Asymmetric generalizability of multimodal brain-behavior associations across age-groups

Machine learning methods have increasingly been used to map out brain-behavior associations (BBA), and to predict out-of-scanner behavior of unseen subjects. Given the brain changes that occur in the context of aging, the accuracy of these predictions is likely to depend on how similar the training and testing data sets are in terms of age. To this end, we examined how well BBAs derived from an age-group generalize to other age-groups. We partitioned the CAM-CAN data set (N = 550) into the young, middle, and old age-groups, then used the young and old age-groups to construct prediction models for 11 behavioral outcomes using multimodal neuroimaging features (i.e., structural and resting-state functional connectivity, and gray matter volume/cortical thickness). These models were then applied to all three age-groups to predict their behavioral scores. When the young-derived models were used, a graded pattern of age-generalization was generally observed across most behavioral outcomes-predictions are the most accurate in the young subjects in the testing data set, followed by the middle and then old-aged subjects. Conversely, when the old-derived models were used, the disparity in the predictive accuracy across age-groups was mostly negligible. These findings hold across different imaging modalities. These results suggest the asymmetric age-generalization of BBAs-old-derived BBAs generalized well to all age-groups, however young-derived BBAs generalized poorly beyond their own age-group.Nanyang Technological UniversityNational Research Foundation (NRF)Published versionJunhong Yu is supported by the Nanyang Assistant Professorship (Award no. 021080-00001). Nastassja L. Fischer is supported by the Cambridge-NTU Centre for Lifelong Learning and Individualised Cognition (CLIC), a project by the National Research Foundation (NRF), Prime Minister's Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) Programme. Data collection and sharing for this project was provided by the CamCAN. CamCAN funding was provided by the UK Biotechnology and Biological Sciences Research Council (grant number BB/H008217/1), together with support from the UK Medical Research Council and University of Cambridge, UK

Age-specificity and generalization of behavior-associated structural and functional networks and their relevance to behavioral domains

Behavior-associated structural connectivity (SC) and resting-state functional connectivity (rsFC) networks undergo various changes in aging. To study these changes, we proposed a continuous dimension where at one end networks generalize well across age groups in terms of behavioral predictions (age-general) and at the other end, they predict behaviors well in a specific age group but fare poorly in another age group (age-specific). We examined how age generalizability/specificity of multimodal behavioral associated brain networks varies across behavioral domains and imaging modalities. Prediction models consisting of SC and/or rsFC networks were trained to predict a diverse range of 75 behavioral outcomes in a young adult sample (N = 92). These models were then used to predict behavioral outcomes in unseen young (N = 60) and old (N = 60) subjects. As expected, behavioral prediction models derived from the young age group, produced more accurate predictions in the unseen young than old subjects. These behavioral predictions also differed significantly across behavioral domains, but not imaging modalities. Networks associated with cognitive functions, except for a few mostly relating to semantic knowledge, fell toward the age-specific end of the spectrum (i.e., poor young-to-old generalizability). These findings suggest behavior-associated brain networks are malleable to different degrees in aging; such malleability is partly determined by the nature of the behavior.Nanyang Technological UniversityPublished versionNanyang Assistant Professorship, Grant/Award Number: 021080-00001

Exposure to stressful events during a peacekeeping mission may have a price : the impact on trait of negative and positive affect and mental health.

We evaluated the participants? negative affect, positive affect, post-traumatic stress disorder, and depression symptoms before and after a peacekeeping mission. Depression symptoms and positive affect after mission were significantly associated with exposure to stressful events during the mission, controlled by the respective characteristics before mission. Negative affect and post-traumatic stress disorder symptoms after mission had a tendency to be associated with exposure to stressful events during the mission, controlled by the respective characteristics before mission. In conclusion, even in healthy and physically active male peacekeepers, those more exposed to stressful events could be more vulnerable to present negative outcomes

Singapore Longitudinal EArly Development Study (SG LEADS)

doi:10.25540/DNBB-GFD0Singapore Longitudinal Early Development Study (SG LEADS)SG LEADS was funded in 2017 to investigate early childhood development in Singapore. The study highlights the importance of promoting human development to increase productivity and maintaining the well-being of a population as a means of achieving a vibrant economy and secure society. SG LEADS examines factors that affect children&rsquo;s early development in the domains of health, cognitive, and social-psychological functions. It also aims to understand how multiple contexts such as the family, pre-school, community and the state interact to influence children&rsquo;s development. The study intends to track development of children in Singapore to understand factors that can promote Singaporean children&rsquo;s early childhood development and provide interventions that can help address these factors.&nbsp; The main research questions are: (1) what is the state of Singapore children, (2) how family, childcare and early education institutions, community, and state interact to shape the development of Singapore&rsquo;s children, and (3) how these investments affect intergenerational mobility and social stratification in Singapore. Our research addresses policy concerns such as how caregiving arrangements, preschool education, the roles of mother, father and extended family, cross-cultural family background, family resources, time and technology use, living arrangements, and family dynamics/relations affect children&rsquo;s social-emotional, cognitive, and health development, and what roles community and government can play in improving child outcomes.&nbsp; SG LEADS consists of a core panel survey and three sub-projects.&nbsp; The Panel Survey is comprised of 2 waves of survey, with the first one conducted in 2018/2019 and the second in 2021. The Panel Survey is led by PI Professor Wei-Jun Jean Yeung and co-PIs Assistant Professor Ding Xiaopan and Associate Professor Ryan Hong from the NUS Department of Psychology, and Professor Lim Sun Sun from the Singapore University of Technology and Design. Wave 1 data collection was completed with 5,005 children and Wave 2 data collection was completed with 4,352 children. More information on the core panel survey can be found in the documents attached.&nbsp; The 3 sub-projects focus respectively on 1) children&rsquo;s language development, 2) children&rsquo;s social skills development, and 3) development in the context of cross-cultural families. Information on each sub-project can be found in the document attached &ldquo;Description for SG LEADS Subprojects&rdquo;. The Core Panel Study documents and datasets included in this folder are: &bull; Wave 1 Questionnaires &ndash; Household Information Form, Household Questionnaire, Child Questionnaire &bull; Wave 1 Study Guide &bull; Wave 1 Technical Reports &ndash; Report 1-12 &bull; Wave 1 Data &ndash; Main Dataset, Time Diary Dataset, Codebook, Variable Codebook &nbsp; &bull; Wave 2 Questionnaires &ndash; Household Information Form, Household Questionnaire, Child Questionnaire &bull; Wave 2 Study Guide &bull; Wave 2 Technical Reports &ndash; Report 1-11 &bull; Wave 2 Data &ndash; Main Dataset, Time Diary Dataset, Codebook, Variable Codebook The Wave 1 Study Guide describes the study&rsquo;s design, questionnaire development, field procedures, response rate calculation, and sampling weights. It also provides technical notes on how the data was weighted and how variables were coded and scored.&nbsp; The Wave 2 Study Guide documents the second wave of the panel survey&rsquo;s study design, instruments, field procedures, response rate calculation and sampling weights. For enquiries on the study, please email Professor Wei-Jun Jean Yeung at [email protected]&nbsp;</p

Proceedings of the OHBM Brainhack 2021

The global pandemic presented new challenges and op-portunities for organizing conferences, and OHBM 2021was no exception. The OHBM Brainhack is an event thatoccurs just prior to the OHBM meeting, typically in-per-son, where scientists of all levels of expertise and interestgather to work and learn together for a few days in a col-laborative hacking-style environment on projects of com-mon interest (1). Building off the success of the OHBM2020 Hackathon (2), the 2021 Open Science SpecialInterest Group came together online to organize a largecoordinated Brainhack event that would take place overthe course of 4 days. The OHBM 2021 Brainhack eventwas organized along two guiding principles, providinga highly inclusive collaborative environment for inter-action between scientists across disciplines and levelsof expertise to push forward important projects thatneed support, also known as the “Hack-Track” of theBrainhack. The second aim of the OHBM Brainhack is toempower scientists to improve the quality of their sci-entific endeavors by providing high-quality hands-ontraining on best practices in open-science approaches.This is best exemplified by the training events providedby the “Train-Track” at the OHBM 2021 Brainhack. Here,we briefly explain both of these elements of the OHBM2021 Brainhack, before continuing on to the Brainhackproceedings