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A classification-based generative approach to selective targeting of global slow oscillations during sleep.

Mahmoud AlipourSangCheol SeokSara C MednickPaola Malerba
Published in: Frontiers in human neuroscience (2024)
Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.
Keyphrases
  • sleep quality
  • physical activity
  • cancer therapy
  • machine learning
  • deep learning
  • working memory
  • depressive symptoms
  • multiple sclerosis
  • white matter
  • artificial intelligence