No abstract

We report on a quantitative analysis of electrocorticography data from a study that acquired continuous ambulatory recordings in humans over extended periods of time. The objectives were to examine patterns of seizures and spontaneous interictal spikes, their relationship to each other, and the nature of periodic variation. The recorded data were originally acquired for the purpose of seizure prediction, and were subsequently analysed in further detail. A detection algorithm identified potential seizure activity and a template matched filter was used to locate spikes. Seizure events were confirmed manually and classified as either clinically correlated, electroencephalographically identical but not clinically correlated, or subclinical. We found that spike rate was significantly altered prior to seizure in 9 out of 15 subjects. Increased pre-ictal spike rate was linked to improved predictability; however, spike rate was also shown to decrease before seizure (in 6 out of the 9 subjects). The probability distribution of spikes and seizures were notably similar, i.e. at times of high seizure likelihood the probability of epileptic spiking also increased. Both spikes and seizures showed clear evidence of circadian regulation and, for some subjects, there were also longer term patterns visible over weeks to months. Patterns of spike and seizure occurrence were highly subject-specific. The pre-ictal decrease in spike rate is not consistent with spikes promoting seizures. However, the fact that spikes and seizures demonstrate similar probability distributions suggests they are not wholly independent processes. It is possible spikes actively inhibit seizures, or that a decreased spike rate is a secondary symptom of the brain approaching seizure. If spike rate is modulated by common regulatory factors as seizures then spikes may be useful biomarkers of cortical excitability.

Background and Purpose-A number of therapies in development for patients with central nervous system injury aim to reduce disability by improving function of surviving brain elements rather than by salvaging tissue. The current study tested the hypothesis that, after adjusting for a number of clinical assessments, a measure of brain function at baseline would improve prediction of behavioral gains after treatment. Methods-Twenty-four patients with chronic stroke underwent baseline clinical and functional MRI assessments, received 6 weeks of rehabilitation therapy with or without investigational motor cortex stimulation, and then had repeat assessments. Thirteen baseline clinical/radiological measures were evaluated for ability to predict subsequent trial-related gains. Results-Across all patients, bivariate analyses found that greater trial-related functional gains were predicted by (1) smaller infarct volume, (2) greater baseline clinical status, and (3) lower degree of activation in stroke-affected motor cortex on baseline functional MRI. When these 3 variables were further assessed using multivariate linear regression modeling, only lower motor cortex activation and greater clinical status at baseline remained significant predictors. Note that lower baseline motor cortex activation was also associated with larger increases in motor cortex activation after treatment. Conclusions-Lower motor cortex activity at baseline predicted greater behavioral gains after therapy, even after controlling for a number of clinical assessments. The boosts in cortical activity that paralleled behavioral gains suggest that in some patients, low baseline cortical activity represents underuse of surviving cortical resources. A measure of brain function might be important for optimal clinical decision-making in the context of a restorative intervention.