The Effectiveness of Vagus Nerve Stimulation in Drug-Resistant Epilepsy Correlates with Vagus Nerve Stimulation-Induced Electroencephalography Desynchronization

Brainstem neuronal responses to transcutaneous auricular and cervical vagus nerve stimulation in rats

Transcutaneous auricular vagus nerve stimulation (taVNS) targets subcutaneous axons in the auricular branch of the vagus nerve at the outer ear. Its non-invasive nature makes it a potential treatment for various disorders. taVNS induces neuromodulatory effects within the nucleus of the solitary tract (NTS), and due to its widespread connectivity, the NTS acts as a gateway to elicit neuromodulation in both higher-order brain regions and other brainstem nuclei (e.g. spinal trigeminal nucleus; Sp5). Our objective was to examine stimulation parameters on single-neuron electrophysiological responses in α-chloralose-anaesthetized Sprague-Dawley rats within NTS and Sp5. taVNS was also compared to traditional cervical VNS (cVNS) on single neuronal activation. Specifically, electrophysiological extracellular recordings were evaluated for a range of frequency and intensity parameters (20-250 Hz, 0.5-1.0 mA). Neurons were classified as positive, negative or non-responders based on increased activity, decreased activity or no response during stimulation, respectively. Frequency-dependent analysis showed that 20 and 100 Hz generated the highest proportion of positive responders in NTS and Sp5 with 1.0 mA intensities eliciting the greatest magnitude of response. Comparisons between taVNS and cVNS revealed similar parameter-specific activation for caudal NTS neuronal populations; however, individual neurons showed different activation profiles. The latter suggests that cVNS and taVNS send afferent input to NTS via different neuronal pathways. This study demonstrates differential parameter-specific taVNS responses and begins an investigation of the mechanisms responsible for taVNS modulation. Understanding the neuronal pathways responsible for eliciting neuromodulatory effects will enable more tailored taVNS treatments in various clinical disorders. KEY POINTS: Transcutaneous auricular vagus nerve stimulation (taVNS) offers a non-invasive alternative to invasive cervical vagus nerve stimulation (cVNS) by activating vagal afferents in the ear to induce neuromodulation. Our study evaluated taVNS effects on neuronal firing patterns in the nucleus of the solitary tract (NTS) and spinal trigeminal nucleus (Sp5) and found that 20 and 100 Hz notably increased neuronal activity during stimulation in both nuclei. Increasing taVNS intensity not only increased the number of neurons responding in Sp5 but also increased the magnitude of response, suggesting a heightened sensitivity to taVNS compared to NTS. Comparisons between cVNS and taVNS revealed similar overall activation but different responses on individual neurons, indicating distinct neural pathways. These results show parameter-specific and nuclei-specific responses to taVNS and confirm that taVNS can elicit responses comparable to cVNS at the neuronal level, but it does so through different neuronal pathways.

Vagus Nerve Stimulation Therapy in Epilepsy: An Overview of Technical and Surgical Method, Patient Selection, and Treatment Outcomes

Epilepsy affects over 65 million people worldwide. One-third of people with epilepsy do not respond to medication and may benefit from surgery. Vagus nerve stimulation (VNS) is the first neuromodulation therapy for the treatment of drug-resistant epilepsy. This method is used in combination with anti-seizure medications in adults and in the pediatric population. VNS has also been demonstrated to have benefits for some epilepsy comorbidities, such as depression, and can be used in combination with other neuromodulation therapies in epilepsy. The authors present an overview of VNS physiology, patient selection, surgery and risks, neuromodulation therapy, and application to epilepsy comorbidities.

A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy

AIMS

To predict the vagus nerve stimulation (VNS) efficacy for pediatric drug-resistant epilepsy (DRE) patients, we aim to identify preimplantation biomarkers through clinical features and electroencephalogram (EEG) signals and thus establish a predictive model from a multi-modal feature set with high prediction accuracy.

METHODS

Sixty-five pediatric DRE patients implanted with VNS were included and followed up. We explored the topological network and entropy features of preimplantation EEG signals to identify the biomarkers for VNS efficacy. A Support Vector Machine (SVM) integrated these biomarkers to distinguish the efficacy groups.

RESULTS

The proportion of VNS responders was 58.5% (38/65) at the last follow-up. In the analysis of parieto-occipital α band activity, higher synchronization level and nodal efficiency were found in responders. The central-frontal θ band activity showed significantly lower entropy in responders. The prediction model reached an accuracy of 81.5%, a precision of 80.1%, and an AUC (area under the receiver operating characteristic curve) of 0.838.

CONCLUSION

Our results revealed that, compared to nonresponders, VNS responders had a more efficient α band brain network, especially in the parieto-occipital region, and less spectral complexity of θ brain activities in the central-frontal region. We established a predictive model integrating both preimplantation clinical and EEG features and exhibited great potential for discriminating the VNS responders. This study contributed to the understanding of the VNS mechanism and improved the performance of the current predictive model.

Rapid eye movement sleep and epilepsy: exploring interactions and therapeutic prospects

While research interest in the relationship between sleep and epilepsy is growing, it primarily centres on the effects of non-rapid eye movement (NREM) sleep in favouring seizures. Nonetheless, a noteworthy aspect is the observation that, in the lives of patients with epilepsy, REM sleep represents the moment with the least epileptic activity and the lowest probability of having a seizure. Studies demonstrate a suppressive effect of phasic REM sleep on interictal epileptiform discharges, potentially offering insights into epilepsy localisation and management. Furthermore, epilepsy impacts REM sleep, with successful treatment correlating with improved REM sleep quality. Novel therapeutic strategies aim to harness REM's anti-epileptic effects, including pharmacological approaches targeting orexinergic systems and neuromodulation techniques promoting cortical desynchronisation. These findings underscore the intricate relationship between REM sleep and epilepsy, highlighting avenues for further research and therapeutic innovation in epilepsy management.

High-definition transcranial direct current stimulation desynchronizes refractory status epilepticus

Recently, we showed that high-definition transcranial direct current stimulation (hd-tDCS) can acutely reduce epileptic spike rates during and after stimulation in refractory status epilepticus (RSE), with a greater likelihood of patient discharge from the intensive care unit compared to historical controls. We investigate whether electroencephalographic (EEG) desynchronization during hd-tDCS can help account for observed anti-epileptic effects. Defining desynchronization as greater power in higher frequencies such as above 30 ​Hz ("gamma") and lesser power in frequency bands lower than 30 ​Hz, we analyzed 27 EEG sessions from 10 RSE patients who had received 20-minute session(s) of 2-milliamperes of transcranial direct current custom-targeted at the epileptic focus as previously determined by a clinical EEGer monitoring the EEG in real-time. During hd-tDCS, median relative power change over the EEG electrode chains in which power changes were maximal was +4.84%, -5.25%, -1.88%, -1.94%, and +4.99% for respective delta, theta, alpha, beta, and gamma frequency bands in the bipolar longitudinal montage (p ​= ​0.0001); and +4.13%, -5.44%, -1.81%, -3.23%, and +5.41% in the referential Laplacian montage (p ​= ​0.0012). After hd-tDCS, median relative power changes reversed over the EEG electrode chains in which power changes were maximal: -2.74%, +4.20%, +1.74%, +1.75%, and -4.68% for the respective delta, theta, alpha, beta, and gamma frequency bands in the bipolar longitudinal montage (p ​= ​0.0001); and +1.59%, +5.07%, +1.74%, +2.40%, and -5.12% in the referential Laplacian montage (p ​= ​0.0004). These findings are consistent with EEG desynchronization through theta-alpha-beta-gamma bands during hd-tDCS, helping account for the efficacy of hd-tDCS as an emerging novel anti-epileptic therapy against RSE.

Right-sided vagus nerve stimulation for drug-resistant epilepsy: A systematic review of the literature and perspectives

BACKGROUND

Right-sided vagus nerve stimulation (RS-VNS) is indicated when the procedure was deemed not technically feasible or too risky on the indicated left side.

OBJECTIVE

The present study aims to systematically review the literature on RS-VNS, assessing its effectiveness and safety.

METHODS

A systematic review following PRISMA guidelines was conducted: Pubmed/MEDLINE, The Cochrane Library, Scopus, Embase and Web of science databases were searched from inception to August 13th,2023. Gray literature was searched in two libraries. Eligible studies included all studies reporting, at least, one single case of RS-VNS in patients for the treatment of drug-resistant epilepsy.

RESULTS

Out of 2333 initial results, 415 studies were screened by abstract. Only four were included in the final analysis comprising seven patients with RS-VNS for a drug-resistant epilepsy. One patient experienced nocturnal asymptomatic bradycardia whereas the other six patients did not display any cardiac symptom. RS-VNS was discontinued in one case due to exercise-induced airway disease exacerbation. Decrease of epileptic seizure frequency after RS-VNS ranged from 25 % to 100 % in six cases. In the remaining case, VNS effectiveness was unclear. In one case, RS-VNS was more efficient than left-sided VNS (69 % vs 50 %, respectively) whereas in another case, RS-VNS was less efficient (50 % vs 95 %, respectively).

CONCLUSION

Literature on the present topic is limited. In six out of seven patients, RS-VNS for drug-resistant epilepsy displayed reasonable effectiveness with a low complication rate. Further research, including prospective studies, is necessary to assess safety and effectiveness of RS-VNS for drug-resistant epilepsy patients.

Acute Effect of Vagus Nerve Stimulation in Patients with Drug-Resistant Epilepsy: A Preliminary Exploration via Stereoelectroencephalogram

As the pathophysiological mechanisms of vagus nerve stimulation (VNS) causing individual differences in the vagal ascending network remains unclear, stereoelectroencephalography (SEEG) provides a unique platform to explore the brain networks affected by VNS and helps to understand the anti-seizure mechanism of VNS more comprehensively. This study presents a preliminary exploration of the acute effect of VNS. SEEG signals were collected to assess the acute effect of VNS on neural synchronization in patients with drug-resistant epilepsy, especially in epileptogenic networks. The results show that the better the efficacy of VNS, the wider the spread of desynchronization assessed by weighted phase lag index at a high frequency band caused by VNS. Future studies should focus on the association between the change in synchronization and the efficacy of VNS, exploring the possibility of synchronization as a biomarker for patient screening and parameter programming.

Role of Vagus Nerve Stimulation in Refractory and Super Refractory Status Epilepticus: A Pediatric Case Series

BACKGROUND

Status epilepticus is a life-threatening condition that is defined as refractory (RSE) when the seizure activity continues despite treatment with benzodiazepine and a second appropriate treatment. Super refractory status epilepticus (SRSE) is an RSE that persists or recurs for ≥24 h. Few papers have reported the outcomes of pediatric patients affected by RSE and SRSE and treated with neuromodulation therapies. Vagus nerve stimulation (VNS) is an approved treatment for drug-resistant epilepsy. We present our findings of pediatric patients treated with VNS for RSE/SRSE.

METHODS

We present a case series of seven consecutive pediatric patients treated with VNS for SRSE since 2012 by a single surgeon in Monza and Padua. A rapid titration was started soon after implantation. We considered electroclinical data before and after VNS implantation and at the last follow-up.

RESULTS

We achieved the resolution of SRSE in five out of seven patients in a mean time of two weeks. At the last follow-up, these patients had a significant reduction of seizure burden without any relapse of SE.

DISCUSSION AND CONCLUSIONS

Based on our limited findings, we discuss the potential role of VNS therapy in similar but distinct clinical contexts. For patients with drug-resistant epilepsy and RSE/SRSE, prompt VNS consideration is suggested, offering rapid responses and potentially reducing pharmacological load. Meanwhile, in NORSE/FIRES, we suggest early neuromodulation during the acute phase if standard treatments prove ineffective or not tolerated. This approach may leverage VNS's potential anti-inflammatory effects and neuromodulation, enhancing patient-specific treatments. Expanding case studies and prolonged follow-ups are recommended to strengthen these clinical insights.

Brain functional connectivity-based prediction of vagus nerve stimulation efficacy in pediatric pharmacoresistant epilepsy

OBJECTIVE

Although vagus nerve stimulation (VNS) is a common and widely used therapy for pharmacoresistant epilepsy, the reported efficacy of VNS in pediatric patients varies, so it is unclear which children will respond to VNS therapy. This study aimed to identify functional brain network features associated with VNS action to distinguish VNS responders from nonresponders using scalp electroencephalogram (EEG) data.

METHODS

Twenty-three children were included in this study, 16 in the discovery cohort and 7 in the test cohort. Using partial correlation value as a measure of whole-brain functional connectivity, we identified the differential edges between responders and nonresponders. Results derived from this were used as input to generate a support vector machine-learning classifier to predict VNS outcomes.

RESULTS

The postcentral gyrus in the left and right parietal lobe regions was identified as the most significant differential brain region between VNS responders and nonresponders (p < 0.001). The resultant classifier demonstrated a mean AUC value of 0.88, a mean sensitivity rate of 91.4%, and a mean specificity rate of 84.3% on fivefold cross-validation in the discovery cohort. In the testing cohort, our study demonstrated an AUC value of 0.91, a sensitivity rate of 86.6%, and a specificity rate of 79.3%. Furthermore, for prediction accuracy, our model can achieve 81.4% accuracy at the epoch level and 100% accuracy at the patient level.

SIGNIFICANCE

This study provides the first treatment response prediction model for VNS using scalp EEG data with ictal recordings and offers new insights into its mechanism of action. Our results suggest that brain functional connectivity features can help predict therapeutic response to VNS therapy. With further validation, our model could facilitate the selection of targeted pediatric patients and help avoid risky and costly procedures for patients who are unlikely to benefit from VNS therapy.

Entropy in scalp EEG can be used as a preimplantation marker for VNS efficacy

Vagus nerve stimulation (VNS) is a therapeutic option in drug-resistant epilepsy. VNS leads to ≥ 50% seizure reduction in 50 to 60% of patients, termed "responders". The remaining 40 to 50% of patients, "non-responders", exhibit seizure reduction < 50%. Our work aims to differentiate between these two patient groups in preimplantation EEG analysis by employing several Entropy methods. We identified 59 drug-resistant epilepsy patients treated with VNS. We established their response to VNS in terms of responders and non-responders. A preimplantation EEG with eyes open/closed, photic stimulation, and hyperventilation was found for each patient. The EEG was segmented into eight time intervals within four standard frequency bands. In all, 32 EEG segments were obtained. Seven Entropy methods were calculated for all segments. Subsequently, VNS responders and non-responders were compared using individual Entropy methods. VNS responders and non-responders differed significantly in all Entropy methods except Approximate Entropy. Spectral Entropy revealed the highest number of EEG segments differentiating between responders and non-responders. The most useful frequency band distinguishing responders and non-responders was the alpha frequency, and the most helpful time interval was hyperventilation and rest 4 (the end of EEG recording).

Alteration of Excitation/Inhibition Imbalance in the Hippocampus and Amygdala of Drug-Resistant Epilepsy Patients Treated with Acute Vagus Nerve Stimulation

An imbalance between excitation (E) and inhibition (I) in the brain has been identified as a key pathophysiology of epilepsy over the years. The hippocampus and amygdala in the limbic system play a crucial role in the initiation and conduction of epileptic seizures and are often referred to as the transfer station and amplifier of seizure activities. Existing animal and imaging studies reveal that the hippocampus and amygdala, which are significant parts of the vagal afferent network, can be modulated in order to generate an antiepileptic effect. Using stereo-electroencephalography (SEEG) data, we examined the E/I imbalance in the hippocampus and amygdala of ten drug-resistant epilepsy children treated with acute vagus nerve stimulation (VNS) by estimating the 1/f power slope of hippocampal and amygdala signals in the range of 1-80 Hz. While the change in the 1/f power slope from VNS-BASE varied between different stimulation amplitudes and brain regions, it was more prominent in the hippocampal region. In the hippocampal region, we found a flatter 1/f power slope during VNS-ON in patients with good responsiveness to VNS under the optimal stimulation amplitude, indicating that the E/I imbalance in the region was improved. There was no obvious change in 1/f power slope for VNS poor responders. For VNS non-responders, the 1/f power slope slightly increased when the stimulation was applied. Overall, this study implies that the regulation of E/I imbalance in the epileptic brain, especially in the hippocampal region, may be an acute intracranial effect of VNS.

Resting-state SEEG-based brain network analysis for the detection of epileptic area

BACKGROUND

Most epilepsy research is based on interictal or ictal functional connectivity. However, prolonged electrode implantation may affect patients' health and the accuracy of epileptic zone identification. Brief resting-state SEEG recordings reduce the observation of epileptic discharges by reducing electrode implantation and other seizure-inducing interventions.

NEW METHOD

The location coordinates of SEEG in the brain were identified using CT and MRI. Based on undirected brain network connectivity, five functional connectivity measures and data feature vector centrality were calculated. Network connectivity was calculated from multiple perspectives of linear correlation, information theory, phase, and frequency, and the relative influence of nodes on network connectivity was considered. We investigated the potential value of resting-state SEEG for epileptic zone identification by comparing the differences between epileptic and non-epileptic zones, as well as the differences between patients with different surgical outcomes.

RESULTS

By comparing the centrality of brain network connectivity between epileptic and non-epileptic zones, we found significant differences in the distribution of brain networks between the two zones. There was a significant difference in brain network between patients with good surgical outcomes and those with poor surgical outcomes (p < 0.01). By combining support vector machines with static node importance, we predicted an AUC of 0.94 ± 0.08 for the epilepsy zone.

CONCLUSIONS AND SIGNIFICANCE

The results illustrated that nodes in epileptic zones are distinct from those in non-epileptic zones. Analysis of resting-state SEEG data and the importance of nodes in the brain network may contribute to identifying the epileptic zone and predicting the outcome.

EEG: Current relevance and promising quantitative analyses

Electroencephalography (EEG) remains an essential tool, characterized by an excellent temporal resolution and offering a real window on cerebral functions. Surface EEG signals are mainly generated by the postsynaptic activities of synchronously activated neural assemblies. EEG is also a low-cost tool, easy to use at bed-side, allowing to record brain electrical activities with a low number or up to 256 surface electrodes. For clinical purpose, EEG remains a critical investigation for epilepsies, sleep disorders, disorders of consciousness. Its temporal resolution and practicability also make EEG a necessary tool for cognitive neurosciences and brain-computer interfaces. EEG visual analysis is essential in clinical practice and the subject of recent progresses. Several EEG-based quantitative analyses may complete the visual analysis, such as event-related potentials, source localizations, brain connectivity and microstates analyses. Some developments in surface EEG electrodes appear also, potentially promising for long term continuous EEGs. We overview in this article some recent progresses in visual EEG analysis and promising quantitative analyses.

Consciousness alteration in focal epilepsy is related to loss of signal complexity and information processing

Alteration of awareness is a main feature of focal epileptic seizures. In this work, we studied how the information contained in EEG signals was modified during temporal lobe seizures with altered awareness by using permutation entropy (PE) as a measure of the complexity of the signal. PE estimation was performed in thirty-six seizures of sixteen patients with temporal lobe epilepsy who underwent SEEG recordings. We tested whether altered awareness (based on the Consciousness Seizure Score) was correlated with a loss of signal complexity. We estimated global changes in PE as well as regional changes to gain insight into the mechanisms associated with awareness impairment. Our results reveal a positive correlation between the decrease of entropy and the consciousness score as well as the existence of a threshold on entropy that could discriminate seizures with no alteration of awareness from seizures with profound alteration of awareness. The loss of signal complexity was diffuse, extending bilaterally and to the associative cortices, in patients with profound alteration of awareness and limited to the temporal mesial structures in patients with no alteration of awareness. Thus PE is a promising tool to discriminate between the different subgroups of awareness alteration in TLE.

Development of localized interictal epileptiform discharges following vagus nerve stimulation for lennox-gastaut syndrome: a case report

Background

Lennox-gastaut syndrome (LGS) is an epileptic encephalopathy often associated with behavioral and psychiatric disorders. Vagus nerve stimulation (VNS) has been approved effective for LGS treatment. Surgical resection is also an option for LGS patients with focal pathology, offering a high probability of seizure control. However, it is challenging to accurately localize the seizure focus.

Case presentation

The case presented here is a 19-year-old male with a 16-year history of epilepsy with comorbid severe cognitive and psychiatric disorders. He was diagnosed with LGS due to generalized slow spike-wave discharges and multiple seizure types. He was treated with VNS in 2017 at the age of 15. After that, the frequency of the short tonic seizures decreased from 4–5 times per day to 2–5 times per year, and the generalized tonic–clonic seizure pattern did not recur, which had a frequency of 2–4 times per month before the surgery. In 2019, the generalized abnormal interictal epileptiform discharges changed to be localized in the right frontal–temporal lobe at the age of 17 years (2019).

Conclusions

This case report suggested that the generalized epileptiform discharges evolve into localized discharges after VNS treatment, which may help reveal the primary seizure focus for resection surgery in patients with LGS.

Interictal Functional Connectivity in Focal Refractory Epilepsies Investigated by Intracranial EEG

Introduction: Focal epilepsies are diseases of neuronal excitability affecting macroscopic networks of cortical and subcortical neural structures. These networks ("epileptogenic networks") can generate pathological electrophysiological activities during seizures, and also between seizures (interictal period). Many works attempt to describe these networks by using quantification methods, particularly based on the estimation of statistical relationships between signals produced by brain regions, namely functional connectivity (FC). Results: FC has been shown to be greatly altered during seizures and in the immediate peri-ictal period. An increasing number of studies have shown that FC is also altered during the interictal period depending on the degree of epileptogenicity of the structures. Furthermore, connectivity values could be correlated with other clinical variables including surgical outcome. Significance: This leads to a conceptual change and to consider epileptic areas as both hyperexcitable and abnormally connected. These data open the door to the use of interictal FC as a marker of epileptogenicity and as a complementary tool for predicting the effect of surgery. Aim: In this article, we review the available data concerning interictal FC estimated from intracranial electroencephalograhy (EEG) in focal epilepsies and discuss it in the light of data obtained from other modalities (EEG imaging) and modeling studies.

Estimated EEG functional connectivity and aperiodic component induced by vagal nerve stimulation in patients with drug-resistant epilepsy

Background

Vagal nerve stimulation (VNS) improves seizure frequency and quality of life in patients with drug-resistant epilepsy (DRE), although the exact mechanism is not fully understood. Previous studies have evaluated the effect of VNS on functional connectivity using the phase lag index (PLI), but none has analyzed its effect on EEG aperiodic parameters (offset and exponent), which are highly conserved and related to physiological functions.

Objective

This study aimed to evaluate the effect of VNS on PLI and aperiodic parameters and infer whether these changes correlate with clinical responses in subjects with DRE.

Materials and methods

PLI, exponent, and offset were derived for each epoch (and each frequency band for PLI), on scalp-derived 64-channel EEG traces of 10 subjects with DRE, recorded before and 1 year after VNS. PLI, exponent, and offset were compared before and after VNS for each patient on a global basis, individual scalp regions, and channels and separately in responders and non-responders. A correlation analysis was performed between global changes in PLI and aperiodic parameters and clinical response.

Results

PLI (global and regional) decreased after VNS for gamma and delta bands and increased for an alpha band in responders, but it was not modified in non-responders. Aperiodic parameters after VNS showed an opposite trend in responders vs. non-responders: both were reduced in responders after VNS, but they were increased in non-responders. Changes in aperiodic parameters correlated with the clinical response.

Conclusion

This study explored the action of VNS therapy from a new perspective and identified EEG aperiodic parameters as a new and promising method to analyze the efficacy of neuromodulation.

Latest Views on the Mechanisms of Action of Surgically Implanted Cervical Vagal Nerve Stimulation in Epilepsy

BACKGROUND

Vagus nerve stimulation (VNS) is approved as an adjunctive treatment for drug-resistant epilepsy. Although there is a substantial amount of literature aiming at unraveling the mechanisms of action of VNS in epilepsy, it is still unclear how the cascade of events triggered by VNS leads to its antiepileptic effect.

OBJECTIVE

In this review, we integrated available peer-reviewed data on the effects of VNS in clinical and experimental research to identify those that are putatively responsible for its therapeutic effect. The topic of transcutaneous VNS will not be covered owing to the current lack of data supporting the differences and commonalities of its mechanisms of action in relation to invasive VNS.

SUMMARY OF THE MAIN FINDINGS

There is compelling evidence that the effect is obtained through the stimulation of large-diameter afferent myelinated fibers that project to the solitary tract nucleus, then to the parabrachial nucleus, which in turn alters the activity of the limbic system, thalamus, and cortex. VNS-induced catecholamine release from the locus coeruleus in the brainstem plays a pivotal role. Functional imaging studies tend to point toward a common vagal network that comes into play, made up of the amygdalo-hippocampal regions, left thalamus, and insular cortex.

CONCLUSIONS

Even though some crucial pieces are missing, neurochemical, molecular, cellular, and electrophysiological changes occur within the vagal afferent network at three main levels (the brainstem, the limbic system [amygdala and hippocampus], and the cortex). At this final level, VNS notably alters functional connectivity, which is known to be abnormally high within the epileptic zone and was shown to be significantly decreased by VNS in responders. The effect of crucial VNS parameters such as frequency or current amplitude on functional connectivity metrics is of utmost importance and requires further investigation.

Transcranial current stimulation in epilepsy: A systematic review of the fundamental and clinical aspects

Purpose

Transcranial electrical current stimulation (tES or tCS, as it is sometimes referred to) has been proposed as non-invasive therapy for pharmacoresistant epilepsy. This technique, which includes direct current (tDCS) and alternating current (tACS) stimulation involves the application of weak currents across the cortex to change cortical excitability. Although clinical trials have demonstrated the therapeutic efficacy of tES, its specific effects on epileptic brain activity are poorly understood. We sought to summarize the clinical and fundamental effects underlying the application of tES in epilepsy.

Methods

A systematic review was performed in accordance with the PRISMA guidelines. A database search was performed in PUBMED, MEDLINE, Web of Science and Cochrane CENTRAL for articles corresponding to the keywords “epilepsy AND (transcranial current stimulation OR transcranial electrical stimulation)”.

Results

A total of 56 studies were included in this review. Through these records, we show that tDCS and tACS epileptic patients are safe and clinically relevant techniques for epilepsy. Recent articles reported changes of functional connectivity in epileptic patients after tDCS. We argue that tDCS may act by affecting brain networks, rather than simply modifying local activity in the targeted area. To explain the mechanisms of tES, various cellular effects have been identified. Among them, reduced cell loss, mossy fiber sprouting, and hippocampal BDNF protein levels. Brain modeling and human studies highlight the influence of individual brain anatomy and physiology on the electric field distribution. Computational models may optimize the stimulation parameters and bring new therapeutic perspectives.

Conclusion

Both tDCS and tACS are promising techniques for epilepsy patients. Although the clinical effects of tDCS have been repeatedly assessed, only one clinical trial has involved a consistent number of epileptic patients and little knowledge is present about the clinical outcome of tACS. To fill this gap, multicenter studies on tES in epileptic patients are needed involving novel methods such as personalized stimulation protocols based on computational modeling. Furthermore, there is a need for more in vivo studies replicating the tES parameters applied in patients. Finally, there is a lack of clinical studies investigating changes in intracranial epileptiform discharges during tES application, which could clarify the nature of tES-related local and network dynamics in epilepsy.

A prediction model integrating synchronization biomarkers and clinical features to identify responders to vagus nerve stimulation among pediatric patients with drug-resistant epilepsy

Aims

Vagus nerve stimulation (VNS) is a neuromodulation therapy for children with drug‐resistant epilepsy (DRE). The efficacy of VNS is heterogeneous. A prediction model is needed to predict the efficacy before implantation.

Methods

We collected data from children with DRE who underwent VNS implantation and received regular programming for at least 1 year. Preoperative clinical information and scalp video electroencephalography (EEG) were available in 88 children. Synchronization features, including phase lag index (PLI), weighted phase lag index (wPLI), and phase‐locking value (PLV), were compared between responders and non‐responders. We further adapted a support vector machine (SVM) classifier selected from 25 clinical and 18 synchronization features to build a prediction model for efficacy in a discovery cohort (n = 70) and was tested in an independent validation cohort (n = 18).

Results

In the discovery cohort, the average interictal awake PLI in the high beta band was significantly higher in responders than non‐responders (p < 0.05). The SVM classifier generated from integrating both clinical and synchronization features had the best prediction efficacy, demonstrating an accuracy of 75.7%, precision of 80.8% and area under the receiver operating characteristic (AUC) of 0.766 on 10‐fold cross‐validation. In the validation cohort, the prediction model demonstrated an accuracy of 61.1%.

Conclusion

This study established the first prediction model integrating clinical and baseline synchronization features for preoperative VNS responder screening among children with DRE. With further optimization of the model, we hope to provide an effective and convenient method for identifying responders before VNS implantation.

Prediction of the Responsiveness to Vagus-Nerve Stimulation in Patients with Drug-Resistant Epilepsy via Directed-Transfer-Function Analysis of Their Perioperative Scalp EEGs

This study aims to compare directed transfer function (DTF), which is an effective connectivity analysis, derived from scalp EEGs between responder and nonresponder groups implanted with vagus-nerve stimulation (VNS). Twelve patients with drug-resistant epilepsy (six responders and six nonresponders) and ten controls were recruited. A good response to VNS was defined as a reduction of ≥50% in seizure frequency compared with the presurgical baseline. DTF was calculated in five frequency bands (delta, theta, alpha, beta, and broadband) and seven grouped electrode regions (left and right frontal, temporal, parieto-occipital, and midline) in three different states (presurgical, stimulation-on, and stimulation-off states). Responders showed presurgical nodal strength close to the control group in both inflow and outflow, whereas nonresponders exhibited increased inward and outward connectivity measures. Nonresponders also had increased inward and outward connectivity measures in the various brain regions and various frequency bands assessed compared with the control group when the stimulation was on or off. Our study demonstrated that the presurgical DTF profiles of responders were different from those of nonresponders. Moreover, a presurgical normal DTF profile may predict good responsiveness to VNS.

Analysis of power spectrum and phase lag index changes following deep brain stimulation of the anterior nucleus of the thalamus in patients with drug-resistant epilepsy: A retrospective study

OBJECTIVES

The mechanisms underlying the anterior nucleus of the thalamus (ANT) deep brain stimulation (DBS) for the treatment of drug-resistant epilepsy (DRE) have not been fully explored. The present study aimed to measure the changes in whole-brain activity generated by ANT DBS using interictal electroencephalography (EEG).

MATERIALS AND METHODS

Interictal EEG signals were retrospectively collected in 20 DRE patients who underwent ANT DBS surgery. Patients were classified as responders or non-responders depending on their response to ANT DBS treatment. The power spectrum (PS) and Phase Lag Index (PLI) were determined and data analyzed using a paired sample t-test to evaluate activity differences between pre-and-post-treatment on different frequency categories. Student's t-test, Mann-Whitney test (non-parametric test) and Fisher exact test were used to compare groups in terms of clinical variables and EEG metrics. P values < 0.05 were considered statistically significant, and FDR-corrected values were used for multiple testing.

RESULTS

PS analysis revealed that whole-brain spectral power had a significant decrease in the beta (p = 0.005) and gamma (p = 0.037) bands following ANT DBS treatment in responders. The analysis of scalp topographic images of all patients showed that ANT DBS decreases PS in the beta band at the F3, F7 and Cz electrode sites. The findings indicated a decrease in PS in the gamma band at the Fp2, F3, Cz, T3, T5 and Oz electrode sites. After ANT DBS treatment, PLI analysis showed a significant decrease in PLI between Fp1 and T3 in the gamma band in responders.

CONCLUSION

The findings showed that ANT DBS induces a decrease in power in the left frontal lobe, left temporal lobe and midline areas in the beta and gamma bands. Lower whole-brain power in the beta and gamma bands can be used as biomarkers for a favorable therapeutic response to ANT DBS, and decreased synchronization between the left frontal pole and temporal lobe in the gamma band can also be used as a biomarker for effective clinical stimulation to guide postoperative programming.

Vagal Nerve Stimulation: The Effect on the Brain Oscillatory Field Potential

More than thirty years of medical treatment with the use of vagal nerve stimulation (VNS) has shown that this therapeutic procedure works in a number of homeostatic disturbances. Although the clinical usage of VNS has a long history, our knowledge about the central mechanisms underlying this treatment is still limited. In the present paper we review the effects of VNS on brain oscillations as a possible electrophysiological bio-marker of VNS efficacy. The review was prepared mainly on the basis of data delivered from clinical observations and the outcomes of electrophysiological experiments conducted on laboratory animals that are available in PubMed. We consciously did not focus on epileptiform activity understood as a pathologic oscillatory activity, which was widely discussed in the numerous previously published reviews. The main conclusion of the present paper is that further, well-designed experiments on laboratory animals are absolutely necessary to address the electrophysiological issues. These will fill a number of gaps in our present knowledge of the central mechanisms underlying VNS therapy.

Vagus Nerve Stimulation Elicits Sleep EEG Desynchronization and Network Changes in Responder Patients in Epilepsy

Neural desynchronization was shown as a key mechanism of vagus nerve stimulation (VNS) action in epilepsy, and EEG synchronization measures are explored as possible response biomarkers. Since brain functional organization in sleep shows different synchrony and network properties compared to wakefulness, we aimed to explore the effects of acute VNS on EEG-derived measures in the two different states of vigilance. EEG epochs were retrospectively analyzed from twenty-four VNS-treated epileptic patients (11 responders, 13 non-responders) in calm wakefulness and stage N2 sleep. Weighted Phase Lag Index (wPLI) was computed as connectivity measure of synchronization, for VNS OFF and VNS ON conditions. Global efficiency (GE) was computed as a network measure of integration. Ratios OFF/ON were obtained as desynchronization/de-integration index. Values were compared between responders and non-responders, and between EEG states. ROC curve and area-under-the-curve (AUC) analysis was performed for response classification. In responders, stronger VNS-induced theta desynchronization (p < 0.05) and decreased GE (p < 0.05) were found in sleep, but not in wakefulness. Theta sleep wPLI Ratio OFF/ON yielded an AUC of 0.825, and 79% accuracy as a response biomarker if a cut-off value is set at 1.05. Considering all patients, the VNS-induced GE decrease was significantly more important in sleep compared to awake EEG state (p < 0.01). In conclusion, stronger sleep EEG desynchronization in theta band distinguishes responders to VNS therapy from non-responders. VNS-induced reduction of network integration occurs significantly more in sleep than in wakefulness.

Vagus nerve stimulation in brain diseases: Therapeutic applications and biological mechanisms

Brain diseases, including neurodegenerative, cerebrovascular and neuropsychiatric diseases, have posed a deleterious threat to human health and brought a great burden to society and the healthcare system. With the development of medical technology, vagus nerve stimulation (VNS) has been approved by the Food and Drug Administration (FDA) as an alternative treatment for refractory epilepsy, refractory depression, cluster headaches, and migraines. Furthermore, current evidence showed promising results towards the treatment of more brain diseases, such as Parkinson's disease (PD), autistic spectrum disorder (ASD), traumatic brain injury (TBI), and stroke. Nonetheless, the biological mechanisms underlying the beneficial effects of VNS in brain diseases remain only partially elucidated. This review aims to delve into the relevant preclinical and clinical studies and update the progress of VNS applications and its potential mechanisms underlying the biological effects in brain diseases.