Human neuroimaging offers non-invasive insights into the structure and function of the living brain, allowing us to quantify variability in the brain that may confer risk for psychiatric and neurological disorders. However, statistical principles do not make exceptions for medical data, and the potential to use imaging to understand the variation in the brain that may confer risk for psychiatric and neurological disorders has been hampered by an overwhelming number of unreproducible findings. Studies with small samples, overly-lenient thresholds for statistical significance, and publication biases tend to seed hypothesis driven research, leading to a cyclic exaggeration of potentially incomplete or biased, unreliable findings. Recently, large-scale international consortia have been formed to address the reliability and reproducibility of biomedical findings. I will be discussing the work and findings from the ENIGMA consortium, which began to perform unbiased genome-wide association scans of brain structure and has recently pooled together neuroimaging and genomic information from over 60 datasets around the world. We recently identified hundreds of genetic loci that help shape localized cortical and subcortical brain morphometry, and a genetic architecture that correlates with genetic risk factors for disease. ENIGMA has expanded beyond studies of common genetics to incorporate over 30 clinical, methodological, and biologically focused working groups, which range from efforts to map normative brain development and aging across the lifespan, to a transdiagnostic initiative to study the neurobiological signatures of suicidal thoughts and behaviors. The continuously growing collaborations have many advantages, yet bring new challenges for data harmonization, integration, and tools for the continuous refinement of knowledge. This talk will highlight findings from a few of our ongoing initiatives in ENIGMA, touch upon new study directions currently underway in my lab, and I will discuss open challenges in the field of collaborative neuroscience.
Dr. Neda Jahanshad is an Associate Professor of Neurology and Biomedical Engineering at the USC Mark and Mary Stevens Neuroimaging and Informatics Institute at the University of Southern California, working to bridge AI, informatics, data science and engineering with neurology and psychiatry. Dr. Jahanshad is director of USC’s Laboratory of Brain eScience and associate director of the international neuroimaging consortium, ENIGMA, which conducts harmonized analyses across tens to hundreds of datasets worldwide to reliably study the brain in health and disease as observed using neuroimaging. In particular, Dr. Jahanshad co-leads two ENIGMA working groups -- one on the neurological effects of HIV infection, and another on suicidal thoughts and behaviors. Dr. Jahanshad’s research focus is on developing tools and algorithms to assess brain structure, microstructure, and connectivity throughout the lifespan, determining genetic and environmental factors that contribute to the variability in brain connections, risk for brain dysfunctions, and outcomes for people with mental illnesses, developmental and neurodegenerative disorders, and dementias.
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Host: Muhao Chen POC: Alma Nava