Recent findings suggest a close link between long-term meditation practices and the structure of the corpus callosum. Prior analyses, however, have focused on estimating mean fractional anisotropy (FA) within two large pre-defined callosal tracts only. Additional effects might exist in other, non-explored callosal regions and/or with respect to callosal attributes not captured by estimates of FA. To further explore callosal features in the framework of meditation, we analyzed 30 meditators and 30 controls, carefully matched for sex, age, and handedness. We applied a multimodal imaging approach using diffusion tensor imaging (DTI) in combination with structural magnetic resonance imaging (MRI). Callosal measures of tract-specific FA were complemented with other global (segment-specific) estimates as well as extremely local (point-wise) measures of callosal micro- and macro-structure. Callosal measures were larger in long-term meditators compared to controls, particularly in anterior callosal sections. However, differences achieved significance only when increasing the regional sensitivity of the measurement (i.e., using point-wise measures versus segment-specific measures) and were more prominent for microscopic than macroscopic characteristics (i.e., callosal FA versus callosal thickness). Thicker callosal regions and enhanced FA in meditators might indicate greater connectivity, possibly reflecting increased hemispheric integration during cerebral processes involving (pre)frontal regions. Such a brain organization might be linked to achieving characteristic mental states and skills as associated with meditation, though this hypothesis requires behavioral confirmation. Moreover, longitudinal studies are required to address whether the observed callosal effects are induced by meditation or constitute an innate prerequisite for the start or successful continuation of meditation.
brain; corpus callosum; DTI; mindfulness; MRI; plasticity
Very little is known on white collar crime and how it differs to other forms of offending. This study tests the hypothesis that white collar criminals have better executive functioning, enhanced information processing, and structural brain superiorities compared to offender controls. Using a case-control design, executive functioning, orienting, and cortical thickness was assessed in 21 white collar criminals matched with 21 controls on age, gender, ethnicity, and general level of criminal offending. White collar criminals had significantly better executive functioning, increased electrodermal orienting, increased arousal, and increased cortical gray matter thickness in the ventromedial prefrontal cortex, inferior frontal gyrus, somatosensory cortex, and the temporal-parietal junction compared to controls. Results, while initial, constitute the first findings on neurobiological characteristics of white-collar criminals It is hypothesized that white collar criminals have information-processing and brain superiorities that give them an advantage in perpetrating criminal offenses in occupational settings.
antisocial; ventromedial; inferior frontal; temporal-parietal; somatosensory; orienting; arousal; electrodermal
Structural and diffusion tensor imaging studies implicate gray and white matter (WM) abnormalities and disruptions of neural circuitry in schizophrenia. However, the structural integrity of the superficial WM, comprising short-range association (U-fibers) and intracortical axons, has not been investigated in schizophrenia.
High-resolution structural and diffusion tensor images and sophisticated cortical pattern matching methods were used to measure and compare global and local variations in superficial WM fractional anisotropy between schizophrenia patients and their relatives and community comparison subjects and their relatives (n = 150).
Compared with control subjects, patients showed reduced superficial WM fractional anisotropy distributed across each hemisphere, particularly in left temporal and bilateral occipital regions (all p < .05, corrected). Furthermore, by modeling biological risk for schizophrenia in patients, patient relatives, and control subjects, fractional anisotropy was shown to vary in accordance with relatedness to a patient in both hemispheres and in the temporal and occipital lobes (p < .05, corrected). However, effects did not survive correction procedures for two-group comparisons between patient relatives and control subjects.
Results extend previous findings restricted to deep WM pathways to demonstrate that disturbances in corticocortical connectivity are associated with schizophrenia and might indicate a genetic predisposition for the disorder. Because the structural integrity of WM plays a crucial role in the functionality of networks linking gray matter regions, disturbances in the coherence and organization of fibers at the juncture of the neuropil might relate to features of schizophrenia at least partially attributable to disease-related genetic factors.
Diffusion tensor imaging (DTI); fractional anisotropy (FA); magnetic resonance imaging (MRI); short-range association fibers; U-fibers; white matter (WM)
The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.
National centers for biomedical computing; NCBC; center for computational biology; computational neuroscience; atlas; manifold; computational infrastructure; collaborative and sustainable biomedical research; neuroscience; neuroimaging; data sharing; data mining; brain; segmentation
A key challenge in the accurate reconstruction of cortical surfaces is the automated correction of geometric and topological outliers in tissue boundaries. Conventionally these two types of errors are handled separately. In this work, we propose a unified analysis framework for the joint correction of geometric and topological outliers in cortical reconstruction. Using the Reeb graph of intrinsically defined Laplace-Beltrami eigenfunctions, our method automatically locates spurious branches, handles and holes on tissue boundaries and corrects them with image information and geometric regularity derived from paired boundary evolutions. In our experiments, we demonstrate on 200 MR images from two datasets that our method is much faster and achieves better performance than FreeSurfer in population studies.
Diffusion tensor imaging is widely used in brain connectivity study. As
more and more group studies recruit a large number of subjects, it is important
to design registration methods that are not only theoretically rigorous, but
also computationally efficient, for processing large data sets. However, the
requirement of reorienting diffusion tensors complicates and slows down the
registration, especially for those methods whose scalar-image versions have
linear complexity, for example, the Demons algorithm. In this paper, we propose
an extension of the Demons algorithm that incorporates exact reorientation and
regularization into the calculation of deforming velocity, yet preserving its
linear complexity. This method restores the computational efficiency of the
Demons algorithm to diffusion images, but does not sacrifice registration
goodness. In our experiments, the new algorithm achieved state-of-art
performance at a ten-fold decrease of computational time.
In this study, we used manual delineation of high-resolution magnetic resonance imaging (MRI) to determine the spatial and temporal characteristics of the cerebellar atrophy in spinocerebellar ataxia type 2 (SCA2). Ten subjects with SCA2 were compared to ten controls. The volume of the pons, the total cerebellum, and the individual cerebellar lobules were calculated via manual delineation of structural MRI. SCA2 showed substantial global atrophy of the cerebellum. Furthermore, the degeneration was lobule-specific, selectively affecting the anterior lobe, VI, Crus I, Crus II, VIII, uvula, corpus medullare, and pons, while sparing VIIB, tonsil/paraflocculus, flocculus, declive, tuber/folium, pyramis, and nodulus. The temporal characteristics differed in each cerebellar subregion: 1) Duration of disease: Crus I, VIIB, VIII, uvula, corpus medullare, pons, and the total cerebellar volume correlated with the duration of disease; 2) Age: VI, Crus II, and flocculus correlated with age in control subjects; 3) Clinical scores: VI, Crus I, VIIB, VIII, corpus medullare, pons, and the total cerebellar volume correlated with clinical scores in SCA2. No correlations were found with the age of onset. Our extrapolated volumes at the onset of symptoms suggest that neurodegeneration may be present even during the presymptomatic stages of disease. The spatial and temporal characteristics of the cerebellar degeneration in SCA2 are region-specific. Furthermore, our findings suggest the presence of presymptomatic atrophy and a possible developmental component to the mechanisms of pathogenesis underlying SCA2. Our findings further suggest that volumetric analysis may aid in the development of a non-invasive, quantitative biomarker.
ataxia; spinocerebellar ataxia type 2 (SCA2); magnetic resonance imaging (MRI); biomarker
Understanding the variability of the hippocampus in human brain research is essential. The effect of age on the hippocampus has been explored in several studies that have been focused on either normal aging or neural degeneration. Shape analysis of magnetic resonance imaging (MRI) provides morphological measures for brain structures. This study further investigates the age effects on hippocampal morphology in three groups (104 normal controls, 24 Alzheimer’s disease (AD) and 14 vascular dementia (VaD) patients). By utilizing a parametric shape analysis of hippocampal MRI scans, each individual distance map is generated and analyzed statistically. Specifically, after eliminating similarity parameters (rotation, translation, and scaling) effects for each hippocampus, an individual distance map is generated from parametric hippocampal surfaces and medial axes. Then statistical methods, including regression, and permutation tests, are applied to detect the differences in hippocampal distance maps and volumes under the effect of age in each group. Statistical analyses reveal that the loss of hippocampal volume and changes in shape are more significantly related to aging in the control group than in AD/VaD. The results also show that the asymmetry of hippocampus in healthy subjects is greater than that in either of the disease groups. Our study shows that 3D statistical shape analysis could enhance the understanding of age effects on local areas of hippocampi. However, the sample sizes of disease groups are relatively low; further studies with more AD/VaD data are needed.
Statistical shape analysis; age; hippocampus; Alzheimer’s disease; vascular dementia
The development of late-onset Alzheimer’s disease (LOAD) is under strong genetic control and there is great interest in the genetic variants that confer increased risk. The Alzheimer’s disease risk gene, growth factor receptor bound protein 2-associated protein (GAB2), has been shown to provide a 1.27–1.51 increased odds of developing LOAD for rs7101429 major allele carriers, in case-control analysis. GAB2 is expressed across the brain throughout life, and its role in LOAD pathology is well understood. Recent studies have begun to examine the effect of genetic variation in the GAB2 gene on differences in the brain. However, the effect of GAB2 on the young-adult brain has yet to be considered. Here we found a significant association between the GAB2 gene and morphological brain differences in 755 young-adult twins (469 females) (M = 23.1, SD = 3.1 years), using a gene-based test with principal components regression (PCReg). Detectable differences in brain morphology are therefore associated with variation in the GAB2 gene, even in young adults, long before the typical age of onset of Alzheimer’s disease.
GAB2; imaging genetics; tensor-based morphometry; Alzheimer’s disease
Background & Aims
Regional reductions in gray matter (GM) have been reported in several chronic somatic and visceral pain conditions, including irritable bowel syndrome (IBS) and chronic pancreatitis. Reported GM reductions include insular and anterior cingulate cortices, even though subregions are generally not specified. The majority of published studies suffer from limited sample size, heterogeneity of populations, and lack of analyses for sex differences. We aimed to characterize regional changes in cortical thickness (CT) in a large number of well phenotyped IBS patients, taking into account the role of sex related differences.
Cortical GM thickness was determined in 266 subjects (90 IBS [70 predominantly premenopausal female] and 176 healthy controls (HC) [155 predominantly premenopausal female]) using the Laboratory of Neuro Imaging (LONI) Pipeline. A combined region of interest (ROI) and whole brain approach was used to detect any sub-regional and vertex-level differences after removing effects of age and total GM volume. Correlation analyses were performed on behavioral data.
While IBS as a group did not show significant differences in CT compared to HCs, sex related differences were observed both within the IBS and the HC groups. When female IBS patients were compared to female HCs, whole brain analysis showed significant CT increase in somatosensory and primary motor cortex, as well as CT decrease in bilateral subgenual anterior cingulate cortex (sgACC). The ROI analysis showed significant regional CT decrease in bilateral subregions of insular cortex, while CT decrease in cingulate was limited to left sgACC, accounting for the effect of age and GM volume. Several measures of IBS symptom severity showed significant correlation with CT changes in female IBS patients.
Significant, sex related differences in CT are present in both HCs and in IBS patients. The biphasic neuroplastic changes in female IBS patients are related to symptom severity.
Structural brain deficits, especially fronto-temporal volume reduction and ventricular enlargement, have been repeatedly reported in patients with schizophrenia. However, it remains unclear whether brain structural deformations may be attributable to disease-related or genetic factors. In this study, the structural magnetic resonance imaging data of 48 adult-onset schizophrenia patients, 65 first-degree non-psychotic relatives of schizophrenia patients, 27 community comparison (CC) probands and 73 CC relatives were examined using tensor-based morphometry (TBM) to isolate global and localized differences in tissue volume across the entire brain between groups. We found brain tissue contractions most prominently in frontal and temporal regions and expansions in the putamen/ pallidum, and lateral and third ventricles in schizophrenia patients when compared to unrelated CC probands. Results were similar, though less prominent when patients were compared with their non-psychotic relatives. Structural deformations observed in unaffected patient relatives compared to age-similar CC relatives were suggestive of schizophrenia-related genetic liability and were pronounced in the putamen/ pallidum and medial temporal regions. Schizophrenia and genetic liability effects for the putamen/ pallidum were confirmed by regions-of-interest analysis. In conclusion, TBM findings complement reports of frontal, temporal and ventricular dysmorphology in schizophrenia and further indicate that putamen/ pallidum enlargements, originally linked mainly with medication exposure in early studies, also reflect a genetic predisposition for schizophrenia. Thus, brain deformation profiles revealed in this study may help to clarify the role of specific genetic or environmental risk factors towards altered brain morphology in schizophrenia.
Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20–30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.
neuroimaging; brain structure; DTI; genetics; genetic profiles; prediction; imaging; clinical or preclinical; neuroanatomy; neurogenetics; pharmacogenetics / pharmacogenomics; neuroimaging; brain structure; DTI; genetics; genetic profiles
The Alzheimer's Disease Neuroimaging Initiative (ADNI)
recently added diffusion tensor imaging (DTI), among several other new imaging
modalities, in an effort to identify sensitive biomarkers of Alzheimer's disease
(AD). While anatomical MRI is the main structural neuroimaging method used in
most AD studies and clinical trials, DTI is sensitive to microscopic white
matter (WM) changes not detectable with standard MRI, offering additional
markers of neurodegeneration. Prior DTI studies of AD report lower fractional
anisotropy (FA), and increased mean, axial, and radial diffusivity (MD, AxD, RD)
throughout WM. Here we assessed which DTI measures may best identify differences
among AD, mild cognitive impairment (MCI), and cognitively healthy elderly
control (NC) groups, in region of interest (ROI) and voxel-based analyses of 155
ADNI participants (mean age: 73.5 ± 7.4; 90
M/65 F; 44 NC, 88 MCI, 23 AD). Both VBA and ROI analyses
revealed widespread group differences in FA and all diffusivity measures. DTI
maps were strongly correlated with widely-used clinical ratings (MMSE, CDR-sob,
and ADAS-cog). When effect sizes were ranked, FA analyses were least sensitive
for picking up group differences. Diffusivity measures could detect more subtle
MCI differences, where FA could not. ROIs showing strongest group
differentiation (lowest p-values) included tracts that
pass through the temporal lobe, and posterior brain regions. The left
hippocampal component of the cingulum showed consistently high effect sizes for
distinguishing groups, across all diffusivity and anisotropy measures, and in
correlations with cognitive scores.
•DTI scans in ADNI2 provide numerous biomarkers of
Alzheimer's disease.•FA, MD, AxD, and RD measures all detect MCI and AD
white matter deficits.•DTI FA and diffusivity measures are correlated with
clinical cognitive scores.•FA is the least sensitive DTI measure for detecting
AD related differences.•WM in the temporal lobe, corpus callosum and
cingulum is repeatedly implicated.
NC, normal control; RD, radial diffusivity; AxD, axial diffusivity; ADNI, Alzheimer's Disease Neuroimaging Initiative; DTI; Alzheimer's disease; MCI; White matter; Clinical scores; Biomarkers
The link between brain structure and intelligence is a well-investigated topic, but existing analyses have mainly focused on adult samples. Studies in healthy children and adolescents are rare, and normative data specifically addressing the association between corpus callosum morphology and intellectual abilities is quite limited. To advance this field of research, we mapped the correlations between standardized intelligence measures and callosal thickness based on high-resolution magnetic resonance imaging (MRI) data. Our large and well-matched sample included 200 normally developing subjects (100 males, 100 females) ranging from 6 to 17 years of age. Although the strongest correlations were negative and confined to the splenium, the strength and the direction of intelligence-callosal thickness associations varied considerably with respect to age and sex. While significant correlations in females were mainly positive, significant correlations in males were exclusively negative. However, only the negative correlations in the overall sample (i.e., males and females combined) remained significant when controlling for multiple comparisons. The observed negative correlations between callosal thickness and intelligence in children and adolescents contrast with the positive correlations typically reported in adult samples. However, negative correlations are in line with reports from other pediatric studies relating cognitive measures to other brain attributes such as cortical thickness, gray matter volume, and gray matter density. Altogether, these findings suggest that relationships between callosal morphology and cognition are highly dynamic during brain maturation. Sex effects on links between callosal thickness and intelligence during childhood and adolescence are present but appear rather weak in general.
brain; corpus callosum; development; gender; IQ; MRI
Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead.
image metadata; file format; data archive
Scientific studies addressing anatomical variations in meditators' brains have emerged rapidly over the last few years, where significant links are most frequently reported with respect to gray matter (GM). To advance prior work, this study examined GM characteristics in a large sample of 100 subjects (50 meditators, 50 controls), where meditators have been practicing close to 20 years, on average. A standard, whole-brain voxel-based morphometry approach was applied and revealed significant meditation effects in the vicinity of the hippocampus, showing more GM in meditators than in controls as well as positive correlations with the number of years practiced. However, the hippocampal complex is regionally segregated by architecture, connectivity, and functional relevance. Thus, to establish differential effects within the hippocampal formation (cornu ammonis, fascia dentata, entorhinal cortex, subiculum) as well as the hippocampal-amygdaloid transition area, we utilized refined cytoarchitectonic probabilistic maps of (peri-) hippocampal subsections. Significant meditation effects were observed within the subiculum specifically. Since the subiculum is known to play a key role in stress regulation and meditation is an established form of stress reduction, these GM findings may reflect neuronal preservation in long-term meditators—perhaps due to an attenuated release of stress hormones and decreased neurotoxicity.
cytoarchitectonics; hippocampus; mapping; meditation; mindfulness; MRI; subiculum; VBM
Gray matter atrophy is an important correlate to clinical disability in multiple sclerosis (MS) and many treatment trials include atrophy as an outcome measure. Atrophy has been shown to occur in experimental autoimmune encephalomyelitis (EAE), the most commonly used animal model of MS. While the clinical severity of EAE is reduced in estrogen treated mice, it remains unknown whether estrogen treatment can reduce gray matter atrophy in EAE. In this study, mice with EAE were treated with either estrogen receptor (ER)-alpha ligand or ER-beta ligand, diffusion tensor images (DTI) were collected and neuropathology performed. DTI showed atrophy in the cerebellar gray matter of vehicle-treated EAE mice as compared to healthy controls, but not in ER-alpha or ER-beta ligand-treated EAE mice. Neuropathology demonstrated that Purkinje cell numbers were decreased in vehicle-treated EAE mice, while neither ER ligand-treated EAE groups showed a decrease. This is the first report of a neuroprotective therapy in EAE that unambiguously prevents gray matter atrophy while sparing a major neuronal cell type. Fractional anisotropy (FA) in the cerebellar white matter was decreased in vehicle-and ER-beta ligand-treated, but not in ER-alpha ligand-treated EAE mice. Inflammatory cell infiltration was increased in vehicle-and ER-beta ligand-treated, but not in ER-alpha ligand-treated EAE mice. Myelin staining was decreased in vehicle-treated EAE mice, and spared in both ER ligand-treated groups. This is consistent with decreased FA as a potential biomarker for inflammation rather than myelination or axonal damage in the cerebellum in EAE.
dti; multiple sclerosis; mouse; ligand
The corpus callosum changes structurally throughout life, but most dramatically during childhood and adolescence. Even so, existing studies of callosal development tend to use parcellation schemes that may not capture the complex spatial profile of anatomical changes. Thus, more detailed mapping of callosal growth processes is desirable to create a normative reference. This will help to relate and interpret other structural, functional, and behavioral measurements, both from healthy subjects and pediatric patients. We applied computational surface-based mesh-modeling methods to analyze callosal morphology at extremely high spatial resolution. We mapped callosal development and explored sex differences in a large and well-matched sample of healthy children and adolescents (n=190) aged 5 to 18 years. Except for the rostrum in females, callosal thickness increased across the whole surface, with sex- and region-specific rates of growth, and also shrinkage at times. The temporally distinct changes in callosal thickness are likely to be a consequence of varying degrees of axonal myelination, redirection, and pruning. Alternating phases of callosal growth and shrinkage may reflect a permanent adjustment and fine-tuning of fibers connecting homologous cortical areas during childhood and adolescence. Our findings emphasize the importance of taking into account sex differences in future studies, as existing developmental effects might remain disguised (or biased towards the effect of the dominant sex in unbalanced statistical designs) when pooling male and female samples.
Age; Female; Isthmus; Male; MRI; Sex; Splenium
Naturally occurring mutants and genetically manipulated strains of mice are widely used to model a variety of human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison and to facilitate the integration of anatomic, genetic, and physiologic observations from multiple subjects and experiments. We have developed digital atlases of the C57BL/6J mouse brain (adult and neonate) as comprehensive frameworks for storing and accessing the myriad types of information about the mouse brain. Along with raw and annotated images, these contain database management systems and a set of tools for comparing information from different techniques and different animals. Each atlas establishes a canonical representation of the mouse brain and provides the tools for the manipulation and analysis of new data. We describe both these atlases and discuss how they may be put to use in organizing and analyzing data from mouse models of epilepsy.
Anatomy; Atlas; Neonatal; Probabilistic
Although the systematic study of meditation is still in its infancy, research has provided evidence for meditation-induced improvements in psychological and physiological well-being. Moreover, meditation practice has been shown not only to benefit higher-order cognitive functions but also to alter brain activity. Nevertheless, little is known about possible links to brain structure. Using high-resolution MRI data of 44 subjects, we set out to examine the underlying anatomical correlates of long-term meditation with different regional specificity (i.e., global, regional, and local). For this purpose, we applied voxel-based morphometry in association with a recently validated automated parcellation approach. We detected significantly larger gray matter volumes in meditators in the right orbito-frontal cortex (as well as in the right thalamus and left inferior temporal gyrus when co-varying for age and/or lowering applied statistical thresholds). In addition, meditators showed significantly larger volumes of the right hippocampus. Both orbito-frontal and hippocampal regions have been implicated in emotional regulation and response control. Thus, larger volumes in these regions might account for meditators’ singular abilities and habits to cultivate positive emotions, retain emotional stability, and engage in mindful behavior. We further suggest that these regional alterations in brain structures constitute part of the underlying neurological correlate of long-term meditation independent of a specific style and practice. Future longitudinal analyses are necessary to establish the presence and direction of a causal link between meditation practice and brain anatomy.
Thalamus; Orbital; Hippocampus; MRI; Plasticity; VBM
Designers of clinical trials for Alzheimer's disease (AD) and mild cognitive impairment (MCI) are actively considering structural and functional neuroimaging, cerebrospinal fluid and genetic biomarkers to reduce the sample sizes needed to detect therapeutic effects. Genetic pre-selection, however, has been limited to Apolipoprotein E (ApoE). Recently discovered polymorphisms in the CLU, CR1 and PICALM genes are also moderate risk factors for AD; each affects lifetime AD risk by ~ 10–20%. Here, we tested the hypothesis that pre-selecting subjects based on these variants along with ApoE genotype would further boost clinical trial power, relative to considering ApoE alone, using an MRI-derived 2-year atrophy rate as our outcome measure. We ranked subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) based on their cumulative risk from these four genes. We obtained sample size estimates in cohorts enriched in subjects with greater aggregate genetic risk. Enriching for additional genetic biomarkers reduced the required sample sizes by up to 50%, for MCI trials. Thus, AD drug trial enrichment with multiple genotypes may have potential implications for the timeliness, cost, and power of trials.
•ApoE genotype status helps enrich MCI trials, using a structural MRI outcome measure.•CLU, PICALM and CR1 risk genes boost potential MCI trial power beyond ApoE alone.•CLU, PICALM and CR1 show significant, aggregate effects on TBM maps of brain atrophy.
Alzheimer's disease; Neuroimaging; Brain atrophy; Genetics; Genetic risk score; Clinical trial enrichment
The different brain anatomy of men and women is both a classic and continuing topic of major interest. Among the most replicated and robust sex differences are larger overall brain dimensions in men, and relative increases of global and regional gray matter (GM) in women. However, the question remains whether sex-typical differences in brain size (i.e., larger male and smaller female brains) or biological sex itself account for the observed sex effects on tissue amount and distribution. Exploring cerebral structures in men and women with similar brain size may clarify the true contribution of biological sex. We thus examined a sample of 24 male and 24 female subjects with brains identical in size, in addition to 24 male and 24 female subjects with considerable brain size differences. Using this large set of brains (n=96), we applied a well-validated and automated voxel-based approach to examine regional volumes of GM. While we revealed significant main effects of sex, there were no significant effects of brain size (and no significant interactions between sex and brain size). When conducting post hoc tests, we revealed a number of regions where women had larger GM volumes compared to men. Importantly, these sex effects remained evident when comparing men and women with the same brain size. Altogether, our findings suggest that the observed increased regional GM volumes in female brains constitute sex-dependent redistributions of tissue volume, rather than individual adjustments attributable to brain size.
Female; Gender; Male; MRI; TBV; VBM
As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm.
Graphics Processing Unit (GPU); Performance Optimization; Compute-bound; Memory-bound; CUDA; Fermi; Neuroimaging