Published December 1, 2017 | Version v1
Journal article

A robust statistical framework for instantaneous electroencephalogram phase and frequency estimation and analysis

  • 1. School of Electrical and Computer Engineering, Shiraz University, Shiraz (Iran, Islamic Republic of)

Description

Objective: The instantaneous phase (IP) and instantaneous frequency (IF) of the electroencephalogram (EEG) are considered as notable complements for the EEG spectrum. The calculation of these parameters commonly includes narrow-band filtering, followed by the calculation of the signal's analytical form. The calculation of the IP and IF is highly susceptible to the filter parameters and background noise level, especially in low analytical signal amplitudes. The objective of this study is to propose a robust statistical framework for EEG IP/IF estimation and analysis. Approach: Herein, a Monte Carlo estimation scheme is proposed for the robust estimation of the EEG IP and IF. It is proposed that any EEG phase-related inference should be reported as an average with confidence intervals obtained by repeating the IP and IF estimation under infinitesimal variations (selected by an expert), in algorithmic parameters such as the filter's bandwidth, center frequency and background noise level. In the second part of the paper, a stochastic model consisting of the superposition of narrow-band foreground and background EEG is used to derive analytically probability density functions of the instantaneous envelope (IE) and IP of EEG signals, which justify the proposed Monte Carlo scheme. Main results: The instantaneous analytical envelope of the EEG, which has been empirically used in previous studies, is shown to have a fundamental impact on the accuracy of the EEG phase contents. It is rigorously shown that the IP/IF estimation quality highly depends on the IE and any phase/frequency interpretations in low IE are statistically unreliable and require a hypothesis test. Significance: The impact of the proposed method on previous studies, including time-domain phase synchrony, phase resetting, phase locking value and phase amplitude coupling are studied with examples. The findings of this research can set forth new standards for EEG phase/frequency estimation and analysis techniques. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1361-6579/aa93a1

Additional details

Identifiers

Publishing Information

Journal Title
Physiological Measurement (Print)
Journal Volume
38
Journal Issue
12
Journal Page Range
p. 2141-2163
ISSN
0967-3334

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
51084048
Subject category
S60: APPLIED LIFE SCIENCES;
Descriptors DEI
BACKGROUND NOISE; HYPOTHESIS; MONTE CARLO METHOD; PROBABILITY DENSITY FUNCTIONS; STOCHASTIC PROCESSES
Descriptors DEC
CALCULATION METHODS; FUNCTIONS; NOISE