scholarly journals Simulating Epileptic Seizures using the Bidomain Model

2021 ◽  
Author(s):  
Jakob Schreiner ◽  
Kent-Andre Mardal
Keyword(s):  
Power Law ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Patient Specific ◽  
Normal Brain ◽  
Bidomain Model ◽  
Power Law Distribution ◽  
Whole Brain ◽  
Power Law Exponent ◽  
Electric Potentials

Abstract Epileptic seizures are due to excessive and synchronous neural activity. Extensive modelling of seizures has been done on the neuronal level, but it remains a challenge to scale these models up to whole brain models. Measurements of the brain’s activity over several spatiotemporal scales follow a power-law distribution in terms of frequency. During normal brain activity, the power-law exponent is often found to be around 2 for frequencies between a few Hz and up to 150 Hz, but is higher during seizures and for higher frequencies. The Bidomain model has been used with success in modelling the electrical activity of the heart, but has been explored far less in the context of the brain. This study extends previous models of epileptic seizures on the neuronal level to the whole brain using the Bidomain model. Our approach is evaluated in terms of power-law distributions. The electric potentials were simulated in 7 idealized 2D models and 3 MRI-derived 3D patient-specific models. Computed electric potentials were found to follow power-law distribtions with slopes ranging from 2 to 5 for frequencies greater than 10-30 Hz.

Empirical Analysis on Human Dynamics of QQ Group Communication

2014 ◽  
Vol 998-999 ◽  
pp. 1146-1150
Author(s):  
Rui Tian ◽  
Xu Han ◽  
Wen Jun Wang
Keyword(s):  
Power Law ◽  
Time Distribution ◽  
Group Communication ◽  
Communication Tool ◽  
Power Law Distribution ◽  
Human Dynamics ◽  
Event Time ◽  
Human Interactions ◽  
Power Law Exponent ◽  
Individual Human

The understanding of the temporal patterns of individual human interactions is essential in explaining many characteristics of human behavior. The instant communication tool QQ is developing rapidly on the network in recent years. Based on the QQ group communication records provided by some volunteers, this paper investigates the statistics of the inter-event intervals between two consecutive messages. The result shows that they follow power-law distribution. And there are obvious positive correlation between the activity of QQ group and the power-law exponent of inter-event time distribution. In further study, we find that the distribution displays a strong bursty property yet weak memory effects, then we analysis the distribution of the number of events in a bursty period.

scholarly journals A pan-cancer signature of neutral tumor evolution

2015 ◽  
Author(s):  
Andrea Sottoriva ◽  
Trevor Graham
Keyword(s):  
Power Law ◽  
Large Scale ◽  
Evolutionary Dynamics ◽  
Genomic Data ◽  
Next Generation Sequencing Data ◽  
Patient Specific ◽  
Tumor Evolution ◽  
Sequencing Data ◽  
Power Law Distribution ◽  
Multiple Tumor

Despite extraordinary efforts to profile cancer genomes on a large scale, interpreting the vast amount of genomic data in the light of cancer evolution and in a clinically relevant manner remains challenging. Here we demonstrate that cancer next-generation sequencing data is dominated by the signature of growth governed by a power-law distribution of mutant allele frequencies. The power-law signature is common to multiple tumor types and is a consequence of the effectively-neutral evolutionary dynamics that underpin the evolution of a large proportion of cancers, giving rise to the abundance of mutations responsible for intra-tumor heterogeneity. Importantly, the law allows the measurement, in each individual cancer, of the in vivo mutation rate and the timing of mutations with remarkable precision. This result provides a new way to interpret cancer genomic data by considering the physics of tumor growth in a way that is both patient-specific and clinically relevant.

Epileptic Seizure Detection and Classification Using Machine Learning

2019 ◽  
pp. 152-164
Author(s):  
Rekh Ram Janghel ◽  
Yogesh Kumar Rathore ◽  
Gautam Tatiparti
Keyword(s):  
Brain Activity ◽  
Epileptic Seizures ◽  
Seizure Detection ◽  
The United States ◽  
Normal Brain ◽  
Great Success ◽  
Ann Models ◽  
Recognition Systems ◽  
The Brain

Epilepsy is a brain ailment identified by unpredictable interruptions of normal brain activity. Around 1% of mankind experience epileptic seizures. Around 10% of the United States population experiences at least a single seizure in their life. Epilepsy is distinguished by the tendency of the brain to generate unexpected bursts of unusual electrical activity that disrupts the normal functioning of the brain. As seizures usually occur rarely and are unforeseeable, seizure recognition systems are recommended for seizure detection during long-term electroencephalography (EEG). In this chapter, ANN models, namely, BPA, RNN, CL, PNN, and LVQ, have been implemented. A prominent dataset was employed to assess the proposed method. The proposed method is capable of achieving an accuracy of 97.5%; the high accuracy obtained has confirmed the great success of the method.

scholarly journals Spatiotemporal distributions of icebergs in a temperate fjord: Columbia Fjord, Alaska

2019 ◽  
Vol 13 (7) ◽  
pp. 1785-1799 ◽  
Author(s):  
Sarah U. Neuhaus ◽  
Slawek M. Tulaczyk ◽  
Carolyn Branecky Begeman
Keyword(s):  
Surface Area ◽  
Power Law ◽  
Vertical Mixing ◽  
Heat Content ◽  
Back Stress ◽  
Late Winter ◽  
Power Law Distribution ◽  
Cross Sectional ◽  
Power Law Exponent ◽  
Pixel Brightness

Abstract. Much of the world's ice enters the ocean via outlet glaciers terminating in fjords. Inside fjords, icebergs may affect glacier–ocean interactions by cooling incoming ocean waters, enhancing vertical mixing, or providing back stress on the terminus. However, relatively few studies have been performed on iceberg dynamics inside fjords, particularly outside of Greenland. We examine icebergs calved from Columbia Glacier, Alaska, over 8 months spanning late winter to mid-fall using 0.5 m resolution satellite imagery, identifying icebergs based on pixel brightness. Iceberg sizes fit a power-law distribution with an overall power-law exponent, m, of -1.26±0.05. Seasonal variations in the power-law exponent indicate that brittle fracture of icebergs is more prevalent in the summer months. Combining our results with those from previous studies of iceberg distributions, we find that iceberg calving rate, rather than water temperature, appears to be the major control on the exponent value. We also analyze icebergs' spatial distribution inside the fjord and find that large icebergs (10 000–100 000 m2 cross-sectional area) have low spatial correlation with icebergs of smaller sizes due to their tendency to ground on shallow regions. We estimate the surface area of icebergs in contact with incoming seawater to be 3.0±0.63×104 m2. Given the much larger surface area of the terminus, 9.7±3.7×105 m2, ocean interactions with the terminus may have a larger impact on ocean heat content than interactions with icebergs.

scholarly journals Power law statistics of force and acoustic emission from a slowly penetrated granular bed

2014 ◽  
Vol 21 (1) ◽  
pp. 1-8 ◽  
Author(s):  
K. Matsuyama ◽  
H. Katsuragi
Keyword(s):  
Acoustic Emission ◽  
Power Law ◽  
Glass Bead ◽  
Power Laws ◽  
Solid Sphere ◽  
Granular Bed ◽  
Power Law Distribution ◽  
Energy Scaling ◽  
Power Law Exponent ◽  
Ae Signal

Abstract. Penetration-resistant force and acoustic emission (AE) from a plunged granular bed are experimentally investigated through their power law distribution forms. An AE sensor is buried in a glass bead bed. Then, the bed is slowly penetrated by a solid sphere. During the penetration, the resistant force exerted on the sphere and the AE signal are measured. The resistant force shows power law relation to the penetration depth. The power law exponent is independent of the penetration speed, while it seems to depend on the container's size. For the AE signal, we find that the size distribution of AE events obeys power laws. The power law exponent depends on grain size. Using the energy scaling, the experimentally observed power law exponents are discussed and compared to the Gutenberg–Richter (GR) law.

scholarly journals Magnetoencephalography: Fundamentals and Established and Emerging Clinical Applications in Radiology

2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Sven Braeutigam
Keyword(s):  
Pervasive Developmental Disorders ◽  
Developmental Disorders ◽  
Brain Activity ◽  
Analytical Techniques ◽  
Epileptic Seizures ◽  
Clinical Applications ◽  
Patient Treatment ◽  
Normal Brain ◽  
Clinical Tool ◽  
Wide Range

Magnetoencephalography is a noninvasive, fast, and patient friendly technique for recording brain activity. It is increasingly available and is regarded as one of the most modern imaging tools available to radiologists. The dominant clinical use of this technology currently centers on two, partly overlapping areas, namely, localizing the regions from which epileptic seizures originate, and identifying regions of normal brain function in patients preparing to undergo brain surgery. As a consequence, many radiologists may not yet be familiar with this technique. This review provides an introduction to magnetoencephalography, discusses relevant analytical techniques, and presents recent developments in established and emerging clinical applications such as pervasive developmental disorders. Although the role of magnetoencephalography in diagnosis, prognosis, and patient treatment is still limited, it is argued that this technology is exquisitely capable of contributing indispensable information about brain dynamics not easily obtained with other modalities. This, it is believed, will make this technology an important clinical tool for a wide range of disorders in the future.

scholarly journals Vibration Analysis of Post-buckled Fluid-conveying Functionally Graded Pipe

2020 ◽  
Author(s):  
Abdellatif Selmi
Keyword(s):  
Power Law ◽  
Fluid Velocity ◽  
Functionally Graded ◽  
Pipe Material ◽  
Power Law Distribution ◽  
Initial Tension ◽  
Various Boundary Conditions ◽  
Power Law Exponent ◽  
Graded Material ◽  
Post Buckling

Abstract The vibration of post - buckl ed fluid - conveying pipe made of functionally graded material is analyzed . The pipe material properties are assumed to be graded in the thickness dire ction according to power - law distribution. A n exact solution is obtained for the post - buckling deformation of the fluid - conveying functionally graded pipe with various boundary conditions. T he linear vibration problem is solved around the first buckled con figuration and t he natural frequencies of the three lowest vibration modes are obtained. The influences of power - law exponent, initial tension, fluid density and fluid velocity on the static deflection and free vibration frequencies are studied.

scholarly journals A personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mauro. F. Pinto ◽  
Adriana Leal ◽  
Fábio Lopes ◽  
António Dourado ◽  
Pedro Martins ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Brain Activity ◽  
Patient Specific ◽  
Normal Brain ◽  
Seizure Prediction ◽  
Optimization Strategy ◽  
Computationally Efficient ◽  
High Stake ◽  
Time Dependencies ◽  
Drug Resistant Epilepsy

AbstractSeizure prediction may improve the quality of life of patients suffering from drug-resistant epilepsy, which accounts for about 30% of the total epileptic patients. The pre-ictal period determination, characterized by a transitional stage between normal brain activity and seizure, is a critical step. Past approaches failed to attain real-world applicability due to lack of generalization capacity. More recently, deep learning techniques may outperform traditional classifiers and handle time dependencies. However, despite the existing efforts for providing interpretable insights, clinicians may not be willing to make high-stake decisions based on them. Furthermore, a disadvantageous aspect of the more usual seizure prediction pipeline is its modularity and significant independence between stages. An alternative could be the construction of a search algorithm that, while considering pipeline stages’ synergy, fine-tunes the selection of a reduced set of features that are widely used in the literature and computationally efficient. With extracranial recordings from 19 patients suffering from temporal-lobe seizures, we developed a patient-specific evolutionary optimization strategy, aiming to generate the optimal set of features for seizure prediction with a logistic regression classifier, which was tested prospectively in a total of 49 seizures and 710 h of continuous recording and performed above chance for 32% of patients, using a surrogate predictor. These results demonstrate the hypothesis of pre-ictal period identification without the loss of interpretability, which may help understanding brain dynamics leading to seizures and improve prediction algorithms.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

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