Interruption of perivascular sympathetic nerves of cerebral arteries offers neuroprotection against ischemia.

Sympathetic nervous system activity is increased after cardiopulmonary arrest, resulting in vasoconstrictor release from the perivascular sympathetic nerves of cerebral arteries. However, the pathophysiological function of the perivascular sympathetic nerves in the ischemic brain remains unclear. A rat model of global cerebral ischemia (asphyxial cardiac arrest, ACA) was used to investigate perivascular sympathetic nerves of cerebral arteries via bilateral decentralization (preganglionic lesion) of the superior cervical ganglion (SCG). Decentralization of the SCG 5 days before ACA alleviated hypoperfusion and afforded hippocampal neuroprotection and improved functional outcomes. These studies can provide further insights into the functional mechanism(s) of the sympathetic nervous system during ischemia. NEW & NOTEWORTHY: Interruption of the perivascular sympathetic nerves can alleviate CA-induced hypoperfusion and neuronal cell death in the CA1 region of the hippocampus to enhance functional learning and memory.

Loss of white matter integrity in major depressive disorder: evidence using tract-based spatial statistical analysis of diffusion tensor imaging.

White matter (WM) has been shown to be affected in elderly patients with major depressive disorders (MDD). There is only limited evidence of WM structural abnormalities in nongeriatric MDD patients. This study investigates WM microstructural integrity in nongeriatric MDD patients recruited as part of the International Study to Predict Optimized Treatment in Depression clinical trial and establishes the validity of diffusion tensor imaging measures for the investigation of depression. Baseline diffusion tensor imaging data from 29 nongeriatric MDD participants (11 with melancholia) and 39 healthy control participants were used in this analysis. We performed tract-based spatial statistics analyses to evaluate WM microstructural integrity (1) between all healthy controls and all MDD participants, (2) between melancholic and nonmelancholic MDD participants, and (3) between each subgroup (melancholic and nonmelancholic) and controls. Significant WM integrity deficits were seen only for the melancholic MDD participants compared with controls. Compared with controls, melancholic participants showed an average reduction of 7.8% in fractional anisotropy over WM regions associated with the limbic system, dorsolateral prefrontal cortex, thalamic projection fibers, corpus callosum, and other association fibers. These fractional anisotropy deficits were also associated with decreased axial and increased radial diffusivity in these WM regions, suggesting a pattern of decreased myelination or other degeneration change. Our findings of WM structural abnormalities associated with the limbic system, the frontal cortex, and the thalamus support the prevailing theory of limbic-dorsolateral prefrontal cortex-thalamic dysfunction in depression. Our results also suggest that these deficits are most prominent in the melancholic subtype of MDD.

Is occipital bending a structural biomarker of risk for depression and sensitivity to treatment?

Occipital bending (OB) describes asymmetry of the occipital lobes where one lobe wraps across the midline, and has been associated with the presence of mood disorders. We evaluated the relationship between OB and major depressive disorder (MDD) in a large population of subjects from the International Study to Predict Optimized Treatment in Depression. MDD patients (n = 231) and healthy controls (n = 68) underwent MRI and neuropsychiatric evaluation, including response or remission to antidepressant medication at baseline and at 8 weeks. Cortical thickness, ventricular volumes and regional grey matter volumes were measured. OB was visually assessed and OB angle measured using a semi-automated method. Correlations with MDD diagnosis, MRI measures and clinical features were tested. Results demonstrated a greater proportion of rightwards OB in MDD compared to control subjects (p = 0.02). There was no difference in the total prevalence of OB (combined left and rightward bending) between MDD and controls. MDD subjects with right OB had greater cortical thickness in three medial occipital regions (cuneus, lingual gyrus and calcarine sulcus) on the left. Lateral ventricular size was 20% lower bilaterally in right OB MDD subjects compared to non-OB MDD subjects. OB was not associated with severity (HDRS-17). Our data suggest the presence of a strong link between greater rightward occipital bending and MDD. Rightward-OB is associated with greater left medial occipital cortical thickness, and with reduced lateral ventricular size. The cause for greater rightward bending in MDD patients is unclear, however our data suggest a developmental aetiology.

Gender-specific structural abnormalities in major depressive disorder revealed by fixel-based analysis.

BACKGROUND: Major depressive disorder (MDD) is a chronic disease with a large global impact. There are currently no clinically useful predictors of treatment outcome, and the development of biomarkers to inform clinical treatment decisions is highly desirable. METHODS: In this exploratory study we performed fixel-based analysis of diffusion MRI data from the International Study to Predict Optimized Treatment in Depression with the aim of identifying novel biomarkers at baseline that may relate to diagnosis and outcome to treatment with antidepressant medications. Analyses used MR data from individuals with MDD (n = 221) and healthy controls (n = 67). RESULTS: We show focal, gender-specific differences in the anterior limb of the internal capsule (males) and bilaterally in the genu of the corpus callosum (females) associated with diagnosis. Lower fibre cross-section in the tapetum, the conduit between the right and left hippocampi, were also associated with a decreased probability of remission. Analysis of conventional fractional anisotropy showed scattered abnormalities in the corona radiata, cerebral peduncles and mid-brain which were much lower in total volume compared to fixel-based analysis. CONCLUSIONS: Fixel-based analysis appeared to identify different underlying abnormalities than conventional tensor-based metrics, with almost no overlap between significant regions. We show that MDD is associated with gender specific abnormalities in the genu of the corpus callosum (females) and in the anterior limb of the internal capsule (males), as well as gender-independent differences in the tapetum that predict remission. Diffusion MRI may play a key role in future guidance of clinical decision-making for MDD.

Profound and reproducible patterns of reduced regional gray matter characterize major depressive disorder.

Reduced gray matter (GM) volume may represent a hallmark of major depressive disorder (MDD) neuropathology, typified by wide-ranging distribution of structural alteration. In the study, we aimed to replicate and extend our previous finding of profound and widespread GM loss in MDD, and evaluate the diagnostic accuracy of a structural biomarker derived from GM volume in an interconnected pattern across the brain. In a sub-study of the International Study to Predict Optimized Treatment in Depression (iSPOT-D), two cohorts of clinically defined MDD participants "Test" (n = 98) and "Replication" (n = 131) were assessed alongside healthy controls (n = 66). Using 3T MRI T1-weighted volumes, GM volume differences were evaluated using voxel-based morphometry. Sensitivity, specificity, and area under the receiver operating characteristic curve were used to evaluate an MDD diagnostic biomarker based on a precise spatial pattern of GM loss constructed using principal component analysis. We demonstrated a highly conserved symmetric widespread pattern of reduced GM volume in MDD, replicating our previous findings. Three bilateral dominant clusters were observed: Cluster 1: midline/cingulate (GM reduction: Test: 6.4%, Replication: 5.3%), Cluster 2: medial temporal lobe (GM reduction: Test: 8.2%, Replication: 11.9%), Cluster 3: prefrontal cortex (GM reduction: Test: 12.1%, Replication: 23.2%). We developed a biomarker reflecting the global pattern of GM reduction, achieving good diagnostic classification performance (AUC: Test = 0.75, Replication = 0.84). This study establishes that a highly specific pattern of reduced GM volume is a feature of MDD, suggestive of a structural basis for this disease. We introduce and validate a novel diagnostic biomarker based on this pattern.

Neuroscience data and tool sharing: a legal and policy framework for neuroinformatics.

The requirements for neuroinformatics to make a significant impact on neuroscience are not simply technical--the hardware, software, and protocols for collaborative research--they also include the legal and policy frameworks within which projects operate. This is not least because the creation of large collaborative scientific databases amplifies the complicated interactions between proprietary, for-profit R&D and public "open science." In this paper, we draw on experiences from the field of genomics to examine some of the likely consequences of these interactions in neuroscience. Facilitating the widespread sharing of data and tools for neuroscientific research will accelerate the development of neuroinformatics. We propose approaches to overcome the cultural and legal barriers that have slowed these developments to date. We also draw on legal strategies employed by the Free Software community, in suggesting frameworks neuroinformatics might adopt to reinforce the role of public-science databases, and propose a mechanism for identifying and allowing "open science" uses for data whilst still permitting flexible licensing for secondary commercial research.

Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience.

There is significant interest amongst neuroscientists in sharing neuroscience data and analytical tools. The exchange of neuroscience data and tools between groups affords the opportunity to differently re-analyze previously collected data, encourage new neuroscience interpretations and foster otherwise uninitiated collaborations, and provide a framework for the further development of theoretically based models of brain function. Data sharing will ultimately reduce experimental and analytical error. Many small Internet accessible database initiatives have been developed and specialized analytical software and modeling tools are distributed within different fields of neuroscience. However, in addition large-scale international collaborations are required which involve new mechanisms of coordination and funding. Provided sufficient government support is given to such international initiatives, sharing of neuroscience data and tools can play a pivotal role in human brain research and lead to innovations in neuroscience, informatics and treatment of brain disorders. These innovations will enable application of theoretical modeling techniques to enhance our understanding of the integrative aspects of neuroscience. This article, authored by a multinational working group on neuroinformatics established by the Organization for Economic Co-operation and Development (OECD), articulates some of the challenges and lessons learned to date in efforts to achieve international collaborative neuroscience.

Using standardized fMRI protocols to identify patterns of prefrontal circuit dysregulation that are common and specific to cognitive and emotional tasks in major depressive disorder: first wave results from the iSPOT-D study.

Functional neuroimaging studies have implicated dysregulation of prefrontal circuits in major depressive disorder (MDD), and these circuits are a viable target for predicting treatment outcomes. However, because of the heterogeneity of tasks and samples used in studies to date, it is unclear whether the central dysfunction is one of prefrontal hyperreactivity or hyporeactivity. We used a standardized battery of tasks and protocols for functional magnetic resonance imaging, to identify the common vs the specific prefrontal circuits engaged by these tasks in the same 30 outpatients with MDD compared with 30 matched, healthy control participants, recruited as part of the International Study to Predict Optimized Treatment in Depression (iSPOT-D). Reflecting cognitive neuroscience theory and established evidence, the battery included cognitive tasks designed to assess functions of selective attention, sustained attention-working memory and response inhibition, and emotion tasks to assess explicit conscious and implicit nonconscious viewing of facial emotion. MDD participants were distinguished by a distinctive biosignature of: hypoactivation of the dorsolateral prefrontal cortex during working memory updating and during conscious negative emotion processing; hyperactivation of the dorsomedial prefrontal cortex during working memory and response inhibition cognitive tasks and hypoactivation of the dorsomedial prefrontal during conscious processing of positive emotion. These results show that the use of standardized tasks in the same participants provides a way to tease out prefrontal circuitry dysfunction related to cognitive and emotional functions, and not to methodological or sample variations. These findings provide the frame of reference for identifying prefrontal biomarker predictors of treatment outcomes in MDD.

Widespread reductions in gray matter volume in depression.

Abnormalities in functional limbic-anterior cingulate-prefrontal circuits associated with emotional reactivity, evaluation and regulation have been implicated in the pathophysiology of major depressive disorder (MDD). However, existing knowledge about structural alterations in depression is equivocal and based on cohorts of limited sample size. This study used voxel-based morphometry (VBM) and surface-based cortical thickness to investigate the structure of these circuits in a large and well-characterized patient cohort with MDD. Non-geriatric MDD outpatients (n = 102) and age- and gender-matched healthy control participants (n = 34) provided T1-weighted magnetic resonance imaging data during their baseline visit as part of the International Study to Predict Optimized Treatment for Depression. Whole-brain VBM volumetric and surface-based cortical thickness assessments were performed voxel-wise and compared (at p < 0.05 corrected for multiple comparisons) between the MDD and control groups. MDD participants had reduced gray matter volume in the anterior cingulate cortex, regions of the prefrontal circuits, including dorsolateral and dorsomedial prefrontal cortices, and lateral and medial orbitofrontal cortices, but not in limbic regions. Additional reductions were observed cortically in the posterior temporal and parieto-occipital cortices and, subcortically in the basal ganglia and cerebellum. Focal cortical thinning in the medial orbitofrontal cortex was also observed for the MDD group. These alterations in volume and cortical thickness were not associated with severity of depressive symptoms. The findings demonstrate that widespread gray matter structural abnormalities are present in a well-powered study of patients with depression. The patterns of gray matter loss correspond to the same brain functional network regions that were previously established to be abnormal in MDD, which may support an underlying structural abnormality for these circuits.

Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial.

BACKGROUND: Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. METHODS/DESIGN: The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n=102), test the findings in the second half, and then extend the analyses to the total sample. TRIAL REGISTRATION: International Study to Predict Optimized Treatment--in Depression (iSPOT-D). ClinicalTrials.gov, NCT00693849.

Sensitivity, specificity, and predictive power of the "Brief Risk-resilience Index for SCreening," a brief pan-diagnostic web screen for emotional health.

Few standardized tools are available for time-efficient screening of emotional health status across diagnostic categories, especially in primary care. We evaluated the 45-question Brief Risk-resilience Index for SCreening (BRISC) and the 15-question mini-BRISC in identifying poor emotional health and coping capacity across a range of diagnostic groups - compared with a detailed clinical assessment - in a large sample of adult outpatients. Participants 18-60 years of age (n = 1079) recruited from 12 medical research and clinical sites completed the computerized assessments. Three index scores were derived from the full BRISC and the mini-BRISC: one for risk (negativity-positivity bias) and two for coping (resilience and social capacity). Summed answers were converted to standardized z-scores. BRISC scores were compared with detailed health assessment and diagnostic interview (for current psychiatric, psychological, and neurological conditions) by clinicians at each site according to diagnostic criteria. Clinicians were blinded to BRISC scores. Clinical assessment stratified participants as having "clinical" (n = 435) or "healthy" (n = 644) diagnostic status. Receiver operating characteristic analyses showed that a z-score threshold of -1.57 on the full BRISC index of emotional health provided an optimal classification of "clinical" versus "healthy" status (sensitivity: 81.2%, specificity: 92.7%, positive predictive power: 80.2%, and negative predictive power: 93.1%). Comparable findings were revealed for the mini-BRISC. Negativity-positivity bias index scores contributed the most to prediction. The negativity-positivity index of emotional health was most sensitive to classifying major depressive disorder (100%), posttraumatic stress disorder (95.8%), and panic disorder (88.7%). The BRISC and mini-BRISC both offer a brief, clinically useful screen to identify individuals at risk of disorders characterized by poor emotion regulation, from those with good emotional health and coping.

International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol.

BACKGROUND: Clinically useful treatment moderators of Major Depressive Disorder (MDD) have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators. METHODS/DESIGN: The International Study to Predict Optimized Treatment - in Depression (iSPOT-D) is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65) from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls). Study-eligible patients are antidepressant medication (ADM) naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary) and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary). Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm. DISCUSSION: First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide. TRIAL REGISTRATION: International Study to Predict Optimised Treatment - in Depression (iSPOT-D) ClinicalTrials.gov Identifier: NCT00693849. URL: http://clinicaltrials.gov/ct2/show/NCT00693849?term=International+Study+to+Predict+Optimized+Treatment+for+Depression&rank=1

Discovery and integrative neuroscience.

Hypothesis driven research has been shown to be an excellent model for pursuing investigations in neuroscience. The Human Genome Project demonstrated the added value of discovery research, especially in areas where large amounts of data are produced. Neuroscience has become a data rich field, and one that would be enhanced by incorporating the discovery approach. Databases, as well as analytical, modeling and simulation tools, will have to be developed, and they will need to be interoperable and federated. This paper presents an overview of the development of the field of neuroscience databases and associate tools: Neuroinformatics. The primary focus is on the impact of NIH funding of this process. The important issues of data sharing, as viewed from the perspective of the scientist and private and public funding organizations, are discussed. Neuroinformatics will provide more than just a sophisticated array of information technologies to help scientists understand and integrate nervous system data. It will make available powerful models of neural functions and facilitate discovery, hypothesis formulation and electronic collaboration.