Interictal functional connectivity in focal refractory epilepsies investigated by intracranial EEG

S Lagarde, CG Bénar, F Wendling, F Bartolomei - Brain connectivity, 2022 - liebertpub.com
Introduction: Focal epilepsies are diseases of neuronal excitability affecting macroscopic
networks of cortical and subcortical neural structures. These networks (“epileptogenic …

Brain–computer interface (BCI) applications in mapping of epileptic brain networks based on intracranial-EEG: An update

R Alkawadri - Frontiers in neuroscience, 2019 - frontiersin.org
The main applications of the Brain–Computer Interface (BCI) have been in the domain of
rehabilitation, control of prosthetics, and in neuro-feedback. Only a few clinical applications …

Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

M Goodfellow, C Rummel, E Abela, MP Richardson… - Scientific reports, 2016 - nature.com
Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant
post-operative improvements are not always attained. This is due in part to our incomplete …

Virtual intracranial EEG signals reconstructed from MEG with potential for epilepsy surgery

M Cao, D Galvis, SJ Vogrin, WP Woods… - Nature …, 2022 - nature.com
Modelling the interactions that arise from neural dynamics in seizure genesis is challenging
but important in the effort to improve the success of epilepsy surgery. Dynamical network …

One-shot learning for iEEG seizure detection using end-to-end binary operations: Local binary patterns with hyperdimensional computing

A Burrello, K Schindler, L Benini… - 2018 IEEE Biomedical …, 2018 - ieeexplore.ieee.org
This paper presents an efficient binarized algorithm for both learning and classification of
human epileptic seizures from intracranial electroencephalography (iEEG). The algorithm …

Association of cortical stimulation–induced seizure with surgical outcome in patients with focal drug-resistant epilepsy

CC Oderiz, N von Ellenrieder, F Dubeau… - JAMA …, 2019 - jamanetwork.com
Importance Cortical stimulation is used during presurgical epilepsy evaluation for functional
mapping and for defining the cortical area responsible for seizure generation. Despite wide …

Hyperdimensional computing with local binary patterns: One-shot learning of seizure onset and identification of ictogenic brain regions using short-time iEEG …

A Burrello, K Schindler, L Benini… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Objective: We develop a fast learning algorithm combining symbolic dynamics and brain-
inspired hyperdimensional computing for both seizure onset detection and identification of …

An ensemble of hyperdimensional classifiers: Hardware-friendly short-latency seizure detection with automatic iEEG electrode selection

A Burrello, S Benatti, K Schindler… - IEEE journal of …, 2020 - ieeexplore.ieee.org
We propose a new algorithm for detecting epileptic seizures. Our algorithm first extracts
three features, namely mean amplitude, line length, and local binary patterns that are fed to …

An optimal strategy for epilepsy surgery: Disruption of the rich-club?

MA Lopes, MP Richardson, E Abela… - PLoS computational …, 2017 - journals.plos.org
Surgery is a therapeutic option for people with epilepsy whose seizures are not controlled by
anti-epilepsy drugs. In pre-surgical planning, an array of data modalities, often including …

[HTML][HTML] MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses

L Tait, J Zhang - NeuroImage, 2022 - Elsevier
EEG microstate analysis is an approach to study brain states and their fast transitions in
healthy cognition and disease. A key limitation of conventional microstate analysis is that it …