With the advancement in artificial intelligence (AI) and machine learning (ML) techniques,
researchers are striving towards employing these techniques for advancing clinical practice …

Epilepsy has been historically seen as a functional brain disorder associated with excessive
synchronization of large neuronal populations leading to a hypersynchronous state. Recent …

Electroencephalogram (EEG) signals contain vital information on the electrical activities of
the brain and are widely used to aid epilepsy analysis. A challenging element of epilepsy …

Epilepsy is a neurological disorder characterized by the presence of recurring seizures. Like
many other neurological disorders, epilepsy can be assessed by the electroencephalogram …

One of the central questions in neuroscience is how communication in the brain is organized
under normal conditions and how this architecture breaks down in neurological disease. It …

Many complex and interesting phenomena in nature are due to nonlinear phenomena. The
theory of nonlinear dynamical systems, also called 'chaos theory', has now progressed to a …

The sudden and apparently unpredictable nature of seizures is one of the most disabling
aspects of the disease epilepsy. A method capable of predicting the occurrence of seizures …

Multivariate time series analysis is extensively used in neurophysiology with the aim of
studying the relationship between simultaneously recorded signals. Recently, advances on …

Today, neuroimaging techniques are frequently used to investigate the integration of
functionally specialized brain regions in a network. Functional connectivity, which quantifies …

Recent research has investigated the possibility of predicting epileptic seizures. Intervention
before the onset of seizure manifestations could be envisioned with accurate seizure …