Correlation of EEG with neuropsychological status in children with epilepsy.

Objective: To determine correlations of the EEG frequency spectrum with neuropsychological status in children with idiopathic epilepsy.

Methods: Forty-six children ages 8-18 years old with idiopathic epilepsy were retrospectively identified and analyzed for correlations between EEG spectra and neuropsychological status using multivariate linear regression. In addition, the theta/beta ratio, which has been suggested as a clinically useful EEG marker of attention-deficit hyperactivity disorder (ADHD), and an EEG spike count were calculated for each subject.

Time-frequency analysis using damped-oscillator pseudo-wavelets: Application to electrophysiological recordings.

The damped-oscillator pseudo-wavelet is presented as a method of time-frequency analysis along with a new spectral density measure, the data power. An instantaneous phase can be defined for this pseudo-wavelet, and it is easily inverted. The data power measure is tested on both computer generated data and in vivo intrahippocampal electrophysiological recordings from a rat.

Zwanzig-Mori projection operators and EEG dynamics: deriving a simple equation of motion.

We present a macroscopic theory of electroencephalogram (EEG) dynamics based on the laws of motion that govern atomic and molecular motion. The theory is an application of Zwanzig-Mori projection operators. The result is a simple equation of motion that has the form of a generalized Langevin equation (GLE), which requires knowledge only of macroscopic properties.

An open hypothesis: is epilepsy learned, and can it be unlearned?

Plasticity is central to the ability of a neural system to learn and also to its ability to develop spontaneous seizures. What is the connection between the two? Learning itself is known to be a destabilizing process at the algorithmic level. We have investigated necessary constraints on a spontaneously active Hebbian learning system and find that the ability to learn appears to confer an intrinsic vulnerability to epileptogenesis on that system.

Simple spontaneously active Hebbian learning model: homeostasis of activity and connectivity, and consequences for learning and epileptogenesis.

A spontaneously active neural system that is capable of continual learning should also be capable of homeostasis of both firing rate and connectivity. Experimental evidence suggests that both types of homeostasis exist, and that connectivity is maintained at a state that is optimal for information transmission and storage. This state is referred to as the critical state.