Signal Fluctuation Sensitivity: An Improved Metric for Optimizing Detection of Resting-State fMRI Networks

Task-free connectivity analyses have emerged as a powerful tool in functional neuroimaging. Because the cross-correlations that underlie connectivity measures are sensitive to distortion of time-series, here we used a novel dynamic phantom to provide a ground truth for dynamic fidelity between blood oxygen level dependent (BOLD)-like inputs and fMRI outputs. We found that the de facto quality-metric for task-free fMRI, temporal signal to noise ratio (tSNR), correlated inversely with dynamic fidelity; thus, studies optimized for tSNR actually produced time-series that showed the greatest distortion of signal dynamics. Instead, the phantom showed that dynamic fidelity is reasonably approximated by a measure that, unlike tSNR, dissociates signal dynamics from scanner artifact. We then tested this measure, signal fluctuation sensitivity (SFS), against human resting-state data. As predicted by the phantom, SFS—and not tSNR—is associated with enhanced sensitivity to both local and long-range connectivity within the brain's default mode network

Mega-analysis methods in ENIGMA: the experience of the generalized anxiety disorder working group

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA‐Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega‐analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between‐country transfer of subject‐level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega‐analyses

Autonomic Modulation and Health-Related Quality of Life among Schizophrenic Patients Treated with Non-Intensive Case Management

Schizophrenia is associated with autonomic dysfunction and this may increase cardiovascular mortality. Past studies on autonomic modulation of schizophrenic patients focused on inpatients rather than individuals in a community setting, especially those receiving non-intensive case management (non-ICM). Besides, autonomic modulation and its association with health-related quality of life (HRQoL) in this population remain unexplored.A total of 25 schizophrenic patients treated by non-ICM and 40 healthy volunteers were matched by age, gender and body mass index; smokers were excluded. Between the two groups, we compared the individuals' 5 min resting assessments of heart rate variability and their HRQoL, which was measured using EuroQoL-5D (EQ-5D). Patients with schizophrenia were assessed for psychopathology using the Positive and Negative Syndrome Scale for Schizophrenia (PANSS). We examined the relationship between heart rate variability measurements, HRQoL scores, PANSS scores, and other clinical variables among the schizophrenic patients treated by non-ICM.Compared to the controls, patients with schizophrenia showed a significant impairment of autonomic modulation and a worse HRQoL. Cardiovagal dysfunction among the schizophrenic patients could be predicted independently based on lower educational level and more negative symptoms. Sympathetic predominance was directly associated with anticholinergics use and EQ-5D using a visual analogue scale (EQ-VAS).Patients with schizophrenia treated by non-ICM show a significant impairment of their autonomic function and HRQoL compared to the controls. Since the sympathovagal dysfunction is associated with more negative symptoms or higher VAS score, the treatment of the negative symptoms as well as the monitoring of HRQoL might help to manage cardiovascular risk among these individuals. In addition, EQ-VAS scores must be interpreted more cautiously in such a population

Processing of Body Odor Signals by the Human Brain

Brain development in mammals has been proposed to be promoted by successful adaptations to the social complexity as well as to the social and non-social chemical environment. Therefore, the communication via chemosensory signals might have been and might still be a phylogenetically ancient communication channel transmitting evolutionary significant information. In humans, the neuronal underpinnings of the processing of social chemosignals have been investigated in relation to kin recognition, mate choice, the reproductive state and emotional contagion. These studies reveal that human chemosignals are probably not processed within olfactory brain areas but through neuronal relays responsible for the processing of social information. It is concluded that the processing of human social chemosignals resembles the processing of social signals originating from other modalities, except that human social chemosignals are usually communicated without the allocation of attentional resources, that is below the threshold of consciousness. Deviances in the processing of human social chemosignals might be related to the development and maintenance of mental disorders

ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the enigma-anxiety working group

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology