D Velis | PubMed Health

PubMed2004

Electrical brain-stimulation paradigm for estimating the seizure onset site and the time to ictal transition in temporal lobe epilepsy.

OBJECTIVE: To explore and validate a novel stimulation and analysis paradigm proposed to monitor spatial distribution and temporal changes of the excitability state in patients with temporal lobe epilepsy (TLE). METHODS: We use intermittent pulse stimulation in the frequency range 10-20Hz. A quantitative measure of spectral phase de-modulation, the relative phase clustering index (rPCI) was applied to the evoked EEG signals, measured from electrodes implanted in the hippocampal formation. RESULTS: We found that in the interictal periods, high values of rPCI recorded from specific sites were correlated with the most probable seizure onset sites (SOS). Furthermore we found that high values of rPCI from certain locations correlated with shorter time intervals to the next seizure. CONCLUSIONS: Our clinical findings indicate that although the precise moment of ictal transitions is in general unpredictable, it may be possible to estimate the probability of occurrence of some epileptic seizures. SIGNIFICANCE: The use of the rPCI for probabilistic forecasting of upcoming epileptic seizures is warranted. rPCI measurements may be used to guide interventions with the aim of modifying local tissue excitability that ultimately might prevent ictal transitions.

Brain Mapping↗

PubMed1997

Alpha rhythms: noise, dynamics and models.

Alpha rhythms appear as sinusoidal-like oscillations in the electroencephalogram (EEG) within the frequency range 8-12 Hz that waxe and wane in a more or less irregular way. The irregularity may have various origins. It may be due to noise or the oscillations may have an intrinsic irregular character, e.g. they may be generated by chaotic processes [Jansen (1991) Quantitative analysis of electroencephalograms: is there chaos in the future? Int. J. Biomed. Comput., 27: 95-123; Pradham, N. and Dutt, D.N. (1993) A nonlinear perspective in understanding the neurodynamics of EEG. Comput. Biol. Med., 23: 425-442; Pritchard et al. (1995) Dimensional analysis of resting human EEG II: Surrogate-data testing indicates nonlinearily but not low-dimensional chaos. Psychophysiology. 32: 486]. The term noise is often used in neurophysiology with different connotations as pointed out by Bullock (1990), either meaning an unwanted signal from the point of view of the receiver of a message, or a signal with intrinsic random fluctuations, i.e. with a stochastic character. Here we consider noise in this sense, as random or quasi-random neural activity. In this overview, we concentrate on the question of whether alpha rhythms should be considered generated in neuronal networks (1) as forms of filtered noise, (2) as deterministic oscillations influenced by noise or (3) as the result of chaotic dynamics. A clear answer to this question can have theoretical value because it may lead to a general model of the generation of this important EEG signal. Such a model, of course, would be a macroscopic one, since it would primarily account for the properties of the alpha rhythms at the neuronal network level. A translation of these properties to the microscopic, i.e. neuronal, level will not be easy to achieve without more direct knowledge of the membrane and synaptic basic properties of the neurons involved. Here we consider the question formulated above by presenting some relevant experimental evidence and theoretical arguments. The consideration whether alpha rhythms may have noise or chaotic sources implies examining how and where such sources can occur in the neuronal networks of the brain. Therefore we present, first, some basic data regarding the possible origin of noise and of chaos in neuronal networks. Second, the signal analysis methods that have to be applied in order to discriminate between filtered noise activities and chaotic oscillations are introduced. Third, the implications of these signal analyses regarding the possible answer to the initial question are discussed.

Alpha Rhythm↗