Suchergebnisse

AbstractExecutive Function (EF) and Effortful Control (EC) have traditionally been viewed as distinct constructs related to cognition and temperament during development. More recently, EF and EC have been implicated in top‐down self‐regulation ‐ the goal‐directed control of cognition, emotion, and behavior. We propose that executive attention, a limited‐capacity attentional resource subserving goal‐directed cognition and behavior, is the common cognitive mechanism underlying the self‐regulatory capacities captured by EF and EC. We addressed three related questions: (a) Do behavioral ratings of EF and EC represent the same self‐regulation construct? (b) Is this self‐regulation construct explained by a common executive attention factor as measured by performance on cognitive tasks? and (c) Does the executive attention factor explain additional variance in attention deficit hyperactivity disorder (ADHD) problems to behavioral ratings of self‐regulation? Measures of performance on complex span, general intelligence, and response inhibition tasks were obtained from 136 preadolescent children (M = 11 years, 10 months, SD = 8 months), along with self‐ and parent‐reported EC, and parent‐reported EF, and ADHD problems. Results from structural equation modeling demonstrated that behavioral ratings of EF and EC measured the same self‐regulation construct. Cognitive tasks measured a common executive attention factor that significantly explained 30% of the variance in behavioral ratings of self‐regulation. Executive attention failed to significantly explain additional variance in ADHD problems beyond that explained by behavioral ratings of self‐regulation. These findings raise questions about the utility of task‐based cognitive measures in research and clinical assessment of self‐regulation and psychopathology in developmental samples.

Background: Orbitofrontal cortex (OFC) dysfunction has been proposed to increase the risk for developing a substance use disorder (SUD) during adolescence. In this study, we suggest that a reduction in OFC volumes might underlie temperament-based risk factors for SUD, and examined whether smaller OFC volumes during early adolescence could predict later development of SUD. Methods and Materials: Adolescents (n = 107; 58 male, 49 female) underwent structural MRI and completed a self-report measure of temperamental effortful control at age 12. At 3 subsequent assessments (aged 15, 16, and 18) SUD was assessed via a semi-structured clinical interview. By the third assessment, 24 participants (22.4%) had received a lifetime diagnosis of SUD. Results: Smaller volumes of the left OFC, right OFC, and left medial subregions predicted lifetime history of SUD by age 18. Volumes of the left OFC and left lateral subregions were positively correlated with effortful control, and left OFC volumes mediated the relationship between effortful control and SUD. Conclusions: Smaller volumes of the OFC and low effortful control during adolescence appear to be associated phenotypes that increase the risk of subsequent SUD. Further studies examining the temporal sequence of these risk factors are needed to fully understand this relationship.

AbstractEarly to mid‐adolescence is an important developmental period for subcortical brain maturation, but longitudinal studies of these neurodevelopmental changes are lacking. The present study acquired repeated magnetic resonance images from 60 adolescent subjects (28 female) at ages 12.5 and 16.5 years to map changes in subcortical structure volumes. Automated segmentation techniques optimized for longitudinal measurement were used to delineate volumes of the caudate, putamen, nucleus accumbens, pallidum, hippocampus, thalamus and the whole brain. Amygdala volumes were described using manual tracing methods. The results revealed heterogeneous maturation across the regions of interest (ROIs), and change was differentially moderated by sex and hemisphere. The caudate, thalamus and putamen declined in volume, more for females relative to males, and decreases in the putamen and thalamus were greater in the left hemisphere. The pallidum increased in size, but more so in the left hemisphere. While the left nucleus accumbens increased in size, the right accumbens decreased in size over the follow‐up period. Increases in hippocampal volume were greater in the right hemisphere. While amygdala volume did not change over time, the left hemisphere was consistently larger than the right. These results suggest that subcortical brain development from early to middle adolescence is characterized by striking hemispheric specialization and sexual dimorphisms, and provide a framework for interpreting normal and abnormal changes in cognition, affect and behavior. Moreover, the differences in findings compared to previous cross‐sectional research emphasize the importance of within‐subject assessment of brain development during adolescence.

AbstractMeta‐emotion philosophy refers to an organized set of thoughts, reactions, and feelings about one's emotions and the emotions of others (Gottman, Katz, & Hooven, 1997). This study investigated the prospective relationship between family meta‐emotion processes and adolescent‐onset major depressive disorder (MDD). Adolescents (N = 198, mean age 12.5 years) and one of their parents each completed the Meta‐Emotion Interview (Katz & Gottman, 1986), and adolescents were followed‐up at ages 15, 16.5, and 19 years to assess for MDD onset. In the Meta‐Emotion Interviews, parents and adolescents were asked about both their own, and the others', anger and sadness. Results showed that parent‐report of their own meta‐emotion philosophy of sadness prospectively predicted MDD onset in adolescence, as did adolescent‐report of low parental emotion coaching in relation to sadness, and adolescent self‐perceived emotional competence in relation to sadness. Adolescents' perceptions of family emotional environments characterized by high levels of parental anger expression and family conflict also prospectively predicted MDD onset. These findings highlight the continued importance of family emotional processes in adolescence, and provide insight into how parents' and adolescents' perceptions of emotional processes within the family, particularly in relation to sadness, may be prospectively associated with risk for adolescent onset MDD.

Alberta has rich clinical and health services data held under the custodianship of Alberta Health and Alberta Health Services (AHS), which is not only used for clinical and administrative purposes but also disease surveillance and epidemiological research. Alberta is the largest province in Canada with a single payer centralised health system, AHS, and a consolidated data and analytics team supporting researchers across the province.
This paper describes Alberta's data custodians, data governance mechanisms, and streamlined processes followed for research data access. AHS has created a centralised data repository from multiple sources, including practitioner claims data, hospital discharge data, and medications dispensed, available for research use through the provincial Data and Research Services (DRS) team. The DRS team is integrated within AHS to support researchers across the province with their data extraction and linkage requests. Furthermore, streamlined processes have been established, including: 1) ethics approval from a research ethics board, 2) any necessary operational approvals from AHS, and 3) a tripartite legal agreement dictating terms and conditions for data use, disclosure, and retention. This allows researchers to gain timely access to data. To meet the evolving and ever-expanding big-data needs, the University of Calgary, in partnership with AHS, has built high-performance computing (HPC) infrastructure to facilitate storage and processing of large datasets. When releasing data to researchers, the analytics team ensures that Alberta's Health Information Act's guiding principles are followed. The principal investigator also ensures data retention and disposition are according to the plan specified in ethics and per the terms set out by funding agencies.
Even though there are disparities and variations in the data protection laws across the different provinces in Canada, the streamlined processes for research data access in Alberta are highly efficient.

Background: The orbitofrontal cortex (OFC) has consistently been implicated in the pathology of both drug and behavioral addictions. However, no study to date has examined OFC thickness in internet addiction. In the current study, we investigated the existence of differences in cortical thickness of the OFC in adolescents with internet addiction. On the basis of recently proposed theoretical models of addiction, we predicted a reduction of thickness in the OFC of internet addicted individuals.Findings: Participants were 15 male adolescents diagnosed as having internet addiction and 15 male healthy comparison subjects. Brain magnetic resonance images were acquired on a 3T MRI and group differences in cortical thickness were analyzed using FreeSurfer. Our results confirmed that male adolescents with internet addiction have significantly decreased cortical thickness in the right lateral OFC (p<0.05).Conclusion: This finding supports the view that the OFC alterations in adolescents with internet addiction reflect a shared neurobiological marker of addiction-related disorders in general. ; This work was supported by the Seoul National University Brain Fusion Program Research Fund. SBH was supported by a National Research Foundation of Korea (NRF) grant (Global Internship Program) funded by the Korean government (MEST). MY was supported by an NHMRC fellowship grant (#1021973). ; OAIID:oai:osos.snu.ac.kr:snu2013-01/102/0000003446/2 ; SEQ:2 ; PERF_CD:SNU2013-01 ; EVAL_ITEM_CD:102 ; USER_ID:0000003446 ; ADJUST_YN:Y ; EMP_ID:A072419 ; DEPT_CD:701 ; CITE_RATE:2.127 ; FILENAME:첨부된 내역이 없습니다. ; DEPT_NM:교육학과 ; EMAIL:cdkim@snu.ac.kr ; SCOPUS_YN:Y ; CONFIRM:Y

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research. ; ENIGMA MDD work is supported by NIH grants U54 EB020403 (Thompson), R01 MH116147 (Thompson), and R01 MH117601 (Jahanshad & Schmaal). LS was supported by an NHMRC Career Development Fellowship (1140764). AFFDIS cohort: this study was funded by the University Medical Center Goettingen (UMG Startfoerderung) and the research team is supported by German Federal Ministry of Education and Research (Bundesministerium fuer Bildung und Forschung, BMBF: 01 ZX 1507, "PreNeSt - e:Med"). Barcelona cohort: MJP is funded by the Ministerio de Ciencia e Innovación of the Spanish Government and by the Instituto de Salud Carlos III through a 'Miguel Servet' research contract (CP16–0020); National Research Plan (Plan Estatal de I + D + I 2016–2019); and co-financed by the European Regional Development Fund (ERDF). BRC DeCC cohort: CHYF is supported by NIHR BRC. Calgary cohort: supported by Canadian Institutes for Health Research, Branch Out Neurological Foundation. Cardiff cohort: supported by the Medical Research Council (grant G 1100629) and the National Center for Mental Health (NCMH), funded by Health Research Wales (HS/14/20). CLING cohort: this study was partially supported by the Deutsche Forschungsgemeinschaft (DFG) via grants to OG (GR1950/5–1 and GR1950/10–1). CODE cohort: Henrik Walter is supported by a grant of the Deutsche Forschungsgemeinschaft (WA 1539/4–1). The CODE cohort was collected from studies funded by Lundbeck and the German Research Foundation (WA 1539/4–1, SCHN 1205/3–1, SCHR443/11–1). DIP-Groningen cohort: this study was supported by the Gratama Foundation, the Netherlands (2012/35 to NG). Edinburgh cohort: The research leading to these results was supported by IMAGEMEND, which received funding from the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 602450. This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award 104036/Z/14/Z. FOR2107-Marburg cohort: funded by the German Research Foundation (DFG, grant FOR2107 KR 3822/7–2 to AK; FOR2107 KI 588/14–2 to TK and FOR2107 JA 1890/7–2 to AJ). Houston cohorts: supported in part by NIMH grant R01 085667 and the Dunn Research Foundation. JCS is supported by the Pat Rutherford, Jr. Endowed Chair in Psychiatry. IMH Study cohort: supported by funding from NHG (SIG/15012) and NMRC CISSP (2018). Melbourne cohort: funded by National Health and Medical Research Council of Australia (NHMRC) Project Grants 1064643 (Principal Investigator BJH) and 1024570 (Principal Investigator CGD). Minnesota cohort: the study was funded by the National Institute of Mental Health (K23MH090421; Dr. Cullen) and Biotechnology Research Center (P41 RR008079; Center for Magnetic Resonance Research), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, and the Minnesota Medical Foundation. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute. Münster cohort: funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5–1 and DA1151/5–2 to UD; SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). NESDA cohort: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10–000–1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. Pharmo cohort: supported by ERA-NET PRIOMEDCHILD FP 6 (EU) grant 11.32050.26. PSYABM-NORMENT: supported by the Research Council of Norway (project number 229135). The South East Norway Health Authority Research Funding (project number 2015052). The Department of Psychology, University of Oslo, Norway. San Francisco cohort: supported by NIH/NCCIH 1R61AT009864–01A1. NIMH R01MH085734. SHIP and SHIP-trend cohorts: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. Stanford cohorts: this work was supported by NIH grant R37 MH101495. The BiDirect Study was supported by grants from the German Federal Ministry of Education and Research (BMBF; grants FKZ-01ER0816 and FKZ-01ER1506). MDS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. TCH is supported by NIMH grant 5K01MH117442. EJWVS, JL, and TFB are supported by European Research Council grant no. ERC-ADG-2014–671084 INSOMNIA. TFB is supported by a VU University Amsterdam University Research Fellowship 2016–2017. JL is supported by a VU University Amsterdam University Research Fellowship 2017–2018. ; publishedVersion