Aristotle N. Voineskos

Age-related decline in white matter tract integrity and cognitive performance: a DTI tractography and structural equation modeling study.

Age-related decline in microstructural integrity of certain white matter tracts may explain cognitive decline associated with normal aging. Whole brain tractography and a clustering segmentation in 48 healthy individuals across the adult lifespan were used to examine: interhemispheric (corpus callosum), intrahemispheric association (cingulum, uncinate, arcuate, inferior longitudinal, inferior occipitofrontal), and projection (corticospinal) fibers. Principal components analysis reduced cognitive tests into 6 meaningful factors: (1) memory and executive function; (2) visuomotor dexterity; (3) motor speed; (4) attention and working memory; (5) set-shifting/flexibility; and (6) visuospatial construction. Using theory-based structural equation modeling, relationships among age, white matter tract integrity, and cognitive performance were investigated. Parsimonious model fit demonstrated relationships where decline in white matter integrity may explain age-related decline in cognitive performance: inferior longitudinal fasciculus (ILF) with visuomotor dexterity; the inferior occipitofrontal fasciculus with visuospatial construction; and posterior fibers (i.e., splenium) of the corpus callosum with memory and executive function. Our findings suggest that decline in the microstructural integrity of white matter fibers can account for cognitive decline in normal aging.

Brain monoamine oxidase a binding in major depressive disorder: Relationship to selective serotonin reuptake inhibitor treatment, recovery and recurrence

CONTEXT Highly significant elevations in regional brain monoamine oxidase A (MAO-A) binding were recently reported during major depressive episodes (MDEs) of major depressive disorder (MDD). The relationship between MAO-A levels and selective serotonin reuptake inhibitor (SSRI) treatment, recovery, and recurrence in MDD is unknown. OBJECTIVES To determine whether brain MAO-A binding changes after SSRI treatment, whether brain MAO-A binding normalizes in subjects with MDD in recovery, and whether there is a relationship between prefrontal and anterior cingulate cortex MAO-A binding in recovery and subsequent recurrence of MDE. DESIGN Case-control study. SETTING Tertiary care psychiatric hospital. PARTICIPANTS Twenty-eight healthy subjects, 16 subjects with an MDE secondary to MDD, and 18 subjects with MDD in recovery underwent carbon 11-labeled harmine positron emission tomography scans. Subjects with MDE were scanned before and after 6 weeks of SSRI treatment. All were otherwise healthy, nonsmoking, and medication free. Subjects with MDD in recovery were followed up for 6 months after MAO-A binding measurement. MAIN OUTCOME MEASURE Monoamine oxidase A V(T), an index of MAO-A density, was measured in the prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, dorsal putamen, ventral striatum, thalamus, anterior temporal cortex, midbrain, and hippocampus. RESULTS Monoamine oxidase A V(T) was significantly elevated in each brain region both during MDE and after SSRI treatment as compared with healthy controls. During recovery, MAO-A V(T) was significantly elevated in each brain region; however, those who went on to recurrence had significantly higher MAO-A V(T) in the prefrontal and anterior cingulate cortex than those who did not. CONCLUSIONS Elevated MAO-A binding after SSRI treatment indicates persistence of a monoamine-lowering process not present in health. This provides a strong conceptual rationale for continuing SSRI treatment during early remission. Greater MAO-A binding in the prefrontal and anterior cingulate cortex in subjects with MDD in recovery and its association with subsequent recurrence argue that deficient monoamine neuromodulation may persist into recovery and contribute to recurrence.

Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates

INTRODUCTION Advances in image segmentation of magnetic resonance images (MRI) have demonstrated that multi-atlas approaches improve segmentation over regular atlas-based approaches. These approaches often rely on a large number of manually segmented atlases (e.g. 30-80) that take significant time and expertise to produce. We present an algorithm, MAGeT-Brain (Multiple Automatically Generated Templates), for the automatic segmentation of the hippocampus that minimises the number of atlases needed whilst still achieving similar agreement to multi-atlas approaches. Thus, our method acts as a reliable multi-atlas approach when using special or hard-to-define atlases that are laborious to construct. METHOD MAGeT-Brain works by propagating atlas segmentations to a template library, formed from a subset of target images, via transformations estimated by nonlinear image registration. The resulting segmentations are then propagated to each target image and fused using a label fusion method. We conduct two separate Monte Carlo cross-validation experiments comparing MAGeT-Brain and basic multi-atlas whole hippocampal segmentation using differing atlas and template library sizes, and registration and label fusion methods. The first experiment is a 10-fold validation (per parameter setting) over 60 subjects taken from the Alzheimers Disease Neuroimaging Database (ADNI), and the second is a five-fold validation over 81 subjects having had a first episode of psychosis. In both cases, automated segmentations are compared with manual segmentations following the Pruessner-protocol. Using the best settings found from these experiments, we segment 246 images of the ADNI1:Complete 1Yr 1.5 T dataset and compare these with segmentations from existing automated and semi-automated methods: FSL FIRST, FreeSurfer, MAPER, and SNT. Finally, we conduct a leave-one-out cross-validation of hippocampal subfield segmentation in standard 3T T1-weighted images, using five high-resolution manually segmented atlases (Winterburn et al., 2013). RESULTS In the ADNI cross-validation, using 9 atlases MAGeT-Brain achieves a mean Dices Similarity Coefficient (DSC) score of 0.869 with respect to manual whole hippocampus segmentations, and also exhibits significantly lower variability in DSC scores than multi-atlas segmentation. In the younger, psychosis dataset, MAGeT-Brain achieves a mean DSC score of 0.892 and produces volumes which agree with manual segmentation volumes better than those produced by the FreeSurfer and FSL FIRST methods (mean difference in volume: 80 mm(3), 1600 mm(3), and 800 mm(3), respectively). Similarly, in the ADNI1:Complete 1Yr 1.5 T dataset, MAGeT-Brain produces hippocampal segmentations well correlated (r>0.85) with SNT semi-automated reference volumes within disease categories, and shows a conservative bias and a mean difference in volume of 250 mm(3) across the entire dataset, compared with FreeSurfer and FSL FIRST which both overestimate volume differences by 2600 mm(3) and 2800 mm(3) on average, respectively. Finally, MAGeT-Brain segments the CA1, CA4/DG and subiculum subfields on standard 3T T1-weighted resolution images with DSC overlap scores of 0.56, 0.65, and 0.58, respectively, relative to manual segmentations. CONCLUSION We demonstrate that MAGeT-Brain produces consistent whole hippocampal segmentations using only 9 atlases, or fewer, with various hippocampal definitions, disease populations, and image acquisition types. Additionally, we show that MAGeT-Brain identifies hippocampal subfields in standard 3T T1-weighted images with overlap scores comparable to competing methods.

A novel in vivo atlas of human hippocampal subfields using high-resolution 3 T magnetic resonance imaging.

The hippocampus is a neuroanatomical structure that has been widely studied in the context of learning, memory, stress, and neurodegeneration. Neuroanatomically, the hippocampus is subdivided into several subfields with intricate morphologies and complex three-dimensional relationships. Recent studies have demonstrated that the identification of different subfields is possible with high-resolution and -contrast image volumes acquired using ex vivo specimens in a small bore 9.4 T scanner and, more recently, in vivo, at 7 T. In these studies, the neuroanatomical definitions of boundaries between subfields are based upon salient differences in image contrast. Typically, the definition of subfields has not been possible using commonly available magnetic resonance (MR) scanners (i.e.: 1.5 or 3T) due to resolution and contrast limitations. To overcome the limited availability of post-mortem specimens and expertise in state-of-the-art high-field imaging, we propose a coupling of MR acquisition and detailed segmentation techniques that allow for the reliable identification of hippocampal anatomy (including subfields). High-resolution and -contrast T1- and T2-weighted image volumes were acquired from 5 volunteers (2 male; 3 female; age range: 29-57, avg. 37) using a clinical research-grade 3T scanner and have final super-sampled isotropic voxel dimensions of 0.3mm. We demonstrate that by using these acquisition techniques, our data results in contrast-to-noise ratios that compare well with high-resolution images acquired with long scan times using post-mortem data at higher field strengths. For the subfields, the cornus ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus, stratum radiatum/stratum lacunosum/stratum moleculare, and subiculum were all labeled as separate structures. Hippocampal volumes are reported for each of the substructures and the hippocampus as a whole (range for hippocampus: 2456.72-3325.02 mm(3)). Intra-rater reliability of our manual segmentation protocol demonstrates high reliability for the whole hippocampus (mean Dice Kappa of 0.91; range 0.90-0.92) and for each of the subfields (range of Dice Kappas: 0.64-0.83). We demonstrate that our reliability is better than the Dice Kappas produced by simulating the following errors: a translation by a single voxel in all cardinal directions and 1% volumetric shrinkage and expansion. The completed hippocampal atlases are available freely online (info2.camh.net/kf-tigr/index.php/Hippocampus) and can be coupled with novel computational neuroanatomy techniques that will allow for them to be customized to the unique neuroanatomy of different subjects, and ultimately be utilized in different analysis pipelines.

Diffusion tensor tractography findings in schizophrenia across the adult lifespan

In healthy adult individuals, late life is a dynamic time of change with respect to the microstructural integrity of white matter tracts. Yet, elderly individuals are generally excluded from diffusion tensor imaging studies in schizophrenia. Therefore, we examined microstructural integrity of frontotemporal and interhemispheric white matter tracts in schizophrenia across the adult lifespan. Diffusion tensor imaging data from 25 younger schizophrenic patients (< or = 55 years), 25 younger controls, 25 older schizophrenic patients (> or = 56 years) and 25 older controls were analysed. Patients with schizophrenia in each group were individually matched to controls. Whole-brain tractography and clustering segmentation were employed to isolate white matter tracts. Groups were compared using repeated measures analysis of variance with 12 within-group measures of fractional anisotropy: (left and right) uncinate fasciculus, arcuate fasciculus, inferior longitudinal fasciculus, inferior occipito-frontal fasciculus, cingulum bundle, and genu and splenium of the corpus callosum. For each white matter tract, fractional anisotropy was then regressed against age in patients and controls, and correlation coefficients compared. The main effect of group (F(3,92) = 12.2, P < 0.001), and group by tract interactions (F(26,832) = 1.68, P = 0.018) were evident for fractional anisotropy values. Younger patients had significantly lower fractional anisotropy than younger controls (Bonferroni-corrected alpha = 0.0042) in the left uncinate fasciculus (t(48) = 3.7, P = 0.001) and right cingulum bundle (t(48) = 3.6, P = 0.001), with considerable effect size, but the older groups did not differ. Schizophrenic patients did not demonstrate accelerated age-related decline compared with healthy controls in any white matter tract. To our knowledge, this is the first study to examine the microstructural integrity of frontotemporal white matter tracts across the adult lifespan in schizophrenia. The left uncinate fasciculus and right cingulum bundle are disrupted in younger chronic patients with schizophrenia compared with matched controls, suggesting that these white matter tracts are related to frontotemporal disconnectivity. The absence of accelerated age-related decline, or differences between older community-dwelling patients and controls, suggests that these patients may possess resilience to white matter disruption.

Treating Working Memory Deficits in Schizophrenia: A Review of the Neurobiology

Cognitive deficits are a core feature of schizophrenia. Among these deficits, working memory impairment is considered a central cognitive impairment in schizophrenia. The prefrontal cortex, a region critical for working memory performance, has been demonstrated as a critical liability region in schizophrenia. As yet, there are no standardized treatment options for working memory deficits in schizophrenia. In this review, we summarize the neuronal basis for working memory impairment in schizophrenia, including dysfunction in prefrontal signaling pathways (e.g., γ-aminobutyric acid transmission) and neural network synchrony (e.g., gamma/theta oscillations). We discuss therapeutic strategies for working memory dysfunction such as pharmacological agents, cognitive remediation therapy, and repetitive transcranial magnetic stimulation. Despite the drawbacks of current approaches, the advances in neurobiological and translational treatment strategies suggest that clinical application of these methods will occur in the near future.

A review of structural neuroimaging in schizophrenia: from connectivity to connectomics.

In patients with schizophrenia neuroimaging studies have revealed global differences with some brain regions showing focal abnormalities. Examining neurocircuitry, diffusion-weighted imaging studies have identified altered structural integrity of white matter in frontal and temporal brain regions and tracts such as the cingulum bundles, uncinate fasciculi, internal capsules and corpus callosum associated with the illness. Furthermore, structural co-variance analyses have revealed altered structural relationships among regional morphology in the thalamus, frontal, temporal and parietal cortices in schizophrenia patients. The distributed nature of these abnormalities in schizophrenia suggests that multiple brain circuits are impaired, a neural feature that may be better addressed with network level analyses. However, even with the advent of these newer analyses, a large amount of variability in findings remains, likely partially due to the considerable heterogeneity present in this disorder.

The Brain-Derived Neurotrophic Factor Val66Met Polymorphism and Prediction of Neural Risk for Alzheimer Disease

CONTEXT The brain-derived neurotrophic factor (BDNF) Val66Met (rs6265) polymorphism may predict the risk of Alzheimer disease (AD). However, genetic association studies of the BDNF gene with AD have produced equivocal results. Imaging-genetics strategies may clarify the manner in which BDNF gene variation predicts the risk of AD via characterization of its effects on at-risk structures or neural networks susceptible in this disorder. OBJECTIVE To determine whether the BDNF Val66Met gene variant interacts with age to predict brain and cognitive measures in healthy volunteers across the adult lifespan in an intermediate phenotype pattern related to AD by examining (1) cortical thickness, (2) fractional anisotropy of white matter tracts (ie, white matter integrity), and (3) episodic memory performance. DESIGN A cross-sectional study using genetics, high-resolution magnetic resonance imaging, diffusion tensor imaging, and cognitive testing in healthy individuals spanning the adult lifespan. SETTING University hospital. PARTICIPANTS A total of 69 healthy volunteers ranging from 19 to 82 years of age. MAIN OUTCOME MEASURES The BDNF Val66Met genotype, apolipoprotein E genotype, cortical thickness, microstructural integrity of white matter tracts, and episodic memory performance were evaluated. RESULTS The BDNF Val66Met polymorphism interacted with age to predict (1) cortical thickness (prominently at the entorhinal cortex and temporal gyri), (2) fractional anisotropy of white matter tracts (prominently at white matter tracts connecting to the medial temporal lobe), and (3) episodic memory performance. For each of these findings, the pattern was similar: valine/valine individuals in late life were susceptible, and in early adult life, methionine allele carriers demonstrated susceptibility. CONCLUSIONS The BDNF gene confers risk in an age-dependent manner on the brain structures and cognitive functions that are consistent with the neural circuitry vulnerable in the earliest stages of AD. Our novel findings provide convergent evidence in vivo for a BDNF genetic mechanism of susceptibility in an intermediate phenotype related to AD.

The role of the corpus callosum in transcranial magnetic stimulation induced interhemispheric signal propagation.

BACKGROUND The corpus callosum, the main interhemispheric connection in the brain, may serve to preserve functional asymmetry between homologous cortical regions. METHODS To test this hypothesis, 30 healthy adult subjects underwent combined transcranial magnetic stimulation (TMS)-electroencephalography procedures. Nineteen of these subjects also completed diffusion tensor imaging and tractography procedures. We examined the relationship between microstructural integrity of subdivisions of the corpus callosum with TMS-induced interhemispheric signal propagation. RESULTS We found a significant inverse relationship between microstructural integrity of callosal motor fibers with TMS-induced interhemispheric signal propagation from left to right motor cortex. We also found a significant inverse relationship between microstructural integrity of genu fibers of the corpus callosum and TMS-induced interhemispheric signal propagation from left to right dorsolateral prefrontal cortex (DLPFC). We then demonstrated neuroanatomic specificity of these relationships. CONCLUSIONS Taken together, our findings suggest that TMS-induced interhemispheric signal propagation is transcallosally mediated and neuroanatomically specific and support a role for the corpus callosum in preservation of functional asymmetry between homologous cortical regions. Delineation of the relationship between corpus callosum microstructure and interhemispheric signal propagation in neuropsychiatric disorders, such as schizophrenia, may reveal novel mechanisms of pathophysiology.

Can Repetitive Magnetic Stimulation Improve Cognition in Schizophrenia? Pilot Data from a Randomized Controlled Trial

BACKGROUND Working memory represents a core cognitive domain that is impaired in schizophrenia for which there are currently no satisfactory treatments. Repetitive transcranial magnetic stimulation (rTMS) targeted over the dorsolateral prefrontal cortex has been shown to modulate neurophysiological mechanisms linked to working memory in schizophrenia and improves working memory performance in healthy subjects and might therefore represent a treatment modality for schizophrenia patients. The objectives were to evaluate the effects of rTMS on working memory performance in schizophrenia patients and evaluate whether rTMS normalizes performance to healthy subject levels. METHODS In a 4-week randomized double-blind sham-controlled pilot study design, 27 medicated schizophrenia patients were tested at the Centre for Addiction and Mental Health (a university teaching hospital that provides psychiatric care to a large urban catchment area and serves as a tertiary referral center for the province of Ontario). Patients performed the verbal working memory n-back task before and after rTMS magnetic resonance image targeted bilaterally sequentially to left and right dorsolateral prefrontal cortex 750 pulses/side at 20 Hz for 20 treatments. The main outcome measure was mean magnitude of change in the n-back accuracy for target responses with active (n = 13) or sham (n = 12) rTMS treatment course. RESULTS The rTMS significantly improved 3-back accuracy for targets compared with placebo sham (Cohens d = .92). The improvement in 3-back accuracy was also found to be at a level comparable to healthy subjects. CONCLUSIONS These pilot data suggest that bilateral rTMS might be a novel, efficacious, and safe treatment for working memory deficits in patients with schizophrenia.