ADDRESSES AND ORIGINAL ARTICLESRHYTHM IN EPILEPSY
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Cited by (95)
Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study
2021, EBioMedicineCircadian and multiday rhythms are found across many biological systems, including cardiology, endocrinology, neurology, and immunology. In people with epilepsy, epileptic brain activity and seizure occurrence have been found to follow circadian, weekly, and monthly rhythms. Understanding the relationship between these cycles of brain excitability and other physiological systems can provide new insight into the causes of multiday cycles. The brain-heart link has previously been considered in epilepsy research, with potential implications for seizure forecasting, therapy, and mortality (i.e., sudden unexpected death in epilepsy).
We report the results from a non-interventional, observational cohort study, Tracking Seizure Cycles. This study sought to examine multiday cycles of heart rate and seizures in adults with diagnosed uncontrolled epilepsy (N=31) and healthy adult controls (N=15) using wearable smartwatches and mobile seizure diaries over at least four months (M=12.0, SD=5.9; control M=10.6, SD=6.4). Cycles in heart rate were detected using a continuous wavelet transform. Relationships between heart rate cycles and seizure occurrence were measured from the distributions of seizure likelihood with respect to underlying cycle phase.
Heart rate cycles were found in all 46 participants (people with epilepsy and healthy controls), with circadian (N=46), about-weekly (N=25) and about-monthly (N=13) rhythms being the most prevalent. Of the participants with epilepsy, 19 people had at least 20 reported seizures, and 10 of these had seizures significantly phase locked to their multiday heart rate cycles.
Heart rate cycles showed similarities to multiday epileptic rhythms and may be comodulated with seizure likelihood. The relationship between heart rate and seizures is relevant for epilepsy therapy, including seizure forecasting, and may also have implications for cardiovascular disease. More broadly, understanding the link between multiday cycles in the heart and brain can shed new light on endogenous physiological rhythms in humans.
This research received funding from the Australian Government National Health and Medical Research Council (investigator grant 1178220), the Australian Government BioMedTech Horizons program, and the Epilepsy Foundation of America's ‘My Seizure Gauge’ grant.
Long-term seizure dynamics are determined by the nature of seizures and the mutual interactions between them
2021, Neurobiology of DiseaseThe seemingly random and unpredictable nature of seizures is a major debilitating factor for people with epilepsy. An increasing body of evidence demonstrates that the epileptic brain exhibits long-term fluctuations in seizure susceptibility, and seizure emergence seems to be a consequence of processes operating over multiple temporal scales. A deeper insight into the mechanisms responsible for long-term seizure fluctuations may provide important information for understanding the complex nature of seizure genesis. In this study, we explored the long-term dynamics of seizures in the tetanus toxin model of temporal lobe epilepsy. The results demonstrate the existence of long-term fluctuations in seizure probability, where seizures form clusters in time and are then followed by seizure-free periods. Within each cluster, seizure distribution is non-Poissonian, as demonstrated by the progressively increasing inter-seizure interval (ISI), which marks the approaching cluster termination. The lengthening of ISIs is paralleled by: increasing behavioral seizure severity, the occurrence of convulsive seizures, recruitment of extra-hippocampal structures and the spread of electrographic epileptiform activity outside of the limbic system. The results suggest that repeated non-convulsive seizures obey the ‘seizures-beget-seizures’ principle, leading to the occurrence of convulsive seizures, which decrease the probability of a subsequent seizure and, thus, increase the following ISI. The cumulative effect of repeated convulsive seizures leads to cluster termination, followed by a long inter-cluster period. We propose that seizures themselves are an endogenous factor that contributes to long-term fluctuations in seizure susceptibility and their mutual interaction determines the future evolution of disease activity.
Temporal patterns in the first unprovoked seizure
2021, Epilepsy and BehaviorCyclic phenomena in epilepsy are well recognized. We investigated a multicenter cohort of unprovoked first seizure presentations to determine whether seizures have a preponderance to occur in: a particular time of the day, a particular day of the week, a particular month of the year, day time versus night time, and wakefulness versus sleep.
We retrospectively studied adults who presented with a first-ever unprovoked seizure to the First Seizure Clinic at two tertiary centers in Australia. Seizure onset time was obtained from the emergency department and ambulance documentations. Electro-clinical and neuroimaging findings were reviewed. We used histograms and Poisson regression modeling to determine whether seizures have a preponderance to occur at a particular time and calculated incidence rate ratios (IRR). We performed further analysis on patients with “first seizure epilepsy” and “first seizure not epilepsy” based on the ILAE criteria for a diagnosis of epilepsy after a single unprovoked seizure, as well as comparing patients that could be categorized as having a generalized-onset seizure versus those with focal–onset seizures.
We analyzed 1724 patients (38% females; age range 14–97 yr, median 39 yr), of whom 18% had epileptiform abnormalities on EEG and potentially epileptogenic lesions were detected on neuroimaging in 28%. Whole cohort analysis shows the incidence rate ratios (IRR) of seizures varied significantly across the 24-hour clock-time of the day (p < 0.001), peaking at hour 12 (IRR 3.18). The first unprovoked seizure was significantly less likely to be reported during the night (IRR 0.61, p < 0.001) and during sleep (IRR 0.29, p < 0.001). Both the “first seizure epilepsy” and “first seizure not epilepsy” subgroups’ analysis demonstrated similar patterns. An infraradian pattern was also noted with seizures most likely to occur in May (IRR 1.29, p = 0.02). Both “first seizure epilepsy – generalized” and “first seizure epilepsy – focal” groups had a preponderance for seizures to occur during the day versus night and wakefulness as opposed to sleep, but the association was more robust for generalized seizures.
Our results suggest that temporal patterns are seen in patients with first-ever unprovoked seizures, including those that meet contemporary criteria for epilepsy. These results raise the possibility that first unprovoked seizures have intrinsic rhythmicity similar to epileptic seizures.
Neural signal data collection and analysis of Percept™ PC BrainSense recordings for thalamic stimulation in epilepsy
2024, Journal of Neural EngineeringUltradian rhythms in accelerometric and autonomic data vary based on seizure occurrence in paediatric epilepsy patients
2024, Brain CommunicationsSeizure forecasting: Where do we stand?
2023, Epilepsia