Identifying Abnormal Connectivity in Patients Using Dynamic Causal Modeling of fMRI Responses

Functional imaging studies of brain damaged patients offer a unique opportunity to understand how sensorimotor and cognitive tasks can be carried out when parts of the neural system that support normal performance are no longer available. In addition to knowing which regions a patient activates, we also need to know how these regions interact with one another, and how these inter-regional interactions deviate from normal. Dynamic causal modeling (DCM) offers the opportunity to assess task-dependent interactions within a set of regions. Here we review its use in patients when the question of interest concerns the characterization of abnormal connectivity for a given pathology. We describe the currently available implementations of DCM for fMRI responses, varying from the deterministic bilinear models with one-state equation to the stochastic non-linear models with two-state equations. We also highlight the importance of the new Bayesian model selection and averaging tools that allow different plausible models to be compared at the single subject and group level. These procedures allow inferences to be made at different levels of model selection, from features (model families) to connectivity parameters. Following a critical review of previous DCM studies that investigated abnormal connectivity we propose a systematic procedure that will ensure more flexibility and efficiency when using DCM in patients. Finally, some practical and methodological issues crucial for interpreting or generalizing DCM findings in patients are discussed

Cosmic-ray-induced ionization in molecular clouds adjacent to supernova remnants - Tracing the hadronic origin of GeV gamma radiation

Energetic gamma rays (GeV to TeV photon energy) have been detected toward several supernova remnants (SNR) associated with molecular clouds. If the gamma rays are produced mainly by hadronic processes rather than leptonic processes like bremsstrahlung, then the flux of energetic cosmic ray (CR) nuclei (>1 GeV) required to produce the gamma rays can be inferred at the site where the particles are accelerated in SNR shocks. It is of great interest to understand the acceleration of the CR of lower energy (<1 GeV) accompanying the energetic component. These particles of lower energy are most effective in ionizing interstellar gas, leaving an observable imprint on the interstellar ion chemistry. A correlation of energetic gamma radiation with enhanced interstellar ionization can thus support the hadronic origin of the gamma rays and constrain the acceleration of ionizing CR in SNR. We propose a method to test the hadronic origin of GeV gamma rays from SNR associated with a molecular cloud. We use observational gamma ray data for each of these SNR known, modeling the observations to obtain the underlying proton spectrum assuming that the gamma rays are produced by pion decay. Assuming that the acceleration mechanism does not only produce high energy protons, but also low energy protons, this proton spectrum at the source is then used to calculate the ionization rate of the molecular cloud. Ionized molecular hydrogen triggers a chemical network forming molecular ions. The relaxation of these ions results in characteristic line emission, which can be predicted. We show that the ionization rate for at least two objects is more than an order of magnitude above Galactic average for molecular clouds, hinting at an enhanced formation rate of molecular ions. There will be interesting opportunities to measure crucial molecular ions in the infrared and submillimeter-wave parts of the spectrum.Comment: published in Astronomy and Astrophysics, 13 pages, 19 figure

Resting state functional connectivity in patients with remitted psychotic depression: A multi-centre STOP-PD study

BACKGROUND: There is paucity of neurobiological knowledge about major depressive disorder with psychotic features ( psychotic depression ). This study addresses this knowledge gap by using resting state functional magnetic resonance imaging (R-fMRI) to compare functional connectivity in patients with psychotic depression and healthy controls. METHODS: We scanned patients who participated in a randomized controlled trial as well as healthy controls. All patients achieved remission from depressive and psychotic symptoms with sertraline and olanzapine. We employed Independent Component Analysis in independent samples to isolate the default mode network (DMN) and compared patients and controls. FINDINGS: The Toronto sample included 28 patients (mean [SD], age 56.2 [13.7]) and 39 controls (age 55.1 [13.5]). The Replication sample included 29 patients (age 56.1 [17.7]) and 36 controls (age 48.3 [17.9]). Patients in the Toronto sample demonstrated decreased between-network functional connectivity between the DMN and bilateral insular, somatosensory/motor, and auditory cortices with peak activity in the right planum polare (t=4.831; p=0.001, Family Wise Error (FWE) corrected). A similar pattern of between-network functional connectivity was present in our Replication sample with peak activity in the right precentral gyrus (t=4.144; p=0.003, FWE corrected). INTERPRETATION: Remission from psychotic depression is consistently associated with an absence of increased DMN-related functional connectivity and presence of decreased between-network functional connectivity. Future research will evaluate this abnormal DMN-related functional connectivity as a potential biomarker for treatment trajectories. FUNDING: National Institute of Mental Health

A communal catalogue reveals Earth's multiscale microbial diversity

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

Structural brain networks in remitted psychotic depression

Major depressive disorder with psychotic features (psychotic depression) is a severe disorder. Compared with other psychotic disorders such as schizophrenia, relatively few studies on the neurobiology of psychotic depression have been pursued. Neuroimaging studies investigating psychotic depression have provided evidence for distributed structural brain abnormalities implicating the insular cortex and limbic system. We examined structural brain networks in participants (N = 245) using magnetic resonance imaging. This sample included healthy controls (n = 159) and the largest cross-sectional sample of patients with remitted psychotic depression (n = 86) collected to date. All patients participated in the Study of Pharmacotherapy of Psychotic Depression II randomized controlled trial. We used a novel, whole-brain, data-driven parcellation technique-non-negative matrix factorization-and applied it to cortical thickness data to derive structural covariance networks. We compared patients with remitted psychotic depression to healthy controls and found that patients had significantly thinner cortex in five structural covariance networks (insular-limbic, occipito-temporal, temporal, parahippocampal-limbic, and inferior fronto-temporal), confirming our hypothesis that affected brain networks would incorporate cortico-limbic regions. We also found that cross-sectional depression and severity scores at the time of scanning were associated with the insular-limbic network. Furthermore, the insular-limbic network predicted future severity scores that were collected at the time of recurrence of psychotic depression or sustained remission. Overall, decreased cortical thickness was found in five structural brain networks in patients with remitted psychotic depression and brain-behavior relationships were observed, particularly between the insular-limbic network and illness severity

Transcranial direct-current stimulation (tDCS) for bipolar depression: A systematic review and meta-analysis

OBJECTIVE: Bipolar disorder (BD) is a severe and recurrent brain disorder that can manifest in manic or depressive episodes. Transcranial Direct Current Stimulation (tDCS) has been proposed as a novel therapeutic modality for patients experiencing bipolar depression, for which standard treatments are often inefficient. While several studies have been conducted in this patient group, there has been no systematic review or meta-analysis that specifically examines bipolar depression. We aimed to address this gap in the literature and evaluated the efficacy and tolerability of tDCS in patients fulfilling DSM-IV-TR criteria for BD I, II, or BD not otherwise specified (NOS). METHODS: We systematically searched the literature from April 2002 to November 2016 to identify relevant publications for inclusion in our systematic review and meta-analysis. Effect sizes for depression rating-scale scores were expressed as the standardized mean difference (SMD) before and after tDCS. RESULTS: Thirteen of 382 identified studies met eligibility criteria for our systematic review. The meta-analysis included 46 patients from 7 studies with depression rating-scale scores pre- and post-tDCS. Parameters of tDCS procedures were heterogeneous. Depression scores decreased significantly with a medium effect size after acute-phase of treatment (SMD 0.71 [0.25-1.18], z=3.00, p=0.003) and at the furthest endpoint (SMD 1.27 [0.57-1.97], z=3.57, p=0.0004). Six cases of affective switching under tDCS treatment protocols were observed. CONCLUSIONS: Depressive symptoms respond to tDCS in patients with BD. Additional studies, and particularly randomized controlled trials, are needed to clarify the effectiveness of tDCS in bipolar depression, the frequency of tDCS-emergent hypomania/mania, and which tDCS modalities are most efficient

Effects of Antipsychotic Medication on Brain Structure in Patients With Major Depressive Disorder and Psychotic Features: Neuroimaging Findings in the Context of a Randomized Placebo-Controlled Clinical Trial

Importance: Prescriptions for antipsychotic medications continue to increase across many brain disorders, including off-label use in children and elderly individuals. Concerning animal and uncontrolled human data suggest antipsychotics are associated with change in brain structure, but to our knowledge, there are no controlled human studies that have yet addressed this question. Objective: To assess the effects of antipsychotics on brain structure in humans. Design, Setting, and Participants: Prespecified secondary analysis of a double-blind, randomized, placebo-controlled trial over a 36-week period at 5 academic centers. All participants, aged 18 to 85 years, were recruited from the multicenter Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II). All participants had major depressive disorder with psychotic features (psychotic depression) and were prescribed olanzapine and sertraline for a period of 12 to 20 weeks, which included 8 weeks of remission of psychosis and remission/near remission of depression. Participants were then were randomized to continue receiving this regimen or to be switched to placebo and sertraline for a subsequent 36-week period. Data were analyzed between October 2018 and February 2019. Interventions: Those who consented to the imaging study completed a magnetic resonance imaging (MRI) scan at the time of randomization and a second MRI scan at the end of the 36-week period or at time of relapse. Main Outcomes and Measures: The primary outcome measure was cortical thickness in gray matter and the secondary outcome measure was microstructural integrity of white matter. Results: Eighty-eight participants (age range, 18-85 years) completed a baseline scan; 75 completed a follow-up scan, of which 72 (32 men and 40 women) were useable for final analyses. There was a significant treatment-group by time interaction in cortical thickness (left, t = 3.3; P = .001; right, t = 3.6; P \u3c .001) but not surface area. No significant interaction was found for fractional anisotropy, but one for mean diffusivity of the white matter skeleton was present (t = -2.6, P = .01). When the analysis was restricted to those who sustained remission, exposure to olanzapine compared with placebo was associated with significant decreases in cortical thickness in the left hemisphere (beta [SE], 0.04 [0.009]; t34.4 = 4.7; P \u3c .001), and the right hemisphere (beta [SE], 0.03 [0.009]; t35.1 = 3.6; P \u3c .001). Post hoc analyses showed that those who relapsed receiving placebo experienced decreases in cortical thickness compared with those who sustained remission. Conclusions and Relevance: In this secondary analysis of a randomized clinical trial, antipsychotic medication was shown to change brain structure. This information is important for prescribing in psychiatric conditions where alternatives are present. However, adverse effects of relapse on brain structure support antipsychotic treatment during active illness. Trial Registration: ClinicalTrials.gov Identifier: NCT01427608