Circadian and multiday seizure periodicities, and seizure clusters in canine epilepsy

Abstract

Advances in ambulatory intracranial EEG devices have enabled objective analyses of circadian and multiday seizure periodicities, and seizure clusters in humans. This study characterizes circadian and multiday seizure periodicities, and seizure clusters in dogs with naturally occurring focal epilepsy, and considers the implications of an animal model for the study of seizure risk patterns, seizure forecasting and personalized treatment protocols. In this retrospective cohort study, 16 dogs were continuously monitored with ambulatory intracranial EEG devices designed for humans. Detailed medication records were kept for all dogs. Seizure periodicity was evaluated with circular statistics methods. Circular non-uniformity was assessed for circadian, 7-day and approximately monthly periods. The Rayleigh test was used to assess statistical significance, with correction for multiple comparisons. Seizure clusters were evaluated with Fano factor (index of dispersion) measurements, and compared to a Poisson distribution. Relationships between interseizure interval (ISI) and seizure duration were evaluated. Six dogs met the inclusion criteria of having at least 30 seizures and were monitored for an average of 65 weeks. Three dogs had seizures with circadian seizure periodicity, one dog had a 7-day periodicity, and two dogs had approximately monthly periodicity. Four dogs had seizure clusters and significantly elevated Fano factor values. There were subject-specific differences in the dynamics of ISI and seizure durations, both within and between lead and clustered seizure categories. Our findings show that seizure timing in dogs with naturally occurring epilepsy is not random, and that circadian and multiday seizure periodicities, and seizure clusters are common. Circadian, 7-day, and monthly seizure periodicities occur independent of antiseizure medication dosing, and these patterns likely reflect endogenous rhythms of seizure risk.

Keywords: EEG; ambulatory EEG; animal models; epilepsy; intracranial EEG; seizure prediction.

Graphical Abstract

Figure 1

Temporal distribution of seizures at multiple time scales in canine epilepsy. (A) Schematic of a dog with epilepsy and an implanted ambulatory iEEG device. (B) Raw iEEG tracings from a single referential contact displayed at multiple time scales, which shows a seizure, a seizure cluster and a pair of seizure clusters separated by a prolonged ISI. Red triangles indicate seizure onset.

Figure 2

Lead seizure counts and total seizure counts over time. (A) Cumulative lead seizure counts over time. Subject specific seizure rates [equal to the slope of the least squares line (orange line)], were stable throughout the recording for five dogs. Dog 1 had a 2-year non-recording period between NeuroVista explanation and RC+S device implantation, over which time there was a change in seizure rate. (B) Total seizure counts plotted relative to time. Dogs 1, 2, 5 and 6 had significant seizure clustering. Non-recording time periods were removed from analysis and are indicated by hash-marks.

Figure 3

Circadian, circaseptan and monthly seizure periodicity. Circular histograms of all dogs for (A) 24-h, (B) 7-day and (C) approximately monthly period durations. The red bar is the resultant vector, or R-value. Concentric rings demarcate the number of seizures (five seizures per concentric ring in (A), two seizure per ring in (B) and (C). Dogs with statistically significant periodicity are marked in red font and by ‘asterisk’. In (B) and (C), ‘hash’ next to Dog 5 and Dog 2, respectively, indicates a trend towards significant periodicity that did not survive FDR correction. (D) The R-value is plotted for cycle durations of 6 h to 35 days in steps of quarter-days. (A) Results for lead seizures only. Statistically significant R-values as determined by the Rayleigh test (P < 0.05 without correction for multiple comparisons) are marked in red.

Figure 4

Seizure clustering. (A) Fano factor for each dog for day, week and month-long intervals. (B) Blue circles are the logarithm of the proportion of seizures with ISI > x_i, relative to ISI x_i, for each subject. Linearity of the distribution in consistent with a Poisson process, shown in red (Taubøll et al., 1991). A negative deviation from Poisson distribution (down and to the left) indicates seizure clustering. The dogs whose temporal distribution of seizures best fit a Poisson process (Pearson’s r in graph) also have non-significant Fano factor values (Dogs 3 and 4), and vice versa.

Figure 5

Dynamics of clustered seizures. All dogs with seizure clusters. (A) Histograms of clustered seizure counts relative to ISI (Dog 1, n = 125; Dog 2, n = 40; Dog 6, n = 96; and All Dogs, n = 298 seizures). (B) Dog 5 had periodicity of clustered seizures apparent in the histogram (n = 37 seizures). The box-plot shows ISI data for each of the dog’s seizure clusters that contained at least three seizures (cluster 1, n = 4; cluster 2, n = 10; cluster 3, n = 4; cluster 4, n = 7; cluster 5, n = 6; cluster 6, n = 7; cluster 8, n = 4). The circular histogram period length was defined as the clustered seizure median ISI, which is 5 h and 16 min; five seizures per concentric ring.