Coincident frequencies and relative phases among brain activity and hormonal signals
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BioMed Central
Open Access
Methodology
Coincident frequencies and relative phases among brain activity and hormonal signals Silvia Solís-Ortíz1, Rafael G Campos2, Julián Félix3 and Octavio Obregón*3 Address: 1Departamento de Ciencias Médicas, División de Ciencias de la Salud, Campus León, Universidad de Guanajuato, León 37320, Guanajuato, México, 2Facultad de Ciencias Físico-Matemáticas, Universidad Michoacana, Morelia, 58060, Michoacán, México and 3Departamento de Física, División de Ciencias e Ingenierías, Campus León, Universidad de Guanajuato, León 37150, Guanajuato, México Email: Silvia Solís-Ortíz - [email protected]; Rafael G Campos - [email protected]; Julián Félix - [email protected]; Octavio Obregón* - [email protected] * Corresponding author
Published: 14 March 2009 Behavioral and Brain Functions 2009, 5:18
doi:10.1186/1744-9081-5-18
Received: 13 October 2008 Accepted: 14 March 2009
This article is available from: http://www.behavioralandbrainfunctions.com/content/5/1/18 © 2009 Solís-Ortíz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract Background: Fourier transform is a basic tool for analyzing biological signals and is computed for a finite sequence of data sample. The electroencephalographic (EEG) signals analyzed with this method provide only information based on the frequency range, for short periods. In some cases, for long periods it can be useful to know whether EEG signals coincide or have a relative phase between them or with other biological signals. Some studies have evidenced that sex hormones and EEG signals show oscillations in their frequencies across a period of 28 days; so it seems of relevance to seek after possible patterns relating EEG signals and endogenous sex hormones, assumed as long time-periodic functions to determine their typical periods, frequencies and relative phases. Methods: In this work we propose a method that can be used to analyze brain signals and hormonal levels and obtain frequencies and relative phases among them. This method involves the application of a discrete Fourier Transform on previously reported datasets of absolute power of brain signals delta, theta, alpha1, alpha2, beta1 and beta2 and the endogenous estrogen and progesterone levels along 28 days. Results: Applying the proposed method to exemplary datasets and comparing each brain signal with both sex hormones signals, we found a characteristic profile of coincident periods and typical relative phases. For the corresponding coincident periods the progesterone seems to be essentially in phase with theta, alpha1, alpha2 and beta1, while delta and beta2 go oppositely. For the relevant coincident periods, the estrogen goes in phase with delta and theta and goes oppositely with alpha2. Conclusion: Findings suggest th
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