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 Noninvasive brain stimulation (NIBS) provides a treatment option for patients not eligible for surgical intervention or who seek low‐risk approaches and may be used in the hospital, clinic, and at home. Our objective is to summarize our single‐center experience with multiple NIBS approaches for the treatment of focal epilepsy. Methods A retrospective chart review identified drug‐resistant focal epilepsy patients who received NIBS as an epilepsy treatment at Mayo Clinic in Rochester, MN. Patients were typically treated as follows: (1) for TMS, 1 Hz stimulation was applied for five consecutive days in the neuromodulation clinic, (2) for outpatient tDCS, stimulation was applied for five consecutive days in the clinic, followed by optional treatment at home, and (3) for inpatient tDCS, stimulation was applied for three consecutive days. We analyzed continuous EEG data for the inpatient tDCS cohort and available HD‐EEG data for outpatient cohorts to quantify changes in interictal epileptiform discharges (IEDs) as a result of stimulation. Outcomes were assessed at 1 month for TMS and outpatient tDCS and 1 week for inpatient tDCS. Results Twenty‐four patients were treated with TMS ( n = 10) and tDCS ( n = 14, 9 as outpatients). The median age was 40 years (range 15–73). The median seizure reduction following stimulation was 50%. Fourteen patients (58%) were responders to treatment (TMS = 4/10, tDCS Outpatient = 7/9, tDCS Inpatient = 3/5). Five outpatient tDCS participants elected to continue treatment at home. Four TMS and four outpatient tDCS patients underwent high‐density EEG before and after 5 days of therapy. Following stimulation, IED rate was reduced in 4/5 inpatient tDCS patients, 4/4 outpatient tDCS patients, and 4/4 TMS patients. Two patients experienced an increase in seizure frequency (1 following TMS and 1 following outpatient tDCS), which returned to baseline 4–6 weeks after stimulation treatments were discontinued. Significance TMS and tDCS are potential treatment approaches for drug‐resistant focal epilepsy patients in the hospital, clinic, and home. They have a favorable safety profile and can lead to a reduction in IED rates and seizures. These results suggest further studies are needed to examine NIBS as a treatment for epilepsy. Plain Language Summary Noninvasive brain stimulation, such as transcranial magnetic stimulation and transcranial direct current stimulation, offers new treatment options for patients with focal seizures. This study reviewed the experience at Mayo Clinic using noninvasive brain stimulation in the hospital, clinic, and at‐home settings to treat seizures. The results showed an overall 50% median seizure reduction, and 58% of patients had at least a 50% reduction in seizures. Noninvasive brain stimulation is a promising treatment approach with a favorable safety profile.

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.