160 research outputs found
A Symmetry-Based Method to Infer Structural Brain Networks from Probabilistic Tractography Data
Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP) have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that interconnects a given set of Regions of Interest (ROIs) from probabilistic tractography data. The proposed method, referred to as Minimum Asymmetry Network Inference Algorithm (MANIA), does not determine the connectivity between two ROIs based on an arbitrary connectivity threshold. Instead, we exploit a basic limitation of the tractography process: the observed streamlines from a source to a target do not provide any information about the polarity of the underlying white matter, and so if there are some fibers connecting two voxels (or two ROIs) X and Y, tractography should be able in principle to follow this connection in both directions, from X to Y and from Y to X. We leverage this limitation to formulate the network inference process as an optimization problem that minimizes the (appropriately normalized) asymmetry of the observed network. We evaluate the proposed method using both the FiberCup dataset and based on a noise model that randomly corrupts the observed connectivity of synthetic networks. As a case-study, we apply MANIA on diffusion MRI data from 28 healthy subjects to infer the structural network between 18 corticolimbic ROIs that are associated with various neuropsychiatric conditions including depression, anxiety and addiction
Towards a multilevel model of major depression: genes, immuno-metabolic function, and cortico-striatal signaling
Biological assay and imaging techniques have made visible a great deal of the machinery of mental illness. Over fifty years of investigation of mood disorders using these technologies has identified several biological regularities in these disorders. Here we present a narrative connecting genetic, cytokine, neurotransmitter, and neural-systems-level findings in major depressive disorder (MDD). Specifically, we connect recent genome-wide findings in MDD to metabolic and immunological disturbance in this disorder and then detail links between immunological abnormalities and dopaminergic signaling within cortico-striatal circuitry. Following this, we discuss implications of reduced dopaminergic tone for cortico-striatal signal conduction in MDD. Finally, we specify some of the flaws in the current model and propose ways forward for advancing multilevel formulations of MDD most efficiently.publishedVersio
Effects of Subcallosal Cingulate Deep Brain Stimulation on Negative Self-bias in Patients With Treatment-resistant Depression
Background: The cognitive neuropsychological model states that antidepressant treatment alters emotional biases early in treatment, and after this initial change in emotional processing, environmental and social interactions allow for long-term/sustained changes in mood and behavior. Objective: Changes in negative self-bias after chronic subcallosal cingulate (SCC) deep brain stimulation (DBS) were investigated with the hypothesis that treatment would lead to changes in emotional biases followed by changes in symptom severity. Methods: Patients (N = 7) with treatment-resistant depression were assessed at three time points: pretreatment; after one month stimulation; and after six months stimulation. The P1, P2, P3, and LPP (late positive potential) components of the event-related potential elicited by positive and negative trait adjectives were recorded in both a self-referential task and a general emotion recognition task. Results: Results indicate that DBS reduced automatic attentional bias toward negative words early in treatment, as indexed by the P1 component, and controlled processing of negative words later in treatment, as indexed by the P3 component. Reduction in negative words endorsed as self-descriptive after six months DBS was associated with reduced depression severity after six months DBS. Change in emotional processing may be restricted to the self-referential task. Conclusions: Together, these results suggest that the cognitive neuropsychological model, developed to explain the time-course of monoamine antidepressant treatment, may also be used as a framework to interpret the antidepressant effects of SCC DBS. (C) 2015 Elsevier Inc. All rights reserved
Asymmetrical Contribution of Brain Structures to Treatment-Resistant Depression As Illustrated by Effects of Right Subgenual Cingulum Stimulation
Major depressive disorder is one of the most common psychiatric disorders, with a worldwide lifetime prevalence rate of 10%-20% in women and a slightly lower rate in men. While many patients are successfully treated using established therapeutic strategies, a significant percentage of patients fail to respond. This report describes the successful recovery of a previously treatment-resistant patient following right unilateral deep brain stimulation of Brodmann´s area 25. Current therapeutic approaches to treatment-resistant patients are reviewed in the context of this case with an emphasis on the role of the right and left hemispheres in mediating disease pathogenesis and clinical recovery.Fil: Guinjoan, Salvador Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Mayberg, Helen S.. University Of Emory; Estados UnidosFil: Costanzo, Elsa Y.. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Fahrer, Rodolfo D.. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Tenca, Eduardo. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Antico, Julio. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Cerquetti, Daniel. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Smyth, Elisa. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Leiguarda, Ramón Carlos. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Nemeroff, Charles B.. University of Miami; Estados Unido
Treatment-Specific Hippocampal Subfield Volume Changes With Antidepressant Medication or Cognitive-Behavior Therapy in Treatment-Naive Depression.
Background: Hippocampal atrophy has been consistently reported in major depressive disorder with more recent focus on subfields. However, literature on hippocampal volume changes after antidepressant treatment has been limited. The first-line treatments for depression include antidepressant medication (ADM) or cognitive-behavior therapy (CBT). To understand the differential effects of CBT and ADM on the hippocampus, we investigated the volume alterations of hippocampal subfields with treatment, outcome, and chronicity in treatment-naïve depression patients. Methods: Treatment-naïve depressed patients from the PReDICT study were included in this analysis. A total of 172 patients who completed 12 weeks of randomized treatment with CBT (n = 45) or ADM (n = 127) were included for hippocampal subfield volume analysis. Forty healthy controls were also included for the baseline comparison. Freesurfer 6.0 was used to segment 26 hippocampal substructures and bilateral whole hippocampus from baseline and week 12 structural MRI scans. A generalized linear model with covariates of age and gender was used for group statistical tests. A linear mixed model for the repeated measures with covariates of age and gender was used to examine volumetric changes over time and the contributing effects of treatment type, outcome, and illness chronicity. Results: Of the 172 patients, 85 achieved remission (63/127 ADM, 22/45 CBT). MDD patients showed smaller baseline volumes than healthy controls in CA1, CA3, CA4, parasubiculum, GC-ML-DG, Hippocampal Amygdala Transition Area (HATA), and fimbria. Over 12 weeks of treatment, further declines in the volumes of CA1, fimbria, subiculum, and HATA were observed regardless of treatment type or outcome. CBT remitters, but not ADM remitters, showed volume reduction in the right hippocampal tail. Unlike ADM remitters, ADM non-responders had a decline in volume in the bilateral hippocampal tails. Baseline volume of left presubiculum (regardless of treatment type) and right fimbria and HATA in CBT patients were correlated with a continuous measure of clinical improvement. Chronicity of depression had no effect on any measures of hippocampal subfield volumes. Conclusion: Two first-line antidepressant treatments, CBT and ADM, have different effects on hippocampal tail after 12 weeks. This finding suggests that remission achieved via ADM may protect against progressive hippocampal atrophy by altering neuronal plasticity or supporting neurogenesis. Studies with multimodal neuroimaging, including functional and structural analysis, are needed to assess further the impact of two different antidepressant treatments on hippocampal subfields
Indoxyl sulfate, a gut microbiome-derived uremic toxin, is associated with psychic anxiety and its functional magnetic resonance imaging-based neurologic signature
Background: It is unknown whether indoles, metabolites of tryptophan that are derived entirely from bacterial metabolism in the gut, are associated with symptoms of depression and anxiety. Methods: Serum samples (baseline, 12 weeks) were drawn from participants (n=196) randomized to treatment with cognitive behavioral therapy (CBT), escitalopram, or duloxetine for major depressive disorder. Results: Baseline indoxyl sulfate abundance was positively correlated with severity of psychic anxiety and total anxiety and with resting state functional connectivity to a network that processes aversive stimuli (which includes the subcallosal cingulate cortex (SCC-FC), bilateral anterior insula, right anterior midcingulate cortex, and the right premotor areas). The relation between indoxyl sulfate and psychic anxiety was mediated only through the metabolite's effect on the SCC-FC with the premotor area. Baseline indole abundances were unrelated to post-treatment outcome measures, which suggests that CBT and antidepressant medications relieve anxiety via mechanisms unrelated to gut microbiota. Conclusions: A peripheral gut microbiome-derived metabolite was associated with altered neural processing and with psychiatric symptom (anxiety) in humans, which provides further evidence that gut microbiome disruption can contribute to neuropsychiatric disorders that may require different therapeutic approaches
Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder
Background: Electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder. Recently, there has been increasing attention to evaluate the effect of ECT on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of depressive disorder (DEP) patients with healthy participants, investigate whether pre-ECT dynamic functional network connectivity network (dFNC) estimated from patients rs-fMRI is associated with an eventual ECT outcome, and explore the effect of ECT on brain network states. Method: Resting-state functional magnetic resonance imaging (fMRI) data were collected from 119 patients with depression or depressive disorder (DEP) (76 females), and 61 healthy (HC) participants (34 females), with an age mean of 52.25 (N = 180) years old. The pre-ECT and post-ECT Hamilton Depression Rating Scale (HDRS) were 25.59 ± 6.14 and 11.48 ± 9.07, respectively. Twenty-four independent components from default mode (DMN) and cognitive control network (CCN) were extracted, using group-independent component analysis from pre-ECT and post-ECT rs-fMRI. Then, the sliding window approach was used to estimate the pre-and post-ECT dFNC of each subject. Next, k-means clustering was separately applied to pre-ECT dFNC and post-ECT dFNC to assess three distinct states from each participant. We calculated the amount of time each subject spends in each state, which is called “occupancy rate” or OCR. Next, we compared OCR values between HC and DEP participants. We also calculated the partial correlation between pre-ECT OCRs and HDRS change while controlling for age, gender, and site. Finally, we evaluated the effectiveness of ECT by comparing pre- and post-ECT OCR of DEP and HC participants. Results: The main findings include (1) depressive disorder (DEP) patients had significantly lower OCR values than the HC group in state 2, where connectivity between cognitive control network (CCN) and default mode network (DMN) was relatively higher than other states (corrected p = 0.015), (2) Pre-ECT OCR of state, with more negative connectivity between CCN and DMN components, is linked with the HDRS changes (R = 0.23 corrected p = 0.03). This means that those DEP patients who spent less time in this state showed more HDRS change, and (3) The post-ECT OCR analysis suggested that ECT increased the amount of time DEP patients spent in state 2 (corrected p = 0.03). Conclusion: Our finding suggests that dynamic functional network connectivity (dFNC) features, estimated from CCN and DMN, show promise as a predictive biomarker of the ECT outcome of DEP patients. Also, this study identifies a possible underlying mechanism associated with the ECT effect on DEP patients
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