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Neuromodulation techniques have emerged as promising approaches for treating a wide range of neurological disorders, precisely delivering electrical stimulation to modulate abnormal neuronal activity. While leveraging the unique…

The electrical stimulation to the seizure onset zone (SOZ) serves as an efficient approach to seizure suppression. Recently, seizure dynamics have gained widespread attendance in its network propagation mechanisms. Compared with the direct…

Neurons and Cognition · Quantitative Biology 2024-06-17 Zhichao Liang , Guanyi Zhao , Yinuo Zhang , Weiting Sun , Jingzhe Lin , Jialin Wang , Quanying Liu

Mental disorders may exhibit pathological brain rhythms and neurostimulation promises to alleviate of patients' symptoms by modifying these rhythms. Today, most neurostimulation schemes are open-loop, i.e. administer experimental…

Neurons and Cognition · Quantitative Biology 2023-03-21 Thomas Wahl , Michel Duprez , Axel Hutt

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…

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements. Epileptic seizure detection methods involve neurological…

Constructing electronic models of neurons has several applications including reproducing dynamics of biological neurons and their networks and neuroprosthetics. In the brain, most neurons themselves are in a non-oscillatory mode, and brain…

Adaptation and Self-Organizing Systems · Physics 2023-05-09 Nikita M. Egorov , Marina V. Sysoeva , Vladimir I. Ponomarenko , Ilya V. Sysoev

To improve the understanding of human gait and to facilitate novel developments in gait rehabilitation, the neural correlates of human gait as measured by means of non-invasive electroencephalography (EEG) have been investigated recently.…

Neurons and Cognition · Quantitative Biology 2020-03-03 Cornelia Herbert , Jan Nachtsheim , Michael Munz

Objectives: This study examines human Photoplethysmogram (PPG) along with Electrocardiogram (ECG) signals to study cardiac autonomic imbalance in epileptic seizures. The significance and the prevalence of changes in PPG morphological…

Signal Processing · Electrical Eng. & Systems 2019-12-12 Seyede Mahya Safavi , Ninaz Valisharifabad , Robert Sabino , Hsinchung Chen , Ali HeydariGorji , Demi Tran , Jack Lin , Beth Lopour , Pai H. Chou

Epilepsy is the fourth most common neurological disorder, affecting about 1% of the population at all ages. As many as 60% of people with epilepsy experience focal seizures which originate in a certain brain area and are limited to part of…

Machine Learning · Computer Science 2019-03-20 Diyuan Lu , Jochen Triesch

Epilepsy is the fourth most common neurological disorder and affects people of all ages worldwide. Deep Brain Stimulation (DBS) has emerged as an alternative treatment option when anti-epileptic drugs or resective surgery cannot lead to…

Image and Video Processing · Electrical Eng. & Systems 2022-01-27 Han Liu , Kathryn L. Holloway , Dario J. Englot , Benoit M. Dawant

An implanted device for brain-responsive neurostimulation (RNS System) is approved as an effective treatment to reduce seizures in adults with medically-refractory focal epilepsy. Clinical trials of the RNS System demonstrate…

Neurons and Cognition · Quantitative Biology 2021-02-22 Sharon Chiang , Ankit N. Khambhati , Emily T. Wang , Marina Vannucci , Edward F. Chang , Vikram R. Rao

Epilepsy is a prevalent neurological disorder marked by sudden, brief episodes of excessive neuronal activity caused by abnormal electrical discharges, which may lead to some mental disorders. Most existing deep learning methods for…

Machine Learning · Computer Science 2025-10-16 Zexin Wang , Lin Shi , Haoyu Wu , Junru Luo , Xiangzeng Kong , Jun Qi

Seizure type identification is essential for the treatment and management of epileptic patients. However, it is a difficult process known to be time consuming and labor intensive. Automated diagnosis systems, with the advancement of machine…

Signal Processing · Electrical Eng. & Systems 2023-03-09 Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

Epileptic seizures are one of the most crucial neurological disorders, and their early diagnosis will help the clinicians to provide accurate treatment for the patients. The electroencephalogram (EEG) signals are widely used for epileptic…

An epileptic seizure is a transient event of abnormal excessive neuronal discharge in the brain. This unwanted event can be obstructed by detection of electrical changes in the brain that happen before the seizure takes place. The automatic…

Machine Learning · Computer Science 2016-04-29 Z. Roshan Zamir

Temporal-lobe epilepsy in humans is often associated with widespread, synchronized neuron firing that co-occurs with traveling waves in local field potential. These traveling waves generate stochastic oscillations in a time series of…

Neurons and Cognition · Quantitative Biology 2023-01-18 Francois A. Marshall

A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its…

Real time seizure detection is a fundamental problem in computational neuroscience towards diagnosis and treatment's improvement of epileptic disease. We propose a real-time computational method for tracking and detection of epileptic…

Quantitative Methods · Quantitative Biology 2024-06-17 Ximena Fernández , Diego Mateos

Epilepsy is a neurological disorder that affects normal neural activity. These electrical activities can be recorded as signals containing information about the brain known as Electroencephalography (EEG) signals. Analysis of the EEG…

Signal Processing · Electrical Eng. & Systems 2025-07-10 Fatemeh Valipour , Zahra Valipour , Mani Garousi , Ali Khadem

Temporal correlations in the brain are thought to have very dichotomic roles. On one hand they are ubiquitously present in the healthy brain and are thought to underlie feature binding during information processing. On the other hand large…

Biological Physics · Physics 2009-11-10 Bethany Percha , Rhonda Dzakpasu , Michał Żochowski
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