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About Us

The Population Neuroscience and Genetics (PoNG) Lab, co-directed by Drs. Chun Chieh Fan and Wesley K. Thompson, is dedicated to understanding how human brain and cognition develops through complex interactions of genes and environment. To answer this challenging question, we focus on developing cutting-edge analytic methods and applying them to large-scale population-based studies across the lifespan.

Large-scale neuroimaging analysis

Neuroimaging studies are currently undergoing a transformation to a much larger number of subjects and population-based sampling frames, providing new opportunities and challenges analyzing high-dimensional multi-modal neuroimaging data. In addition to high dimensionality, other challenges to traditional neuroimaging analyses include: 1) ubiquitous but small effect sizes, 2) unknown but possibly pervasive confounds, 3) poor to moderate test-retest reliability. The PoNG Lab focuses on developing multivariate methods to enhance the power and validity of associating brain measures and behavioral outcomes and to obtain unbiased estimates of the impact of genetics and environment on behavioral outcomes as mediated via multi-modal neuroimaging data. 

Polygenic inferences

Modern genome-wide association studies have opened a path for using genetics as powerful analytical instruments in a myriad of research applications. The PoNG Lab is focusing on using polygenic information as causal anchors to identify the key risk factors for human neurocognitive outcomes, either in normative developing context or in clinical manifestations. We are particularly interested in 1) genetic determinants on high-dimensional multivariate outcomes, 2) enhancing predictions using multi-omics, and 3) robust inference across genetic ancestry background.

National registries and biobank datamining

Medical and behavioral data, recorded in national health and civil registries, are a treasure trove for obtaining unbiased estimates of the clinical impact of risk factors. The PoNG Lab is particularly focused on gene and environmental interactions (GxE) that contribute to heterogeneity of clinical manifestations for psychiatric disorders. Through our collaborators in Denmark and Taiwan, we have developed and applied novel algorithms to critically examine the impact of GxE on psychiatric outcomes.