OBJECTIVE: We examined the white-matter microstructure of the left arcuate fasciculus, which has been associated with reading ability, in beginning readers with or without reading disability.
METHOD: Groups were typically reading children (n = 26) or children with reading disability (n = 26), Ages 6-9, and equated on nonverbal cognitive abilities. Diffusion-weighted images were collected and TRACULA was used to extract fractional anisotropy measures from the left arcuate fasciculus.
RESULTS: White-matter microstructure was altered in children with reading disability, who exhibited significantly reduced fractional anisotropy in the left arcuate fasciculus. Among typically reading children, lower fractional anisotropy of the left arcuate fasciculus was associated with superior pseudoword reading performance. Both the group differences and variation in reading scores among the children with reading disability were associated with radial diffusivity (but not axial diffusivity), whereas variation in reading scores among typically reading children was associated with axial diffusivity (but not radial diffusivity).
CONCLUSIONS: The paradoxical findings that lower fractional anisotropy was associated both with reading disability and also with better phonological awareness in typical reading development suggest that there are different maturational trajectories of white-matter microstructure in typical readers and children with reading disability, and that this difference is unique to the beginning stages of reading acquisition. The finding that reading disability was associated with radial diffusivity, but that variation in ability among typically developing readers was associated with axial diffusivity, suggests that different neural mechanisms may be associated with reading development in children with or without reading disability. (PsycINFO Database Record
Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging.
We consider the problem of reconstructing white-matter pathways in a longitudinal study, where diffusion-weighted and T1-weighted MR images have been acquired at multiple time points for the same subject. We propose a method for joint reconstruction of a subject's pathways at all time points given the subject's entire set of longitudinal data. We apply a method for unbiased within-subject registration to generate a within-subject template from the T1-weighted images of the subject at all time points. We follow a global probabilistic tractography approach, where the unknown pathway is represented in the space of this within-subject template and propagated to the native space of the diffusion-weighted images at all time points to compute its posterior probability given the images. This ensures spatial correspondence of the reconstructed pathway among time points, which in turn allows longitudinal changes in diffusion measures to be estimated consistently along the pathway. We evaluate the reliability of the proposed method on data from healthy controls scanned twice within a month, where no changes in white-matter microstructure are expected between scans. We evaluate the sensitivity of the method on data from Huntington's disease patients scanned repeatedly over the course of several months, where changes are expected between scans. We show that reconstructing white-matter pathways jointly using the data from all time points leads to improved reliability and sensitivity, when compared to reconstructing the pathways at each time point independently.
Preterm birth and very low birth weight (VLBW, ≤1500 g) are worldwide problems that burden survivors with lifelong cognitive, psychological, and physical challenges. In this multimodal structural magnetic resonance imaging (MRI) and diffusion MRI (dMRI) study, we investigated differences in subcortical brain volumes and white matter tract properties in children born preterm with VLBW compared to term-born controls (mean age=8 years). Subcortical brain structure volumes and cortical thickness estimates were obtained, and fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were generated for 18 white matter tracts. We also assessed structural relationships between white matter tracts and cortical thickness of the tract endpoints. Compared to controls, the VLBW group had reduced volumes of thalamus, globus pallidus, corpus callosum, cerebral white matter, ventral diencephalon, and brain stem, while the ventricular system was larger in VLBW subjects, after controlling for age, sex, IQ, and estimated total intracranial volume. For the dMRI parameters, group differences were not significant at the whole-tract level, though pointwise analysis found shorter segments affected in forceps minor and left superior longitudinal fasciculus - temporal bundle. IQ did not correlate with subcortical volumes or dMRI measures in the VLBW group. While the deviations in subcortical volumes were substantial, there were few differences in dMRI measures between the two groups, which may reflect the influence of advances in perinatal care on white matter development.
A causal link between decreases in white matter (WM) integrity and cortical degeneration is assumed, but there is scarce knowledge on the relationship between these changes across the adult human lifespan. We investigated changes in thickness throughout the cortical mantle and WM tract integrity derived from T1 and diffusion weighted magnetic resonance imaging (MRI) scans in 201 healthy adults aged 23-87 years over a mean interval of 3.6 years. Fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivity changes were calculated for forceps minor and major and eight major white matter tracts in each hemisphere by use of a novel automated longitudinal tractography constrained by underlying anatomy (TRACULA) approach. We hypothesized that increasing MD and decreasing FA across tracts would relate to cortical thinning, with some anatomical specificity. WM integrity decreased across tracts non-uniformly, with mean annual percentage decreases ranging from 0.20 in the Inferior Longitudinal Fasciculus to 0.65 in the Superior Longitudinal Fasciculus. For most tracts, greater MD increases and FA decreases related to more cortical thinning, in areas in part overlapping with but also outside the projected tract endings. The findings indicate a combination of global and tract-specific relationships between WM integrity and cortical thinning.
Although much prior work has focused on the known cortical pathology that defines Alzheimer's disease (AD) histologically, recent work has additionally demonstrated substantial damage to the cerebral white matter in this condition. While there is large evidence of diffuse damage to the white matter in AD, it is unclear whether specific white matter tracts exhibit a more accelerated pattern of damage and whether the damage is associated with the classical neurodegenerative changes of AD. In this study, we investigated microstructural differences in the large fascicular bundles of the cerebral white matter of individuals with AD and mild cognitive impairment (MCI), using recently developed automated diffusion tractography procedures in the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset. Eighteen major fiber bundles in a total of 36 individuals with AD, 81 MCI and 60 control participants were examined with the TRActs Constrained by UnderLying Anatomy (TRACULA) procedure available as part of the FreeSurfer image processing software package. For each fiber bundle, the mean fractional anisotropy (FA), and mean, radial and axial diffusivities were calculated. Individuals with AD had increased diffusivities in both left and right cingulum-angular bundles compared to control participants (p<0.001). Individuals with MCI also had increased axial and mean diffusivities and increased FA in both cingulum-angular bundles compared to control participants (p<0.05) and decreased radial diffusivity compared to individuals with AD (p<0.05). We additionally examined how white matter deterioration relates to hippocampal volume, a traditional imaging measure of AD pathology, and found the strongest negative correlations in AD patients between hippocampal volume and the diffusivities of the cingulum-angular and cingulum-cingulate gyrus bundles and of the corticospinal tracts (p<0.05). However, statistically controlling for hippocampal volume did not remove all group differences in white matter measures, suggesting a unique contribution of white matter damage to AD unexplained by this disease biomarker. These results suggest that (1) AD-associated deterioration of white matter fibers is greatest in tracts known to be connected to areas of pathology in AD and (2) lower white matter tract integrity is more diffusely associated with lower hippocampal volume indicating that the pathology in the white matter follows to some degree the neurodegenerative staging and progression of this condition.
Typical brain development includes coordinated changes in both white matter (WM) integrity and cortical thickness (CT). These processes have been shown to be disrupted in schizophrenia, which is characterized by abnormalities in WM microstructure and by reduced CT. The aim of this study was to identify patterns of association between WM markers and cortex-wide CT in healthy controls (HCs) and patients with schizophrenia (SCZ). Using diffusion tensor imaging and structural magnetic resonance imaging data of the Mind Clinical Imaging Consortium study (130 HC and 111 SCZ), we tested for associations between (a) fractional anisotropy in selected manually labeled WM pathways (corpus callosum, anterior thalamic radiation, and superior longitudinal fasciculus) and CT, and (b) the number of lesion-like WM regions ("potholes") and CT. In HC, but not SCZ, we found highly significant negative associations between WM integrity and CT in several pathways, including frontal, temporal, and occipital brain regions. Conversely, in SCZ the number of WM potholes correlated with reduced CT in the left lateral temporal gyrus, left fusiform, and left lateral occipital brain area. Taken together, we found differential patterns of association between WM integrity and CT in HC and SCZ. Although the pattern in HC can be explained from a developmental perspective, the reduced gray matter CT in SCZ patients might be the result of focal but spatially heterogeneous disruptions of WM integrity.
Diffusion-weighted MRI (DW-MRI) has become a popular imaging modality for probing the microstructural properties of white matter and comparing them between populations in vivo. However, the contrast in DW-MRI arises from the microscopic random motion of water molecules in brain tissues, which makes it particularly sensitive to macroscopic head motion. Although this has been known since the introduction of DW-MRI, most studies that use this modality for group comparisons do not report measures of head motion for each group and rely on registration-based correction methods that cannot eliminate the full effects of head motion on the DW-MRI contrast. In this work we use data from children with autism and typically developing children to investigate the effects of head motion on differences in anisotropy and diffusivity measures between groups. We show that group differences in head motion can induce group differences in DW-MRI measures, and that this is the case even when comparing groups that include control subjects only, where no anisotropy or diffusivity differences are expected. We also show that such effects can be more prominent in some white-matter pathways than others, and that they can be ameliorated by including motion as a nuisance regressor in the analyses. Our results demonstrate the importance of taking head motion into account in any population study where one group might exhibit more head motion than the other.
We established a strategy to perform cross-validation of serial optical coherence scanner imaging (SOCS) and diffusion tensor imaging (DTI) on a postmortem human medulla. Following DTI, the sample was serially scanned by SOCS, which integrates a vibratome slicer and a multi-contrast optical coherence tomography rig for large-scale three-dimensional imaging at microscopic resolution. The DTI dataset was registered to the SOCS space. An average correlation coefficient of 0.9 was found between the co-registered fiber maps constructed by fractional anisotropy and retardance contrasts. Pixelwise comparison of fiber orientations demonstrated good agreement between the DTI and SOCS measures. Details of the comparison were studied in regions exhibiting a variety of fiber organizations. DTI estimated the preferential orientation of small fiber tracts; however, it didn't capture their complex patterns as SOCS did. In terms of resolution and imaging depth, SOCS and DTI complement each other, and open new avenues for cross-modality investigations of the brain.
One of the most widely cited features of the neural phenotype of autism is reduced "integrity" of long-range white matter tracts, a claim based primarily on diffusion imaging studies. However, many prior studies have small sample sizes and/or fail to address differences in data quality between those with autism spectrum disorder (ASD) and typical participants, and there is little consensus on which tracts are affected. To overcome these problems, we scanned a large sample of children with autism (n = 52) and typically developing children (n = 73). Data quality was variable, and worse in the ASD group, with some scans unusable because of head motion artifacts. When we follow standard data analysis practices (i.e., without matching head motion between groups), we replicate the finding of lower fractional anisotropy (FA) in multiple white matter tracts. However, when we carefully match data quality between groups, all these effects disappear except in one tract, the right inferior longitudinal fasciculus (ILF). Additional analyses showed the expected developmental increases in the FA of fiber tracts within ASD and typical groups individually, demonstrating that we had sufficient statistical power to detect known group differences. Our data challenge the widely claimed general disruption of white matter tracts in autism, instead implicating only one tract, the right ILF, in the ASD phenotype.
Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.
The lack of consistency of genetic associations in highly heritable mental illnesses, such as schizophrenia, remains a challenge in molecular psychiatry. Because clinical phenotypes for psychiatric disorders are often ill defined, considerable effort has been made to relate genetic polymorphisms to underlying physiological aspects of schizophrenia (so called intermediate phenotypes), that may be more reliable. Given the polygenic etiology of schizophrenia, the aim of this work was to form a measure of cumulative genetic risk and study its effect on neural activity during working memory (WM) using functional magnetic resonance imaging. Neural activity during the Sternberg Item Recognition Paradigm was measured in 79 schizophrenia patients and 99 healthy controls. Participants were genotyped, and a genetic risk score (GRS), which combined the additive effects of 41 single-nucleotide polymorphisms (SNPs) from 34 risk genes for schizophrenia, was calculated. These risk SNPs were chosen according to the continuously updated meta-analysis of genetic studies on schizophrenia available at www.schizophreniaresearchforum.org. We found a positive relationship between GRS and left dorsolateral prefrontal cortex inefficiency during WM processing. GRS was not correlated with age, performance, intelligence, or medication effects and did not differ between acquisition sites, gender, or diagnostic groups. Our study suggests that cumulative genetic risk, combining the impact of many genes with small effects, is associated with a known brain-based intermediate phenotype for schizophrenia. The GRS approach could provide an advantage over studying single genes in studies focusing on the genetic basis of polygenic conditions such as neuropsychiatric disorders.
Developmental dyslexia, an unexplained difficulty in learning to read, has been associated with alterations in white matter organization as measured by diffusion-weighted imaging. It is unknown, however, whether these differences in structural connectivity are related to the cause of dyslexia or if they are consequences of reading difficulty (e.g., less reading experience or compensatory brain organization). Here, in 40 kindergartners who had received little or no reading instruction, we examined the relation between behavioral predictors of dyslexia and white matter organization in left arcuate fasciculus, inferior longitudinal fasciculus, and the parietal portion of the superior longitudinal fasciculus using probabilistic tractography. Higher composite phonological awareness scores were significantly and positively correlated with the volume of the arcuate fasciculus, but not with other tracts. Two other behavioral predictors of dyslexia, rapid naming and letter knowledge, did not correlate with volumes or diffusion values in these tracts. The volume and fractional anisotropy of the left arcuate showed a particularly strong positive correlation with a phoneme blending test. Whole-brain regressions of behavioral scores with diffusion measures confirmed the unique relation between phonological awareness and the left arcuate. These findings indicate that the left arcuate fasciculus, which connects anterior and posterior language regions of the human brain and which has been previously associated with reading ability in older individuals, is already smaller and has less integrity in kindergartners who are at risk for dyslexia because of poor phonological awareness. These findings suggest a structural basis of behavioral risk for dyslexia that predates reading instruction.
The neural mechanisms underlying genetic risk for schizophrenia, a highly heritable psychiatric condition, are still under investigation. New schizophrenia risk genes discovered through genome-wide association studies (GWAS), such as neurogranin (NRGN), can be used to identify these mechanisms. In this study we examined the association of two common NRGN risk single nucleotide polymorphisms (SNPs) with functional and structural brain-based intermediate phenotypes for schizophrenia. We obtained structural, functional MRI and genotype data of 92 schizophrenia patients and 114 healthy volunteers from the multisite Mind Clinical Imaging Consortium study. Two schizophrenia-associated NRGN SNPs (rs12807809 and rs12541) were tested for association with working memory-elicited dorsolateral prefrontal cortex (DLPFC) activity and surface-wide cortical thickness. NRGN rs12541 risk allele homozygotes (TT) displayed increased working memory-related activity in several brain regions, including the left DLPFC, left insula, left somatosensory cortex and the cingulate cortex, when compared to non-risk allele carriers. NRGN rs12807809 non-risk allele (C) carriers showed reduced cortical gray matter thickness compared to risk allele homozygotes (TT) in an area comprising the right pericalcarine gyrus, the right cuneus, and the right lingual gyrus. Our study highlights the effects of schizophrenia risk variants in the NRGN gene on functional and structural brain-based intermediate phenotypes for schizophrenia. These results support recent GWAS findings and further implicate NRGN in the pathophysiology of schizophrenia by suggesting that genetic NRGN risk variants contribute to subtle changes in neural functioning and anatomy that can be quantified with neuroimaging methods.
Previous studies have found varying relationships between cognitive functioning and brain volumes in patients with schizophrenia. However, cortical thickness may more closely reflect cytoarchitectural characteristics than gray matter density or volume estimates. Here, we aimed to compare associations between regional variation in cortical thickness and executive functions, memory, as well as verbal and spatial processing in patients with schizophrenia and healthy controls (HCs). We obtained magnetic resonance imaging and neuropsychological data for 131 patients and 138 matched controls. Automated cortical pattern matching methods allowed testing for associations with cortical thickness estimated as the shortest distance between the gray/white matter border and the pial surface at thousands of points across the entire cortical surface. Two independent measures of working memory showed robust associations with cortical thickness in lateral prefrontal cortex in HCs, whereas patients exhibited associations between working memory and cortical thickness in the right middle and superior temporal lobe. This study provides additional evidence for a disrupted structure-function relationship in schizophrenia. In line with the prefrontal inefficiency hypothesis, schizophrenia patients may engage a larger compensatory network of brain regions other than frontal cortex to recall and manipulate verbal material in working memory.
In diffusion MRI, simultaneous multi-slice single-shot EPI acquisitions have the potential to increase the number of diffusion directions obtained per unit time, allowing more diffusion encoding in high angular resolution diffusion imaging (HARDI) acquisitions. Nonetheless, unaliasing simultaneously acquired, closely spaced slices with parallel imaging methods can be difficult, leading to high g-factor penalties (i.e., lower SNR). The CAIPIRINHA technique was developed to reduce the g-factor in simultaneous multi-slice acquisitions by introducing inter-slice image shifts and thus increase the distance between aliased voxels. Because the CAIPIRINHA technique achieved this by controlling the phase of the RF excitations for each line of k-space, it is not directly applicable to single-shot EPI employed in conventional diffusion imaging. We adopt a recent gradient encoding method, which we termed "blipped-CAIPI", to create the image shifts needed to apply CAIPIRINHA to EPI. Here, we use pseudo-multiple replica SNR and bootstrapping metrics to assess the performance of the blipped-CAIPI method in 3× simultaneous multi-slice diffusion studies. Further, we introduce a novel image reconstruction method to reduce detrimental ghosting artifacts in these acquisitions. We show that data acquisition times for Q-ball and diffusion spectrum imaging (DSI) can be reduced 3-fold with a minor loss in SNR and with similar diffusion results compared to conventional acquisitions.
BACKGROUND: Previous studies have suggested that motivational aspects of executive functioning, which may be disrupted in schizophrenia patients with negative symptoms, are mediated in part by the striatum. Negative symptoms have been linked to impaired recruitment of both the striatum and the dorsolateral prefrontal cortex (DLPFC). Here we tested the hypothesis that negative symptoms are associated primarily with striatal dysfunction, using functional magnetic resonance imaging (fMRI).
METHOD: Working-memory load-dependent activation and gray matter volumes of the striatum and DLPFC were measured using a region-of-interest (ROI) approach, in 147 schizophrenia patients and 160 healthy controls. In addition to testing for a linear relationships between striatal function and negative symptoms, we chose a second, categorical analytic strategy in which we compared three demographically and behaviorally matched subgroups: patients with a high burden of negative symptoms, patients with minimal negative symptoms, and healthy subjects.
RESULTS: There were no differences in striatal response magnitudes between schizophrenia patients and healthy controls, but right DLPFC activity was higher in patients than in controls. Negative symptoms were inversely associated with striatal, but not DLPFC, activity. In addition, patients with a high burden of negative symptoms exhibited significantly lower bilateral striatal, but not DLPFC, activation than schizophrenia patients with minimal negative symptoms. Working memory performance, antipsychotic exposure and changes in gray matter volumes did not account for these differences.
CONCLUSIONS: These data provide further evidence for a robust association between negative symptoms and diminished striatal activity. Future work will determine whether low striatal activity in schizophrenia patients could serve as a reliable biomarker for negative symptoms.
Diffusion spectrum imaging offers detailed information on complex distributions of intravoxel fiber orientations at the expense of extremely long imaging times (∼1 h). Recent work by Menzel et al. demonstrated successful recovery of diffusion probability density functions from sub-Nyquist sampled q-space by imposing sparsity constraints on the probability density functions under wavelet and total variation transforms. As the performance of compressed sensing reconstruction depends strongly on the level of sparsity in the selected transform space, a dictionary specifically tailored for diffusion probability density functions can yield higher fidelity results. To our knowledge, this work is the first application of adaptive dictionaries in diffusion spectrum imaging, whereby we reduce the scan time of whole brain diffusion spectrum imaging acquisition from 50 to 17 min while retaining high image quality. In vivo experiments were conducted with the 3T Connectome MRI. The root-mean-square error of the reconstructed "missing" diffusion images were calculated by comparing them to a gold standard dataset (obtained from acquiring 10 averages of diffusion images in these missing directions). The root-mean-square error from the proposed reconstruction method is up to two times lower than that of Menzel et al.'s method and is actually comparable to that of the fully-sampled 50 minute scan. Comparison of tractography solutions in 18 major white-matter pathways also indicated good agreement between the fully-sampled and 3-fold accelerated reconstructions. Further, we demonstrate that a dictionary trained using probability density functions from a single slice of a particular subject generalizes well to other slices from the same subject, as well as to slices from other subjects.
BACKGROUND: Disrupted in schizophrenia 1 (DISC1) is known to play a major role during brain development and is a candidate gene for schizophrenia. Cortical thickness is highly heritable and several MRI studies have shown widespread reductions of cortical thickness in patients with schizophrenia. Here, we investigated the effects of variation in DISC1 on cortical thickness. In a subsequent analysis we tested whether the identified DISC1 risk variant is also associated with neural activity during working memory functioning.
METHODS: We acquired structural MRI (sMRI), functional MRI (fMRI) and genotype data from 96 healthy volunteers. Separate cortical statistical maps for five single nucleotide polymorphisms (SNP) of DISC1 were generated to detect differences of cortical thickness in genotype groups across the entire cortical surface. Working-memory related load-dependent activation was measured during the Sternberg Item Recognition Paradigm and analyzed using a region-of-interest approach.
RESULTS: Phe allele carriers of the DISC1 SNP Leu607Phe had significantly reduced cortical thickness in the left supramarginal gyrus compared to Leu/Leu homozygotes. Neural activity in the left dorsolateral prefrontal cortex (DLPFC) during working memory task was increased in Phe allele carriers, whereas working memory performance did not differ between genotype groups.
CONCLUSIONS: This study provides convergent evidence for the effect of DISC1 risk variants on two independent brain-based intermediate phenotypes of schizophrenia. The same risk variant was associated with cortical thickness reductions and signs of neural inefficiency during a working memory task. Our findings provide further evidence for a neurodevelopmental model of schizophrenia.
We have developed a method for automated probabilistic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images. Our method is called TRACULA (TRActs Constrained by UnderLying Anatomy) and utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual interaction with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. In this paper we illustrate the application of the method on data from a schizophrenia study and investigate whether the inclusion of both patients and healthy subjects in the training set affects our ability to reconstruct the pathways reliably. We show that, since our method does not constrain the exact spatial location or shape of the pathways but only their trajectory relative to the surrounding anatomical structures, a set a of healthy training subjects can be used to reconstruct the pathways accurately in patients as well as in controls.