Biomedical subjects

Robert Savit

Publications and source records attributed to Robert Savit.

4 recordsLinked to original sources

PubMed2005

Seizure anticipation, states of consciousness and marginal predictability in temporal lobe epilepsy.

PURPOSE: It has recently been shown that differences between the marginal predictability associated with scalp electrodes adjacent to and remote from the site of a seizure focus are able to distinguish between epochs temporally distant from and just prior to (within about 20 min) the onset of a seizure in patients with temporal lobe epilepsy. The purpose of this paper is to show that these differences of marginal predictability intervals are independent of the state of consciousness of the patient. METHODS: We have studied a data set encompassing 33 preictal epochs (within 1 h prior to a seizure) and 61 interictal epochs (defined as at least 1 h away from any seizure) from 14 patients. Each 30 s interval of each epoch was categorized into one of seven different states of consciousness. Statistical models were used to search for relationships (in aggregated data) between the values of differences of marginal predictabilities and state of consciousness. RESULTS: It was not possible to reject the null hypothesis of no relationship between differences of marginal predictabilities and state of consciousness. CONCLUSIONS: The values of the differences between marginal predictabilities on aggregated data are apparently insensitive to the state of consciousness. This conclusion, coupled with the fact that the differences between marginal predictabilities do depend on time to seizure, suggests the potential utility of these measures as the basis for ambulatory, non-invasive methods of seizure anticipation. However, the development of a practical non-invasive method for seizure anticipation requires further extensive study on disaggregated data from individual patients.

Adolescent↗

PubMed2003

Seizure prediction using scalp electroencephalogram.

Using a measure of nonlinear dynamical changes we term marginal predictability, we report evidence of robust changes in this parameter on scalp EEG in a cohort of patients with medically refractory mesiobasal temporal lobe epilepsy (MBTLE). In the baseline (interictal) state there are distinct differences in this nonlinear measure between epileptic and neurologically normal subjects. At baseline, in patients with MBTLE there are differences in these measures between electrodes adjacent to the ictal onset zone and more remotely placed electrodes. The character of these differences evolves over a period of approximately 30 min before a seizure. We discuss and integrate our findings with two emerging concepts in epileptology, first, the concept of a preictal or transition phase rather than an abrupt movement from interictal to ictal activity, and second, the notion of an epileptic neural network with changes in areas of brain remote from what has traditionally been considered the ictal onset zone influencing "ictogenesis."

Adolescent↗

PubMed2003

Non-linear, non-invasive method for seizure anticipation in focal epilepsy.

In this paper we discuss an approach, using methods of non-linear time series analysis applied to scalp electrode recordings, which is able to distinguish between epochs temporally distant from and just prior to, the onset of a seizure in patients with temporal lobe epilepsy. The method involves a comparison of recordings taken from electrodes adjacent to and remote from the site of ictal onset. In particular, we define a non-linear quantity which we call 'marginal predictability'. This quantity is computed using data from remote and from adjacent electrodes. We find that the difference between the marginal predictabilities computed for the remote and adjacent electrodes decreases several tens of minutes prior to seizure onset, compared to its value interictally.

Adolescent↗

PubMedDate not supplied

Linear and nonlinear measures and seizure anticipation in temporal lobe epilepsy.

In a recent paper, we showed that the value of a nonlinear quantity computed from scalp electrode data was correlated with the time to a seizure in patients with temporal lobe epilepsy. In this paper we study the relationship between the linear and nonlinear content and analyses of the scalp data. We do this in two ways. First, using surrogate data methods, we show that there is important nonlinear structure in the scalp electrode data to which our methods are sensitive. Second, we study the behavior of some simple linear metrics on the same set of scalp data to see whether the nonlinear metrics contain additional information not carried by the linear measures. We find that, while the nonlinear measures are correlated with time to seizure, the linear measures are not, over the time scales we have defined. The linear and nonlinear measures are themselves apparently linearly correlated, but that correlation can be ascribed to the influence of a small set of outliers, associated with muscle artifact. A remaining, more subtle relation between the variance of the values of a nonlinear measure and the expectation value of a linear measure persists. Implications of our observations are discussed.

Electroencephalography↗