Cart (Loading....) | Create Account
Close category search window
 

Rhythmogram-Based Analysis for Continuous Electrographic Data of the Human Brain

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ioannides, A.A. ; Lab. for Human Brain Dynamics, AAI Sci. Cultural Services Ltd., Nicosia, Cyprus ; Sargsyan, A.

Ecologically relevant stimuli are rarely used in scientific studies because they are difficult to control. Instead, researchers employ simple stimuli with sharp boundaries (in space and time). Here, we explore how the rhythmogram can be used to provide much needed rigorous control of natural continuous stimuli like music and speech. The analysis correlates important features in the time course of stimuli with corresponding features in brain activations elicited by the same stimuli. Correlating the identified regularities of the stimulus time course with the features extracted from the activations of each voxel of a tomographic analysis of brain activity provides a powerful view of how different brain regions are influenced by the stimulus at different times and over different (user-selected) timescales. The application of the analysis to tomographic solutions extracted from magnetoencephalographic data recorded while subjects listen to music reveals a surprising and aesthetically pleasing aspect of brain function: an area believed to be specialized for visual processing is recruited to analyze the music after the acoustic signal is transformed to a feature map. The methodology is ideal for exploring processing of complex stimuli, e.g., linguistic structure and meaning and how it fails, for example, in developmental dyslexia.

Published in:

Information Technology in Biomedicine, IEEE Transactions on  (Volume:16 ,  Issue: 2 )

Date of Publication:

March 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.