Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis

The Effects of X Chromosome Loss on Neuroanatomical and Cognitive Phenotypes During Adolescence: a Multi-modal Structural MRI and Diffusion Tensor Imaging Study

The absence of all or part of one X chromosome in female humans causes Turner's syndrome (TS), providing a unique "knockout model" to investigate the role of the X chromosome in neuroanatomy and cognition. Previous studies have demonstrated TS-associated brain differences; however, it remains largely unknown 1) how the brain structures are affected by the type of X chromosome loss and 2) how X chromosome loss influences the brain-cognition relationship. Here, we addressed these by investigating gray matter morphology and white matter connectivity using a multimodal MRI dataset from 34 adolescent TS patients (13 mosaic and 21 nonmosaic) and 21 controls. Intriguingly, the 2 TS groups exhibited significant differences in surface area in the right angular gyrus and in white matter integrity of the left tapetum of corpus callosum; these data support a link between these brain phenotypes and the type of X chromosome loss in TS. We further showed that the X chromosome modulates specific brain-cognition relationships: thickness and surface area in multiple cortical regions are positively correlated with working-memory performance in controls but negatively in TS. These findings provide novel insights into the X chromosome effect on neuroanatomical and cognitive phenotypes and highlight the role of genetic factors in brain-cognition relationships.

The dynamic role of genetics on cortical patterning during childhood and adolescence

Longitudinal imaging and quantitative genetic studies have both provided important insights into the nature of human brain development. In the present study we combine these modalities to obtain dynamic anatomical maps of the genetic contributions to cortical thickness through childhood and adolescence. A total of 1,748 anatomic MRI scans from 792 healthy twins and siblings were studied with up to eight time points per subject. Using genetically informative latent growth curve modeling of 81,924 measures of cortical thickness, changes in the genetic contributions to cortical development could be visualized across the age range at high resolution. There was highly statistically significant (P < 0.0001) genetic variance throughout the majority of the cerebral cortex, with the regions of highest heritability including the most evolutionarily novel regions of the brain. Dynamic modeling of changes in heritability over time demonstrated that the heritability of cortical thickness increases gradually throughout late childhood and adolescence, with sequential emergence of three large regions of high heritability in the temporal poles, the inferior parietal lobes, and the superior and dorsolateral frontal cortices.

The Richness of Task-Evoked Hemodynamic Responses Defines a Pseudohierarchy of Functionally Meaningful Brain Networks

Functional magnetic resonance imaging can measure distributed and subtle variations in brain responses associated with task performance. However, it is unclear whether the rich variety of responses observed across the brain is functionally meaningful and consistent across individuals. Here, we used a multivariate clustering approach that grouped brain regions into clusters based on the similarity of their task-evoked temporal responses at the individual level, and then established the spatial consistency of these individual clusters at the group level. We observed a stable pseudohierarchy of task-evoked networks in the context of a delayed sequential motor task, where the fractionation of networks was driven by a gradient of involvement in motor sequence preparation versus execution. In line with theories about higher-level cognitive functioning, this gradient evolved in a rostro-caudal manner in the frontal lobe. In addition, parcellations in the cerebellum and basal ganglia matched with known anatomical territories and fiber pathways with the cerebral cortex. These findings demonstrate that subtle variations in brain responses associated with task performance are systematic enough across subjects to define a pseudohierarchy of task-evoked networks. Such networks capture meaningful functional features of brain organization as shaped by a given cognitive context.

Ontology driven decision support for the diagnosis of mild cognitive impairment

In recent years, mild cognitive impairment (MCI) has attracted significant attention as an indicator of high risk for Alzheimer's disease (AD), and the diagnosis of MCI can alert patient to carry out appropriate strategies to prevent AD. To avoid subjectivity in diagnosis, we propose an ontology driven decision support method which is an automated procedure for diagnosing MCI through magnetic resonance imaging (MRI). In this approach, we encode specialized MRI knowledge into an ontology and construct a rule set using machine learning algorithms. Then we apply these two parts in conjunction with reasoning engine to automatically distinguish MCI patients from normal controls (NC). The rule set is trained by MRI data of 187 MCI patients and 177 normal controls selected from Alzheimer's Disease Neuroimaging Initiative (ADNI) using C4.5 algorithm. By using a 10-fold cross validation, we prove that the performance of C4.5 with 80.2% sensitivity is better than other algorithms, such as support vector machine (SVM), Bayesian network (BN) and back propagation (BP) neural networks, and C4.5 is suitable for the construction of reasoning rules. Meanwhile, the evaluation results suggest that our approach would be useful to assist physicians efficiently in real clinical diagnosis for the disease of MCI.

Dopamine precursor depletion impairs structure and efficiency of resting state brain functional networks

Spatial patterns of functional connectivity derived from resting brain activity may be used to elucidate the topological properties of brain networks. Such networks are amenable to study using graph theory, which shows that they possess small world properties and can be used to differentiate healthy subjects and patient populations. Of particular interest is the possibility that some of these differences are related to alterations in the dopamine system. To investigate the role of dopamine in the topological organization of brain networks at rest, we tested the effects of reducing dopamine synthesis in 13 healthy subjects undergoing functional magnetic resonance imaging. All subjects were scanned twice, in a resting state, following ingestion of one of two amino acid drinks in a randomized, double-blind manner. One drink was a nutritionally balanced amino acid mixture, and the other was tyrosine and phenylalanine deficient. Functional connectivity between 90 cortical and subcortical regions was estimated for each individual subject under each dopaminergic condition. The lowered dopamine state caused the following network changes: reduced global and local efficiency of the whole brain network, reduced regional efficiency in limbic areas, reduced modularity of brain networks, and greater connection between the normally anti-correlated task-positive and default-mode networks. We conclude that dopamine plays a role in maintaining the efficient small-world properties and high modularity of functional brain networks, and in segregating the task-positive and default-mode networks. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'.

Neuroanatomical correlates of musical transposition in adolescents: a longitudinal approach

Musicians are trained in melodic transposition, the skill of extracting the pitch interval structure (i.e., the frequency ratios between pitches) and moving it into different keys (i.e., different pitch levels). This ability to recognize whether a melody is the same or altered when it is played back in a different key is correlated with both greater neural activation and cortical thickness in bilateral intraparietal sulcus (IPS). Musical training only explains part of this finding, suggesting that the ability to transpose a melody may have innate predispositions. The current study was designed to address this question: are the anatomical correlates of musical transposition already present in non-musician children at 14 years of age? If so, is there any evidence that those traits were already in place at earlier ages? To answer this question, we recruited 47 adolescents (age 14.5 years) from a longitudinal study and tested them on a melodic transposition task. These adolescents had already undergone anatomical magnetic resonance imaging (MRI) at the ages of 10 (Time 1), 11.5 (Time 2), 13 (Time 3) years, as well as at age 14.5 years (Time 4) They were tested on the transposition task during Time-4 visit. During this visit, we found a relationship between cortical thickness in left IPS and performance on the transposed melody task in the girls and not the boys; no such relationship was observed at any of the earlier ages. Given that girls reach more advanced staged of pubertal maturation earlier than boys, it is possible that the relationship between cortical thickness in IPS and skill at melodic transposition only emerges once the brain has reached a certain degree of maturity. This claim is supported by a lack of similar sex differences in the adults: the degree of correlation between cortical thickness and performance on the same transposed melody task did not differ between men and women in a previous study. Taken together, our results suggest that the relationship between cortical thickness and the ability to transpose a melody is not fixed, and that the effects observed in adults are neither due exclusively to training nor to predisposition.

Cortical morphology in children with alcohol-related neurodevelopmental disorder

INTRODUCTION

It is well established that individuals exposed to alcohol in utero have reduced cortical grey matter volumes. However, the candidate determinants of these reductions, cortical thickness (CT) and surface area (SA), have not been investigated exclusively in alcohol-related neurodevelopmental disorder (ARND), the most prevalent fetal alcohol spectrum disorder subgroup that lacks the characteristic facial dysmorphology.

METHODS

T1-weighted magnetic resonance imaging scans were obtained from 88 participants (8-16 years), 36 diagnosed with ARND and 52 typically developing controls. Scans were submitted to the CIVET pipeline (version 1.1.10). Deformable models were used to construct the inner white matter surfaces and pial surfaces from which CT and SA measures were derived. Group differences in cortical volume, CT, and SA were computed using a general linear model covaried for age, sex, and handedness.

RESULTS

Global cortical volume reductions in ARND did not reflect CT, which did not differ between groups. Instead, volume decreases were consistent with global SA reductions in bilateral frontal and temporal as well as right occipital regions. Local reductions in SA were observed in the right superior temporal gyrus and the right occipital-temporal region.

CONCLUSION

Results suggest that in ARND, prenatal alcohol exposure perturbs global SA to a greater degree than CT, particularly in the right temporal lobe.

Association of a risk allele of ANK3 with cognitive performance and cortical thickness in patients with first-episode psychosis

BACKGROUND

The gene ANK3 is implicated in bipolar disorder and schizophrenia. The present study investigated the influence of this gene on cognitive performance and brain structure among individuals with first-episode psychosis (FEP). The brief illness duration of an FEP sample makes it well suited for studying the effects of genetic variation.

METHODS

We genotyped 2 single nucleotide polymorphisms (SNPs; rs1938526 and rs10994336) in ANK3 in patients with FEP. Multivariate analysis of variance compared risk allele carriers and noncarriers on 6 domains of cognition consistent with MATRICS consensus. A subsample of 82 patients was assessed using magnetic resonance imaging. We compared brain structure between carriers and noncarriers using cortical thickness analysis and voxel-based morphometry on white matter.

RESULTS

In the 173 patients with FEP included in our study, rs1938526 and rs10994336 were in very high linkage disequilibrium (d' = 0.95), and analyses were therefore only carried out on the SNP (rs1938526) with the highest minor allele frequency (G). Allele G of rs1938526, was associated with lower cognitive performance across domains (F6,164 = 2.38, p = 0.030) and significantly lower scores on the domains of verbal memory (p = 0.015), working memory (p = 0.006) and attention (p = 0.019). The significant effects of this SNP on cognition were not maintained when controlling for IQ. Cortical thinning was observed in risk allele carriers at diverse sites across cortical lobes bilaterally at a threshold of p < 0.01, false discovery rate-corrected. Risk-allele carriers did not show any regions of reduced white matter volume.

LIMITATIONS

The sample size is modest given that a low-frequency variant was being examined.

CONCLUSION

The ANK3 risk allele rs1938526 appears to be associated with general cognitive impairment and widespread cortical thinning in patients with FEP.

Central nervous system imaging in diabetic cerebrovascular diseases and white matter hyperintensities

Diabetes mellitus is an important vascular risk factor for cerebrovascular disease. This occurs through pathophysiologic changes to the microcirculation as arteriolosclerosis and to the macrocirculation as large artery atherosclerosis. Imaging techniques can provide detailed visualization of the cerebrovasculature using CT (computed tomography) angiography and MR (magnetic resonance) angiography. Newer techniques focused on advanced parenchymal imaging include CT perfusion, quantitative MRI, and diffusion tensor imaging; each identifies brain lesion burden due to diabetes mellitus. These imaging approaches have provided insights into the diabetes mellitus brain and cerebral circulation pathophysiology. Imaging has taught us that diabetics develop cerebral atrophy, silent infarcts, and white matter disease more rapidly than other patient populations. Longitudinal studies are needed to quantify the rate and extent of such structural brain and blood vessel changes and how they relate to cognitive decline. Diabetes prevention and treatment strategies will then be possible to slow the development of such changes.

SELF-SUPERVISED MRI TISSUE SEGMENTATION BY DISCRIMINATIVE CLUSTERING

The study of brain lesions can benefit from a clear identification of transitions between healthy and pathological tissues, through the analysis of brain imaging data. Current signal processing methods, able to address these issues, often rely on strong prior information. In this article, a new method for tissue segmentation is proposed. It is based on a discriminative strategy, in a self-supervised machine learning approach. This method avoids the use of prior information, which makes it very versatile, and able to cope with different tissue types. It also returns tissue probabilities for each voxel, crucial for a good characterization of the evolution of brain lesions. Simulated as well as real benchmark data were used to validate the accuracy of the method and compare it against other segmentation algorithms.

Neuroanatomical heterogeneity of essential tremor according to propranolol response

BACKGROUND

Recent studies have suggested that essential tremor (ET) is a more complex and heterogeneous clinical entity than initially thought. In the present study, we assessed the pattern of cortical thickness and diffusion tensor white matter (WM) changes in patients with ET according to the response to propranolol to explore the pathogenesis underlying the clinical heterogeneity of ET.

METHODS

A total of 32 patients with drug naive ET were recruited prospectively from the Movement Disorders outpatient clinic. The patients were divided into a propranolol-responder group (n = 18) and a non-responder group (n = 14). We analyzed the pattern of cortical thickness and diffusion tensor WM changes between these two groups and performed correlation analysis between imaging and clinical parameters.

RESULTS

There were no significant differences in demographic characteristics, general cognition, or results of detailed neuropsychological tests between the groups. The non-responder group showed more severe cortical atrophy in the left orbitofrontal cortex and right temporal cortex relative to responders. However, the responders exhibited significantly lower fractional anisotropy values in the bilateral frontal, corpus callosal, and right parietotemporal WM compared with the non-responder group. There were no significant clusters where the cortical thickness or WM alterations were significantly correlated with initial tremor severity or disease duration.

CONCLUSIONS

The present data suggest that patients with ET have heterogeneous cortical thinning and WM alteration with respect to responsiveness to propranolol, suggesting that propranolol responsiveness may be a predictive factor to determine ET subtypes in terms of neuroanatomical heterogeneity.

Network efficiency in autism spectrum disorder and its relation to brain overgrowth

A substantial body of evidence links differences in brain size to differences in brain organization. We have hypothesized that the developmental aspect of this relation plays a role in autism spectrum disorder (ASD), a neurodevelopmental disorder which involves abnormalities in brain growth. Children with ASD have abnormally large brains by the second year of life, and for several years thereafter their brain size can be multiple standard deviations above the norm. The greater conduction delays and cellular costs presumably associated with the longer long-distance connections in these larger brains is thought to influence developmental processes, giving rise to an altered brain organization with less communication between spatially distant regions. This has been supported by computational models and by findings linking greater intra-cranial volume, an index of maximum brain-size during development, to reduced inter-hemispheric connectivity in individuals with ASD. In this paper, we further assess this hypothesis via a whole-brain analysis of network efficiency. We utilize diffusion tractography to estimate the strength and length of the connections between all pairs of cortical regions. We compute the efficiency of communication between each network node and all others, and within local neighborhoods; we then assess the relation of these measures to intra-cranial volume, and the differences in these measures between adults with autism and typical controls. Intra-cranial volume is shown to be inversely related to efficiency for wide-spread regions of cortex. Moreover, the spatial patterns of reductions in efficiency in autism bear a striking resemblance to the regional relationships between efficiency and intra-cranial volume, particularly for local efficiency. The results thus provide further support for the hypothesized link between brain overgrowth in children with autism and the efficiency of the organization of the brain in adults with autism.

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

Trajectories of cerebral cortical development in childhood and adolescence and adult attention-deficit/hyperactivity disorder

BACKGROUND

Childhood attention-deficit/hyperactivity disorder (ADHD) persists into adulthood in around half of those affected, constituting a major public health challenge. No known demographic, clinical, or neuropsychological factors robustly explain the clinical course, directing our focus to the brain. Herein, we link the trajectories of cerebral cortical development during childhood and adolescence with the severity of adult ADHD.

METHODS

Using a longitudinal study design, 92 participants with ADHD had childhood (mean 10.7 years, SD 3.3) and adult clinical assessments (mean 23.8 years, SD 4.3) with repeated neuroanatomic magnetic resonance imaging. Contrast was made against 184 matched typically developing volunteers.

RESULTS

Attention-deficit/hyperactivity disorder persisted in 37 (40%) subjects and adult symptom severity was linked to cortical trajectories. Specifically, as the number of adult symptoms increased, particularly inattentive symptoms, so did the rate of cortical thinning in the medial and dorsolateral prefrontal cortex. For each increase of one symptom of adult ADHD, the rate of cortical thinning increased by .0018 mm (SE = .0004, t = 4.2, p < .0001), representing a 5.6% change over the mean rate of thinning for the entire group. These differing trajectories resulted in a convergence toward typical dimensions among those who remitted and a fixed, nonprogressive deficit in persistent ADHD. Notably, cortical thickening or minimal thinning (greater than -.007 mm/year) was found exclusively among individuals who remitted.

CONCLUSIONS

Adult ADHD status is linked with the developmental trajectories of cortical components of networks supporting attention, cognitive control, and the default mode network. This informs our understanding of the developmental pathways to adult ADHD.

Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state

The effect of regressing out the global average signal (GAS) in resting state fMRI data has become a concern for interpreting functional connectivity analyses. It is not clear whether the reported anti-correlations between the Default Mode and the Dorsal Attention Networks are intrinsic to the brain, or are artificially created by regressing out the GAS. Here we introduce a concept, Impact of the Global Average on Functional Connectivity (IGAFC), for quantifying the sensitivity of seed-based correlation analyses to the regression of the GAS. This voxel-wise IGAFC index is defined as the product of two correlation coefficients: the correlation between the GAS and the fMRI time course of a voxel, times the correlation between the GAS and the seed time course. This definition enables the calculation of a threshold at which the impact of regressing-out the GAS would be large enough to introduce spurious negative correlations. It also yields a post-hoc impact correction procedure via thresholding, which eliminates spurious correlations introduced by regressing out the GAS. In addition, we introduce an Artificial Negative Correlation Index (ANCI), defined as the absolute difference between the IGAFC index and the impact threshold. The ANCI allows a graded confidence scale for ranking voxels according to their likelihood of showing artificial correlations. By applying this method, we observed regions in the Default Mode and Dorsal Attention Networks that were anti-correlated. These findings confirm that the previously reported negative correlations between the Dorsal Attention and Default Mode Networks are intrinsic to the brain and not the result of statistical manipulations. Our proposed quantification of the impact that a confound may have on functional connectivity can be generalized to global effect estimators other than the GAS. It can be readily applied to other confounds, such as systemic physiological or head movement interferences, in order to quantify their impact on functional connectivity in the resting state.

Improved inference in Bayesian segmentation using Monte Carlo sampling: application to hippocampal subfield volumetry

Many segmentation algorithms in medical image analysis use Bayesian modeling to augment local image appearance with prior anatomical knowledge. Such methods often contain a large number of free parameters that are first estimated and then kept fixed during the actual segmentation process. However, a faithful Bayesian analysis would marginalize over such parameters, accounting for their uncertainty by considering all possible values they may take. Here we propose to incorporate this uncertainty into Bayesian segmentation methods in order to improve the inference process. In particular, we approximate the required marginalization over model parameters using computationally efficient Markov chain Monte Carlo techniques. We illustrate the proposed approach using a recently developed Bayesian method for the segmentation of hippocampal subfields in brain MRI scans, showing a significant improvement in an Alzheimer's disease classification task. As an additional benefit, the technique also allows one to compute informative "error bars" on the volume estimates of individual structures.

Interactive effects of dehydroepiandrosterone and testosterone on cortical thickness during early brain development

Humans and the great apes are the only species demonstrated to exhibit adrenarche, a key endocrine event associated with prepubertal increases in the adrenal production of androgens, most significantly dehydroepiandrosterone (DHEA) and to a certain degree testosterone. Adrenarche also coincides with the emergence of the prosocial and neurobehavioral skills of middle childhood and may therefore represent a human-specific stage of development. Both DHEA and testosterone have been reported in animal and in vitro studies to enhance neuronal survival and programmed cell death depending on the timing, dose, and hormonal context involved, and to potentially compete for the same signaling pathways. Yet no extant brain-hormone studies have examined the interaction between DHEA- and testosterone-related cortical maturation in humans. Here, we used linear mixed models to examine changes in cortical thickness associated with salivary DHEA and testosterone levels in a longitudinal sample of developmentally healthy children and adolescents 4-22 years old. DHEA levels were associated with increases in cortical thickness of the left dorsolateral prefrontal cortex, right temporoparietal junction, right premotor and right entorhinal cortex between the ages of 4-13 years, a period marked by the androgenic changes of adrenarche. There was also an interaction between DHEA and testosterone on cortical thickness of the right cingulate cortex and occipital pole that was most significant in prepubertal subjects. DHEA and testosterone appear to interact and modulate the complex process of cortical maturation during middle childhood, consistent with evidence at the molecular level of fast/nongenomic and slow/genomic or conversion-based mechanisms underlying androgen-related brain development.

Reduced cortical thickness in primary open-angle glaucoma and its relationship to the retinal nerve fiber layer thickness

OBJECTIVES

To examine possible changes in cortical thickness and their relationship to retinal nerve fiber layer (RNFL) thickness in patients with primary open-angle glaucoma (POAG).

MATERIALS AND METHODS

Thirty-six patients with POAG and 40 matched healthy controls were enrolled in this study. All subjects underwent a comprehensive ophthalmologic examination and a high resolution structural magnetic resonance scan. Cortical thickness analysis was used to assess the changes between patients and controls. Correlations between the thickness of the visual cortex and RNFL thickness were also analyzed. Finally, the relationship between the severity of changes in the visual cortex and RNFL thickness was evaluated by comparing patients with mild and severe groups.

RESULTS

POAG patients showed significant bilateral cortical thinning in the anterior half of the visual cortex around the calcarine sulci (left BA 17 and BA 18, right BA17) and in some smaller regions located in the left middle temporal gyrus (BA37) and fusiform gyrus (BA19). The thickness of the visual cortex correlated positively with RNFL thickness (left, r = 0.44, p = 0.01; right, r = 0.38, p = 0.03). Significant differences between mild and severe groups were observed with regard to both RNFL thickness and the thickness of bilateral visual cortex (p < 0.05).

CONCLUSION

Our findings indicate that cortical thickness analysis may be sufficiently sensitive to detect cortical alterations in POAG and that the measurement has great potential for clinical application.

Temporally consistent probabilistic detection of new multiple sclerosis lesions in brain MRI

Detection of new Multiple Sclerosis (MS) lesions on magnetic resonance imaging (MRI) is important as a marker of disease activity and as a potential surrogate for relapses. We propose an approach where sequential scans are jointly segmented, to provide a temporally consistent tissue segmentation while remaining sensitive to newly appearing lesions. The method uses a two-stage classification process: 1) a Bayesian classifier provides a probabilistic brain tissue classification at each voxel of reference and follow-up scans, and 2) a random-forest based lesion-level classification provides a final identification of new lesions. Generative models are learned based on 364 scans from 95 subjects from a multi-center clinical trial. The method is evaluated on sequential brain MRI of 160 subjects from a separate multi-center clinical trial, and is compared to 1) semi-automatically generated ground truth segmentations and 2) fully manual identification of new lesions generated independently by nine expert raters on a subset of 60 subjects. For new lesions greater than 0.15 cc in size, the classifier has near perfect performance (99% sensitivity, 2% false detection rate), as compared to ground truth. The proposed method was also shown to exceed the performance of any one of the nine expert manual identifications.

Localized cortical thinning in patients with obstructive sleep apnea syndrome

STUDY OBJECTIVES

To investigate differences in cortical thickness in patients with obstructive sleep apnea (OSA) syndrome and healthy controls.

DESIGN

Cortical thickness was measured using a three-dimensional surface-based method that enabled more accurate measurement in deep sulci and localized regional mapping.

SETTING

University hospital.

PATIENTS

Thirty-eight male patients with severe OSA (mean apnea-hypopnea index > 30/h) and 36 age-matched male healthy controls were enrolled.

INTERVENTIONS

Cortical thickness was obtained at 81,924 vertices across the entire brain by reconstructing inner and outer cortical surfaces using an automated anatomical pipeline.

MEASUREMENTS

Group difference in cortical thickness and correlation between patients' data and thickness were analyzed by a general linear model.

RESULTS

Localized cortical thinning in patients was found in the orbitorectal gyri, dorsolateral/ventromedial prefrontal regions, pericentral gyri, anterior cingulate, insula, inferior parietal lobule, uncus, and basolateral temporal regions at corrected P < 0.05. Patients with OSA showed impaired attention and learning difficulty in memory tests compared to healthy controls. Higher number of respiratory arousals was related to cortical thinning of the anterior cingulate and inferior parietal lobule. A significant correlation was observed between the longer apnea maximum duration and the cortical thinning of the dorsolateral prefrontal regions, pericentral gyri, and insula. Retention scores in visual memory tests were associated with cortical thickness of parahippocampal gyrus and uncus.

CONCLUSIONS

Brain regions with cortical thinning may provide elucidations for prefrontal cognitive dysfunction, upper airway sensorimotor dysregulation, and cardiovascular disturbances in OSA patients, that experience sleep disruption including sleep fragmentation and oxygen desaturation.

Dimensionality reduced cortical features and their use in predicting longitudinal changes in Alzheimer's disease

Neuroimaging features derived from the cortical surface provide important information in detecting changes related to the progression of Alzheimer's disease (AD). Recent widespread adoption of neuroimaging has allowed researchers to study longitudinal data in AD. We adopted cortical thickness and sulcal depth, parameterized by three-dimensional meshes, from magnetic resonance imaging as the surface features. The cortical feature is high-dimensional, and it is difficult to use directly with a classifier because of the "small sample size" problem. We applied manifold learning to reduce the dimensionality of the feature and then tested the usage of the dimensionality reduced feature with a support vector machine classifier. Principal component analysis (PCA) was chosen as the method of manifold learning. PCA was applied to a region of interest within the cortical surface. We used 30 normal, 30 mild cognitive impairment (MCI) and 12 conversion cases taken from the ADNI database. The classifier was trained using the cortical features extracted from normal and MCI patients. The classifier was tested for the 12 conversion patients only using the imaging data before the actual conversion. The conversion was predicted early with an accuracy of 83%.

Increasing the contrast of the brain MR FLAIR images using fuzzy membership functions and structural similarity indices in order to segment MS lesions

Segmentation is an important step for the diagnosis of multiple sclerosis (MS). This paper presents a new approach to the fully automatic segmentation of MS lesions in Fluid Attenuated Inversion Recovery (FLAIR) Magnetic Resonance (MR) images. With the aim of increasing the contrast of the FLAIR MR images with respect to the MS lesions, the proposed method first estimates the fuzzy memberships of brain tissues (i.e., the cerebrospinal fluid (CSF), the normal-appearing brain tissue (NABT), and the lesion). The procedure for determining the fuzzy regions of their member functions is performed by maximizing fuzzy entropy through Genetic Algorithm. Research shows that the intersection points of the obtained membership functions are not accurate enough to segment brain tissues. Then, by extracting the structural similarity (SSIM) indices between the FLAIR MR image and its lesions membership image, a new contrast-enhanced image is created in which MS lesions have high contrast against other tissues. Finally, the new contrast-enhanced image is used to segment MS lesions. To evaluate the result of the proposed method, similarity criteria from all slices from 20 MS patients are calculated and compared with other methods, which include manual segmentation. The volume of segmented lesions is also computed and compared with Gold standard using the Intraclass Correlation Coefficient (ICC) and paired samples t test. Similarity index for the patients with small lesion load, moderate lesion load and large lesion load was 0.7261, 0.7745 and 0.8231, respectively. The average overall similarity index for all patients is 0.7649. The t test result indicates that there is no statistically significant difference between the automatic and manual segmentation. The validated results show that this approach is very promising.

The effect of diagnosis, age, and symptom severity on cortical surface area in the cingulate cortex and insula in autism spectrum disorders

Functional activity in the anterior cingulate cortex and insula has been reported to be abnormal during social tasks in autism spectrum disorders. However, few studies have examined surface morphometry in these regions and how this may be related to autism spectrum disorder symptomatology. In this study, 27 individuals with autism spectrum disorders and 25 controls between the ages of 7 to 39 years underwent structural magnetic resonance imaging. Our primary analysis examined differences in surface area in the cingulate and insula, between individuals with and without autism spectrum disorders, as well as age-related changes and associations with social impairments. Surface area in the right cingulate was significantly different between groups and decreased more rapidly with age in autism spectrum disorder participants. In addition, greater surface area in the insula and isthmus was associated with poorer social behaviors. Results suggest atypical surface morphometry in brain regions involved in social function, which appeared to be related to poorer social ability scores.

Workflow efficiency of two 1.5 T MR scanners with and without an automated user interface for head examinations

RATIONALE AND OBJECTIVES

Workflow efficiency and workload of radiological technologists (RTs) were compared in head examinations performed with two 1.5 T magnetic resonance (MR) scanners equipped with or without an automated user interface called "day optimizing throughput" (Dot) workflow engine.

MATERIALS AND METHODS

Thirty-four patients with known intracranial pathology were examined with a 1.5 T MR scanner with Dot workflow engine (Siemens MAGNETOM Aera) and with a 1.5 T MR scanner with conventional user interface (Siemens MAGNETOM Avanto) using four standardized examination protocols. The elapsed time for all necessary work steps, which were performed by 11 RTs within the total examination time, was compared for each examination at both MR scanners. The RTs evaluated the user-friendliness of both scanners by a questionnaire. Normality of distribution was checked for all continuous variables by use of the Shapiro-Wilk test. Normally distributed variables were analyzed by Student's paired t-test, otherwise Wilcoxon signed-rank test was used to compare means.

RESULTS

Total examination time of MR examinations performed with Dot engine was reduced from 24:53 to 20:01 minutes (P < .001) and the necessary RT intervention decreased by 61% (P < .001). The Dot engine's automated choice of MR protocols was significantly better assessed by the RTs than the conventional user interface (P = .001).

CONCLUSIONS

According to this preliminary study, the Dot workflow engine is a time-saving user assistance software, which decreases the RTs' effort significantly and may help to automate neuroradiological examinations for a higher workflow efficiency.

Insular cortex mediates increased pain tolerance in yoga practitioners

Yoga, an increasingly popular discipline among Westerners, is frequently used to improve painful conditions. We investigated possible neuroanatomical underpinnings of the beneficial effects of yoga using sensory testing and magnetic resonance imaging techniques. North American yogis tolerated pain more than twice as long as individually matched controls and had more gray matter (GM) in multiple brain regions. Across subjects, insular GM uniquely correlated with pain tolerance. Insular GM volume in yogis positively correlated with yoga experience, suggesting a causal relationship between yoga and insular size. Yogis also had increased left intrainsular white matter integrity, consistent with a strengthened insular integration of nociceptive input and parasympathetic autonomic regulation. Yogis, as opposed to controls, used cognitive strategies involving parasympathetic activation and interoceptive awareness to tolerate pain, which could have led to use-dependent hypertrophy of insular cortex. Together, these findings suggest that regular and long-term yoga practice improves pain tolerance in typical North Americans by teaching different ways to deal with sensory inputs and the potential emotional reactions attached to those inputs leading to a change in insular brain anatomy and connectivity.

Self-injurious behaviours are associated with alterations in the somatosensory system in children with autism spectrum disorder

Children with autism spectrum disorder (ASD) frequently engage in self-injurious behaviours, often in the absence of reporting pain. Previous research suggests that altered pain sensitivity and repeated exposure to noxious stimuli are associated with morphological changes in somatosensory and limbic cortices. Further evidence from postmortem studies with self-injurious adults has indicated alterations in the structure and organization of the temporal lobes; however, the effect of self-injurious behaviour on cortical development in children with ASD has not yet been determined. Thirty children and adolescents (mean age = 10.6 ± 2.5 years; range 7-15 years; 29 males) with a clinical diagnosis of ASD and 30 typically developing children (N = 30, mean age = 10.7 ± 2.5 years; range 7-15 years, 26 males) underwent T1-weighted magnetic resonance and diffusion tensor imaging. No between-group differences were seen in cerebral volume, surface area or cortical thickness. Within the ASD group, self-injury scores negatively correlated with thickness in the right superior parietal lobule t = 6.3, p < 0.0001, bilateral primary somatosensory cortices (SI) (right: t = 4.4, p = 0.02; left: t = 4.48, p = 0.004) and the volume of the left ventroposterior (VP) nucleus of the thalamus (r = -0.52, p = 0.008). Based on these findings, we performed an atlas-based region-of-interest diffusion tensor imaging analysis between SI and the VP nucleus and found that children who engaged in self-injury had significantly lower fractional anisotropy (r = -0.4, p = 0.04) and higher mean diffusivity (r = 0.5, p = 0.03) values in the territory of the left posterior limb of the internal capsule. Additionally, greater incidence of self-injury was associated with increased radial diffusivity values in bilateral posterior limbs of the internal capsule (left: r = 0.5, p = 0.02; right: r = 0.5, p = 0.009) and corona radiata (left: r = 0.6, p = 0.005; right: r = 0.5, p = 0.009). Results indicate that self-injury is related to alterations in somatosensory cortical and subcortical regions and their supporting white-matter pathways. Findings could reflect use-dependent plasticity in the somatosensory system or disrupted brain development that could serve as a risk marker for self-injury.

Simultaneous analysis and quality assurance for diffusion tensor imaging

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible.

The genome-wide supported microRNA-137 variant predicts phenotypic heterogeneity within schizophrenia

We examined the influence of the genome-wide significant schizophrenia risk variant rs1625579 near the microRNA (miRNA)-137 (MIR137) gene on well-established sources of phenotypic variability in schizophrenia: age-at-onset of psychosis and brain structure. We found that the MIR137 risk genotype strongly predicts an earlier age-at-onset of psychosis across four independently collected samples of patients with schizophrenia (n=510; F1,506=17.7, P=3.1 × 10(-5)). In an imaging-genetics subsample that included additional matched controls (n=213), patients with schizophrenia who had the MIR137 risk genotype had reduced white matter integrity (F3,209=13.6, P=3.88 × 10(-8)) throughout the brain as well as smaller hippocampi and larger lateral ventricles; the brain structure of patients who were carriers of the protective allele was no different from healthy control subjects on these neuroimaging measures. Our findings suggest that MIR137 substantially influences variation in phenotypes that are thought to have an important role in clinical outcome and treatment response. Finally, the possible consequences of genetic risk factors may be distinct in patients with schizophrenia compared with healthy controls.

Anterior cingulate cortical thickness is a stable predictor of recovery from post-traumatic stress disorder

BACKGROUND

Decreased cortical thickness in frontal and temporal regions has been observed in individuals suffering from post-traumatic stress disorder (PTSD), compared to healthy controls and trauma-exposed participants without PTSD. In addition, individual differences, both functional and structural, in the anterior cingulate cortex (ACC) have been shown to predict symptom severity reduction. Although there is some evidence suggesting that activity in this region changes as a function of recovery, it remains unknown whether there are any structural correlates of recovery from PTSD.

METHOD

Thirty participants suffering from moderate to severe PTSD underwent a magnetic resonance imaging (MRI) scan following an initial clinical assessment. A second assessment took place 6-9 months later. In addition, a subgroup of 25 participants completed a second MRI scan at that time. PTSD symptom severity changes over time were regressed against vertex-based cortical thickness.

RESULTS

We found that cortical thickness in the right subgenual ACC (sgACC) predicted symptom improvement. Moreover, cortical thickness within this region of the ACC, measured 6-9 months later (n = 25), was also correlated with the same measure of symptom improvement. By contrast, no relationship was found between change in cortical thickness in this area and current PTSD symptom levels or degree of recovery.

CONCLUSIONS

Our results suggest that sgACC thickness may be a stable marker of recovery potential in PTSD.

Atrial fibrillation is associated with reduced brain volume and cognitive function independent of cerebral infarcts

BACKGROUND AND PURPOSE

Atrial fibrillation (AF) has been associated with cognitive decline independent of stroke, suggesting additional effects of AF on the brain. We aimed to assess the association between AF and brain function and structure in a general elderly population.

METHODS

This is a cross-sectional analysis of 4251 nondemented participants (mean age, 76 ± 5 years) in the population-based Age, Gene/Environment Susceptibility-Reykjavik Study. Medical record data were collected for the presence, subtype, and time from first diagnosis of AF; 330 participants had AF. Brain volume measurements, adjusted for intracranial volume, and presence of cerebral infarcts were determined with magnetic resonance imaging. Memory, speed of processing, and executive function composites were calculated from a cognitive test battery. In a multivariable linear regression model, adjustments were made for demographic factors, cardiovascular risk factors, and cerebral infarcts.

RESULTS

Participants with AF had lower total brain volume compared with those without AF (P<0.001). The association was stronger with persistent/permanent than paroxysmal AF and with increased time from the first diagnosis of the disease. Of the brain tissue volumes, AF was associated with lower volume of gray and white matter hyperintensities (P<0.001 and P = 0.008, respectively), but not of white matter hyperintensities (P = 0.49). Participants with AF scored lower on tests of memory.

CONCLUSIONS

AF is associated with smaller brain volume, and the association is stronger with increasing burden of the arrhythmia. These findings suggest that AF has a cumulative negative effect on the brain independent of cerebral infarcts.

Spatial navigational strategies correlate with gray matter in the hippocampus of healthy older adults tested in a virtual maze

Healthy young adults use different strategies when navigating in a virtual maze. Spatial strategies involve using environmental landmarks while response strategies involve executing a series of movements from specific stimuli. Neuroimaging studies previously confirmed that people who use spatial strategies show increased activity and gray matter in the hippocampus, while those who use response strategies show increased activity and gray matter in caudate nucleus (Iaria et al., 2003; Bohbot et al., 2007). A growing number of studies report that cognitive decline that occurs with normal aging is correlated with a decrease in volume of the hippocampus. Here, we used voxel-based morphometry (VBM) to examine whether spatial strategies in aging are correlated with greater gray matter in the hippocampus, as found in our previous study with healthy young participants. Forty-five healthy older adults were tested on a virtual navigation task that allows spatial and response strategies. All participants learn the task to criterion after which a special “probe” trial that assesses spatial and response strategies is given. Results show that spontaneous spatial memory strategies, and not performance on the navigation task, positively correlate with gray matter in the hippocampus. Since numerous studies have shown that a decrease in the volume of the hippocampus correlates with cognitive deficits during normal aging and increases the risks of ensuing dementia, the current results suggest that older people who use their spatial memory strategies in their everyday lives may have increased gray matter in the hippocampus and enhance their probability of healthy and successful aging.

A comprehensive approach to the segmentation of multichannel three-dimensional MR brain images in multiple sclerosis

Accurate classification and quantification of brain tissues is important for monitoring disease progression, measurement of atrophy, and correlating magnetic resonance (MR) measures with clinical disability. Classification of MR brain images in the presence of lesions, such as multiple sclerosis (MS), is particularly challenging. Images obtained with lower resolution often suffer from partial volume averaging leading to false classifications. While partial volume averaging can be reduced by acquiring volumetric images at high resolution, image segmentation and quantification can be technically challenging. In this study, we integrated the brain anatomical knowledge with non-parametric and parametric statistical classifiers for automatically classifying tissues and lesions on high resolution multichannel three-dimensional images acquired on 60 MS brains. The results of automatic lesion segmentation were reviewed by the expert. The agreement between results obtained by the automated analysis and the expert was excellent as assessed by the quantitative metrics, low absolute volume difference percent (36.18 ± 34.90), low average symmetric surface distance (1.64 mm ± 1.30 mm), high true positive rate (84.75 ± 12.69), and low false positive rate (34.10 ± 16.00). The segmented results were also in close agreement with the corrected results as assessed by Bland-Altman and regression analyses. Finally, our lesion segmentation was validated using the MS lesion segmentation grand challenge dataset (MICCAI 2008).

Evidence for a cerebral cortical thickness network anti-correlated with amygdalar volume in healthy youths: implications for the neural substrates of emotion regulation

Recent functional connectivity studies have demonstrated that, in resting humans, activity in a dorsally-situated neocortical network is inversely associated with activity in the amygdalae. Similarly, in human neuroimaging studies, aspects of emotion regulation have been associated with increased activity in dorsolateral, dorsomedial, orbital and ventromedial prefrontal regions, as well as concomitant decreases in amygdalar activity. These findings indicate the presence of two countervailing systems in the human brain that are reciprocally related: a dorsally-situated cognitive control network, and a ventrally-situated limbic network. We investigated the extent to which this functional reciprocity between limbic and dorsal neocortical regions is recapitulated from a purely structural standpoint. Specifically, we hypothesized that amygdalar volume would be related to cerebral cortical thickness in cortical regions implicated in aspects of emotion regulation. In 297 typically developing youths (162 females, 135 males; 572 MRIs), the relationship between cortical thickness and amygdalar volume was characterized. Amygdalar volume was found to be inversely associated with thickness in bilateral dorsolateral and dorsomedial prefrontal, inferior parietal, as well as bilateral orbital and ventromedial prefrontal cortices. Our findings are in line with previous work demonstrating that a predominantly dorsally-centered neocortical network is reciprocally related to core limbic structures such as the amygdalae. Future research may benefit from investigating the extent to which such cortical-limbic morphometric relations are qualified by the presence of mood and anxiety psychopathology.

Brain morphological abnormalities in 49,XXXXY syndrome: A pediatric magnetic resonance imaging study

As a group, people with the sex chromosome aneuploidy 49,XXXXY have characteristic physical and cognitive/behavioral tendencies, although there is high individual variation. In this study we use magnetic resonance imaging (MRI) to examine brain morphometry in 14 youth with 49,XXXXY compared to 42 age-matched healthy controls. Total brain size was significantly smaller (t=9.0, p<.001), and rates of brain abnormalities such as colpocephaly, plagiocephaly, periventricular cysts, and minor craniofacial abnormalities were significantly increased. White matter lesions were identified in 50% of subjects, supporting the inclusion of 49,XXXXY in the differential diagnosis of small multifocal white matter lesions. Further evidence of abnormal development of white matter was provided by the smaller cross sectional area of the corpus callosum. These results suggest that increased dosage of genes on the X chromosome has adverse effects on white matter development.

Effects of age and symptomatology on cortical thickness in autism spectrum disorders

Several brain regions show structural and functional abnormalities in individuals with autism spectrum disorders (ASD), but the developmental trajectory of abnormalities in these structures and how they may relate to social and communicative impairments are still unclear. We assessed the effects of age on cortical thickness in individuals with ASD, between the ages of 7 and 39 years in comparison to typically developing controls. Additionally, we examined differences in cortical thickness in relation to symptomatology in the ASD group, and their association with age. Analyses were conducted using a general linear model, controlling for sex. Social and communication scores from the Autism Diagnostic Interview-Revised (ADI-R) were correlated with the thickness of regions implicated in those functions. Controls showed widespread cortical thinning relative to the ASD group. Within regions-of-interest, increased thickness in the rostral anterior cingulate cortex was associated with poorer social scores. Additionally, a significant interaction between age and social impairment was found in the orbitofrontal cortex, with more impaired younger children having decreased thickness in this region. These results suggest that differential neurodevelopmental trajectories are present in individuals with ASD and some differences are associated with diagnostic behaviours.

Lack of gender influence on cortical and subcortical gray matter development in childhood-onset schizophrenia

BACKGROUND

Progressive cortical gray matter (GM) abnormalities are an established feature of schizophrenia and are more pronounced in rare, severe, and treatment refractory childhood-onset schizophrenia (COS) cases. The effect of sex on brain development in schizophrenia is poorly understood and studies to date have produced inconsistent results.

METHODS

Using the largest to date longitudinal sample of COS cases (n = 104, scans = 249, Male/Female [M/F] = 57/47), we compared COS sex differences with sex differences in a sample of matched typically developing children (n = 104, scans = 244, M/F = 57/47), to determine whether or not sex had differential effects on cortical and subcortical brain development in COS.

RESULTS

Our results showed no significant differential sex effects in COS for either GM cortical thickness or subcortical volume development (sex × diagnosis × age interaction; false discovery rate q = 0.05).

CONCLUSION

Sex appears to play a similar role in cortical and subcortical GM development in COS as it does in normally developing children.

Verbal memory is associated with structural hippocampal changes in newly diagnosed Parkinson's disease

BACKGROUND AND OBJECTIVE

Cognitive impairment, including impairment of episodic memory, is frequently found in newly diagnosed Parkinson's disease (PD). In this longitudinal observational study we investigated whether performance in memory encoding, retention, recognition and free recall is associated with reduced hippocampal radial distance.

METHODS

We analysed baseline T1-weighted brain MRI data from 114 PD subjects without cognitive impairment, 29 PD subjects with mild cognitive impairment and 99 normal controls from the ParkWest study. Age- and education-predicted scores for the California Verbal Learning Test 2 (CVLT-2) and tests of executive function were regressed against hippocampal radial distance while adjusting for imaging centre.

RESULTS

There was no association between encoding or performance on executive tests and hippocampal atrophy in the PD group. In the full PD sample we found bilaterally significant associations between lower delayed free recall scores and hippocampal atrophy in the CA1, CA3 and subiculum area (left, p=0.0013; right, p=0.0082). CVLT-2 short delay free recall scores were associated with bilateral hippocampal CA1 and subicular atrophy in the full PD sample (left, p=0.013; right, p=0.047). CVLT-2 recognition scores showed a significant association with right-sided subicular and CA1 atrophy in the full PD sample (p=0.043).

CONCLUSIONS

At the time of PD diagnosis, subjects' verbal memory performance in recall and recognition are associated with atrophy of the hippocampus, while encoding is not associated with hippocampal radial distance. We postulate that impaired recall and recognition might reflect deficient memory consolidation at least partly due to structural hippocampal changes.

Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis

Focal lesions and brain atrophy are the most extensively studied aspects of multiple sclerosis (MS), but the image acquisition and analysis techniques used can be further improved, especially those for studying within-patient changes of lesion load and atrophy longitudinally. Improved accuracy and sensitivity will reduce the numbers of patients required to detect a given treatment effect in a trial, and ultimately, will allow reliable characterization of individual patients for personalized treatment. Based on open issues in the field of MS research, and the current state of the art in magnetic resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations to improve these measures for longitudinal studies of MS. Briefly, they are (1) images should be acquired using 3D pulse sequences, with near-isotropic spatial resolution and multiple image contrasts to allow more comprehensive analyses of lesion load and atrophy, across timepoints. Image artifacts need special attention given their effects on image analysis results. (2) Automated image segmentation methods integrating the assessment of lesion load and atrophy are desirable. (3) A standard dataset with benchmark results should be set up to facilitate development, calibration, and objective evaluation of image analysis methods for MS.

Anatomical substrates of the alerting, orienting and executive control components of attention: focus on the posterior parietal lobe

Both neuropsychological and functional neuroimaging studies have identified that the posterior parietal lobe (PPL) is critical for the attention function. However, the unique role of distinct parietal cortical subregions and their underlying white matter (WM) remains in question. In this study, we collected both magnetic resonance imaging and diffusion tensor imaging (DTI) data in normal participants, and evaluated their attention performance using attention network test (ANT), which could isolate three different attention components: alerting, orienting and executive control. Cortical thickness, surface area and DTI parameters were extracted from predefined PPL subregions and correlated with behavioural performance. Tract-based spatial statistics (TBSS) was used for the voxel-wise statistical analysis. Results indicated structure-behaviour relationships on multiple levels. First, a link between the cortical thickness and WM integrity of the right inferior parietal regions and orienting performance was observed. Specifically, probabilistic tractography demonstrated that the integrity of WM connectivity between the bilateral inferior parietal lobules mediated the orienting performance. Second, the scores of executive control were significantly associated with the WM diffusion metrics of the right supramarginal gyrus. Finally, TBSS analysis revealed that alerting performance was significant correlated with the fractional anisotropy of local WM connecting the right thalamus and supplementary motor area. We conclude that distinct areas and features within PPL are associated with different components of attention. These findings could yield a more complete understanding of the nature of the PPL contribution to visuospatial attention.