory over-responsivity (SOR), deﬁned as a negative response to or avoidance of
sensory stimuli, is both highly prevalent and extremely impairing in youth with autism spectrum
disorders (ASD), yet little is known about the neurological bases of SOR. This study aimed to
examine the functional neural correlates of SOR by comparing brain responses to sensory stimuli
in youth with and without ASD. Method: A total of 25 high-functioning youth with ASD and
25 age- and IQ-equivalent typically developing (TD) youth were presented with mildly aversive
auditory and visual stimuli during a functional magnetic resonance imaging (fMRI) scan. Parents
NEW RESEARCH
Overreactive Brain Responses to Sensory
Stimuli in Youth With Autism Spectrum
Disorders
Shulamite A. Green, M.A., Jeffrey D. Rudie, Ph.D., Natalie L. Colich, M.A.,
Jeffrey J. Wood, Ph.D., David Shirinyan, Ph.D., Leanna Hernandez, M.A.,
Nim Tottenham, Ph.D., Mirella Dapretto, Ph.D., Susan Y. Bookheimer, Ph.D.
provided ratings of children’s SOR and anxiety symptom severity. Results: Compared to TD
participants, ASD participants displayed greater activation in primary sensory cortical areas as
well as amygdala, hippocampus, and orbital-frontal cortex. In both groups, the level of activity
in these areas was positively correlated with level of SOR severity as rated by parents, over
provided ratings of children’s SOR and anxiety symptom severity. Results: Compared to TD
participants, ASD participants displayed greater activation in primary sensory cortical areas as
well as amygdala, hippocampus, and orbital-frontal cortex. In both groups, the level of activity
in these areas was positively correlated with level of SOR severity as rated by parents, over
and above behavioral ratings of anxiety. Conclusions: This study demonstrates that youth
with ASD show neural hyper-responsivity to sensory stimuli, and that behavioral symptoms of
SOR may be related to both heightened responsivity in primary sensory regions as well as
areas related to emotion processing and regulation. J. Am. Acad. Child Adolesc. Psychiatry,
2013;52(11):1158–1172. Key Words: amygdala, anxiety, autism spectrum disorders, functional
magnetic resonance imaging (fMRI), sensory over-responsivity
C
hildren with autism spectrum disorders
(ASD) often display impairments in
responding to sensory stimuli, in addition
to the core symptoms of ASD, which include
impairments in language and reciprocal social
behavior. Sensory over-responsivity (SOR) is
characterized by an extreme negative response to,
or avoidance of, sensory stimuli such as noisy or
visually stimulating environments, sudden loud
noises, seams in clothing, or being touched un-
expectedly.1
About 56% to 70% of children with
ASD meet criteria for SOR2,3
compared to 10% to
17% of typically developing (TD) children.3,4
SOR
is associated with increased functional impair-
ment in children with ASD, including lower
levels of social and adaptive skills,1,5
negative
emotionality,6
and anxiety.5,6
Despite the prevalence of and considerable
impairment caused by SOR in children with
ASD, there is a paucity of research on the neuro-
biological bases of SOR. Research in this area is
critical to help explain heterogeneity within ASD,
and can inform intervention targeted at speciﬁc
subgroups of children with ASD. In one of the few
functional MRI (fMRI) studies of response to
nonsocial sensory stimuli in children with ASD,
Gomot et al.7
found that early adolescents with
ASD responded faster to novel sounds than did
TD controls, and had higher activation in pre-
frontal and inferior parietal regions but no differ-
ences in activation of auditory cortex. The authors
theorized that novel auditory stimuli are initially
processed normally but receive differential atten-
tion from the novelty detection circuit. Similarly,
Hadjikani et al.8
presented expanding circles of
color to adults with and without ASD, and found
no between-group differences in visual cortex
retinotopic maps. However, some electroenceph-
alography (EEG) studies have found group dif-
ferences in event-related potentials (ERPs) in
response to tones, which may suggest an atypical
response to sound in the primary auditory cortex.9
JOURNAL OF THE AMERICAN ACADEMY OF CHILD & ADOLESCENT PSYCHIATRY
1158 www.jaacap.org VOLUME 52 NUMBER 11 NOVEMBER 2013

Sensory Over-Responsivity (SOR)
•  Extremely common in ASD
-  Rates estimated between 56-70%
(Baranek et al., 2006; Ben-Sasson et al. 2007)
- Compared to 10-17% in typically
developing youth (Ben-Sasson et al., 2009)
•  Characterized by negative reaction to,
and avoidance of sensory stimulation
•  Associated with lower social and
adaptive skills, more behavioral and
internalizing problems, especially
anxiety (e.g., Ben-Sasson et al., 2008; Liss et al., 2006;
Pfeiffer et al., 2005)

Neural Over-Responsitivity
to Sensory Stimuli in Youth with ASD

+
(sound)
+
+
(sound)
3 sec
3 sec
Jittered
1.25-3.5 sec
Jittered
1.25-3.5 sec
Green et al, JACAAP, 2013

Neural Over-Responsitivity
to Sensory Stimuli in Youth with ASD
-1
-0.5
0
0.5
1
1.5
-2 0 2 4
HippocampusPE
SOR Composite (Std. Res.)
TD
ASD
Z
1.7
2.
3
ASD TD
TD
LL
ASD
1
.
7
L
ASD
>TD
L
Green et al, JACAAP, 2013

Neural Basis of SOR (Cont’d)

Neural Basis of SOR:
Auditory and Tactile Stimulation
+
+ + + + + + +
(Auditory) (Tactile) (Joint)
12.5 sec 15 sec 12.5 sec 15 sec 12.5 sec 15 sec 12.5 sec
(x4)
Green et al, JAMA Psychiatry, 2015

Behavioral Assessment
-0.7
-0.2
0.3
0.8
1.3
1.8
ASD SOR ASD no SOR TD no SOR
SOR composite
0
5
10
15
20
25
ASD SOR ASD no SOR TD no SOR
SCARED Anxiety
•  Short Sensory Profile – SSP (Dunn, 1999)
•  Sensory Over-Responsivity Inventory - SensOR (Schoen et al., 2008)
•  SOR Composite Score = SSP tactile sensitivity, auditory filtering &
auditory/visual sensitivity + SenSOR auditory & tactile subscales
•  Screen for Child Anxiety Related Emotional Disorders - SCARED
(Birmaher et al., 1997)

Neural Responsivity to Both
Auditory and Tactile Stimulation
Green et al, 2015,
JAMA Psychiatry

SOR Severity Correlates
with Neural Over-Responsivity
Green et al, 2015, JAMA Psychiatry

Mechanisms Underlying SOR:
Reduced Habituation
p=.
05
p=.
04
ASD no SOR
ASD SOR
TD no SOR

Mechanisms Underlying SOR:
Reduced Prefrontal Regulation
TD>ASD
Amygdala Seed

Salience Network
•  Detects and integrates external sensory information with internal
emotional and bodily states
•  Balances attentional resources between internal and external stimuli
•  Coordinates dynamic interplay between other brain networks
implicated in self-referential thinking/social cognition (Default Mode
Network) and externally driven action (Central Executive Network)

Salience Network OverConnecHvity in ASD
criminating ASD from TD, we focused on exploring relation-
ships with this specific network. We found that the salience
network was related to restricted and repetitive behaviors as
dren with ASD from TD peers. We found that childhood au-
tism is characterized by hyperconnectivity of major large-
scale brain networks and that the salience network may be a
Figure 2. Brain Network Hyperconnectivity in Children With Autism Spectrum Disorder (ASD) Compared With Typically Developing (TD) Children
0.95
x=–2 y=16 z=–4
0.96 0.97 0.98 0.99 1.00 0.95 0.96 0.97 0.98 0.99 1.00
x=–19 y=–78 z=38
0.95
x=–4 y=–57 z=41
0.96 0.97 0.98 0.99 1.00 0.95 0.96 0.97 0.98 0.99 1.00
x=–2 y=–89 z=10
0.95
x=–52 y=–3 z=19
0.96 0.97 0.98 0.99 1.00 0.95 0.96 0.97 0.98 0.99 1.00
x=–54 y=–34 z=–1
Salience
Motor
Posterior Default Mode
Visual Association
Primary Visual
Frontotemporal
A
B
C
D
E
F
Autism spectrum disorder greater than TD functional connectivity was
observed in 6 of the 10 networks examined: salience (A), posterior default
mode (B), motor (C), visual association (D), primary visual (E), and
frontotemporal (F). Group difference maps were thresholded using
threshold-free cluster enhancement (P < .05).
Research Original Investigation Salience Network–Based Classification
Uddin et al, JAMA Psychiatry, 2013
ASD > TD
Connectivity
in 6 out of 10
Networks

Salience Network Overconnectivity
as a Biomarker of ASD
Figure 3. Classification Analysis and Accuracy
50
80
75
ClassificationAccuracy,%
Train on Individual
Participants Networks
... n-1
ASD ASD TD TD
Leave-One-Out
Cross-Validation
Test on Left-Out
Participants Network
70
65
60
55
Salience Central Posterior Ventral Anterior Dorsal Motor Visual Primary Frontotemporal
ASD or TD?
A
B
Salience Network–Based Classification Original Investigation Research
Figure 3. Classification Analysis and Accuracy
50
80
75
Component
Train on Individual
Participants Networks
... n-1
ASD ASD TD TD
Leave-One-Out
Cross-Validation
Test on Left-Out
70
65
60
55
Salience Central
Executive
Posterior
DMN
Ventral
DMN
Anterior
DMN
Dorsal
Attention
Motor Visual
Association
Primary
Visual
Frontotemporal
ASD or TD?
A
B
A, Classification analysis flowchart. The 10 components identified from each participant served as features to be input into classification analyses. A linear classifier
built using logistic regression was used to classify children with autism spectrum disorder (ASD) from typically developing (TD) children. B, Classification accuracy
for brain networks. The salience network produced the highest classification accuracy at 78% (P = .02). DMN indicates default mode network.
Table 2. Brain Network Connectivity Patterns for Children With Autism Spectrum Disorder From Typically Developing Children
Classification Sensitivity, Specificity, Positive Predictive Negative Predictive
Salience Network–Based Classification Original Investigation Research
frontal and posterior cortical regions.6,65,66
It is not yet clear
how connectivity measures can be affected by methodologic
choices.5
In addition, few studies have addressed the ques-
autism, at times more proximal to the onset of the disorder.37
Wereporthyperconnectivityofseveralmajorlarge-scalebrain
networks in children with autism. We found that in the sa-
50
80
75
Component
Leave-One-Out
Cross-Validation
Test on Left-Out
70
65
60
55
Salience Central
Executive
Posterior
DMN
Ventral
DMN
Anterior
DMN
Dorsal
Attention
Motor Visual
Association
Primary
Visual
Frontotemporal
ASD or TD?
B
A, Classification analysis flowchart. The 10 components identified from each participant served as features to be input into classification analyses. A linear classifier
built using logistic regression was used to classify children with autism spectrum disorder (ASD) from typically developing (TD) children. B, Classification accuracy
for brain networks. The salience network produced the highest classification accuracy at 78% (P = .02). DMN indicates default mode network.
Table 2. Brain Network Connectivity Patterns for Children With Autism Spectrum Disorder From Typically Developing Children
Network
Classification
Accuracy, %
Sensitivity,
%
Specificity,
%
Positive Predictive
Value, %
Negative Predictive
Value, % P Value
Salience 78 75 80 79 76 .02
Salience (independent
data set)
83 67 100 100 75 .02
Dorsal attention 73 75 70 71 74 .06
Primary visual 73 60 85 80 68 .06
Motor 68 60 75 71 65 .15
Frontotemporal 68 60 75 71 65 .16
Visual association 65 65 65 65 65 .21
Default mode
Anterior 63 50 75 67 60 .28
Posterior 63 65 60 62 63 .29
Ventral 60 55 65 61 59 .36
Central executive 58 55 60 58 57 .47

SOR and Salience Network Connectivity
Higher levels of SOR in ASD = Greater connectivity between SN
and regions implicated in sensory processing and attention
Green et al, JACAAP, In Press

SOR and Salience Network Connectivity
Green et al, JACAAP, In Press
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
-0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
AI-amygdala connec:vity
during res:ng state
Amygdala ac:va:on during sensory s:mula:on
R2=.38
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
-0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4
AI-SMS connec:vity during
res:ng state
SMS ac:va:on during sensory s:mula:on
R2=.44

Early Salience Network Connectivity
Salience Network in Neonates

The “Infant Sibs” Approach
•  Recurrence rate within families in community samples is
~ 10% (vs. ~1% in the general populaHon)
•  Rate in higher, ~ 20%, in prospecHve studies of infants at
high-risk (HR) for ASD (Ozonoﬀ et al, 2011), parHcularly in
mulHplex families (~45% for boys!)
•  By comparing prospecHve data collected in HR infants
who later do or do not meet diagnosHc criteria for ASD,
we may idenHfy early markers of later diagnosis
•  Early idenHﬁcaHon = early intervenHon to ameliorate, or
even prevent, onset of full symptomatology

Salience Network Connectivity
in Infants at High & Low Risk for ASD
2.3
8.0 High Risk
Infants
Low Risk
Infants

Altered Salience Network Connectivity
in Infants at High Risk for ASD
1.7
3.0
High Risk > Low Risk:
Greater ConnecHvity with
Somatosensory CorHces
Low Risk > High Risk:
Greater ConnecHvity with
Frontal Regions

Future Directions:
SOR and Social Attention
•  From birth, neonates have been shown to respond preferenHally to the
human voice, parHcularly their mother s (e.g., DeCasper & Feifer 1980)
•  A visual preference for faces is also seen from the first days of life in typically
developing infants (e.g., Valenza et al 1996, Conellan et al 2001)
•  Children with auHsm do not seem to show a preference for listening to their
mother s voice (e.g., Klin 1992, Dawson et al 1998) and prefer a non-speech analog to
motherese (Kuhl et al 2005)
•  Decreased afenHon to faces is one of the first noHceable symptoms of ASD
(e.g., Osterling & Dawson 1994, Osterling et al 2002, Chawarska et al 2010)
•  This lack of afenHon to social sHmuli may lead to a cascade of negaHve
consequences for later social development that could account for the core
deficits in ASD (Dawson et al, 1998)
Can early SOR be related to decreased social a3en4on?

Future Directions:
Assessing Sensory Responsivity

Future Directions:
SOR across Clinical Populations

Interested in Our Studies?
Just email us at:
auHsm.ucla@gmail.com
Or call us at:
310- 825-3478
(ACE Infant Sibs Study)
310-825-5326
(ACE Network Study, age: 8-16)

Mirella Dapretto, PhD: Sensory Over-Responsivity in ASD: Insights from Neuroimaging

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