Brainstem volume mediates seasonal variation in depressive symptoms : A cross sectional study in the UK Biobank cohort

This research has been conducted using the UK Biobank resource. UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. This work was supported by the Aberdeen Biomedical Imaging Centre with financial support from the Roland Sutton Academic Trust (RSAT-0039/R/16) and the Saudi Cultural Bureau in contact with Jazan University (PhD scholarship for NAM). Data Availability: The datasets processed and analysed during the current study are available from the online open access UK Biobank repository (https://www.ukbiobank.ac.uk/). This research was conducted under the UK Biobank Resource under Application Number 24089 (PI Waiter).Peer reviewedPublisher PD

Amygdala and subregion volume are associated with photoperiod and seasonal depressive symptoms : A cross sectional study in the UK Biobank cohort

ACKNOWLEDGEMENTS This research has been conducted using the UK Biobank Resource. This work was supported by the Aberdeen Biomedical Imaging Centre with financial support from the Roland Sutton Academic Trust (RSAT-0039/R/16) and Jazan University and Ministry of Health in Saudi Arabia.Peer reviewedPublisher PD

Inter-individual Differences in fMRI Entropy Measurements in Old Age

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkWe investigated the association between individual differences in cognitive performance in old age and the approximate entropy (ApEn) measured from functional magnetic resonance imaging (fMRI) data acquired from 40 participants of the Aberdeen Birth Cohort 1936 (ABC1936), while undergoing a visual information processing task: inspection time (IT). Participants took a version of the Moray House Test (MHT) No. 12 at age 11, a valid measure of childhood intelligence. The same individuals completed a test of non-verbal reasoning (Raven’s Standard Progressive Matrices [RPM]) aged about 68 years. The IT, MHT and RPM scores were used as indicators of cognitive performance. Our results show that higher regional signal entropy is associated with better cognitive performance. This finding was independent of ability in childhood but not independent of current cognitive ability. ApEn is used for the first time to identify a potential source of individual differences in cognitive ability using fMRI data

Structural brain correlates of serum and epigenetic markers of inflammation in major depressive disorder

Funding Information: Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Edinburgh Clinical Research Facility, University of Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award “STratifying Resilience and Depression Longitudinally” (STRADL) Reference 104036/Z/14/Z). CG is supported by The Medical Research Council and The University of Edinburgh through the Precision Medicine Doctoral Training program. SRC is supported by the UK Medical Research Council [MR/R024065/1] and a National Institutes of Health (NIH) research grant R01AG054628. Acknowledgements The authors thank all of the STRADL and Generation Scotland participants for their time and effort taking part in this study. We would also like to thank all of the research assistants, clinicians and technicians for their help in the collecting this data.Peer reviewedPublisher PD

Nonlinear complexity analysis of brain fMRI signals in schizophrenia

Peer reviewedPublisher PD

Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study:A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessments

Grant information: STRADL is supported by the Wellcome Trust through a Strategic Award (104036/Z/14/Z). GS:SFHS received core support from the CSO of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). ADM is supported by Innovate UK, the European Commission, the Scottish Funding Council via the Scottish Imaging Network SINAPSE, and the CSO. HCW is supported by a JMAS SIM Fellowship from the Royal College of Physicians of Edinburgh, by an ESAT College Fellowship from the University of Edinburgh, and has received previous funding from the Sackler Trust. LR has previously received financial support from Pfizer (formerly Wyeth) in relation to imaging studies of people with schizophrenia and bipolar disorder. JDH is supported by the MRC. DJM is an NRS Clinician, funded by the CSO. RMR is supported by the British Heart Foundation. ISP-V and MRM are supported by the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health; and MRM is also supported by the MRC MC_UU_12013/6). JMW is supported by MRC UK Dementia Research Institute and MRC Centre and project grants, EPSRC, Fondation Leducq, Stroke Association, British Heart Foundation, Alzheimer Society, and the European Union H2020 PHC-03-15 SVDs@Target grant agreement (666881). DJP is supported by Wellcome Trust Longitudinal Population Study funding (216767/Z/19/Z) the Eva Lester bequest to the University of Edinburgh. AMM is additionally supported by the MRC (MC_PC_17209, MC_PC_MR/R01910X/1, MR/S035818/1), The Wellcome Trust (216767/Z/19/Z ), The Sackler Trust, and has previously received research funding from Pfizer, Eli Lilly, and Janssen. Both AMM and IJD are members of The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1); funding from the BBSRC and MRC is gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptPeer reviewedPublisher PD

Developmental malformation of the corpus callosum: a review of typical callosal development and examples of developmental disorders with callosal involvement

This review provides an overview of the involvement of the corpus callosum (CC) in a variety of developmental disorders that are currently defined exclusively by genetics, developmental insult, and/or behavior. I begin with a general review of CC development, connectivity, and function, followed by discussion of the research methods typically utilized to study the callosum. The bulk of the review concentrates on specific developmental disorders, beginning with agenesis of the corpus callosum (AgCC)—the only condition diagnosed exclusively by callosal anatomy. This is followed by a review of several genetic disorders that commonly result in social impairments and/or psychopathology similar to AgCC (neurofibromatosis-1, Turner syndrome, 22q11.2 deletion syndrome, Williams yndrome, and fragile X) and two forms of prenatal injury (premature birth, fetal alcohol syndrome) known to impact callosal development. Finally, I examine callosal involvement in several common developmental disorders defined exclusively by behavioral patterns (developmental language delay, dyslexia, attention-deficit hyperactive disorder, autism spectrum disorders, and Tourette syndrome)

General intelligence is associated with working memory-related brain activity: new evidence from a large sample study

Psychometric intelligence is closely related to working memory capacity. Here we aim to determine the associations of neural activation patterns during the N-back working memory paradigm with psychometric intelligence and working memory performance. We solved the statistical problems of previous studies using (1) a large cohort of 1235 young adults and (2) robust voxel-by-voxel permutation-based statistics at the whole-brain level. Many of the significant correlations were we ak, and our findings were not consistent with those of previous studies. We observed that many of the significant correlations involved brain areas in the periphery or boundaries between the task-positive network (TPN) and task-negative network (TNN), suggesting that the expansion of the TPN or TNN is associated with greater cognitive ability. Lower activity in TPN and less task-induced deactivation (TID) in TNN were associated with greater cognitive ability. These findings indicate that subjects with greater cognitive ability have a lower brain response to task demand, consistent with the notion that TID in TNN reflects cognitive demand but partly inconsistent with the prevailing neural efficiency theory. One exception was the pre-supplementary motor area, which plays a key role in cognitive control and sequential processing. In this area, intelligent subjects demonstrated greater activity related to working memory, suggesting that the pre-supplementary motor area plays a unique role in the execution of working memory tasks in intelligent subjects