Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

White matter abnormalities associated with Alzheimer's disease and mild cognitive impairment: A critical review of MRI studies

In this article, the authors aim to present a critical review of recent MRI studies addressing white matter (WM) abnormalities in Alzheimer's disease (AD) and mild cognitive impairment (MCI), by searching PubMed and reviewing MRI studies evaluating subjects with AD or MCI using WM volumetric methods, diffusion tensor imaging and assessment of WM hyperintensities. Studies have found that, compared with healthy controls, AD and MCI samples display WM volumetric reductions and diffusion tensor imaging findings suggestive of reduced WM integrity. These changes affect complex networks relevant to episodic memory and other cognitive processes, including fiber connections that directly link medial temporal structures and the corpus callosum. Abnormalities in cortico-cortical and cortico-subcortical WM interconnections are associated with an increased risk of progression from MCI to dementia. It can be concluded that WM abnormalities are detectable in early stages of AD and MCI. Degeneration of WM networks causes disconnection among neural cells and the degree of such changes is related to cognitive decline. © 2013 2013 Expert Reviews Ltd.

Voxelwise evaluation of white matter volumes in first-episode psychosis

The occurrence of white matter (WM) abnormalities in psychotic disorders has been suggested by several studies investigating brain pathology and diffusion tensor measures, but evidence assessing regional WM morphometry is still scarce and conflicting. In the present study, 122 individuals with first-episode psychosis (FEP) (62 fulfilling criteria for schizophrenia/schizophreniform disorder, 26 psychotic bipolar I disorder, and 20 psychotic major depressive disorder) underwent magnetic resonance imaging, as well as 94 epidemiologically recruited controls. Images were processed with the Statistical Parametric Mapping (SPM2) package, and voxel-based morphometry was used to compare groups (t-test) and subgroups (ANOVA). Initially, no regional WM abnormalities were observed when both groups (overall FEP group versus controls) and subgroups (i.e., schizophrenia/schizophreniform, psychotic bipolar I disorder, psychotic depression, and controls) were compared. However, when the voxelwise analyses were repeated excluding subjects with comorbid substance abuse or dependence, the resulting statistical maps revealed a focal volumetric reduction in right frontal WM, corresponding to the right middle frontal gyral WM/third subcomponent of the superior longitudinal fasciculus, in subjects with schizophrenia/schizophreniform disorder (n = 40) relative to controls (n = 89). Our results suggest that schizophrenia/schizophreniform disorder is associated with right frontal WM volume decrease at an early course of the illness. (c) 2012 Elsevier Ireland Ltd. All rights reserved.

Can neuroimaging be used as a support to diagnosis of borderline personality disorder? An approach based on computational neuroanatomy and machine learning

Several recent studies in literature have identified brain morphological alterations associated to Borderline Personality Disorder (BPD) patients. These findings are reported by studies based on voxel-based-morphometry analysis of structural MRI data, comparing mean gray-matter concentration between groups of BPD patients and healthy controls. On the other hand, mean differences between groups are not informative about the discriminative value of neuroimaging data to predict the group of individual subjects. In this paper, we go beyond mean differences analyses, and explore to what extent individual BPD patients can be differentiated from controls (25 subjects in each group), using a combination of automated-morphometric tools for regional cortical thickness/volumetric estimation and Support Vector Machine classifier. The approach included a feature selection step in order to identify the regions containing most discriminative information. The accuracy of this classifier was evaluated using the leave-one-subject-out procedure. The brain regions indicated as containing relevant information to discriminate groups were the orbitofrontal, rostral anterior cingulate, posterior cingulate, middle temporal cortices, among others. These areas, which are distinctively involved in emotional and affect regulation of BPD patients, were the most informative regions to achieve both sensitivity and specificity values of 80% in SVM classification. The findings suggest that this new methodology can add clinical and potential diagnostic value to neuroimaging of psychiatric disorders. (C) 2012 Elsevier Ltd. All rights reserved.

ON THE MERITS OF VOXEL-BASED MORPHOMETRIC PATH-ANALYSIS FOR INVESTIGATING VOLUMETRIC MEDIATION OF A TOXICANT'S INFLUENCE ON COGNITIVE FUNCTION

We previously showed that lifetime cumulative lead dose, measured as lead concentration in the tibia bone by X-ray fluorescence, was associated with persistent and progressive declines in cognitive function and with decreases in MRI-based brain volumes in former lead workers. Moreover, larger region-specific brain volumes were associated with better cognitive function. These findings motivated us to explore a novel application of path analysis to evaluate effect mediation. Voxel-wise path analysis, at face value, represents the natural evolution of voxel-based morphometry methods to answer questions of mediation. Application of these methods to the former lead worker data demonstrated potential limitations in this approach where there was a tendency for results to be strongly biased towards the null hypothesis (lack of mediation). Moreover, a complimentary analysis using anatomically-derived regions of interest volumes yielded opposing results, suggesting evidence of mediation. Specifically, in the ROI-based approach, there was evidence that the association of tibia lead with function in three cognitive domains was mediated through the volumes of total brain, frontal gray matter, and/or possibly cingulate. A simulation study was conducted to investigate whether the voxel-wise results arose from an absence of localized mediation, or more subtle defects in the methodology. The simulation results showed the same null bias evidenced as seen in the lead workers data. Both the lead worker data results and the simulation study suggest that a null-bias in voxel-wise path analysis limits its inferential utility for producing confirmatory results.

DTI and VBM reveal white matter changes without associated gray matter changes in patients with idiopathic restless legs syndrome

BACKGROUND AND PURPOSE We evaluated cerebral white and gray matter changes in patients with iRLS in order to shed light on the pathophysiology of this disease. METHODS Twelve patients with iRLS were compared to 12 age- and sex-matched controls using whole-head diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) techniques. Evaluation of the DTI scans included the voxelwise analysis of the fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). RESULTS Diffusion tensor imaging revealed areas of altered FA in subcortical white matter bilaterally, mainly in temporal regions as well as in the right internal capsule, the pons, and the right cerebellum. These changes overlapped with changes in RD. Voxel-based morphometry did not reveal any gray matter alterations. CONCLUSIONS We showed altered diffusion properties in several white matter regions in patients with iRLS. White matter changes could mainly be attributed to changes in RD, a parameter thought to reflect altered myelination. Areas with altered white matter microstructure included areas in the internal capsule which include the corticospinal tract to the lower limbs, thereby supporting studies that suggest changes in sensorimotor pathways associated with RLS.

Evidence of altered prefrontal-thalamic circuitry in schizophrenia: An optimised diffusion MRI study

MRI diffusion tensor imaging (DTI), optimized for measuring the trace of the diffusion tensor, was used to investigate microstructural changes in the brains of 12 individuals with schizophrenia compared with 12 matched control subjects. To control for the effects of anatomic variation between subject groups, all participants' diffusion images were non-linearly registered to standard anatomical space. Significant statistical differences in mean diffusivity (MD) measures between the two groups were determined on a pixel-by-pixel basis, using Gaussian random field theory. We found significantly elevated MD measures within temporal, parietal and prefrontal cortical regions in the schizophrenia group (P > 0.001), especially within the medial frontal gyrus and anterior cingulate. The dorsal medial and anterior nucleus of the thalamus, including the caudate, also exhibited significantly increased MD in the schizophrenia group (P > 0.001). This study has shown for the first time that MD measures offer an alternative strategy for investigating altered prefrontal-thalamic circuitry in schizophrenia. (c) 2006 Elsevier Inc. All rights reserved.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

Neuroreceptor availability and cerebral morphology in human obesity

Obesity is a major challenge to human health worldwide. Little is known about the brain mechanisms that are associated with overeating and obesity in humans. In this project, multimodal neuroimaging techniques were utilized to study brain neurotransmission and anatomy in obesity. Bariatric surgery was used as an experimental method for assessing whether the possible differences between obese and non-obese individuals change following the weight loss. This could indicate whether obesity-related altered neurotransmission and cerebral atrophy are recoverable or whether they represent stable individual characteristics. Morbidly obese subjects (BMI ≥ 35 kg/m2) and non-obese control subjects (mean BMI 23 kg/m2) were studied with positron emission tomography (PET) and magnetic resonance imaging (MRI). In the PET studies, focus was put on dopaminergic and opioidergic systems, both of which are crucial in the reward processing. Brain dopamine D2 receptor (D2R) availability was measured using [11C]raclopride and µ-opioid receptor (MOR) availability using [11C]carfentanil. In the MRI studies, voxel-based morphometry (VBM) of T1-weighted MRI images was used, coupled with diffusion tensor imaging (DTI). Obese subjects underwent bariatric surgery as their standard clinical treatment during the study. Preoperatively, morbidly obese subjects had significantly lower MOR availability but unaltered D2R availability in several brain regions involved in reward processing, including striatum, insula, and thalamus. Moreover, obesity disrupted the interaction between the MOR and D2R systems in ventral striatum. Bariatric surgery and concomitant weight loss normalized MOR availability in the obese, but did not influence D2R availability in any brain region. Morbidly obese subjects had also significantly lower grey and white matter densities globally in the brain, but more focal changes were located in the areas associated with inhibitory control, reward processing, and appetite. DTI revealed also signs of axonal damage in the obese in corticospinal tracts and occipito-frontal fascicles. Surgery-induced weight loss resulted in global recovery of white matter density as well as more focal recovery of grey matter density among obese subjects. Altogether these results show that the endogenous opioid system is fundamentally linked to obesity. Lowered MOR availability is likely a consequence of obesity and may mediate maintenance of excessive energy uptake. In addition, obesity has adverse effects on brain structure. Bariatric surgery however reverses MOR dysfunction and recovers cerebral atrophy. Understanding the opioidergic contribution to overeating and obesity is critical for developing new psychological or pharmacological treatments for obesity. The actual molecular mechanisms behind the positive change in structure and neurotransmitter function still remain unclear and should be addressed in the future research.

Infratentorial Gray Matter Atrophy And Excess In Primary Craniocervical Dystonia.

Primary craniocervical dystonia (CCD) is generally attributed to functional abnormalities in the cortico-striato-pallido-thalamocortical loops, but cerebellar pathways have also been implicated in neuroimaging studies. Hence, our purpose was to perform a volumetric evaluation of the infratentorial structures in CCD. We compared 35 DYT1/DYT6 negative patients with CCD and 35 healthy controls. Cerebellar volume was evaluated using manual volumetry (DISPLAY software) and infratentorial volume by voxel based morphometry of gray matter (GM) segments derived from T1 weighted 3 T MRI using the SUIT tool (SPM8/Dartel). We used t-tests to compare infratentorial volumes between groups. Cerebellar volume was (1.14 ± 0.17) × 10(2) cm(3) for controls and (1.13 ± 0.14) × 10(2) cm(3) for patients; p = 0.74. VBM demonstrated GM increase in the left I-IV cerebellar lobules and GM decrease in the left lobules VI and Crus I and in the right lobules VI, Crus I and VIIIb. In a secondary analysis, VBM demonstrated GM increase also in the brainstem, mostly in the pons. While gray matter increase is observed in the anterior lobe of the cerebellum and in the brainstem, the atrophy is concentrated in the posterior lobe of the cerebellum, demonstrating a differential pattern of infratentorial involvement in CCD. This study shows subtle structural abnormalities of the cerebellum and brainstem in primary CCD.

Proteome analysis of schizophrenia patients Wernicke's area reveals an energy metabolism dysregulation

Background: Schizophrenia is likely to be a consequence of DNA alterations that, together with environmental factors, will lead to protein expression differences and the ultimate establishment of the illness. The superior temporal gyrus is implicated in schizophrenia and executes functions such as the processing of speech, language skills and sound processing. Methods: We performed an individual comparative proteome analysis using two-dimensional gel electrophoresis of 9 schizophrenia and 6 healthy control patients' left posterior superior temporal gyrus (Wernicke's area - BA22p) identifying by mass spectrometry several protein expression alterations that could be related to the disease. Results: Our analysis revealed 11 downregulated and 14 upregulated proteins, most of them related to energy metabolism. Whereas many of the identified proteins have been previously implicated in schizophrenia, such as fructose-bisphosphate aldolase C, creatine kinase and neuron-specific enolase, new putative disease markers were also identified such as dihydrolipoyl dehydrogenase, tropomyosin 3, breast cancer metastasis-suppressor 1, heterogeneous nuclear ribonucleoproteins C1/C2 and phosphate carrier protein, mitochondrial precursor. Besides, the differential expression of peroxiredoxin 6 (PRDX6) and glial fibrillary acidic protein (GFAP) were confirmed by western blot in schizophrenia prefrontal cortex. Conclusion: Our data supports a dysregulation of energy metabolism in schizophrenia as well as suggests new markers that may contribute to a better understanding of this complex disease.

Striatal volume abnormalities in treatment-naive patients diagnosed with pediatric major depressive disorder

Objective: The striatum, including the putamen and caudate, plays an important role in executive and emotional processing and may be involved in the pathophysiology of mood disorders. Few studies have examined structural abnormalities of the striatum in pediatric major depressive disorder (MDD) patients. We report striatal volume abnormalities in medication-naive pediatric MDD compared to healthy comparison subjects. Method: Twenty seven medication-naive pediatric Diagnostic and Statistical Manual of Mental Disorders, 4(th) edition (DSM-IV) MDD and 26 healthy comparison subjects underwent volumetric magnetic resonance imaging (MRI). The putamen and caudate volumes were traced manually by a blinded rater, and the patient and control groups were compared using analysis of covariance adjusting for age, sex, intelligence quotient, and total brain volumes. Results: MDD patients had significantly smaller right striatum (6.0% smaller) and right caudate volumes (7.4% smaller) compared to the healthy subjects. Left caudate volumes were inversely correlated with severity of depression in MDD subjects. Age was inversely correlated with left and right putamen volumes in MDD patients but not in the healthy subjects. Conclusions: These findings provide fresh evidence for abnormalities in the striatum of medication-naive pediatric MDD patients and suggest the possible involvement of the striatum in the pathophysiology of MDD.

Mapping cortical change in Alzheimer's disease, brain development, and schizophrenia

This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.

Age-related gray matter volume changes in the brain during non-elderly adulthood

Previous magnetic resonance imaging (MRI) studies described consistent age-related gray matter (GM) reductions in the fronto-parietal neocortex, insula and cerebellum in elderly subjects, but not as frequently in limbic/paralimbic structures. However, it is unclear whether such features are already present during earlier stages of adulthood, and if age-related GM changes may follow non-linear patterns at such age range. This voxel-based morphometry study investigated the relationship between GM volumes and age specifically during non-elderly life (18-50 years) in 89 healthy individuals (48 males and 41 females). Voxelwise analyses showed significant (p < 0.05, corrected) negative correlations in the right prefrontal cortex and left cerebellum, and positive correlations (indicating lack of GM loss) in the medial temporal region, cingulate gyrus, insula and temporal neocortex. Analyses using ROI masks showed that age-related dorsolateral prefrontal volume decrements followed non-linear patterns, and were less prominent in females compared to males at this age range. These findings further support for the notion of a heterogeneous and asynchronous pattern of age-related brain morphometric changes, with region-specific non-linear features. (C) 2009 Elsevier Inc. All rights reserved.

Volume reduction of the corpus callosum and its relationship with deficits in interhemispheric transfer of information in recent-onset psychosis

The present study aimed to investigate the presence of corpus callosum (CC) volume deficits in a population-based recent-onset psychosis (ROP) sample, and whether CC volume relates to interhemispheric communication deficits. For this purpose, we used voxel-based morphometry comparisons of magnetic resonance imaging data between ROP (n = 122) and healthy control (n = 94) subjects. Subgroups (38 ROP and 39 controls) were investigated for correlations between CC volumes and performance on the Crossed Finger Localization Test (CFLT). Significant CC volume reductions in ROP subjects versus controls emerged after excluding substance misuse and non-right-handedness. CC reductions retained significance in the schizophrenia subgroup but not in affective psychoses subjects. There were significant positive correlations between CC volumes and CFLT scores in ROP subjects, specifically in subtasks involving interhemispheric communication. From these results, we can conclude that CC volume reductions are present in association with ROP. The relationship between such deficits and CFLT performance suggests that interhemispheric communication impairments are directly linked to CC abnormalities in ROP. (C) 2010 Elsevier Ireland Ltd. All rights reserved.