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. RESULTS: Neuropsychological status was highly correlated with posterior alpha (8-15 Hz) EEG activity in a complex way, with both positive and negative correlations at lower and higher alpha frequency sub-bands for each cognitive task in a pattern that depends on the specific cognitive task. In addition, the theta/beta ratio was a specific but insensitive indicator of ADHD status in children with epilepsy; most children both with and without epilepsy have normal theta/beta ratios. The spike count showed no correlations with neuropsychological status. CONCLUSIONS: (1) The alpha rhythm may have at least two sub-bands which serve different purposes. (2) The theta/beta ratio is not a sensitive indicator of ADHD status in children with epilepsy. (3) The EEG frequency spectrum correlates more robustly with neuropsychological status than spike count analysis in children with idiopathic epilepsy. SIGNIFICANCE: (1) The role of posterior alpha rhythms in cognition is complex and can be overlooked if EEG spectral resolution is too coarse or if neuropsychological status is assessed too narrowly. (2) ADHD in children with idiopathic epilepsy may involve different mechanisms from those in children without epilepsy. (3) Reliable correlations with neuropsychological status require longer EEG samples when using spike count analysis than when using frequency spectra.

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. The data power spectral density is found to give better time and frequency resolution than the more conventional total energy measure, and additionally shows intricate time-frequency structure in the rat that is altered in association with the emergence of epilepsy. With epileptogenesis, the baseline theta oscillation is severely degraded and is absorbed into a broader gamma band. There are also broad 600 Hz and 2000 Hz bands which localize to hippocampal layers that are distinct from those of the theta and gamma bands. The 600 Hz band decreases in prominence with epileptogenesis while the 2000 Hz band increases in prominence. The origins of these high frequency bands await further study. In general, we find that the damped-oscillator pseudo-wavelet is easy to use and is particularly suitable for problems where a wide range of oscillator frequencies is expected.

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. The macroscopic properties can be extracted from experimental data by one of two possible variational principles. These variational principles are our principal contribution to the formalism. Potential applications are discussed, including applications to the theory of critical phenomena in the brain, Granger causality and Kalman filters.PACS code: 87.19.lj.

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. We hypothesize that epilepsy arises as an abnormal learned response of such a system to certain repeated provocations. This response is a network-level effect. If epilepsy really is a learned response, then it should be possible to reverse it, that is, to unlearn epilepsy. Unlearning epilepsy may then provide a new approach to its treatment.

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. We present a simple stochastic computational Hebbian learning model that incorporates both firing rate and critical homeostasis, and we explore its stability and connectivity properties. We also examine the behavior of our model with a simulated seizure and with simulated acute deafferentation. We argue that a neural system that is more highly connected than the critical state (i.e., one that is "supercritical") is epileptogenic. Based on our simulations, we predict that the postseizural and postdeafferentation states should be supercritical and epileptogenic. Furthermore, interventions that boost spontaneous activity should be protective against epileptogenesis.