EEG DIMENSIONAL COMPLEXITY MAPPING IN STROKE

2000 ◽  
Author(s):  
M. MOLNÁR ◽  
Z. NAGY ◽  
J. KENÉZ
1999 ◽  
Vol 13 (3) ◽  
pp. 163-172 ◽  
Author(s):  
R. Krug ◽  
M. Mölle ◽  
H.L. Fehm ◽  
J. Born

Abstract Previous studies have indicated: (1) peak performance on tests of divergent creative thinking during the ovulatory phase of the menstrual cycle; (2) compared to convergent analytical thinking, divergent thinking was found to be associated with a distinctly increased dimensional complexity of ongoing EEG activity. Based on these findings, we hypothesized that cortical information processing during the ovulatory phase is characterized by an increased EEG dimensionality. Each of 16 women was tested on 3 occasions: during the ovulatory phase, the luteal phase, and menses. Presence of the phases was confirmed by determination of plasma concentrations of estradiol, progesterone, and luteinizing hormone. The EEG was recorded while the women performed: (1) tasks of divergent thinking; (2) tasks of convergent thinking; and (3) during mental relaxation. In addition to EEG dimensional complexity, conventional spectral power analysis was performed. Behavioral data confirmed enhanced creative performance during the ovulatory phase while convergent thinking did not vary across cycle phases. EEG complexity was higher during divergent than convergent thought, but this difference remained unaffected by the menstrual phase. Influences of the menstrual phase on EEG activity were most obvious during mental relaxation. In this condition, women during the ovulatory phase displayed highest EEG dimensionality as compared with the other cycle phases, with this effect being most prominent over the central and parietal cortex. Concurrently, power within the alpha frequency band as well as theta power at frontal and parietal leads were lower during the luteal than ovulatory phase. EEG results indicate that task demands of thinking overrode effects of menstrual cycle. However, with a less demanding situation, an ovulatory increase in EEG dimensionality became prominent suggesting a loosening of associative habits during this phase.


1997 ◽  
Vol 68 (2-3) ◽  
pp. 182
Author(s):  
B. Weber ◽  
T. Dierks ◽  
W.K. Strik ◽  
K. Maurer

2001 ◽  
Vol 24 (5) ◽  
pp. 823-824 ◽  
Author(s):  
Márk Molnár

We discuss whether low-dimensional chaos and even nonlinear processes can be traced in the electrical activity of the brain. Experimental data show that the dimensional complexity of the EEG decreases during event-related potentials associated with cognitive effort. This probably represents increased nonlinear cooperation between different neural systems during sensory information processing.


2005 ◽  
Vol 67 ◽  
pp. 297-305 ◽  
Author(s):  
Shan Tong ◽  
Hua Huang ◽  
Ju Luan ◽  
Huaiqing Chen

2001 ◽  
Vol 11 (01) ◽  
pp. 19-26 ◽  
Author(s):  
RAY BROWN ◽  
ROBERT BEREZDIVIN ◽  
LEON O. CHUA

In this paper we show how to relate a form of high-dimensional complexity to chaotic and other types of dynamical systems. The derivation shows how "near-chaotic" complexity can arise without the presence of homoclinic tangles or positive Lyapunov exponents. The relationship we derive follows from the observation that the elements of invariant finite integer lattices of high-dimensional dynamical systems can, themselves, be viewed as single integers rather than coordinates of a point in n-space. From this observation it is possible to construct high-dimensional dynamical systems which have properties of shifts but for which there is no conventional topological conjugacy to a shift. The particular manner in which the shift appears in high-dimensional dynamical systems suggests that some forms of complexity arise from the presence of chaotic dynamics which are obscured by the large dimensionality of the system domain.


1992 ◽  
Vol 15 ◽  
pp. 567B
Author(s):  
D. Lehmann ◽  
C. M. Michel ◽  
J. Wackermann

1996 ◽  
Vol 06 (02) ◽  
pp. 267-278 ◽  
Author(s):  
N. BIRBAUMER ◽  
W. LUTZENBERGER ◽  
H. RAU ◽  
C. BRAUN ◽  
G. MAYER-KRESS

The nonlinear resonance hypothesis of music perception was tested in an experiment comparing a group of musically sophisticated and a group of less sophisticated subjects. The prediction that weakly chaotic music entrains less complex brain wave (EEG) oscillations at the prefrontal cortex was confirmed by using a correlational dimension algorithm. Strongly chaotic (stochastic) and periodic music both stimulated higher brain wave complexity. More sophisticated subjects who prefer classical music showed higher EEG dimensions while less sophisticated subjects responded with a drop in brain wave complexity to rhythmical weakly chaotic music. Subjects ratings of perceived complexity of the musical pieces followed mathematical (objective) structure of the music and did not reflect the changes in brain wave complexity. The results are interpreted in the context of an associated (Hebbian) network theory of nonlinear brain dynamics.


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