O7-H Using Machine Learning to Discover How the Brain Works

PI: Allen Malony

The goals of this projects are to (1) develop ML/DL tools to understand high-resolution temporal/spatial neurological data and (2) use ML/DL to create/refine brain models (mouse, human) to emulate brain dynamics.

Methods

  • Dense-array EEG (dEEG), fMRI, multiphoton imaging
  • Analysis of high-resolution temporal and spatial brain activity (EEG, neuron)
  • The Virtual Brain (TVB) neural connectivity and neural mass modeling
  • ML/DL classification of brain dynamics patterns w.r.t. experiment context
  • Discovery of neural model parameters for accurate brain emulation with ML/DL