Alzheimer's Neural Network EEG Research Laboratory

Hawai‘i Memory Disorders Center &
Alzheimer’s Research Unit

2024 ANNE Research Team

(front) medical students Michael Read, janette Keola, Kirra Borrelo, Nathan Kim Neurologist Kore Kai Liow, MD, Shay Nakahira, Kaylie Yamauchi, Sarah Hogue, Research staffs (back row) Kelly Asahi, Jason Edwards, Sam Kim, John Seib, Qi Zhi, DNP, MPH, Ena Zhu

ANNE (Alzheimer’s Neural Network EEG) Lab joins Mass General & UCSD as Early Adopters to Harness AI’s Power to Pioneer Use of EEG in Early Detection and Monitoring of Alzheimer’s Disease

There is currently no widely available tool to measure someone’s memory or cognitive abilities to look for early signs of Alzheimer’s or monitor the efficacy of treatment or progression. Traditional memory testing are subjective and depends on patients’ performance thus we rely on invasive test like spinal tap and use of radioactive substance injected into body to look for Alzheimer’s biomarker in the brain which are not readily accessible in island communities such as Hawaii state and many rural communities in US. Lack of readily available testing often leads to delayed diagnosis & intervention and eventually poor long-term outcome.

The Hawaii Memory Disorders Center & Alzheimer’s Research Unit collaborates with the Advance Brain Monitoring to launch the Hawaii ANNE (Alzheimer’s Neural Network EEG) Lab dedicated to develop an easily accessible, noninvasive, nontoxic and cost effective tool to measures synaptic neuronal network brain electrical activities using BEAM™ (Biomarker based Electrophysiology Advanced Brain Monitoring). BEAM is a proven EEG platform developed using machine learning AI algorithms to map the progression of cognitive decline across the dementias.

Peer Reviewed Pub Med Publication: Abnormal Temporal Slowing on EEG Findings in Preclinical Alzheimer’s Disease Patients with the ApoE4 Allele: A Pilot Study Kim N, Tan C, Ma E, Kutlu S, Carrazana E, Vimala V, Viereck J, Liow K. (October 28, 2023) Cureus 15(10): e47852. DOI 10.7759/Cureus.47852.

“Our Hawaii patients, caregivers, families, neurologists & researchers are honored to be able to play a role to contribute to this important ground breaking research to develop a noninvasive, widely available and cost effective tool for Alzheimer’s Disease to serve our island and rural populations, ” Kore Kai Liow, MD, Director, Hawaii Memory Disorders Center Principal Investigator, Alzheimer’s Neural Network EEG (ANNE) Research Lab, Clinical Professor of Medicine (Neurology), Graduate Faculty, Clinical & Translational Research, University of Hawai`i John Burns School of Medicine. Dr. Liow is a research neurologist trained in clinical neurophysiology & EEG at National Institutes of Health (NIH), Bethesda, Maryland. Info: kliow@hawaii.edu

Denver, CO, July 2021

Evaluating Whether EEG could Predict Alzheimer’s Disease Onset in Preclinical Patients with the ApoE41

Nashville, TN, Dec 2022

EEG Predicting Alzheimer’s Disease Onset in Preclinical Patients with the ApoE4 Allele: An Update on EEG Findings

Alzheimer's Neural Network EEG Research Updates for Hawaii

Evaluation of BEAM™ EEG Biomarkers Versus MMSE in Detecting Mild Cognitive Impairment and Alzheimer’s Disease

December 19, 2025

Accurate detection of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is critical as therapeutic strategies increasingly emphasize early intervention. While the Mini-Mental State Examination (MMSE) remains a widely used cognitive screening tool, its sensitivity to subtle neurophysiological changes is limited. Emerging evidence suggests that EEG-based biomarkers may provide more objective and biologically grounded indicators […]

Using BEAM to Distinguish Alzheimer’s Disease from Mild Cognitive Impairment Through Electrophysiology

December 19, 2025

Early and accurate differentiation between Alzheimer’s disease (AD) and mild cognitive impairment (MCI) is increasingly critical as new disease-modifying therapies emphasize intervention at the earliest possible stages. However, MCI often represents a heterogeneous and nonspecific prodromal phase, complicating clinical diagnosis when symptoms overlap. Recent research highlights the potential of Biomarker-Based Electrophysiology for Advanced Monitoring (BEAM) […]

ERP Biomarkers in Alzheimer’s Disease: Real-World Evidence from CTAD 2025

December 16, 2025

ERP Biomarkers of Cognitive Dysfunction in Alzheimer’s Disease: Real-World Evidence Supporting Translational Clinical Trial Endpoints Advances in neuroscience and digital biomarkers are transforming how clinicians and researchers detect, monitor, and study Alzheimer’s disease (AD). At the 2025 Clinical Trials on Alzheimer’s Disease (CTAD) Conference in San Diego, researchers presented compelling evidence demonstrating how event-related potentials […]

2025 EVALUATION OF BEAM EEG BIOMARKERS VERSUS MMSE IN DETECTING MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE RETROSPECTIVE STUDY

2025 Using Biomarker-Based Electrophysiology for Advanced Monitoring (BEAM) to Distinguish Alzheimer’s Disease and Mild Cognitive Impairment

2025 ANNE Lab work on ERP and EEG presented at 2025 CTAD San Diego 2025

2025 Comparative Efficacy BEAM EEG and MMSE in Early Detection Mild Cognitive Impairment

2025 P300 EEG Biomarker in the early identification of Alzheimer’s Disease

2024 Sept Hawaii’s Alzheimer’s Neural Network EEG (ANNE) Lab AI Machine Learning Detection of AD presented 2023 Sept Tokyo AAIC

2024 Jan EEG Slowing and CSF Amyloid Status Implications for Alzheimer Disease Detection and Progression Presented 2023 WCN

2024 Feb EEG Slowing and CSF Amyloid Status Implications for Alzheimer's Disease Detection and Progression 2024 EEG Meeting

2023 Sept Tokyo AAIC Poster on Using AI Machine Learning Early Detection AD

2023 Feb EEG Slowing and CSF Amyloid Status Implications for Alzheimer's Disease Detection and Progression

What is BEAM? (Biomarker – Based Electrophysiology for Advanced Monitoring)

BEAM™ is a new test used by neurologist combining EEG with neurocognitive testing.

In addition to routine EEG, you will be asked to perform a series of active and passive visual, auditory tasks to assess attention, memory and emotion.

Using the latest AI- Machine Learning technology, a set of unique brain “fingerprints” or cognitive biomarkers unique to the patient will be generated in comparison with thousands of normal data to help your doctor to:

-making accurate diagnosis of your condition

-quantify the severity of the condition

-tracking disease progression

-assessing whether a treatment or intervention has been effective

For more information: https://hawaiineuroscience.com/alzheimer-eeg-project/

https://www.advancedbrainmonitoring.com/applications/biomarkers

Professor of Medicine (Neurology), Graduate Faculty, Clinical & Translational Research, University of Hawai`i John Burns School of Medicine. Dr. Liow is a research neurologist trained in clinical neurophysiology & EEG at National Institutes of Health (NIH), Bethesda, Maryland. Info: ANNE Research Lab PI kliow@hawaii.edu