University of Wisconsin, Madison
This study aims to validate a novel real-time algorithm (Presence-IP1.0) designed to detect consciousness from TMS-evoked EEG responses using a reduced electrode montage. Thirty healthy adult participants will undergo TMS-EEG recordings during wakefulness and sleep. The algorithm's ability to differentiate conscious from unconscious states will be evaluated against behavioral and physiological state classification. The goal is to determine whether Presence-IP1.0 achieves clinically useful accuracy for detecting consciousness using a portable, reduced-channel system.
Inclusion Criteria: * Healthy adults greater than or equal to 18 years * Able to provide informed consent * Able to undergo TMS and EEG recordings * Able to sleep in laboratory setting Exclusion Criteria: * History of neurological or psychiatric disorders * Pregnancy * Sleep disorders affecting normal sleep architecture * Current history of poorly controlled headaches including intractable or poorly controlled migraines * Any systemic illness or unstable medical condition that may cause a medical emergency in case of a provoked seizure (cardiac malformation, cardiac dysrhythmia, asthma, etc…
Structural MRI is used to help determine coil placement, before TMS-EEG visit.
novel algorithm
Arctuva estimate
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