Electrophysiological measures of regional neural interactive coupling. Linear and non-linear dependence relationships among multiple channel electroencephalographic recordings.

Linear spectral coherence (Sklar et al., 1973) measures have been used in the neurosciences to test hypotheses which address the question of whether multiple EEG recording sites are independent or whether they are activated by common sources of neurophysiological activity. This measure is appropriate when regional neural sources interact and thereby electrically activate several recording sites through linear transmission pathways which may or may not be different in their linear transformation properties. However, if the transmission media are non-linear, then interactive dependency is not necessarily revealed by a linear coherence test. Therefore, if common sources are activating EEG recording sites through nonlinear media, evaluating the resulting relationships among the signals recorded from these sites requires a test which reveals the presence of such nonlinear relationships. In neurophysiological applications, a polycoherence cross-spectral measure provides such a test for nonlinear dependency (similar to the linear coherence test) among EEG recording sites. The data requirements and statistical properties of these linear and non-linear measures are described and results of a linear coherence analysis are presented in the context of an EEG pilot study of learning-disabled children.

Moments of the power spectral density estimated from samples of the autocorrelation function (a robust procedure for monitoring changes in the statistical properties of lengthy non-stationary time series such as the EEG.

Accurate estimates of the statistical moments of the power spectral density (PSD) are obtained without computing the Fourier transform of the associated time series. An innovative analytical procedure is derived which reduces the problem to that of summing a small number of weighted samples of the autocorrelation function (ACF). This result significantly reduces the computational requirements for generating meaningful PSD shape descriptors and thus is especially important in biomedical applications where the cost and effort of monitoring lengthy non-stationary time series is a serious practical limitation. In addition the procedure is robust and therefore can be rigorously applied to any stochastic process to estimate its fundamental statistical properties.

EEG time and frequency domain measures of cerebral specialization.

Electroencephalographic (EEG) studies of lateralized cognitive functions have primarily relied upon measures of averaged evoked potentials (AEP) and power spectra (PS) to demonstrate hemispheric differences. The nature of the tasks appropriate to each of these methods of signal analysis generally require different cognitive activities and suggest different assumptions about cerebral specialization. This study investigated whether the tasks associated with either method were more likely to produce EEG asymmetries. Eighteen right-handed subjects participated in a three phase experiment which varied the amount of subject involvement in task performance. Phase I entailed passive listening to speech and nonspeech sounds. Phase II required active attention to speech and nonspeech sounds. Phase III involved a verbal matching task, a spatial rotations task, and a noncognitive control task. Auditory AEPs were measured in Phases I and II, and PS were measured in Phase II and III. EEG recordings were obtained from frontal and parietal areas of both hemispheres (F3, F4, P3, P4) referred to linked ears. Power spectra were derived from the 4-8, 8-13, and 13-20 Hz frequency bands at each lead. Despite statistically significant task and/or stimuli differences found in all three phases of study, essentially no task by lead interactions were obtained. That is, interhemispheric activity did not covary with differing stimuli and tasks. The absence of such interactions calls into question uncritical acceptance of a simple direct relation between task performance, EEG activity, and hemisphere specialization.

Evoked potential studies of the effects of impact acceleration on the motor nervous system.

The initial results of a continuing investigation into the effects of various levels of impact acceleration on the functional integrity of the motor nervous system are summarized. The results are based on the measurement of alterations in neural transmission along the motor pathway of the Rhesus monkey as revealed by latency and amplitude changes in the motor pathway evoked potential (EP) following the delivery of various levels of impact acceleration to a test vehicle. The EPs were produced by electrical stimulation of and recording from the motor pathway of experimental animals subjected to -Y (lateral impact) acceleration and animals subjected to -X (frontal impact) acceleration. High resolution latency and amplitude measures of the EP recorded from these animals before and after impact were tracked so that the time course of recovery of nerve propagation following impact could be accurately assessed. Analysis of these EP measures revealed that the time course of recovery to preimpact values is directly related to the intensity of the acceleration impulse delivered to the test vehicle.

Epilepsy: a heuristic model for relating nocturnal sleep EEG spike distributions to the risk of seizure.

The cumulative temporal distribution of epileptiform events in the sleep EEG of epileptic patients is represented by a second-degree regression equation as a basis for summarizing properties of the spike distribution. This heuristic regression model attempts to provide a quantitative as well as an intuitive physical basis for understanding the relationship between epileptiform events and the state of the epileptic patient. The mathematical model is derived in this paper and the regression parameters associated with the model are interpreted. Computer implementation of the epileptiform event detection and the regression analysis have been carried out and typical results obtained from all-night EEG recordings are described.