Partially enhanced thalamocortical functional connectivity in autism

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a v a i l a b l e a t w w w. s c i e n c e d i r e c t . c o m

w w w. e l s e v i e r. c o m / l o c a t e / b r a i n r e s

Research Report

Partially enhanced thalamocortical functional connectivity in autism Akiko Mizunoa , Michele E. Villalobos a , Molly M. Davies a , Branelle C. Dahl a , Ralph-Axel Müller a,b,⁎ a

Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, CA 92120, USA Department of Cognitive Science, University of California, San Diego, USA

b

A R T I C LE I N FO

AB S T R A C T

Article history:

Based on evidence for thalamic abnormalities in autism, impairments of thalamocortical

Accepted 19 May 2006

pathways have been suspected. We examined the functional connectivity between

Available online 7 July 2006

thalamus and cerebral cortex in terms of blood oxygen level dependent (BOLD) signal cross-correlation in 8 male participants with high-functioning autism and matched normal

Keywords:

controls, using functional MRI during simple visuomotor coordination. Both groups

Autism

exhibited widespread connectivity, consistent with known extensive thalamocortical

Functional connectivity

connectivity. In a direct group comparison, overall more extensive connectivity was

Thalamus

observed in the autism group, especially in the left insula and in right postcentral and

Functional MRI

middle frontal regions. Our findings are inconsistent with the hypothesis of general underconnectivity in autism and instead suggest that subcortico-cortical connectivity may

Abbreviations:

be hyperfunctional, potentially compensating for reduced cortico-cortical connectivity.

BOLD, blood oxygenation level

© 2006 Elsevier B.V. All rights reserved.

dependent fMRI, functional magnetic resonance imaging fcMRI, functional connectivity magnetic resonance imaging

1.

Introduction

Autism is a neurodevelopmental disorder characterized by language delay, socio-communicative deficits, and repetitive behaviors. While varying in severity, pervasive disturbances in development indicate involvement of multiple brain systems. Recently, investigation of the integrity of neuronal pathways in the autistic brain has taken precedence over the search for more localized abnormality.

Because of language delay and abnormal social interaction, autism is usually noticed by parents between the first and second birthdays (De Giacomo and Fombonne, 1998; Rogers and DiLalla, 1990). However, detectable behavioral signs for autism have been documented for earlier periods of life, based on retrospective home video observations (Baranek, 1999; Werner et al., 2000) and parent questionnaires (Werner et al., 2005). In addition to deficiency of joint attention as one of the earliest symptoms (Charman et al., 1997; Osterling and Dawson, 1994), sensory and motor impairments have been

⁎ Corresponding author. Department of Psychology, San Diego State University, 6363 Alvarado Ct., #225 E San Diego, CA 92120-1863, USA. Fax: +1 619 594 8707. E-mail address: [email protected] (R.-A. Müller). 0006-8993/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2006.05.064

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suggested as early detectable symptoms occurring within the first few months of life (i.e., lying, righting, sitting, crawling) before the onset of social impairments (Teitelbaum et al., 1998). This suggests that sensorimotor networks are affected in autism, including thalamocortical pathways. One set of criteria for autism in the DSM-IV-TR (American Psychiatric Association, 2000) is repetitive and stereotyped patterns of behavior. These stereotyped patterns may be present at cognitive (e.g., obsessive routines) and motor levels (e.g., hand flipping, body rocking). Repetitive behaviors can be observed as early as age two (Moore and Goodson, 2003). Behavioral studies have reported that, as time progresses, other types of motor impairments appear, which affect walking, dexterity, reach-to-grasp movement, movement preparation, oromotor and object control skills, and gross motor functions (Mari et al., 2003; Miyahara et al., 1997; Rinehart et al., 2001). Functional MRI (fMRI) studies have further shown atypically diffuse and enhanced activations in autistic cerebellum during simple motor tasks (Allen et al., 2004). Similar atypical activation patterns have also been observed in the cerebral cortex. Müller et al. (2001) found that, during finger tapping, autistic subjects exhibited atypical spatial variability of activation peaks across individuals, often accompanied by scattered activation patterns in frontal and parietal lobes that were not seen in normal control subjects. As described below, such abnormalities may suggest compromised thalamocortical connectivity in autism. Thalamic abnormalities in autism have been observed in a number of recent studies (Friedman et al., 2003; Ito et al., 2005; Ray et al., 2005; Tsatsanis et al., 2003; Waiter et al., 2004). In an early positron emission tomography study, Horwitz et al. (1988) observed reduced correlation of glucose metabolic rates between thalamus and fronto-parietal cortex in autistic men. More recently, a magnetic resonance spectroscopy (MRS) study found reduced neuronal integrity in the autistic thalamus (Friedman et al., 2003), and single-photon emission computed tomography (SPECT) studies revealed reduced thalamic perfusion (Ryu et al., 1999; Starkstein et al., 2000). These functional findings are complemented by a structural MRI study showing reduced thalamic volume relative to total brain volume (Tsatsanis et al., 2003). Traditionally, the thalamus is known as a “sensory gate” receiving afferents from sensory receptors and projecting received sensory information to targeted cortical regions. Connectivity between thalamus and cortex is bidrectional, with feedback connections from cortex to thalamus. In a noninvasive human diffusion tensor imaging (DTI) study, extensive thalamic connections with nearly all cortical regions were demonstrated (Behrens et al., 2003). During development, the thalamus has crucial impact on the functional specialization of neocortex, which is not only predetermined by intrinsic genetic factors but also by extrinsic factors (i.e., sensory input and experience). These extrinsic factors contribute to the functional organization of cortex via thalamic projections, as demonstrated in animal studies (O'Leary and Nakagawa, 2002; Stojic et al., 1998). For example, Schlaggar and O'Leary (1991) transplanted late embryonic visual cortex into the somatosensory cortex in rats. The transplanted visual cortex, which received somatosensory thalamic projections, developed a

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pattern similar to normally developed barrel fields in the host region of the somatosensory cortex. This finding underscores the important role of thalamic afferents in determining the functional differentiation of developing neocortex. Thalamocortical connections also participate in cerebello– thalamo–cortical pathways (Schmahmann, 1996). Cerebellar abnormality has been suspected in autism for a long time. Reduced size of the cerebellum, traditionally considered to be involved in motor functions, was reported in some autism studies (Courchesne et al., 1988; Hashimoto et al., 1995), although there have been many non-replications (Brambilla et al., 2003). Cellular anomalies, in particular reduced numbers of Purkinje cells, are a rather consistent finding in autism (Bailey et al., 1998; Palmen et al., 2004). Impairment of cerebello– thalamo–cortical pathways has been suspected in autism, possibly related to an early reduction of cerebellar Purkinje cells (Bailey et al., 1998). Furthermore, Chugani et al. (1997) found atypical serotonin synthesis along the dentato–thalamo–cortical pathway, using positron emission tomography (PET). A structural MRI study also revealed an atypical inverse volumetric correlation between frontal lobe and cerebellar vermis lobules VI and VII (Carper and Courchesne, 2000), further suggesting pathogenic mechanisms at work along cerebello–thalamo–cortical pathways. Aside from the above findings indicating involvement of the thalamus and its connections, there is also general evidence of white matter abnormality in autism. This evidence includes disrupted schedules of white matter growth across cerebral lobes (Carper et al., 2002), abnormally increased white matter volume in late myelinating frontal white matter (Herbert et al., 2004), and disproportionately reduced size of the corpus callosum compared to cerebral volume (Boger-Megiddo et al., 2006), all of which may indicate atypical neuronal connections in autistic brain. In the present study, we employed functional connectivity MRI (fcMRI) to assess potential disturbances in thalamocortical pathways. Functional connectivity is defined as the “temporal correlation between spatially remote neurophysiological events” (Friston et al., 1993). Biswal et al. (1995) and Xiong et al. (1999) found that low-frequency fluctuations (<0.08 Hz) in the BOLD signal during rest were synchronized between brain areas known to belong to the motor network. These findings have been replicated in a number of studies examining other cortico-cortical and cortico-subcortical networks (Cordes et al., 2001; Hampson et al., 2002; Lowe et al., 1998; Stein et al., 2000). It has been suggested that low-frequency BOLD crosscorrelations may be related to fluctuations of local field potentials (Leopold et al., 2003), although the underlying physiology has not been definitively established (cf. Obrig et al., 2000). Clinical studies in patients with schizophrenia, Alzheimer's disease, depression, and multiple sclerosis have yielded abnormal patterns of functional connectivity (Greicius et al., 2004; Jacobsen et al., 2004; Lawrie et al., 2002; Pezawas et al., 2005; Saini et al., 2004). One study showed absence of normal interhemispheric fcMRI effects in callosal agenesis patients (Quigley et al., 2003), further supporting the sensitivity of fcMRI measures in detecting compromised neuronal connectivity. Based on the evidence suggesting thalamic and thalamocortical abnormalities in autism described above, we

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hypothesized that our autism group would show reduced thalamocortical connectivity compared to the normal control group.

2.

Results

2.1.

Behavioral data

For condition A (index finger only), there was no significant group difference in the number of button presses per block (autism: M = 53.4, SD = 24.1; control: M = 59.1, SD = 3.0; p = 0.53). In condition B (sequences), no significant difference (p = 0.22) was found in response time (RT) between the autism group (M = 574.1 ms, SD = 179.9) and the control group (M = 513.9 ms, SD = 81.0). However, the number of errors per block was significantly higher (p = 0.025) in the autism group (M = 12.2, SD = 8.4) than the control group (M = 3.4, SD = 4.3).

2.2.

Activation analysis

Results of the activation analysis have been previously reported (Müller et al., 2003) and are briefly presented here only for background information. Large activation clusters extended across fronto-parietal regions in both groups, with peaks in premotor, inferior frontal, superior parietal, and temporo-occipital cortices, as well as in thalamus and basal ganglia. Thalamic activation was seen predominantly on the left in the control group, but on the right in the autism group. Only the control group exhibited activation clusters in the left anterior cerebellum.

2.3.

Functional connectivity analysis

2.3.1.

Control group

Clusters of functional connectivity found in the control group are shown in Table 1 and Fig. 1A. Connectivity with the bilateral thalamus was extensive in bilateral pericentral cortices and a number of bilateral frontal regions, such as the cingulate and the superior, inferior, middle, and medial frontal gyri. Bilateral effects were also observed in the parietal lobe and the basal ganglia. Further fcMRI clusters were observed in left occipital and right temporal cortex, as well as the cerebellar vermis. In a separate unilateral analysis for the left thalamus, we observed large clusters in fronto-parietal cortices and the basal ganglia bilaterally (Fig. 1F). Results for this analysis mostly resembled those for the bilateral thalamus, although pericentral fcMRI clusters were less extensive in the analysis for the left thalamic seed. On the other hand, additional clusters not seen for the bilateral seed were identified in left parahippocampal, right occipital, and left anterior cerebellar regions. Analysis for the right thalamus resulted in large clusters mainly in right frontal and right parietal regions (Fig. 1H). No occipital clusters were observed in this analysis.

2.3.2.

Autism group

Functional connectivity clusters for the autism group are shown in Table 2. In the analysis for the bilateral thalamic seed volume (Fig. 1B), fcMRI clusters were found in frontal and

pericentral regions bilaterally, including a large cluster in the left insula. Further clusters were observed in the parietal lobes and basal ganglia bilaterally. No effects were seen in temporal and occipital lobes. For the left thalamus (Fig. 1G), we observed a similar pattern of fcMRI effects, although clusters were less extensive. In particular, no effects were seen in the right parietal lobe and the left basal ganglia. In the analysis for the right thalamus (Fig. 1I), significant fcMRI effects occurred only in bilateral frontal regions with a small right parietal cluster.

2.3.3.

Group comparison

Direct group comparisons yielded a number of clusters with significantly greater functional connectivity for the autism group compared to the control group (Table 3 and Fig. 1C). For the bilateral thalamus, these effects were found in frontal and pericentral regions bilaterally, as well as the left inferior parietal lobe. Both analyses for unilateral seed volumes showed very similar patterns of fcMRI effects. Only a few clusters showed inverse effects of greater functional connectivity in the control group compared to the autism group (Table 3). These were seen in lateral and medial temporal lobes in all three unilateral and bilateral analyses (Fig. 1C). For the right thalamus, we also observed bilateral frontal, left pericentral, and right parietal clusters showing this effect.

2.3.4.

Subsample analyses

In order to assess potential laterality effects, we conducted additional analyses for subsamples of only right-handed subjects in both control and autism groups (n = 5 each). In both groups, similar patterns of functional connectivity were seen for right-handed subsamples and full samples (Figs. 1L–P; see Discussion). Furthermore, in order to rule out potential maturational confounds related to the inclusion of one adolescent subject in the autism group, we performed a within-group analysis that only included the seven remaining adult autistic subjects. Results for this analysis were almost identical to those for the full autism sample (small renderings inserted in Fig. 1B), suggesting that no such confound occurred.

3.

Discussion

Clusters of functional connectivity with bilateral thalami, measured in terms of BOLD signal cross-correlation, extended to all four forebrain lobes in the control group. These findings are consistent with known extensive thalamocortical connectivity (Nieuwenhuys et al., 1988), as confirmed in vivo in a recent diffusion tensor imaging (DTI) study (Behrens et al., 2003). In the autism group, clusters of functional connectivity with bilateral thalami were also distributed across several cerebral cortical regions, but no effects were found in the temporal and occipital lobes. Thalamocortical pathways are functionally segregated and mostly reciprocal, with distinct thalamic nuclei connecting to specific cortical regions. Thalamic nuclei can be classified as relay (specific) or diffuse (non-specific) (Sherman and Guillery, 2001). Among the relay, nuclei are the lateral geniculate

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nucleus (LGN) for visual information connecting with primary visual cortex, the ventral posterior lateral nucleus for somatosensory information connecting with the postcentral area, and the medial geniculate nucleus for auditory information connecting with the temporal lobe. Non-specific nuclei are involved in cortical arousal and the integration of sensory submodalities (Amaral, 2000), connecting with widespread regions of cerebral cortex (Berendse and Groenewegen, 1991), cerebellum, and subcortex, in particular, the striatum (Sherman and Guillery, 2001). Based on previous evidence of abnormalities of the thalamus and thalamocortical pathways in autism (Chugani et al., 1997; Friedman et al., 2003; Müller et al., 1998; Tsatsanis et al., 2003), we expected atypical thalamic functional connectivity in autism. Since thalamocortical pathways provide critical inputs for the normal development of neocortex (O'Leary and Nakagawa, 2002; Schlaggar and O'Leary, 1991; Stojic et al., 1998), we hypothesized that disorganized functional maps in autistic cortex, as previously observed (Müller et al., 2001, 2003), could be caused by disruptions of the thalamocortical pathways and that this disruption would be reflected in reduced thalamocortical functional connectivity. Inspection of within-group fcMRI effects appeared partially consistent with this hypothesis as temporal and occipital connectivity present in the control group was not seen in the autism group. However, on direct statistical group comparison, the autism group showed an overall greater volume of fcMRI effects between thalamus and cerebral cortex than the control group, suggesting more spatially extensive thalamocortical functional connectivity in autism. These effects were most pronounced in the left insula and frontal operculum, the right middle frontal and postcentral gyri, and the left inferior parietal region (Fig. 1C). Among the areas showing greater fcMRI effects in the autism than in the control group, the largest cluster was located in the left anterior insula and frontal operculum. The insula connects with several ventral thalamic nuclei, such as the ventral anterior nucleus (VA), the ventral posterior medial nucleus (VPMpc), the ventral posterior inferior nucleus (VPI), and the ventral posterior lateral nucleus (VPL) (Flynn et al., 1999). As the ventral nuclei are the part of cerebello–thalamo– cortical pathways (Fanardzhyan et al., 2002) that mainly convey motor signals, these nuclei are considered motor thalamus (Krack et al., 2002). However, activation in the anterior insula bilaterally has also been observed for social and emotional stimuli in fMRI (Critchley et al., 2004; Singer et al., 2004), and reduced activation in this region – albeit in the right hemisphere – was seen in an autism fMRI study on socioaffective judgment by Baron-Cohen et al. (1999). Although conditions applied in the present study did not relate to the socio-affective domain, abnormal recruitment of the thalamo– insular circuit in the autism group might relate to cognitive arousal, as further discussed below. As expected, multiple clusters of fcMRI effects in pericentral regions (BA 1–6) were found for both groups. Direct group comparison, however, showed greater fcMRI effects for the autism group in several pericentral clusters bilaterally. In a previous fMRI study of autism, atypically strong activation in right pericentral and premotor regions were observed during advanced stages of visuomotor learning, suggesting atypical

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reliance on stimulus-driven strategies (Müller et al., 2004). Although activation effects were regressed out in the present study, these previous results may relate to atypically enhanced functional connectivity between thalamus and pericentral regions. Whereas overall our autism group showed greater thalamocortical functional connectivity on direct group comparisons, we also identified a few clusters showing inverse effects, i.e., greater functional connectivity in the control group compared to the autism group. These were mainly in the temporal lobes, i.e., in right anterior superior temporal sulcus (BA 38) and bilateral parahippocampal cortices (BA 28 and 34). Lateral and medial temporal lobes have reciprocal connections with the thalamic pulvinar nuclei (Nieuwenhuys et al., 1988), which are thought to be involved in attention (Posner and Petersen, 1990) by virtue of their ability to facilitate functional synchronization of distributed cortical networks (Shipp, 2003). Temporal lobe abnormality has been suspected in autism, both with regard to lateral and medial cortices. There is no consensus regarding volumetric abnormalities in temporal lobes (Bigler et al., 2003), but in view of a number of atypical functional findings, Bigler et al. (2003) suggest that temporal lobe abnormality in autism may reflect functional rather than anatomical abnormality. Such functional abnormalities in lateral temporal lobes have been reported in imaging studies of autism, showing hypoperfusion in bilateral superior temporal gyrus (Zilbovicius et al., 2000) and reduced activation in response to human voices in the superior temporal sulcus (Gervais et al., 2004). Our finding of reduced fcMRI effects occurred in the anterior portion of the right superior temporal sulcus. The superior temporal sulcus (STS) is recognized as an integrating point of the ventral “what” and dorsal “where” streams of visual processing. More specifically, STS is known for its involvement in biological motion (Puce and Perrett, 2003; Vaina and Gross, 2004), a domain reported to be abnormal in autism (Blake et al., 2003). Parahippocampal cortex is a part of limbic association cortex located in the medial temporal lobe. It receives cortical inputs from the higher order sensory areas and sends efferents to the hippocampal formation and amygdala (Adolphs, 2003; Eichenbaum, 2004). These circuits are mainly involved in memory and socio-affective functions. Evidence from animal models of autism suggests significant involvement of the medial temporal lobe in the socio-affective domain (Bachevalier, 1994). Considering that the results of two within-group analyses indicated an overall greater volume of fcMRI effects in the control group compared to the autism group, the result of the direct group comparison was unexpected. We therefore inspected fcMRI effects within each group at lower thresholds (p = 0.001, uncorrected; compared to original height thresholds at p = 0.000005). Clusters obtained from statistical group comparisons showing greater fcMRI effects in the autism group were found to be embedded in regions of low-threshold within-group effects for this group (as, for example, in the left insula; see Fig. 1J). A similar pattern was observed for the control group in some temporo-occipital regions (Fig. 1K). Partially increased thalamocortical signal cross-correlation observed in our autism group may relate to greater general

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Table 1 – Functional connectivity clusters (p < 0.01; corrected)

Anatomical location

Frontal Left

Right

Paracentral Left Right

Bilateral thalamus Volume Max (μl) Int (t)

L cingulate (24) L middle frontal (6) L superior frontal (10) L inferior frontal (9) L medial frontal (6)

R superior/medial frontal (9) R superior frontal (6) R cingulate (32) R medial frontal (8) R medial frontal (9/10) R inferior frontal (46)

L paracentral (31) L precentral (4) R precentral (6) R postcentral (2) R precentral (4) R postcentral (3) R precentral (4/6)

Left thalamus Stereotactic coodinates x

y

z

1088 672 312 232 184

32.7 24.7 32.4 32.7 17.2

−3 −41 −21 −41 −13

3 5 47 9 11

44 46 16 26 48

688 432 320 168 128 104

29.6 23.9 19.8 16.7 20.8 19.3

21 1 1 9 19 39

33 1 19 33 39 31

30 64 36 36 24 14

1088 288 1432 1192 880 160 96

32.7 21.7 30.0 30.9 22.0 19.1 17.4

−5 −35 35 41 27 11 47

−27 −19 −7 −29 −21 −37 −15

Right thalamus

Volume Max (μl) Int (t)

L superior frontal (6) L medial frontal (6) L cingulate (24) L middle frontal (6/8) L superior frontal (10) L middle frontal (6) L inferior frontal (9) R middle frontal (6) R medial frontal (8) R superior frontal (6) R inferior frontal (45) R medial frontal (9) R cingulate (31)

44 L precentral (4) 54 36 R precentral (4) 36 56 66 42

Stereotactic coodinates x

y

z

13 −5 3 7 47 5 9 1 33 1 27 39 31

48 50 42 48 20 48 24 50 36 64 22 24 14

456 336 208 152 136 136 104 1752 776 184 168 112 112

20.9 20.6 20.2 22.3 16.0 15.6 20.9 32.7 28.9 27.1 15.3 20.7 17.6

−11 −5 −3 −31 −23 −41 −43 35 9 3 27 19 19

144

21.0

−35 −19

888

32.7

27 −19

Volume Max (μl) Int (t)

L middle frontal (6)

R inferior frontal (40) R cingulate (24/32) R cingulate (32) R middle frontal (9) R middle frontal (6) R middle frontal (8) R middle frontal (6)

54 L postcentral (3/4) L paracentral (5) 54 R paracentral (31)

Stereotactic coodinates x

y

z

−39

9

44

152

24.4

2128 1800 360 336 152 120 104

25.9 32.1 27.1 30.9 27.3 16.5 18.0

29 −37 1 3 1 17 27 32 41 3 23 17 23 −1

38 44 38 22 44 42 50

528 160 584

19.1 21.7 27.4

−35 −21 −5 −41 1 −25

46 52 44

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Control group

Parietal Left

Right

Temporal Left Right

464 96

20.2 14.9

−35 −53 −7 −43

50 L cingulate (31) 40 L precuneus (7) L precuneus (31) L inferior parietal (40) L superior parietal (7) L cingulate (31) 16 R precuneus (7) 34 R inferior parietal (40) R precuneus (7) R precuneus (7)

856 752 352 296 160 128 184 144 128 104

24.1 32.0 19.7 21.5 20.0 15.4 17.6 21.2 19.7 16.9

−7 −25 −7 −35 −23 −17 23 33 25 11

R cingulate (31) R precuneus (7)

360 240

20.5 18.6

1 −63 27 −61

R superior temporal (42) R middle temporal (21)

288 128

19.5 20.8

45 −31 37 −23

L precuneus (18) L lingual (19) L cuneus (18)

608 168 104

22.3 20.6 16.4

−23 −63 −9 −59 −21 −79

L parahipoccanpal (28) 16 R superior temporal (42) −4

296 400

25.6 32.7

−21 −11 −20 L superior temporal (21) 45 −31 16 R superior temporal (21)

28 L cuneus (18) −2 L lingual (19) 18 R lingual (19) R lingual (18)

256 144

28.4 17.9

−21 −77 −9 −53

20 0

128 104

23.5 23.3

21 −49 23 −73

−2 2

4 L putamen/lentiform 14 R caudate R putamen/lentiform R subtiantial nigra

1840 720 112 104

32.7 21.5 15.2 17.1

−27 1 15 9 23 3 7 −15

−3 −47 −14 Vermis L anterior cerebellum

208 488

15.7 28.7

1 −37 −12 Vermis −13 −31 −12 L anterior cerebellum R anterior cerebellum

Right Subcortical Left Right

L putamen/lentiform R caudate

856 744

30.6 31.2

Vermis

960

24.0

−23 17

1 9

−23 −63 −67 −55 −49 51 −51 −33 −61 −51

42 32 18 42 60 28 48 38 34 48

L inferior parietal (40) L precuneus (7)

216 160

21.5 24.2

−39 −37 −19 −51

50 40

R precuneus (7) R precuneus (31) R precuneus (7)

656 136 104

26.2 15.7 14.6

9 −53 15 −53 25 −59

44 30 38

104 128

23.6 20.6

−49 −27 35 −27

0 −2

120 120 104

17.6 16.4 25.0

1 −47 −12 −13 −53 −10 9 −39 −18

2 L putamen/globus pallidus 14 −2 −6

Cerebellar Left Right

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Occipital Left

L inferior parietal (40) L cingulate (31)

165

166

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cognitive arousal. Autism has been classified by some researchers as a disorder of arousal-modulating systems, which might be associated with atypically increased functional connectivity (Belmonte et al., 2004). Sherman and Guillery (2001) describe the thalamic “gate” function as transforming burst sensory information to tonic mode. Chronic arousal in autism could be related to a failure of these gating functions in thalamocortical pathways, i.e., either excessive burst information or decreased tonic information (cf. Levitt et al., 2004). Other potential causes that have been suggested for this chronic arousal are a deficiency of lateral inhibition by gamma-aminobutyric acid (GABA)-ergic interneurons (Casanova et al., 2003; Rubenstein and Merzenich, 2003), abnormality of minicolumnar organization (Casanova et al., 2002), and abnormal patterns of serotonin synthesis (Chandana et al., 2005; Chugani et al., 1997). However, the finding by Villalobos et al. (2005) of largely reduced functional connectivity with primary visual cortex during the identical visuomotor condition as in the present study, as well as other reports of underconnnectivity (Just et al., 2004), speaks against diffuse and globally enhanced functional connectivity in autism, although they do not rule out the possibility of region-specific enhancement due to arousal and deficient inhibition. Limited sample size and heterogeneity within our autism group need to be considered. In particular, the very large standard deviation observed in the autism group for performance in condition A (mean number of button presses per block) may have reflected variability in arousal or general cognitive state, which could have affected our fcMRI findings. Fig. 1E indicates subjects performing outside the range observed in control subjects on this measure (red arrows: lower number, green arrows: higher number of presses). Qualitative inspection yields no obvious relation between diffuse or regionally atypical fcMRI effects and performance variability. While autistic individuals overall tended to show more diffuse fcMRI effects, there was also substantial individual variability, even across control subjects. Comparisons of

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single-subject analyses must be taken with great caution as it is known that many technical and noise factors (e.g., slight differences in head motion) may contribute to observed differences in the magnitude and spatial extent of effects at a given threshold. However, since there were no group differences in head motion (as previously reported in Müller et al., 2003), it is unlikely that the results of our group analyses were related to head movement. The thalamus is part of the cerebello–thalamo–cortical pathway, and early reduction of Purkinje cells in autism may be related to defects of this pathway (Bailey et al., 1998). Atypically increased thalamocortical connectivity in autism, as observed in the present study, could result from disinhibition of deep nuclei in the cerebellum caused by the loss of Purkinje cells. Carper and Courchesne (2000) reported significantly reduced volumes of the cerebellar vermis and an inverse correlation with frontal volume in autism, which could be indicative of structural maldevelopment of cerebello– thalamo–cortical pathways, consistent with activation results (Müller et al., 1998) including those previously reported for the present data set (Müller et al., 2003). Possibly related to this finding, Chugani et al. (1997) observed reduction of serotonin synthesis capacity in the left thalamus and frontal cortex with concurrent increase in the contralateral dentate nucleus of the cerebellum in autism, using positron emission tomography. Only very few studies to date have investigated functional connectivity in autism (Castelli et al., 2002; Just et al., 2004; Koshino et al., 2005; Villalobos et al., 2005). These studies focused on cortico-cortical connectivity and predominantly suggested atypically reduced functional connectivity in autism samples. This appears consistent with a view of autism as a disorder of complex information processing, as derived from neuropsychological data (Minshew et al., 1997). Based on the finding of overall reduced functional connectivity during semantic comprehension, Just et al. (2004) put forth a hypothesis of general underconnectivity in autism. Largely in support of general underconnectivity, Koshino et al. (2005) also observed reduced synchronization of time courses

Fig. 1 – Bilateral thalamic seed volume. Functional connectivity maps for bilateral thalamic seed volumes in control (A) and autism groups (B). For the autism group, smaller brain renderings are inserted in (B) for seven adult subjects only (excluding one 15-year-old), showing virtually identical effects (at the same t threshold) as for the complete sample. Direct group comparison (C) shows mostly greater connectivity in the autism group (orange clusters), especially in the bilateral frontal and pericentral regions. Inverse effects (Control > Autism; blue clusters) are seen in lateral and medial temporal lobes. fcMRI effects in each individual subject are shown for the control (D) and autism groups (E), generally thresholded at p < 1e−7 (uncorr.). For better visualization and comparison of individual regional effects, thresholds have been adjusted up (p < 1e−10) in control subject 4 and autism subjects 1 and 6, and down (p < 1e−4) in autism subject 2. Arrows at the top left of these images indicate autistic subjects performing outside the range of the mean number of button presses per block observed in individual control subjects for condition A (index finger presses only; control range: 52–62). Red arrows indicate number below the range, green arrows above the range. Autistic subject number 2 was the only subject, also performing outside the range seen in control subjects with regard to errors in condition B (sequences), indicated by the two red arrows. Comparison with analyses for unilateral seeds. Comparison between analyses for bilateral and unilateral thalamic seed volumes (F–I) shows mostly overlapping effects (green clusters) in control and autism groups. Comparison with low-threshold effects (J–K). Effects of direct group comparison (p < 0.05, corr.) compared to within-group effects at relaxed thresholds (p < 0.001, uncorr.). A cluster of significantly greater fcMRI effects in the left insula for the autism group overlaps with and is embedded in a larger cluster of low-threshold effects for autism on the within-group analysis (J). An analogous pattern is seen for mediotemporal effects (Control > Autism), which are embedded in a large cluster of low-threshold effects for controls on within-group analysis (K). Comparison with right-handed subsamples. Comparison between analyses for full samples (n = 8) and right-handed subsamples (n = 5) in control (L–N) and autism groups (O–P), showing largely consistent effects.

168

Table 2 – Functional connectivity clusters (p < 0.01; corrected) Autism group Bilateral thalamus Anatomical location

Max Int (t)

Stereotactic coodinates x

y

z

Volume (μl)

Max Int (t)

Right thalamus Stereotactic coodinates x

y

z

insula/claustrum cingulate (24) medial frontal (8) middle frontal (6)

760 200 160 112

29.4 18.4 16.4 16.4

−35 −19 −11 −27

−7 −13 3 −1

12 42 50 50

L insula/claustrum

376

20.7

−31

−7

12

medial frontal (32/6) medial frontal (9) inferior frontal (44) medial frontal (32)

512 112 104

24.0 17.8 25.5

3 5 47

9 35 5

46 30 26

R inferior frontal (44)

128

20.2

49

5

28

Pericentral Left L postcentral (3/1) L precentral (6) Right R precentral (6) R precentral (4) R postcentral (1/2) R precentral (6) R precentral (4) R paracentral (31)

368 192 576 160 128 120 120 112

21.9 17.7 18.6 15.7 17.3 16.6 16.8 15.6

−45 −57 25 35 29 43 25 3

−21 −5 −13 −19 −21 −11 −27 −21

52 6 58 46 32 34 52 44

L paracentral (31)

272

15.9

−1

−21

44

R postcentral (4) R precentral (6) R paracentral (31) R paracentral (31)

144 120 120 112

17.6 15.5 19.1 21.7

25 31 3 7

−27 −13 −9 31

54 44 44 28

Parietal Left L inferior parietal (40) Right R inferior parietal (40)

136 160

20.8 23.6

−51 41

−33 −43

30 36

L inferior parietal (40)

176

17.1

−43

−53

34

R precuneus (7) R superior parietal (7)

152 152

22.3 18.1

13 25

−51 −41

40 56

280 216

27.7 21.7

−1 13

11 −3

6 12

Right

R R R R

Subcortical Left L caudate Right R globus pallidus/putamen

Volume (μl)

L cingulate (31) L medial frontal (32) L insula/claustrum L superior frontal (6) L insula (41) R superior frontal (6)

R superior parietal (40)

R caudate

360

R lentiform/putamen

208

32.7 18.2

3 19

9 1

6 10

Max Int (t)

Stereotactic coodinates x

y

z

448 288 216 184 128 680

24.1 23.0 24.9 22.6 23.8 27.5

−15 19 −33 −13 −39 1

−25 21 5 −13 −31 5

34 34 8 64 12 52

96

17.0

25

−41

56

BR A I N R ES E A RC H 1 1 0 4 ( 2 00 6 ) 1 6 0 –17 4

Frontal Left L L L L

Volume (μl)

Left thalamus

Table 3 – Functional connectivity clusters (p < 0.01; corrected) Autism > Normal Anatomical location

Frontal Left

Right

Right

Parietal Left

Left thalamus

Volume Max Stereotactic (μl) Int coodinates (t) x y z L insula/frontal operculum L medial frontal/cingulate (6/24) L middle frontal (46/10)

2768 368 48

5.7 4.8 3.5

−37 −13 −31

7 5 17

R middle frontal (44/10) R inferior frontal (44)

1144 168

5.3 4.8

39 39

11 13

L postcentral (2) L precentral (6) L postcentral (2) R postcentral (1/2) R precentral (6)

88 72 56 644 392

4.5 4.1 3.6 7.2 5.6

−55 −9 −45 45 47

−27 −23 −19 −15 7

L inferior parietal (40) L inferior parietal (40/39)

496 160

5.0 3.9

−51 −51 −43 −37

Right thalamus

Volume Max Stereotactic (μl) Int coodinates (t) x y z

4 L insula/frontal operculum 48 L middle frontal (46/10) 20 L middle frontal (24) L medial frontal (6) L middle frontal (8) 10 R middle frontal (46/10) 12 R inferior frontal (45) R inferior parietal (44) R inferior frontal (9/6) R insula

672 608 152 72 48 344 272 136 88 48

4.8 6.0 3.8 4.1 3.9 4.5 4.1 4.4 4.1 4.4

−37 7 −31 45 −13 −5 −9 −23 −37 23 19 47 33 37 41 17 47 1 31 13

4 24 48 58 42 22 10 8 24 18

48 L precentral (6) 58 32 24 R precentral (6) 10 R postcentral (1/2)

176

5.5

−57

−5

464 392

5.2 5.4

47 7 47 −15

46 L inferior parietal (40) 40 L cuneus (7)

280 88

4.9 4.1

72

3.6

Temporal Left

L superior temporal (38)

Normal > Autism Frontal Left Right Pericentral Left

L paracentral (6)

64

4.0

−1

−27

48

Parietal Right

L parahippocampal (34) R superior temporal (38/21) R parahippocampal (28)

56 504 80

3.9 5.2 3.9

−9 −5 −12 L parahippocampal (34) 39 1 −18 R superior temporal (38) 17 −15 −12 R parahippocampal (28)

48 416 48

4.5 5.5 3.7

insula/frontal operculum insula/precentral medial frontal (6) middle frontal (6/8)

1384 120 120 56

5.1 4.0 4.1 3.8

R inferior/middle frontal (46) R insula R inferior frontal (45/44)

672 168 104

6.4 4.2 4.2

10 L postcentral (3/1)

88

8 R precentral (6/4) 24 R postcentral (43)

−51 −51 −17 −77

46 L inferior parietal (40) 14

−45

−8

1

L L L L

Stereotactic coodinates x

y

−35 5 −41 −11 −13 −7 −33 −11

8 10 48 44

37 1 17

16 16 12

4.5

−55 −27

48

160 104

4.4 4.2

47 −1 53 −11

22 22

192

4.1

−55 −55

48

L superior frontal (10) R superior frontal (6)

72 128

3.9 3.9

−11 1

63 7

18 64

L paracentral (5)

248

5.2

−1 −27

48

R precuneus (31)

56

4.2

11 −53

36

56 288 120

5.5 4.5 3.8

−9 −7 −14 L medial/middle temporal (21) 45 3 −18 R superior temporal (38) 17 −15 −12 R parahippocampal (35)

43 37 39

z

−43 −1 −22 39 1 −18 17 −17 −14

169

Temporal Left Right

Volume Max (μl) Int (t)

BR A I N R ES E A RC H 1 1 0 4 ( 2 00 6 ) 1 6 0 –1 74

Pericentral Left

Bilateral thalamus

170

BR A I N R ES E A RC H 1 1 0 4 ( 2 00 6 ) 1 6 0 –17 4

between paired cortical regions of interest in autism during working memory. The fcMRI studies of autism by Just and coworkers (Just et al., 2004; Koshino et al., 2005) assessed task-specific functional connectivity. In our study, subjects had to perform a task throughout, but orthogonal regressors corresponding to the task cycle were applied to remove effects of activation. Apparently inconsistent findings could therefore be related to the impact of activation effects in fcMRI analyses. However, Villalobos et al. (2005) also found mostly reduced functional connectivity in autism between primary visual cortex (Brodmann area 17) and other cortical regions, largely consistent with the underconnectivity hypothesis (Just et al., 2004), but using methods almost identical to those employed in the present study (i.e., regressing out effects associated with task cycles). This suggests that our finding of partial overconnectivity is related to the choice of a subcortical region of interest. The present fcMRI study is the first to examine functional connectivity between subcortex and cerebral cortex in autism. Our findings are incongruent with a general underconnectivity theory, as proposed by Just et al. (2004). Based on the currently limited evidence, they may indicate predominantly reduced cortico-cortical functional connectivity in autism, but partially enhanced subcortico-cortical functional connectivity. From a developmental perspective, the differences may relate to disrupted white matter growth schedules in autism (Courchesne et al., 2001) and the relatively early maturation of thalamocortical axons, compared to late maturation of longdistance cortico-cortical connections (see review in Sur and Leamey, 2001). Because of their reciprocal connections, thalamus and cerebral cortex have mutual effects upon each other during development. Increased thalamocortical functional connectivity may be associated with excessive synaptic generation and reduced pruning, which have been suggested as underlying causes of brain enlargement in autism (Eigsti and Shapiro, 2003; McCaffery and Deutsch, 2005). Since our functional connectivity procedure measured lowfrequency BOLD correlation, there is no assumption that fcMRI effects would solely reflect monosynaptic connections. Furthermore, fcMRI maps are not sensitive to the direction of the communication between spatially distinct regions. In primates, more than half of the connections between thalamus and cortex are cortico-thalamic feedback connections (Sherman and Guillery, 2001). Looped cortico–thalamo–cortical pathways may serve as indirect cortico-cortical connections (Sherman and Guillery, 2001). One possibility to be examined in further studies would be that partially enhanced connectivity may reflect increased function of these indirect connections, potentially compensating for reduced or inefficient direct long-distance cortico-cortical connectivity. Atypical or inconsistent hand preference is relatively common in autism (Escalante-Mead et al., 2003). The present study included three non-right-handed autism subjects. Although autism and control groups were matched for handedness and although a previous activation study (Müller et al., 2003) showed no robust differences related to handedness, we nonetheless focused on bilateral thalamic analyses in the present study in an attempt to reduce effects related to laterality. However, we performed additional analyses for

right-handed subsamples. The results for these were largely concordant with results for complete samples (Figs. 1L–P). Since each unilateral thalamus mostly receives sensory information from the contralateral side of the body and projects to the ipsilateral side of cortex, we further performed analyses for unilateral thalamic seed volumes (Figs. 1F–I). In the control group, fcMRI effects for the left thalamic seed had a very similar pattern compared to those for the bilateral seed, whereas those for the right thalamic seed were predominantly found in ipsilateral fronto-parietal regions. This may relate to the finding of left-sided thalamic activation, presumably associated with more distributed functional connectivity during visuomotor coordination (Müller et al., 2003). As mentioned above, there was no expectation of exclusively ipsilateral fcMRI effects between thalamus and cerebral cortex, as low-frequency cross-correlations do not uniquely reflect monosynaptic connectivity. Nonetheless, fcMRI effects in cortex ipsilateral to the thalamic seed were predominant in the control group. This was not the case in the autism group, where frontal effects were bilateral for both seeds. Remarkably, no pericentral effects were found for the right thalamic seed. The technique of fcMRI applied here cannot capture all aspects of neural connectivity but rather focuses on functional correlations at low temporal frequencies. Other approaches, such as diffusion tensor imaging, examine the structural integrity of white matter. Barnea-Goraly et al. (2004) applied this latter technique in children and adolescents with highfunctioning autism and found reduced white matter integrity (fractional anisotropy) in medial frontal, temporoparietal, superior temporal, and callosal regions. No findings specifically relating to thalamocortical fiber tracts were reported in this study. In conclusion, this is the first fcMRI study to examine subcortico-cortical functional connectivity in autism. Contrary to our hypothesis, we found partially increased thalamocortical functional connectivity in our autism group compared to matched control subjects. This effect may reflect atypically diffuse subcortico-cortical connections in the autistic brain, particularly in motor and somatosensory systems. However, due to limitations in spatial resolution, our findings cannot fully capture the complex and specific connectivity between individual thalamic nuclei and cerebral cortical regions, which may be addressed in future studies.

4.

Experimental procedures

4.1.

Participants

Subjects were eight high-functioning autistic men (mean age: 28.4 years; range: 15–39) and eight male normal control subjects (mean age: 28.1 years; range: 21–43). Autism participants met criteria for autistic disorder defined by the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 2000), the Childhood Autism Rating Scale (Schopler et al., 1980), and the Autism Diagnostic Interview-Revised (Lord et al., 1994). All autistic subjects fulfilled diagnostic criteria on the above three measures except one subject, whose score on the CARS was lower than

BR A I N R ES E A RC H 1 1 0 4 ( 2 00 6 ) 1 6 0 –1 74

cutoff, but who fulfilled diagnostic criteria on the other measures. Subjects' intelligence quotients (IQs) were evaluated using the Wechsler Adult Intelligence Scale-Revised (Wechsler, 1981) or the Wechsler Intelligence Scale for Children-Revised (Wechsler, 1974). All participants were non-retarded (full-scale IQ >70). Mean nonverbal IQ for the autism group was in the normal range (92.3; range: 80–112). None of the autism subjects had any history of additional medical and neurologic disease, such as seizures or fragile X syndrome, or used any psychotropic medication. The normal control group consisted of healthy subjects without history of any developmental, psychiatric, and neurologic disorders. Groups were matched for mean age, sex, and handedness. One ambidextrous subject in the autism group was matched with a left-handed normal control subject. The Institutional Review Boards of Children's Hospital and the University of California, San Diego, approved this study. Informed consents were obtained from all subjects. For a 15year-old autistic subject, additional written informed assent was obtained from a parent.

4.2.

field, which are associated with image distortion, we applied an unwarping algorithm (Reber, 1998), using field maps acquired for each session. In each EPI dataset, the first three time points were eliminated to remove initial MRI signal instability. For each subject, data were motion-corrected, temporally smoothed (filtered voxel intensity at time point b = 0.15 * a + 0.7 * b + 0.15 * c), spatially normalized to Talairach space (Talairach and Tournoux, 1988), and smoothed with a Gaussian kernel of 6 mm3 (full-width half-maximum). Lowpass-filtering at 0.1 Hz was performed given that interregional cross-correlations reflecting functional connectivity are strongest in the low-frequency domain (Cordes et al., 2001; Salvador et al., 2005), as well as in an effort to reduce physiological confounds (respiration, heart beat) and other high frequency noise components. It should be noted that, given our sampling rate (TR = 2.5 s), analyses were not fully protected by the use of motion regressors (see below) against aliasing effects of cardiac rhythms (Lowe et al., 1998). However, our study used a sampling rate comparable to previous fcMRI studies in clinical populations (Quigley et al., 2003), including autism (Just et al., 2004; Welchew et al., 2005).

Experimental conditions 4.4.2.

Visual stimuli were back-projected onto a screen at a distance of about 12 ft from participants' heads. Stimuli consisted of the diagram of a hand and a blue dot that appeared every 550 ms on one of the four fingers, excluding the thumb. Participants performed a visuomotor task throughout the experiment, being instructed to press a button on a 4-button device with the corresponding finger of their preferred hand as soon as the stimulus was detected. Each block was initiated by the visual instruction “Press” with two conditions alternating every 40 s (ABABAB). In condition A, the blue dot appeared only on the index finger, and participants pressed the corresponding button with their index finger. In condition B, the stimulus was a pseudo-random 6-digit sequence (e.g., 1–3–2–4–1–2) repeated 10 times per block. Novel sequences were presented in each block.

4.3.

171

Magnetic resonance imaging

MR images were obtained using a GE Signa 1.5-T magnet with a custom-made head gradient coil. After manual shimming, T2*-weighted echo-planar images (EPIs) were acquired with a single-shot gradient-recalled pulse sequence (interleaved slice acquisition: repetition time [TR] 2.5 s; echo time [TE] 40 ms; flip angle 90°; 19 sagittal 7 mm slabs (1 mm gap); in-plane resolution 3.75 mm2). A time series of 98 EPIs was acquired. High-resolution structural images were acquired by a 3D Magnetization Prepared Rapid Gradient Echo (MPRAGE) pulse sequence (TR 30 ms, TE 5 ms, flip angle 90°, FOV 24 cm, slice thickness 1.2 mm; in-plane resolution 1 mm2) for each subject during the same session.

4.4.

Data analysis

4.4.1.

Preprocessing

All preprocessing and analysis steps were performed using the software suite Analysis of Functional NeuroImages (AFNI; Cox, 1996). To reduce effects of inhomogeneities in the magnetic

Activation analysis

Activation was assessed in terms of hemodynamic changes associated with condition B compared to condition A. In each subject, voxel time series were regressed against a hemodynamic model, which was a smoothed boxcar, shifted by 2 TRs (5 s). Main effects of task within each group were examined by means of general linear tests. Z maps were thresholded at p < 0.05, with a correction for multiple comparisons based on the number of image resolution elements (for details, see Müller et al., 2003).

4.4.3.

Functional connectivity

Functional connectivity was measured as BOLD signal correlation with each thalamus. Following spatial normalization of high-resolution anatomical MPRAGE images into Talairach space, the thalami were traced on each subject's individual anatomical volume, separately in the left and right hemispheres, based on gray–white contrast, which is easily detectable on T1-weighted MRIs, and comparison with the atlas by Talairach and Tournoux (1988). These tracings were used to generate seed volumes for unilateral and bilateral thalami in each subject. The primary fcMRI analyses were performed for the bilateral thalamus, but analyses for unilateral thalami were additionally carried out for comparison of potentially lateralizing effects (see Discussion). A mean BOLD time series of all voxels was computed for bilateral and unilateral thalami in each subject after removing linear trends. In order to remove effects of task-control cycles as well as eye and head movement, we used eight orthogonal regressors: a smoothed boxcar model of task-control cycles, an eye movement time series computed from mean time series in the orbits for each individual subject (Tregellas et al., 2002), and six head movement time series (three rotations and three axes). Both within-group (one-sample) and between-group (two-sample) voxel-by-voxel t tests were performed for bilateral and unilateral thalami, entering fit coefficients from single-subject analyses. All statistical maps were corrected for multiple comparison, using Monte-Carlo-type alpha

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simulations (Forman et al., 1995). Height thresholds for within-group analyses were t = 12.44, p < 0.000005, with an extent threshold of 16 μl for a corrected cluster significance threshold of p < 0.01. For between-group analysis, which showed less robust effects, a height threshold of t = 3.33, p < 0.005 with an extent threshold of 48 μl was chosen, for a corrected cluster significance threshold of p < 0.05.

Acknowledgments This study was supported by NIMH grant R01-DC06155 (RalphAxel Müller) and R01-MH36840 (Eric Courchesne; MR scanning). Thanks to Greg Allen for methodological help.

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