Machine Learning SIG

1. Decoding
   1. Multivariate time series classification between conditions
   2. Realtime - Brain computer interface / neurofeedback
2. Subject classification –
   1. eg. Healthy Control vs Major Depressive Disorder
   2. What are the significant features (brain regions, Hz)
3. Prediction of future condition / Biomarkers
   1. What signals predict conversion from mild cognitive impairment to Alzheimer
   2. What signals predict recovery from traumatic brain injury
   3. What signals predict poor outcome for epilepsy surgery
4. Multimodal Integration
   1. Timing derived from MEG / localization from fMRI – joint ICA (??)
   2. Signal comparison between naturalistic viewing data MEG/fMRI
5. Signal classification
   1. Artifact
   2. Signal of interest – Spike detection for epilepsy
   3. Signal/sequence predicts correct response
6. Temporal learning models – RNN DL / markov model
   1. Inferences from deep learning models
   2. CNN on images vs. CNN of brain responses to same images