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VERSION:2.0
PRODID:-//RLASKEY//CALENDEROUS//EN
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METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260918T153339Z
LAST-MODIFIED:20200128T145036Z
DTSTART:20200720T160000Z
DTEND:20200720T170000Z
UID:event2278@bu.edu
URL:http://physics.bu.edu/internal/events/show/2278
SUMMARY:Assessing fractality for empirical temporal signals with applicatio
	n to brain dynamics
DESCRIPTION:Featuring Andras Eke\, Semmelweis University & Yale University\
	nHosted by: Plamen Ivanov\n\nPart of the Biophysics Seminars.\n\nIn my pres
	entation 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 nee
	d to establish a model-based framework with the central theme of signal cla
	ssification (1\,2\,3)\, the need for testing the performance of data acquis
	ition (using the exemplary case of functional magnetic resonance imaging bl
	ood oxygen level-dependent (fMRI-BOLD) signal)(4) and analytical tools (1-3
	). I will elaborate on our findings on fractal temporal correlation in cere
	bral hemodynamics in animal and human models using laser Doppler flowmetry\
	, laser speckle contrast imaging\, functional near-infrared spectroscopy (f
	NIRS) 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 a
	pproach 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 m
	ost recent discovery of the true multifractality of dynamic functional conn
	ectivity metrics and their topology in the human brain using data from fNIR
	S and electroencephalography measurements (13-16).\n\nReferences:\n\n1. 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 Jo
	urnal of Physiology 439(4): 403-415.\n\n2. Eke\, A.\, P. Herman\, L. Kocsis
	 and L. R. Kozak (2002). "Fractal characterization of complexity in tempora
	l physiological signals." Physiological Measurement 23(1): R1-38.\n\n3. Har
	tmann\, A.\, P. Mukli\, Z. Nagy\, L. Kocsis\, P. Hermán and A. Eke (2013).
	 "Real-time fractal signal processing in the time domain." Physica A: Stati
	stical Mechanics and its Applications 392(1): 89-102.\n\n4. Eke\, A.\, P. H
	erman\, B. G. Sanganahalli\, F. Hyder\, P. Mukli and Z. Nagy (2012). "Pitfa
	lls in fractal time series analysis: fMRI BOLD as an exemplary case." Front
	iers in Fractal Physiology 3(417): 1-24.\n\n5. Eke\, A. and P. Herman (1999
	). "Fractal analysis of spontaneous fluctuations in human cerebral hemoglob
	in content and its oxygenation level recorded by NIRS." Advances in Experim
	ental Medicine and Biology 471: 49-55.\n\n6. Herman\, P. and A. Eke (2006).
	 "Nonlinear analysis of blood cell flux fluctuations in the rat brain corte
	x during stepwise hypotension challenge." Journal of Cerebral Blood Flow & 
	Metabolism 26(9): 1189-1197.\n\n7. Herman\, P.\, L. Kocsis and A. Eke (2009
	). Fractal Characterization of Complexity in Dynamic Signals: Application t
	o Cerebral Hemodynamics. Methods in Molecular Biology\, Humana Press. 489: 
	23-40.\n\n8. Herman\, P.\, B. G. Sanganahalli\, F. Hyder and A. Eke (2011).
	 "Fractal analysis of spontaneous fluctuations of the BOLD signal in rat br
	ain." NeuroImage 58: 1060-1069.\n\n9. Eke\, A.\, P. Hermán and M. Hajnal (
	2006). "Fractal and noisy CBV dynamics in humans: influence of age and gend
	er." Journal of Cerebral Blood Flow and Metabolism 26(7): 891-898.\n\n10. M
	ukli\, P.\, Z. Nagy and A. Eke (2015). "Multifractal formalism by enforcing
	 the universal behavior of scaling functions." Physica A: Statistical Mecha
	nics and Its Applications 417: 150-167.\n\n11. Nagy\, Z.\, P. Mukli\, P. He
	rman and A. Eke (2017). "Decomposing multifractal crossovers." Frontiers in
	 Physiology 8(533): 1-19.\n\n12. Mukli\, P.\, Z. Nagy\, F. S. Racz\, P. Her
	man and A. Eke (2018). "Impact of Healthy Aging on Multifractal Hemodynamic
	 Fluctuations in the Human Prefrontal Cortex." Frontiers in Physiology 9.\n
	\n13. Racz\, F. S.\, P. Mukli\, Z. Nagy and A. Eke (2017). "Increased prefr
	ontal cortex connectivity during cognitive challenge assessed by fNIRS imag
	ing." Biomedical Optics Express 8(8): 3842-3855.\n\n14. Racz\, F. S.\, P. M
	ukli\, Z. Nagy and A. Eke (2018). "Multifractal dynamics of resting-state f
	unctional connectivity in the prefrontal cortex." Physiological Measurement
	 39.\n\n15. Racz\, F. S.\, O. Stylianou\, P. Mukli and A. Eke (2018). "Mult
	ifractal dynamic functional connectivity in the resting-state brain." Front
	iers in Physiology 9: 1704-1701-1718.\n\n16. Racz\, F.\, O. Stylianou\, P. 
	Mukli and A. Eke (2019). "Multifractal and entropy analysis of resting-stat
	e electroencephalography reveals spatial organization in local dynamic func
	tional connectivity." Scientific Reports 9: 13474.
LOCATION:SCI 352\, 590 Commonwealth Avenue\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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