# Assessment of Cognitive Impairment Syndromes using Automated, Dynamical Analyses of Physiologic Signals

> **NIH NIH R01** · BETH ISRAEL DEACONESS MEDICAL CENTER · 2021 · $437,500

## Abstract

Risk assessment for cognitive impairment syndromes, culminating in Alzheimer's disease and related
dementias, is the major public health priority addressed by this special notice supplement to our ongoing
NIBIB-sponsored PhysioNet project, “Resource for Complex Physiologic Signals.” A key motivating knowledge
gap is the lack of reliable, quantitative and non-invasive methods that complement expensive brain imaging
technologies and semi-quantitative functional tests, as well as emerging biochemical probes. An important
insight into the pathophysiology of cognitive impairment syndromes derives from increasing evidence linking
central nervous system (CNS) dysfunction to alterations in the function of other organ systems including the
regulation of the heartbeat. A major focus of PhysioNet has been on the development and dissemination of
open source algorithms quantifying information encoded in the dynamics of physiologic signals. We have
developed widely used tools such as multiscale entropy, cardiopulmonary coupling and, more recently, heart
rate fragmentation, along with the physiologic frameworks that support their applications. However, the
potential value of these tools in assessing and predicting cognitive decline have yet to be established in large
studies. We now propose to quantify the value of dynamical metrics of relevant physiologic signals in this
context. We focus on heart rate, respiration and electroencephalographic (EEG) fluctuations and their
interactions, using data from the Multi-Ethnic Study of Atherosclerosis (MESA, ongoing), the Sleep Heart
Health Study (SHHS) and the Osteoporotic Fractures (MrOS). In preliminary MESA analyses, we find
significant associations between altered measures of heart rate dynamics and cognitive decline. We also find
that participants with the dynamical heart rate signature of central sleep apnea have a significantly higher risk
of experiencing cognitive decline over the same period. Specifically, our working hypotheses are that higher
heart rate fragmentation, lower multiscale heart rate complexity, higher amounts of low-frequency
cardiopulmonary coupling and lower multiscale complexity of EEG are associated with decreased cognitive
performance, greater cognitive decline and more incident dementia. We will pursue hypothesized links
between neuroautonomic dysfunction and cognitive impairment by means of the following specific aims: 1) in
cross-sectional analyses of MESA, quantify the associations of EEG- and ECG-derived dynamical indices with
standard measures of cognitive function; 2) in prospective analysis of MESA, quantify the associations of EEG
and ECG-derived dynamical indices with: i) standard measures of cognitive function; ii) changes in cognitive
function measures, and iii) incident dementia; and 3) validate the findings in the SHHS and MrOS cohorts. The
proposed analyses directly align with the NIH strategic objective to develop new, noninvasive ways of
detecting, predicting, and monitorin...

## Key facts

- **NIH application ID:** 10284942
- **Project number:** 3R01EB030362-14S1
- **Recipient organization:** BETH ISRAEL DEACONESS MEDICAL CENTER
- **Principal Investigator:** Ary Louis Goldberger
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $437,500
- **Award type:** 3
- **Project period:** 2007-09-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10284942

## Citation

> US National Institutes of Health, RePORTER application 10284942, Assessment of Cognitive Impairment Syndromes using Automated, Dynamical Analyses of Physiologic Signals (3R01EB030362-14S1). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10284942. Licensed CC0.

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