Biostatistics journal club: Enhancing Reproducibility of Neuroimaging Research with Large-Scale Open Access Datasets – December 1
1:00 pm – 2:00 pm
Biostatistics journal club: Enhancing Reproducibility of Neuroimaging Research with Large-Scale Open Access Datasets.
Lisa Nickerson, PhD, Harvard Medical School, McLean Hospital, will describe reproducibility in the context of neuroimaging and the “replication crisis” that has received great attention over the past decade. She will then discuss new large-scale open access datasets that can be used to enhance the reproducibility of neuroimaging studies, including several large-scale initiatives that are collecting a wealth of neuroimaging and complimentary behavioral, self-report, and clinical measures in hundreds to thousands to a hundred thousand participants. These studies include the Human Connectome Lifespan and Disease studies, the Adolescent Brain and Cognitive Development study, UK Biobank, Alzheimer’s Disease Neuroimaging Initiative, and others. These datasets provide unique opportunities to conduct novel neuroimaging studies of health and disease while enhancing reproducibility of the research, however, she will conclude with a discussion of the methodological and statistical challenges involved in secondary analyses of these datasets.
Statistical Challenges in”Big Data” Human Neuroimaging
Best Practices in Data Analysis and Sharing in Neuroimaging Using MRI
Lisa Nickerson, PhD, is the director of the Applied Neuroimaging Statistics Lab at McLean Hospital, which focuses on developing new statistical methods for functional magnetic resonance imaging (fMRI) data analysis for neuroimaging research on drug use and psychiatric disorders. Her current research involves using large-scale open access neuroimaging datasets including HCP and UK Biobank to develop and apply new data-driven statistical methods, such as ICA and data fusion, for investigating brain structure and function in drug use and psychiatric disorders. Nickerson also provides statistical support and training for numerous junior scientists and collaborators, mentoring, and teaches seminars and courses on imaging statistics, resting state and task fMRI data processing, multivariate data-driven methods and human brain connectomics. She is a faculty member of the Harvard Mind Brain Behavior and the Harvard Data Science Initiatives.