Measurement of correlations between brain regions (functional connectivity) using blood
oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the …

Granger causality has long been a prominent method for inferring causal interactions
between stochastic variables for a broad range of complex physical systems. However, it …

Interictal epileptiform discharges (spikes, IEDs) are electrographic markers of epileptic tissue
and their quantification is utilized in planning of surgical resection. Visual analysis of long …

Often, while analyzing naturally generated signals (such as speech, seismogram,
electroencephalogram, etc.), questions of stationarity and Gaussianity (normality) arise. This …

The ability to predict seizures may enable patients with epilepsy to better manage their
medications and activities, potentially reducing side effects and improving quality of life …

This paper describes a novel on-line learning approach for radial basis function (RBF)
neural network. Based on an RBF network with individually tunable nodes and a fixed small …

Recent advances in computational modeling techniques have facilitated a more nuanced
understanding of sleep neural dynamics across the lifespan. In this study, we tensorize …

Objective: Nonlinear modeling of cortical responses (EEG) to wrist perturbations allows for
the quantification of cortical sensorimotor function in healthy and neurologically impaired …

The mental workload (MWL) classification is a critical problem for quantitative assessment
and analysis of operator functional state in many safety-critical situations with indispensable …

One of the greatest challenges in data mining is related to processing and analysis of
massive data streams. Contrary to traditional static data mining problems, data streams …