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Methods to Compare Predicted and Observed Phosphene Experience in tACS Subjects.

Aprinda IndahlastariAditya K KasinadhuniChristopher SaarKevin CastellanoBakir MousaMunish ChauhanThomas H MareciRosalind J Sadleir
Published in: Neural plasticity (2018)
These methods may have promise for predicting phosphene generation using data collected during in-scanner tACS sessions and may enable better understanding of phosphene origin. Additional empirical data in a larger cohort is required to fully test the robustness of the proposed methods. Future studies should include additional montages that could dissociate retinal and occipital stimulation.
Keyphrases
  • big data
  • electronic health record
  • diabetic retinopathy
  • artificial intelligence
  • current status
  • magnetic resonance imaging
  • machine learning
  • magnetic resonance
  • deep learning