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).
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)
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
Adults (≥18 years) with terminal illness or severe acute trauma who have a do-not-resuscitate (DNR/DNI) order and for whom a legally authorized surrogate has provided informed consent. Participants are recruited from hospice, palliative care units, and intensive care units at three U.S. academic medical centers. The study focuses on individuals with physician-estimated survival of 7 days or less. All participants receive continuous non-invasive EEG/BCI monitoring during the peri-death period.
Cohort
Prospective
Not listed
Detection of Neurocognitive Signals After Clinical Death Prior to Brain 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.
Successful Capture and Preservation of Neurocognitive Signals
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.
Spectral Power of Neurocognitive Signals
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).
Functional Connectivity Patterns
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).
Cross-Frequency Coupling
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).
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Noah Tech, Corp.
Lead sponsor
Columbia University
Collaborator
Massachusetts Institute of Technology
Collaborator
Stanford University
Collaborator
City of Hope Medical Center
Collaborator
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