Improving control effects of absence seizures using single-pulse alternately resetting stimulation (SARS) of corticothalamic circuit

Presently,we develop a simplified corticothalamic(SCT)model and propose a single-pulse alternately resetting stimulation(SARS)with sequentially applying anodic(A,“+”)or cathodic(C,“−”)phase pulses to the thalamic reticular(RE)nuclei,thalamus-cortex(TC)relay nuclei,and cortical excitatory(EX)neurons,respectively.Abatement effects of ACC-SARS of RE,TC,and EX for the 2 Hz-4 Hz spike and wave discharges(SWD)of absence seizures are then concerned.The m∶n on-off ACC-SARS protocol is shown to effectively reduce the SWD with the least current consumption.In particular,when its frequency is out of the 2 Hz-4 Hz SWD dominant rhythm,the desired seizure abatements can be obtained,which can be further improved by our proposed directional steering(DS)stimulation.The dynamical explanations for the SARS induced seizure abatements are lastly given by calculating the averaged mean firing rate(AMFR)of neurons and triggering averaged mean firing rates(TAMFRs)of 2 Hz-4 Hz SWD.

Regulating absence seizures by tri-phase delay stimulation applied to globus pallidus internal

In this paper,a reduced globus pallidus internal(GPI)-corticothalamic(GCT)model is developed,and a tri-phase delay stimulation(TPDS)with sequentially applying three pulses on the GPI representing the inputs from the striatal D_(1)neurons,subthalamic nucleus(STN),and globus pallidus external(GPE),respectively,is proposed.The GPI is evidenced to control absence seizures characterized by 2 Hz–4 Hz spike and wave discharge(SWD).Hence,based on the basal ganglia-thalamocortical(BGCT)model,we firstly explore the triple effects of D_(1)-GPI,GPE-GPI,and STN-GPI pathways on seizure patterns.Then,using the GCT model,we apply the TPDS on the GPI to potentially investigate the alternative and improved approach if these pathways to the GPI are blocked.The results show that the striatum D_(1),GPE,and STN can indeed jointly and significantly affect seizure patterns.In particular,the TPDS can effectively reproduce the seizure pattern if the D_(1)-GPI,GPE-GPI,and STN-GPI pathways are cut off.In addition,the seizure abatement can be obtained by well tuning the TPDS stimulation parameters.This implies that the TPDS can play the surrogate role similar to the modulation of basal ganglia,which hopefully can be helpful for the development of the brain-computer interface in the clinical application of epilepsy.

Effect of the coordinated reset stimulations on controlling absence seizure

Based on a macroscopic mean-field model associating with the thalamus and cerebral cortex, we investigate how the newly proposed coordinated reset stimulation(CRS) strategy controls the absence seizures as some key parameters are changed.Different from the previous stimulation processes, CRS represents the intermittent pulse current administered to different structures including cortex, specific relay nuclei(SRN) and thalamus reticular nucleus(TRN) at different time by using three different micro-electrodes. In particular, we first simulate a typical absence epilepsy activity under the combined effect of the coupling strength between inhibitory interneurons(IIN)-excitatory pyramidal neurons(EPN) and EPN-TRN pathway. And then we explore the control mechanism of different parameters of 3:2 ON-OFF CRS on spike and slow-wave discharges(SWDs)region. Through analyzing the corresponding two-dimensional bifurcation diagrams, we find CRS is effective on controlling absence seizures in proper ranges of stimulation parameters. Especially, the combination of frequency and positive input duration can inhibit the pathological area more effectively. The obtained results might be helpful to study the pathophysiology mechanism of epilepsy, although the CRS's feasibility still needs further exploration in clinical experiments.

Absence seizures in lesion‑related epilepsy

Background In the new International League Against Epilepsy(ILAE)classification of seizure types,generalized seizures such as absence seizures(ASs)may originate from a focal point and rapidly spread to the bilaterally distributed brain network.Increasing evidence from animal and clinical studies has indicated that focal changes may occur prior to ASs;however,the relationship of ASs with epileptogenic lesions remains unclear.Methods We retrospectively collected and analyzed the clinical,imaging,and electrophysiological data of 16 patients who had ASs and structural lesions with seizure-free outcomes after lesion resection.Results In semiology analysis,nine patients displayed focal onset;only two patients showed simple ASs,and seizure types other than ASs were observed in the remaining patients.On ictal electroencephalography(EEG),four patients showed bilateral synchronous symmetric 3 Hz generalized spike-wave discharges(GSWDs),and the remaining patients showed bilateral 1.5–2.5 Hz GSWDs.Moreover,most patients(13/16,81.3%)exhibited focal features in addition to ASs,while interictal EEG was the same in 12 patients.Furthermore,on stereoelectroencephalogram(SEEG),2/5 patients showed focal discharges before bilateral burst GSWDs.Additionally,all patients had structural lesions on imaging.In four typical AS patients,the lesions were located in deep brain regions.Notably,in 9 patients(9/16,56%),the lesions were located in the posterior cortex.All patients underwent lesion resection and had seizure-free outcomes during follow-up,and intelligence quotient(IQ)also improved by 10.71±3.90 one year after surgery.Conclusions Patients with lesion-related epilepsy may present with ASs that have a focal onset and are associated with good surgical outcomes.

Classification of epilepsy using computational intelligence techniques

This paper deals with a real-life application of epilepsy classification, where three phases of absence seizure, namely pre-seizure, seizure and seizure-free, are classified using real clinical data. Artificial neural network （ANN） and support vector machines （SVMs） combined with su- pervised learning algorithms, and k-means clustering （k-MC） combined with unsupervised techniques are employed to classify the three seizure phases. Different techniques to combine binary SVMs, namely One Vs One （OvO）, One Vs All （OVA） and Binary Decision Tree （BDT）, are employed for multiclass classification. Comparisons are performed with two traditional classification methods, namely, k-Nearest Neighbour （k- NN） and Naive Bayes classifier. It is concluded that SVM-based classifiers outperform the traditional ones in terms of recognition accuracy and robustness property when the original clinical data is distorted with noise. Furthermore, SVM-based classifier with OvO provides the highest recognition accuracy, whereas ANN-based classifier overtakes by demonstrating maximum accuracy in the presence of noise.