Neurostimulation for drug-resistant epilepsy: a systematic review of clinical evidence for efficacy, safety, contraindications and predictors for response

Boon, Paul; Cock, Elien De; Mertens, Ann C.; Trinka, Eugen

doi:10.1097/wco.0000000000000534

Cited by 88 publications

(67 citation statements)

References 96 publications

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“…Vagus nerve stimulation (VNS) has been successfully used to reduce epileptic seizures in patients with drug-resistant epilepsy since 1988 (Krahl and Clark, 2012) and is clinically effective for many patients treated with invasive VNS (Boon et al, 2018;Kwon et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Transcutaneous vagus nerve stimulation in humans induces pupil dilation and attenuates alpha oscillations

Sharon

Fahoum

Nir

2020

Preprint

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Vagus nerve stimulation (VNS) is widely used to treat drug-resistant epilepsy and depression. While the precise mechanisms mediating its long-term therapeutic effects are not fully resolved, they likely involve Locus Coeruleus (LC) stimulation via the nucleus of the solitary tract (NTS) that receives afferent vagal inputs. In rats, VNS elevates LC firing and forebrain noradrenaline (NE) levels, whereas LC lesions suppress VNS therapeutic efficacy. Non-invasive transcutaneous VNS (tVNS) employs electrical stimulation targeting the auricular branch of the vagus nerve at the Cymba Conchae of the ear, but it remains unclear to what extent tVNS mimics VNS. Here, we investigated the short-term effects of tVNS in healthy human male volunteers (n=24) using high-density EEG and pupillometry during visual fixation at rest, comparing short (3.4s) trials of tVNS to sham electrical stimulation at the earlobe (far from the vagus nerve branch) to control for somatosensory stimulation. Although tVNS and sham stimulation did not differ in subjective intensity ratings, tVNS led to robust pupil dilation (peaking 4-5s after trial onset) that was significantly higher than following sham stimulation. We further quantified how tVNS modulates idle occipital alpha (8-13Hz) activity, identified in each participant using parallel factor analysis. We found that tVNS attenuates alpha oscillations to a greater extent than does sham stimulation. Thus, tVNS reliably induces pupillary and EEG markers of arousal beyond the effects of somatosensory stimulation, supporting the hypothesis that it elevates noradrenaline and acetylcholine signaling and mimics invasive VNS.

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Section: Introductionmentioning

confidence: 99%

Transcutaneous vagus nerve stimulation in humans induces pupil dilation and attenuates alpha oscillations

Sharon

Fahoum

Nir

2020

Preprint

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“…Recently, neuromodulation therapy using various brain stimulation modalities, including deep brain stimulation, vagal nerve stimulation, or external responsive neurostimulation, have been attempted to control intractable seizures. 18 – 22 Those therapies modulate brain functions or pathological states at the entire brain network level, by stimulating the specific brain region to induce changes not only in the stimulated brain regions but also in distant areas that are connected to them through the anatomical or functional brain connectivity. While the neuromodulation therapies have been known as novel and promising treatment methods, demonstrating seizure reduction in about one-third to one-half of patients, 18 – 22 there are still many obstacles for improving the treatment efficacy by finding the optimal stimulation sites or stimulation parameters, or understanding the mechanisms behind the treatment.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and Computational Approaches for Epilepsy

An¹,

Kang²,

Lee³

2020

J Epilepsy Res

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Studies on treatment of epilepsy have been actively conducted in multiple avenues, but there are limitations in improving its efficacy due to between-subject variability in which treatment outcomes vary from patient to patient. Accordingly, there is a growing interest in precision medicine that provides accurate diagnosis for seizure types and optimal treatment for an individual epilepsy patient. Among these approaches, computational studies making this feasible are rapidly progressing in particular and have been widely applied in epilepsy. These computational studies are being conducted in two main streams: 1) artificial intelligence-based studies implementing computational machines with specific functions, such as automatic diagnosis and prognosis prediction for an individual patient, using machine learning techniques based on large amounts of data obtained from multiple patients and 2) patient-specific modeling-based studies implementing biophysical in-silico platforms to understand pathological mechanisms and derive the optimal treatment for each patient by reproducing the brain network dynamics of the particular patient per se based on individual patient’s data. These computational approaches are important as it can integrate multiple types of data acquired from patients and analysis results into a single platform. If these kinds of methods are efficiently operated, it would suggest a novel paradigm for precision medicine.

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“…Instead, targeted approaches that only directly affect a small number of brain regions have been proposed. These techniques range from localised opening of the blood-brain-barrier through focused ultrasound [3,4], to invasive and non-invasive brain stimulation [5][6][7][8], and, when no alternative options are suitable, to surgical removal of brain tissue [9,10]. The problem then is to choose the right set of target regions for individual patients to maximize treatment effects and to minimize side effects.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, techniques used in the treatment of other diseases, like the coordinated reset [15,16] method (used for treatment of Parkinson's) that aims to desynchronise neuronal populations (pathological synchronization being a major feature of epilepsy) could potentially be used in treating epilepsy. The effectiveness of the methods used varies [7] and when it comes to TCS-one of the non-invasive methods-there are of contradictory results concerning its efficacy for treating epilepsy [17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

et al. 2020

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Computational studies of the influence of different network parameters on the dynamic and topological network effects of brain stimulation can enhance our understanding of different outcomes between individuals. In this study, a brain stimulation session along with the subsequent post-stimulation brain activity is simulated for a period of one day using a network of modified Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine how differences in the interregion connectivity and the excitability of stimulated regions at the time of stimulation can affect post-stimulation behaviours. Our findings indicate that the initial inter-region connectivity can heavily affect the changes that stimulation induces in the connectivity of the network. Moreover, differences in the excitability of the stimulated regions seem to lead to different post-stimulation connectivity changes across the model network, including on the internal connectivity of non-stimulated regions.

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Neurostimulation for drug-resistant epilepsy: a systematic review of clinical evidence for efficacy, safety, contraindications and predictors for response

Cited by 88 publications

References 96 publications

Transcutaneous vagus nerve stimulation in humans induces pupil dilation and attenuates alpha oscillations

Transcutaneous vagus nerve stimulation in humans induces pupil dilation and attenuates alpha oscillations

Artificial Intelligence and Computational Approaches for Epilepsy

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

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