[Show abstract][Hide abstract] ABSTRACT: A single case study recently documented one woman's ability to recall accurately vast amounts of autobiographical information, spanning most of her lifetime, without the use of practiced mnemonics (Parker, Cahill, & McGaugh, 2006). The current study reports findings based on eleven participants expressing this same memory ability, now referred to as Highly Superior Autobiographical Memory (HSAM). Participants were identified and subsequently characterized based on screening for memory of public events. They were then tested for personal autobiographical memories as well as for memory assessed by laboratory memory tests. Additionally, whole-brain structural MRI scans were obtained. Results indicated that HSAM participants performed significantly better at recalling public as well as personal autobiographical events as well as the days and dates on which these events occurred. However, their performance was comparable to age- and sex-matched controls on most standard laboratory memory tests. Neuroanatomical results identified nine structures as being morphologically different from those of control participants. The study of HSAM may provide new insights into the neurobiology of autobiographical memory.
Neurobiology of Learning and Memory 05/2012; 98(1):78-92. · 3.33 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Diffusion MR imaging provides a unique tool to probe the microgeometry of nervous tissue and to explore the wiring diagram of the neural connections noninvasively. Generally, a forward model is established to map the intra-voxel fiber architecture onto the observable diffusion signals, which is reformulated in this article by adopting a measure-theoretic approach. However, the inverse problem, i.e., the spherical deconvolution of the fiber orientation density from noisy MR measurements, is ill-posed. We propose a nonparametric representation of the tangential distribution of the nerve fibers in terms of a Dirichlet process mixture. Given a second-order approximation of the impulse response of a fiber segment, the specified problem is solved by Bayesian statistics under a Rician noise model, using an adaptive reversible jump Markov chain Monte Carlo sampler. The density estimation framework is demonstrated by various experiments with a diffusion MR dataset featuring high angular resolution, uncovering the fiber orientation field in the cerebral white matter of the living human brain.
Medical image analysis 02/2012; 16(4):876-88. · 3.09 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Reconstruction of the cerebral cortex from magnetic resonance (MR) images is an important step in quantitative analysis of the human brain structure, for example, in sulcal morphometry and in studies of cortical thickness. Existing cortical reconstruction approaches are typically optimized for standard resolution (~1 mm) data and are not directly applicable to higher resolution images. A new PDE-based method is presented for the automated cortical reconstruction that is computationally efficient and scales well with grid resolution, and thus is particularly suitable for high-resolution MR images with submillimeter voxel size. The method uses a mathematical model of a field in an inhomogeneous dielectric. This field mapping, similarly to a Laplacian mapping, has nice laminar properties in the cortical layer, and helps to identify the unresolved boundaries between cortical banks in narrow sulci. The pial cortical surface is reconstructed by advection along the field gradient as a geometric deformable model constrained by topology-preserving level set approach. The method's performance is illustrated on exvivo images with 0.25-0.35 mm isotropic voxels. The method is further evaluated by cross-comparison with results of the FreeSurfer software on standard resolution data sets from the OASIS database featuring pairs of repeated scans for 20 healthy young subjects.
International Journal of Biomedical Imaging 01/2012; 2012:870196.
[Show abstract][Hide abstract] ABSTRACT: Careful selection of the reference region for non-quantitative positron emission tomography (PET) analyses is critically important for Region of Interest (ROI) data analyses. We introduce an empirical method of deriving the most suitable reference region for computing neurodegeneration sensitive (18)fluorodeoxyglucose (FDG) PET ratios based on the dataset collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Candidate reference regions are selected based on a heat map of the difference in coefficients of variation (COVs) of FDG ratios over time for each of the Automatic Anatomical Labeling (AAL) atlas regions normalized by all other AAL regions. Visual inspection of the heat map suggests that the portion of the cerebellum and vermis superior to the horizontal fissure is the most sensitive reference region. Analyses of FDG ratio data show increases in significance on the order of ten-fold when using the superior portion of the cerebellum as compared with the traditionally used full cerebellum. The approach to reference region selection in this paper can be generalized to other radiopharmaceuticals and radioligands as well as to other disorders where brain changes over time are hypothesized and longitudinal data is available. Based on the empirical evidence presented in this study, we demonstrate the usefulness of the COV heat map method and conclude that intensity normalization based on the superior portion of the cerebellum may be most sensitive to measuring change when performing longitudinal analyses of FDG-PET ratios as well as group comparisons in Alzheimer's disease. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.
Biochimica et Biophysica Acta 09/2011; 1822(3):457-66. · 4.66 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Registration of histology to three-dimensional (3D) magnetic resonance (MR) images is often required for the analysis of brain structure and investigation of brain pathologies. A novel algorithm for deformable registration of an individual histological section to a brain MR image is described. The cost function uses a novel hybrid intensity- and boundary surface-based measure that reflects the contrast of histological slice intensities across the boundary of the pial and inner cortical surface. The algorithm relies on implicit representation of cortical surfaces reconstructed from an anatomical MR image, and computes the cost function in a level set framework. The algorithm is evaluated on cross-modality registration of myelin-stained histological sections to a high-resolution MR image of the human brain.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:4876-9.
[Show abstract][Hide abstract] ABSTRACT: Diffusion magnetic resonance (MR) imaging has enabled us to reveal the white matter geometry in the living human brain. The Q-ball technique is widely used nowadays to recover the orientational heterogeneity of the intra-voxel fiber architecture. This article proposes to employ the Funk-Radon transform in a Hilbert space with a reproducing kernel derived from the spherical Laplace-Beltrami operator, thus generalizing previous approaches that assume a bandlimited diffusion signal. The function estimation problem is solved within a Tikhonov regularization framework, while a Gaussian process model allows for the selection of the smoothing parameter and the specification of confidence bands. Shortcomings of Q-ball imaging are discussed.
IEEE transactions on medical imaging. 05/2011; 30(11):1877-86.
[Show abstract][Hide abstract] ABSTRACT: We present a novel approach to identifying poorly resolved boundaries between adjacent sulcal cortical banks in MR images of the human brain. The algorithm calculates an electrostatic potential field in a partial differential equation (PDE) model of inhomogeneous "dielectric" layer of gray matter that surrounds "conductive" white matter. Correspondence trajectories and geodesic distances are computed along the streamlines of the potential field gradient using PDEs in a Eulerian framework. The skeleton of a sulcal medial boundary is identified by a simple procedure that finds irregularities/collisions in the field of correspondences. The skeleton detection procedure is robust to noise, does not produce spurious artifacts and does not require tunable parameters. We compare results of our algorithm and a closely related technique, called Anatomically Consistent Enhancement (ACE), which is based on the Eikonal equation (Han et al. "CRUISE: Cortical reconstruction using implicit surface evolution", 2004). The results demonstrate that our approach has a number of advantages over ACE and produces skeletons with a more regular structure. Our algorithm was developed as a part of a more general PDE-based framework for cortical reconstruction, which integrates the potential field gradient flow and the skeleton barriers into a level set deformable model. Our technique is primarily aimed at anatomically consistent and accurate reconstruction of cortical surface models in the presence of imaging noise and partial volume effects, but the identified intrasulcal medial surfaces can serve other purposes as well, e.g. as landmarks in nonrigid registration, or sulcal ribbons in characterization of cortical folding.
[Show abstract][Hide abstract] ABSTRACT: Registration of histological images to three-dimensional imaging modalities is an important step in quantitative analysis of brain structure, in architectonic mapping of the brain, and in investigation of the pathology of a brain disease. Reconstruction of histology volume from serial sections is a well-established procedure, but it does not address registration of individual slices from sparse sections, which is the aim of the slice-to-volume approach. This study presents a flexible framework for intensity-based slice-to-volume nonrigid registration algorithms with a geometric transformation deformation field parametrized by various classes of spline functions: thin-plate splines (TPS), Gaussian elastic body splines (GEBS), or cubic B-splines. Algorithms are applied to cross-modality registration of histological and magnetic resonance images of the human brain. Registration performance is evaluated across a range of optimization algorithms and intensity-based cost functions. For a particular case of histological data, best results are obtained with a TPS three-dimensional (3D) warp, a new unconstrained optimization algorithm (NEWUOA), and a correlation-coefficient-based cost function.
Anatomy research international. 01/2011; 2011:287860.
[Show abstract][Hide abstract] ABSTRACT: Lesions of the brain’s white matter are common findings in MR examinations of elderly subjects. A fully automatic method for segmenting white matter lesions is proposed here. The joint probability of multi-modality MR image intensities is used as a feature to segment lesions, because lesion intensities usually are outliers of the normal tissue intensities and the lesions’ joint intensity probability appears much smaller than those of normal brain tissues. The χ2χ2 random field theory is used to determine the significance of a detected lesion and provides a strict statistical analysis to exclude small-sized false-positive lesions. Experimental results show that the automatic segmentation of lesions is in high agreement with manual segmentation, and the χ2χ2 random-field-based statistical analysis greatly improves lesion segmentation results.
[Show abstract][Hide abstract] ABSTRACT: The topologically correct and geometrically accurate reconstruction of the cerebral cortex from magnetic resonance (MR) images is an important step in quantitative analysis of the human brain structure, e.g. in cortical thickness measurement studies. Limited resolution of MR images, noise, intensity inhomogeneities, and partial volume effects can all contribute to geometrical inaccuracies and topological errors in the model of cortical surfaces. For example, unresolved touching banks of gray matter (GM) in narrow sulci pose a particular challenge for an automated algorithm, requiring specific steps for the recovery of separating boundaries. We present a method for the automated reconstruction of the cortical compartment from MR images. The method is based on several partial differential equation (PDE) modelling stages. First, a potential field is computed in an electrostatic model with GM posing as an insulating dielectric layer surrounding a charged conductive white matter (WM) object. Second, geodesic distances from WM along the streamlines of the potential field are computed in a Eulerian framework PDE. Third, a digital skeleton surface separating GM sulcal banks is derived by finding shocks in the distance field. At the last stage, a geometric deformable model based on the level set PDE is used to reconstruct the outer cortical surface by advection along the gradient of the distance or potential field. The rule preserving the digital topology, and the skeleton of the distance field resolving fused adjacent banks in sulci, constrain the deformable model evolution. In addition, the deformable model may use the distance field as a constraint on thickness of the reconstructed cortical layer.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 01/2010; 2010:4278-83.
[Show abstract][Hide abstract] ABSTRACT: Morphometry of brain structures based on magnetic resonance imaging (MRI) data has become an important tool in neurobiology. Recent multicenter studies in neurodegenerative diseases raised the issue of the precision of volumetric measures, and their dependence on the scanner properties and imaging protocol. A large dataset consisting of 1073 MRI examinations in 843 subjects, acquired on 90 scanners at 58 sites, is analyzed here. A comprehensive set of image quality and content measures is used to describe the influence of the scanner hardware and imaging protocol on the variability of morphometric measures. Scanners equipped with array coils show a remarkable advantage over conventional coils in terms of image quality measures. The signal- and contrast-to-noise ratio in similar systems is equal or slightly better at 1.5 T than 3.0 T, while the white/grey matter tissue contrast is generally better on high-field systems. Repeated MRI investigations on the same scanner were available in 41 subjects, on different scanners in 172 subjects. The retest reliability of repeated volumetric measures under the same conditions was found as sufficient to track changes in longitudinal examinations in individual subjects. Using different acquisition conditions in the same subject, however, the variance of volumetric measures was up to 10 times greater. Two likely factors explaining this finding are scanner-dependent geometrical inaccuracies and differences in the white/grey matter tissue contrast.
[Show abstract][Hide abstract] ABSTRACT: Functional neuroimaging studies have reported that the neural correlates of retrieval success (old>new effects) are larger and more widespread in older than in young adults. In the present study we investigated whether this pattern of age-related 'over-recruitment' continues into advanced age. Using functional magnetic resonance imaging (fMRI), retrieval-related activity from two groups (N=18 per group) of older adults aged 84-96 years ('old-old') and 64-77 years ('young-old') was contrasted. Subjects studied a series of pictures, half of which were presented once, and half twice. At test, subjects indicated whether each presented picture was old or new. Recognition performance of the old-old subjects for twice-studied items was equivalent to that of the young-old subjects for once-studied items. Old>new effects common to the two groups were identified in several cortical regions, including medial and lateral parietal and prefrontal cortex. There were no regions where these effects were of greater magnitude in the old-old group, and thus no evidence of over-recruitment in this group relative to the young-old individuals. In one region of medial parietal cortex, effects were greater (and only significant) in the young-old group. The failure to find evidence of over-recruitment in the old-old subjects relative to the young-old group, despite their markedly poorer cognitive performance, suggests that age-related over-recruitment effects plateau in advanced age. The findings for the medial parietal cortex underscore the sensitivity of this cortical region to increasing age.
[Show abstract][Hide abstract] ABSTRACT: With the exception of APOE epsilon4 allele, the common genetic risk factors for sporadic Alzheimer's Disease (AD) are unknown.
We completed a genome-wide association study on 381 participants in the ADNI (Alzheimer's Disease Neuroimaging Initiative) study. Samples were genotyped using the Illumina Human610-Quad BeadChip. 516,645 unique Single Nucleotide Polymorphisms (SNPs) were included in the analysis following quality control measures. The genotype data and raw genetic data are freely available for download (LONI, http://www.loni.ucla.edu/ADNI/Data/). Two analyses were completed: a standard case-control analysis, and a novel approach using hippocampal atrophy measured on MRI as an objectively defined, quantitative phenotype. A General Linear Model was applied to identify SNPs for which there was an interaction between the genotype and diagnosis on the quantitative trait. The case-control analysis identified APOE and a new risk gene, TOMM40 (translocase of outer mitochondrial membrane 40), at a genome-wide significance level of < or =10(-6) (10(-11) for a haplotype). TOMM40 risk alleles were approximately twice as frequent in AD subjects as controls. The quantitative trait analysis identified 21 genes or chromosomal areas with at least one SNP with a p-value < or =10(-6), which can be considered potential "new" candidate loci to explore in the etiology of sporadic AD. These candidates included EFNA5, CAND1, MAGI2, ARSB, and PRUNE2, genes involved in the regulation of protein degradation, apoptosis, neuronal loss and neurodevelopment. Thus, we identified common genetic variants associated with the increased risk of developing AD in the ADNI cohort, and present publicly available genome-wide data. Supportive evidence based on case-control studies and biological plausibility by gene annotation is provided. Currently no available sample with both imaging and genetic data is available for replication.
Using hippocampal atrophy as a quantitative phenotype in a genome-wide scan, we have identified candidate risk genes for sporadic Alzheimer's disease that merit further investigation.
PLoS ONE 02/2009; 4(8):e6501. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The human brain cortex is a highly convoluted sheet of gray matter composed of folds (gyri) and fissures (sulci). Sulci serve as important macroscopic landmarks to distinguish different functional areas of the brain. The exact segmentation and identification of sulci is critical for human brain mapping studies that aim at finding correspondences between structures and their function. In this paper, a sulcus identification algorithm is introduced using shape, orientation, location, and neighborhood information. Experimental results demonstrate that the method is efficient and accurate.
[Show abstract][Hide abstract] ABSTRACT: The architectonic analysis of the human cerebral cortex is presently based on the examination of stained tissue sections. Recent progress in high-resolution magnetic resonance imaging (MRI) promotes the feasibility of an in vivo architectonic analysis. Since the exact relationship between the laminar fine-structure of a cortical MRI signal and histological cyto-and myeloarchitectonic staining patterns is not known, a quantitative study comparing high-resolution MRI to histological ground truth images is necessary for validating a future MRI based architectonic analysis. This communication describes an ongoing study comparing post mortem MR images to a myelin-stained histology of the brain cortex. After establishing a close spatial correspondence between histological sections and MRI using a slice-to-volume nonrigid registration algorithm, transcortical intensity profiles, extracted from both imaging modalities along curved trajectories of a Laplacian vector field, are compared via a cross-correlational analysis.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 01/2009; 2009:85-9.
[Show abstract][Hide abstract] ABSTRACT: The neocortical surface has a rich and complex structure comprised of folds (gyri) and fissures (sulci). Sulci are important macroscopic landmarks for orientation on the cortex. A precise segmentation and labeling of sulci is helpful in human brain mapping studies relating brain anatomy and function. Due to their structural complexity and inter-subject variability, this is considered as a non-trivial task. An automatic algorithm is proposed to accurately segment neocortical sulci: vertices of a white/gray matter interface mesh are classified under a Bayesian framework as belonging to gyral and sulcal compartments using information about their geodesic depth and local curvature. Then, vertices are collected into sulcal regions by a watershed-like growing method. Experimental results demonstrate that the method is accurate and robust.
Medical image analysis 09/2008; 12(4):442-51. · 3.09 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Complex shapes - such as the surface of the human brain - may be represented and analyzed in frequency space by means of a spherical harmonics transformation. A key step of the processing chain is introducing a suitable parametrization of the triangular mesh representing the brain surface. This problem corresponds to mapping a surface of topological genus zero on a unit sphere. An algorithm is described that produces an optimal combination of an area- and angle-preserving mapping. A multi-resolution scheme provides the robustness required to map the highly detailed and convoluted brain surface. More than 1000 datasets were successfully processed by this mature and robust approach.
Medical image analysis 07/2008; 12(3):291-9. · 3.09 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Diffuse lesions of the white matter of the human brain are common pathological findings in magnetic resonance images of elderly subjects. These lesions are typically caused by small vessel diseases (e.g., due to hypertension, diabetes), and related to cognitive decline. Because these lesions are inhomogeneous, unsharp, and faint, but show an intensity pattern that is different from the adjacent healthy tissue, a segmentation based on texture properties is proposed here. This method was successfully applied to a set of 116 image data sets of elderly subjects. Quantitative measures for the lesion load are derived that compare well with results from experts that visually rated lesions on a semiquantitative scale. Texture-based segmentation can be considered as a general method for lesion segmentation, and an outline for adapting this method to similar problems is presented.