Modulation of the fractal properties of low frequency endogenous brain oscillations in functional MRI by a working memory task

Anna Barnes*, Garry Honey, Alle Meije Wink, Edward T. Bullmore, John Suckling

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


Fractals - signals that display scale-invariant behaviour - are ubiquitous in nature including a wide variety of physiological processes. Fractal analysis of blood oxygen level dependent (BOLD) time-series of fMRI acquisitions from the brain can be achieved by decomposing the data Into a hierarchy of temporal scales so that although the signal may well be irregular and contain singularities, the properties of these singularities are constant in time and the entire series can be characterised by a single scaling exponent: the Hurst exponent, H. The observation that a signal has a noninteger fractal dimension suggests that the generating system is complex and has the potential to adapt to a wide variety of challenges. In contrast, the emergence of white noise or, alternatively, signal periodicity can be seen as degradation of fractal complexity and hence, maladaptivity. We tested the hypothesis that exogenous stimuli affects fractal signal properties In the context of brain function by manipulating the cognitive demand of a working memory task and using H as a summary measure of signal complexity. We show that this stimulus has a significant effect on H estimated from resting data acquired immediately before and after the task, and that the degree of change is related to cognitive load.

Original languageEnglish
Title of host publication2008 International Joint Conference on Neural Networks, IJCNN 2008
Number of pages4
Publication statusPublished - 24 Nov 2008
Event2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, China
Duration: 1 Jun 20088 Jun 2008

Publication series

NameProceedings of the International Joint Conference on Neural Networks


Conference2008 International Joint Conference on Neural Networks, IJCNN 2008
CityHong Kong

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