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OHBM annual meeting 2022: Glasgow

Resource page for my poster presentations at the Organization of Human Brain Mapping society's (OHBM) annual meeting in Glasgow, Scotland.


The Normative Modeling Framework for Computational Psychiatry: A Tutorial and Dataset.


References:

  1. Tutorial Paper, The Normative Modeling Framework for Computational Psychiatry. Nature Protocols link.

  2. Dataset paper, Charting Brain Growth and Aging at High Spatial Precision. eLife link.

  3. Evidence for Embracing Normative Models (preprint)

GitHub links:

  1. Apply pre-trained dataset to new models (with example data)

  2. Tutorial on training a normative model. Start to finish instructions (with example data)

  3. PCNToolkit python package for normative modeling

  4. Tutorial on visualization of normative modeling evaluation metrics

  5. Downstream analysis using deviation scores: classification & group difference testing

  6. Downstream analysis using deviation scores: regression - predicting general cognitive ability

  7. Additional tutorials

Google Colaboratory links (recommended method)):

Run python notebooks in the web browser for free, no need to set up a python environment

  1. Apply pre-trained dataset to new models (with example data)

  2. Tutorial on training a normative model. Start to finish instructions (with example data)

  3. Tutorial on visualization of normative modeling evaluation metrics

  4. Downstream analysis using deviation scores: classification & group difference testing

  5. Downstream analysis using deviation scores: regression - predicting general cognitive ability

  6. Additional tutorials

Chat with the PCNToolkit developers and users on Gitter.

Documentation on Read The Docs.

Interactive visualization of evaluation metrics website.


Functional Connectivity Architecture of Social Cognition in Schizophrenia and Early Psychosis.


Seed ROIs were chosen based on: Green, M. F., Horan, W. P., & Lee, J. (2015). Social cognition in schizophrenia. Nature Reviews Neuroscience, 16(10), 620–631. https://doi.org/10.1038/nrn4005


Predictive Modeling methods paper: Sripada, C., Angstadt, M., Rutherford, S., Kessler, D., Kim, Y., Yee, M., & Levina, E. (2019). Basic Units of Inter-Individual Variation in Resting-State Connectomes. Scientific Reports, 9(1), 1900. https://doi.org/10.1038/s41598-018-38406-5


Open Science Framework pre-registration: https://osf.io/jh5fc


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