Tundra Space

Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

2 clinical studies listed.

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Gamma Oscillations

Tundra lists 2 Gamma Oscillations clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.

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NOT YET RECRUITING

NCT07690865

Investigating the Effectiveness of Personalized Optimal Gamma Auditory Frequency Stimulation Intervention on Cognitive Function Enhancement

This study aims to evaluate whether personalized gamma-frequency auditory stimulation enhances cognitive function and brain synchronization. While 40 Hz auditory stimulation has been widely studied, recent evidence suggests optimal frequencies vary by individual. Using a cross-over design with 20 healthy adults, the research compares "optimal" versus "non-optimal" frequencies over one-month intervention periods. Effectiveness is measured through EEG recordings and executive function tasks. The goal is to determine if personalized sensory intervention provides a more effective, non-invasive strategy for enhancing cognitive performance.

Gender: All

Ages: 18 Years - 40 Years

Updated: 2026-07-16

1 state

Gamma Oscillations
Healthy Adults
Alzheimer's Disease (AD)
+1
NOT YET RECRUITING

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).

Gender: All

Ages: 18 Years - Any

Updated: 2026-03-17

Terminal Illness
End-of-Life Care
Death
+11