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Population Neuroscience and Genetics Center

Population Neuroscience and Genetics (PNG) Center

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Center Directors

​Wes Thompson, Ph.D.
​Chun Chieh Fan, M.D, Ph.D.
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PNG Center Vision


As neuroscientific studies mature to sample sizes and diversity relevant for making population inferences, the field is just beginning to realize the need for integrating multiple existing research frameworks, including epidemiology, data science, genetics and genomics, and biophysics into a consistent framework. From national health registries, to large-scale imaging cohorts, to single cell molecular assays, there is a pressing need (with corresponding funding calls from agencies) to combine multi-scale/multi-level data to understand the neurobiological basis of human behavior and mental health and to ascertain the factors impacting neuropsychiatric outcomes in diverse populations. 

The Population Neuroscience and Genetics (PNG) Center addresses this need by developing and applying cutting-edge analytic methods from multiple fields (e.g., causal inference, psychometrics, high-dimensional Bayesian inference) to address these challenges under the rubric of Population Neuroscience. The multidisciplinary PNG investigative team extends an epidemiologically- and psychometrically-informed causal inference framework to neuroscientific research (existing in vivo human datasets from population registers and large-scale imaging genetic studies), developing and applying novel statistical and bioinformatic tools to critically examine the potential biases, causal pathways, and heterogeneity in longitudinal, lifespan neuropsychiatric outcomes. 

​With core PNG faculty and staff dedicated to curating and accessing existing large-scale datasets, building necessary bioinformatic pipelines, managing the data in-flow/out-flow, exploratory data analyses and developing novel data science tools, we are working to forge a path toward better understanding of the factors shaping human brain development, how pathological symptoms emerge, heterogeneity in prognoses, and population-level impacts of exposures and outcomes.

As a commitment to understand the diversity of the human brain, the PNG Center is dedicated to recruit and maintain highly diverse staff and collaborators. By integrating perspectives from researchers with diverse backgrounds, we will foster an environment ideally situated to focus on important public health problems, revealing causal factors underlying the heterogeneous effects and outcomes commonly-observed in population neuroscience data. 
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We envisage the PNG Center as a hub for fellow researchers from multiple fields (e.g., neuroscience, genetics, epidemiology, data science, statistics, psychology and psychiatry), working together to move the field toward better analytic practice, more accessible research tools, and deeper understanding of heterogeneity of neuropsychiatric outcomes at the population level. With insight gained from vertical integration of whole-brain imaging analyses, population cohorts, and detailed molecular assays, we strive to get closer to discovering leverage points for improving psychiatric well-being. 

PNG Research Themes and Ongoing Agenda


Meaningful Effects / Biomedical Population Inference
  • Empirical Bayes estimation of effect sizes for imaging and genetic data
  • Incorporating prior information / covariates / sources of variation, such as molecular annotations for genetic risk prediction.
  • Generalization analysis / Bias analysis / Test-Retest Reliability / Causal Inference in population neuroscience data / Accounting for diverse samples
  • Models for examining heterogeneity in diagnostic trajectories (Computational Psychiatry applications) - GRANT APPLICATION
  • High-dimensional mediation analyses 

Utilizing Population Registers
  • National health and civil registries data exploration - Danish and Taiwanese registers - GRANT APPLICATION
  • Heritability / Genomic architecture based on registry data
  • Prediction / Prognosis / Tx effects / Causal inference using diagnoses and drug use patterns extracted from health registries
  • Longitudinal trajectories of diagnostic progression mapped from health registries
  • G x E analyses with large scale biobank/registry samples, using civil registry derived environmental variables

Genomic Data Methods
  • Imaging Genetics - using genetic markers to examine the brain variations measured through multi-modal imaging 
  • Gene by Environment analysis, examining environmental factors that modulate the genetic predispositions
  • Polygenic scores for predicting disease risks, symptom specificities, and prognoses
  • Using pleiotropy across brain related phenotype to identify key molecular pathways and hub genes

Vertical Integration of Neuroscience Data
  • Data and variable harmonization, using IRT / meta-analyses / predictive algorithms with large scale population data - GRANT APPLICATION
  • Cloud-based informatic tool for population neuroscience data (e.g. DEAP-BRAIN)
  • Integrating multi-level human brain data, from cellular level to whole brain imaging level. 

Meet Our Team


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​Chun Chieh Fan, M.D, Ph.D.
Principal Investigator
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​Wes Thompson, Ph.D.
Principal Investigator
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​Bohan Xu
Data Scientist
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​Firas Naber
Research Assistant

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  • HOME
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    • MISSION
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    • INVESTIGATORS >
      • PRINCIPAL >
        • ROBIN AUPPERLE
        • CHUN CHIEH FAN
        • SALVADOR GUINJOAN
        • SAHIB KHALSA
        • MARTIN PAULUS
        • JONATHAN SAVITZ
        • RYAN SMITH
        • JENNIFER STEWART
        • WESLEY THOMPSON
        • EVAN WHITE
      • ASSOCIATE >
        • LEANDRA FIGUEROA-HALL
        • MARIA IRONSIDE
        • MASAYA MISAKI
        • AKI TSUCHIYAGAITO
        • HAIXIA ZHENG
      • AFFILIATE >
        • HAMED EKHTIARI
        • NAMIK KIRLIC
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        • HEEKYEONG PARK
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        • MICHAEL ROHAN
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