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NCT Number: NCT07477028

Non-Invasive Detection and Preservation of Neurocognitive Signals in the Peri-Death Period Using Brain-Computer Interface and Artificial Intelligence

Background: Recent electroencephalography (EEG) data indicate that the transition from clinical death to cellular death is marked by highly organized neurophysiological events, including significant surges in gamma-band power, cross-frequency coupling, and distinct spreading depolarization waves. This prospective, observational feasibility study utilizes rapid-deployment, high-density, noninvasive BCI hardware paired with proprietary AI analytics to detect, classify, and securely archive these terminal neurocognitive signals.

Objectives: (1) Quantify transient gamma-band activity and cross-frequency connectivity post-clinical death; (2) Validate the efficacy of machine learning models for real-time signal classification in high-noise clinical environments; (3) Establish a highly secure, encrypted bio-informational archive of peri-life EEG data.

Design: Prospective, open-label, multicenter, observational cohort (n>20).

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Key information

Conditions

Terminal Illness Brain Death Brain Diseases Central Nervous System Diseases Cognition Cognitive Coma Consciousness Consciousness Disorders Death Death Anxiety EEG Electroencephalography End-of-life Care Gamma Oscillations Memory Near-Death Phenomena Necrophobia Nervous System Diseases Neurobehavioral Manifestations Neurologic Manifestations Pathologic Processes Pathological Conditions, Signs and Symptoms Severe Acute Trauma Unconsciousness

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

About this study

This prospective observational feasibility study will use non-invasive high-density EEG combined with a wireless brain-computer interface (BCI) and artificial intelligence analytics to detect, characterize, and archive neurocognitive signals in adult patients during the peri-death period. The study includes individuals with terminal illness or severe acute trauma who have a do-not-resuscitate (DNR/DNI) order. Building on recent human findings of gamma oscillation surges and cross-frequency coupling (Vicente et al., 2022; Xu et al., 2023), the study aims to quantify these signals, test AI-driven real-time classification, and explore technical feasibility for future signal preservation and continuity research. No therapeutic intervention is performed. All monitoring is conducted with surrogate consent under strict ethical oversight.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Adults ≥18 years with terminal illness or severe acute trauma
  • Do-not-resuscitate (DNR/DNI) order in place
  • Surrogate decision-maker available and willing to provide informed consent
  • Expected survival ≤7 days (physician estimate)

Exclusion criteria

  • Brain death already declared > 24 hours prior to enrollment
  • Contraindication to EEG/BCI headset placement (e.g., severe scalp injury)
  • Patient lacks a legally authorized representative

Treatment and study plan

Primary outcomes

  1. Detection of Neurocognitive Signals After Clinical Death Prior to Brain Death

    Time frame: 0-120 minutes after clinical death

    Presence or absence of organized neurocognitive signals and measurable brain activity, as recorded by non-invasive high-density electroencephalography (EEG), in the human brain during the period immediately following clinical death (cessation of circulation) but prior to declaration of brain death. The primary outcome will be reported as the proportion of participants with detectable organized neural activity (yes/no) meeting predefined signal thresholds.

Secondary outcomes

  1. Successful Capture and Preservation of Neurocognitive Signals

    Time frame: Up to 24 hours after clinical death

    Proportion of participants for whom real-time neurocognitive signals were successfully captured, recorded in high quality, and securely preserved for long-term storage using non-invasive high-density EEG and wireless brain-computer interface (BCI) technology. Reported as the number and percentage of participants with complete, artifact-free recordings suitable for analysis.

  2. Spectral Power of Neurocognitive Signals

    Time frame: Up to 24 hours after clinical death

    Quantitative analysis of spectral power of captured neurocognitive signals, measured in microvolts squared per hertz (µV²/Hz), across standard EEG frequency bands (delta, theta, alpha, beta, gamma).

  3. Functional Connectivity Patterns

    Time frame: Up to 24 hours after clinical death

    Quantitative analysis of functional connectivity patterns among brain regions, measured using coherence and phase-locking value (PLV) indices, reported on a scale from 0 (no connectivity) to 1 (perfect connectivity).

  4. Cross-Frequency Coupling

    Time frame: Up to 24 hours after clinical death

    Quantitative analysis of cross-frequency coupling between EEG frequency bands, measured using the modulation index (MI), reported as a unitless value ranging from 0 (no coupling) to 1 (maximum coupling).

  5. Temporal Dynamics of Neurocognitive Signals

    Time frame: Up to 24 hours after clinical death

    Quantitative analysis of the temporal dynamics of neurocognitive signals, including signal duration and onset latency, measured in seconds (s) from the time of clinical death.

  6. Informational Content of Neurocognitive Signals

    Time frame: Up to 24 hours after clinical death

    Qualitative and quantitative analysis of the potential informational content of captured neurocognitive signals, measured using permutation entropy, reported as a unitless value on a scale from 0 (completely regular/predictable) to 1 (completely random).

Study contacts

Contact information is provided by the study sponsor or research team.

Dr. Wallace Lynch, Ph.D.

CONTACT

[email protected]

6504895808

Sponsors and collaborators

Lead sponsor

Noah Tech, Corp.

Industry

Collaborators

  • City of Hope Medical Center
  • Columbia University
  • Massachusetts Institute of Technology
  • Stanford University

Registry information

Official study title

Feasibility of Non-Invasive Detection and Preservation of Neurocognitive Signals in the Peri-Death Period Using Brain-Computer Interface and Artificial Intelligence: A Prospective Observational Study (NeuroCogPresv)

Acronym: NeuroCogPresv

Important dates

Study start
2026
Primary completion
2030
Study completion
2035
First posted
Mar 17, 2026
Registry last updated
Mar 17, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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