Qualitative Analysis of Decision to Pursue Electrical Brain Stimulation by Patients With Drug-Resistant Epilepsy and Their Caregivers.

Background and Objectives: To understand why patients with drug-resistant epilepsy (DRE) pursue invasive electrical brain stimulation (EBS). Methods: We interviewed patients with DRE (n = 20) and their caregivers about their experiences in pursuing EBS approximately 1 year post device implant. Inductive analysis was applied to identify key motivating factors. Results: The cohort included participants aged from teens to 50s with deep brain stimulation, vagus nerve stimulation, responsive neurostimulation, and chronic subthreshold cortical stimulation. Patients' motivations included (1) improved quality of life (2) intolerability of antiseizure medications, (3) desperation, and (4) patient-family dynamics. Both patients and caregivers described a desire to alleviate burdens of the other. Patient apprehensions about EBS focused on invasiveness and the presence of electrodes in the brain. Previous experiences with invasive monitoring and the ability to see hardware in person during clinical visits influenced patients' comfort in proceeding with EBS. Despite realistic expectations for modest and delayed benefits, patients held out hope for an exceptionally positive outcome. Discussion: Our findings describe the motivations and decision-making process for patients with DRE who pursue invasive EBS. Patients balance feelings of desperation, personal goals, frustration with medication side effects, fears about surgery, and potential pressure from concerned caregivers. These factors together with the sense that patients have exhausted therapeutic alternatives may explain the limited decisional ambivalence observed in this cohort. These themes highlight opportunities for epilepsy care teams to support patient decision-making processes.

Pathogenic gating pore current conducted by autism-related mutations in the NaV1.2 brain sodium channel.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by social and communication deficits and repetitive behaviors. The genetic heterogeneity of ASD presents a challenge to the development of an effective treatment targeting the underlying molecular defects. ASD gating charge mutations in the KCNQ/KV7 potassium channel cause gating pore currents (Igp) and impair action potential (AP) firing of dopaminergic neurons in brain slices. Here, we investigated ASD gating charge mutations of the voltage-gated SCN2A/NaV1.2 brain sodium channel, which ranked high among the ion channel genes with mutations in individuals with ASD. Our results show that ASD mutations in the gating charges R2 in Domain-II (R853Q), and R1 (R1626Q) and R2 (R1629H) in Domain-IV of NaV1.2 caused Igp in the resting state of ~0.1% of the amplitude of central pore current. The R1626Q mutant also caused significant changes in the voltage dependence of fast inactivation, and the R1629H mutant conducted proton-selective Igp. These potentially pathogenic Igp were exacerbated by the absence of the extracellular Mg2+ and Ca2+. In silico simulation of the effects of these mutations in a conductance-based single-compartment cortical neuron model suggests that the inward Igp reduces the time to peak for the first AP in a train, increases AP rates during a train of stimuli, and reduces the interstimulus interval between consecutive APs, consistent with increased neural excitability and altered input/output relationships. Understanding this common pathophysiological mechanism among different voltage-gated ion channels at the circuit level will give insights into the underlying mechanisms of ASD.

A platform for brain network sensing and stimulation with quantitative behavioral tracking: Application to limbic circuit epilepsy.

Temporal lobe epilepsy is a common neurological disease characterized by recurrent seizures. These seizures often originate from limbic networks and people also experience chronic comorbidities related to memory, mood, and sleep (MMS). Deep brain stimulation targeting the anterior nucleus of the thalamus (ANT-DBS) is a proven therapy, but the optimal stimulation parameters remain unclear. We developed a neurotechnology platform for tracking seizures and MMS to enable data streaming between an investigational brain sensing-stimulation implant, mobile devices, and a cloud environment. Artificial Intelligence algorithms provided accurate catalogs of seizures, interictal epileptiform spikes, and wake-sleep brain states. Remotely administered memory and mood assessments were used to densely sample cognitive and behavioral response during ANT-DBS. We evaluated the efficacy of low-frequency versus high-frequency ANT-DBS. They both reduced seizures, but low-frequency ANT-DBS showed greater reductions and better sleep and memory. These results highlight the potential of synchronized brain sensing and behavioral tracking for optimizing neuromodulation therapy.

Impedance Rhythms in Human Limbic System.

The impedance is a fundamental electrical property of brain tissue, playing a crucial role in shaping the characteristics of local field potentials, the extent of ephaptic coupling, and the volume of tissue activated by externally applied electrical brain stimulation. We tracked brain impedance, sleep-wake behavioral state, and epileptiform activity in five people with epilepsy living in their natural environment using an investigational device. The study identified impedance oscillations that span hours to weeks in the amygdala, hippocampus, and anterior nucleus thalamus. The impedance in these limbic brain regions exhibit multiscale cycles with ultradian (∼1.5-1.7 h), circadian (∼21.6-26.4 h), and infradian (∼20-33 d) periods. The ultradian and circadian period cycles are driven by sleep-wake state transitions between wakefulness, nonrapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. Limbic brain tissue impedance reaches a minimum value in NREM sleep, intermediate values in REM sleep, and rises through the day during wakefulness, reaching a maximum in the early evening before sleep onset. Infradian (∼20-33 d) impedance cycles were not associated with a distinct behavioral correlate. Brain tissue impedance is known to strongly depend on the extracellular space (ECS) volume, and the findings reported here are consistent with sleep-wake-dependent ECS volume changes recently observed in the rodent cortex related to the brain glymphatic system. We hypothesize that human limbic brain ECS changes during sleep-wake state transitions underlie the observed multiscale impedance cycles. Impedance is a simple electrophysiological biomarker that could prove useful for tracking ECS dynamics in human health, disease, and therapy.SIGNIFICANCE STATEMENT The electrical impedance in limbic brain structures (amygdala, hippocampus, anterior nucleus thalamus) is shown to exhibit oscillations over multiple timescales. We observe that impedance oscillations with ultradian and circadian periodicities are associated with transitions between wakefulness, NREM, and REM sleep states. There are also impedance oscillations spanning multiple weeks that do not have a clear behavioral correlate and whose origin remains unclear. These multiscale impedance oscillations will have an impact on extracellular ionic currents that give rise to local field potentials, ephaptic coupling, and the tissue activated by electrical brain stimulation. The approach for measuring tissue impedance using perturbational electrical currents is an established engineering technique that may be useful for tracking ECS volume.

Correction: Neural adaptation and fractional dynamics as a window to underlying neural excitability.

[This corrects the article DOI: 10.1371/journal.pcbi.1010527.].

Emerging approaches in neurostimulation for epilepsy.

PURPOSE OF REVIEW: Neurostimulation is a quickly growing treatment approach for epilepsy patients. We summarize recent approaches to provide a perspective on the future of neurostimulation. RECENT FINDINGS: Invasive stimulation for treatment of focal epilepsy includes vagus nerve stimulation, responsive neurostimulation of the cortex and deep brain stimulation of the anterior nucleus of the thalamus. A wide range of other targets have been considered, including centromedian, central lateral and pulvinar thalamic nuclei; medial septum, nucleus accumbens, subthalamic nucleus, cerebellum, fornicodorsocommissure and piriform cortex. Stimulation for generalized onset seizures and mixed epilepsies as well as increased efforts focusing on paediatric populations have emerged. Hardware with more permanently implanted lead options and sensing capabilities is emerging. A wider variety of programming approaches than typically used may improve patient outcomes. Finally, noninvasive brain stimulation with its favourable risk profile offers the potential to treat increasingly diverse epilepsy patients. SUMMARY: Neurostimulation for the treatment of epilepsy is surprisingly varied. Flexibility and reversibility of neurostimulation allows for rapid innovation. There remains a continued need for excitability biomarkers to guide treatment and innovation. Neurostimulation, a part of bioelectronic medicine, offers distinctive benefits as well as unique challenges.

Neural adaptation and fractional dynamics as a window to underlying neural excitability.

The relationship between macroscale electrophysiological recordings and the dynamics of underlying neural activity remains unclear. We have previously shown that low frequency EEG activity (<1 Hz) is decreased at the seizure onset zone (SOZ), while higher frequency activity (1-50 Hz) is increased. These changes result in power spectral densities (PSDs) with flattened slopes near the SOZ, which are assumed to be areas of increased excitability. We wanted to understand possible mechanisms underlying PSD changes in brain regions of increased excitability. We hypothesized that these observations are consistent with changes in adaptation within the neural circuit. We developed a theoretical framework and tested the effect of adaptation mechanisms, such as spike frequency adaptation and synaptic depression, on excitability and PSDs using filter-based neural mass models and conductance-based models. We compared the contribution of single timescale adaptation and multiple timescale adaptation. We found that adaptation with multiple timescales alters the PSDs. Multiple timescales of adaptation can approximate fractional dynamics, a form of calculus related to power laws, history dependence, and non-integer order derivatives. Coupled with input changes, these dynamics changed circuit responses in unexpected ways. Increased input without synaptic depression increases broadband power. However, increased input with synaptic depression may decrease power. The effects of adaptation were most pronounced for low frequency activity (< 1Hz). Increased input combined with a loss of adaptation yielded reduced low frequency activity and increased higher frequency activity, consistent with clinical EEG observations from SOZs. Spike frequency adaptation and synaptic depression, two forms of multiple timescale adaptation, affect low frequency EEG and the slope of PSDs. These neural mechanisms may underlie changes in EEG activity near the SOZ and relate to neural hyperexcitability. Neural adaptation may be evident in macroscale electrophysiological recordings and provide a window to understanding neural circuit excitability.

Case Report: Prolonged Effects of Short-Term Transcranial Magnetic Stimulation on EEG Biomarkers, Spectral Power, and Seizure Frequency.

Transcranial magnetic stimulation (TMS) is a non-invasive modality of focal brain stimulation in which a fluctuating magnetic field induces electrical currents within the cortex. It remains unclear to what extent TMS alters EEG biomarkers and how EEG biomarkers may guide treatment of focal epilepsy. We present a case of a 48-year-old man with focal epilepsy, refractory to multiple medication trials, who experienced a dramatic reduction in seizures after targeting the area of seizure onset within the left parietal-occipital region with low-frequency repetitive TMS (rTMS). Prior to treatment, he experienced focal seizures that impacted cognition including apraxia at least 50-60 times daily. MRI of the brain showed a large focal cortical dysplasia with contrast enhancement involving the left occipital-parietal junction. Stimulation for 5 consecutive days was well-tolerated and associated with a day-by-day reduction in seizure frequency. In addition, he was monitored with continuous video EEG, which showed continued and progressive changes in spectral power (decreased broadband power and increased infraslow delta activity) and a gradual reduction in seizure frequency and duration. One month after initial treatment, 2-day ambulatory EEG demonstrated seizure-freedom and MRI showed resolution of focal contrast enhancement. He continues to receive 2-3 days of rTMS every 2-4 months. He was seizure-free for 6 months, and at last follow-up of 17 months was experiencing auras approximately every 2 weeks without progression to disabling seizures. This case demonstrates that rTMS can be a well-tolerated and effective means of controlling medication-refractory seizures, and that EEG biomarkers change gradually in a fashion in association with seizure frequency. TMS influences cortical excitability, is a promising non-invasive means of treating focal epilepsy, and has measurable electrophysiologic effects.

Electrical brain stimulation and continuous behavioral state tracking in ambulatory humans.

Objective.Electrical deep brain stimulation (DBS) is an established treatment for patients with drug-resistant epilepsy. Sleep disorders are common in people with epilepsy, and DBS may actually further disturb normal sleep patterns and sleep quality. Novel implantable devices capable of DBS and streaming of continuous intracranial electroencephalography (iEEG) signals enable detailed assessments of therapy efficacy and tracking of sleep related comorbidities. Here, we investigate the feasibility of automated sleep classification using continuous iEEG data recorded from Papez's circuit in four patients with drug resistant mesial temporal lobe epilepsy using an investigational implantable sensing and stimulation device with electrodes implanted in bilateral hippocampus (HPC) and anterior nucleus of thalamus (ANT).Approach.The iEEG recorded from HPC is used to classify sleep during concurrent DBS targeting ANT. Simultaneous polysomnography (PSG) and sensing from HPC were used to train, validate and test an automated classifier for a range of ANT DBS frequencies: no stimulation, 2 Hz, 7 Hz, and high frequency (>100 Hz).Main results.We show that it is possible to build a patient specific automated sleep staging classifier using power in band features extracted from one HPC iEEG sensing channel. The patient specific classifiers performed well under all thalamic DBS frequencies with an average F1-score 0.894, and provided viable classification into awake and major sleep categories, rapid eye movement (REM) and non-REM. We retrospectively analyzed classification performance with gold-standard PSG annotations, and then prospectively deployed the classifier on chronic continuous iEEG data spanning multiple months to characterize sleep patterns in ambulatory patients living in their home environment.Significance.The ability to continuously track behavioral state and fully characterize sleep should prove useful for optimizing DBS for epilepsy and associated sleep, cognitive and mood comorbidities.

EEG source imaging concordance with intracranial EEG and epileptologist review in focal epilepsy.

EEG source imaging is becoming widely used for the evaluation of medically refractory focal epilepsy. The validity of EEG source imaging has been established in several studies comparing source imaging to the surgical resection cavity and subsequent seizure freedom. We present a cohort of 87 patients and compare EEG source imaging of both ictal and interictal scalp EEG to the seizure onset zone on intracranial EEG. Concordance of EEG source imaging with intracranial EEG was determined on a sublobar level and was quantified by measuring the distance between the source imaging result and the centroid of the active seizure onset zone electrodes. The EEG source imaging results of a subgroup of 26 patients with high density 76-channel EEG were compared with the localization of three experienced epileptologists. Of 87 patients, 95% had at least one analysis concordant with intracranial EEG and 74% had complete concordance. There was a higher rate of complete concordance in temporal lobe epilepsy compared to extratemporal (89.3 and 62.8%, respectively, P = 0.015). Of the total 282 analyses performed on this cohort, higher concordance was also seen in temporal discharges (95%) compared to extratemporal (77%) (P = 0.0012), but no difference was seen comparing high-density EEG with standard (32-channel) EEG. Subgroup analysis of ictal waveforms showed greater concordance for ictal spiking, compared with rhythmic activity, paroxysmal fast activity, or obscured onset. Median distances from the dipole and maximum distributed source to a centroid of seizure onset zone electrodes were 30.0 and 32.5 mm, respectively, and the median distances from dipole and maximum distributed source to nearest seizure onset zone electrode were 22.8 and 21.7, respectively. There were significantly shorter distances in ictal spiking. There were shorter distances in patients with Engel Class 1 outcome from surgical resection compared to patients with worse outcomes. For the subgroup of 26 high-density EEG patients, EEG source localization had a significantly higher concordance (92% versus 65%), sensitivity (57% versus 35%) and positive predictive value (60% versus 36%) compared with epileptologist localization. Our study demonstrates good concordance between ictal and interictal source imaging and intracranial EEG. Temporal lobe discharges have higher concordance rates than extratemporal discharges. Importantly, this study shows that source imaging has greater agreement with intracranial EEG than visual review alone, supporting its role in surgical planning.

Low frequency novel interictal EEG biomarker for localizing seizures and predicting outcomes.

Localizing hyperexcitable brain tissue to treat focal seizures remains challenging. We want to identify the seizure onset zone from interictal EEG biomarkers. We hypothesize that a combination of interictal EEG biomarkers, including a novel low frequency marker, can predict mesial temporal involvement and can assist in prognosis related to surgical resections. Interictal direct current wide bandwidth invasive EEG recordings from 83 patients implanted with 5111 electrodes were retrospectively studied. Logistic regression was used to classify electrodes and patient outcomes. A feed-forward neural network was implemented to understand putative mechanisms. Interictal infraslow frequency EEG activity was decreased for seizure onset zone electrodes while faster frequencies such as delta (2-4 Hz) and beta-gamma (20-50 Hz) activity were increased. These spectral changes comprised a novel interictal EEG biomarker that was significantly increased for mesial temporal seizure onset zone electrodes compared to non-seizure onset zone electrodes. Interictal EEG biomarkers correctly classified mesial temporal seizure onset zone electrodes with a specificity of 87% and positive predictive value of 80%. These interictal EEG biomarkers also correctly classified patient outcomes after surgical resection with a specificity of 91% and positive predictive value of 87%. Interictal infraslow EEG activity is decreased near the seizure onset zone while higher frequency power is increased, which may suggest distinct underlying physiologic mechanisms. Narrowband interictal EEG power bands provide information about the seizure onset zone and can help predict mesial temporal involvement in seizure onset. Narrowband interictal EEG power bands may be less useful for predictions related to non-mesial temporal electrodes. Together with interictal epileptiform discharges and high-frequency oscillations, these interictal biomarkers may provide prognostic information prior to surgical resection. Computational modelling suggests changes in neural adaptation may be related to the observed low frequency power changes.

Anterior Nucleus of the Thalamus Deep Brain Stimulation with Concomitant Vagus Nerve Stimulation for Drug-Resistant Epilepsy.

BACKGROUND: The Food and Drug Administration approved the deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) as an adjunctive therapy for drug-resistant epilepsy (DRE) in the United States in 2018. The DBS Therapy for Epilepsy Post-Approval Study is further evaluating the safety and effectiveness of ANT-DBS among different patients' groups. For this study, devices for vagus nerve stimulation (VNS) must be removed prior to enrolment. OBJECTIVE: To investigate the outcomes of concomitant ANT-DBS and VNS treatment for DRE. METHODS: A retrospective analysis was performed for 33 patients who underwent ANT-DBS using previous VNS to define distinct subgroups: standard ANT-DBS (9 subjects), ANT-DBS with functional VNS (12 subjects), and ANT-DBS with the VNS implantable pulse generator explanted or turned off at the time of the DBS (12 subjects). Effectiveness and safety data were analyzed across the whole population and among subgroups. RESULTS: A mean decrease in seizure frequency of 55% was observed after a mean follow-up of 25.5 mo. Approximately 67% of patients experienced ≥50% reduction in seizure frequency. Seizure reduction percentage was not significantly different among groups. Approximately 50% of subjects with no appreciable improvement and 75% of those who showed benefit after VNS (including improvement in seizure frequency, seizure severity, and seizure duration or quality of life) achieved a seizure reduction ≥50% after ANT-DBS surgery. There were no complications related to concomitant VNS and ANT-DBS. CONCLUSION: ANT-DBS for DRE provides excellent results despite previous and ongoing VNS therapy. Removal of VNS does not appear to be necessary before ANT-DBS.

Invasive Electrophysiology for Circuit Discovery and Study of Comorbid Psychiatric Disorders in Patients With Epilepsy: Challenges, Opportunities, and Novel Technologies.

Intracranial electroencephalographic (iEEG) recordings from patients with epilepsy provide distinct opportunities and novel data for the study of co-occurring psychiatric disorders. Comorbid psychiatric disorders are very common in drug-resistant epilepsy and their added complexity warrants careful consideration. In this review, we first discuss psychiatric comorbidities and symptoms in patients with epilepsy. We describe how epilepsy can potentially impact patient presentation and how these factors can be addressed in the experimental designs of studies focused on the electrophysiologic correlates of mood. Second, we review emerging technologies to integrate long-term iEEG recording with dense behavioral tracking in naturalistic environments. Third, we explore questions on how best to address the intersection between epilepsy and psychiatric comorbidities. Advances in ambulatory iEEG and long-term behavioral monitoring technologies will be instrumental in studying the intersection of seizures, epilepsy, psychiatric comorbidities, and their underlying circuitry.

Centromedian thalamic nucleus with or without anterior thalamic nucleus deep brain stimulation for epilepsy in children and adults: A retrospective case series.

The centromedian (CM) and anterior nucleus of the thalamus (ANT) are deep brain stimulation (DBS) targets for management of generalized, and focal drug resistant epilepsy (DRE), respectively. We report on a single center retrospective case series of 16 children and adults with DRE who underwent CM with simultaneous ANT (69 %) or CM without simultaneous ANT DBS (31 %). Seizure frequency, epilepsy severity, life satisfaction, and quality of sleep before and after DBS were compared. Baseline median seizure frequency was 323 seizures per month (IQR, 71-563 sz/mo). Median follow up time was 80 months (IQR 37-97 mo). Median seizure frequency reduction was 58 % (IQR 13-87 %, p = 0.002). Ten patients (63 %) reported ≥50 % seizure frequency reduction. Median seizure frequency reduction and responder rate were not significantly different for CM + ANT versus CM only. Seizure severity and life satisfaction were significantly improved. Three patients (19 %) developed device-related side effects, 2 of them (12.5 %) required surgical intervention. In a heterogenous population of children and adults with generalized, multifocal, posterior onset, and poorly localized DRE, CM with or without ANT DBS is feasible, relatively safe and is associated with reduced seizure frequency and severity, as well as improved life satisfaction.

Cortical and thalamic electrode implant followed by temporary continuous subthreshold stimulation yields long-term seizure freedom: A case report.

Neuromodulation strategies that target the epileptogenic network are options for treating focal drug-resistant epilepsy. These brain stimulation approaches include responsive neurostimulation and more recently, chronic subthreshold stimulation. Long-term seizure freedom with neuromodulation is uncommon. Seizure control typically requires ongoing froms of electrical stimulation. Here, we present the case of a patient implanted with three cortical electrodes targeting the inferior frontal lobe, insula, and one subcortical electrode targeting the ipsilateral anterior thalamic nucleus. This patient received continuous subthreshold electrical stimulation to the frontal electrodes for 7 months, at which time stimulation was inadvertently stopped. He has now been free of seizures for 42 months. This case suggests the possibility that neuromodulation can alter epileptogenic networks and lead to seizure freedom without ongoing electrical stimulation.

Chronic subthreshold cortical stimulation and stimulation-related EEG biomarkers for focal epilepsy.

Brain stimulation offers an alternative to focal resection for the treatment of focal drug-resistant epilepsy. Chronic subthreshold cortical stimulation is an individualized biomarker-informed open-loop continuous electrical stimulation approach targeting the seizure onset zone and surrounding areas. Before permanent implantation, trial stimulation is performed during invasive monitoring to assess stimulation efficacy as well as to optimize stimulation location and parameters by modifying interictal EEG biomarkers. We present clinical and neurophysiological results from a retrospective analysis of 21 patients, showing a median percent reduction in seizure frequency of 100% and responder rate of 89% with a median follow-up of 27 months. About 40% of patients were free of disabling seizures for a 12-month period or longer. We find that stimulation-induced decreases in delta (1-4 Hz) power and increases in alpha and beta (8-20 Hz) power during trial stimulation correlate with improved long-term clinical outcomes. These results suggest chronic subthreshold cortical stimulation may be an effective alternative approach to treating focal drug-resistant epilepsy and that short-term stimulation-related changes in spectral power may be a useful interictal biomarker and relate to long-term clinical outcome.

A Review of Neurostimulation for Epilepsy in Pediatrics.

Neurostimulation for epilepsy refers to the application of electricity to affect the central nervous system, with the goal of reducing seizure frequency and severity. We review the available evidence for the use of neurostimulation to treat pediatric epilepsy, including vagus nerve stimulation (VNS), responsive neurostimulation (RNS), deep brain stimulation (DBS), chronic subthreshold cortical stimulation (CSCS), transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). We consider possible mechanisms of action and safety concerns, and we propose a methodology for selecting between available options. In general, we find neurostimulation is safe and effective, although any high quality evidence applying neurostimulation to pediatrics is lacking. Further research is needed to understand neuromodulatory systems, and to identify biomarkers of response in order to establish optimal stimulation paradigms.