Assessing fractality for empirical temporal signals with application to brain dynamics

Speaker: Andras Eke, Semmelweis University & Yale University

When: July 20, 2020 (Mon), 12:00PM to 01:00PM (add to my calendar)
Location: SCI 352
Hosted by: Plamen Ivanov

This event is part of the Biophysics Seminars. 12:30PM.

In my presentation I will provide a cross-section of the research efforts of my group in the field. Starting out with monofractality, I will talk about the need to establish a model-based framework with the central theme of signal classification (1,2,3), the need for testing the performance of data acquisition (using the exemplary case of functional magnetic resonance imaging blood oxygen level-dependent (fMRI-BOLD) signal)(4) and analytical tools (1-3). I will elaborate on our findings on fractal temporal correlation in cerebral hemodynamics in animal and human models using laser Doppler flowmetry, laser speckle contrast imaging, functional near-infrared spectroscopy (fNIRS) and fMRI-BOLD signals (5-9). Then I will continue with addressing the challenging aspects of assessing multifractality of commonly heterogeneous empirical signals by introducing our focus-based multifractal analytical approach and its adaptation to bimodal signals acquired in animal and human brain fMRI-BOLD and fNIRS data (10-12). I will conclude by discussing our most recent discovery of the true multifractality of dynamic functional connectivity metrics and their topology in the human brain using data from fNIRS and electroencephalography measurements (13-16).


  1. Eke, A., P. Herman, J. B. Bassingthwaighte, G. M. Raymond, D. B. Percival, M. Cannon, I. Balla and C. Ikrenyi (2000). "Physiological time series: distinguishing fractal noises from motions." Pflügers Archiv - European Journal of Physiology 439(4): 403-415.

  2. Eke, A., P. Herman, L. Kocsis and L. R. Kozak (2002). "Fractal characterization of complexity in temporal physiological signals." Physiological Measurement 23(1): R1-38.

  3. Hartmann, A., P. Mukli, Z. Nagy, L. Kocsis, P. Hermán and A. Eke (2013). "Real-time fractal signal processing in the time domain." Physica A: Statistical Mechanics and its Applications 392(1): 89-102.

  4. Eke, A., P. Herman, B. G. Sanganahalli, F. Hyder, P. Mukli and Z. Nagy (2012). "Pitfalls in fractal time series analysis: fMRI BOLD as an exemplary case." Frontiers in Fractal Physiology 3(417): 1-24.

  5. Eke, A. and P. Herman (1999). "Fractal analysis of spontaneous fluctuations in human cerebral hemoglobin content and its oxygenation level recorded by NIRS." Advances in Experimental Medicine and Biology 471: 49-55.

  6. Herman, P. and A. Eke (2006). "Nonlinear analysis of blood cell flux fluctuations in the rat brain cortex during stepwise hypotension challenge." Journal of Cerebral Blood Flow & Metabolism 26(9): 1189-1197.

  7. Herman, P., L. Kocsis and A. Eke (2009). Fractal Characterization of Complexity in Dynamic Signals: Application to Cerebral Hemodynamics. Methods in Molecular Biology, Humana Press. 489: 23-40.

  8. Herman, P., B. G. Sanganahalli, F. Hyder and A. Eke (2011). "Fractal analysis of spontaneous fluctuations of the BOLD signal in rat brain." NeuroImage 58: 1060-1069.

  9. Eke, A., P. Hermán and M. Hajnal (2006). "Fractal and noisy CBV dynamics in humans: influence of age and gender." Journal of Cerebral Blood Flow and Metabolism 26(7): 891-898.

  10. Mukli, P., Z. Nagy and A. Eke (2015). "Multifractal formalism by enforcing the universal behavior of scaling functions." Physica A: Statistical Mechanics and Its Applications 417: 150-167.

  11. Nagy, Z., P. Mukli, P. Herman and A. Eke (2017). "Decomposing multifractal crossovers." Frontiers in Physiology 8(533): 1-19.

  12. Mukli, P., Z. Nagy, F. S. Racz, P. Herman and A. Eke (2018). "Impact of Healthy Aging on Multifractal Hemodynamic Fluctuations in the Human Prefrontal Cortex." Frontiers in Physiology 9.

  13. Racz, F. S., P. Mukli, Z. Nagy and A. Eke (2017). "Increased prefrontal cortex connectivity during cognitive challenge assessed by fNIRS imaging." Biomedical Optics Express 8(8): 3842-3855.

  14. Racz, F. S., P. Mukli, Z. Nagy and A. Eke (2018). "Multifractal dynamics of resting-state functional connectivity in the prefrontal cortex." Physiological Measurement 39.

  15. Racz, F. S., O. Stylianou, P. Mukli and A. Eke (2018). "Multifractal dynamic functional connectivity in the resting-state brain." Frontiers in Physiology 9: 1704-1701-1718.

  16. Racz, F., O. Stylianou, P. Mukli and A. Eke (2019). "Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity." Scientific Reports 9: 13474.