Detecting consciousness using a small TMS-EEG setup and the Presence-IP1.0 algorithm

Prospective Validation of a Reduced-Montage TMS-EEG Complexity Algorithm (Presence-IP1.0) to Differentiate Conscious and Unconscious States Across Wakefulness and Sleep

Not applicable Interventional University of Wisconsin, Madison · NCT07523191

This project will try the Presence-IP1.0 algorithm with a reduced-channel TMS-EEG setup to see if it can tell when healthy adults are awake and conscious versus asleep.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment30 (estimated)
Ages18 Years to 85 Years
SexAll
SponsorUniversity of Wisconsin, Madison Academic / other
Locations1 site (Madison, Wisconsin)
Trial IDNCT07523191 on ClinicalTrials.gov

What this trial studies

Thirty healthy adult participants will undergo TMS-EEG recordings during wakefulness and natural sleep using a reduced electrode montage designed for portability. A real-time algorithm, Presence-IP1.0, will analyze TMS-evoked EEG responses to classify conscious versus unconscious states. Algorithm classifications will be compared against behavioral and physiological measures of state to determine accuracy. The aim is to determine whether a reduced-channel, portable system can achieve clinically useful accuracy for detecting consciousness.

Who should consider this trial

Good fit: Ideal participants are adults (≥18) who are healthy, can give informed consent, tolerate TMS and EEG, and can sleep in a laboratory setting without disruptive sleep disorders or disqualifying implants.

Not a fit: People with neurological or psychiatric disorders, pregnancy, metal implants or implanted medical devices, uncontrolled medical conditions, significant sleep disorders, or inability to sleep in the lab are unlikely to benefit or be eligible.

Why it matters

Potential benefit: If successful, this approach could enable faster, portable, noninvasive detection of consciousness to help diagnose and monitor patients with impaired awareness.

How similar studies have performed: Previous TMS-EEG approaches, including perturbational complexity metrics, have distinguished conscious from unconscious states in research, but Presence-IP1.0's reduced-channel, real-time implementation is novel and less tested.

Eligibility criteria

Show full inclusion / exclusion criteria
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.)
* Possible pregnancy or plan to become pregnant in the next 6 months
* Any metal in the head
* Any metal in the body
* Any medical devices or implants (i.e. cardiac pacemaker, medication infusion pump, cochlear implant, vagal nerve stimulator) unless otherwise approved by the responsible MD
* Dental implants
* Permanent retainers
* Claustrophobia (a fear of small or closed places)
* Back problems that would prevent lying flat for several hours
* Regular night-shift work (second or third shift)

Where this trial is running

Madison, Wisconsin

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions SleepTMS-EEGconsciousnesscomplexity
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.