Despite promising preliminary results in treating fibromyalgia (FM) pain, no neuromodulation technique has been adopted in clinical practice because of limited efficacy, low response rate, or poor tolerability. This phase II open-label trial aims to define a methodology for a clinically effective treatment of pain in FM by establishing treatment protocols and screening procedures to maximize efficacy and response rate. High-definition transcranial direct current stimulation (HD-tDCS) provides targeted subthreshold brain stimulation, combining tolerability with specificity. We aimed to establish the number of HD-tDCS sessions required to achieve a 50% FM pain reduction, and to characterize the biometrics of the response, including brain network activation pain scores of contact heat-evoked potentials. We report a clinically significant benefit of a 50% pain reduction in half (n = 7) of the patients (N = 14), with responders and nonresponders alike benefiting from a cumulative effect of treatment, reflected in significant pain reduction (P = .035) as well as improved quality of life (P = .001) over time. We also report an aggregate 6-week response rate of 50% of patients and estimate 15 as the median number of HD-tDCS sessions to reach clinically meaningful outcomes. The methodology for a pivotal FM neuromodulation clinical trial with individualized treatment is thus supported.
Post-traumatic migraine (PTM) (i.e., headache, nausea, light and/or noise sensitivity) is an emerging risk factor for prolonged recovery following concussion. Concussions and migraine share similar pathophysiology characterized by specific ionic imbalances in the brain. Given these similarities, patients with PTM following concussion may exhibit distinct electrophysiological patterns, although researchers have yet to examine the electrophysiological brain activation in patients with PTM following concussion. A novel approach that may help differentiate brain activation in patients with and without PTM is brain network activation (BNA) analysis. BNA involves an algorithmic analysis applied to multichannel EEG-ERP data that provides a network map of cortical activity and quantitative data during specific tasks. A prospective, repeated measures design was used to evaluate BNA (during Go/NoGo task), EEG-ERP, cognitive performance, and concussion related symptoms at 1, 2, 3, and 4-week post-injury intervals among athletes with a medically diagnosed concussion with PTM (n = 15) and without (NO-PTM) (n = 22); and age, sex, and concussion history matched controls without concussion (CONTROL) (n = 20). Participants with PTM had significantly reduced BNA compared to NO-PTM and CONTROLS for Go and NoGo components at 3 weeks and for NoGo component at 4 weeks post-injury. The PTM group also demonstrated a more prominent deviation of network activity compared to the other two groups over a longer period of time. The composite BNA algorithm may be a more sensitive measure of electrophysiological change in the brain that can augment established cognitive assessment tools for detecting impairment in individuals with PTM.
Simultaneous EEG-fMRI (Electroencephalography-functional Magnetic Resonance Imaging) recording provides a means for acquiring high temporal resolution electrophysiological data and high spatial resolution metabolic data of the brain in the same experimental runs. Carbon wire electrodes (not metallic EEG electrodes with carbon wire leads) are suitable for simultaneous EEG-fMRI recording, because they cause less RF (radio-frequency) heating and susceptibility artifacts than metallic electrodes. These characteristics are especially desirable for recording the EEG in high field MRI scanners. Carbon wire electrodes are also comfortable to wear during long recording sessions. However, carbon electrodes have high electrode-electrolyte potentials compared to widely used Ag/ AgCl (silver/silver-chloride) electrodes, which may cause slow voltage drifts. This paper introduces a prototype EEG recording system with carbon wire electrodes and a circuit that suppresses the slow voltage drift. The system was tested for the voltage drift, RF heating, susceptibility artifact, and impedance, and was also evaluated in a simultaneous ERP (event-related potential)-fMRI experiment.
Background: Pain perception is typically assessed using subjective measures; an objective measure of the response to pain would be valuable. In this study, Brain Network Activation (BNA), a novel multivariate pattern analysis and scoring algorithm, was applied to event-related potentials (ERPs) elicited by cortical responses to brief heat stimuli. Objectives of this study were to evaluate the utility of BNA as a quantitative and qualitative measure of cortical response to pain. Methods: Contact Heat Evoked Potentials (CHEPs) data were collected from 17 healthy, right-handed volunteers (10 M, 7F) using 5 different temperatures (35, 41, 46, 49 and 52°C). A set of spatio-temporal activity patterns common to all the subjects in the group (Reference Brain Network Model; RBNM) was generated using the BNA algorithm, based on evoked responses at 52°C. Results: Frame by frame 'unfolding' of the brain network across time showed qualitative differences between responses to painful and non-painful stimuli. Brain network activation scores were shown to be a better indicator of the individual's sensitivity to pain when compared to subjective pain ratings. Additionally, BNA scores correlated significantly with temperature, demonstrated good testretest reliability, as well as a high degree of sensitivity, specificity and accuracy in correctly categorizing subjects who reported stimuli as painful. Conclusions: These results may provide evidence that the multivariate analysis performed with BNA may be useful as a quantitative, temporally sensitive tool for assessment of pain perception.
The aim of this study was to dissociate the contributions of memory-based (cognitive) and adaptationbased (sensory) mechanisms underlying deviance detection in the context of natural speech. Twenty healthy righthanded native speakers of English participated in an eventrelated design scan in which natural speech stimuli,
Attentional selection in the context of goal-directed behavior involves top-down modulation to enhance the contrast between relevant and irrelevant stimuli via enhancement and suppression of sensory cortical activity. Acetylcholine (ACh) is believed to be involved mechanistically in such attention processes. The objective of the current study was to examine the effects of donepezil, a cholinesterase inhibitor that increases synaptic levels of ACh, on the relationship between performance and network dynamics during a visual working memory (WM) task involving relevant and irrelevant stimuli. Electroencephalogram (EEG) activity was recorded in 14 healthy young adults while they performed a selective face/scene working memory task. Each participant received either placebo or donepezil (5 mg, orally) on two different visits in a double-blinded study. To investigate the effects of donepezil on brain network dynamics we utilized a novel EEG-based Brain Network Activation (BNA) analysis method that isolates location–time–frequency interrelations among event-related potential (ERP) peaks and extracts condition-specific networks. The activation level of the network modulated by donepezil, reflected in terms of the degree of its dynamical organization, was positively correlated with WM performance. Further analyses revealed that the frontal–posterior theta–alpha sub-network comprised the critical regions whose activation level correlated with beneficial effects on cognitive performance. These results indicate that condition-specific EEG network analysis could potentially serve to predict beneficial effects of therapeutic treatment in working memory.
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