Electrocorticographic Dynamics as a Novel Biomarker in Five Models of Epileptogenesis.

Postinjury epilepsy (PIE) is a devastating sequela of various brain insults. While recent studies offer novel insights into the mechanisms underlying epileptogenesis and discover potential preventive treatments, the lack of PIE biomarkers hinders the clinical implementation of such treatments. Here we explored the biomarker potential of different electrographic features in five models of PIE. Electrocorticographic or intrahippocampal recordings of epileptogenesis (from the insult to the first spontaneous seizure) from two laboratories were analyzed in three mouse and two rat PIE models. Time, frequency, and fractal and nonlinear properties of the signals were examined, in addition to the daily rate of epileptiform spikes, the relative power of five frequency bands (theta, alpha, beta, low gamma, and high gamma) and the dynamics of these features over time. During the latent pre-seizure period, epileptiform spikes were more frequent in epileptic compared with nonepileptic rodents; however, this feature showed limited predictive power due to high inter- and intra-animal variability. While nondynamic rhythmic representation failed to predict epilepsy, the dynamics of the theta band were found to predict PIE with a sensitivity and specificity of >90%. Moreover, theta dynamics were found to be inversely correlated with the latency period (and thus predict the onset of seizures) and with the power change of the high-gamma rhythm. In addition, changes in theta band power during epileptogenesis were associated with altered locomotor activity and distorted circadian rhythm. These results suggest that changes in theta band during the epileptogenic period may serve as a diagnostic biomarker for epileptogenesis, able to predict the future onset of spontaneous seizures.SIGNIFICANCE STATEMENT Postinjury epilepsy is an unpreventable and devastating disorder that develops following brain injuries, such as traumatic brain injury and stroke, and is often associated with neuropsychiatric comorbidities. As PIE affects as many as 20% of brain-injured patients, reliable biomarkers are imperative before any preclinical therapeutics can find clinical translation. We demonstrate the capacity to predict the epileptic outcome in five different models of PIE, highlighting theta rhythm dynamics as a promising biomarker for epilepsy. Our findings prompt the exploration of theta dynamics (using repeated electroencephalographic recordings) as an epilepsy biomarker in brain injury patients.

Paroxysmal slow cortical activity in Alzheimer's disease and epilepsy is associated with blood-brain barrier dysfunction.

A growing body of evidence shows that epileptic activity is frequent but often undiagnosed in patients with Alzheimer's disease (AD) and has major therapeutic implications. Here, we analyzed electroencephalogram (EEG) data from patients with AD and found an EEG signature of transient slowing of the cortical network that we termed paroxysmal slow wave events (PSWEs). The occurrence per minute of the PSWEs was correlated with level of cognitive impairment. Interictal (between seizures) PSWEs were also found in patients with epilepsy, localized to cortical regions displaying blood-brain barrier (BBB) dysfunction, and in three rodent models with BBB pathology: aged mice, young 5x familial AD model, and status epilepticus-induced epilepsy in young rats. To investigate the potential causative role of BBB dysfunction in network modifications underlying PSWEs, we infused the serum protein albumin directly into the cerebral ventricles of naïve young rats. Infusion of albumin, but not artificial cerebrospinal fluid control, resulted in high incidence of PSWEs. Our results identify PSWEs as an EEG manifestation of nonconvulsive seizures in patients with AD and suggest BBB pathology as an underlying mechanism and as a promising therapeutic target.