# Measuring, Modeling, and Modulating Cross-Frequency Coupling

> **NIH NIH R01** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2020 · $330,898

## Abstract

PROJECT SUMMARY
Although rhythms are a prominent feature of brain activity, the role of rhythms in brain function (and
dysfunction) remains elusive. Rhythms have been proposed to organize information transfer within and
between brain regions by modulating neural excitability at different time scales. Rhythms have also been
proposed to interact across these different time scales, a phenomenon labeled cross-frequency coupling or
CFC. Clinical and experimental observations have identified many different types of CFC, such as coupling
between the phase of a low frequency rhythm and the amplitude of a high frequency rhythm (phase-amplitude
coupling), or between the phases of two different frequency rhythms (phase-phase coupling). Many functional
roles for CFC have been proposed, including in working memory, neuronal computation, communication,
learning and emotion. Despite the mounting experimental evidence for CFC, three important challenges
remain that limit understanding of this phenomenon. First, many different data analysis methods have been
developed to characterize CFC, with each method typically focused on one type of CFC. Choosing an
inappropriate method weakens statistical power and introduces opportunities for confounding effects. Second,
analysis of CFC typically occurs post hoc, prohibiting opportunities to modulate CFC during an experiment.
New methods are needed to assess CFC in real time while limiting the impacts of potential confounds. Third,
the mechanisms that produce CFC are not known. While computational models developed to explore these
mechanisms provide important insights, these models have been mainly restricted to synaptic mechanisms of
rhythm generation and associations between two types of rhythms. New models are needed to examine the
role of other rhythms and rhythm generating mechanisms in CFC. Inclusion of more realistic biological
features in simulations of neural rhythms facilitates exploration of a new challenge: how electrical stimulation
modulates CFC. In this project, an interdisciplinary research group consisting of a statistician, a
mathematician, and a psychiatrist-engineer will analyze, model, and modulate cross-frequency coupling. To
do so, the team will develop and apply a statistical inference framework suitable for real time analysis of CFC,
and apply this framework to analyze - and modulate with electrical stimulation - in vivo recordings from rat
cortex and subcortex. The team will also develop computational models of CFC, to link the observed data to
cellular mechanisms, and create hypotheses testable in the in vivo experiments. Completion of the proposed
research will represent a significant step forward toward a more complete understanding of cross-frequency
coupling, and toward a system for exploring and testing innovative methods for its modulation.

## Key facts

- **NIH application ID:** 10002222
- **Project number:** 5R01EB026938-03
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Uri Tzvi Eden
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $330,898
- **Award type:** 5
- **Project period:** 2018-09-20 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10002222

## Citation

> US National Institutes of Health, RePORTER application 10002222, Measuring, Modeling, and Modulating Cross-Frequency Coupling (5R01EB026938-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10002222. Licensed CC0.

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