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      The Role of Prefrontal Cortical Surface Area and Volume in Preclinical Suicidal Ideation in a Non-Clinical Sample

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          Abstract

          Suicidal ideation (SUI) can occur in the absence of concomitant psychiatric diagnoses, and even normal levels can be problematic among individuals experiencing excess stress or lack of social support. The objective of this study was to investigate the neuroanatomical basis of SUI in non-clinical human populations who are within the normal limits of SUI, after accounting for elevated stress and perceived lack of social support. Neuroanatomical data were collected from 55 healthy individuals (mean age 30.9 ± 8.1 years, 27 females) whose depression severity levels were below the Diagnostic and Statistical Manual of Mental Disorders criteria. Measures of SUI, aggression, stress, non-support, and treatment rejection were collected from the treatment-consideration scales (TCS) of the Personality Assessment Inventory (PAI). Correlations between standardized SUI scores and three brain morphometry measures, including vertex wise cortical thickness (CT), cortical surface area (CSA), and cortical volume (CV), were estimated for each participant, controlling for age, sex, intracranial volume, and the remaining TCS measures. We observed a significant negative association between scores on SUI and both CSA and CV (cluster-forming threshold of p < 0.005, clusterwise threshold of p < 0.05, FDR corrected for multiple comparisons) within the left rostral middle frontal gyrus. Our findings suggest that greater CSA and CV within the dorsolateral prefrontal cortex are associated with reduced SUI in a non-clinical population with mild levels of stress and perceived lack of social support. Because the dorsolateral prefrontal cortex has been broadly linked to cognitive reappraisal, self-critical thoughts, and emotional regulation, greater CSA and CV within these regions may lead to better mental health by protecting healthy individuals from engaging in SUI during periods of stress and perceived insufficient social support. As our data consisted of only healthy individuals with non-clinical levels of SUI, further investigation will be necessary to explore the neural basis of SUI in populations who may be at greater risk of future suicidal behavior

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          Most cited references36

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          Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies.

          Choosing the appropriate neuroimaging phenotype is critical to successfully identify genes that influence brain structure or function. While neuroimaging methods provide numerous potential phenotypes, their role for imaging genetics studies is unclear. Here we examine the relationship between brain volume, grey matter volume, cortical thickness and surface area, from a genetic standpoint. Four hundred and eighty-six individuals from randomly ascertained extended pedigrees with high-quality T1-weighted neuroanatomic MRI images participated in the study. Surface-based and voxel-based representations of brain structure were derived, using automated methods, and these measurements were analysed using a variance-components method to identify the heritability of these traits and their genetic correlations. All neuroanatomic traits were significantly influenced by genetic factors. Cortical thickness and surface area measurements were found to be genetically and phenotypically independent. While both thickness and area influenced volume measurements of cortical grey matter, volume was more closely related to surface area than cortical thickness. This trend was observed for both the volume-based and surface-based techniques. The results suggest that surface area and cortical thickness measurements should be considered separately and preferred over gray matter volumes for imaging genetic studies. Copyright 2009 Elsevier Inc. All rights reserved.
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            Brain size and cortical structure in the adult human brain.

            We investigated the scale relationship between size and cortical structure of human brains in a large sample of magnetic resonance imaging data. Cortical structure was estimated with several measures (cortical volume, surface area, and thickness, sulcal depth, and absolute mean curvature in sulcal regions and sulcal walls) using three-dimensional surface-based methods in 148 normal subjects (n [men/women]: 83/65, age [mean +/- standard deviation]: 25.0 +/- 4.9 years). We found significantly larger scaling exponents than geometrically predicted for cortical surface area, absolute mean curvature in sulcal regions and in sulcal walls, and smaller ones for cortical volume and thickness. As brain size increases, the cortex thickens only slightly, but the degree of sulcal convolution increases dramatically, indicating that human cortices are not simply scaled versions of one another. Our results are consistent with previous hypotheses that greater local clustering of interneuronal connections would be required in a larger brain, and fiber tension between local cortical areas would induce cortical folds. We suggest that sex effects are explained by brain size effects in cortical structure at a macroscopic and lobar regional level, and that it is necessary to consider true relationships between cortical measures and brain size due to the limitations of linear stereotaxic normalization.
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              False positive rates in surface-based anatomical analysis

              The false positive rates (FPR) for surface-based group analysis of cortical thickness, surface area, and volume were evaluated for parametric and non-parametric clusterwise correction for multiple comparisons for a range of smoothing levels and cluster-forming thresholds (CFT) using real data under group assignments that should not yield significant results. For whole cortical surface analysis, thickness showed modest inflation in parametric FPRs above the nominal level (10% versus 5%). Surface area and volume FPRs were much higher (20-30%). In the analysis of interhemispheric thickness asymmetries, FPRs were well controlled by parametric correction, but FPRs for surface area and volume asymmetries were still inflated. In all cases, non-parametric permutation adequately controlled the FPRs. It was found that inflated parametric FPRs were caused by violations in the parametric assumptions, namely a heavier-than-Gaussian spatial correlation. The non-Gaussian spatial correlation originates from anatomical features unique to individuals (e.g., a patch of cortex slightly thicker or thinner than average) and is not a by-product of scanning or processing. Thickness performed better than surface area and volume because thickness does not require a Jacobian correction.
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                21 June 2019
                2019
                : 10
                : 445
                Affiliations
                [1] 1Social, Cognitive and Affective Neuroscience Laboratory (SCAN Lab), Department of Psychiatry, College of Medicine, University of Arizona , Tucson, AZ, United States
                [2] 2The Laureate Institute for Brain Research (LIBR) , Tulsa, OK, United States
                Author notes

                Edited by: Marco Sarchiapone, University of Molise, Italy

                Reviewed by: Nefize Yalin, King’s College London, United Kingdom; Laura Orsolini, University of Hertfordshire, United Kingdom

                *Correspondence: Sahil Bajaj, sahil.neurores@ 123456gmail.com

                This article was submitted to Mood and Anxiety Disorders, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2019.00445
                6613495
                31312146
                0029e606-1fe9-4914-ad5e-e722dba69560
                Copyright © 2019 Bajaj, Raikes, Smith, Vanuk and Killgore

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 13 January 2019
                : 05 June 2019
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 50, Pages: 9, Words: 5037
                Funding
                Funded by: Medical Research and Materiel Command 10.13039/100000182
                Categories
                Psychiatry
                Original Research

                Clinical Psychology & Psychiatry
                cortical structure,stress,social support,neuroanatomy,personality assessment

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