Quantifying Phase- Amplitude Modulation in Neural Data

Victoria Subritzky-Katz, Aaron L. Sampson, Erik Emeric, Witold Lipski, Sophia Moreira-Gonzalez, Jorge Gonzalez-Martinez, Sridevi Sarma, Veit Stuphorn, Ernst Niebur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Phase-amplitude modulation (the modulation of the amplitude of higher frequency oscillations by the phase of lower frequency oscillations) is a specific type of cross-frequency coupling that has been observed in neural recordings from multiple species in a range of behavioral contexts. Given its potential importance, care must be taken with how it is measured and quantified. Previous studies have quantified phase-amplitude modulation by measuring the distance of the amplitude distribution from a uniform distribution. While this method is of general applicability, it is not targeted to the specific modulation pattern frequently observed with low-frequency oscillations. Here we develop a new method that has increased specificity to detect modulation in the sinusoidal shape commonly observed in neural data.

Original languageEnglish (US)
Title of host publication2023 57th Annual Conference on Information Sciences and Systems, CISS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665451819
DOIs
StatePublished - 2023
Event57th Annual Conference on Information Sciences and Systems, CISS 2023 - Baltimore, United States
Duration: Mar 22 2023Mar 24 2023

Publication series

Name2023 57th Annual Conference on Information Sciences and Systems, CISS 2023

Conference

Conference57th Annual Conference on Information Sciences and Systems, CISS 2023
Country/TerritoryUnited States
CityBaltimore
Period3/22/233/24/23

Keywords

  • ECoG
  • EEG
  • cross-frequency coupling
  • phase-amplitude modulation
  • sEEG

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Artificial Intelligence
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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