Altered brain connectivity in sagittal craniosynostosis

Laboratory investigation

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Object

Sagittal nonsyndromic craniosynostosis (sNSC) is the most common form of NSC. The condition is associated with a high prevalence (> 50%) of deficits in executive function. The authors employed diffusion tensor imaging (DTI) and functional MRI to evaluate whether hypothesized structural and functional connectivity differences underlie the observed neurocognitive morbidity of sNSC.

Methods

Using a 3-T Siemens Trio MRI system, the authors collected DTI and resting-state functional connectivity MRI data in 8 adolescent patients (mean age 12.3 years) with sNSC that had been previously corrected via total vault cranioplasty and 8 control children (mean age 12.3 years) without craniosynostosis. Data were analyzed using the FMRIB Software Library and BioImageSuite.

Results

Analyses of the DTI data revealed white matter alterations approaching statistical significance in all supratentorial lobes. Statistically significant group differences (sNSC < control group) in mean diffusivity were localized to the right supramarginal gyrus. Analysis of the resting-state seed in relation to whole-brain data revealed significant increases in negative connectivity (anticorrelations) of Brodmann area 8 to the prefrontal cortex (Montreal Neurological Institute [MNI] center of mass coordinates [x, y, z]: −6, 53, 6) and anterior cingulate cortex (MNI coordinates 6, 43, 14) in the sNSC group relative to controls. Furthermore, in the sNSC patients versus controls, the Brodmann area 7, 39, and 40 seed had decreased connectivity to left angular gyrus (MNI coordinates −31, −61, 34), posterior cingulate cortex (MNI coordinates 13, −52, 18), precuneus (MNI coordinates 10, −55, 54), left and right parahippocampus (MNI coordinates −13, −52, 2 and MNI coordinates 11, −50, 2, respectively), lingual (MNI coordinates −11, −86, −10), and fusiform gyri (MNI coordinates −30, −79, −18). Intrinsic connectivity analysis also revealed altered connectivity between central nodes in the default mode network in sNSC relative to controls; the left and right posterior cingulate cortices (MNI coordinates −5, −35, 34 and MNI coordinates 6, −42, 39, respectively) were negatively correlated to right hemisphere precuneus (MNI coordinates 6, −71, 46), while the left ventromedial prefrontal cortex (MNI coordinates 6, 34, −8) was negatively correlated to right middle frontal gyrus (MNI coordinates 40, 4, 33). All group comparisons (sNSC vs controls) were conducted at a whole brain–corrected threshold of p < 0.05.

Conclusions

This study demonstrates altered neocortical structural and functional connectivity in sNSC that may, in part or substantially, underlie the neuropsychological deficits commonly reported in this population. Future studies combining analysis of multimodal MRI and clinical characterization data in larger samples of participants are warranted.

Abbreviations used in this paper:BA = Brodmann area; DMN = default mode network; DTI = diffusion tensor imaging; MNI = Montreal Neurological Institute; NSC = nonsyndromic craniosynostosis; ROI = region of interest; rs-fcMRI = resting-state functional connectivity MRI; sNSC = sagittal NSC; WISC-III = Wechsler Intelligence Scale for Children 3rd edition.

Object

Sagittal nonsyndromic craniosynostosis (sNSC) is the most common form of NSC. The condition is associated with a high prevalence (> 50%) of deficits in executive function. The authors employed diffusion tensor imaging (DTI) and functional MRI to evaluate whether hypothesized structural and functional connectivity differences underlie the observed neurocognitive morbidity of sNSC.

Methods

Using a 3-T Siemens Trio MRI system, the authors collected DTI and resting-state functional connectivity MRI data in 8 adolescent patients (mean age 12.3 years) with sNSC that had been previously corrected via total vault cranioplasty and 8 control children (mean age 12.3 years) without craniosynostosis. Data were analyzed using the FMRIB Software Library and BioImageSuite.

Results

Analyses of the DTI data revealed white matter alterations approaching statistical significance in all supratentorial lobes. Statistically significant group differences (sNSC < control group) in mean diffusivity were localized to the right supramarginal gyrus. Analysis of the resting-state seed in relation to whole-brain data revealed significant increases in negative connectivity (anticorrelations) of Brodmann area 8 to the prefrontal cortex (Montreal Neurological Institute [MNI] center of mass coordinates [x, y, z]: −6, 53, 6) and anterior cingulate cortex (MNI coordinates 6, 43, 14) in the sNSC group relative to controls. Furthermore, in the sNSC patients versus controls, the Brodmann area 7, 39, and 40 seed had decreased connectivity to left angular gyrus (MNI coordinates −31, −61, 34), posterior cingulate cortex (MNI coordinates 13, −52, 18), precuneus (MNI coordinates 10, −55, 54), left and right parahippocampus (MNI coordinates −13, −52, 2 and MNI coordinates 11, −50, 2, respectively), lingual (MNI coordinates −11, −86, −10), and fusiform gyri (MNI coordinates −30, −79, −18). Intrinsic connectivity analysis also revealed altered connectivity between central nodes in the default mode network in sNSC relative to controls; the left and right posterior cingulate cortices (MNI coordinates −5, −35, 34 and MNI coordinates 6, −42, 39, respectively) were negatively correlated to right hemisphere precuneus (MNI coordinates 6, −71, 46), while the left ventromedial prefrontal cortex (MNI coordinates 6, 34, −8) was negatively correlated to right middle frontal gyrus (MNI coordinates 40, 4, 33). All group comparisons (sNSC vs controls) were conducted at a whole brain–corrected threshold of p < 0.05.

Conclusions

This study demonstrates altered neocortical structural and functional connectivity in sNSC that may, in part or substantially, underlie the neuropsychological deficits commonly reported in this population. Future studies combining analysis of multimodal MRI and clinical characterization data in larger samples of participants are warranted.

Craniosynostosis results in abnormal head shape and brain morphology and can occur as either part of a syndrome, such as syndromic craniosynostosis), or in isolation, known as nonsyndromic craniosynostosis (NSC). Syndromic craniosynostosis frequently results from inherited genetic aberrations, is often associated with extracranial skeletal findings, and may be accompanied by relatively severe impairments in cognitive development. In contrast, NSC, which comprises 80% of all craniosynostosis cases, has poorly understood genetic etiology and is associated with subtle neurocognitive morbidity.8,17,19,34

Sagittal nonsyndromic craniosynostosis (sNSC) is the most common form of NSC, comprising approximately 40%–60% of cases.18 It results in a well-characterized cranial-vault dysmorphology that is widest temporally and narrow toward the vertex, frequently with ridging over the fused sagittal suture.13 Children with sNSC generally have normal IQ and gross development scores; however, recent studies have revealed that up to 50% of these children exhibit deficits in executive functioning.1,17,18,21,36,42 To date, no studies have explored the relationship between the observed cognitive deficits and anatomical or functional differences in the brain of sNSC children.

Resting-state functional connectivity MRI (rs-fcMRI) is a task-independent method to identify spatially distant brain regions that generate synchronized temporal fluctuations in the blood oxygenation level–dependent (BOLD) contrast signal. Interestingly, a number of distinct intrinsically connected brain networks have been identified using this method, and alterations within these networks are thought to account for some of the neurocognitive deficits observed in numerous conditions (particularly the default mode and frontoparietal attention networks).20,30,47 Diffusion tensor imaging (DTI) has been used extensively in the past decade to characterize the integrity of white matter microstructure. We combined these 2 techniques to gain valuable insight into the brain basis of neurocognitive deficits in sNSC.

Methods

Subjects

This was a prospective cohort study performed in accordance with the Yale Institutional Review Board. We studied 8 adolescents (mean age of 12.3 years) with sNSC, which was previously treated by Drs. John Persing and Charles Duncan by total vault cranioplasty at Yale–New Haven Hospital, and 8 control children (mean age 12.3) without craniosynostosis. The children with sNSC did not exhibit signs of syndromic craniosynostosis (specifically extracranial skeletal manifestations), and both groups of children were without cranial prostheses, mental retardation, known neurological disorder, or history of traumatic head injury or intracranial hemorrhage. As illustrated in Table 1, the groups of children were group-matched by age, sex, race, and handedness, as well as by performance IQ (PIQ) and verbal IQ (VIQ) measured using the Wechsler Intelligence Scale for Children 3rd edition (WISC-III).46

TABLE 1:

Characteristics of sagittal synostosis subjects and controls*

CharacteristicComparison Groupp Value
Corrected sNSCControls
no. of patients88NS
mean age ± SD (yrs)12.3 ± 1.812.3 ± 1.6NS
sexNS
 male67
 female21
raceNS
 white77
 African American11
rt handedness88NS
mean age at op ± SD (mos)7 ± 2NANS
mean WISC-III score ± SDNS
 performance IQ111 ± 15115 ± 10NS
 verbal IQ100 ± 16120 ± 16NS

NA = not applicable; NS = not significant.

Scan Protocol

All of the MRI scans were obtained using a single 3-T Siemens (Erlangen, Germany) Tim Trio MR system with a 32-coil polarized head coil. The DTI protocol consisted of a localizing scan, an MPRAGE anatomical scan (160 slices, 1.00-mm thickness, FOV 256 mm, TR 1900 msec, TE 2.96 msec), and 3 runs of diffusion-weighted imaging (TR 6.4 sec, TE 86 msec, slice thickness 2.5 mm, FOV 240 mm, matrix 96 × 96, 30 directions, b0 = 5, voxel size 2.5 × 2.5 × 2.5 mm, b = 1000 sec/mm2). For functional scanning, 34 axial slices (slice thickness 4.0 mm, no gap, FOV 220 mm, matrix size 64 × 64) were acquired using a T1-weighted sequence (TR 270 msec, TE 2.46 msec, FOV 220 mm, matrix size 256 × 256, flip angle 60°). Functional imaging volumes were collected in the same slice position as the preceding T1-weighted data. Two functional runs were acquired using a T2-sensitive gradient (TR 2 sec, TE 25 msec, FOV 220 mm, flip angle 60°, matrix size 64 × 64). Each volume consisted of 34 slices and each functional run was composed of 160 volumes. The participants were instructed to visually fixate on a black computer screen displaying a 1-in white plus sign during the functional scanning, to avoid movement, and to “think of nothing or zone out.”

Analysis

The 3 diffusion runs were manually inspected for movement artifact, and those with artifact were excluded from the analysis. The remaining runs were averaged and then processed utilizing FMRIB Software Library (FSL; http://fsl.fmrib.ox.ac.uk). Eddy current correction was used to correct for gradient-coil distortions and small head motions. Voxel-wise statistical analysis of the diffusion imaging data was carried out using tract-based spatial statistics,39 part of FSL.40 Analyzed diffusion data included fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. The following is a description of how fractional anisotropy data are processed and analyzed; however, the steps are similar for the analysis of mean diffusivity, axial diffusivity, and radial diffusivity. First, fractional anisotropy images were created by fitting a tensor model to the raw diffusion data using FMRIB's Diffusion Toolbox. Next, the brain was isolated using the Brain Extraction Tool.38 All subjects' fractional anisotropy data were then aligned into a common space using the nonlinear registration tool FNIRT, which uses a b-spline representation of the registration warp field. Next, the mean fractional anisotropy image was created and thinned to create a mean fractional anisotropy skeleton. Each subject's aligned fractional anisotropy data were then projected onto this skeleton, and the resulting data were fed into voxel-wise cross-subject statistics. The functional data were corrected for movement and slice time utilizing Matlab (MathWorks). Warping of the data were accomplished using 2 linear transformations within subjects and a nonlinear registration into Montreal Neurological Institute (MNI) center of mass coordinates. Whole-brain ipsilateral intrinsic connectivity contrast of the functional data was conducted using BioImage Suite with a cluster threshold of 150 and p < 0.1. This was done following manual inspection of the registrations as a provision for potential morphology differences resulting from dolichocephalism (www.bioimagesuite.org). After initial whole-brain ipsilateral intrinsic connectivity contrast analysis, a follow-up seed-based analysis utilizing a neocortical region of interest (ROI) identified from the intrinsic connectivity contrast analysis was performed where a cluster threshold of 150 and p < 0.05 were used to control for multiple comparisons. Finally, intrinsic connectivity networks, including the default mode network and frontoparietal attention network, were analyzed using the following method. Antomical ROIs representing the default mode network and frontoparietal attention network were selected based on the literature (Table 2).10,23,45 The ROIs were then generated in MNI space using the closest parcellation to previous reported results (Fig. 1).35 Inverse transforms were used to bring ROIs back to individual space. Correlations between ROIs were run and transformed into z-scores with the Fisher transform to generate correlation matrices. T-tests were run in Matlab to compare connectivity differences within each group and between the 2 groups (p < 0.05, uncorrected). Matrix results were “thresholded” using false discovery rate correction for multiple comparisons (p < 0.05, corrected).

TABLE 2:

Regions of interest used for intrinsic connectivity network analysis*

NetworkROIVol (mm3)MNI (x, y, z) Center of Mass CoordinateColor
DMN
lt ant med PFC3813(−6, 45, 19)red
rt ant med PFC3548(7, 47, 24)maroon
lt vent med PFC3361(−6, 37, −8)yellow
rt vent med PFC2647(6, 34, −8)light yellow
lt MFG5480(−42, 9, 33)sea green
rt MFG3798(40, 4, 33)pale seagreen
lt SFG3799(−16, 31, 53)purple
rt SFG5521(15, 29, 55)lilac
lt PCC2646(−5, −35, 34)orange
rt PCC2896(6, −42, 39)light orange
lt precuneus3455(−4, −71, 41)bright pink
rt precuneus3600(6, −71, 46)pink
lt ITG7050(−60, −27, −19)bright green
rt ITG5280(62, −27, −20)lime green
lt parahipp6505(−23, −31, −23)cyan
rt parahipp5992(29, −35, −28)light blue
lt lat parietal5497(−51, −47, 43)plum
rt lat parietal5204(50, −49, 43)light plum
FPN
lt dorsolat PFC5432(−39, 23, 46)forest green
rt dorsolat PFC3331(37, 27, 43)olive green
lt IPL4060(−55, −51, 25)cranberry
rt IPL6795(47, −62, 35)raspberry
lt IPS4456(−28, −63, 38)salmon
rt IPS3928(31, −71, 41)peach
lt anterior insula4130(−37, 11, 6)royal blue
rt anterior insula4987(41, 8, 0)periwinkle
lt FEF4719(−28, −11, 60)brown
rt FEF4452(25, −14, 66)beige

ant med = anterior medial; DMN = default mode network; FEF = frontal eye field; FPN = frontoparietal attention network; IPL = inferior parietal lobe; IPS = inferior parietal sulcus; ITG = inferior temporal gyrus; MFG = middle frontal gyrus; parahipp = parahippocampus; PCC = posterior cingulate cortex; PFC = prefrontal cortex; SFG = superior frontal gyrus; vent med = ventral medial.

Fig. 1.
Fig. 1.

Color map of default mode and frontoparietal attention network regions of interest used in intrinsic connectivity network analysis.

Results

Diffusion Tensor Imaging

Diffusion-weighted imaging revealed trends toward extensive white matter alterations in all supratentorial lobes. However, statistically significant (p < 0.05, corrected) changes were only seen in mean diffusivity adjacent to the right supramarginal gyrus. There were no differences in axial diffusivity between the 2 groups of participants. Group differences in radial diffusivity did not reach statistical significance; however, there was a trend toward significance, with radial diffusivity being greater in control children than in children with sNSC in frontal, parietal, occipital, and temporal white matter as well as major tracts such as the corpus callosum, inferior and superior longitudinal fasciculus, and corona radiata (p = 0.10). Statistical analysis of mean diffusivity also revealed trends toward widespread mean diffusivity being greater in control children than in children with sNSC (p = 0.10), which anatomically mirrored those shown by radial diffusivity analysis. A region of white matter under the right supramarginal gyrus (MNI coordinates [x, y, z]: 46, −48, 36) demonstrated statistically significant (p < 0.05) mean diffusivity changes (Fig. 2). Differences in fractional anisotropy again mirrored the anatomical regions of radial diffusivity and mean diffusivity, with a trend toward lower fractional anisotropy in control children compared to children with sNSC (p = 0.10).

Fig. 2.
Fig. 2.

Statistical map of medial diffusion differences showing decreased mean diffusivity in children with sNSC compared to controls (p < 0.05). Green represents major white matter tracts; red represents differences in mean diffusivity.

rs-fcMRI

Whole-Brain Ipsilateral Intrinsic Connectivity Analysis

As illustrated in Fig. 3, intrinsic connectivity contrast analysis of the rs-fcMR images revealed increased activation differences in the left angular gyrus and the left superior parietal lobule (Brodmann area [BA] 7, 39, and 40) and decreased activation differences in the vermis of the cerebellum and medial frontal cortex (BA 8) in control children compared to those with sNSC (k = 150, p < 0.1).

Fig. 3.
Fig. 3.

Map showing group differences (subject vs control, p < 0.1) in whole-brain ipsilateral intrinsic connectivity contrast analysis. Warm (orange to yellow) colors represent greater activation in subject group. Blue colors represent greater activation in the control group.

Region of Interest Seeds to Whole-Brain Analysis

As shown in Fig. 4 left, seeds to whole brain–based functional connectivity analyses demonstrated increased negative connectivity (anticorrelations) of BA 8 to prefrontal cortex (MNI coordinates −6, 53, 6) and anterior cingulate cortex (MNI coordinates 6, 43, 14) in sNSC relative to unaffected adolescents. The BA 7, 39, and 40 seed had decreased connectivity to left the angular gyrus (MNI coordinates −31, −61, 34), left supramarginal gyrus (MNI coordinates −48, −44, 38), posterior cingulate cortex (MNI coordinates 13, −52, 18), precuneus (MNI coordinates 10, −55, 54), left and right parahippocampus (MNI coordinates −13, −52, 2 and MNI coordinates 11, −50, 2, respectively), lingual gyrus (MNI coordinates −11, −86, −10), and fusiform gyrus (MNI coordinates −30, −79, −18) in sNSC relative to unaffected controls (Fig. 4 right). These results are also presented in Table 3.

Fig. 4.
Fig. 4.

Left: Map showing group differences (subject vs control, p < 0.05) in connectivity from BA 8 seed-to-whole brain analysis. Stronger negative connectivity (anticorrelations) to anterior cingulate and medial prefrontal cortex is observed for the sNSC group compared with the controls. Green represents ROI seed. Right: Map showing group differences (subject vs control, p < 0.05) in connectivity from left BAs 7, 39, and 40 seed-to-whole brain analysis. Decreased connectivity to left angular gyrus, left supramarginal gyrus, precuneus, posterior cingulate, cuneus, and parahippocampus for the sNSC group than the control group. Green represents ROI seed.

TABLE 3:

Results of ROI seed to whole-brain connectivity analysis

ROI SeedAreas of Altered Connectivity*MNI Coordinates (x, y, z)Connectivity Finding
BA 8anticorrelated
middle frontal gyrus(−6, 53, 6)
anterior cingulate cortex(6, 43, 14)
BAs 7, 39, & 40
precuneus(10, −55, 54)
PCC(13, −52, 18)
lt angular gyrus (−31, −61, 34)decreased
lt supramarginal gyrus(−48, −44, 38)
lt parrahipp(−13, −52, 2)
rt parahipp(11, −50, 2)
lingual gyrus(−11, −86, −10)
fusiform gyrus(−30, −79, −18)

Found to be significant at p < 0.05.

Sagittal NSC relative to control.

Intrinsic Network Connectivity Analysis

Correlation matrices, as shown in Fig. 5, depict within-group connectivity networks (p < 0.05, uncorrected) as well as between-group connectivity differences (p < 0.05, corrected). Significant negative correlations (anticorrelations) between the central default mode network nodes were found in the sNSC group relative to unaffected adolescents (Fig. 5C and D). Left ventromedial prefrontal cortex (MNI coordinates −6, 37, −8) was negatively correlated with the right middle frontal gyrus (MFG; MNI coordinates 40, 4, 33) (p < 0.05, corrected). The left posterior cingulate cortex (MNI coordinates −5, −35, 34) and right posterior cingulate cortex (MNI coordinates 6, −42, 39) were both negatively correlated with the right precuneus (MNI coordinates 6, −71, 46) (p < 0.05, corrected). A general trend of decreased activation in both networks, although more strongly in the default mode, was observed in sNSC patients relative to unaffected controls (p < 0.05, uncorrected).

Fig. 5.
Fig. 5.

A and B: Correlation matrices for ROIs representing default mode network and frontoparietal attention networks in unaffected controls (A; p < 0.05, uncorrected), and sNSC patients (B; p < 0.05, uncorrected). C and D: Connectivity differences show a trend toward decreased default mode network and frontoparietal attention network connectivity in subjects relative to controls (C; p < 0.05, uncorrected) and specific default mode network disconnectivity between left and right posterior cingulate cortex and precuneus and left ventromedial prefrontal cortex and right middle frontal gyrus in subjects relative to controls (D; p < 0.05, corrected). Warm colors represent greater activation in subject group. Blue colors represent greater activation in control group.

Discussion

Recent studies on neurocognitive and behavioral outcomes in NSC indicate that while IQ and adaptive development scores fall within the normal range, nearly 50% of subjects demonstrate deficiency in visual-spatial planning ability, language impairment, or other “cognitive abnormality.”17,21 These findings come at a time of overall flux in the approach to surgical correction of NSC. Traditionally, an extensive open procedure was favored; however, recently, minimally invasive techniques have emerged for the treatment of isolated craniosynostosis.14 Compared with the traditional approach, minimally invasive endoscopic strip craniectomy has been reported to result in less blood loss and shorter hospital stay, and it can be performed in individuals at an earlier age.7 The technique, however, requires helmet therapy for up to 1 year postoperatively to complete morphological correction of the calvarial vault and delay the maximal correction of shape for prolonged periods (up to 1 year).

What remains unknown is if there is a role for surgical correction in the abatement or prevention of neurocognitive deficit. This is, to our knowledge, the first application of MRI techniques in the analysis of NSC brain connectivity and function. It should be noted that while few of the DTI findings reached statistical significance at p < 0.05 (mean diffusivity values of p < 0.05 were found at coordinates 40, −41, −36 in the white matter under the right supramarginal gyrus and angular gyrus), these preliminary data underscore important trends of diffuse white matter alterations that provide impetus for expanded studies.

Resting-state functional connectivity data failed to reach statistical significance in the whole-brain ipsilateral intrinsic connectivity contrast analysis. Follow-up seed-to-whole-brain ROI analysis revealed significant abnormal connectivity within the medial prefrontal region (BA 8; posterior frontomedian cortex) as well as in language and visuospatial regions of left hemisphere parietal cortex (BA 7, 39, and 40). A discussion and interpretation of these results are presented below and are followed by a final discussion of the intrinsic network analysis.

We found significant altered connectivity within the posterior frontomedian cortex as well as of the cortex of the anterior cingulate (Fig. 4 left). Altered connectivity of the posterior frontomedian cortex is associated with problems in language processing, attention, and behavior.3,15,16,43 The area is further responsible for organization of thoughts, performance adjustment, attention switching, behavior modulation, decision making, and resolving uncertainty, functions that are reported to be abnormal in many children with sNSC.21,28,30 Altered connectivity of the posterior frontomedian cortex to the anterior cingulate is particularly interesting in sNSC as both are central nodes in the executive control network.27 Decreased connectivity involving these 2 regions is thought to account for problems with inhibition and social adjustment in some disorders.20,25,29 Ultimately, their altered connectivity is not unsurprising given the reported executive dysfunction in sNSC and supports the need to further characterize the medial executive control network in this condition.

The left lateral parietal seed (BAs 7, 39, and 40) had significantly decreased connectivity to areas of visuospatial processing (superior parietal lobule, precuneus, and posterior cingulate), to regions of language processing (left angular gyrus, left supramarginal gyrus, lingual gyrus, fusiform gyrus), and to loci of memory retrieval and consolidation (parahippocampus) in the sNSC group relative to unaffected adolescents (Fig. 4 right). All of these areas, including the fusiform and lingual gyri, are nodes in the default mode network and therefore suggest its potential dysfunction in sNSC.10,23,32,45 The altered activation and connectivity of the angular gyrus is interesting in this patient population as it is well known to be altered in children with abnormal reading and dyslexia.12 Furthermore, the angular gyrus plays a major role in semantic processing, word reading and comprehension, number processing, the default mode network, memory retrieval, attention, and spatial-cognition disabilities shared by many children with NSC.19,33 Altered connectivity of the superior parietal lobule (BA 7) to the precuneus, posterior cingulate cortex, and fusiform and lingual gyri may also explain some of the attention and spatial-cognition disabilities seen in sNSC. These regions are intimately involved in visuospatial processing and memory,2,6,22,37 and abnormal connectivity is found in a number of cognitive conditions. In fact, altered function of the superior parietal lobule (BA 7) is believed to account for the hallmark visuospatial disability in Williams syndrome.9

Finally, intrinsic connectivity network analysis indicated an abnormal default mode network in the sNSC brain (Fig. 5). This corroborates the findings from the seed-to-whole-brain analysis discussed above where both ROIs expressed altered connectivity to the precuneus and/or cingulate. The default mode network is the primary network at rest. It functions in referential introspection, processing new information, retrieving memories, and generating new thoughts.4 Moreover, a strong positively connected default mode network at rest correlates with better performance during active engagement in cognitive tasks.11 Specifically, abnormal decreased connectivity involving the posterior cingulate cortex, precuneus, and ventromedial prefrontal cortex—the major nodes in the default mode network—have been found in patients with attention deficit hyperactivity disorder, and altered negative connectivity is now reported in sNSC.5,41 Abnormal decreased connectivity within the default mode network is further associated with a host of conditions of memory and executive dysfunction.24,26,31,44,47 Our similar findings of decreased and negative connectivity involving the posterior cingulate cortex, precuneus, and ventromedial prefrontal cortex in the sagittal group may explain some of the executive dysfunction, learning disabilities, and/or behavioral problems observed in the condition. It should be recalled, as a final note, that both the prefrontal and lateral parietal seeds—in conjunction with and independent of the intrinsic network analysis—negatively correlated with the precuneus and/or cingulate, supporting the idea that the major default mode network nodes have convincing abnormal connectivity in sNSC. Lastly, while there were no significant findings within the frontoparietal attention network at rest, a more appropriate task-based design should be employed to inspect this system.

Ultimately, preliminary resting-state data of the sNSC brain reveal altered connectivity in central default mode network nodes, areas of executive function (prefrontal cortex), and regions of language and visuospatial processing (superior parietal lobule, angular and supramarginal gyri). Such data demonstrate that further studies are needed.

Conclusions

Sagittal craniosynostosis is associated with an increased rate of learning disability. This study lends evidence to the fact that this learning disability may be rooted in a diffuse microstructural abnormality, specific brain regions responsible for language processing and executive function, and/or aberrant function connectivity within the brain's intrinsic networks. Ultimately, this study provides a foundational basis for a hypothesized altered neocortical structure-function relationship in the sNSC. This warrants future studies combining multimodal MRI and neurocognitive characterization on a larger number of sNSC subjects.

Acknowledgment

Special thanks to Jeffery Eilbott for technical expertise in coding, image acquisition, and analysis.

Disclosure

The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

This work was supported by a Doris Duke Charitable Foundation Clinical Scholars Fellowship; a National Institutes of Health–National Center for Advancing Translational Science Award TL1: One Year Medical Student Research Fellowship; and an American Society of Maxillofacial Surgeons Research Grant.

Author contributions to the study and manuscript preparation include the following. Conception and design: Beckett, Brooks. Acquisition of data: Beckett, Brooks. Analysis and interpretation of data: Beckett, Brooks. Drafting the article: Beckett, Brooks. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Beckett. Statistical analysis: Beckett, Brooks, Lacadie. Administrative/technical/material support: Brooks. Study supervision: Constable, Pelphrey, Persing.

This article contains some figures that are displayed in color online but in black-and-white in the print edition.

Presented in abstract form at the 2013 Annual Meeting of the American Association of Neurological Surgeons, New Orleans, LA, April 27–May 1. Abstract was published in J Neurosurg 119:A547, 2013.

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    Jimenez DFBarone CM: Early treatment of anterior calvarial craniosynostosis using endoscopic-assisted minimally invasive techniques. Childs Nerv Syst 23:141114192007

    • Search Google Scholar
    • Export Citation
  • 15

    Johnson MKNolen-Hoeksema SMitchell KJLevin Y: Medial cortex activity, self-reflection and depression. Soc Cogn Affect Neurosci 4:3133272009

    • Search Google Scholar
    • Export Citation
  • 16

    Just MAKeller TAMalave VLKana RKVarma S: Autism as a neural systems disorder: a theory of frontal-posterior underconnectivity. Neurosci Biobehav Rev 36:129213132012

    • Search Google Scholar
    • Export Citation
  • 17

    Kapp-Simon KASpeltz MLCunningham MLPatel PKTomita T: Neurodevelopment of children with single suture craniosynostosis: a review. Childs Nerv Syst 23:2692812007

    • Search Google Scholar
    • Export Citation
  • 18

    Kolar JC: An epidemiological study of nonsyndromal craniosynostoses. J Craniofac Surg 22:47492011

  • 19

    Korpilahti PSaarinen PHukki J: Deficient language acquisition in children with single suture craniosynostosis and deformational posterior plagiocephaly. Childs Nerv Syst 28:4194252012

    • Search Google Scholar
    • Export Citation
  • 20

    Liddle EBHollis CBatty MJGroom MJTotman JJLiotti M: Task-related default mode network modulation and inhibitory control in ADHD: effects of motivation and methylphenidate. J Child Psychol Psychiatry 52:7617712011

    • Search Google Scholar
    • Export Citation
  • 21

    Magge SNWesterveld MPruzinsky TPersing JA: Long-term neuropsychological effects of sagittal craniosynostosis on child development. J Craniofac Surg 13:991042002

    • Search Google Scholar
    • Export Citation
  • 22

    Maguire EAFrith CDBurgess NDonnett JGO'Keefe J: Knowing where things are parahippocampal involvement in encoding object locations in virtual large-scale space. J Cogn Neurosci 10:61761998

    • Search Google Scholar
    • Export Citation
  • 23

    Marrelec GFransson P: Assessing the influence of different ROI selection strategies on functional connectivity analyses of fMRI data acquired during steady-state conditions. PLoS One 6:e147882011

    • Search Google Scholar
    • Export Citation
  • 24

    McFadden KLTregellas JRShott MEFrank GK: Reduced salience and default mode network activity in women with anorexia nervosa. J Psychiatry Neurosci 38:1300462013

    • Search Google Scholar
    • Export Citation
  • 25

    Mundy P: Annotation: the neural basis of social impairments in autism: the role of the dorsal medial-frontal cortex and anterior cingulate system. J Child Psychol Psychiatry 44:7938092003

    • Search Google Scholar
    • Export Citation
  • 26

    Peng ZWXu THe QHShi CZWei ZMiao GD: Default network connectivity as a vulnerability marker for obsessive compulsive disorder. Psychol Med [epub ahead of print]2013

    • Search Google Scholar
    • Export Citation
  • 27

    Petersen SEPosner MI: The attention system of the human brain: 20 years after. Annu Rev Neurosci 35:73892012

  • 28

    Ridderinkhof KRUllsperger MCrone EANieuwenhuis S: The role of the medial frontal cortex in cognitive control. Science 306:4434472004

    • Search Google Scholar
    • Export Citation
  • 29

    Rubia KOvermeyer STaylor EBrammer MWilliams SCSimmons A: Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: a study with functional MRI. Am J Psychiatry 156:8918961999

    • Search Google Scholar
    • Export Citation
  • 30

    Rushworth MFSWalton MEKennerley SWBannerman DM: Action sets and decisions in the medial frontal cortex. Trends Cogn Sci 8:4104172004

    • Search Google Scholar
    • Export Citation
  • 31

    Sambataro FWolf NDPennuto MVasic NWolf RC: Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity. Psychol Med [epub ahead of print]2013

    • Search Google Scholar
    • Export Citation
  • 32

    Schmidt SAAkrofi KCarpenter-Thompson JRHusain FT: Default mode, dorsal attention and auditory resting state networks exhibit differential functional connectivity in tinnitus and hearing loss. PLoS ONE 8:e764882013

    • Search Google Scholar
    • Export Citation
  • 33

    Seghier ML: The angular gyrus: multiple functions and multiple subdivisions. Neuroscientist 19:43612013

  • 34

    Sharma RK: Craniosynostosis. Indian J Plast Surg 46:18272013

  • 35

    Shen XTokoglu FPapademetris XConstable RT: Groupwise whole-brain parcellation from resting-state fMRI data for network node identification. Neuroimage 82:4034152013

    • Search Google Scholar
    • Export Citation
  • 36

    Shipster CHearst DSomerville AStackhouse JHayward RWade A: Speech, language, and cognitive development in children with isolated sagittal synostosis. Dev Med Child Neurol 45:34432003

    • Search Google Scholar
    • Export Citation
  • 37

    Small DMGitelman DRGregory MDNobre ACParrish TBMesulam MM: The posterior cingulate and medial prefrontal cortex mediate the anticipatory allocation of spatial attention. Neuroimage 18:6336412003

    • Search Google Scholar
    • Export Citation
  • 38

    Smith SM: Fast robust automated brain extraction. Hum Brain Mapp 17:1431552002

  • 39

    Smith SMJenkinson MJohansen-Berg HRueckert DNichols TEMackay CE: Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:148715052006

    • Search Google Scholar
    • Export Citation
  • 40

    Smith SMJenkinson MWoolrich MWBeckmann CFBehrens TEJohansen-Berg H: Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23:Suppl 1S208S2192004

    • Search Google Scholar
    • Export Citation
  • 41

    Sonuga-Barke EJFairchild G: Neuroeconomics of attention-deficit/hyperactivity disorder: differential influences of medial, dorsal, and ventral prefrontal brain networks on suboptimal decision making?. Biol Psychiatry 72:1261332012

    • Search Google Scholar
    • Export Citation
  • 42

    Speltz MLKapp-Simon KCollett BKeich YGaither RCradock MM: Neurodevelopment of infants with single-suture craniosynostosis: presurgery comparisons with case-matched controls. Plast Reconstr Surg 119:187418812007

    • Search Google Scholar
    • Export Citation
  • 43

    Volz KGSchubotz RIvon Cramon DY: Variants of uncertainty in decision-making and their neural correlates. Brain Res Bull 67:4034122005

    • Search Google Scholar
    • Export Citation
  • 44

    Wang KLiang MWang LTian LZhang XLi K: Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study. Hum Brain Mapp 28:9679782007

    • Search Google Scholar
    • Export Citation
  • 45

    Watanabe THirose SWada HImai YMachida TShirouzu I: A pairwise maximum entropy model accurately describes resting-state human brain networks. Nat Commun 4:13702013

    • Search Google Scholar
    • Export Citation
  • 46

    Wechsler D: WISC-III: Wechsler Intelligence Scale for Children ed 3San Antonio, TXPsychological Corporation1991

  • 47

    Whitfield-Gabrieli SFord JM: Default mode network activity and connectivity in psychopathology. Annu Rev Clin Psychol 8:49762012

If the inline PDF is not rendering correctly, you can download the PDF file here.

Article Information

* Dr. Beckett and Mr. Brooks contributed equally to the work.

Address correspondence to: Joel Beckett, M.D., UCLA Neurosurgery, Box 956901, Los Angeles, CA 90095-6910. email: jbeckett@mednet.ucla.edu.

Please include this information when citing this paper: published online April 18, 2014; DOI: 10.3171/2014.3.PEDS13516.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    Color map of default mode and frontoparietal attention network regions of interest used in intrinsic connectivity network analysis.

  • View in gallery

    Statistical map of medial diffusion differences showing decreased mean diffusivity in children with sNSC compared to controls (p < 0.05). Green represents major white matter tracts; red represents differences in mean diffusivity.

  • View in gallery

    Map showing group differences (subject vs control, p < 0.1) in whole-brain ipsilateral intrinsic connectivity contrast analysis. Warm (orange to yellow) colors represent greater activation in subject group. Blue colors represent greater activation in the control group.

  • View in gallery

    Left: Map showing group differences (subject vs control, p < 0.05) in connectivity from BA 8 seed-to-whole brain analysis. Stronger negative connectivity (anticorrelations) to anterior cingulate and medial prefrontal cortex is observed for the sNSC group compared with the controls. Green represents ROI seed. Right: Map showing group differences (subject vs control, p < 0.05) in connectivity from left BAs 7, 39, and 40 seed-to-whole brain analysis. Decreased connectivity to left angular gyrus, left supramarginal gyrus, precuneus, posterior cingulate, cuneus, and parahippocampus for the sNSC group than the control group. Green represents ROI seed.

  • View in gallery

    A and B: Correlation matrices for ROIs representing default mode network and frontoparietal attention networks in unaffected controls (A; p < 0.05, uncorrected), and sNSC patients (B; p < 0.05, uncorrected). C and D: Connectivity differences show a trend toward decreased default mode network and frontoparietal attention network connectivity in subjects relative to controls (C; p < 0.05, uncorrected) and specific default mode network disconnectivity between left and right posterior cingulate cortex and precuneus and left ventromedial prefrontal cortex and right middle frontal gyrus in subjects relative to controls (D; p < 0.05, corrected). Warm colors represent greater activation in subject group. Blue colors represent greater activation in control group.

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    Jane JAEdgerton MTFutrell JWPark TS: Immediate correction of sagittal synostosis. J Neurosurg 49:7057101978

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    Jimenez DFBarone CM: Early treatment of anterior calvarial craniosynostosis using endoscopic-assisted minimally invasive techniques. Childs Nerv Syst 23:141114192007

    • Search Google Scholar
    • Export Citation
  • 15

    Johnson MKNolen-Hoeksema SMitchell KJLevin Y: Medial cortex activity, self-reflection and depression. Soc Cogn Affect Neurosci 4:3133272009

    • Search Google Scholar
    • Export Citation
  • 16

    Just MAKeller TAMalave VLKana RKVarma S: Autism as a neural systems disorder: a theory of frontal-posterior underconnectivity. Neurosci Biobehav Rev 36:129213132012

    • Search Google Scholar
    • Export Citation
  • 17

    Kapp-Simon KASpeltz MLCunningham MLPatel PKTomita T: Neurodevelopment of children with single suture craniosynostosis: a review. Childs Nerv Syst 23:2692812007

    • Search Google Scholar
    • Export Citation
  • 18

    Kolar JC: An epidemiological study of nonsyndromal craniosynostoses. J Craniofac Surg 22:47492011

  • 19

    Korpilahti PSaarinen PHukki J: Deficient language acquisition in children with single suture craniosynostosis and deformational posterior plagiocephaly. Childs Nerv Syst 28:4194252012

    • Search Google Scholar
    • Export Citation
  • 20

    Liddle EBHollis CBatty MJGroom MJTotman JJLiotti M: Task-related default mode network modulation and inhibitory control in ADHD: effects of motivation and methylphenidate. J Child Psychol Psychiatry 52:7617712011

    • Search Google Scholar
    • Export Citation
  • 21

    Magge SNWesterveld MPruzinsky TPersing JA: Long-term neuropsychological effects of sagittal craniosynostosis on child development. J Craniofac Surg 13:991042002

    • Search Google Scholar
    • Export Citation
  • 22

    Maguire EAFrith CDBurgess NDonnett JGO'Keefe J: Knowing where things are parahippocampal involvement in encoding object locations in virtual large-scale space. J Cogn Neurosci 10:61761998

    • Search Google Scholar
    • Export Citation
  • 23

    Marrelec GFransson P: Assessing the influence of different ROI selection strategies on functional connectivity analyses of fMRI data acquired during steady-state conditions. PLoS One 6:e147882011

    • Search Google Scholar
    • Export Citation
  • 24

    McFadden KLTregellas JRShott MEFrank GK: Reduced salience and default mode network activity in women with anorexia nervosa. J Psychiatry Neurosci 38:1300462013

    • Search Google Scholar
    • Export Citation
  • 25

    Mundy P: Annotation: the neural basis of social impairments in autism: the role of the dorsal medial-frontal cortex and anterior cingulate system. J Child Psychol Psychiatry 44:7938092003

    • Search Google Scholar
    • Export Citation
  • 26

    Peng ZWXu THe QHShi CZWei ZMiao GD: Default network connectivity as a vulnerability marker for obsessive compulsive disorder. Psychol Med [epub ahead of print]2013

    • Search Google Scholar
    • Export Citation
  • 27

    Petersen SEPosner MI: The attention system of the human brain: 20 years after. Annu Rev Neurosci 35:73892012

  • 28

    Ridderinkhof KRUllsperger MCrone EANieuwenhuis S: The role of the medial frontal cortex in cognitive control. Science 306:4434472004

    • Search Google Scholar
    • Export Citation
  • 29

    Rubia KOvermeyer STaylor EBrammer MWilliams SCSimmons A: Hypofrontality in attention deficit hyperactivity disorder during higher-order motor control: a study with functional MRI. Am J Psychiatry 156:8918961999

    • Search Google Scholar
    • Export Citation
  • 30

    Rushworth MFSWalton MEKennerley SWBannerman DM: Action sets and decisions in the medial frontal cortex. Trends Cogn Sci 8:4104172004

    • Search Google Scholar
    • Export Citation
  • 31

    Sambataro FWolf NDPennuto MVasic NWolf RC: Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity. Psychol Med [epub ahead of print]2013

    • Search Google Scholar
    • Export Citation
  • 32

    Schmidt SAAkrofi KCarpenter-Thompson JRHusain FT: Default mode, dorsal attention and auditory resting state networks exhibit differential functional connectivity in tinnitus and hearing loss. PLoS ONE 8:e764882013

    • Search Google Scholar
    • Export Citation
  • 33

    Seghier ML: The angular gyrus: multiple functions and multiple subdivisions. Neuroscientist 19:43612013

  • 34

    Sharma RK: Craniosynostosis. Indian J Plast Surg 46:18272013

  • 35

    Shen XTokoglu FPapademetris XConstable RT: Groupwise whole-brain parcellation from resting-state fMRI data for network node identification. Neuroimage 82:4034152013

    • Search Google Scholar
    • Export Citation
  • 36

    Shipster CHearst DSomerville AStackhouse JHayward RWade A: Speech, language, and cognitive development in children with isolated sagittal synostosis. Dev Med Child Neurol 45:34432003

    • Search Google Scholar
    • Export Citation
  • 37

    Small DMGitelman DRGregory MDNobre ACParrish TBMesulam MM: The posterior cingulate and medial prefrontal cortex mediate the anticipatory allocation of spatial attention. Neuroimage 18:6336412003

    • Search Google Scholar
    • Export Citation
  • 38

    Smith SM: Fast robust automated brain extraction. Hum Brain Mapp 17:1431552002

  • 39

    Smith SMJenkinson MJohansen-Berg HRueckert DNichols TEMackay CE: Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:148715052006

    • Search Google Scholar
    • Export Citation
  • 40

    Smith SMJenkinson MWoolrich MWBeckmann CFBehrens TEJohansen-Berg H: Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23:Suppl 1S208S2192004

    • Search Google Scholar
    • Export Citation
  • 41

    Sonuga-Barke EJFairchild G: Neuroeconomics of attention-deficit/hyperactivity disorder: differential influences of medial, dorsal, and ventral prefrontal brain networks on suboptimal decision making?. Biol Psychiatry 72:1261332012

    • Search Google Scholar
    • Export Citation
  • 42

    Speltz MLKapp-Simon KCollett BKeich YGaither RCradock MM: Neurodevelopment of infants with single-suture craniosynostosis: presurgery comparisons with case-matched controls. Plast Reconstr Surg 119:187418812007

    • Search Google Scholar
    • Export Citation
  • 43

    Volz KGSchubotz RIvon Cramon DY: Variants of uncertainty in decision-making and their neural correlates. Brain Res Bull 67:4034122005

    • Search Google Scholar
    • Export Citation
  • 44

    Wang KLiang MWang LTian LZhang XLi K: Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study. Hum Brain Mapp 28:9679782007

    • Search Google Scholar
    • Export Citation
  • 45

    Watanabe THirose SWada HImai YMachida TShirouzu I: A pairwise maximum entropy model accurately describes resting-state human brain networks. Nat Commun 4:13702013

    • Search Google Scholar
    • Export Citation
  • 46

    Wechsler D: WISC-III: Wechsler Intelligence Scale for Children ed 3San Antonio, TXPsychological Corporation1991

  • 47

    Whitfield-Gabrieli SFord JM: Default mode network activity and connectivity in psychopathology. Annu Rev Clin Psychol 8:49762012

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