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IGMN NeuroComputation Workshop

  • Objective: to provide an overview of computational methodologies useful for various types of neuroscience data, plus opportunities to “practice” with example data sets. The “practice” sessions will include basic instruction on using R, python, and matlab; data management, data transfer, and data cleaning concepts; and practice using various data analysis/visualization programs.
  • Dates: early/mid-August (6-13th?)
  • Schedule: 6-7 days; 3-4 h morning presentations followed by optional ~ 2 h “hands-on” practice
  • Requirement for Graduate Minor in Neuroscience: Students who attend and engage in all the workshop presentations will receive a “Certificate of Completion”, which will verify that they have met this requirement for the Graduate Minor in Neuroscience.

Topics:

1) Omics – transcriptomics, proteomics, metabolomics (3 days)

Lead Instructor: Dan Jacobson

  • Introduction to data collection techniques, data processing, available analytical tools
  • GWAS (genome-wide association studies) –based systems biology
  • Machine learning/higher order relationships for omics datasets
  • Integration of different data types: visualization, network theory, networks, pathways and biomarker discovery

2) Brain imaging-Neural activity – single neuron/small population analyses, EEG, fNIRS, fMRI, (3 days)

Lead Instructors: Aaron Buss, Xiaopeng Zhao, Sara Hanrahan

  • Introduction to data collection techniques, data processing, available analytical tools
  • Time/ frequency domain neural cell activity analyses

3)  Computational Modeling of Neural networks (1 day)

Lead Instructor: Bruce MacLennan

  • Levels of models, applications of models, available modeling software

Additional Instructors: Bobby Whitten and Lonnie Crosby

August 2018

Monday Tuesday Wednesday Thursday Friday
6
Omics 1
7
Omics 2
8
Omics 3
9
Brain Imaging-Neural activity 1
10
Brain Imaging-Neural activity 2
13
Brain Imaging-Neural activity 3
14
Neural Networks

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