Seizure occurrence is linked to multiday cycles in diverse physiological signals

Abstract

Objective: The factors that influence seizure timing are poorly understood, and seizure unpredictability remains a major cause of disability. Work in chronobiology has shown that cyclical physiological phenomena are ubiquitous, with daily and multiday cycles evident in immune, endocrine, metabolic, neurological, and cardiovascular function. Additionally, work with chronic brain recordings has identified that seizure risk is linked to daily and multiday cycles in brain activity. Here, we provide the first characterization of the relationships between the cyclical modulation of a diverse set of physiological signals, brain activity, and seizure timing.

Methods: In this cohort study, 14 subjects underwent chronic ambulatory monitoring with a multimodal wrist-worn sensor (recording heart rate, accelerometry, electrodermal activity, and temperature) and an implanted responsive neurostimulation system (recording interictal epileptiform abnormalities and electrographic seizures). Wavelet and filter-Hilbert spectral analyses characterized circadian and multiday cycles in brain and wearable recordings. Circular statistics assessed electrographic seizure timing and cycles in physiology.

Results: Ten subjects met inclusion criteria. The mean recording duration was 232 days. Seven subjects had reliable electroencephalographic seizure detections (mean = 76 seizures). Multiday cycles were present in all wearable device signals across all subjects. Seizure timing was phase locked to multiday cycles in five (temperature), four (heart rate, phasic electrodermal activity), and three (accelerometry, heart rate variability, tonic electrodermal activity) subjects. Notably, after regression of behavioral covariates from heart rate, six of seven subjects had seizure phase locking to the residual heart rate signal.

Significance: Seizure timing is associated with daily and multiday cycles in multiple physiological processes. Chronic multimodal wearable device recordings can situate rare paroxysmal events, like seizures, within a broader chronobiology context of the individual. Wearable devices may advance the understanding of factors that influence seizure risk and enable personalized time-varying approaches to epilepsy care.

Keywords: biomarkers; chronobiology; seizure forecasting; wearable devices.

Figure 1. Chronic brain and wearable recordings.

Unprocessed chronic brain and wearable device recordings. A) Brain and wearable recording device illustration, and representative interictal recordings. B) Concurrent brain and wearable ictal recordings (subject 3). C) Data from ten subjects were analyzed, seven of whom had reliable electrographic seizure detections (marked by lightning bolt). D) Concurrent chronic ambulatory brain and wearable recordings; 2-day moving average values; red dots mark seizure onset times. Interictal and chronic recordings are from subject 4. RNS = responsive neurostimulation. BVP = blood volume pulse. IBI = inter-beat-interval. HR = heart rate. EDA = electrodermal activity. ACC = accelerometry. TEMP = temperature. IEA = Interictal epileptiform activity.

Figure 2. Amplitude spectral density.

Amplitude spectral density of chronic brain and wearable device recordings. The top row presents the time averaged ASD for each channel across all subjects. The bottom panel shows the count of relative maxima for multiday cycles in the ASD above the 95^th percentile of normally distributed white noise (red dotted line). Vertical grey dashed lines mark daily, 7-day, and 14-day cycle periods. ASD = amplitude spectral density. IEA = interictal epileptiform activity. ACC = accelerometry. HR = heart rate. HRV = heart rate variability. EDAt = tonic electrodermal activity. EDAp = phasic electrodermal activity. TEMP = temperature.

Figure 3. Circadian cycles of seizure risk.

A) Daily average wearable sensor and brain recordings over the duration of monitoring, relative to clock-time. Error bars reflect standard error of the mean. Seizures relative to daily clock-time are marked by black circles. B) Resultant vector of seizure phase locking to circadian physiology. Only statistically significant resultant vectors are shown (dashed vectors indicate statistical significance by Rayleigh but not Omnibus test). Red and blue arrows correspond to the subjects in A) and black arrows correspond to the remaining subjects. IEA = interictal epileptiform activity. ACC = accelerometry. HR = heart rate. HRV = heart rate variability. EDAt = tonic electrodermal activity. EDAp = phasic electrodermal activity. TEMP = temperature.

Figure 4. Multiday cycles of seizure risk.

A) Polar plots of the resultant vector of seizure phase locking to multiday cycles of chronic brain and wearable recordings (dashed vectors indicate statistical significance by Rayleigh but not Omnibus test; a single white/black arrowhead in A) EDA tonic, and one in B) HR residual indicate statistical significance on Omnibus but not Rayleigh test). B) Polar plot of the resultant vector of seizure phase locking to multiday cycles of residual HR. C) Histogram showing the prevalence of significant seizure phase locking to circadian and multiday cycles. Seizure phase locking to residual HR after regression of behavioral activity (ACC) is marked in shades of red. D) Sorted resultant vector amplitude (R-value) for seizure phase locking to multiday cycles. The HR plot shows seizure phase locking R-values for HR cycles and residual HR cycles. Plots show R-value for all significant peaks in amplitude spectral density plots, (not limited to cycles with significant seizure phase locking as in A)-C)). IEA = interictal epileptiform activity. ACC = accelerometry. HR = heart rate. HRV = heart rate variability. EDAt = tonic electrodermal activity. EDAp = phasic electrodermal activity. TEMP = temperature.

Figure 5. Multiscale cycles of seizure risk.

A) Examples of chronic wearable sensor and brain and recordings, and below, circadian and multiday bandpass filtered tracings and seizure onset times. B) Corresponding polar histogram plots, with pink arrow R-value. The outer ring number is seizure count; for R-value amplitude, the outer ring = 1. C) Corresponding phase-phase plots show seizure counts with respect to circadian and multiday cycles. Π = cycle trough, 0 and 2Π = peak, and ↑/↓ = rising or falling phase. D) Group averaged phase-phase plots for all significant (Rayleigh test) circadian and multiday cycles. Phase-phase plots were normalized to the total number of seizures per subject and the median circadian and multiday phases were centered prior to averaging. The colormap scale has a fixed proportional scale relative to the total seizure count for each channel, for direct comparisons between channels. The top right inset script is the number of subjects (S) and phase-phase analyses (PhPh) included in the group plot. IEA = interictal epileptiform activity. ACC = accelerometry. HR = heart rate. HRV = heart rate variability. EDAt = tonic electrodermal activity. EDAp = phasic electrodermal activity. TEMP = temperature. e = power of 10 (1e2 = 1x10²).