Cortical Gray Matter Density Research Articles

Longitudinal evolution of neuropathological substrates of Alzheimer’s disease in obese patients

AbstractBackgroundObesity is a metabolic condition with increasing prevalence all over the world. Patients with a body mass index (BMI) higher than 30 are considered obese. Obesity is also a risk factor for chronic morbidities such as type 2 diabetes and may increase the risk of developing Alzheimer's disease (AD). Not much is known about longitudinal changes in Alzheimer’s pathology in these patients. We hypothesised that BMI would predict longitudinal pathological alterations derived from imaging parameters.Method252 participants (n=107 obese non‐diabetic patients with BMI>30) cognitively normal (n=80) and with mild cognitive impairment (n=172) were evaluated from the Alzheimer’s Disease Neuroimaging Initiative (Mean age = 73.6 years, SD = 8.0). All participants had two T1‐weighted MPRAGE MRI scans within two‐years (Mean gap=718 days, SD=107). Regional cortical thickness was measured on T1‐MPRAGE using FreeSurfer v.6.0. Individual gray matter density maps were computed using voxel‐based morphometry (VBM) and regional values were sampled in various cortical regions. Regional cortical thickness and gray matter density are expressed as delta values between baseline and followup (Value followup ‐ Value Baseline). Spearman’s correlation coefficients were calculated to assess the relationship between BMI and imaging biomarkers.ResultIn the whole cohort, we found that BMI is significantly negatively correlated with longitudinal changes in cortical thickness in anterior cingulate (ACC, p=0.0073, r=‐0.17) and posterior cingulate (PCC, p=0.0147, r=‐0.15) cortical thickness. We also found that BMI is significantly negatively correlated with longitudinal changes in frontal (p=0.0184, r=‐0.15), parietal (p=0.0057, r=‐0.18) and temporal (p=0.0141, r=‐0.16) gray matter density. When looking only at MCI participants, we found similar results with even stronger correlations. BMI is significantly negatively correlated with delta anterior cingulate (ACC, p=0.0008, r=‐0.25) and posterior cingulate (PCC, p=0.004, r=‐0.22) cortical thickness.ConclusionIn this cohort of obese and non‐obese participants cognitively normal and with MCI, we found that obesity was associated with a longitudinal 2‐years worsening of macrostructural changes. Higher BMI was associated with a higher reduction of cortical thickness and with a decreased gray matter density in several brain regions.

Regional gray matter abnormalities in pre-adolescent binge eating disorder: A voxel-based morphometry study

BackgroundBinge eating disorder (BED) is a pernicious psychiatric disorder which is linked with an array of multisystemic organ morbidity, broad psychiatric morbidity, and obesity. Despite behavioral markers often developing in early childhood, the neurobiological markers of early-onset BED remain understudied, and developmental pathophysiology remains poorly understood. Methods71 preadolescent children (aged 9–10-years) with BED and 74 age, BMI and developmentally matched control children were extracted from the 3.0 baseline (Year 0) release of the Adolescent Brain Cognitive Development (ABCD) Study. We investigated group differences in gray matter density (GMD) via voxel-based morphometry (VBM). We additionally performed region of interest analyses, assessing the association between GMD in nodes of the reward (orbitofrontal cortex; OFC) and inhibitory control (dorsolateral prefrontal cortex; dlPFC) networks, and parent-reported behavioral inhibition and approach tendencies. ResultsDiffuse elevations in cortical GMD were noted in those with BED, which spanned prefrontal, parietal, and temporal regions. No areas of reduced GMD were noted in those with BED. No alterations in subcortical GMD were noted. Brain-behavioral associations suggest a distinct and negative relationship between GMD in the OFC and dlPFC, respectively, and self-reported markers of hedonic behavioral approach tendencies. ConclusionsEarly-onset BED may be characterized by diffuse morphological abnormalities in gray matter density, suggesting alterations in cortical architecture which may reflect decreased synaptic pruning and arborization, or decreased myelinated fibers and therefore inter-regional afferents.

Prescribing cholinesterase inhibitors in mild cognitive impairment-Observations from the Alzheimer's Disease Neuroimaging Initiative.

IntroductionAnalyses of off‐label use of acetylcholinesterase inhibitors (AChEIs) in mild cognitive impairment (MCI) has produced mixed results. Post hoc analyses of observational cohorts, such as the Alzheimer's Disease Neuroimaging Initiative (ADNI), have reported deleterious effects in AChEI‐treated subjects (AChEI+). Here, we used neuroimaging biomarkers to determine whether AChEI+ subjects had a greater rate of neurodegeneration than untreated (AChEI–) subjects while accounting for baseline differences.MethodsWe selected 121 ADNI MCI AChEI+ subjects and 151 AChEI– subjects with a magnetic resonance imaging (MRI) scan; 82 AChEI+ and 110 AChEI– also had a fluorodeoxyglucose (FDG) scan. A subset (83 AChEI+ and 98 AChEI–) had cerebrospinal fluid (CSF) or amyloid positron emission tomography (PET) assessment for amyloid positivity. Linear regression models were used to compare the effect of treatment on changes in Mini‐Mental State Examination and Clinical Dementia Rating‐Sum of Boxes scores. We used standard regression in SPM (for baseline) and the SPM toolbox sandwich estimator, SwE (for longitudinal) for comparisons of AChEI+ and AChEI– FDG PET and MRI data.ResultsAt baseline, the AChEI+ group had significantly reduced cortical gray matter density (GMD) and more hypometabolism than AChEI– subjects. The greater rate of atrophy and hypometabolic changes over time in AChEI+ compared to AChEI– subjects did not survive correction for baseline differences. AChEI+ participants were more likely to be amyloid‐positive and have lower GMD and FDG standardized uptake value ratio than AChEI– at baseline. AChEI+ subjects showed greater atrophy over time, which remained significant after controlling for amyloid status.DiscussionOur data suggest that the observed differences in rates of cognitive decline, atrophy, and hypometabolism are likely the result of significant baseline differences between the groups. Furthermore, the data indicate no treatment effect of AChEI (positive of negative), rather that physicians prescribe AChEI to subjects who present with more severe clinical impairment. This alone may account for the negative effect seen previously in the ADNI population of AChEI use among MCI subjects.

Subcortical structural abnormalities in female neuromyelitis optica patients with neuropathic pain

Neuromyelitis optica (NMO) is a disease characterised by severe relapses of optic neuritis and longitudinally extensive transverse myelitis and it has a strong female predilection. Pain is one of the most typical symptom in NMO. However, few studies have been conducted to examine the neuropathic pain mechanism of NMO patients or gender-specific effects using magnetic resonance imaging technique. A total of 38 female patients with NMO, 28 with pain (NMOWP) and 10 without pain (NMOWoP), were classified using the Brief Pain Inventory (BPI); 22 healthy females were also recruited. We used the FSL Image Registration and Segmentation Toolbox (FIRST) for subcortical region volumes quantifications, and voxel-based morphometry analysis for cortical gray matter (GM) volume, to examine the brain morphology in NMOWP patients. In addition, correlation test between structural measurements of NMO patients and clinical indexes was also performed. The results showed: 1) no significant differences in cortical GM density between the NMOWP and NMOWoP groups; 2) significantly smaller hippocampus and pallidum volumes in the NMOWP group compared with the NMOWoP group; 3) significant negative correlation between the average BPI and volumes of the accumbens nucleus and thalamus in NMO patients. These results revealed that structural abnormality exists in NMO female patients who have pain, with significant implications for our understanding of the brain morphology in NMO patients with pain.

High-Dimensional Mapping of Cognition to the Brain Using Voxel-Based Morphometry and Subcortical Shape Analysis.

It is increasingly recognized that the complex functions of human cognition are not accurately represented by arbitrarily-defined anatomical brain regions. Given the considerable functional specialization within such regions, more fine-grained studies of brain structure could capture such localized associations. However, such analyses/studies in a large community-dwelling population are lacking. To perform a fine-mapping of cognitive ability to cortical and subcortical grey matter on magnetic resonance imaging (MRI). In 3,813 stroke-free and non-demented persons from the Rotterdam Study (mean age 69.1 (±8.8) years; 55.8% women) with cognitive assessments and brain MRI, we performed voxel-based morphometry and subcortical shape analysis on global cognition and separate tests that tapped into memory, information processing speed, fine motor speed, and executive function domains. We found that the different cognitive tests significantly associated with grey matter density in differential but also overlapping brain regions, primarily in the left hemisphere. Clusters of significantly associated voxels with global cognition were located within multiple anatomic regions: left amygdala, hippocampus, parietal lobule, superior temporal gyrus, insula and posterior temporal lobe. Subcortical shape analysis revealed associations primarily within the head and tail of the caudate nucleus, putamen, ventral part of the thalamus, and nucleus accumbens, more equally distributed among the left and right hemisphere. Within the caudate nucleus both positive (head) as well as negative (tail) associations were observed with global cognition. In a large population-based sample, we mapped cognitive performance to cortical and subcortical grey matter density using a hypothesis-free approach with high-dimensional neuroimaging. Leveraging the power of our large sample size, we confirmed well-known associations as well as identified novel brain regions related to cognition.

Effect of the SIRT1 gene on regional cortical grey matter density in the Han Chinese population.

Our previous genome-wide association study (CONVERGE sample) identified significant association between single nucleotide polymorphisms (SNPs) near the SIRT1 gene and major depressive disorder (MDD) in Chinese populations. To investigate whether SNPs across the SIRT1 gene locus affect regional grey matter density in the Han Chinese population. T1-weighted structural magnetic resonance imaging was conducted on 92 healthy participants from Eastern China. Grey matter was segmented from the image, which consisted of voxel-wise grey matter density. The effect of SIRT1 SNPs on grey matter density was determined by a multiple linear regression framework. SNP rs4746720 was significantly associated with grey matter density in two brain cortical regions: the orbital part of the right inferior frontal gyrus and the orbital part of the left inferior frontal gyrus (family-wise error-corrected P < 0.05; voxel-wise P < 0.001). Also, rs4746720 exceeded genome-wide significance in association with MDD in our CONVERGE sample (P = 3.32 × 10-08, odds ratio 1.161). Our results provided evidence for a potential role of the SIRT1 gene in the brain, implying a possible pathophysiological mechanism underlying susceptibility to MDD.

Distinguishing early and late brain aging from the Alzheimer's disease spectrum: consistent morphological patterns across independent samples

Alzheimer's disease (AD) is a debilitating age-related neurodegenerative disorder. Accurate identification of individuals at risk is complicated as AD shares cognitive and brain features with aging. We applied linked independent component analysis (LICA) on three complementary measures of gray matter structure: cortical thickness, area and gray matter density of 137 AD, 78 mild (MCI) and 38 subjective cognitive impairment patients, and 355 healthy adults aged 18–78 years to identify dissociable multivariate morphological patterns sensitive to age and diagnosis. Using the lasso classifier, we performed group classification and prediction of cognition and age at different age ranges to assess the sensitivity and diagnostic accuracy of the LICA patterns in relation to AD, as well as early and late healthy aging. Three components showed high sensitivity to the diagnosis and cognitive status of AD, with different relationships with age: one reflected an anterior-posterior gradient in thickness and gray matter density and was uniquely related to diagnosis, whereas the other two, reflecting widespread cortical thickness and medial temporal lobe volume, respectively, also correlated significantly with age. Repeating the LICA decomposition and between-subject analysis on ADNI data, including 186 AD, 395 MCI and 220 age-matched healthy controls, revealed largely consistent brain patterns and clinical associations across samples. Classification results showed that multivariate LICA-derived brain characteristics could be used to predict AD and age with high accuracy (area under ROC curve up to 0.93 for classification of AD from controls). Comparison between classifiers based on feature ranking and feature selection suggests both common and unique feature sets implicated in AD and aging, and provides evidence of distinct age-related differences in early compared to late aging.

Preferential susceptibility of limbic cortices to microstructural damage in temporal lobe epilepsy: A quantitative T1 mapping study

The majority of MRI studies in temporal lobe epilepsy (TLE) have utilized morphometry to map widespread cortical alterations. Morphological markers, such as cortical thickness or grey matter density, reflect combinations of biological events largely driven by overall cortical geometry rather than intracortical tissue properties. Because of its sensitivity to intracortical myelin, quantitative measurement of longitudinal relaxation time (qT1) provides and an in vivo proxy for cortical microstructure. Here, we mapped the regional distribution of qT1 in a consecutive cohort of 24 TLE patients and 20 healthy controls. Compared to controls, patients presented with a strictly ipsilateral distribution of qT1 increases in temporopolar, parahippocampal and orbitofrontal cortices. Supervised statistical learning applied to qT1 maps could lateralize the seizure focus in 92% of patients. Intracortical profiling of qT1 along streamlines perpendicular to the cortical mantle revealed marked effects in upper levels that tapered off at the white matter interface. Findings remained robust after correction for cortical thickness and interface blurring, suggesting independence from previously reported morphological anomalies in this disorder. Mapping of qT1 along hippocampal subfield surfaces revealed marked increases in anterior portions of the ipsilateral CA1-3 and DG that were also robust against correction for atrophy. Notably, in operated patients, qualitative histopathological analysis of myelin stains in resected hippocampal specimens confirmed disrupted internal architecture and fiber organization. Both hippocampal and neocortical qT1 anomalies were more severe in patients with early disease onset. Finally, analysis of resting-state connectivity from regions of qT1 increases revealed altered intrinsic functional network embedding in patients, particularly to prefrontal networks. Analysis of qT1 suggests a preferential susceptibility of ipsilateral limbic cortices to microstructural damage, possibly related to disrupted myeloarchitecture. These alterations may reflect atypical neurodevelopment and affect the integrity of fronto-limbic functional networks.

Classification of brain disease in magnetic resonance images using two-stage local feature fusion.

BackgroundMany classification methods have been proposed based on magnetic resonance images. Most methods rely on measures such as volume, the cerebral cortical thickness and grey matter density. These measures are susceptible to the performance of registration and limited in representation of anatomical structure. This paper proposes a two-stage local feature fusion method, in which deformable registration is not desired and anatomical information is represented from moderate scale.MethodsKeypoints are firstly extracted from scale-space to represent anatomical structure. Then, two kinds of local features are calculated around the keypoints, one for correspondence and the other for representation. Scores are assigned for keypoints to quantify their effect in classification. The sum of scores for all effective keypoints is used to determine which group the test subject belongs to.ResultsWe apply this method to magnetic resonance images of Alzheimer's disease and Parkinson's disease. The advantage of local feature in correspondence and representation contributes to the final classification. With the help of local feature (Scale Invariant Feature Transform, SIFT) in correspondence, the performance becomes better. Local feature (Histogram of Oriented Gradient, HOG) extracted from 16×16 cell block obtains better results compared with 4×4 and 8×8 cell block.DiscussionThis paper presents a method which combines the effect of SIFT descriptor in correspondence and the representation ability of HOG descriptor in anatomical structure. This method has the potential in distinguishing patients with brain disease from controls.

Distinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disorders.

The brain underpinnings of schizophrenia and bipolar disorders are multidimensional, reflecting complex pathological processes and causal pathways, requiring multivariate techniques to disentangle. Furthermore, little is known about the complementary clinical value of brain structural phenotypes when combined with data on cognitive performance and genetic risk. Using data-driven fusion of cortical thickness, surface area, and gray matter density maps (GMD), we found six biologically meaningful patterns showing strong group effects, including four statistically independent multimodal patterns reflecting co-occurring alterations in thickness and GMD in patients, over and above two other independent patterns of widespread thickness and area reduction. Case-control classification using cognitive scores alone revealed high accuracy, and adding imaging features or polygenic risk scores increased performance, suggesting their complementary predictive value with cognitive scores being the most sensitive features. Multivariate pattern analyses reveal distinct patterns of brain morphology in mental disorders, provide insights on the relative importance between brain structure, cognitive and polygenetic risk score in classification of patients, and demonstrate the importance of multivariate approaches in studying the pathophysiological substrate of these complex disorders.

Severity of alcohol dependence is negatively related to hypothalamic and prefrontal cortical gray matter density in heavy drinking smokers

ABSTRACTBackground: While research has examined brain structure in individuals who use alcohol or nicotine, heavy drinking smokers comprise a unique subpopulation of substance users for whom less is known about the relationship between alcohol or nicotine use and structural brain abnormalities. Objectives: The present study examined gray matter morphometry in a sample of 39 heavy drinking smokers (24 males, 15 females) in relation to alcohol and nicotine dependence and quantity of use. Methods: Traditional voxel-based morphometry techniques were employed for preprocessing of imaging data. One multiple regression analysis for alcohol and nicotine dependence severity and another for alcohol and nicotine quantity of use were conducted, while controlling for age, gender, and total intracranial volume (ICV). Results: Alcohol dependence severity was significantly negatively associated with gray matter density in the hypothalamus (p < 0.001, uncorrected) and the right superior frontal gyrus (p < 0.001, uncorrected), while controlling for nicotine dependence severity, age, gender, and ICV. There were no significant relationships observed with respect to nicotine dependence severity, the quantity of alcohol use, or the quantity of nicotine use variables and gray matter density. Conclusions: These findings suggest that within heavy drinking smokers, alcohol dependence severity is significantly related to alterations in brain structure, while this effect is not seen for the quantity of alcohol or nicotine use, or severity of nicotine dependence. The current findings help clarify the contribution of alcohol and nicotine effects on brain structure, which could aid in understanding their neurocognitive consequences in heavy drinking smokers.

The selective anatomical vulnerability of ALS: ‘disease-defining’ and ‘disease-defying’ brain regions

A large multiparametric MRI study has been undertaken to evaluate anatomical patterns of basal ganglia, white matter and cortical grey matter involvement in ALS. Unaffected brain regions are mapped in patients with significant disability. Multiple white matter diffusivity measures, cortical grey matter density alterations, basal ganglia volumes and subcortical grey matter atrophy patterns are evaluated. Results demonstrated a strikingly selective anatomical vulnerability pattern in ALS that preferentially affects specific grey matter structures, commissural white matter tracts and basal ganglia regions, suggestive of networkwise neurodegeneration in ALS. In conclusion, ALS pathology exhibits predilection for selective and inter-connected anatomical sites that can be comprehensively characterized in vivo by multiparametric neuroimaging. The systematic characterization of unaffected brain regions in ALS has implications for the development of classifier analyses and elucidation of disease biology. The involvement and sparing of contiguous brain regions raises important pathophysiological, phylogenetic and ontogenetic questions regarding ALS pathogenesis and disease spread.

Brain connectivity in normally developing children and adolescents

The developing human brain undergoes an astonishing sequence of events that continuously shape the structural and functional brain connectivity. Distinct regional variations in the timelines of maturational events (synaptogenesis and synaptic pruning) occurring at the synaptic level are reflected in brain measures at macroscopic resolution (cortical thickness and gray matter density). Interestingly, the observed brain changes coincide with cognitive milestones suggesting that the changing scaffold of brain circuits may subserve cognitive development. Recent advances in connectivity analysis propelled by graph theory have allowed, on one hand, the investigation of maturational changes in global organization of structural and functional brain networks; and on the other hand, the exploration of specific networks within the context of global brain networks. An emerging picture from several connectivity studies is a system-level rewiring that constantly refines the connectivity of the developing brain.

Cerebral volumetric abnormalities in Neurofibromatosis type 1: associations with parent ratings of social and attention problems, executive dysfunction, and autistic mannerisms.

BackgroundNeurofibromatosis type 1 (NF1) is a single-gene neurodevelopmental disorder, in which social and cognitive problems are highly prevalent. Several commonly observed central nervous system (CNS) abnormalities in NF1 might underlie these social and cognitive problems. Cerebral volumetric abnormalities are among the most consistently observed CNS abnormalities in NF1. This study investigated whether differences were present between NF1 patients and healthy controls (HC) in volumetric measures of cortical and subcortical brain regions and whether differential associations existed for NF1 patients and HC between the volumetric measures and parent ratings of social skills, attention problems, social problems, autistic mannerisms, and executive dysfunction.MethodsFifteen NF1 patients (mean age 12.9 years, SD 2.6) and 18 healthy controls (HC, mean age 13.8 years, SD 3.6) underwent 3 T MRI scanning. Segmentation of cortical gray and white matter, as well as volumetry of subcortical nuclei, was carried out. Voxel-based morphometry was performed to assess cortical gray matter density. Correlations were calculated, for NF1-patients and HC separately, between MRI parameters and scores on selected dimensions of the following behavior rating scales: the Social Skills Rating System, the Child Behavior Checklist, the Social Responsiveness Scale, the Behavior Rating Inventory of Executive Functioning, and the Dysexecutive Questionnaire.ResultsAfter correction for age, sex, and intracranial volume, larger volumes of all subcortical regions were found in NF1 patients compared to controls. Patients further showed decreased gray matter density in midline regions of the frontal and parietal lobes and larger total white matter volume. Significantly more social and attention problems, more autistic mannerisms, and poorer executive functioning were reported for NF1 patients compared to HC. In NF1 patients, larger left putamen volume and larger total white matter volume were associated with more social problems and poorer executive functioning, larger right amygdala volume with poorer executive functioning and autistic mannerisms, and smaller precentral gyrus gray matter density was associated with more social problems. In controls, only significant negative correlations were observed: larger volumes (and greater gray matter density) were associated with better outcomes.ConclusionsWidespread volumetric differences between patients and controls were found in cortical and subcortical brain regions. In NF1 patients but not HC, larger volumes were associated with poorer behavior ratings.

Abnormalities in cortical gray matter density in borderline personality disorder

BackgroundBorderline personality disorder (BPD) is a chronic condition with a strong impact on patients’ affective, cognitive and social functioning. Neuroimaging techniques offer invaluable tools to understand the biological substrate of the disease. We aimed to investigate gray matter alterations over the whole cortex in a group of Borderline Personality Disorder (BPD) patients compared to healthy controls (HC). MethodsMagnetic resonance-based cortical pattern matching was used to assess cortical gray matter density (GMD) in 26 BPD patients and in their age- and sex-matched HC (age: 38±11; females: 16, 61%). ResultsBPD patients showed widespread lower cortical GMD compared to HC (4% difference) with peaks of lower density located in the dorsal frontal cortex, in the orbitofrontal cortex, the anterior and posterior cingulate, the right parietal lobe, the temporal lobe (medial temporal cortex and fusiform gyrus) and in the visual cortex (P<0.005). Our BPD subjects displayed a symmetric distribution of anomalies in the dorsal aspect of the cortical mantle, but a wider involvement of the left hemisphere in the mesial aspect in terms of lower density. A few restricted regions of higher density were detected in the right hemisphere. All regions remained significant after correction for multiple comparisons via permutation testing. ConclusionsBPD patients feature specific morphology of the cerebral structures involved in cognitive and emotional processing and social cognition/mentalization, consistent with clinical and functional data.

Event time analysis of longitudinal neuroimage data

This paper presents a method for the statistical analysis of the associations between longitudinal neuroimaging measurements, e.g., of cortical thickness, and the timing of a clinical event of interest, e.g., disease onset. The proposed approach consists of two steps, the first of which employs a linear mixed effects (LME) model to capture temporal variation in serial imaging data. The second step utilizes the extended Cox regression model to examine the relationship between time-dependent imaging measurements and the timing of the event of interest. We demonstrate the proposed method both for the univariate analysis of image-derived biomarkers, e.g., the volume of a structure of interest, and the exploratory mass-univariate analysis of measurements contained in maps, such as cortical thickness and gray matter density. The mass-univariate method employs a recently developed spatial extension of the LME model. We applied our method to analyze structural measurements computed using FreeSurfer, a widely used brain Magnetic Resonance Image (MRI) analysis software package. We provide a quantitative and objective empirical evaluation of the statistical performance of the proposed method on longitudinal data from subjects suffering from Mild Cognitive Impairment (MCI) at baseline.

The structure of the corpus callosum in obsessive compulsive disorder

Abnormal brain connectivity has recently been reported in obsessive compulsive disorder (OCD). However, structural differences in the corpus callosum (CC), the primary structure connecting the two hemispheres, have not been extensively studied. In this case-control study, we recruited 30 patients with OCD and 30 healthy control subjects carefully matched for age, sex and handedness. Combining surface-based mesh-modeling and voxel-based morphometry (VBM), we compared callosal thickness and white matter (WM) density in patients and controls. We investigated associations between callosal structure and cortical gray matter (GM) density, and we related CC measures to neuropsychological performance in OCD. OCD patients showed small anterior and posterior callosal regions compared to healthy control subjects. In the OCD group, anterior callosal thickness was positively correlated with GM density of the right mid-dorso-lateral prefrontal (BA 9/46) area, while posterior callosal thickness was positively correlated with GM density in the left supramarginal gyrus (BA 40). Moreover, posterior callosal WM density was positively correlated with verbal memory, visuo-spatial memory, verbal fluency, and visuo-spatial reasoning performances. Callosal attributes were related to GM density in cortical areas innervated by the CC, and were also related to performance in cognitive domains impaired in the disorder. The CC may therefore be integrally involved in OCD.

The structure of the corpus callosum in obsessive compulsive disorder

Abnormal brain connectivity has recently been reported in obsessive compulsive disorder (OCD). However, structural differences in the corpus callosum (CC), the primary structure connecting the two hemispheres, have not been extensively studied. In this case-control study, we recruited 30 patients with OCD and 30 healthy subjects carefully matched for age, sex and handedness. Combining surface-based mesh-modeling and voxel-based morphometry (VBM), we compared callosal thickness and white matter (WM) density in patients and controls. We investigated associations between callosal structure and cortical gray matter (GM) density, and we related CC measures to neuropsychological performance in OCD. OCD patients showed small anterior and posterior callosal regions compared to healthy subjects. In the OCD group, anterior callosal thickness was positively correlated with GM density in the right mid-dorsolateral prefrontal (BA 9/46) area, while posterior callosal thickness was positively correlated with GM density in the left supramarginal (BA 40). Moreover, posterior callosal WM density was positively correlated with verbal memory, visuo-spatial memory, verbal fluency, and visuo-spatial reasoning performance. Callosal attributes were related to GM density in cortical areas innervated by the CC, and were also related to performance in cognitive areas impaired in the disorder. The CC may therefore be integrally involved in OCD.

Cortical thickness and voxel-based morphometry in depressed elderly

This is the first study to examine concurrently cortical thickness and voxel-based morphometric (VBM) abnormalities in patients with major depressive disorder (MDD). In the current study we set out to investigate depressed elderly patients to determine whether a previous depression is related to neurobiological abnormalities in older age. Cortical thickness measures and VBM were applied to the same magnetic resonance imaging data set of 28 female elderly subjects with MDD and 38 age-matched control subjects. Two principal findings emerge from this study. First, no effect of illness on cortical thickness or gray matter density measurements was found. Moreover, life time depression, severity of illness and the number of depressive episodes were not associated with neurobiological abnormalities in older age in our patient group. Second, a diffuse pattern of highly significant age effects was found in cortical thickness as well as in the VBM measurements in the same areas, irrespective of diagnosis. In contrast to most findings of the literature to date, the results from this study indicate that lifetime depression as well as current state does not seem to influence brain structure in depressed female elderly.

Global and local morphometric differences in recently abstinent methamphetamine-dependent individuals

Methamphetamine (MA) is associated with behavioral and cognitive deficits that may be related to macrostructural abnormalities. Quantitative anatomical comparisons between controls and methamphetamine-dependent individuals have produced conflicting results. We examined local and global differences in brain structure in 61 abstinent methamphetamine-dependent individuals and 44 controls with voxel-based morphometry and tissue segmentation. We related regional differences in gray matter density and whole brain segmentation volumes to performance on a behavioral measure of impulsivity and group membership using multiple linear regression. Within the MA group, we related cortical and subcortical gray matter density to length of abstinence. Controls had greater density relative to MA in bilateral insula and left middle frontal gyrus. Impulsivity was higher in the MA group and, within all subjects, impulsivity was positively correlated with gray matter density in posterior cingulate cortex and ventral striatum and negatively correlated in left superior frontal gyrus. Length of abstinence from MA was associated with greater amygdalar density. Earlier age of first use of MA (in subjects who initiated use before age 21) was associated with smaller intracranial volume. The findings are consistent with multiple possible mechanisms including neuroadaptations due to addictive behavior, neuroinflammation as well as dopaminergic and serotonergic neurotoxicity.