Abstracts

Rationale: Interictal spikes are brief (< 250 milliseconds), high-amplitude discharges observed in the EEG (scalp and intracranial) in patients who are predisposed to spontaneous seizures. The temporo-spatial distribution of spikes is variable and depends on states of vigilance (SOV) and seizure. In focal epilepsy, spikes are often found in regions beyond the seizure onset zone(SOZ) and are defined as “irritative zone”(IZ). Continuous dynamic interactions between SOZ and IZ are influenced by underlying synchronization that in turn is regulated by SOV. Studies demonstrating the variation in spike distribution are often constrained to cortical structures. Thalamus, a subcortical node interconnected to diverse cortical network including mesial temporal lobe, is implicated in regulation of SOV and in genesis of focal seizures. However to date, no study has explored the distribution of spike within the thalamo-cortical network in human focal epilepsy. We hypothesize, that the prevalence of spike within the SOZ and thalamus will vary with SOV and the spike count in thalamus will be higher during sleep than in wakefulness. Methods: Five adults with suspected temporal lobe epilepsy underwent stereoEEG (SEEG) investigation. Anterior thalamic nucleus (TH) ipsilateral to the SOZ was sampled with SEEG. The study was approved by IRB and written consent was obtained before surgery. Simultaneous scalp EEG was recorded that guided identification of NREM sleep (S) and wakefulness (A). Epileptogenic index was performed to identify SOZ. Spikes were analyzed during S and A from three channels :a) one within the SOZ; b) second from Th; and c) third outside the SOZ (control - C). Automated spike detection (P- operator) was validated by comparing the algorithm output to visual identification in 30 mins data per subject. For the spike count between SOV independent T-tests were performed to assess the bivariate relationships. Analysis of variance Welch ANOVA was used to analyze the differences in SOV as a function of three different independent samples (Channels). All statistical analyses were performed using IBM SPSS. Results: A total of 150 hours (15 hours of awake and 15 hours of sleep per subject X 5 subjects) was analyzed. SOZ were- temporo-insular, amygdala-hippocampus, temporo-perisylvian (N= 2) and hippocampal-anterior cingulate.  Descriptive analyses included means, standard deviations, medians, and ranges of spikes were in table 1. For the SOZ the mean spike count for awake state were lower than sleep state (70.16 ± 22.36 compared to 97.52 ± 23.45, respectively; (t(df= 785)= -16.46, p0.001). For the TH channels the mean spike count for awake state were lower than sleep state (15.19 ± 11.29 compared to 72.43 ± 39.65, respectively; (t(df= 440.1)= -27.06, p0.001).  Control channels did not show a significant difference between SOV. The differences between the channels (SOZ, TH and C) during different SOV were significantly different (Table 1 and Fig1).  The ratio of spikes between SOZ:TH during awake and sleep were 4.6 and 1.6 respectively. The morphology of the spikes (duration, amplitude) was compared between SOZ and TH (Fig 1). Conclusions: Following transition from awake to sleep, there was a- 1) significant increase in spike count in SOZ and TH; and 2) the increment in TH was significantly higher than in SOZ. Spikes in SOZ were faster than in TH. Funding: This study was funded by the NSF EPSCoR OIA 1632891.