# Advanced signal processing methods for neural data analysis to support development of brain dynamic biomarkers for research and clinical applications in patients with Alzheimer's and related dementias

> **NIH NIH R01** · STANFORD UNIVERSITY · 2023 · $1,303,780

## Abstract

Digital technologies can have enormous impact in the prediction, early detection, and tracking of Alzheimer’s
disease progression. In particular, there is a need to develop digital biomarkers that can detect early changes in
brain function before the onset of cognitive symptoms and/or brain biomarkers. The EEG is a compelling
candidate for an early “digital biomarker” of AD as numerous EEG features are known to be correlated with AD
progression and fundamental biomarkers. Unfortunately, there is limited evidence that these same EEG
measures, as currently constructed to describe population-level data, can accurately track, or predict AD
progression in individuals. One reason for this is that EEG signals have many sources of with- and between-
subject variation that are not accounted for in current analysis methods, leading to imprecise markers that only
have sufficient statistical power at the population-level. There have been recent advances in neural signal
processing that make it possible to account for these sources of error and in turn dramatically improve the
precision of EEG-derived measures. Over the past several years our lab has made significant strides to account
for these sources of error leading us to develop novel, sophisticated signal processing algorithms that can
enhance the precision of EEG derived measures. Through the specific aims of this project, we seek to provide
the AD research community with a suite of powerful, accessible signal processing software tools that will
dramatically enhance the precision and quality of EEG-derived biomarkers related to AD progression.

## Key facts

- **NIH application ID:** 10739673
- **Project number:** 1R01AG079345-01A1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Patrick L. Purdon
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $1,303,780
- **Award type:** 1
- **Project period:** 2023-09-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10739673

## Citation

> US National Institutes of Health, RePORTER application 10739673, Advanced signal processing methods for neural data analysis to support development of brain dynamic biomarkers for research and clinical applications in patients with Alzheimer's and related dementias (1R01AG079345-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10739673. Licensed CC0.

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