ABSTRACT
OBJECTIVES: The most widely used and studied neurostimulation procedure for medically refractory epilepsy is vagus nerve stimulation (VNS) Therapy. The goal of this study was to develop a computational model for improved understanding of the anatomy and neurophysiology of the vagus nerve as it pertains to the principles of electrical stimulation, aiming to provide clinicians with a systematic and rational understanding of VNS Therapy. MATERIALS AND METHODS: Computational modeling allows the study of electrical stimulation of peripheral nerves. We used finite element electric field models of the vagus nerve with VNS Therapy electrodes to calculate the voltage field for several output currents and studied the effects of two programmable parameters (output current and pulse width) on optimal fiber activation. RESULTS: The mathematical models correlated well with strength-duration curves constructed from actual patient data. In addition, digital constructs of chronic versus acute implant models demonstrated that at a given pulse width and current combination, presence of a 110-µm fibrotic tissue can decrease fiber activation by 50%. Based on our findings, a range of output current settings between 0.75 and 1.75 mA with pulse width settings of 250 or 500 µs may result in optimal stimulation. CONCLUSIONS: The modeling illustrates how to achieve full or nearly full activation of the myelinated fibers of the vagus nerve through output current and pulse width settings. This knowledge will enable clinicians to apply these principles for optimal vagus nerve activation and proceed to adjust duty cycle and frequency to achieve effectiveness.
Subject(s)
Computer Simulation , Models, Neurological , Models, Theoretical , Vagus Nerve Stimulation , Vagus Nerve/physiology , Action Potentials/physiology , Epilepsy/physiopathology , Epilepsy/therapy , HumansABSTRACT
BACKGROUND: The value of vagus nerve stimulation (VNS) for treating patients with drug-resistant idiopathic generalized epilepsy (IGE) is not well documented. PATIENTS AND METHODS: Twelve patients (2 males, 10 females) with a mean age of 31 years (11-48 years) and with drug-resistant IGE had VNS implanted in the period 1995-2006. All had generalized seizures documented by video-electroencephalogram. Mean follow-up period was 23 months (9-54 months). RESULTS: There was a total seizure reduction of 61% (P = 0.0002). There was 62% reduction of generalized tonic-clonic seizures (P = 0.0020), 58% of absences (P = 0.0003) and 40% of myoclonic seizures (P = 0.0156). Eight patients were considered responders (>50% seizure reduction); two of these patients became seizure-free. Five out of seven patients with juvenile myoclonic epilepsy were responders. At the last follow-up visit, the patients had reduced the anti-epileptic drug (AED) usage from an average of 2.3 to 1.7 AED per patient (P = 0.0625). Two patients are currently being treated with VNS therapy only. Nine patients reported side effects, which were mostly mild and tended to diminish over time. CONCLUSION: Our results indicate that adjunctive VNS therapy is a favourable treatment option for patients with drug-resistant IGE. Rapid cycling seems worth trying in some of the non-responders.
Subject(s)
Electric Stimulation Therapy/standards , Epilepsy, Generalized/therapy , Vagus Nerve/physiology , Action Potentials/physiology , Adolescent , Adult , Anticonvulsants/therapeutic use , Brain/physiopathology , Child , Drug Resistance/physiology , Electric Stimulation Therapy/adverse effects , Electric Stimulation Therapy/statistics & numerical data , Electrodes, Implanted/adverse effects , Electrodes, Implanted/standards , Electroencephalography , Epilepsies, Myoclonic/physiopathology , Epilepsies, Myoclonic/therapy , Epilepsy, Generalized/physiopathology , Epilepsy, Tonic-Clonic/physiopathology , Epilepsy, Tonic-Clonic/therapy , Female , Humans , Male , Middle Aged , Postoperative Complications/etiology , Treatment Outcome , Visceral Afferents/physiologyABSTRACT
OBJECTIVE: Clinically, intra-subject variability of the alpha frequency is well known, but sparsely documented and practically not used in the evaluation of the electroencephalogram (EEG). In cognitive science, however, the peak alpha frequency (PAF) variations are implemented. The aim of the present study was to document the clinical notion of differences in alpha frequency variations in patients with epilepsy compared to a control group. METHODS: Standard EEG recordings from 28 patients, 18 with epilepsy and 10 patients having EEG for other reasons were included. Ten seconds of artifact free EEG were sampled from F3, F4, T5, T6, O1 and O2 at the beginning, after hyperventilation and at the end of a 20 m recording and Fast Fourier transforms was applied to these epochs of each recording. RESULTS: The study showed a lower frequency in the epilepsy group (frontal 9.22 vs. 10.24 Hz, temporal 9.18 vs. 9.88 Hz and occipital 9.42 vs. 10.30 Hz) and lower frequency variability, with lower values in the epilepsy group in occipital (0.8 vs. 1.44 Hz) and temporal leads (0.89 vs. 1.39 Hz). Frontally, the variability was not significant (0.71 vs. 1.18 Hz, P = 0.0824). Within the groups, there was no relation between frequency and variability. CONCLUSIONS: This study shows that there is PAF variability in the alpha activity. This variability is compromised in patients with epilepsy. Lower alpha frequency is observed in epilepsy group. It is to some extent due to antiepileptic drugs. The lower alpha frequency variability is probably due to a different mechanism as there is no relation between the frequency and its variability within the two groups. SIGNIFICANCE: The alpha activity shows physiological frequency variations that may be compromised by epilepsy.
