Electrically evoked compound action potential artifact rejection by independent component analysis: technique validation.
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ABSTRACT:
SUBMITTER: Akhoun I
PROVIDER: S-EPMC3709093 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Previous research from our laboratory comparing electrically evoked compound action potential (ECAP) artifact reduction methods has shown larger amplitudes and lower thresholds with cathodic-leading forward masking (CathFM) than with alternating polarity (AltPol). One interpretation of this result is that the anodic-leading phase used with AltPol elicits a less excitatory response (in contrast to results from recent studies with humans), which when averaged with responses to cathodic-leading stimuli, results in smaller amplitudes. Another interpretation is that the latencies of the responses to anodic- and cathodic-leading pulses differ, which when averaged together, result in smaller amplitudes than for either polarity alone due to temporal smearing. The purpose of this study was to separate the effects of stimulus polarity and artifact reduction method to determine the relative effects of each.This study used a within-subjects design. ECAP growth functions were obtained using CathFM, anodic-leading forward masking (AnodFM), and AltPol for 23 CI recipients (N = 13 Cochlear and N = 10 Advanced Bionics). N1 latency, amplitude, slope of the amplitude growth function, and threshold were compared across methods. Data were analyzed separately for each manufacturer due to inherent differences between devices.N1 latencies were significantly shorter for AnodFM than for CathFM and AltPol for both Cochlear and Advanced Bionics participants. Amplitudes were larger for AnodFM than for either CathFM or AltPol for Cochlear recipients; amplitude was not significantly different across methods for Advanced Bionics recipients. Slopes were shallowest for CathFM for Cochlear subjects, but were not significantly different among methods for Advanced Bionics subjects. Thresholds with AltPol were significantly higher than both FM methods for Cochlear recipients; there was no difference in threshold across methods for the Advanced Bionics recipients.For Cochlear devices, the smaller amplitudes and higher thresholds observed for AltPol seem to be the result of latency differences between polarities. These results suggest that AltPol is not ideal for managing stimulus artifact for ECAP recordings. For the Advanced Bionics group, there were no significant differences among methods for amplitude, slope, or threshold, which suggests that polarity and artifact reduction method have little influence in these devices. We postulate that polarity effects are minimized for symmetrical biphasic pulses that lack an interphase gap, such as those used with Advanced Bionics devices; however, this requires further investigation.
| S-EPMC5404966 | biostudies-literature
Project description:The electrically evoked compound action potential (eCAP) represents the synchronous firing of a population of electrically stimulated auditory nerve fibers. It can be directly recorded on a surgically exposed nerve trunk in animals or from an intra-cochlear electrode of a cochlear implant. In the past two decades, the eCAP has been widely recorded in both animals and clinical patient populations using different testing paradigms. This paper provides an overview of recording methodologies and response characteristics of the eCAP, as well as its potential applications in research and clinical situations. Relevant studies are reviewed and implications for clinicians are discussed.
| S-EPMC5481377 | biostudies-other
Project description:Previous animal study revealed that post-implantation electrical detection levels significantly declined within days. The impact of cochlear implant (CI) insertion on human auditory pathway in terms of impedance and electrically evoked compound action potential (ECAP) variation within hours after surgery remains unclear, since at this time frequency mapping can only commence weeks after implantation due to factors associated with wound conditions. The study presented our experiences with regards to initial switch-on within 24 hours, and thus the findings about the milieus inside cochlea within the first few hours after cochlear implantation in terms of impedance/ECAP fluctuations. The charts of fifty-four subjects with profound hearing impairment were studied. A minimal invasive approach was used for cochlear implantation, characterized by a small skin incision (? 2.5 cm) and soft techniques for cochleostomy. Impedance/ECAP was measured intro-operatively and within 24 hours post-operatively. Initial mapping within 24 hours post-operatively was performed in all patients without major complications. Impedance/ECAP became significantly lower measured within 24 hours post-operatively as compared with intra-operatively (p<0.001). There were no differences between pre-operative and post-operative threshold for air-conduction hearing. A significant drop of impedance/ECAP in one day after cochlear implantation was revealed for the first time in human beings. Mechanisms could be related to the restoration of neuronal sensitivity to the electrical stimulation, and/or the interaction between the matrix enveloping the electrodes and the electrical stimulation of the initial switch-on. Less wound pain/swelling and soft techniques both contributed to the success of immediate initial mapping, which implied a stable micro-environment inside the cochlea despite electrodes insertion. Our research invites further studies to correlate initial impedance/ECAP changes with long-term hearing/speech performance.
| S-EPMC3753283 | biostudies-literature
Project description:Peripheral neural signals have the potential to provide the necessary motor, sensory or autonomic information for robust control in many neuroprosthetic and neuromodulation applications. However, developing methods to recover information encoded in these signals is a significant challenge. We introduce the idea of using spatiotemporal signatures extracted from multi-contact nerve cuff electrode recordings to classify naturally evoked compound action potentials (CAP). 9 Long-Evan rats were implanted with a 56-channel nerve cuff on the sciatic nerve. Afferent activity was selectively evoked in the different fascicles of the sciatic nerve (tibial, peroneal, sural) using mechano-sensory stimuli. Spatiotemporal signatures of recorded CAPs were used to train three different classifiers. Performance was measured based on the classification accuracy, F1-score, and the ability to reconstruct original firing rates of neural pathways. The mean classification accuracies, for a 3-class problem, for the best performing classifier was 0.686 ± 0.126 and corresponding mean F1-score was 0.605 ± 0.212. The mean Pearson correlation coefficients between the original firing rates and estimated firing rates found for the best classifier was 0.728 ± 0.276. The proposed method demonstrates the possibility of classifying individual naturally evoked CAPs in peripheral neural signals recorded from extraneural electrodes, allowing for more precise control signals in neuroprosthetic applications.
| S-EPMC6668407 | biostudies-literature
Project description:We present an automated algorithm for unified rejection and repair of bad trials in magnetoencephalography (MEG) and electroencephalography (EEG) signals. Our method capitalizes on cross-validation in conjunction with a robust evaluation metric to estimate the optimal peak-to-peak threshold - a quantity commonly used for identifying bad trials in M/EEG. This approach is then extended to a more sophisticated algorithm which estimates this threshold for each sensor yielding trial-wise bad sensors. Depending on the number of bad sensors, the trial is then repaired by interpolation or by excluding it from subsequent analysis. All steps of the algorithm are fully automated thus lending itself to the name Autoreject. In order to assess the practical significance of the algorithm, we conducted extensive validation and comparisons with state-of-the-art methods on four public datasets containing MEG and EEG recordings from more than 200 subjects. The comparisons include purely qualitative efforts as well as quantitatively benchmarking against human supervised and semi-automated preprocessing pipelines. The algorithm allowed us to automate the preprocessing of MEG data from the Human Connectome Project (HCP) going up to the computation of the evoked responses. The automated nature of our method minimizes the burden of human inspection, hence supporting scalability and reliability demanded by data analysis in modern neuroscience.
| S-EPMC7243972 | biostudies-literature
Project description:BackgroundBody surface gastric mapping (BSGM) is a new clinical tool for gastric motility diagnostics, providing high-resolution data on gastric myoelectrical activity. Artifact contamination was a key challenge to reliable test interpretation in traditional electrogastrography. This study aimed to introduce and validate an automated artifact detection and rejection system for clinical BSGM applications.MethodsTen patients with chronic gastric symptoms generated a variety of artifacts according to a standardized protocol (176 recordings) using a commercial BSGM system (Alimetry, New Zealand). An automated artifact detection and rejection algorithm was developed, and its performance was compared with a reference standard comprising consensus labeling by 3 analysis experts, followed by comparison with 6 clinicians (3 untrained and 3 trained in artifact detection). Inter-rater reliability was calculated using Fleiss' kappa.Key resultsInter-rater reliability was 0.84 (95% CI:0.77-0.90) among experts, 0.76 (95% CI:0.68-0.83) among untrained clinicians, and 0.71 (95% CI:0.62-0.79) among trained clinicians. The sensitivity and specificity of the algorithm against experts was 96% (95% CI:91%-100%) and 95% (95% CI:90%-99%), respectively, vs 77% (95% CI:68%-85%) and 99% (95% CI:96%-100%) against untrained clinicians, and 97% (95% CI:92%-100%) and 88% (95% CI:82%-94%) against trained clinicians.Conclusions & inferencesAn automated artifact detection and rejection algorithm was developed showing >95% sensitivity and specificity vs expert markers. This algorithm overcomes an important challenge in the clinical translation of BSGM and is now being routinely implemented in patient test interpretations.
| S-EPMC9786272 | biostudies-literature
Project description:PurposeWe characterized electrically elicited visual evoked potentials (eVEPs) in Argus II retinal implant wearers.MethodseVEPs were recorded in four subjects, and analyzed by determining amplitude and latency of the first two positive peaks (P1 and P2). Subjects provided subjective feedback by rating the brightness and size of the phosphenes. We established eVEP input-output relationships, eVEP variability between and within subjects, the effect of stimulating different areas of the retina, and the maximal pulse rate to record eVEPs reliably.ResultseVEP waveforms had low signal-to-noise ratios, requiring long recording times and substantial signal processing. Waveforms varied between subjects, but showed good reproducibility and consistent parameter dependence within subjects. P2 amplitude overall was the most robust outcome measure and proved an accurate indicator of subjective threshold. Peak latencies showed small within-subject variability, yet their correlation with stimulus level and subjective rating were more variable than that of peak amplitudes. Pulse rates of up to (2)/3 Hz resulted in reliable eVEP recordings. Perceived phosphene brightness declined over time, as reflected in P1 amplitude, but not in P2 amplitude or peak latencies. Stimulating-electrode location significantly affected P1 and P2 amplitude and latency, but not subjective percepts.ConclusionsWhile recording times and signal processing are more demanding than for standard visually evoked potential (VEP) recordings, the eVEP has proven to be a reliable tool to verify retinal implant functionality. eVEPs correlated with various stimulus parameters and with perceptual ratings. In view of these findings, eVEPs may become an important tool in functional investigations of retinal prostheses. (ClinicalTrials.gov number NCT00407602.) Dutch Abstract.
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Project description:Eyeblinks and other large artifacts can create two major problems in event-related potential (ERP) research, namely confounds and increased noise. Here, we developed a method for assessing the effectiveness of artifact correction and rejection methods at minimizing these two problems. We then used this method to assess a common artifact minimization approach, in which independent component analysis (ICA) is used to correct ocular artifacts, and artifact rejection is used to reject trials with extreme values resulting from other sources (e.g., movement artifacts). This approach was applied to data from five common ERP components (P3b, N400, N170, mismatch negativity, and error-related negativity). Four common scoring methods (mean amplitude, peak amplitude, peak latency, and 50% area latency) were examined for each component. We found that eyeblinks differed systematically across experimental conditions for several of the components. We also found that artifact correction was reasonably effective at minimizing these confounds, although it did not usually eliminate them completely. In addition, we found that the rejection of trials with extreme voltage values was effective at reducing noise, with the benefits of eliminating these trials outweighing the reduced number of trials available for averaging. For researchers who are analyzing similar ERP components and participant populations, this combination of artifact correction and rejection approaches should minimize artifact-related confounds and lead to improved data quality. Researchers who are analyzing other components or participant populations can use the method developed in this study to determine which artifact minimization approaches are effective in their data.
| S-EPMC10516012 | biostudies-literature
Project description:Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.
| S-EPMC6866546 | biostudies-literature
Project description:Zebrafish (Danio rerio) have recently emerged as useful model organism for the study of neuronal function. Here, fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes was used to measure locally evoked dopamine release and uptake in zebrafish whole brain preparations and results were compared with those obtained from brain slices. Evoked dopamine release ([DA]max) was similar in whole brain and sagittal brain slice preparations (0.49 ± 0.13 μM in whole brain and 0.59 ± 0.28 μM in brain slices). Treatment with α-methyl-p-tyrosine methyl ester (αMPT), an inhibitor of tyrosine hydroxylase, diminished release and the electrochemical signal reappeared after subsequent drug washout. No observed change in stimulated release current occurred after treatment with desipramine or fluoxetine in the whole brain. Treatment with the uptake inhibitors, nomifensine or GBR 12909 increased [DA]max, while treatment with sulpiride, a D2 dopamine autoreceptor antagonist, resulted in increased stimulated dopamine release in whole brain, but had no effect on release in slices. Dopamine release in whole brains increased progressively up to an electrical stimulation frequency of 25 Hz, while release in slices increased up to a frequency of only 10 Hz and then plateaued, highlighting another key difference between these preparations. We observed a lag in peak dopamine release following stimulation, which we address using diffusion models and pharmacological treatments. Collectively, these results demonstrate the electrochemical determination of dopamine release in the whole, intact brain of a vertebrate species ex vivo and are an important step for carrying out further experiments in zebrafish.
| S-EPMC5846466 | biostudies-literature