Neurophysiological monitoring of tongue muscle activation during hypoglossal nerve stimulation.

OBJECTIVES/HYPOTHESIS: Upper airway stimulation for obstructive sleep apnea (OSA) via implantable hypoglossal nerve stimulation (HGNS) reduces airway obstruction by selectively stimulating nerve fibers that innervate muscles that produce tongue protrusion, while avoiding fibers that produce tongue retraction. This selective stimulation likely depends upon the location, intensity, and type of electrical stimulation delivered. This study investigates the impact of changing stimulation parameters on tongue muscle activation during HGNS using intraoperative nerve integrity monitoring in conjunction with electromyography (EMG). STUDY DESIGN: Prospective case series. METHODS: Ten patients undergoing unilateral HGNS implantation for OSA in a university hospital setting were studied. Data included EMG responses in tongue muscles that produce protrusion (genioglossus), retraction (styloglossus/hyoglossus), and stiffening (transverse/vertical) in response to intraoperative bipolar probe electrical stimulation of lateral and medial branches of the hypoglossal nerve (HGN) and to implantable pulse generator (IPG) unipolar and bipolar settings after placement of the stimulation cuff. RESULTS: Stimulation of medial division HGN branches resulted in EMG responses in genioglossus muscles, but not in styloglossus/hyoglossus muscles, whereas stimulation of the lateral division HGN branches drove responses in styloglossus/hyoglossus muscles. Variable responses in transverse/vertical muscles were observed with stimulation of lateral and medial division branches. After electrode cuff placement, unipolar and bipolar HGN stimulation configurations of IPG resulted in unique patterns of muscle activation. CONCLUSIONS: The relative activation of extrinsic and intrinsic tongue musculature by HGNS is determined by stimulus location, intensity, and type. Intraoperative neurophysiological monitoring of tongue muscle activation enables proper electrode cuff placement and may provide essential data for stimulus optimization. LEVEL OF EVIDENCE: 4 Laryngoscope, 130:1836-1843, 2020.

Real-Time Closed-Loop Functional Electrical Stimulation Control of Muscle Activation with Evoked Electromyography Feedback for Spinal Cord Injured Patients.

Functional electrical stimulation (FES) is a neuroprosthetic technique to help restore motor function of spinal cord-injured (SCI) patients. Through delivery of electrical pulses to muscles of motor-impaired subjects, FES is able to artificially induce their muscle contractions. Evoked electromyography (eEMG) is used to record such FES-induced electrical muscle activity and presents a form of [Formula: see text]-wave. In order to monitor electrical muscle activity under stimulation and ensure safe stimulation configurations, closed-loop FES control with eEMG feedback is needed to be developed for SCI patients who lose their voluntary muscle contraction ability. This work proposes a closed-loop FES system for real-time control of muscle activation on the triceps surae and tibialis muscle groups through online modulating pulse width (PW) of electrical stimulus. Subject-specific time-variant muscle responses under FES are explicitly reflected by muscle excitation model, which is described by Hammerstein system with its input and output being, respectively, PW and eEMG. Model predictive control is adopted to compute the PW based on muscle excitation model which can online update its parameters. Four muscle activation patterns are provided as desired control references to validate the proposed closed-loop FES control paradigm. Real-time experimental results on three able-bodied subjects and five SCI patients in clinical environment show promising performances of tracking the aforementioned reference muscle activation patterns based on the proposed closed-loop FES control scheme.

Changes in laser-evoked potentials during hypnotic analgesia for chronic pain: a pilot study.

BACKGROUND: Hypnotic analgesia is one of the most effective nonpharmacological methods for pain control. Hypnosis and distraction of attention from pain might share similar mechanisms by which brain responses to painful stimulation could be similarly reduced in both states. There is ample evidence for the efficacy of clinical hypnosis as a psychological intervention in the treatment of acute or chronic pain. Results are conflicting, however, with some studies showing an increase, others a reduction, and others still no change in the amplitude of event-related brain potentials during hypnosis as compared to control conditions. Here we compared the effects of clinical hypnosis to simple distraction of attention during recording of laser-evoked potentials (LEPs) in patients with chronic pain. METHODS: The dominant hand in ten patients with chronic pain was tested with LEPs during: (I) resting state; (II) clinical hypnosis, and (III) distraction of attention. Nociceptive responses elicited by LEPs were graded on a numerical rating scale (NRS), and the change in N2-P2 complex amplitude during the three experimental conditions was analyzed. RESULTS: N2-P2 amplitudes were significantly decreased during the hypnotic state as compared to the resting state and distraction of attention. CONCLUSIONS: Hypnosis is a modified state of consciousness that may differ from mental relaxation or distraction of attention from pain. A reduction in N2-P2 amplitude may result from the modulation of diverse brain networks, particularly the frontolimbic pathways, which could modify noxious stimuli input processing during hypnotic analgesia. Our findings indicate that several different brain mechanisms may act together in hypnosis and distraction of attention during pain processing and that clinical hypnosis may provide a useful non-invasive pain relief therapy.

Application of Empirical Mode Decomposition Combined With Notch Filtering for Interpretation of Surface Electromyograms During Functional Electrical Stimulation.

The goal of this paper is to demonstrate a novel approach that combines Empirical Mode Decomposition (EMD) with Notch filtering to remove the electrical stimulation (ES) artifact from surface electromyogram (EMG) data for interpretation of muscle responses during functional electrical stimulation (FES) experiments. FES was applied to the rectus femoris (RF) muscle unilaterally of six able bodied (AB) and one individual with spinal cord injury (SCI). Each trial consisted of three repetitions of ES. We hypothesized that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic mode functions (IMFs) which can be further used to isolate electrical stimulation (ES) artifact. A basic EMD algorithm was used to decompose the EMG signals collected during FES into IMFs for each repetition separately. IMFs most contaminated by ES were identified based on the standard deviation (SD) of each IMF. Each artifact IMF was Notch filtered to filter ES harmonics and added to remaining IMFs containing pure EMG data to get a version of a filtered EMG signal. Of all such versions of filtered signals generated from each artifact IMF, the one with maximum signal to noise ratio (SNR) was chosen as the final output. The validity of the filtered signal was assessed by quantitative metrics, 1) root mean squared error (RMSE) and signal to noise (SNR) ratio values obtained by comparing a clean EMG and EMD-Notch filtered signal from the combination of simulated ES and clean EMG and, 2) using EMG-force correlation analysis on the data collected from AB individuals. Finally, the potential applicability of this algorithm on a neurologically impaired population was shown by applying the algorithm on EMG data collected from an individual with SCI. EMD combined with Notch filtering successfully extracted the EMG signal buried under ES artifact. Filtering performance was validated by smaller RMSE values and greater SNR post filtering. The amplitude values of the filtered EMG signal were seen to be consistent for three repetitions of ES and there was no significant difference among the repetition for all subjects. For the individual with a SCI the algorithm was shown to successfully isolate the underlying bursts of muscle activations during FES. The data driven nature of EMD algorithm and its ability to act as a filter bank at different bandwidths make this method extremely suitable for dissecting ES induced EMG into IMFs. Such IMFs clearly show the presence of ES artifact at different intensities as well as pure artifact free EMG. This allows the application of Notch filters to IMFs containing ES artifact to further isolate the EMG. As a result of such stepwise approach, the extraction of EMG is achieved with minimal data loss. This study provides a unique approach to dissect and interpret the EMG signal during FES applications.

Real-Time, In Vivo Monitoring, and Quantitative Assessment of Intra-Arterial Vasospasm Therapy.

BACKGROUND: Our study aimed to evaluate whether the effect of an intra-arterial vasospasm therapy can be assessed quantitatively by in vivo blood flow analysis using the postprocessing algorithm parametric color coding (PCC). METHODS: We evaluated 17 patients presenting with acute clinical deterioration due to vasospasm following subarachnoidal hemorrhage treated with intra-arterial nimodipine application. Pre- and post-interventional DSA series were post-processed by PCC. The relative time to maximum opacification (rTmax) was calculated in 14 arterially and venously located points of interest. From that data, the pre- and post-interventional cerebral circulation time (CirT) was calculated. Additionally, the arterial vessel diameters were measured. Pre- and post-interventional values were compared and tested for significance, respectively. RESULTS: Flow analysis revealed in all arterial vessel segments a non-statistically significant prolongation of rTmax after treatment. The mean CirT was 5.62 s (±1.19 s) pre-interventionally and 5.16 s (±0.81 s) post-interventionally, and the difference turned out as statistically significant (p = 0.039). A significantly increased diameter was measurable in all arterial segments post-interventionally. CONCLUSION: PCC is a fast applicable imaging technique that allows via real-time and in vivo blood flow analysis a quantitative assessment of the effect of intra-arterial vasospasm therapy. Our results seem to validate in vivo that an intra-arterial nimodipine application induces not only vasodilatation of the larger vessels, but also improves the microcirculatory flow, leading to a shortened cerebral CirT that reaches normal range post-interventionally. Procedural monitoring via PCC offers the option to compare quantitatively different therapy regimes, which allows optimization of existing approaches and implementation of individualized treatment strategies.

Algorithm for Quantifying Frontal EMG Responsiveness for Sedation Monitoring.

INTRODUCTION: To study stimulation-related facial electromyographic (FEMG) activity in intensive care unit (ICU) patients, develop an algorithm for quantifying the FEMG activity, and to optimize the algorithm for monitoring the sedation state of ICU patients. METHODS: First, the characteristics of FEMG response patterns related to vocal stimulation of 17 ICU patients were studied. Second, we collected continuous FEMG data from 30 ICU patients. Based on these data, we developed the Responsiveness Index (RI) algorithm that quantifies FEMG responses. Third, we compared the RI values with clinical sedation level assessments and adjusted algorithm parameters for best performance. RESULTS: In patients who produced a clinically observed response to the vocal stimulus, the poststimulus FEMG power was 0.33 µV higher than the prestimulus power. In nonresponding patients, there was no difference. The sensitivity and specificity of the developed RI for detecting deep sedation in the subgroup with low probability of encephalopathy were 0.90 and 0.79, respectively. CONCLUSION: Consistent FEMG patterns were found related to standard stimulation of ICU patients. A simple and robust algorithm was developed and good correlation with clinical sedation scores achieved in the development data.

Effects of mindfulness-based cognitive therapy on neurophysiological correlates of performance monitoring in adult attention-deficit/hyperactivity disorder.

OBJECTIVE: To examine whether mindfulness-based cognitive therapy (MBCT) would enhance attenuated amplitudes of event-related potentials (ERPs) indexing performance monitoring biomarkers of attention-deficit/hyperactivity disorder (ADHD). METHODS: Fifty adult ADHD patients took part in a randomised controlled study investigating ERP and clinical measures pre-to-post MBCT. Twenty-six patients were randomly allocated to MBCT, 24 to a wait-list control. Main outcome measures included error processing (ERN, Pe), conflict monitoring (NoGo-N2), and inhibitory control (NoGo-P3) ERPs concomitant to a continuous performance task (CPT-X). Inattention and hyperactivity-impulsivity ADHD symptoms, psychological distress and social functioning, and mindfulness skills were also assessed. RESULTS: MBCT was associated with increased Pe and NoGo-P3 amplitudes, coinciding with reduced 'hyperactivity/impulsivity' and 'inattention' symptomatology. Specific to the MBCT; enhanced Pe amplitudes correlated with a decrease in hyperactivity/impulsivity symptoms and increased 'act-with-awareness' mindfulness skill, whereas, enhanced P3 correlated with amelioration in inattention symptoms. CONCLUSIONS: MBCT enhanced ERP amplitudes associated with motivational saliency and error awareness, leading to improved inhibitory regulation. SIGNIFICANCE: MBCT suggests having comparable modulation on performance monitoring ERP amplitudes as pharmacological treatments. Further study and development of MBCT as a treatment for ADHD is warranted, in addition to its potential scope for clinical applicability to broader defined externalising disorders and clinical problems associated with impairments of the prefrontal cortex.

A neural network model can explain ventriloquism aftereffect and its generalization across sound frequencies.

Exposure to synchronous but spatially disparate auditory and visual stimuli produces a perceptual shift of sound location towards the visual stimulus (ventriloquism effect). After adaptation to a ventriloquism situation, enduring sound shift is observed in the absence of the visual stimulus (ventriloquism aftereffect). Experimental studies report opposing results as to aftereffect generalization across sound frequencies varying from aftereffect being confined to the frequency used during adaptation to aftereffect generalizing across some octaves. Here, we present an extension of a model of visual-auditory interaction we previously developed. The new model is able to simulate the ventriloquism effect and, via Hebbian learning rules, the ventriloquism aftereffect and can be used to investigate aftereffect generalization across frequencies. The model includes auditory neurons coding both for the spatial and spectral features of the auditory stimuli and mimicking properties of biological auditory neurons. The model suggests that different extent of aftereffect generalization across frequencies can be obtained by changing the intensity of the auditory stimulus that induces different amounts of activation in the auditory layer. The model provides a coherent theoretical framework to explain the apparently contradictory results found in the literature. Model mechanisms and hypotheses are discussed in relation to neurophysiological and psychophysical data.