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Electrocorticography (ECoG) or intracranial electroencephalography (iEEG) monitors electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery when paired with numerical…

Intracranial EEG (iEEG) is the gold standard technique for epileptogenic zone (EZ) localisation, but requires a hypothesis of which tissue is epileptogenic, guided by qualitative analysis of seizure semiology and other imaging modalities…

The electroencephalography (EEG) forward problem, the computation of the electric potential generated by a known electric current source configuration in the brain, is a key step of EEG source analysis. In this problem, it is often desired…

Medical Physics · Physics 2019-03-28 Axelle Pillain , Lyes Rahmouni , Francesco Andriulli

Intracranial electrocorticography (ECoG) offers high-signal-to-noise access to cortical activity for brain-computer interfaces, yet limited per-patient data has led most prior work to rely on small, subject-specific decoders that neglect…

Artificial Intelligence · Computer Science 2026-05-12 Liuyin Yang , Qiang Sun , Bob Van Dyck , Eva Calvo Merino , Marc M. Van Hulle

Intracranial EEG (IEEG) is used for 2 main purposes, to determine: (1) if epileptic networks are amenable to focal treatment and (2) where to intervene. Currently these questions are answered qualitatively and sometimes differently across…

We propose an approach and the numerical algorithm for pre-processing of the electroencephalography (EEG) data, enabling to generate an accurate mapping of the potential from the measurement area - scalp - to the brain surface. The…

Neurons and Cognition · Quantitative Biology 2019-07-03 Nikolay Koshev , Nikolay Yavich , Mikhail Malovichko , Ekaterina Skidchenko , Maxim Fedorov

Electroencephalography (EEG) and Magnetoencephalography (MEG) are pivotal in understanding brain activity but are limited by their poor spatial resolution. EEG/MEG source imaging (ESI) infers the high-resolution electric field distribution…

Signal Processing · Electrical Eng. & Systems 2024-02-01 Song Wang , Chen Wei , Kexin Lou , Dongfeng Gu , Quanying Liu

Electroencephalography (EEG) has become one of the key modalities underpinning brain-computer interfaces (BCIs) due to its high temporal resolution, rapid responsiveness, non-invasiveness, low cost, and portability. However, EEG signals are…

Neurons and Cognition · Quantitative Biology 2026-04-17 Yihang Dong , Changhong Jing , Shuqiang Wang

Solving the electroencephalography (EEG) forward problem is a fundamental step in a wide range of applications including biomedical imaging techniques based on inverse source localization. State-of-the-art electromagnetic solvers resort to…

Computational Physics · Physics 2020-04-22 Maxime Y. Monin , Lyes Rahmouni , Adrien Merlini , Francesco P. Andriulli

Electroencephalography (EEG) is a neuroimaging technique that records brain neural activity with high temporal resolution. Unlike other methods, EEG does not require prohibitively expensive equipment and can be easily set up using…

Human-Computer Interaction · Computer Science 2024-10-01 Arash Akbarinia

Predicting post-operative seizure freedom using functional correlation networks derived from interictal intracranial EEG has shown some success. However, there are important challenges to consider. 1: electrodes physically closer to each…

A significant challenge in the electroencephalogram EEG lies in the fact that current data representations involve multiple electrode signals, resulting in data redundancy and dominant lead information. However extensive research conducted…

Signal Processing · Electrical Eng. & Systems 2024-07-31 Huyen Ngo , Khoi Do , Duong Nguyen , Viet Dung Nguyen , Lan Dang

Classification of electroencephalogram (EEG) and electrocorticogram (ECoG) signals obtained during motor imagery (MI) has substantial application potential, including for communication assistance and rehabilitation support for patients with…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Shuntaro Suzuki , Shunya Nagashima , Masayuki Hirata , Komei Sugiura

In recent years, multiple noninvasive imaging modalities have been used to develop a better understanding of the human brain functionality, including positron emission tomography, single-photon emission computed tomography, and functional…

Signal Processing · Electrical Eng. & Systems 2019-10-18 Shiva Asadzadeh , Tohid Yousefi Rezaii , Soosan Beheshti , Azra Delpak , Saeed Meshgini

To minimize functional morbidity associated with brain surgery, new preventive approaches (also referred to as "prehabilitation") by using motor-imagery-based computer interfaces (MI-BCIs) can be utilized. To achieve successful MI-BCI…

Neurons and Cognition · Quantitative Biology 2017-08-03 Milena Korostenskaja , Christoph Kapeller , Ki H Lee , Christoph Guger , James Baumgartner , Eduardo M. Castillo

Epilepsy is a highly prevalent brain condition with many serious complications arising from it. The majority of patients which present to a clinic and undergo electroencephalogram (EEG) monitoring would be unlikely to experience seizures…

Signal Processing · Electrical Eng. & Systems 2023-12-14 Matthew McDougall , Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

Bioelectric source analysis in the human brain from scalp electroencephalography (EEG) signals is sensitive to the conductivity of the different head tissues. Conductivity values are subject dependent, so non-invasive methods for…

Computational Engineering, Finance, and Science · Computer Science 2019-08-30 Kostiantyn Maksymenko , Maureen Clerc , Théodore Papadopoulo

Accurate localization of brain regions responsible for language and cognitive functions in Epilepsy patients should be carefully determined prior to surgery. Electrocorticography (ECoG)-based Real Time Functional Mapping (RTFM) has been…

Neurons and Cognition · Quantitative Biology 2017-08-08 Harish RaviPrakash , Milena Korostenskaja , Eduardo Castillo , Ki Lee , James Baumgartner , Ulas Bagci

We study source localization from high dimensional M/EEG data by extending a multiscale method based on Entropic inference devised to increase the spatial resolution of inverse problems. This method is used to construct informative prior…

Quantitative Methods · Quantitative Biology 2015-02-13 Leonardo S. Barbosa , Nestor Caticha

The presence of interictal epileptiform discharges (IEDs) in electroencephalogram (EEG) recordings is a critical biomarker of epilepsy. Even trained neurologists find detecting IEDs difficult, leading many practitioners to turn to machine…

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