Fractal Dimension of EEG Activity Senses Neuronal Impairment in Acute Stroke

Zappasodi, Filippo; Olejarczyk, Elżbieta; Marzetti, Laura; Assenza, Giovanni; Pizzella, Vittorio; Tecchio, Franca

doi:10.1371/journal.pone.0100199

Cited by 135 publications

(96 citation statements)

References 83 publications

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“…The time-variability properties of the EEG signals could instead have an organized complex structure, reflecting non-linear characteristics of the system that are deeply linked to the underlying organ functioning [23]. Indeed, fractal nature of a signal has often been used to quantify the topological and functional complexity of processes generating that signal [23].…”

Section: Discussionmentioning

confidence: 99%

A Minimal Spanning Tree Analysis of EEG Responses to Complex Visual Stimuli

Antonakakis

Zervakis

Tsirka

et al. 2014

2014 IEEE 26th International Conference on Tools With Artificial Intelligence

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Human brain is the most complicated network and its functional mechanism is a demanding concept in neuroscience research. Graph theory and forms an interesting tool for modeling the brain interactions and estimated brain parameters. In this paper, we consider synchronization features for modeling brain operations in electroencephalogram (EEG) responses to kanizsa and fractal stimuli, using minimal spanning tree (MST) on a network of phase synchronization EEG channels. Graphs of phasesynchronization activity and MST structures are computed using these graphs. The proposed approach yields evidence that the fractal stimuli generate stronger energy response and synchronization of theta band in occipital lobe.

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Section: Discussionmentioning

confidence: 99%

A Minimal Spanning Tree Analysis of EEG Responses to Complex Visual Stimuli

Antonakakis

Zervakis

Tsirka

et al. 2014

2014 IEEE 26th International Conference on Tools With Artificial Intelligence

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“…A reduction in complexity may be an indication of neural activity moving away from a fractal dynamic. A study based on the complexity of EEG activity in stroke patients showed a decrease in fractal dimension for patients with lesions in the left or right hemispheres of the brain during the acute phase of stroke [140]. The lower fractal dimension was more noticeable in the affected area.…”

Section: Fractal Dynamics In Physiological Systemsmentioning

confidence: 99%

“…Several studies have found a decreased or abnormal complexity in the EEG activity of other various mental ailments including depression [138] [139], brain lesions due to stroke [140], schizophrenia [138] [141], and Alzheimer's disease [142] [143]. A reduction in complexity may be an indication of neural activity moving away from a fractal dynamic.…”

Section: Fractal Dynamics In Physiological Systemsmentioning

confidence: 99%

Stimulation Therapies and the Relevance of Fractal Dynamics to the Treatment of Diseases

Cheng¹,

Law²,

Kwan³

et al. 2014

OJRM

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This paper provides an overview of the conventional therapeutic stimulation methodologies and proposes a more effective stimulation approach based on a consideration of the inherently fractal nature of normal biological dynamics. There are varying forms of physiological stimulations including the use of electrical currents, electromagnetic fields, temperature change, ultrasound, light and so forth. These stimulation therapies can be categorized into three main modalities: electrical stimulation modalities, thermal modalities, and non-thermal modalities. Electrical stimulation modalities include therapeutic techniques where electrical current is directly applied to the body of treated subject. Direct application of electrical current to the brain also falls under this category. Thermal modalities consist of stimulations that induce temperature change on the body for therapeutic effects without the direct transfer of electrical current. Non-thermal modalities functions through energy transfer without directly applying electrical current and without the effects of temperature change. A fourth miscellaneous category for stimulation techniques consists of the stimulation effects of music along with physical stimulation as in massage therapy. Common to most of these therapeutic strategies is that the stimulation is delivered at certain fixed periods or frequencies. We introduce some rudiments of fractal dynamics, and the notions of self-similarity, scale-invariance, and long-range correlation or memory in the dynamics of a system. We present evidence that fractal dynamics is commonly observed in healthy physiological systems while unhealthy systems are shown to veer away from fractal dynamics towards periodic or random motion. This difference in dynamics can be observed in many biological signals such as in neural activity, heart rate variations, and breathing patterns. We propose that an optimal stimulation technique should thus be one that encourages an unhealthy, non-fractal pathological system * Corresponding author. W. Cheng et al. 74towards a healthy, fractal dynamic. Given the ubiquity of fractality in healthy biological dynamics, we argue that a fractal pattern of stimulation is a more optimal approach to functional restoration than the widely used conventional periodic stimulation, which may further consolidate the existing pathological dynamics.

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“…During years different works have been reported in literatures which focused on analysis of neurophysiological time series using fractal theories [1][2][3][4][5][6][7][8][9][10]. In a recent work on prediction of epileptic seizure onset we proposed a new methodology which is based on studying the EEG signals using two measures, the Hurst exponent and fractal dimension.…”

Section: Hamidreza Namazimentioning

confidence: 99%

Fractal Based Analysis, Modeling and Prediction of Neurophysiological Time Series

2016

ARC Journal of Neuroscience

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Neurophysiology is a branch of physiology and neuroscience that is concerned with the study of the functioning of the nervous system. Neurophysiological time series are signal shaped time series which are governed from different processes that are related to nervous system. The most important neurophysiological time series which is directly related to the activity of the nervous system is the EEG signal. Besides EEG time series there are some other neurophysiological signals which are indirectly related to the activity of the nervous system. For instance, the respiratory signal is another type of neurophysiological time series which is governed from the process of the nervous system. In fact, ventilation occurs under the control of the autonomic nervous system from the medulla oblongata and the pons in the brainstem. These areas of the brain form the respiration regulatory center, a series of interconnected brain cells within the lower and middle brain stem which coordinate respiratory movements. We can call other types of neurophysiological time series such as fixational eye movements time series, etc. Analysis, modeling and prediction of neurophysiological time series always have been an important issue between researchers. One of the most important aspects of these modeling and analysis has been from mathematical point of view. In fact, using mathematics for the modeling purpose helps scientists to investigate precisely about the processes. Employing mathematical models can help them in forecasting the processes in the next step where the biological modeling cannot help. Fractals are scale-invariant geometric objects. A scale invariant object can be self-similar or selfaffine. A self-similar object is a union of rescaled copies of itself which is isotropic or uniform in all directions. But in case of self-affine objects, the mechanism is an isotropic or dependent on the direction. Regular fractals have higher self-similarity, but random fractals have a weaker selfsimilarity. The class of regular fractals includes many familiar simple objects, such as line intervals, solid squares, and solid cubes, and also many irregular objects. The scaling rules are characterized by "scaling exponents" (dimension). "Simple" regular fractals have integer scaling dimensions. Complex self-similar objects have non-integer dimension. Therefore, it is completely incorrect to define fractals as geometric objects having "fractional" (non-integer) dimension. Fractals maybe defined as geometric objects whose scaling exponent (dimension) satisfies the Szpilrajn inequality:ℵ ≥ (1) where ℵ is the scaling exponent (dimension) of the object and is its topological dimension, i.e., Euclidean dimension of units from which the fractal object is built. For example, in case of Brownian motion: the path of a particle, a line of dimension one, traveling for a long time over a plane region, eventually covers the entire plane, an entity of dimension two. In case of multi fractal system a single fractal dimension cannot describe its dynamics. In thi...

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Fractal Dimension of EEG Activity Senses Neuronal Impairment in Acute Stroke

Cited by 135 publications

References 83 publications

A Minimal Spanning Tree Analysis of EEG Responses to Complex Visual Stimuli

A Minimal Spanning Tree Analysis of EEG Responses to Complex Visual Stimuli

Stimulation Therapies and the Relevance of Fractal Dynamics to the Treatment of Diseases

Fractal Based Analysis, Modeling and Prediction of Neurophysiological Time Series

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