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Magnetic resonance imaging (MRI) is a crucial tool to identify brain abnormalities in a wide range of neurological disorders. In focal epilepsy MRI is used to identify structural cerebral abnormalities. For covert lesions, machine learning…

Epileptic seizures are characterized by abnormal and excessive neural activity, where cortical network dynamics seem to become unstable. However, most of the time, during seizure-free periods, cortex of epilepsy patients shows perfectly…

Neurons and Cognition · Quantitative Biology 2021-04-06 Annika Hagemann , Jens Wilting , Bita Samimizad , Florian Mormann , Viola Priesemann

This paper presents an efficient binarized algorithm for both learning and classification of human epileptic seizures from intracranial electroencephalography (iEEG). The algorithm combines local binary patterns with brain-inspired…

Signal Processing · Electrical Eng. & Systems 2018-09-10 Alessio Burrello , Kaspar Schindler , Luca Benini , Abbas Rahimi

Medically uncontrolled epileptic seizures affect nearly 15 million people worldwide, resulting in enormous economic and psychological burdens. Treatment of medically refractory epilepsy is essential for patients to achieve remission,…

Quantitative Methods · Quantitative Biology 2025-12-25 Yaoyue Wang , Arian Ashourvan , Guilherme Ramos , Paul Bogdan , Emily Pereira

Electroencephalogram (EEG) is a common tool used to understand brain activities. The data are typically obtained by placing electrodes at the surface of the scalp and recording the oscillations of currents passing through the electrodes.…

Signal Processing · Electrical Eng. & Systems 2021-02-19 Eddy Kwessi , Lloyd Edwards

Intracranial recordings in epilepsy patients are increasingly utilized to gain insight into the electrophysiological mechanisms of human cognition. There are currently several practical limitations to conducting research with these…

Neurons and Cognition · Quantitative Biology 2021-06-23 Omer E Ashmaig , Liberty S Hamilton , Pradeep Modur , Robert J Buchanan , Alison R Preston , Andrew J Watrous

Epilepsy is a chronic neurological disorder affecting 1\% of people worldwide, deep learning (DL) algorithms-based electroencephalograph (EEG) analysis provides the possibility for accurate epileptic seizure (ES) prediction, thereby…

Signal Processing · Electrical Eng. & Systems 2022-05-10 Yankun Xu , Jie Yang , Mohamad Sawan

Epilepsy is one of the most common neurological disorders, affecting about 1% of the population at all ages. Detecting the development of epilepsy, i.e., epileptogenesis (EPG), before any seizures occur could allow for early interventions…

Machine Learning · Computer Science 2020-06-18 Diyuan Lu , Sebastian Bauer , Valentin Neubert , Lara Sophie Costard , Felix Rosenow , Jochen Triesch

Epilepsy, affecting approximately 50 million people globally, is characterized by abnormal brain activity and remains challenging to treat. The diagnosis of epilepsy relies heavily on electroencephalogram (EEG) data, where specialists…

We analyze the connectivity structure of weighted brain networks extracted from spontaneous magnetoencephalographic (MEG) signals of healthy subjects and epileptic patients (suffering from absence seizures) recorded at rest. We find that,…

Data Analysis, Statistics and Probability · Physics 2011-01-21 M. Chavez , M. Valencia , V. Navarro , V. Latora , J. Martinerie

We consider the electrical signals recorded from a subdural array of electrodes placed on the pial surface of the brain for chronic evaluation of epileptic patients before surgical resection. A simple and computationally fast method to…

Medical Physics · Physics 2007-11-18 Eshel Ben-Jacob , Stefano Boccaletti , Anna Pomyalov , Itamar Procaccia , Vernon L. Towle

Pathophysiolpgical modelling of brain systems from microscale to macroscale remains difficult in group comparisons partly because of the infeasibility of modelling the interactions of thousands of neurons at the scales involved. Here, to…

Neurons and Cognition · Quantitative Biology 2026-01-30 Kang You , Gary Green , Jian Zhang

Epileptic seizures are neurological disorders characterized by abnormal and excessive electrical activity in the brain, resulting in recurrent seizure events. Electroencephalogram (EEG) signals are widely used for seizure diagnosis due to…

Machine Learning · Computer Science 2026-04-02 Ferdaus Anam Jibon , Fazlul Hasan Siddiqui , F. Deeba , Gahangir Hossain

Over 15 million epilepsy patients worldwide do not respond to drugs and require surgical treatment. Successful surgical treatment requires complete removal, or disconnection of the epileptogenic zone (EZ), but without a prospective…

Machine Learning · Computer Science 2022-02-16 Adam Li , Chester Huynh

Objective: Identifying abnormalities in interictal intracranial EEG, by comparing patient data to a normative map, has shown promise for the localisation of epileptogenic tissue and prediction of outcome. The approach typically uses short…

Epileptic seizures are transient neurological events characterized by abnormal and excessive neuron activity in the brain, which are often associated with measurable disturbances in the cardiovascular system. Traditionally,…

Signal Processing · Electrical Eng. & Systems 2026-05-20 Mohammad Reza Chopannavaz , Foad Ghaderi

Predicting seizure freedom is essential for tailoring epilepsy treatment. But accurate prediction remains challenging with traditional methods, especially with diverse patient populations. This study developed a deep learning-based graph…

Importance: Many individuals with drug-resistant epilepsy continue to have seizures after resective surgery. Accurate identification of focal brain abnormalities is essential for successful neurosurgical intervention. Current clinical…

Epileptic seizure forecasting, combined with the delivery of preventative therapies, holds the potential to greatly improve the quality of life for epilepsy patients and their caregivers. Forecasting seizures could prevent some potentially…

Signal Processing · Electrical Eng. & Systems 2020-05-18 Nhan Duy Truong , Yikai Yang , Christina Maher , Armin Nikpour , Omid Kavehei

Brain function emerges from coordinated activity across anatomically connected regions, where structural connectivity (SC) -- the network of white matter pathways - provides the physical substrate for functional connectivity (FC) -- the…

Neurons and Cognition · Quantitative Biology 2025-07-09 Sam Frank Kelemen , Joaquín Gõni , Sérgio Pequito , Arian Ashourvan