Novel Multimodal Neural, Physiological, and Behavioral Sensing and Machine Learning for Mental States
In this program, the investigators will develop novel multimodal neural-behavioral-physiological monitoring tools (software and hardware), and machine learning models for mental states within social processes and beyond. The tools consist of a multimodal skin-like wearable sensor for physiological and biochemical sensing; a conversational virtual human platform to evoke naturalistic social processes; audiovisual affect recognition software; synchronization tools; and machine learning methods to model the multimodal data. The investigators will demonstrate the tools in healthy subjects without neural recordings and in patients with drug-resistant epilepsy who already have intracranial EEG (iEEG) electrodes implanted based on clinical criteria for standard monitoring to localize seizures, which is unrelated to our study.
• Patients who suffer from drug-resistant epilepsy and already have intracranial EEG (iEEG) electrodes implanted based on clinical criteria for their standard seizure localization (unrelated to our study) will be eligible. Most patients are healthy adults outside of their epilepsy.
• Subjects \>= 18 are only included in this study.
• All patients with the above conditions and with already-implanted electrodes who are willing to participate and able to cooperate and follow research instructions will be recruited.