A public resource of baseline data from the Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease Trial.

INTRODUCTION: The Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease (API ADAD) Trial evaluated the anti-oligomeric amyloid beta (Aß) antibody therapy crenezumab in cognitively unimpaired members of the Colombian presenilin 1 (PSEN1) E280A kindred. We report availability, methods employed to protect confidentiality and anonymity of participants, and process for requesting and accessing baseline data. METHODS: We developed mechanisms to share baseline data from the API ADAD Trial in consultation with experts and other groups sharing data from Alzheimer's disease (AD) prevention trials, balancing the need to protect anonymity and trial integrity with making data broadly available to accelerate progress in the field. We pressure-tested deliberate and inadvertent potential threats under specific assumptions, employed a system to suppress or mask both direct and indirect identifying variables, limited and firewalled data managers, and put forth specific principles requisite to receive data. RESULTS: Baseline demographic, PSEN1 E280A and apolipoprotein E genotypes, florbetapir and fluorodeoxyglucose positron emission tomography, magnetic resonance imaging, clinical, and cognitive data can now be requested by interested researchers. DISCUSSION: Baseline data are publicly available; treatment data and biological samples, including baseline and treatment-related blood-based biomarker data will become available in accordance with our original trial agreement and subsequently developed Collaboration for Alzheimer's Prevention principles. Sharing of these data will allow exploration of important questions including the differential effects of initiating an investigational AD prevention therapy both before as well as after measurable Aß plaque deposition.

Tau Positron-Emission Tomography in Former National Football League Players.

BACKGROUND: Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that has been associated with a history of repetitive head impacts. The neuropathological diagnosis is based on a specific pattern of tau deposition with minimal amyloid-beta deposition that differs from other disorders, including Alzheimer's disease. The feasibility of detecting tau and amyloid deposition in the brains of living persons at risk for CTE has not been well studied. METHODS: We used flortaucipir positron-emission tomography (PET) and florbetapir PET to measure deposition of tau and amyloid-beta, respectively, in the brains of former National Football League (NFL) players with cognitive and neuropsychiatric symptoms and in asymptomatic men with no history of traumatic brain injury. Automated image-analysis algorithms were used to compare the regional tau standardized uptake value ratio (SUVR, the ratio of radioactivity in a cerebral region to that in the cerebellum as a reference) between the two groups and to explore the associations of SUVR with symptom severity and with years of football play in the former-player group. RESULTS: A total of 26 former players and 31 controls were included in the analysis. The mean flortaucipir SUVR was higher among former players than among controls in three regions of the brain: bilateral superior frontal (1.09 vs. 0.98; adjusted mean difference, 0.13; 95% confidence interval [CI], 0.06 to 0.20; P<0.001), bilateral medial temporal (1.23 vs. 1.12; adjusted mean difference, 0.13; 95% CI, 0.05 to 0.21; P<0.001), and left parietal (1.12 vs. 1.01; adjusted mean difference, 0.12; 95% CI, 0.05 to 0.20; P = 0.002). In exploratory analyses, the correlation coefficients in these three regions between the SUVRs and years of play were 0.58 (95% CI, 0.25 to 0.79), 0.45 (95% CI, 0.07 to 0.71), and 0.50 (95% CI, 0.14 to 0.74), respectively. There was no association between tau deposition and scores on cognitive and neuropsychiatric tests. Only one former player had levels of amyloid-beta deposition similar to those in persons with Alzheimer's disease. CONCLUSIONS: A group of living former NFL players with cognitive and neuropsychiatric symptoms had higher tau levels measured by PET than controls in brain regions that are affected by CTE and did not have elevated amyloid-beta levels. Further studies are needed to determine whether elevated CTE-associated tau can be detected in individual persons. (Funded by Avid Radiopharmaceuticals and others.).

Sex differences in cognitive resilience in preclinical autosomal-dominant Alzheimer's disease carriers and non-carriers: Baseline findings from the API ADAD Colombia Trial.

INTRODUCTION: Females may have greater susceptibility to Alzheimer's disease (AD)-pathology. We examined the effect of sex on pathology, neurodegeneration, and memory in cognitively-unimpaired Presenilin-1 (PSEN1) E280A mutation carriers and non-carriers. METHODS: We analyzed baseline data from 167 mutation carriers and 75 non-carriers (ages 30 to 53) from the Alzheimer's Prevention Initiative Autosomal Dominant AD Trial, including florbetapir- and fludeoxyglucose-PET, MRI based hippocampal volume and cognitive testing. RESULTS: Females exhibited better delayed recall than males, controlling for age, precuneus glucose metabolism, and mutation status, although the effect was not significant among PSEN1 mutation carriers only. APOE ε4 did not modify the effect of sex on AD biomarkers and memory. DISCUSSION: Our findings suggest that, among cognitively-unimpaired individuals at genetic risk for autosomal-dominant AD, females may have greater cognitive resilience to AD pathology and neurodegeneration than males. Further investigation of sex-specific differences in autosomal-dominant AD is key to elucidating mechanisms of AD risk and resilience.

Brain imaging measurements of fibrillar amyloid-ß burden, paired helical filament tau burden, and atrophy in cognitively unimpaired persons with two, one, and no copies of the APOE ε4 allele.

INTRODUCTION: We previously characterized associations between brain imaging measurements of amyloid-ß (Aß) plaque burden and apolipoprotein E (APOE) ε4 gene dose in a small number of cognitively unimpaired late-middle-aged APOE ε4 homozygotes (HMs), heterozygotes (HTs), and noncarriers (NCs). We now characterize cross-sectional Aß plaque, tau tangle, and cortical atrophy (neurodegeneration) measurements, classifications, and associations with age in a larger number of unimpaired HMs, HTs, and NCs over a wider age range. METHODS: We analyzed 11 C Pittsburgh compound B (Aß) positron emission tomography (PET), flortaucipir (tau) PET, and volumetric magnetic resonance imaging data from 164 study participants of age 47-86 years, including 26 APOE ε4 HMs, 48 HTs, and 90 NCs matched for age and sex. RESULTS: Aß PET measurements rose, plateaued at the respective ages of 68 and 76, and then declined with age in unimpaired HM and HT groups. Compared with NCs, these two groups began to have significantly higher Aß PET measurements at ages 62 and 70, respectively, and no longer had significantly higher measurements by ages 71 and 78, respectively. They began to have significantly higher entorhinal cortex tau PET measurements at ages 66 and 70, respectively, and no longer had significantly higher measurements by ages 74 and 78, respectively. Brain atrophy measurements tended to decline slowly with age in all three genetic groups. Their elevated tau PET measurements were attributable to those with positive Aß PET scans. 41.0%, 18.0%, and 5.0% of the 47- to 70-year-old HMs, HTs, and NCs and 25.0%, 79.0%, and 38.0% of the 71- to 86-year-old HMs, HTs, and NCs had positive Aß PET scans, and the long-term recall memory scores are significantly higher in the older HMs than in HT and NC groups, suggesting resistance to Aß deposition in those HMs who remained unimpaired at older ages. CONCLUSIONS: This study provides information about Aß plaque burden, tau tangle burden, and neurodegeneration in cognitively unimpaired persons at three levels of genetic risk for AD. Unimpaired APOE ε4 HMs can be studied before their 70s to evaluate the understanding of factors, processes, and interventions involved in the predisposition to and prevention of AD, and after their 70s, to discover factors, processes, and interventions involved in the resilience or resistance to and prevention of AD.

Baseline demographic, clinical, and cognitive characteristics of the Alzheimer's Prevention Initiative (API) Autosomal-Dominant Alzheimer's Disease Colombia Trial.

INTRODUCTION: The API AutosomalDominant AD (ADAD) Colombia Trial is a placebo-controlled clinical trial of crenezumab in 252 cognitively unimpaired 30 to 60-year-old Presenilin 1 (PSEN1) E280A kindred members, including mutation carriers randomized to active treatment or placebo and non-carriers who receive placebo. METHODS: Of the 252 enrolled, we present data on a total of 242 mutation carriers and non-carriers matched by age range, excluding data on 10 participants to protect participant confidentiality, genetic status, and trial integrity. RESULTS: We summarize demographic, clinical, cognitive, and behavioral data from 167 mutation carriers and 75 non-carriers, 30 to 53 years of age. Carriers were significantly younger than non-carriers ((mean age ± SD) 37 ± 5 vs 42 ± 6), had significantly lower Mini Mental Status Exam (MMSE) scores (28.8 ± 1.4 vs 29.2 ± 1.0), and had consistently lower memory scores. DISCUSSION: Although PSEN1 E280A mutation carriers in the Trial are cognitively unimpaired, they have slightly lower MMSE and memory scores than non-carriers. Their demographic characteristics are representative of the local population.

Differences in cortico-striatal-cerebellar activation during working memory in syndromal and nonsyndromal children with prenatal alcohol exposure.

Although children with heavy prenatal alcohol exposure may exhibit the distinctive facial dysmorphology seen in full or partial fetal alcohol syndrome (FAS/PFAS), many lack that dysmorphology. This study examined the functional organization of working memory in the brain in three groups of children-those meeting diagnostic criteria for FAS or PFAS, heavily exposed (HE) nonsyndromal children, and healthy controls. A verbal n-back task (1-back and 0-back) was administered to 47 children (17 with FAS/PFAS, 13 HE, and 17 controls) during fMRI. Intra-group one-sample t-tests were used to identify activity regions of interest central to verbal working memory including the dorsal prefrontal cortex (dPFC), inferior frontal gyrus, caudate/putamen, parietal cortex, and cerebellar Crus I/lobule VI and lobule VIIB-IX. Whereas groups did not differ in task sensitivity, fMRI analyses suggested different patterns of sub-network recruitment across groups. Controls primarily recruited left inferior frontal gyrus (Broca's area). By contrast, HE primarily recruited an extensive set of fronto-striatal regions, including left dPFC and left caudate, and the FAS/PFAS group relied primarily on two cerebellar subregions and parietal cortex. This study is, to our knowledge, the first to demonstrate differential recruitment of critical brain regions that subserve basic function in children with different fetal alcohol spectrum disorders compared to controls. The distinct activation patterns seen in the two exposed groups may be related to substantial differences in alcohol dose/occasion to which these groups were exposed in utero.

Individualized network analysis: A novel approach to investigate tau PET using graph theory in the Alzheimer's disease continuum.

Introduction: Tau PET imaging has emerged as an important tool to detect and monitor tangle burden in vivo in the study of Alzheimer's disease (AD). Previous studies demonstrated the association of tau burden with cognitive decline in probable AD cohorts. This study introduces a novel approach to analyze tau PET data by constructing individualized tau network structure and deriving its graph theory-based measures. We hypothesize that the network- based measures are a measure of the total tau load and the stage through disease. Methods: Using tau PET data from the AD Neuroimaging Initiative from 369 participants, we determine the network measures, global efficiency, global strength, and limbic strength, and compare with two regional measures entorhinal and tau composite SUVR, in the ability to differentiate, cognitively unimpaired (CU), MCI and AD. We also investigate the correlation of these network and regional measures and a measure of memory performance, auditory verbal learning test for long-term recall memory (AVLT-LTM). Finally, we determine the stages based on global efficiency and limbic strength using conditional inference trees and compare with Braak staging. Results: We demonstrate that the derived network measures are able to differentiate three clinical stages of AD, CU, MCI, and AD. We also demonstrate that these network measures are strongly correlated with memory performance overall. Unlike regional tau measurements, the tau network measures were significantly associated with AVLT-LTM even in cognitively unimpaired individuals. Stages determined from global efficiency and limbic strength, visually resembled Braak staging. Discussion: The strong correlations with memory particularly in CU suggest the proposed technique may be used to characterize subtle early tau accumulation. Further investigation is ongoing to examine this technique in a longitudinal setting.

Brain activation patterns during visual episodic memory processing among first-degree relatives of schizophrenia subjects.

Episodic memory deficits are proposed as a potential intermediate phenotype of schizophrenia. We examined deficits in visual episodic memory and associated brain activation differences among early course schizophrenia (n=22), first-degree relatives (n=16) and healthy controls without personal or family history of psychotic disorders (n=28). Study participants underwent functional magnetic resonance imaging on a 3T scanner while performing visual episodic memory encoding and retrieval task. We examined in-scanner behavioral performance evaluating response time and accuracy of performance. Whole-brain BOLD response differences were analyzed using SPM5 correcting for multiple comparisons. There was an incremental increase in response time among the study groups (healthy controls

Fronto-parietal hypo-activation during working memory independent of structural abnormalities: conjoint fMRI and sMRI analyses in adolescent offspring of schizophrenia patients.

Adolescent offspring of schizophrenia patients (HR-S) are an important group in whom to study impaired brain function and structure, particularly of the frontal cortices. Studies of working memory have suggested behavioral deficits and fMRI-measured hypoactivity in fronto-parietal regions in these subjects. Independent structural MRI (sMRI) studies have suggested exaggerated frontal gray matter decline. Therefore the emergent view is that fronto-parietal deficits in function and structure characterize HR-S. However, it is unknown if fronto-parietal sub-regions in which fMRI-measured hypo-activity might be observed are precisely those regions of the cortex in which gray matter deficits are also observed. To investigate this question we conducted conjoint analyses of fronto-parietal function and structure in HR-S (n=19) and controls (n=24) with no family history of psychoses using fMRI data during a continuous working memory task (2 back), and sMRI collected in the same session. HR-S demonstrated significantly reduced BOLD activation in left dorso-lateral prefrontal cortex (BA 9/46) and bilateral parietal cortex (BA 7/40). Sub-regions of interest were created from the significant fronto-parietal functional clusters. Analyses of gray matter volume from volume-modulated gray matter segments in these clusters did not reveal significant gray matter differences between groups. The results suggest that functional impairments in adolescent HR-S can be independent of impairments in structure, suggesting that the relationship between impaired function and structure is complex. Further studies will be needed to more closely assess whether impairments in function and structure provide independent or interacting pathways of vulnerability in this population.

PET evidence of preclinical cerebellar amyloid plaque deposition in autosomal dominant Alzheimer's disease-causing Presenilin-1 E280A mutation carriers.

BACKGROUND: In contrast to sporadic Alzheimer's disease, autosomal dominant Alzheimer's disease (ADAD) is associated with greater neuropathological evidence of cerebellar amyloid plaque (Aß) deposition. In this study, we used positron emission tomography (PET) measurements of fibrillar Aß burden to characterize the presence and age at onset of cerebellar Aß deposition in cognitively unimpaired (CU) Presenilin-1 (PSEN1) E280A mutation carriers from the world's largest extended family with ADAD. METHODS: 18F florbetapir and 11C Pittsburgh compound B (PiB) PET data from two independent studies - API ADAD Colombia Trial (NCT01998841) and Colombia-Boston (COLBOS) longitudinal biomarker study were included. The tracers were selected independently by the respective sponsors prior to the start of each study and used exclusively throughout. Template-based cerebellar Aß-SUVR (standard-uptake value ratios) using a known-to-be-spared pons reference region (cerebellar SUVR_pons), to a) compare 28-56-year-old CU carriers and non-carriers; b) estimate the age at which cerebellar SUVR_pons began to differ significantly in carrier and non-carrier groups; and c) characterize in carriers associations with age, cortical SUVR_pons, delayed recall memory, and API ADAD composite score. RESULTS: Florbetapir and PiB cerebellar SUVR_pons were significantly higher in carriers than non-carriers (p < 0.0001). Cerebellar SUVR_pons began to distinguish carriers from non-carriers at age 34, 10 years before the carriers' estimated age at mild cognitive impairment onset. Florbetapir and PiB cerebellar SUVR_pons in carriers were positively correlated with age (r = 0.44 & 0.69, p < 0.001), cortical SUVR_pons (r = 0.55 & 0.69, p < 0.001), and negatively correlated with delayed recall memory (r = -0.21 & -0.50, p < 0.05, unadjusted for cortical SUVR_pons) and API ADAD composite (r = -0.25, p < 0.01, unadjusted for cortical SUVR_pons in florbetapir API ADAD cohort). CONCLUSION: This PET study provides evidence of cerebellar Aß plaque deposition in CU carriers starting about a decade before the clinical onset of ADAD. Additional studies are needed to clarify the impact of using a cerebellar versus pons reference region on the power to detect and track ADAD changes, even in preclinical stages of this disorder.

Grey matter volume reductions in the emotion network of patients with depression and coronary artery disease.

Coronary Artery Disease (CAD) and Major Depressive Disorder (MDD) commonly co-occur and may be linked by a network of brain regions involved in emotion regulation, including the orbitofrontal cortex, amygdala/parahippocamal region and insula. We hypothesized structural differences in this emotion network more prominently in CAD+MDD versus CAD and healthy control (CTRL) groups that do not involve depression-related emotion circuitry. In contrast, we hypothesized structural similarities between CAD+MDD and MDD groups, both involving depression-related circuitry. We obtained structural magnetic resonance imaging scans from age-matched consenting subjects (CAD+MDD, n = 12; CAD, n = 12; MDD, n = 19; CTRL, n = 17) and performed a region of interest analysis. We found decreased grey matter volumes in the bilateral orbitofrontal cortex, bilateral amygdala/parahippocampal gyrus and right insula in CAD+MDD versus CTRL subjects and decreased grey matter volumes in the bilateral amygdala/parahippocampal regions in CAD+MDD versus CAD subjects. We found grey matter reductions in the right orbitofrontal cortex of CAD+MDD versus MDD subjects, and reductions in right insula of CAD versus CRTL subjects. Our results support that the network of brain regions involved in emotion regulation may be relevant to the relationship between CAD and MDD.

Evidence of gray matter reduction and dysfunction in chromosome 22q11.2 deletion syndrome.

Chromosome 22q11.2 deletion syndrome (22q11DS) is associated with cognitive deficits and morphometric brain abnormalities in childhood and a markedly elevated risk of schizophrenia in adolescence/early adulthood. Determining the relationship between neurocognition and neuroimaging findings would yield crucial information about childhood neurodevelopment and provide a basis for the study of the trajectory that occurs on the pathway to psychosis. We compared morphometric brain findings between non-psychotic children with 22q11DS (n = 22) and healthy controls (n = 16), and examined the association between neurocognitive functioning and morphometric brain findings. Volumetric regional gray matter differences between the 22q11DS and control subjects were measured, and correlations of the regional gray matter volumes and neurocognition were performed. Children with 22q11DS demonstrated reductions in gray matter in several brain regions, chiefly the frontal cortices, the cingulate gyrus and the cerebellum. The volumetric reductions in these salient areas were associated with poor performance in sustained attention, executive function and verbal memory; however, the relation of brain volume with cognitive performance did not differ between the patient and control groups. Thus, children with 22q11DS demonstrate gray matter reductions in multiple brain regions that are thought to be relevant to schizophrenia. The correlation of these volumetric reductions with poor neurocognition indicates that these brain regions may mediate higher neurocognitive functions implicated in schizophrenia.

AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction.

The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective intervention and patient selection in clinical trials. Different biomarkers including neuroimaging have been developed to serve the purpose. With extensive methodology development efforts on neuroimaging, an emerging field is deep learning research. One great challenge facing deep learning is the limited medical imaging data available. To address the issue, researchers explore the use of transfer learning to extend the applicability of deep models on neuroimaging research for AD diagnosis and prognosis. Existing transfer learning models mostly focus on transferring the features from the pre-training into the fine-tuning stage. Recognizing the advantages of the knowledge gained during the pre-training, we propose an AD-NET (Age-adjust neural network) with the pre-training model serving two purposes: extracting and transferring features; and obtaining and transferring knowledge. Specifically, the knowledge being transferred in this research is an age-related surrogate biomarker. To evaluate the effectiveness of the proposed approach, AD-NET is compared with 8 classification models from literature using the same public neuroimaging dataset. Experimental results show that the proposed AD-NET outperforms the competing models in predicting the MCI patients at risk for conversion to the AD stage.

Computing Univariate Neurodegenerative Biomarkers with Volumetric Optimal Transportation: A Pilot Study.

Changes in cognitive performance due to neurodegenerative diseases such as Alzheimer's disease (AD) are closely correlated to the brain structure alteration. A univariate and personalized neurodegenerative biomarker with strong statistical power based on magnetic resonance imaging (MRI) will benefit clinical diagnosis and prognosis of neurodegenerative diseases. However, few biomarkers of this type have been developed, especially those that are robust to image noise and applicable to clinical analyses. In this paper, we introduce a variational framework to compute optimal transportation (OT) on brain structural MRI volumes and develop a univariate neuroimaging index based on OT to quantify neurodegenerative alterations. Specifically, we compute the OT from each image to a template and measure the Wasserstein distance between them. The obtained Wasserstein distance, Wasserstein Index (WI) for short to specify the distance to a template, is concise, informative and robust to random noise. Comparing to the popular linear programming-based OT computation method, our framework makes use of Newton's method, which makes it possible to compute WI in large-scale datasets. Experimental results, on 314 subjects (140 Aß + AD and 174 Aß- normal controls) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset, provide preliminary evidence that the proposed WI is correlated with a clinical cognitive measure (the Mini-Mental State Examination (MMSE) score), and it is able to identify group difference and achieve a good classification accuracy, outperforming two other popular univariate indices including hippocampal volume and entorhinal cortex thickness. The current pilot work suggests the application of WI as a potential univariate neurodegenerative biomarker.

Cannabis use and brain structural alterations in first episode schizophrenia--a region of interest, voxel based morphometric study.

Structural alterations of the brain in schizophrenia have been associated with genetic and environmental factors. Among the environmental factors, cannabis use has been associated with increased risk for patients with schizophrenia, but the effect of cannabis on their brain structure is unclear. We examined gray matter alterations in first episode schizophrenia patients (FES) with cannabis use (FES+C; n=15) compared to FES without cannabis use (FES-C; n=24) and 42 healthy controls who did not use cannabis. We conducted a voxel based morphometric analysis of a priori determined regions of interest consisting of the CB1 receptor rich brain regions. We observed a decrease in gray matter density in the right posterior cingulate cortex (PCC) in FES+C when compared with FES-C. The results suggest that cannabis use may be associated with altered brain structure, in particular regions rich in CB1 receptors. These findings need to be confirmed by larger, prospective studies.

An integrated psychobiological predictive model of emergent psychopathology among young relatives at risk for schizophrenia.

OBJECTIVE: Studies of young relatives at elevated risk for schizophrenia have pointed to the importance of a variety of neurobiological, cognitive, and clinical risk factors for the disorder; yet few have employed integrated models to estimate the joint contribution of these factors to heightened schizophrenic risk. We tested the predictive power of an integrated psychobiological model of schizophrenia risk to subsequent psychopathology development among young relatives at risk for the disorder. METHODS: Young first (n=66) and second (n=20) degree relatives of schizophrenia probands were followed for an average of 3 (SD=1.13) years to examine their trajectories toward psychopathology development. Neurobiologic, cognitive, and clinical measures were employed in an integrated structural equation model to estimate their contribution to the prospective emergence of psychopathology. RESULTS: Results indicated that neurobiological, neurocognitive, and psychosis proneness factors at baseline were all uniquely predictive of subsequent psychopathology development, and that an integrated model of psychopathology development that took into account these factors provided an excellent fit to the observed data. Subsequent classification analyses of model accuracy using likelihood ratios adjusting for the base-rate of psychopathology development in this sample revealed that individuals identified by this model had a 71% chance of developing psychopathology in the future. CONCLUSIONS: An integrated model of biobehavioral risk factors may provide a powerful method for predicting psychopathology and schizophrenia risk in at-risk samples. If validated, this model may be useful for early detection and intervention programs. Future research will need to focus particularly on predicting schizophrenia development and refining models to further enhance sensitivity.

Structural brain abnormalities in borderline personality disorder: a voxel-based morphometry study.

Imaging studies using region-of-interest morphometry and positron emission tomography have contributed to our understanding of structural and functional abnormalities in borderline personality disorder (BPD); however, both methods have practical limitations to their usefulness for exploratory studies of brain-behavior relationships. We used voxel-based morphometry (VBM) in 34 subjects with BPD and 30 healthy control (HC) subjects to study effects of diagnosis, gender, childhood sexual abuse, depressed mood, impulsivity and aggression on group differences. VBM is a computer-based method for whole brain analysis that combines the advantages of a functional study with a structural method. The BPD subjects, diagnosed with the Diagnostic Interview for Borderline Patients and the International Personality Disorders Examination, were compared with 30 HC subjects, with age and gender covaried. Analyses were repeated separately by gender and, in women, by histories of childhood sexual abuse. Depressed mood, impulsivity, and aggression were covaried in separate analyses. Compared with HC, BPD subjects had significant bilateral reductions in gray matter concentrations in ventral cingulate gyrus and several regions of the medial temporal lobe, including the hippocampus, amygdala, parahippocampal gyrus, and uncus. BPD women (and abused BPD women), but not BPD men, had significant reductions in medial temporal lobe, including the amygdala. BPD men, but not BPD women, showed diminished gray matter concentrations in the anterior cingulate gyrus compared with findings in HC subjects. Covarying for depressed mood rendered group differences non-significant in the ventral cingulate but had little effect on differences in medial temporal cortex. Covarying for aggression (LHA) had relatively little effect on group differences, while covarying for impulsivity, as determined by the Barratt Impulsiveness Scale, rendered all previously noted voxel-level group differences non-significant. Diminished gray matter in the prefrontal cortex and the medial temporal cortex may mediate the dysregulation of impulse and affect in BPD. Group differences varied greatly by gender, levels of depression, and impulsivity. VBM is an efficient method for exploratory study of brain-behavior relationships.

fMRI BOLD response to the eyes task in offspring from multiplex alcohol dependence families.

BACKGROUND: Increased susceptibility for developing alcohol dependence (AD) may be related to structural and functional differences in brain circuits that influence social cognition and more specifically, theory of mind (ToM). Alcohol dependent individuals have a greater likelihood of having deficits in social skills and greater social alienation. These characteristics may be related to inherited differences in the neuroanatomical network that comprises the social brain. METHODS: Adolescent/young adult participants from multiplex AD families and controls (n = 16) were matched for gender, age, IQ, education, and handedness and administered the Eyes Task of Baron-Cohen during functional magnetic resonance imaging (fMRI). RESULTS: High-risk (HR) subjects showed significantly diminished blood oxygen level dependent (BOLD) response in comparison with low-risk control young adults in the right middle temporal gyrus (RMTG) and the left inferior frontal gyrus (LIFG), areas that have previously been implicated in ToM tasks. CONCLUSIONS: Offspring from multiplex families for AD may manifest one aspect of their genetic susceptibility by having a diminished BOLD response in brain regions associated with performance of ToM tasks. These results suggest that those at risk for developing AD may have reduced ability to empathize with others' state of mind, possibly resulting in diminished social skill.

Deep Learning based Classification of FDG-PET Data for Alzheimers Disease Categories.

Fluorodeoxyglucose (FDG) positron emission tomography (PET) measures the decline in the regional cerebral metabolic rate for glucose, offering a reliable metabolic biomarker even on presymptomatic Alzheimer's disease (AD) patients. PET scans provide functional information that is unique and unavailable using other types of imaging. However, the computational efficacy of FDG-PET data alone, for the classification of various Alzheimers Diagnostic categories, has not been well studied. This motivates us to correctly discriminate various AD Diagnostic categories using FDG-PET data. Deep learning has improved state-of-the-art classification accuracies in the areas of speech, signal, image, video, text mining and recognition. We propose novel methods that involve probabilistic principal component analysis on max-pooled data and mean-pooled data for dimensionality reduction, and multilayer feed forward neural network which performs binary classification. Our experimental dataset consists of baseline data of subjects including 186 cognitively unimpaired (CU) subects, 336 mild cognitive impairment (MCI) subjects with 158 Late MCI and 178 Early MCI, and 146 AD patients from Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We measured F1-measure, precision, recall, negative and positive predictive values with a 10-fold cross validation scheme. Our results indicate that our designed classifiers achieve competitive results while max pooling achieves better classification performance compared to mean-pooled features. Our deep model based research may advance FDG-PET analysis by demonstrating their potential as an effective imaging biomarker of AD.

An Optimal Transportation based Univariate Neuroimaging Index.

The alterations of brain structures and functions have been considered closely correlated to the change of cognitive performance due to neurodegenerative diseases such as Alzheimer's disease. In this paper, we introduce a variational framework to compute the optimal transformation (OT) in 3D space and propose a univariate neuroimaging index based on OT to measure such alterations. We compute the OT from each image to a template and measure the Wasserstein distance between them. By comparing the distances from all the images to the common template, we obtain a concise and informative index for each image. Our framework makes use of the Newton's method, which reduces the computational cost and enables itself to be applicable to large-scale datasets. The proposed work is a generic approach and thus may be applicable to various volumetric brain images, including structural magnetic resonance (sMR) and fluorodeoxyglucose positron emission tomography (FDG-PET) images. In the classification between Alzheimer's disease patients and healthy controls, our method achieves an accuracy of 82.30% on the Alzheimers Disease Neuroimaging Initiative (ADNI) baseline sMRI dataset and outperforms several other indices. On FDG-PET dataset, we boost the accuracy to 88.37% by leveraging pairwise Wasserstein distances. In a longitudinal study, we obtain a 5% significance with p-value = 1.13×105 in a t-test on FDG-PET. The results demonstrate a great potential of the proposed index for neuroimage analysis and the precision medicine research.