Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images

Novel findings from 2,838 Adult Brains on Sex Differences in Gray Matter Brain Volume

There is still disagreement among studies with respect to the magnitude, location, and direction of sex differences of local gray matter volume (GMV) in the human brain. Here, we applied a state-of-the-art technique examining GMV in a well-powered sample (n = 2,838) validating effects in two independent general-population cohorts, age range 21-90 years, measured using the same MRI scanner. More GMV in women than in men was prominent in medial and lateral prefrontal areas, the superior temporal sulcus, the posterior insula, and orbitofrontal cortex. In contrast, more GMV in men than in women was detected in subcortical temporal structures, such as the amygdala, hippocampus, temporal pole, fusiform gyrus, visual primary cortex, and motor areas (premotor cortex, putamen, anterior cerebellum). The findings in this large-scale study may clarify previous inconsistencies and contribute to the understanding of sex-specific differences in cognition and behavior.

Longitudinal fMRI study of language recovery after a left hemispheric ischemic stroke

BACKGROUND

Recovery from stroke-induced aphasia is typically protracted and involves complex functional reorganization. The relative contributions of the lesioned and non-lesioned hemispheres to this process have been examined in several cross-sectional studies but longitudinal studies involving several time-points and large numbers of subjects are scarce.

OBJECTIVE

The aim of this study was to address the gaps in the literature by longitudinally studying the evolution of post-stroke lateralization and localization of language-related fMRI activation in the first year after single left hemispheric ischemic stroke.

METHOD

Seventeen patients with stroke-induced aphasia were enrolled to undergo detailed behavioral testing and fMRI at 2, 6, 12, 26, and 52 weeks post-stroke. Matched for age, handedness and sex participants were also enrolled to visualize canonical language regions.

RESULTS

Behavioral results showed improvements over time for all but one of the behavioral scores (Semantic Fluency Test). FMRI results showed that the left temporal area participates in compensation for language deficits in the first year after stroke, that there is a correlation between behavioral improvement and the left cerebellar activation over time, and that there is a shift towards stronger frontal left-lateralization of the fMRI activation over the first year post-stroke. Temporary compensation observed in the initial phases of post-stroke recovery that involves the non-lesioned hemisphere may not be as important as previously postulated, since in this study the recovery was driven by activations in the left fronto-temporal regions.

CONCLUSION

Language recovery after left hemispheric ischemic stroke is likely driven by the previously involved in language and attention left hemispheric networks.

Developmental cognitive neuroscience using latent change score models: A tutorial and applications

Assessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions. We illustrate the use of LCS models with two empirical examples. In a lifespan cognitive training study (COGITO, N = 204 (N = 32 imaging) on two waves) we observe correlated change in brain and behaviour in the context of a high-intensity training intervention. In an adolescent development cohort (NSPN, N = 176, two waves) we find greater variability in cortical thinning in males than in females. To facilitate the adoption of LCS by the developmental community, we provide analysis code that can be adapted by other researchers and basic primers in two freely available SEM software packages (lavaan and Ωnyx).

Estriol-mediated neuroprotection in multiple sclerosis localized by voxel-based morphometry

INTRODUCTION

Progressive gray matter (GM) atrophy is a hallmark of multiple sclerosis (MS). Cognitive impairment has been observed in 40%-70% of MS patients and has been linked to GM atrophy. In a phase 2 trial of estriol treatment in women with relapsing-remitting MS (RRMS), higher estriol levels correlated with greater improvement on the paced auditory serial addition test (PASAT) and imaging revealed sparing of localized GM in estriol-treated compared to placebo-treated patients. To better understand the significance of this GM sparing, the current study explored the relationships between the GM sparing and traditional MRI measures and clinical outcomes.

METHODS

Sixty-two estriol- and forty-nine placebo-treated RRMS patients underwent clinical evaluations and brain MRI. Voxel-based morphometry (VBM) was used to evaluate voxelwise GM sparing from high-resolution T1-weighted scans.

RESULTS

A region of treatment-induced sparing (TIS) was defined as the areas where GM was spared in estriol- as compared to placebo-treated groups, localized primarily within the frontal and parietal cortices. We observed that TIS volume was directly correlated with improvement on the PASAT. Next, a longitudinal cognitive disability-specific atlas (DSA) was defined by correlating voxelwise GM volumes with PASAT scores, that is, areas where less GM correlated with less improvement in PASAT scores. Finally, overlap between the TIS and the longitudinal cognitive DSA revealed a specific region of cortical GM that was preserved in estriol-treated subjects that was associated with better performance on the PASAT.

CONCLUSIONS

Discovery of this region of overlap was biology driven, not based on an a priori structure of interest. It included the medial frontal cortex, an area previously implicated in problem solving and attention. These findings indicate that localized GM sparing during estriol treatment was associated with improvement in cognitive testing, suggesting a clinically relevant, disability-specific biomarker for clinical trials of candidate neuroprotective treatments in MS.

Correlations between exploratory eye movement, hallucination, and cortical gray matter volume in people with schizophrenia

BACKGROUND

Widespread cortical gray matter alternations in people with schizophrenia are correlated with both psychotic symptoms and cognitive/behavioral abnormalities, including the impairments of exploratory eye movement (EEM). Particularly, the loss of gray matter density is specifically related to deficits of the responsive search score (RSS) of EEM in schizophrenia. It is unknown, however, whether the schizophrenia-related RSS deficits are associated with certain psychotic symptoms, such as hallucinations.

METHODS

In 33 participants with schizophrenia, the measurement of EEM, assessment of the hallucination severity using Positive and Negative Syndrome Scale (PANSS) and a voxel-based morphometric analysis of cortical gray matter volume (GMV) were conducted to investigate the relationships between the RSS of EEM, symptom severity, and GMV. In 29 matched healthy controls, the measurement of EEM and a voxel-based morphometric analysis of cortical GMV were also conducted to investigate the relationship between the RSS of EEM and GMV.

RESULTS

In participants with schizophrenia, the hallucination severity was significantly negatively correlated with both the RSS and the GMV of a large number of brain regions in the frontal, temporal, parietal, orbitofrontal, calcarine, cingulate, and insular cortices, and rolandic operculum, hippocampus, parahippocampal gyrus, and thalamus. Also in participants with schizophrenia, the RSS was significantly positively correlated with the GMV in the left supplementary motor area (SMA), left superior frontal cortex (SFG), bilateral precentral gyri, bilateral postcentral gyri, and bilateral middle frontal cortices. More importantly, the GMV of the SMA, SFG, and precentral gyrus in the left hemisphere was not only significantly negatively correlated with the hallucination severity but also significantly positively correlated with the RSS. No significant correlation could be revealed between the RSS and the GMV of any brain regions in healthy controls.

CONCLUSIONS

There was a significantly negative association between the hallucination severity and the RSS of EEM, suggesting that the RSS may be a potential biomarker for predicting the hallucination severity of schizophrenia. Also, the GMV of the left SMA, SFG, and precentral gyrus may be the common substrates underlying both hallucination induction and the RSS in people with schizophrenia.

Reduced regional volumes associated with total psychopathy scores in an adult population with childhood lead exposure

Childhood lead exposure has been correlated to acts of delinquency and criminal behavior; however, little research has been conducted to examine its potential long term influence on behavioral factors such as personality, specifically psychopathic personality. Neuroimaging studies have demonstrated that the effects of childhood lead exposure persist into adulthood, with structural abnormalities found in gray and white matter regions involved in behavioral decision making. The current study examined whether measurements of adult psychopathy were associated with neuroanatomical differences in structural brain volumes for a longitudinal cohort with measured childhood lead exposure. We hypothesized that increased total psychopathy scores and increased blood lead concentration at 78 months of age (PbB78) would be inversely associated with volumetric measures of gray and white matter brain structures responsible for executive and emotional processing. Analyses did not display a direct effect between total psychopathy score and gray matter volume; however, reduced white matter volume in the cerebellum and brain stem in relation to increased total psychopathy scores was observed. An interaction between sex and total psychopathy score was also detected. Females displayed increased gray matter volume in the frontal, temporal, and parietal lobes associated with increased total psychopathy score, but did not display any white matter volume differences. Males primarily displayed reductions in frontal gray and white matter brain volume in relation to increased total psychopathy scores. Additionally, reduced gray and white matter volume was associated with increased blood lead levels in the frontal lobes; reduced white matter volume was also observed in the parietal and temporal lobes. Females demonstrated gray and white matter volume loss associated with increased PbB78 values in the right temporal lobe, as well as reduced gray matter volume in the frontal lobe. Males displayed reduced white matter volumes associated with increased PbB78 values in the frontal, temporal, and parietal lobes. Comparison of the two primary models revealed a volumetric decrease in the white matter of the left prefrontal cortex associated with increased total psychopathy scores and increased blood lead concentration in males. The results of this study suggested that increased psychopathy scores in this cohort may be attributable to the neuroanatomical abnormalities observed and that childhood lead exposure may be influential to these outcomes.

Acute and long-lasting cortical thickness changes following intensive first-person action videogame practice

Recent evidence shows how an extensive gaming experience might positively impact cognitive and perceptual functioning, leading to brain structural changes observed in cross-sectional studies. Importantly, changes seem to be game-specific, reflecting gameplay styles and therefore opening to the possibility of tailoring videogames according to rehabilitation and enhancement purposes. However, whether if such brain effects can be induced even with limited gaming experience, and whether if they can outlast the gaming period, is still unknown. Here we quantified both cognitive and grey matter thickness changes following 15 daily gaming sessions based on a modified version of a 3D first-person shooter (FPS) played in laboratory settings. Twenty-nine healthy participants were randomly assigned to a control or a gaming group and underwent a cognitive assessment, an in-game performance evaluation and structural magnetic resonance imaging before (T0), immediately after (T1) and three months after the end of the experiment (T2). At T1, a significant increase in thickness of the bilateral parahippocampal cortex (PHC), somatosensory cortex (S1), superior parietal lobule (SPL) and right insula were observed. Changes in S1 matched the hand representation bilaterally, while PHC changes corresponded to the parahippocampal place area (PPA). Surprisingly, changes in thickness were still present at T2 for S1, PHC, SPL and right insula as compared to T0. Finally, surface-based regression identified the lingual gyrus as the best predictor of changes in game performance at T1. Results stress the specific impact of core game elements, such as spatial navigation and visuomotor coordination on structural brain properties, with effects outlasting even a short intensive gaming period.

The right occipital lobe and poor insight in first-episode psychosis

Lack of insight is a core feature of non-affective psychosis and has been associated with poorer outcomes. Brain abnormalities underlying lack of insight have been suggested, mostly in the frontal lobe, although previous research showed mixed results. We used a voxel-based morphometry (VBM) analysis in 108 first-episode non-affective psychosis patients to investigate the pattern of brain structural abnormalities related to lack of insight. In addition, 77 healthy volunteers were compared with the patients classified as having poor and good insight. The shortened version of the Scale to Assess Unawareness of Mental Disorder was used to evaluate insight. Patients with poor insight (n = 68) compared with patients with good insight (n = 40) showed a single significant cluster (kc = 5834; PcFWE = 0.001) of reduced grey matter volume (GMV) in the right occipital lobe extending to its lateral and medial surfaces, the cuneus, and the middle temporal gyrus. In addition, GMV at this cluster showed a negative correlation with the score of the SUMD (r = -0.305; p = 0.001). When comparing patients with poor insight with healthy subjects overall reductions of GMV were found, mainly in frontal and occipital lobes. Hence, poor insight in non-affective psychosis seems to be associated with specific brain abnormalities in the right occipital and temporal cortical regions. Dysfunction in any combination of these areas may contribute to lack of insight in non-affective psychosis. Specifically, the 'right' hemisphere dysfunction underlying impaired insight in our sample is consistent with previously reported similarities between lack of insight in psychosis and anosognosia in neurological disorders.

Common variation in ZNF804A (rs1344706) is not associated with brain morphometry in schizophrenia or healthy participants

BACKGROUND

The single nucleotide polymorphism (SNP) rs1344706 [A>C] within intron 2 of the zinc finger protein 804A gene (ZNF804A) is associated with schizophrenia at the genome-wide level, but its function in relation to the development of psychotic disorders, including its influence on brain morphology remains unclear.

METHODS

Using both univariate (voxel-based morphometry, VBM; cortical thickness) and multivariate (source-based morphometry, SBM) approaches, we examined the effects of variation of the rs1344706 polymorphism on grey matter integrity in 214 Caucasian schizophrenia cases and 94 Caucasian healthy individuals selected from the Australian Schizophrenia Research Bank.

RESULTS

Neither univariate nor multivariate analyses showed any associations between indices of grey matter and rs1344706 variation in schizophrenia or healthy participants. This was revealed in the context of the typical pattern of decreased grey matter integrity in schizophrenia compared to healthy individuals, including: (1) large grey matter volume reductions in the orbitofrontal and anterior cingulate cortices and the left fusiform/inferior temporal gyri; (2) decreased cortical thickness in the left inferior temporal and fusiform gyri, the left orbitofrontal gyrus, as well as in the right pars opercularis/precentral gyrus; and (3) decreased covariation of grey matter concentration in frontal and limbic brain regions emerging from the SBM analyses.

CONCLUSIONS

Contrary to some - but not all - previous findings, this study of a large sample of schizophrenia cases and healthy controls reveals no evidence for association between grey matter alterations and variation in rs1344706 (ZNF804A). Differences in sample sizes and ethnicities may account for discrepant findings between the present and previous studies.

Partial volume-aware assessment of multiple sclerosis lesions

White-matter lesion count and volume estimation are key to the diagnosis and monitoring of multiple sclerosis (MS). Automated MS lesion segmentation methods that have been proposed in the past 20 years reach their limits when applied to patients in early disease stages characterized by low lesion load and small lesions. We propose an algorithm to automatically assess MS lesion load (number and volume) while taking into account the mixing of healthy and lesional tissue in the image voxels due to partial volume effects. The proposed method works on 3D MPRAGE and 3D FLAIR images as obtained from current routine MS clinical protocols. The method was evaluated and compared with manual segmentation on a cohort of 39 early-stage MS patients with low disability, and showed higher Dice similarity coefficients (median DSC = 0.55) and higher detection rate (median DR = 61%) than two widely used methods (median DSC = 0.50, median DR < 45%) for automated MS lesion segmentation. We argue that this is due to the higher performance in segmentation of small lesions, which are inherently prone to partial volume effects.

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Modeling the partial volume improves lesion volumetric measurements.

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Higher detection of small lesions inherently prone to partial volume effects.

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Partial volume effects should be taken into account in early stages of MS.

Reduced Orbitofrontal Gray Matter Concentration as a Marker of Premorbid Childhood Trauma in Cocaine Use Disorder

Background: Childhood trauma affects neurodevelopment and promotes vulnerability to impaired constraint, depression, and addiction. Reduced gray matter concentration (GMC) in the mesocorticolimbic regions implicated in reward processing and cognitive control may be an underlying substrate, as documented separately in addiction and for childhood trauma. The purpose of this study was to understand the contribution of childhood maltreatment to GMC effects in individuals with cocaine use disorder.

Methods: Individuals with cocaine use disorder were partitioned into groups of low vs. high childhood trauma based on median split of the total score of the Childhood Trauma Questionnaire (CTQ; CUD-L, N = 23; CUD-H, N = 24) and compared with age, race, and gender matched healthy controls with low trauma (N = 29). GMC was obtained using voxel-based morphometry applied to T1-weighted MRI scans. Drug use, depression and constraint were assessed with standardized instruments.

Results: Whole-brain group comparisons showed reduced GMC in the right lateral orbitofrontal cortex (OFC) in CUD-H as compared with controls (cluster-level p_FWE-corr < 0.001) and CUD-L (cluster-level p_FWE-corr = 0.035); there were no significant differences between CUD-L and controls. A hierarchical regression analysis across both CUD groups revealed that childhood trauma, but not demographics and drug use, and beyond constraint and depression, accounted for 37.7% of the variance in the GMC in the right lateral OFC (p < 0.001).

Conclusions: Beyond other contributing factors, childhood trauma predicted GMC reductions in the OFC in individuals with cocaine use disorder. These findings underscore a link between premorbid environmental stress and morphological integrity of a brain region central for behaviors underlying drug addiction. These results further highlight the importance of accounting for childhood trauma, potentially as a factor predisposing to addiction, when examining and interpreting neural alterations in cocaine addicted individuals.

Sexual dimorphism of Broca's region: More gray matter in female brains in Brodmann areas 44 and 45

Although a sexual dimorphism in brain structure is generally well established, evidence for sex differences in Brodmann areas (BA) 44 and 45 is inconclusive. This may be due to the difficulty of accurately defining BA 44 and BA 45 in magnetic resonance images, given that these regions are variable in their location and extent and that they do not match well with macroanatomic landmarks. Here we set out to test for possible sex differences in the local gray matter of BA 44/45 by integrating imaging-based signal intensities with cytoarchitectonically defined tissue probabilities in a sample of 50 male and 50 female subjects. In addition to testing for sex differences with respect to left- and right-hemispheric measures of BA 44/45, we also assessed possible sex differences in BA 44/45 asymmetry. Our analyses revealed significantly larger gray matter volumes in females compared with males for BA 44 and BA 45 bilaterally. However, there was a lack of significant sex differences in BA 44/45 asymmetry. These results corroborate reports of a language-related female superiority, particularly with respect to verbal fluency and verbal memory tasks. © 2016 Wiley Periodicals, Inc.

Comparison of image intensity, local, and multi-atlas priors in brain tissue classification

PURPOSE

Automated and accurate tissue classification in three-dimensional brain magnetic resonance images is essential in volumetric morphometry or as a preprocessing step for diagnosing brain diseases. However, noise, intensity in homogeneity, and partial volume effects limit the classification accuracy of existing methods. This paper provides a comparative study on the contributions of three commonly used image information priors for tissue classification in normal brains: image intensity, local, and multi-atlas priors.

METHODS

We compared the effectiveness of the three priors by comparing the four methods modeling them: K-Means (KM), KM combined with a Markov Random Field (KM-MRF), multi-atlas segmentation (MAS), and the combination of KM, MRF, and MAS (KM-MRF-MAS). The key parameters and factors in each of the four methods are analyzed, and the performance of all the models is compared quantitatively and qualitatively on both simulated and real data.

RESULTS

The KM-MRF-MAS model that combines the three image information priors performs best.

CONCLUSIONS

The image intensity prior is insufficient to generate reasonable results for a few images. Introducing local and multi-atlas priors results in improved brain tissue classification. This study provides a general guide on what image information priors can be used for effective brain tissue classification.

Premature brain aging in humans exposed to maternal nutrient restriction during early gestation

BACKGROUND

Prenatal exposure to undernutrition is widespread in both developing and industrialized countries, causing irreversible damage to the developing brain, resulting in altered brain structure and decreased cognitive function during adulthood. The Dutch famine in 1944/45 was a humanitarian disaster, now enabling studies of the effects of prenatal undernutrition during gestation on brain aging in late adulthood.

METHODS

We hypothesized that study participants prenatally exposed to maternal nutrient restriction (MNR) would demonstrate altered brain structure resembling premature brain aging in late adulthood, expecting the effect being stronger in men. Utilizing the Dutch famine birth cohort (n = 118; mean age: 67.5 ± 0.9 years), this study implements an innovative biomarker for individual brain aging, using structural neuroimaging. BrainAGE was calculated using state-of-the-art pattern recognition methods, trained on an independent healthy reference sample, then applied to the Dutch famine MRI sample, to evaluate the effects of prenatal undernutrition during early gestation on individual brain aging in late adulthood.

RESULTS

Exposure to famine in early gestation was associated with BrainAGE scores indicative of an older-appearing brain in the male sample (mean difference to subjects born before famine: 4.3 years, p < 0.05). Furthermore, in explaining the observed variance in individual BrainAGE scores in the male sample, maternal age at birth, head circumference at birth, medical treatment of hypertension, history of cerebral incidences, actual heart rate, and current alcohol intake emerged to be the most influential variables (adjusted R² = 0.63, p < 0.01).

INTERPRETATION

The findings of our study on exposure to prenatal undernutrition being associated with a status of premature brain aging during late adulthood, as well as individual brain structure being shaped by birth- and late-life health characteristics, are strongly supporting the critical importance of sufficient nutrient supply during pregnancy. Interestingly, the status of premature brain aging in participants exposed to the Dutch famine during early gestation occurred in the absence of fetal growth restriction at birth as well as vascular pathology in late-life. Additionally, the neuroimaging brain aging biomarker presented in this study will further enable tracking effects of environmental influences or (preventive) treatments on individual brain maturation and aging in epidemiological and clinical studies.

The Reduction of Ventrolateral Prefrontal Cortex Gray Matter Volume Correlates with Loss of Economic Rationality in Aging

The population of people above 65 years old continues to grow, and there is mounting evidence that as humans age they are more likely to make errors. However, the specific effect of neuroanatomical aging on the efficiency of economic decision-making is poorly understood. We used whole-brain voxel-based morphometry analysis to determine where reduction of gray matter volume in healthy female and male adults over the age of 65 years correlates with a classic measure of economic irrationality: violations of the Generalized Axiom of Revealed Preference. All participants were functionally normal with Mini-Mental State Examination scores ranging between 26 and 30. While our elders showed the previously reported decline in rationality compared with younger subjects, chronological age per se did not correlate with rationality measures within our population of elders. Instead, reduction of gray matter density in ventrolateral prefrontal cortex correlates tightly with irrational behavior. Interestingly, using a large fMRI sample and meta-analytic tool with Neurosynth, we found that this brain area shows strong coactivation patterns with nearly all of the value-associated regions identified in previous studies. These findings point toward a neuroanatomic locus for economic rationality in the aging brain and highlight the importance of understanding both anatomy and function in the study of aging, cognition, and decision-making.SIGNIFICANCE STATEMENT Age is a crucial factor in decision-making, with older individuals making more errors in choices. Using whole-brain voxel-based morphometry analysis, we found that reduction of gray matter density in ventrolateral prefrontal cortex correlates with economic irrationality: reduced gray matter volume in this area correlates with the frequency and severity of violations of the Generalized Axiom of Revealed Preference. Furthermore, this brain area strongly coactivates with other reward-associated regions identified with Neurosynth. These findings point toward a role for neuroscientific discoveries in shaping long-standing economic views of decision-making.

Altered Structure and Intrinsic Functional Connectivity in Post-stroke Aphasia

Previous studies have demonstrated that alterations of gray matter exist in post-stroke aphasia (PSA) patients. However, so far, few studies combined structural alterations of gray matter volume (GMV) and intrinsic functional connectivity (iFC) imbalances of resting-state functional MRI to investigate the mechanism underlying PSA. The present study investigated specific regions with GMV abnormality in patients with PSA (n = 17) and age- and sex- matched healthy controls (HCs, n = 20) using voxel-based morphometry. In addition, we examined whether there is a link between abnormal gray matter and altered iFC. Furthermore, we explored the correlations between abnormal iFC and clinical scores in aphasic patients. We found significantly increased GMV in the right superior temporal gyrus, right inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and left middle occipital gyrus. Decreased GMV was found in the right caudate gyrus, bilateral thalami in PSA patients. Patients showed increased remote interregional FC between the right IPL/SMG and right precuneus, right angular gyrus, right superior occipital gyrus; while reduced FC in the right caudate gyrus and supplementary motor area, dorsolateral superior frontal gyrus. Moreover, iFC strength between the left middle occipital gyrus and the left orbital middle frontal gyrus was positively correlated with the performance quotient. We suggest that GMV abnormality contributes to interregional FC in PSA. These results may provide useful information to understand the pathogenesis of post-stroke aphasia.

Prefrontal gray matter volume recovery in treatment-seeking cocaine-addicted individuals: a longitudinal study

Deficits in prefrontal cortical (PFC) function have been consistently reported in individuals with cocaine use disorders (iCUD), and have separately been shown to improve with longer-term abstinence. However, it is less clear whether the PFC structural integrity possibly underlying these deficits is also modulated by sustained reduction in drug use in iCUD. Here, T1-weighted magnetic resonance imaging scans were acquired, and performance on a neuropsychological test battery was assessed, in 19 initially abstinent treatment-seeking iCUD, first at baseline and then after six months of significantly reduced or no drug use (follow-up). A comparison cohort of 12 healthy controls was also scanned twice with a similar inter-scan interval. The iCUD showed increased gray matter volume in the left inferior frontal gyrus and bilaterally in the ventromedial prefrontal cortex at follow-up compared to baseline; healthy controls, as expected, showed no changes over this same time period. The iCUD also showed improved decision making and cognitive flexibility, with the latter correlated significantly with the gray matter volume increases in the inferior frontal gyrus. Given its association with improved cognitive function, the longitudinal recovery in cortical gray matter volume, particularly in regions where structure and function are adversely affected by chronic drug use, reflects a quantifiable positive impact of significantly reduced drug use on cortical structural integrity.

BrainAGE score indicates accelerated brain aging in schizophrenia, but not bipolar disorder

BrainAGE (brain age gap estimation) is a novel morphometric parameter providing a univariate score derived from multivariate voxel-wise analyses. It uses a machine learning approach and can be used to analyse deviation from physiological developmental or aging-related trajectories. Using structural MRI data and BrainAGE quantification of acceleration or deceleration of in individual aging, we analysed data from 45 schizophrenia patients, 22 bipolar I disorder patients (mostly with previous psychotic symptoms / episodes), and 70 healthy controls. We found significantly higher BrainAGE scores in schizophrenia, but not bipolar disorder patients. Our findings indicate significantly accelerated brain structural aging in schizophrenia. This suggests, that despite the conceptualisation of schizophrenia as a neurodevelopmental disorder, there might be an additional progressive pathogenic component.

Regional gray matter correlates of memory for emotion-laden words in middle-aged and older adults: A voxel-based morphometry study

Emotional content is known to enhance memory in a content-dependent manner in healthy populations. In middle-aged and older adults, a reduced preference for negative material, or even an enhanced preference for positive material has been observed. This preference seems to be modulated by the emotional arousal that the material evokes. The neuroanatomical basis for emotional memory processes is, however, not well understood in middle-aged and older healthy people. Previous research on local gray matter correlates of emotional memory in older populations has mainly been conducted with patients suffering from various neurodegenerative diseases. To our knowledge, this is the first study to examine regional gray matter correlates of immediate free recall and recognition memory of intentionally encoded positive, negative, and emotionally neutral words using voxel-based morphometry (VBM) in a sample of 50-to-79-year-old cognitively intact normal adults. The behavioral analyses yielded a positivity bias in recognition memory, but not in immediate free recall. No associations with memory performance emerged from the region-of-interest (ROI) analyses using amygdalar and hippocampal volumes. Controlling for total intracranial volume, age, and gender, the whole-brain VBM analyses showed statistically significant associations between immediate free recall of negative words and volumes in various frontal regions, between immediate free recall of positive words and cerebellar volume, and between recognition memory of positive words and primary visual cortex volume. The findings indicate that the neural areas subserving memory for emotion-laden information encompass posterior brain areas, including the cerebellum, and that memory for emotion-laden information may be driven by cognitive control functions.

Effects of subclinical depression, anxiety and somatization on brain structure in healthy subjects

BACKGROUND

Dimensional approaches in highly prevalent psychiatric disorders like depression or anxiety could lead to a better understanding of pathogenesis and advantages in early detection and prevention. In an effort to better understand associations of brain structural variation across the depression/anxiety spectra, we investigated minor subclinical symptoms in a non-clinical healthy population.

METHODS

We studied 177 healthy subjects from the community, who underwent high-resolution T1-weighted 3T MRI and completed the symptom-checklist-90 (SCL-90-R). Using voxel-based morphometry (VBM) analysis with CAT12 software, we correlated SCL-90-R-subscales for depression, anxiety, and somatization with gray matter across the brain.

RESULTS

Significant positive gray matter correlations emerged across all three scales in different areas: the depression subscale correlated positively with gray matter in the Rolandic operculum, superior temporal gyrus (left) and postcentral gyrus (bilateral), the anxiety subscale correlated positively with middle temporal gyrus, Rolandic operculum, middle cingular gyrus and precuneus bilaterally, and the somatization subscale with left inferior prefrontal cortex. Somatization also showed negative correlations with cerebellar vermis and right supplementary motor area.

LIMITATIONS

Our study is limited to VBM and does not include surface-based measures. It also only contains subjects with very small psychological distress by partly overlapping symptoms.

CONCLUSION

Our findings are consistent with a non-linear relationship between symptom severity and cortical volume in several brain areas involved in both emotion regulation as well as altered in clinically manifest depressive/anxiety disorders.

Disability-Specific Atlases of Gray Matter Loss in Relapsing-Remitting Multiple Sclerosis

IMPORTANCE

Multiple sclerosis (MS) is characterized by progressive gray matter (GM) atrophy that strongly correlates with clinical disability. However, whether localized GM atrophy correlates with specific disabilities in patients with MS remains unknown.

OBJECTIVE

To understand the association between localized GM atrophy and clinical disability in a biology-driven analysis of MS.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, magnetic resonance images were acquired from 133 women with relapsing-remitting MS and analyzed using voxel-based morphometry and volumetry. A regression analysis was used to determine whether voxelwise GM atrophy was associated with specific clinical deficits. Data were collected from June 28, 2007, to January 9, 2014.

MAIN OUTCOMES AND MEASURES

Voxelwise correlation of GM change with clinical outcome measures (Expanded Disability Status Scale and Multiple Sclerosis Functional Composite scores).

RESULTS

Among the 133 female patients (mean [SD] age, 37.4 [7.5] years), worse performance on the Multiple Sclerosis Functional Composite correlated with voxelwise GM volume loss in the middle cingulate cortex (P < .001) and a cluster in the precentral gyrus bilaterally (P = .004). In addition, worse performance on the Paced Auditory Serial Addition Test correlated with volume loss in the auditory and premotor cortices (P < .001), whereas worse performance on the 9-Hole Peg Test correlated with GM volume loss in Brodmann area 44 (Broca area; P = .02). Finally, voxelwise GM loss in the right paracentral lobulus correlated with bowel and bladder disability (P = .03). Thus, deficits in specific clinical test results were directly associated with localized GM loss in clinically eloquent locations.

CONCLUSIONS AND RELEVANCE

These biology-driven data indicate that specific disabilities in MS are associated with voxelwise GM loss in distinct locations. This approach may be used to develop disability-specific biomarkers for use in future clinical trials of neuroprotective treatments in MS.

Caloric Restriction in Older Adults-Differential Effects of Weight Loss and Reduced Weight on Brain Structure and Function

Dietary modifications such as caloric restriction (CR) have been suggested as a means to improve memory and prevent age-related decline. However, it is unclear whether those effects remain stable over time or are related specifically to negative energy balance during the weight loss phase of CR. Using a randomized interventional design, we investigated changes in recognition memory and neural correlates in postmenopausal obese women (n = 19): 1) after intense weight loss in the course of a 12-week low-caloric diet (reduced body weight and negative energy balance) and 2) after having sustained the reduced weight over 4 more weeks (reduced body weight, but energy balance equilibrium). Participants were contrasted to a control group (n = 18) instructed not to change dietary habits. In the CR group, we found improved recognition memory, paralleled by increased gray matter volume in inferior frontal gyrus and hippocampus, and augmented hippocampal resting-state functional connectivity to parietal areas. Moreover, effects were specific for transient negative energy balance and could not be detected after subsequent weight maintenance. Our data demonstrate for the first time in humans that beneficial effects of CR on brain structure and function are due to weight loss rather than an overall reduced weight.

Active contours driven by local and global fitted image models for image segmentation robust to intensity inhomogeneity

This paper presents a region-based active contour method for the segmentation of intensity inhomogeneous images using an energy functional based on local and global fitted images. A square image fitted model is defined by using both local and global fitted differences. Moreover, local and global signed pressure force functions are introduced in the solution of the energy functional to stabilize the gradient descent flow. In the final gradient descent solution, the local fitted term helps extract regions with intensity inhomogeneity, whereas the global fitted term targets homogeneous regions. A Gaussian kernel is applied to regularize the contour at each step, which not only smoothes it but also avoids the computationally expensive re-initialization. Intensity inhomogeneous images contain undesired smooth intensity variations (bias field) that alter the results of intensity-based segmentation methods. The bias field is approximated with a Gaussian distribution and the bias of intensity inhomogeneous regions is corrected by dividing the original image by the approximated bias field. In this paper, a two-phase model is first derived and then extended to a four-phase model to segment brain magnetic resonance (MR) images into the desired regions of interest. Experimental results with both synthetic and real brain MR images are used for a quantitative and qualitative comparison with state-of-the-art active contour methods to show the advantages of the proposed segmentation technique in practical terms.

Magnetization transfer imaging identifies basal ganglia abnormalities in adult ADHD that are invisible to conventional T1 weighted voxel-based morphometry

In childhood, Attention Deficit Hyperactivity Disorder (ADHD) is reliably associated with reduced volume of the striatum. In contrast, striatal abnormalities are infrequently detected in voxel-based morphometry (VBM) neuroimaging studies of adults with ADHD. This discrepancy has been suggested to reflect normalisation of striatal morphology with age and prolonged treatment of symptoms. If so, this would indicate that while striatal abnormalities are linked to symptom expression in childhood, they cannot explain the persistence of these symptoms in adulthood. However, this may not be case. Instead, we hypothesized that the lack of evidence for striatal abnormalities in adult ADHD may reflect poor sensitivity of typical (T1-weighted) neuroimaging to detect subcortical differences. To address this, we acquired both magnetisation transfer (MT) saturation maps optimised for subcortical contrast, and conventional T1-weighted images in 30 adults with ADHD and 30 age, IQ, gender and handedness-matched controls. Using VBM of both datasets, we demonstrate volumetric reductions within the left ventral striatum on MT that are not observed on identically pre-processed T1-weighted images from the same participants. Nevertheless, both techniques reported similar sensitivity to cortical abnormalities in the right inferior parietal lobe. Additionally, we show that differences in striatal iron may potentially explain this reduced sensitivity of T1-weighted images in adults. Together, these findings indicate that prior VBM studies reporting no abnormalities in striatal volume in adult ADHD might have been compromised by the methodological insensitivity of T1-weighted VBM to subcortical differences, and that structural abnormalities of the striatum in ADHD do indeed persist into adulthood.

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Striatal grey matter changes in adult ADHD are robustly observed using VBM of MT maps.

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These changes are not detectable when using typical T1 images in the same subjects.

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Prior negative findings using T1-VBM in adults were thought to reflect therapeutic volumetric normalisation.

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We suggest that such findings reflect the insensitivity of T1-VBM to these changes, not structural normalisation.

PETPVE12: an SPM toolbox for Partial Volume Effects correction in brain PET - Application to amyloid imaging with AV45-PET

Positron emission tomography (PET) allows detecting molecular brain changes in vivo. However, the accuracy of PET is limited by partial volume effects (PVE) that affects quantitative analysis and visual interpretation of the images. Although PVE-correction methods have been shown to effectively increase the correspondence of the measured signal with the true regional tracer uptake, these procedures are still not commonly applied, neither in clinical nor in research settings. Here, we present an implementation of well validated PVE-correction procedures as a SPM toolbox, PETPVE12, for automated processing. We demonstrate its utility by a comprehensive analysis of the effects of PVE-correction on amyloid-sensitive AV45-PET data from 85 patients with Alzheimer's disease (AD) and 179 cognitively normal (CN) elderly. Effects of PVE-correction on global cortical standard uptake value ratios (SUVR) and the power of diagnostic group separation were assessed for the region-wise geometric transfer matrix method (PVEc-GTM), as well as for the 3-compartmental voxel-wise "Müller-Gärtner" method (PVEc-MG). Both PVE-correction methods resulted in decreased global cortical SUVRs in the low to middle range of SUVR values, and in increased global cortical SUVRs at the high values. As a consequence, average SUVR of the CN group was reduced, whereas average SUVR of the AD group was increased by PVE-correction. These effects were also reflected in increased accuracies of group discrimination after PVEc-GTM (AUC=0.86) and PVEc-MG (AUC=0.89) compared to standard non-corrected SUVR (AUC=0.84). Voxel-wise analyses of PVEc-MG corrected data also demonstrated improved detection of regionally increased AV45 SUVR values in AD patients. These findings complement the growing evidence for a beneficial effect of PVE-correction in quantitative analysis of amyloid-sensitive PET data. The novel PETPVE12 toolbox significantly facilitates the application of PVE-correction, particularly within SPM-based processing pipelines. This is expected to foster the use of PVE-correction in brain PET for more widespread use. The toolbox is freely available at http://www.fil.ion.ucl.ac.uk/spm/ext/#PETPVE12.

Rey's Auditory Verbal Learning Test scores can be predicted from whole brain MRI in Alzheimer's disease

Rey's Auditory Verbal Learning Test (RAVLT) is a powerful neuropsychological tool for testing episodic memory, which is widely used for the cognitive assessment in dementia and pre-dementia conditions. Several studies have shown that an impairment in RAVLT scores reflect well the underlying pathology caused by Alzheimer's disease (AD), thus making RAVLT an effective early marker to detect AD in persons with memory complaints. We investigated the association between RAVLT scores (RAVLT Immediate and RAVLT Percent Forgetting) and the structural brain atrophy caused by AD. The aim was to comprehensively study to what extent the RAVLT scores are predictable based on structural magnetic resonance imaging (MRI) data using machine learning approaches as well as to find the most important brain regions for the estimation of RAVLT scores. For this, we built a predictive model to estimate RAVLT scores from gray matter density via elastic net penalized linear regression model. The proposed approach provided highly significant cross-validated correlation between the estimated and observed RAVLT Immediate (R = 0.50) and RAVLT Percent Forgetting (R = 0.43) in a dataset consisting of 806 AD, mild cognitive impairment (MCI) or healthy subjects. In addition, the selected machine learning method provided more accurate estimates of RAVLT scores than the relevance vector regression used earlier for the estimation of RAVLT based on MRI data. The top predictors were medial temporal lobe structures and amygdala for the estimation of RAVLT Immediate and angular gyrus, hippocampus and amygdala for the estimation of RAVLT Percent Forgetting. Further, the conversion of MCI subjects to AD in 3-years could be predicted based on either observed or estimated RAVLT scores with an accuracy comparable to MRI-based biomarkers.

Deterioration of R-Wave Detection in Pathology and Noise: A Comprehensive Analysis Using Simultaneous Truth and Performance Level Estimation

OBJECTIVE

For long-term electrocardiography (ECG) recordings, accurate R-wave detection is essential. Several algorithms have been proposed but not yet compared on large, noisy, or pathological data, since manual ground-truth establishment is impossible on such large data.

METHODS

We apply the simultaneous truth and performance level estimation (STAPLE) method to ECG signals comparing nine R-wave detectors: Pan and Tompkins (1985), Chernenko (2007), Arzeno et al. (2008), Manikandan et al. (2012), Lentini et al. (2013), Sartor et al. (2014), Liu et al. (2014), Arteaga-Falconi et al. (2015), and Khamis et al. (2016). Experiments are performed on the MIT-BIH database, TELE database, PTB database, and 24/7 Holter recordings of 60 multimorbid subjects.

RESULTS

Existing approaches on R-wave detection perform excellently on healthy subjects (F-measure above 99% for most methods), but performance drops to a range of F = 90.10% (Khamis et al.) to F = 30.10% (Chernenko) when analyzing the 37 million R-waves of multimorbid subjects. STAPLE improves existing approaches (ΔF = 0.04 for the MIT-BIH database and ΔF = 0.95 for the TELE database) and yields a relative (not absolute) scale to compare algorithms' performances.

CONCLUSION

More robust R-wave detection methods or flexible combinations are required to analyze continuous data captured from pathological subjects or that is recorded with dropouts and noise.

SIGNIFICANCE

STAPLE algorithm has been adopted from image to signal analysis to compare algorithms on large, incomplete, and noisy data without manual ground truth. Existing approaches on R-wave detection weakly perform on such data.

Homotaurine Effects on Hippocampal Volume Loss and Episodic Memory in Amnestic Mild Cognitive Impairment

Homotaurine supplementation may have a positive effect on early Alzheimer's disease. Here, we investigated its potential neuroprotective effect on the hippocampus structure and episodic memory performances in amnestic mild cognitive impairment (aMCI). Neuropsychological, clinical, and neuroimaging assessment in 11 treated and 22 untreated patients were performed at baseline and after 1 year. Magnetic resonance data were analyzed using voxel-based morphometry to explore significant differences (Family Wise Error corrected) between the two groups over time. Patients treated with homotaurine showed decreased volume loss in the left and right hippocampal tail, left and right fusiform gyrus, and right inferior temporal cortex which was associated with improved short-term episodic memory performance as measured by the recency effect of the Rey 15-word list learning test immediate recall. Thus, homotaurine supplementation in individuals with aMCI has a positive effect on hippocampus atrophy and episodic memory loss. Future studies should further clarify the mechanisms of its effects on brain morphometry.

Surface-driven registration method for the structure-informed segmentation of diffusion MR images

Current methods for processing diffusion MRI (dMRI) to map the connectivity of the human brain require precise delineations of anatomical structures. This requirement has been approached by either segmenting the data in native dMRI space or mapping the structural information from T1-weighted (T1w) images. The characteristic features of diffusion data in terms of signal-to-noise ratio, resolution, as well as the geometrical distortions caused by the inhomogeneity of magnetic susceptibility across tissues hinder both solutions. Unifying the two approaches, we propose regseg, a surface-to-volume nonlinear registration method that segments homogeneous regions within multivariate images by mapping a set of nested reference-surfaces. Accurate surfaces are extracted from a T1w image of the subject, using as target image the bivariate volume comprehending the fractional anisotropy (FA) and the apparent diffusion coefficient (ADC) maps derived from the dMRI dataset. We first verify the accuracy of regseg on a general context using digital phantoms distorted with synthetic and random deformations. Then we establish an evaluation framework using undistorted dMRI data from the Human Connectome Project (HCP) and realistic deformations derived from the inhomogeneity fieldmap corresponding to each subject. We analyze the performance of regseg computing the misregistration error of the surfaces estimated after being mapped with regseg onto 16 datasets from the HCP. The distribution of errors shows a 95% CI of 0.56-0.66mm, that is below the dMRI resolution (1.25mm, isotropic). Finally, we cross-compare the proposed tool against a nonlinear b0-to-T2w registration method, thereby obtaining a significantly lower misregistration error with regseg. The accurate mapping of structural information in dMRI space is fundamental to increase the reliability of network building in connectivity analyses, and to improve the performance of the emerging structure-informed techniques for dMRI data processing.

White matter microstructural changes are associated with alcohol use in patients with panic disorder

BACKGROUND

A close relationship between panic disorder (PD) and alcohol use disorder (AUD) has been suggested. We aimed to investigate alterations in white matter (WM) volume or integrity in patients with PD comorbid with AUD.

METHODS

Forty-nine patients with PD, free of comorbid AUD (PD-AUD), and 20 patients with PD comorbid with AUD (PD+AUD) were investigated. All subjects were assessed using the Panic Disorder Severity Scale, Anxiety Sensitivity Inventory-Revised (ASI-R), Beck Depression Inventory, and CAGE questionnaire. Voxel-based morphometry and tract-based spatial statistics were used for imaging analysis.

RESULTS

Increased fractional anisotropy (FA), as well as decreased mean diffusivity and radial diffusivity were observed in multiple WM tracts, including the body and splenium of the corpus callosum and the retrolenticular part of the internal capsule, in the PD+AUD group compared to the PD-AUD group. CAGE scores in the PD+AUD group and ASI-R scores in the PD-AUD group were significantly correlated with FA values for the corpus callosum. No WM volume differences were found.

LIMITATIONS

The present study should be considered preliminary due to relatively small sample size.

CONCLUSIONS

Our findings revealed microstructural changes in multiple WM tracts, including the corpus callosum and internal capsule, suggesting they could be significant neural correlates of AUD in patients with PD.

The Effect of the APOE Genotype on Individual BrainAGE in Normal Aging, Mild Cognitive Impairment, and Alzheimer's Disease

In our aging society, diseases in the elderly come more and more into focus. An important issue in research is Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) with their causes, diagnosis, treatment, and disease prediction. We applied the Brain Age Gap Estimation (BrainAGE) method to examine the impact of the Apolipoprotein E (APOE) genotype on structural brain aging, utilizing longitudinal magnetic resonance image (MRI) data of 405 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. We tested for differences in neuroanatomical aging between carrier and non-carrier of APOE ε4 within the diagnostic groups and for longitudinal changes in individual brain aging during about three years follow-up. We further examined whether a combination of BrainAGE and APOE status could improve prediction accuracy of conversion to AD in MCI patients. The influence of the APOE status on conversion from MCI to AD was analyzed within all allelic subgroups as well as for ε4 carriers and non-carriers. The BrainAGE scores differed significantly between normal controls, stable MCI (sMCI) and progressive MCI (pMCI) as well as AD patients. Differences in BrainAGE changing rates over time were observed for APOE ε4 carrier status as well as in the pMCI and AD groups. At baseline and during follow-up, BrainAGE scores correlated significantly with neuropsychological test scores in APOE ε4 carriers and non-carriers, especially in pMCI and AD patients. Prediction of conversion was most accurate using the BrainAGE score as compared to neuropsychological test scores, even when the patient’s APOE status was unknown. For assessing the individual risk of coming down with AD as well as predicting conversion from MCI to AD, the BrainAGE method proves to be a useful and accurate tool even if the information of the patient’s APOE status is missing.

Classifying Schizophrenia Using Multimodal Multivariate Pattern Recognition Analysis: Evaluating the Impact of Individual Clinical Profiles on the Neurodiagnostic Performance

Previous studies have shown that structural brain changes are among the best-studied candidate markers for schizophrenia (SZ) along with functional connectivity (FC) alterations of resting-state (RS) patterns. This study aimed to investigate effects of clinical and sociodemographic variables on the classification by applying multivariate pattern analysis (MVPA) to both gray matter (GM) volume and FC measures in patients with SZ and healthy controls (HC). RS and structural magnetic resonance imaging data (sMRI) from 74 HC and 71 SZ patients were obtained from a Mind Research Network COBRE dataset available via COINS (http://coins.mrn.org/dx). We used a MVPA framework using support-vector machines embedded in a repeated, nested cross-validation to generate a multi-modal diagnostic system and evaluate its generalizability. The dependence of neurodiagnostic performance on clinical and sociodemographic variables was evaluated. The RS classifier showed a slightly higher accuracy (70.5%) compared to the structural classifier (69.7%). The combination of sMRI and RS outperformed single MRI modalities classification by reaching 75% accuracy. The RS based moderator analysis revealed that the neurodiagnostic performance was driven by older SZ patients with an earlier illness onset and more pronounced negative symptoms. In contrast, there was no linear relationship between the clinical variables and neuroanatomically derived group membership measures. This study achieved higher accuracy distinguishing HC from SZ patients by fusing 2 imaging modalities. In addition the results of RS based moderator analysis showed that age of patients, as well as their age at the illness onset were the most important clinical features.

Metacognitive impairment in active cocaine use disorder is associated with individual differences in brain structure

Dysfunctional self-awareness has been posited as a key feature of drug addiction, contributing to compromised control over addictive behaviors. In the present investigation, we showed that, compared with healthy controls (n=13) and even individuals with remitted cocaine use disorder (n=14), individuals with active cocaine use disorder (n=8) exhibited deficits in basic metacognition, defined as a weaker link between objective performance and self-reported confidence of performance on a visuo-perceptual accuracy task. This metacognitive deficit was accompanied by gray matter volume decreases, also most pronounced in individuals with active cocaine use disorder, in the rostral anterior cingulate cortex, a region necessary for this function in health. Our results thus provide a direct unbiased measurement - not relying on long-term memory or multifaceted choice behavior - of metacognition deficits in drug addiction, which are further mapped onto structural deficits in a brain region that subserves metacognitive accuracy in health and self-awareness in drug addiction. Impairments of metacognition could provide a basic mechanism underlying the higher-order self-awareness deficits in addiction, particularly among recent, active users.

Medium-chain plasma acylcarnitines, ketone levels, cognition, and gray matter volumes in healthy elderly, mildly cognitively impaired, or Alzheimer's disease subjects

Aging, amyloid deposition, and tau-related pathology are key contributors to the onset and progression of Alzheimer's disease (AD). However, AD is also associated with brain hypometabolism and deficits of mitochondrial bioenergetics. Plasma acylcarnitines (ACCs) are indirect indices of altered fatty acid beta-oxidation, and ketogenesis has been found to be decreased on aging. Furthermore, in elderly subjects, alterations in plasma levels of specific ACCs have been suggested to predict conversion to mild cognitive impairment (MCI) or AD. In this study, we assayed plasma profiles of ACCs in a cohort of healthy elderly control, MCI subjects, and AD patients. Compared with healthy controls or MCI subjects, AD patients showed significant lower plasma levels of several medium-chain ACCs. Furthermore, in AD patients, these lower concentrations were associated with lower prefrontal gray matter volumes and the presence of cognitive impairment. Interestingly, lower levels of medium-chain ACCs were also found to be associated with lower plasma levels of 2-hydroxybutyric acid. Overall, these findings suggest that altered metabolism of medium-chain ACCs and impaired ketogenesis can be metabolic features of AD.

Serum S100B Protein is Specifically Related to White Matter Changes in Schizophrenia

Background: Schizophrenia can be conceptualized as a form of dysconnectivity between brain regions.To investigate the neurobiological foundation of dysconnectivity, one approach is to analyze white matter structures, such as the pathology of fiber tracks. S100B is considered a marker protein for glial cells, in particular oligodendrocytes and astroglia, that passes the blood brain barrier and is detectable in peripheral blood. Earlier Studies have consistently reported increased S100B levels in schizophrenia. In this study, we aim to investigate associations between S100B and structural white matter abnormalities.

Methods: We analyzed data of 17 unmedicated schizophrenic patients (first and recurrent episode) and 22 controls. We used voxel based morphometry (VBM) to detect group differences of white matter structures as obtained from T1-weighted MR-images and considered S100B serum levels as a regressor in an age-corrected interaction analysis.

Results: S100B was increased in both patient subgroups. Using VBM, we found clusters indicating significant differences of the association between S100B concentration and white matter. Involved anatomical structures are the posterior cingulate bundle and temporal white matter structures assigned to the superior longitudinal fasciculus.

Conclusions: S100B-associated alterations of white matter are shown to be existent already at time of first manifestation of psychosis and are distinct from findings in recurrent episode patients. This suggests involvement of S100B in an ongoing and dynamic process associated with structural brain changes in schizophrenia. However, it remains elusive whether increased S100B serum concentrations in psychotic patients represent a protective response to a continuous pathogenic process or if elevated S100B levels are actively involved in promoting structural brain damage.

Integrated analysis of gray and white matter alterations in attention-deficit/hyperactivity disorder

BACKGROUND

Magnetic resonance imaging (MRI) is able to provide detailed insights into the structural organization of the brain, e.g., by means of mapping brain anatomy and white matter microstructure. Understanding interrelations between MRI modalities, rather than mapping modalities in isolation, will contribute to unraveling the complex neural mechanisms associated with neuropsychiatric disorders as deficits detected across modalities suggest common underlying mechanisms. Here, we conduct a multimodal analysis of structural MRI modalities in the context of attention-deficit/hyperactivity disorder (ADHD).

METHODS

Gray matter volume, cortical thickness, surface areal expansion estimates, and white matter diffusion indices of 129 participants with ADHD and 204 participants without ADHD were entered into a linked independent component analysis. This data-driven analysis decomposes the data into multimodal independent components reflecting common inter-subject variation across imaging modalities.

RESULTS

ADHD severity was related to two multimodal components. The first component revealed smaller prefrontal volumes in participants with more symptoms, co-occurring with abnormal white matter indices in prefrontal cortex. The second component demonstrated decreased orbitofrontal volume as well as abnormalities in insula, occipital, and somato-sensory areas in participants with more ADHD symptoms.

CONCLUSIONS

Our results replicate and extend previous unimodal structural MRI findings by demonstrating that prefrontal, parietal, and occipital areas, as well as fronto-striatal and fronto-limbic systems are implicated in ADHD. By including multiple modalities, sensitivity for between-participant effects is increased, as shared variance across modalities is modeled. The convergence of modality-specific findings in our results suggests that different aspects of brain structure share underlying pathophysiology and brings us closer to a biological characterization of ADHD.

Association Between Autonomic Impairment and Structural Deficit in Parkinson Disease

Patients with Parkinson disease (PD) have impaired autonomic function and altered brain structure. This study aimed to evaluate the relationship of gray matter volume (GMV) determined by voxel-based morphometry (VBM) to autonomic impairment in patients with PD. Whole-brain VBM analysis was performed on 3-dimensional T1-weighted images in 23 patients with PD and 15 sex- and age-matched healthy volunteers. The relationship of cardiovascular autonomic function (determined by survey) to baroreflex sensitivity (BRS) (determined from changes in heart rate and blood pressure during the early phase II of the Valsalva maneuver) was tested using least-squares regression analysis. The differences in GMV, autonomic parameters, and clinical data were correlated after adjusting for age and sex. Compared with controls, patients with PD had low BRS, suggesting worse cardiovascular autonomic function, and smaller GMV in several brain locations, including the right amygdala, left hippocampal formation, bilateral insular cortex, bilateral caudate nucleus, bilateral cerebellum, right fusiform, and left middle frontal gyri. The decreased GMVs of the selected brain regions were also associated with increased presence of epithelial progenitor cells (EPCs) in the circulation. In patients with PD, decrease in cardiovascular autonomic function and increase in circulating EPC level are associated with smaller GMV in several areas of the brain. Because of its possible role in the modulation of the circulatory EPC pool and baroreflex control, the left hippocampal formation may be a bio-target for disease-modifying therapy and treatment monitoring in PD.

Volumetric brain abnormalities in polysubstance use disorder patients

AIM

Polysubstance users represent the largest group of patients seeking treatment at addiction and rehabilitation clinics in Turkey. There is little knowledge about the structural brain abnormalities seen in polysubstance users. This study was conducted to examine the structural brain differences between polysubstance use disorder patients and healthy control subjects using voxel-based morphometry.

METHODS

Forty-six male polysubstance use disorder patients in the early abstinence period and 30 healthy male controls underwent structural magnetic resonance imaging scans. Voxel-based morphometry analysis was performed to examine gray matter (GM) abnormality differences.

RESULTS

Polysubstance use disorder patients displayed significantly smaller GM volume in the thalamus, temporal pole, superior frontal gyrus, cerebellum, gyrus rectus, occipital lobe, anterior cingulate cortex, superior temporal gyrus, and postcentral gyrus.

CONCLUSION

A widespread and smaller GM volume has been found at different regions of the frontal, temporal, occipital, and parietal lobes, cerebellum, and anterior cingulate cortex in polysubstance users.

MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65–80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.

Robust estimation of unbalanced mixture models on samples with outliers

Mixture models are often used to compactly represent samples from heterogeneous sources. However, in real world, the samples generally contain an unknown fraction of outliers and the sources generate different or unbalanced numbers of observations. Such unbalanced and contaminated samples may, for instance, be obtained by high density data sensors such as imaging devices. Estimation of unbalanced mixture models from samples with outliers requires robust estimation methods. In this paper, we propose a novel robust mixture estimator incorporating trimming of the outliers based on component-wise confidence level ordering of observations. The proposed method is validated and compared to the state-of-the-art FAST-TLE method on two data sets, one consisting of synthetic samples with a varying fraction of outliers and a varying balance between mixture weights, while the other data set contained structural magnetic resonance images of the brain with tumors of varying volumes. The results on both data sets clearly indicate that the proposed method is capable to robustly estimate unbalanced mixtures over a broad range of outlier fractions. As such, it is applicable to real-world samples, in which the outlier fraction cannot be estimated in advance.

Neural correlates of abnormal sensory discrimination in laryngeal dystonia

Aberrant sensory processing plays a fundamental role in the pathophysiology of dystonia; however, its underpinning neural mechanisms in relation to dystonia phenotype and genotype remain unclear. We examined temporal and spatial discrimination thresholds in patients with isolated laryngeal form of dystonia (LD), who exhibited different clinical phenotypes (adductor vs. abductor forms) and potentially different genotypes (sporadic vs. familial forms). We correlated our behavioral findings with the brain gray matter volume and functional activity during resting and symptomatic speech production. We found that temporal but not spatial discrimination was significantly altered across all forms of LD, with higher frequency of abnormalities seen in familial than sporadic patients. Common neural correlates of abnormal temporal discrimination across all forms were found with structural and functional changes in the middle frontal and primary somatosensory cortices. In addition, patients with familial LD had greater cerebellar involvement in processing of altered temporal discrimination, whereas sporadic LD patients had greater recruitment of the putamen and sensorimotor cortex. Based on the clinical phenotype, adductor form-specific correlations between abnormal discrimination and brain changes were found in the frontal cortex, whereas abductor form-specific correlations were observed in the cerebellum and putamen. Our behavioral and neuroimaging findings outline the relationship of abnormal sensory discrimination with the phenotype and genotype of isolated LD, suggesting the presence of potentially divergent pathophysiological pathways underlying different manifestations of this disorder.

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Abnormal temporal but not spatial discrimination is an LD mediational endophenotype.

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Penetrance of abnormal TDT is higher in familial than sporadic LD.

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No differences in penetrance between clinical phenotypes of LD

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Distinct neural phenotype/genotype relations of TDT reflect divergent pathophysiology.

Brain structural correlates of schizotypy and psychosis proneness in a non-clinical healthy volunteer sample

Schizotypal traits are phenotypic risk factors for schizophrenia, associated with biological changes across a putative schizophrenia spectrum. In this study, we tested the hypothesis that brain structural changes in key brain areas relevant to this spectrum (esp. medial and lateral prefrontal cortex) would vary across different degrees of schizotypal trait expression and/or phenotypic markers of psychosis proneness in healthy non-clinical volunteers. We analysed high-resolution 3Tesla magnetic resonance images (MRI) of 59 healthy volunteers using voxel-based morphometry (VBM), correlating grey matter values to the positive and negative symptom factors of the schizotypal personality questionnaire (SPQ, German version) and a measure of psychosis proneness (community assessment of psychic experiences, CAPE). We found positive correlations between positive SPQ dimension and bilateral inferior and right superior frontal cortices, and positive CAPE dimension and left inferior frontal cortex, as well as CAPE negative dimension and right supplementary motor area (SMA) and left inferior parietal cortex. However, only the positive correlation of the right precuneus with negative schizotypy scores was significant after FWE correction for multiple comparisons. Our findings confirm an effect of schizotypal traits and psychosis proneness on brain structure in healthy subjects, providing further support to a biological continuum model.

Stratified mixture modeling for segmentation of white-matter lesions in brain MR images

Accurate characterization of white-matter lesions from magnetic resonance (MR) images has increasing importance for diagnosis and management of treatment of certain neurological diseases, and can be performed in an objective and effective way by automated lesion segmentation. This usually involves modeling the whole-brain MR intensity distribution, however, capturing various sources of MR intensity variability and lesion heterogeneity results in highly complex whole-brain MR intensity models, thus their robust estimation on a large set of MR images presents a huge challenge. We propose a novel approach employing stratified mixture modeling, where the main premise is that the otherwise complex whole-brain model can be reduced to a tractable parametric form in small brain subregions. We show on MR images of multiple sclerosis (MS) patients with different lesion loads that robust estimators enable accurate mixture modeling of MR intensity in small brain subregions even in the presence of lesions. Recombination of the mixture models across strata provided an accurate whole-brain MR intensity model. Increasing the number of subregions and, thereby, the model complexity, consistently improved the accuracy of whole-brain MR intensity modeling and segmentation of normal structures. The proposed approach was incorporated into three unsupervised lesion segmentation methods and, compared to original and three other state-of-the-art methods, the proposed modeling approach significantly improved lesion segmentation according to increased Dice similarity indices and lower number of false positives on real MR images of 30 patients with MS.

Correlating Gray Matter Volume with Individual Difference in the Flanker Interference Effect

The Eriksen Flanker task has been widely used as a measurement of cognitive control, however till now information is still scarce about how the neuroanatomical properties are related to performance in this task. Using voxel-based morphometry technique (VBM), the current study identified a set of distributed areas where the gray matter volume (GM) correlated positively with participants’ efficiency in interference inhibition. These areas included the bilateral prefrontal gyri, left insula and inferior temporal gyrus, the left inferior parietal lobule. Further analysis using a novel machine learning algorithm with balanced cross-validation procedure confirmed that in these areas the GM-behavioral association was unlikely a byproduct of outlier values, instead, the gray matter volume could predict reliably participants’ interference inhibition efficiency. These results underscore the importance of the fronto-parietal and insula systems to the brain functioning of interference inhibition from the neuroanatomical perspective.

Nonlinear cerebral atrophy patterns across the Alzheimer's disease continuum: impact of APOE4 genotype

The progression of Alzheimer's disease (AD) is characterized by complex trajectories of cerebral atrophy that are affected by interactions with age and apolipoprotein E allele ε4 (APOE4) status. In this article, we report the nonlinear volumetric changes in gray matter across the full biological spectrum of the disease, represented by the AD-cerebrospinal fluid (CSF) index. This index reflects the subject's level of pathology and position along the AD continuum. We also evaluated the associated impact of the APOE4 genotype. The atrophy pattern associated with the AD-CSF index was highly symmetrical and corresponded with the typical AD signature. Medial temporal structures showed different atrophy dynamics along the progression of the disease. The bilateral parahippocampal cortices and a parietotemporal region extending from the middle temporal to the supramarginal gyrus presented an initial increase in volume which later reverted. Similarly, a portion of the precuneus presented a rather linear inverse association with the AD-CSF index whereas some other clusters did not show significant atrophy until index values corresponded to positive CSF tau values. APOE4 carriers showed steeper hippocampal volume reductions with AD progression. Overall, the reported atrophy patterns are in close agreement with those mentioned in previous findings. However, the detected nonlinearities suggest that there may be different pathological processes taking place at specific moments during AD progression and reveal the impact of the APOE4 allele.