Responsive Neurostimulation for the Treatment of Epilepsy

Adaptive fuzzy iterative learning control based neurostimulation system and in-silico evaluation

Closed-loop neural stimulation has been an effective treatment for epilepsy patients. Currently, most closed-loop neural stimulation strategies are designed based on accurate neural models. However, the uncertainty and complexity of the neural system make it difficult to build an accurate neural model, which poses a significant challenge to the design of the controller. This paper proposes an Adaptive Fuzzy Iterative Learning Control (AFILC) framework for closed-loop neural stimulation, which can realize neuromodulation with no model or model uncertainty. Recognizing the periodic characteristics of neural stimulation and neuronal firing, Iterative Learning Control (ILC) is employed as the primary controller. Furthermore, a fuzzy optimization module is established to update the internal parameters of the ILC controller in real-time. This module enhances the anti-interference ability of the control system and reduces the influence of initial controller parameters on the control process. The efficacy of this strategy is evaluated using a neural computational model. The simulation results validate the capability of the AFILC strategy to suppress epileptic states. Compared with ILC-based closed-loop neurostimulation schemes, the AFILC-based neurostimulation strategy has faster convergence speed and stronger anti-interference ability. Moreover, the control algorithm is implemented based on a digital signal processor, and the hardware-in-the-loop experimental platform is implemented. The experimental results show that the control method has good control performance and computational efficiency, which provides the possibility for future application in clinical research.

Neuroethics of Non-primary Brain Computer Interface: Focus on Potential Military Applications

The field of neuroethics has had to adapt rapidly in the face of accelerating technological advancement; a particularly striking example is the realm of Brain-Computer Interface (BCI). A significant source of funding for the development of new BCI technologies has been the United States Department of Defense, and while the predominant focus has been restoration of lost function for those wounded in battle, there is also significant interest in augmentation of function to increase survivability, coordination, and lethality of US combat forces. While restoration of primary motor and sensory function (primary BCI) has been the main focus of research, there has been marked progress in interface with areas of the brain subserving memory and association. Non-Primary BCI has a different subset of potential applications, each of which also carries its own ethical considerations. Given the amount of BCI research funding coming from the Department of Defense, it is particularly important that potential military applications be examined from a neuroethical standpoint.

Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy

Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy.

Non-pharmacological treatment options for refractory epilepsy: an overview of human treatment modalities and their potential utility in dogs

Refractory epilepsy is a common disorder both in humans and dogs and treatment protocols are difficult to optimise. In humans, different non-pharmacological treatment modalities currently available include surgery, the ketogenic diet and neurostimulation. Surgery leads to freedom from seizures in 50-75% of patients, but requires strict patient selection. The ketogenic diet is indicated in severe childhood epilepsies, but efficacy is limited and long-term compliance can be problematic. In the past decade, various types of neurostimulation have emerged as promising treatment modalities for humans with refractory epilepsy. Currently, none of these treatment options are used in routine daily clinical practice to treat dogs with the condition. Since many dogs with poorly controlled seizures do not survive, the search for alternative treatment options for canine refractory epilepsy should be prioritised. This review provides an overview of non-pharmacological treatment options for human refractory epilepsy. The current knowledge and limitations of these treatments in canine refractory epilepsy is also discussed.

Mode-dependent effect of high-frequency electrical stimulation of the anterior thalamic nucleus on amygdala-kindled seizures in rats

Deep brain stimulation (DBS) is an emerging treatment of epilepsy. Anterior nucleus of the thalamus (ANT) is considered to be an attractive target due to its close connection to the limbic structures and wide regions of neocortex. The present study aimed to investigate the effects of high frequency stimulation (HFS) targeting the ANT on amygdala-kindled seizures in Wistar rats in two different stimulation modes i.e. pre-treatment and post-treatment stimulations, mimicking the scheduled and responsive stimulations in clinical use respectively. When fully-kindled seizures were achieved by daily amygdala kindling (1 s train of 1 ms pulses at 60 Hz), HFS (15 min train of 100 μs pulses at 150 Hz and 450-800 μA) was applied in two modes for 10 days. Bilateral post-treatment with HFS reduced the incidence of generalized seizures and the mean behavioral seizure stage and shortened average afterdischarge duration (ADD) and generalized seizure duration (GSD), while bilateral pre-treatment with HFS resulted in a similar but much weaker inhibition of seizures. On the other hand, we also found the two stimulation modes both increased the afterdischarge threshold (ADT) and the differences of current intensity between ADT and generalized seizure threshold (GST) i.e. Δ(GST-ADT). However, Δ(GST-ADT) increased by at least 20 μA in bilateral post-treatment group, while less in bilateral pre-treatment group. Additionally, unilateral post-treatment with HFS failed to inhibit seizures. Our data show that anti-epileptic effect of bilateral post-treatment with HFS of ANT is much stronger than that of bilateral pre-treatment HFS, indicating bilateral responsive stimulation might be more appropriate for clinical anti-epileptic treatment of ANT HFS.