autism spectrum disorder: does neuroimaging...

ORIGINAL PAPER

Autism Spectrum Disorder: Does Neuroimaging Supportthe DSM-5 Proposal for a Symptom Dyad? A Systematic Reviewof Functional Magnetic Resonance Imaging and Diffusion TensorImaging Studies

Laura Pina-Camacho • Sonia Villero • David Fraguas • Leticia Boada •

Joost Janssen • Francisco J. Navas-Sanchez • Maria Mayoral •

Cloe Llorente • Celso Arango • Mara Parellada

Published online: 20 September 2011

� Springer Science+Business Media, LLC 2011

Abstract A systematic review of 208 studies comprising

functional magnetic resonance imaging and diffusion tensor

imaging data in patients with ‘autism spectrum disorder’

(ASD) was conducted, in order to determine whether these

data support the forthcoming DSM-5 proposal of a social

communication and behavioral symptom dyad. Studies

consistently reported abnormal function and structure of

fronto-temporal and limbic networks with social and prag-

matic language deficits, of temporo-parieto-occipital net-

works with syntactic–semantic language deficits, and of

fronto-striato-cerebellar networks with repetitive behaviors

and restricted interests in ASD patients. Therefore, this

review partially supports the DSM-5 proposal for the ASD

dyad.

Keywords Autism spectrum disorder � Autistic disorder �Asperger syndrome � Functional magnetic resonance

imaging � Diffusion tensor imaging

Introduction

The diagnostic criteria for autistic disorders are undergoing

scrutiny in preparation for the forthcoming revision to the

DSM system (see: www.dsm5.org). Based on the literature,

workgroup discussions, and clinical and research findings

(Klin and Volkmar 2003; Levy et al. 2009), and taking up

the concept introduced by Lorna Wing in the 1990s (Wing

1996), the DSM-5 classification aims to integrate autistic

disorder, Asperger syndrome (AS), childhood disintegra-

tive disorder, and pervasive developmental disorder-not

otherwise specified (PDD-NOS) into a single diagnostic

category: ‘autism spectrum disorder’ (ASD). Instead of the

classical ‘social-communication-behavioral’ triad, broad-

ened by DSM-III-R classification in 1987 (American Psy-

chiatric Association 1987) and maintained in DSM-IV

(American Psychiatric Association 1994), DSM-5 proposes

a symptom dyad for ASD, which would consist of (a) the

presence of deficits in social communication and interac-

tions and (b) the presence of repetitive patterns of behavior,

interests, and activities. In addition, ASD diagnosis would

be adapted to the individual’s clinical presentation by

inclusion of clinical specifiers, such as severity or verbal

abilities, and of associated features, such as known genetic

disorders or intellectual disability (ID). The authors of the

DSM-5 justify the change to the dyad by considering

deficits in communication and social behaviors as

Electronic supplementary material The online version of thisarticle (doi:10.1007/s10803-011-1360-4) contains supplementarymaterial, which is available to authorized users.

L. Pina-Camacho (&) � L. Boada � J. Janssen � M. Mayoral �C. Llorente � C. Arango � M. Parellada

Child and Adolescent Psychiatry Department, Hospital General

Universitario Gregorio Maranon, Centro de Investigacion

Biomedica en Red de Salud Mental, CIBERSAM, C/Ibiza, 43,

Madrid 28009, Spain

e-mail: [email protected]

S. Villero

Unit of Child and Adolescent Mental Health, Department of

Psychiatry, Complejo Hospitalario Mancha Centro, Alcazar de

San Juan, Ciudad Real, Spain

D. Fraguas

Mental Health Department, Complejo Hospitalario Universitario

de Albacete, Centro de Investigacion Biomedica en Red de Salud

Mental, CIBERSAM, Albacete, Spain

F. J. Navas-Sanchez

Department of Experimental Medicine, Hospital General

Universitario Gregorio Maranon, Centro de Investigacion

Biomedica en Red de Salud Mental, CIBERSAM, Madrid, Spain

123

J Autism Dev Disord (2012) 42:1326–1341

DOI 10.1007/s10803-011-1360-4

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http://dx.doi.org/10.1007/s10803-011-1360-4

inseparable and more accurately considered as a single set

of symptoms with contextual and environmental specifici-

ties. Thus, for diagnosis, both criteria would have to be

completely fulfilled, which would improve the specificity

of the diagnosis without impairing sensitivity (see:

www.dsm5.org).

Therefore, the classical DSM-IV social interaction

cluster, defined by impairments in the social abilities of

mentalizing and empathizing (Baron-Cohen 2002; Baron-

Cohen et al. 1985), and the communication cluster, which

includes impairments in semantic-syntactic language

comprehension, in the pragmatic use of language, and in

prosody of speech (Rapin and Dunn 2003), would be col-

lapsed by DSM-5 into a single symptom domain: the social

communication and interaction symptom cluster (see

www.dsm5.org), whereas language delay is proposed as a

clinical specifier and not a diagnostic criterion.

Do neuroimaging findings in ASD support this proposal

of a dyadic grouping? From the beginning, research has

highlighted the role of several specific brain regions in the

pathogenesis of ASD (Volkmar and Pauls 2003). Since the

first findings in the late eighties (Courchesne et al. 1987;

Garber et al. 1989), research in ASD used structural

magnetic resonance imaging (sMRI) (Mana et al. 2010) to

identify specific brain regions affected in this disorder and

the relationship between impaired brain structure and

clinical features (Hardan et al. 2009). The most replicated

sMRI findings in brains of patients with ASD compared

with controls are the increase in total brain volume (TBV),

cerebellar hemispheres volume and caudate nucleus vol-

ume, together with a reduction of the corpus callosum

volume (CCV) (Stanfield et al. 2008). Some sMRI studies

have found several correlations between brain structural

abnormalities and ASD symptoms. For instance, increased

volume of the caudate in autistic patients has been corre-

lated with the severity of repetitive behaviors (Hollander

et al. 2005). However, the sMRI data are still too variable

to adequately elucidate brain-behavior relationships

(Palmen and van Engeland 2004). This may be due to

methodological and design limitations of these studies,

including the use of small and heterogeneous samples with

regard to age, sex, intelligence quotient (IQ) cut-off,

diagnostic criteria, etc. (Stanfield et al. 2008), and also to

the fact that ASD deficits are not always related to ana-

tomical, but often to functional abnormalities (Minshew

and Williams 2007).

In the past decade, some childhood and adolescent

neurobehavioral disorders, such as ASD, have been

described as disorders of impaired structural and functional

network connectivity (Frank and Pavlakis 2001; Stevens

2005). Brains of patients with ASD apparently present

inter- and intra-hemispheric functional ‘underconnectivity’

compared with the general population, together with

reduced structural integrity of white matter (WM) tracts

(Hughes 2007; Minshew and Williams 2007; Muller 2007;

Williams and Minshew 2007). In view of these findings,

current research paradigms in ASD are assessing impair-

ment of specific brain networks instead of focusing on

specific brain regions (Muller 2008). From this research,

new concepts have emerged, such as ‘ASD multi-system

brain disconnectivity–dyssynchrony (MBD)’ (Gepner and

Feron 2009) and ‘developmental disconnection disorder’

(Geschwind and Levitt 2007). However, it is not clear

whether ‘aberrant connectivity’ should be seen as part of

the primary pathogenesis of autism, or whether disrupted

connectivity in ASD emerges over time (Wass 2011).

According to the latter, neuroimaging techniques such as

functional magnetic resonance imaging (fMRI) and diffu-

sion tensor imaging (DTI) can be used to study functional

and structural brain connectivity, respectively (Basser

1995; Marti-Climent et al. 2010), both providing useful

information about the neuroanatomical correlates of ASD

deficits (Deb and Thompson 1998; Rumsey and Ernst

2000; Verhoeven et al. 2010).

Functional MRI detects activation signals based on

increased blood flow and blood oxygenation in regions of

enhanced synaptic transmission (Logothetis 2003) (see

Table 1). In ASD, fMRI provides additional information

(Minshew and Keller 2010), as it can detect functional

changes in anatomically intact brain regions, including

local abnormal activation and abnormal functional con-

nectivity between regions when performing a mental task

or even at rest (Marti-Climent et al. 2010). The presence of

these impaired networks has been related to different

impaired social, communication, and behavioral processes

in ASD (Di Martino et al. 2009a). Furthermore, fMRI

studies conducted in patients with ASD, their siblings, and

healthy controls, have provided further information by

studying differences in brain circuitry and compensatory

activity among them (Kaiser et al. 2010).

A further technique that provides information on the

structure of local and diffuse cortical networks is diffusion

tensor imaging (DTI). This technique analyses the struc-

tural integrity of WM tracts by measuring the diffusion of

water molecules along the axons (Basser and Pierpaoli

1996) (see Table 1). DTI studies have described impaired

network structural connectivity and, sometimes, correlated

it to social, communication, or behavioral deficits of

patients with ASD (Ke et al. 2009).

Given the forthcoming diagnostic changes in the

DSM-5, it would be interesting to know whether findings

published to date from fMRI and DTI studies’ in ASD

support this proposal of a symptom dyad. In particular, it

would be helpful to know whether the social and com-

munication deficits that are seen in ASD appear to be

associated with the shared differences in brain networks, so

J Autism Dev Disord (2012) 42:1326–1341 1327

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they can be collapsed into a single domain, and whether these

networks are different from those that have been associated

with repetitive behaviors and restricted interests. Thus, the

objective of this systematic review is to determine if fMRI

and DTI findings on ASD support a neuroanatomical sub-

strate for the DSM-5 proposal of a symptom dyad.

Methods

According to the PRISMA guidelines (Preferred Reporting

Items for Systematic Reviews and Meta-Analyses) (Liberati

et al. 2009; Moher et al. 2009), a systematic Medline/Pubmed

review of the literature published in English between January

1990 and April 2011 was conducted on functional MRI and

DTI imaging studies in ASD. The following database search

strategy was used: (‘‘Autism spectrum disorders’’[All Fields]

OR ‘‘Asperger syndrome’’[All Fields] OR ‘‘Asperger’s syn-

drome’’[All Fields] OR ‘‘Autistic disorder’’[All Fields]) OR

‘‘CDD’’[All Fields] OR ‘‘Childhood disintegrative disor-

der’’[All Fields]) AND (‘‘Magnetic resonance imaging’’[All

Fields] OR ‘‘Diffusion tensor imaging’’[All Fields]) NOT

pubstatusaheadofprint. In press papers were not included, as

not all of those were available in full text.

After the database search, 612 records were identified

and screened. Out of these, 190 full-text articles were eli-

gible, as they fulfilled all the following inclusion criteria:

(a) being a review or an original article; (b) including

patients with ASD, autistic disorder and/or Asperger syn-

drome; and (c) using a functional MRI and/or a DTI

imaging technique. A total of 422 full-text articles were

excluded because a) they were not a review or an original

article (n = 20); (b) they did not focus on patients with

ASD, Asperger or autism (n = 67); (c) they did not pro-

vide any neuroimaging data (n = 73); or (d) they provided

only sMRI, PET, or SPECT imaging data (n = 262). We

also identified 18 relevant articles that were referenced in

these 190 eligible studies but did not appear in the initial

database search. Thus, a total of 208 studies were finally

included in this review.

We decided not to include Rett syndrome in this review,

as it has disappeared from the DSM-5 proposal on the

grounds that although autistic features of Rett syndrome

are sometimes indistinguishable from autism, they are only

present during a certain phase of the condition, i.e.,

between 1 and 3 years of age, and will alter such that they

no longer meet criteria for ASD diagnosis, and there are

clear gene markers for Rett syndrome—MeCP2 and

CDKL5 (see www.dsm5.org). Regarding CDD, after con-

ducting the search with combination of these terms:

(‘‘CDD’’[All Fields] OR ‘‘Childhood disintegrative disor-

der’’[All Fields] AND (‘‘Magnetic resonance imaging’’[All

Fields] OR ‘‘Diffusion tensor imaging’’[All Fields]), there

were no papers fulfilling our inclusion criteria.

Studies were classified according to the neuroimaging

technique used as follows: (a) fMRI studies using tasks

related to social cognition and interaction, (b) fMRI studies

using language-related tasks, (c) fMRI studies using tasks

related to repetitive behaviors or restricted interests,

(d) studies using ‘fMRI at resting state,’ and (e) studies

using a DTI technique. Within each fMRI study, we

extracted the information about the affected regions in

patients with ASD compared with healthy controls, in

terms of abnormal activity (hypo- or hyper-activation) or

functional connectivity (abnormal activation time series of

this brain region within a brain network). Similarly for DTI

studies, we looked at those affected regions and networks

in patients with ASD compared with controls, in terms of

abnormal structural integrity of WM tracts.

Results

Of the 208 articles included in this review, 120 studies

were original articles using an fMRI and/or DTI technique

and comparing imaging data of patients with ASD and

controls, one of those being a meta-analysis (Di Martino

et al. 2009a). They are all summarized in Figs. 1 and 2. The

‘y’ axis of both figures shows different brain regions and

networks. The ‘x’ axis shows different grayscale shaded

Table 1 Main neuroimaging techniques

Neuroimaging

technique

Assessed issue Basis of image construction

Structural

neuroimaging

(sMRI)

Volumetric measurements in regions of interest

(ROI)

Volumetric data

Functional

neuroimaging

(fMRI)

Regional brain activation

Functional connectivity: correlation between the

activation time series of two brain areas

Blood flow and oxygenation in regions and networks with

enhanced synaptic transmission during a mental task or at rest

Diffusion tensor

imaging (DTI)

Structural connectivity: microstructural integrity of

selected networks

Based on directionality of diffusing water molecules of WM tracts

1328 J Autism Dev Disord (2012) 42:1326–1341

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bars, each representing a different neuroimaging technique.

The length of each bar represents the number of neuro-

imaging studies describing an abnormal activity and/or

functional or structural connectivity within any given brain

region in patients with ASD compared with controls.

Figure 1 shows data from 59 fMRI studies using social

cognition and interaction-related tasks (represented by

black bars within the figure), five fMRI studies using

semantic-pragmatic-related tasks (represented by light gray

bars), ten studies using syntactic-semantic-related tasks

(represented by gray striped bars), and nine fMRI studies

using tasks related to repetitive behaviors and restricted

interests (represented by dark gray bars). Figure 2 includes

data from nine studies exploring the default mode network

by using ‘fMRI at resting state’ (represented by gray hat-

ched bars), and 28 studies used a DTI technique (three of

them in combination with an fMRI language-related tech-

nique and one of them in combination with an fMRI

repetitive behavior-related technique). These DTI studies

are represented by gray dotted bars. Additional data from

these fMRI and DTI studies have been displayed inde-

pendently in Supplementary Tables 1, 2, 3, and 4.

Symptom Cluster (a) Proposal: Deficits in Social

Communication and Interaction

Social Cognition and Interaction Deficits

Functional MRI studies using a social cognitive-related

task and comparing brain activation and connectivity pat-

terns in brains of patients with ASD and controls are rep-

resented by black bars within Fig. 1. Processing of facial

expressions is, by far, the task most frequently used to

assess social cognition in functional studies of ASD, fol-

lowed by gaze-processing tasks or mentalization-related

tasks (Ashwin et al. 2007; Baron-Cohen et al. 1999, 2006;

Bird et al. 2010; Bolte et al. 2008; Bookheimer et al. 2008;

Corbett et al. 2009; Chiu et al. 2008; Dalton et al. 2005,

Fig. 1 Main fMRI studies on

ASD social, language, and

behavioral deficits. The ‘y’ axis

shows different brain regions

and networks. The ‘x’ axis

shows different grayscaleshaded bars, each representing a

different fMRI task-related

technique. The length of each

bar represents the number of

neuroimaging studies describing

an abnormal activity and/or

functional connectivity within

any given brain region in

patients with ASD compared

with controls. R-LAT right-

lateralization, PFC prefrontal

cortex, IFG inferior frontal

gyrus, MNs mirror neuron

system, F lobe frontal lobe, Tlobe temporal lobe, FG fusiform

gyrus, LIMB limbic system

(including amygdala and

hippocampus), ACC anterior

cingulate cortex, CING middle

or posterior cingulate, INSinsula, P lobe parietal lobe, Olobe occipital lobe, CBcerebellum, STR striatum, EVCearly visual cortex, EXT-STRextra striate visual areas


123

2007, 2008; Dapretto et al. 2006; Deeley et al. 2007; Di

Martino et al. 2009a; Dichter and Belger 2007, 2008;

Greimel et al. 2010b; Grezes et al. 2009; Hadjikhani et al.

2004, 2007, 2009; Hall et al. 2010a; Hubl et al. 2003;

Humphreys et al. 2008; Kana et al. 2009; Kleinhans et al.

2008b, 2009, 2011; Knaus et al. 2008; Koshino et al. 2008;

Lombardo et al. 2010; Malisza et al. 2011; Mason et al.

2008; Monk et al. 2010; Nishitani et al. 2004; Noonan et al.

2009; Oktem et al. 2001; Pelphrey et al. 2005, 2007; Pierce

et al. 2001, 2004; Pierce and Redcay 2008; Piggot et al.

2004; Scott-Van Zeeland et al. 2010a; Schmitz et al. 2008;

Schulte-Ruther et al. 2011; Schultz et al. 2000; Shamay-

Tsoory et al. 2010; Shih et al. 2010; Silani et al. 2008;

Spengler et al. 2010; Takeuchi et al. 2004; Uddin et al.

2008; Wang et al. 2004, 2007; Welchew et al. 2005;

Williams et al. 2006).

For the majority of ‘face-processing studies,’ ASD sub-

jects have decreased activation of the fusiform gyrus (FG),

especially of the face-fusiform area (FFA), and an inability to

vary the activity of this area when varying the intensity of the

facial emotional expression. Other replicated findings during

performance of social-related tasks include the abnormal

activation and connectivity of fronto-temporal cortical net-

works, including the mirror neuron system (located in the

inferior frontal gyrus and strongly related to mentalization

abilities) or the anterior cingulate cortex (ACC), and sub-

cortical networks such as the amygdala-hippocampal system

(see Fig. 1, black bars).

The findings of abnormal activation of these brain net-

works associated with impaired social cognitive processing

are corroborated by fMRI studies performed during a passive

‘resting state’ (Assaf et al. 2010; Cherkassky et al. 2006; Di

Martino et al. 2011; Kennedy and Courchesne 2008a, 2008b;

Kennedy et al. 2006; Lai et al. 2010; Monk et al. 2009; Paakki

et al. 2010; Weng et al. 2010). In patients with ASD, the

‘default mode network,’ which includes the posterior

Fig. 2 Main fMRI resting-state and DTI studies on ASD. The ‘y’

axis shows different brain regions and networks. The ‘x’ axis shows

different grayscale shaded bars, each representing a different

neuroimaging technique. The length of each bar represents the

number of neuroimaging studies describing an abnormal activity and/

or functional or structural connectivity within any given brain region

in patients with ASD compared with controls. R-LAT right-laterali-

zation, PFC prefrontal cortex, IFG inferior frontal gyrus, MNs mirror

neuron system, F lobe frontal lobe, T lobe temporal lobe, FG fusiform

gyrus, LIMB limbic system (including amygdala and hippocampus),

ACC anterior cingulate cortex, CING middle or posterior cingulate,

INS insula, P lobe parietal lobe, O lobe occipital lobe, CB cerebellum,

STR striatum, EVC early visual cortex, EXT-STR extra striate visual

areas, CC corpus callosum, IC internal capsule, LF longitudinal

fasciculus, AF arcuate fasciculus


123

cingulate cortex, retrosplenial cortex, lateral parietal cortex,

angular gyrus, medial prefrontal cortex, superior frontal

gyrus, temporal lobe, and parahippocampal gyrus, shows

impaired activity and intrinsic connectivity during a passive

resting state (see Fig. 2, gray hatched bars). This abnormal

connectivity underlies the abnormal social processing and

social impairments in these patients with ASD.

Similarly, DTI supports these MRI findings by showing

a reduced integrity of WM tracts that are part of these

‘social’ fronto-temporal cortical and subcortical networks

(Alexander et al. 2007; Barnea-Goraly et al. 2004; Barnea-

Goraly et al. 2010; Ben Bashat et al. 2007; Bloemen et al.

2010; Brito et al. 2009; Brun et al. 2009; Catani et al. 2008;

Conturo et al. 2008; Cheng et al. 2010; Cheung et al. 2009;

Groen et al. 2011; Jou et al. 2011; Ke et al. 2009; Keller

et al. 2007; Knaus et al. 2010; Lange et al. 2010; Lee et al.

2007a; Noriuchi et al. 2010; Pardini et al. 2009; Pugliese

et al. 2009; Sahyoun et al. 2010; Shukla et al. 2010a, 2011;

Sivaswamy et al. 2010; Sundaram et al. 2008; Thakkar

et al. 2008; Weinstein et al. 2011). See Fig. 2, gray dotted

bars.

Language Processing and Communication Deficits

Concerning fMRI findings in this field, studies use tasks

related either to the syntactic–semantic or to the semantic-

pragmatic component of language. When performing a

syntactic-semantic task, patients with ASD show hyperac-

tivation of Wernicke’s area [instead of the typical activa-

tion of the inferior frontal gyrus (IFG) seen in controls],

reduced or reversed leftward activation asymmetry, and a

tendency to use early visual (parieto-occipital) pathways to

support word processing and reasoning (see Fig. 1, gray

striped bars) (Gaffrey et al. 2007; Harris et al. 2006; Just

et al. 2004; Kana et al. 2006; Kleinhans et al. 2008a; Knaus

et al. 2008, 2010; Redcay and Courchesne 2008; Sahyoun

et al. 2010; Scott-Van Zeeland et al. 2010b; Soulieres et al.

2009). Additionally, one study combining an fMRI syn-

tactic/semantic task and DTI found reduced WM integrity

in tracts of the arcuate fasciculus, which connects Broca’s

and Wernicke’s areas (Knaus et al. 2010). Another similar

study found greater engagement of posterior brain regions

in patients with ASD with respect to controls along with

weaker connections to frontal language areas (Sahyoun

et al. 2010). For DTI studies, see Fig. 2, gray dotted bars.

On the other hand, when performing semantic-pragmatic

tasks, the most replicated findings include lower activation

signals in the left IFG (Broca’s area), prefrontal cortex, and

temporo-parietal areas in brains of patients with ASD

compared with controls, exhibiting functional undercon-

nectivity and undersynchronization within these regions

(Anderson et al. 2010; Hesling et al. 2010; Tesink et al.

2009; Wang et al. 2006, 2007) (see Fig. 1, light gray bars).

Moreover, the lower the activity in these networks, the

more severe the degree of language impairment (Wang

et al. 2007).

Symptom Cluster (b) Proposal: Repetitive Patterns

of Behavior, Interests, and Activities

Compared to fMRI and DTI studies on social and language

deficits in ASD, there are far fewer studies assessing this

symptom cluster. Functional MRI studies that use tasks

assessing repetitive and stereotyped behaviors and autistic

traits, such as resistance to change and obsessive traits (see

Fig. 1, dark gray bars) (Agam et al. 2010; Di Martino et al.

2009b; Gomot et al. 2008; Kana et al. 2007; Lee et al.

2009b; Monk et al. 2009; Shafritz et al. 2008; Thakkar

et al. 2008), together with fMRI studies exploring default

network activity (see Fig. 2, gray hatched bars), have

related these symptoms to abnormal functional connectiv-

ity in patients with ASD compared with controls, within

fronto-cerebellar network, fronto-striatal system, anterior

and posterior cingulate, posterior parietal regions, posterior

regions of corpus callosum (CC), cerebellar vermis and

peduncles (Assaf et al. 2010; Cherkassky et al. 2006; Di

Martino et al. 2011; Kennedy and Courchesne 2008a, b;

Kennedy et al. 2006; Lai et al. 2010; Monk et al. 2009;

Paakki et al. 2010; Weng et al. 2010). These findings are

corroborated by DTI studies showing reduced integrity of

WM tracts that are part of these impaired networks (see

Fig. 2, gray dotted bars) (Alexander et al. 2007; Barnea-

Goraly et al. 2004, 2010; Ben Bashat et al. 2007; Bloemen

et al. 2010; Brito et al. 2009; Brun et al. 2009; Catani et al.

2008; Conturo et al. 2008; Cheng et al. 2010; Cheung et al.

2009; Groen et al. 2011; Jou et al. 2011; Kana et al. 2007;

Ke et al. 2009; Keller et al. 2007; Knaus et al. 2010; Lange

et al. 2010; Noriuchi et al. 2010; Pardini et al. 2009;

Pugliese et al. 2009; Sahyoun et al. 2010; Shukla et al.

2010a, 2011; Sivaswamy et al. 2010; Sundaram et al. 2008;

Thakkar et al. 2008; Weinstein et al. 2011). Finally, dis-

rupted local activation and connectivity in the aforesaid

networks (including the cerebellum, fronto-striatal system,

etc.) have been related to executive function impairments

in patients with ASD, suggesting a common neuroana-

tomical substrate for these deficits (Gilbert et al. 2008; Just

et al. 2007; Silk et al. 2006; Solomon et al. 2009).

Discussion

Functional MRI and DTI findings support the notion that

the brains of patients with ASD share a global pattern of

abnormal structural and functional connectivity and syn-

chronization within different brain networks. Considering

the DSM-5 proposal for a symptom dyad in ASD, a review


123

of these studies provides support for separate neuroana-

tomical substrates for the social communication and the

behavioral symptom domains. However, the available

neuroimaging data only partially support the collapse of the

classical social and language symptom domains into a

single ‘social communication’ domain.

Globally considering the processing strategies of

patients with ASD, studies point to the presence of

abnormal connectivity between areas involved in high

order and low order perception processes (Castelli et al.

2002), and to their tendency to favor local over global

aspects when processing information (Hubl et al. 2003;

Manjaly et al. 2007; Minshew and Williams 2007; Muller

et al. 2003).

Functional MRI studies during social tasks and DTI

studies find in brains of patients with ASD an abnormal

structural and/or functional connectivity of cortical and

subcortical regions and networks such as the prefrontal

cortex, inferior frontal gyrus, temporal and cingulate cor-

tex, or the amygdala-fusiform system. Some authors term

all these regions the ‘social areas of the brain’ (Ashwin

et al. 2007). These regions typically activate in healthy

subjects when performing a social-related task (Gamer and

Buchel 2009; Greimel et al. 2010a; Hall et al. 2010b),

whereas they show abnormal patterns of activation or

connectivity in patients with ASD, this being consistently

related to ASD social deficits. On the other hand, func-

tional MRI-resting state studies in patients with ASD show

impaired activity and intrinsic connectivity in the ‘default

mode network’ (DMN) during a passive resting state. The

DMN includes some regions that are activated at rest, in

the absence of any task, such as the medial prefrontal

cortex, retrosplenial cortex/posterior cingulate cortex or

precuneus, among other regions. This DMN typically

activates when individuals are engaged in internally

focused tasks including autobiographical memory retrieval,

envisioning the future, and conceiving the perspectives of

others (Broyd et al. 2009; Buckner et al. 2008; Kennedy

and Courchesne 2008b; Weng et al. 2010). The abnormal

activity and intrinsic connectivity of this network may

underlie the abnormal social processing and social

impairments in patients with ASD. Social deficits, such as

impaired face processing, usually coexist with deficits in

processing socially relevant auditory information (Gervais

et al. 2004) or in viewing social animations involving

geometric shapes (Klin 2008), and contrast with normal

visual processing of objects and places (Humphreys et al.

2008). In fact, ASD patients have strategies that suggest

more non-face object perception (Schultz et al. 2000),

maybe because they base this processing on visual infor-

mation and not on the social significance of the stimuli

(Bookheimer et al. 2008). This may be due to the presence

of more pronounced impairment in later developing

cortical systems (e.g., face-processing system), than earlier

maturing systems (e.g., those that process objects and

places) (Humphreys et al. 2008). Finally, several studies

indicate that some clinical characteristics, such as level of

social anxiety, may mediate the neural response to this

emotional and social cognition processing (Kleinhans et al.

2010).

Supporting these neuroimaging findings related to social

deficits in ASD, there is one study conducted in general

population that found a positive correlation between par-

ticipant scores on the Social Responsiveness Scale-Adult

version (SRS-A) and the degree of ACC-insula functional

connectivity in a resting state (Di Martino et al. 2009b).

Moreover, some studies support a brain functional overlap

between the aforesaid ‘social regions’ and other neuro-

cognitive processes, These include autobiographical

memory processing (Cabeza et al. 2004; Markowitsch et al.

2000; Spreng et al. 2009), which is commonly impaired in

patients with ASD (Adler et al. 2010; Crane and Goddard

2008; Lind and Bowler 2010), as well as motor processing

(Allen and Courchesne 2003; Allen et al. 2004; Brieber

et al. 2010; Dinstein et al. 2010; Martineau et al. 2010;

Mizuno et al. 2006; Mostofsky et al. 2009; Muller et al.

2001, 2003, 2004; Villalobos et al. 2005) and attention

processing (Dichter and Belger 2007). These data suggest a

common neuroanatomical substrate for all these ASD

deficits (Mostofsky et al. 2009).

The specific contribution of each region and neural

network to these brain-based social deficits still remains

unclear (Dinstein et al. 2010) and seems to be very com-

plex (Williams 2008).For instance, it seems that sometimes

reduced function in a specific network could be due to the

influence on its activity by other structures, e.g., the

reduced activity of the FG during face processing could be

due to a modulatory influence of the amygdala (Schultz

2005) or the posterior cingulate (Klin 2008).

Regarding the communication cluster, this review sup-

ports an overlapped neuroanatomical substrate for seman-

tic-pragmatic and social cognitive deficits in ASD brains,

which is different from the syntactic-semantic deficit sub-

strate. In fact, semantic-pragmatic deficits are more related

to abnormal activity in the left IFG, (Broca’s area), pre-

frontal cortex and temporo-parietal regions, which are also

much more related to social-cognitive and Theory of Mind

(ToM) deficits (see Fig. 1). On the other hand, syntactic-

semantic deficits in ASD are much more related to

decreased activity of the IFG and increased activity of

Wernicke’s area, to the use of visual pathways to support

language comprehension, and to the presence of reduced or

reversed leftward asymmetry. This ‘visually-mediated’

language processing coexists in these patients with abnor-

mal visuomotor processing, showing a functional overlap

between both cognitive processes, where the processing


123

strategy depends to an abnormally large extent on activa-

tion of parieto-occipital pathways (Belmonte et al. 2010;

Belmonte and Yurgelun-Todd 2003; Bolte et al. 2008;

Damarla et al. 2010; Keehn et al. 2008; Ring et al. 1999;

Shukla et al. 2010b). The distinction between the syntactic-

semantic and semantic-pragmatic component of language

has been supported by neuropsychological and neuroim-

aging studies. Neuropsychological studies tend to distin-

guish between patients with a ‘semantic-pragmatic

disorder’, also called ‘pragmatic language impairment’

(PLI), versus those with a ‘syntactic-semantic disorder’ or

‘specific language impairment’ (SLI). PLI subjects have a

profile where language is fluent, complex, and clearly

articulated, but there are abnormalities in the way in which

language is used, in understanding and producing con-

nected discourse. These patients use stereotyped language

with abnormal intonation and prosody and give conversa-

tional responses that are socially inappropriate (Bishop and

Norbury 2002). In contrast, SLI has been explained as a

language impairment specifically affecting processing of

grammar (the syntax and morphology of language) or of

words (Ullman 2004). There is still a debate about whether

PLI is a communicative difficulty only found in verbal

people with autism or not (Bishop and Norbury 2002).

Some authors report that PLI is often seen in high-func-

tioning autistic patients but is not restricted to them alone

(Rapin and Allen 1987), while others think that PLI is a

form of high-functioning autism, with a much closer neu-

ropsychological relationship between PLI and autistic dis-

order than between PLI and typical SLI (Shields et al.

1996). In fact, Bishop et al. (2008) reported that many adult

individuals with autism had been identified with pragmatic

impairments in childhood. Finally, it has even been sug-

gested that PLI is an intermediate disorder between SLI

and core autism (Bishop et al. 2000) or that SLI, PLI and

ASD are related disorders that vary along qualitative

dimensions of language structure, language use, and cir-

cumscribed interests (Whitehouse et al. 2009). Concerning

neuroimaging findings supporting the distinction between

syntactic and semantic-pragmatic deficits, we find fMRI

studies conducted in a healthy population reporting that

syntactic-semantic processing tasks usually involve a

strongly left-dominant activation pattern in the IFG

(Broca’s area) and superior and middle temporal gyri

(Wernicke’s area) (Chou et al. 2006; Holland et al. 2007),

whereas semantic-pragmatic processing underlies more

‘posterior language areas,’ such as the temporo-parietal

junction, and clearly produces a more bilateral distribution

of activation than syntactic-semantic processing (Holland

et al. 2007; Otzenberger et al. 2005). Additionally, it has

been suggested that declarative memory and word pro-

cessing deficits (both components of a SLI), which are

frequently impaired in patients with ASD, share an

abnormal temporo-parietal substrate, as do working mem-

ory and grammar acquisition impairments (another com-

ponent of SLI deficit), sharing a fronto-striatal-cerebellar

overlap (Ullman 2004). In fact, some fMRI studies

exploring working memory in brains of patients with ASD

have described aberrant connectivity of this network,

compared with controls, when performing related tasks

(Koshino et al. 2005; Lee et al. 2007b; Luna et al. 2002;

Manjaly et al. 2007; Ring et al. 1999). In summary, further

studies of these so-called ‘language pathways,’ conducted

in healthy populations and both in patients with specific

language impairments and with ASD would be of great

interest in disentangling which aspects of language pertain

to the ASD domain and which correspond to an indepen-

dent set of disorders.

Finally, regarding the proposed symptom cluster of

‘repetitive patterns of behavior, interests, and activities,’

fMRI and DTI studies have described reduced activation and

connectivity in brains of patients with ASD compared with

controls, mainly within fronto-striatal and posterior brain

structures, such as the posterior parietal lobe, posterior cin-

gulate, posterior corpus callosum and cerebellum, with less

involvement of the ‘social brain areas’ (Courchesne et al.

2004; Cheung et al. 2009; Keller et al. 2007). These networks

also show abnormal function when patients with ASD per-

form an executive function or a working memory task,

suggesting that these deficits may share a common neuro-

anatomical substrate with this behavioral symptom cluster

(Schmitz et al. 2006).

Supporting conclusions of this systematic review, we

find fMRI and DTI studies conducted in other population

groups, such as general population with autistic traits (Di

Martino et al. 2009b), samples of patients with psychosis

and social cognitive deficits (Abdi and Sharma 2004;

Pinkham et al. 2008; Sasson et al. 2007), patients with

cerebellar malformations (Tavano et al. 2007) or injury to

the cerebellar vermis (Limperopoulos et al. 2007), very low

birth weight children with WM injury (Skranes et al. 2007),

and subjects with the fragile X premutation (Hessl et al.

2007) or the fragile X syndrome (Garrett et al. 2004). All

the clinical groups above may demonstrate social, com-

munication, and behavioral impairments that are similar to

those seen in ASD, and have differences in neural con-

nectivity that are demonstrable in similar brain regions and

networks.

However, there are some limitations that could bias the

conclusions of this systematic review. Firstly, fMRI ‘task-

related’ studies do not always characterize cognitive,

emotional, and behavioral responses simultaneously, which

would be a more accurate way to gauge their interaction

(Klin 2008). Secondly, results of task-related studies could

be biased by the confounding effect of abnormal visual

fixation patterns commonly present in patients with ASD


123

and of their lower degree of success, motivation, and

interest when performing these tasks (Hadjikhani et al.

2006; Klin 2008; Yerys et al. 2009). Thirdly, studies usu-

ally point to the presence of highly variable individualistic

responses in different patients with ASD (Hasson et al.

2009), and tend not to differentiate between subgroups,

such as patients with autism (low- and high-functioning) or

patients with Asperger syndrome. Only a small number of

studies have been conducted in patients with Asperger

syndrome (Bloemen et al. 2010; Catani et al. 2008;

Nishitani et al. 2004; Oktem et al. 2001; Pugliese et al.

2009; Shamay-Tsoory et al. 2010), and none of them have

directly compared processing abnormalities between

patients with high-functioning autism and patients with

Asperger syndrome, which may be interesting for refining

the neuroanatomical substrate of their language and social

deficits. Fourthly, fMRI and DTI studies have been fraught

with limitations such as small sample sizes, cross-sectional

designs, heterogeneous subject characteristics, and varying

methodologies (Stigler et al. 2011). They should be con-

ducted longitudinally (Brambilla et al. 2004) in larger

samples of ASD children, and preferably with a wider

range of IQ. For instance, we only found a single DTI study

comparing patients with low-functioning autism (LFA) and

age-matched healthy controls, describing lower fractional

anisotropy (FA) values in brains of LFA patients at the

orbitofrontal cortex and a positive relationship between FA

values and IQ in patients with LFA (Pardini et al. 2009).

Finally, generalization of all fMRI and DTI findings in

ASD may be restricted, as these studies focus only on

specific brain areas, showing increased versus decreased

activation signals, the meaning of which is not clear when

there is not a parallel range of tasks to probe different brain

system deficits (Minshew and Keller 2010). Moreover, few

studies have combined both fMRI and DTI techniques

(Knaus et al. 2010; Sahyoun et al. 2010; Thakkar et al.

2008), or those techniques with sMRI (Cody et al. 2002;

Corbett et al. 2009; Ke et al. 2009). This would be desir-

able in order to obtain more accurate data on affected loci

and networks of ASD brains, as well as on the main causes

of this abnormal neural connectivity and synchronization.

A new type of integrated research has been developed in

the last few years, by using new imaging techniques and

applications and different techniques applied to the same

subjects, looking for converging results (Boddaert and

Zilbovicius 2002; Ingalhalikar et al. 2010; Lee et al. 2009a;

Schippers et al. 2010). Similarly, recent neuroimaging

research is starting to integrate brain-imaging data into

clinical, etiological, diagnostic, and therapeutic research on

ASD (Belmonte et al. 2008; Bolte et al. 2006; Dichter et al.

2010; Greene et al. 2008; Narayanan et al. 2010; Roy et al.

2009; Thompson et al. 2010). However, this type of

research needs to be further developed.

In summary, this systematic review on functional and

DTI neuroimaging studies in ASD only partially supports

the DSM-5 proposal for a social communication and

behavioral symptom dyad. Supporting the dyad, this review

finds a different neuroanatomical substrate for the social

communication and the behavioral domains. However, the

available neuroimaging data only partially support the

proposed collapse of the social and communication

symptom domains into the same symptom cluster. As we

have mentioned before, DSM-IV mixed syntactic and

pragmatic language impairments in its second set of criteria

(‘qualitative impairments in communication’). Data from

our review support the idea that syntactic language

impairment and pragmatic language impairment should be

considered separately. Therefore, our data are congruent

with the DSM-5 idea of considering syntactic language

impairment as an independent clinical specifier. However,

neuroimaging data also support that semantic-pragmatic

language impairments should be merged with social com-

munication deficits. Therefore, it could be suggested that

an explicit mention of pragmatic language deficits be

included within the social communication criteria (criterion

A of the DSM-5 proposal).

Further neuroimaging studies conducted in patients with

ASD would be of great interest in disentangling the DSM-5

dyad controversy by providing disease-specific biological

markers. If different deficits have different neurobiological

underpinnings, this could have substantial implications for

treatment development (Hyman 2007). For instance, if

patients with different language impairments may benefit

from different therapeutic approaches, that may not be

evident if a heterogeneous group with multiple pathophy-

siologies is lumped together. Thus, this distinction may

lead to more accurate diagnoses classifications and to new

research on more specific and effective treatments for these

patients.

Acknowledgments Supported by Centro de Investigacion Biome-

dica en Red de Salud Mental, CIBERSAM, Instituto de Salud Carlos

III, Spanish Ministry of Science and Innovation. Laura Pina-Camacho

has received a grant from Instituto de Salud Carlos III, Spanish

Ministry of Science and Innovation.

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