Richner, Thomas J

The brain is a highly recurrent, nonlinear network hypothesized to remain near the edge of chaos for optimal performance. Excitation and inhibition must be balanced precisely within every neuron to ensure a consistent level of dynamical stability and rich dynamics during transition to chaos. However, analysis of biologically realistic synaptic weight matrices suggests that sparsity and low-dimensional structure interact such that there is no known synaptic balancing rule that constrains the stability (i.e., eigenvalues) of the network while also preserving computationally useful, low-dimensional structure. Further, even if a network were well-balanced, external stimuli interact with the nonlinear activation functions to unbalance the network in real time. Therefore, the brain must utilize dynamic, rather than static, mechanisms to actively regulate its level of stability. We propose that two specific adaptation mechanisms, spike frequency adaptation (SFA) and short-term synaptic depression (STD), continuously modulate the effective connectivity, keeping the brain near the edge of chaos and reducing dynamical fluctuations caused by stimuli. This theoretical framework links intrinsic and synaptic negative feedback mechanisms to network-level dynamics. This offers an explanation of why data-driven modeling of human brain signals, an exciting and useful method in epilepsy and anesthesiology research, seems to require linear time-varying (LTV) models which are refit every half second: difficult to observe adaptation processes interact with nonlinearities to make connectivity effectively dynamic at the macroelectrode scale. We suggest that compromised adaptation may underlie neurological conditions characterized by altered excitability, and that targeted brain stimulation could be used to probe the regulatory action of adaptation.

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.