Stimulation Artifacts Research Articles

A Method for Removal of Deep Brain Stimulation Artifact From Local Field Potentials.

This paper presents a signal processing method for the electrophysiology simultaneously recorded during deep brain stimulation (DBS) as a research tool. Regarding the local field potential (LFP) signals recorded during stimulation, a novel method was proposed for removal of stimulation artifacts caused by the much stronger stimulating pulse compared to typical LFP. This artifact suppression method was tested and evaluated in an in vitro situation. The results indicate that the stimulation artifacts are well suppressed by this method. Secondly, this method was tested in vivo in Parkinson's disease (PD) patients. It was used to process the LFP signals recorded intraoperatively from PD patients to preliminarily explore the quantitative dependencies of beta band synchronization variations in the subthalamic nucleus (STNs) on the applied DBS parameters, including stimulation voltage, frequency and pulse width. The results confirm that DBS therapy can suppress excessive beta frequency activity and that the degree of attenuation increases with increasing DBS voltage within a range of 1-3 V and increasing DBS frequency within a range of 60-120 Hz. The proposed artifact suppression method provides technical support for exploring the direct effect of electrical stimulation on the brain activities.

An evaluation of extracellular MEA versus optogenetic stimulation of cortical neurons

Objective. The importance of extracellular neural stimulation has driven the development of multiple technologies. Of growing importance is accurately stimulating single neurons in dense networks. It is unlikely that one approach is best for all applications, however comparisons between methods are lacking. We aim to show the strengths and suitable applications for two tools; micro-electrode array (MEA) stimulation and optogenetics. Approach. We compare MEA-based electrical stimulation to Channelrhodopsin 2 based optogenetic stimulation of dissociated cortical neurons in vitro. Effectivity is compared based on stimulation success rate, spatial and temporal accuracy, and reproducibility. We discuss how necessities of each method may limit performance in each category. Main Results. MEA stimulation outperformed optogenetic stimulation in the speed with which an action potential could be generated. The relation between the size of the stimulating point (electrode or illumination spot) and the area of stimulated tissue was similar in both methods. However, technical difficulties in maintaining low impedance from very small electrodes allows higher spatial specificity in optogenetic stimulation. If simultaneous recording and stimulation are desired, MEA stimulation artifacts were far more impairing than light induce artifacts on MEA recordings. Significance. The like versus like comparison of stimulation technologies provides an incomplete evaluation tool for researchers desiring to apply these technologies. This comparison highlights advantages for specific applications and should promote more cross-topic evaluations.

Efficient assembly of multi-color fiberless optoelectrodes with on-board light sources for neural stimulation and recording.

Fiberless optoelectrodes are an emerging tool to enable brain circuit mapping by providing precise optical modulation and electrical monitoring of many neurons. While optoelectrodes having an on-board light source offer compact and optically efficient device solutions, many of them fail to provide robust thermal and electrical design to fully exploit the recording capabilities of the device. In this work, we present a novel fiberless multicolor optoelectrode solution, which meets the optical and thermal design requirements of an in vivo neural optoelectrode and offers potential for low-noise neural recording. The total optical loss measured for 405 nm and 635 nm wavelengths through the waveguide is 11.7±1.1 dB and 9.9±0.7 dB, corresponding to respective irradiances of 1928 mW/mm2 and 2905 mW/mm2 at the waveguide tip from 6 mW laser diode chips. The efficient thermal packaging enables continuous device operation for up to 190 seconds at 10% duty cycle. We validated the fully packaged device in the intact brain of anesthetized mice co-expressing Channelrhodopsin-2 and Archaerhodopsin in the hippocampal CA1 region and achieved activation and silencing of the same neurons. We discuss improvements made to reduce the stimulation artifact induced by applying currents to the laser diode chips.

Rejecting deep brain stimulation artefacts from MEG data using ICA and mutual information

BackgroundRecording brain activity during deep brain stimulation (DBS) using magnetoencephalography (MEG) can potentially help clarifying the neurophysiological mechanism of DBS. The DBS artefact, however, distorts MEG data significantly. We present an artefact rejection approach to remove the DBS artefact from MEG data. New methodsWe developed an approach consisting of four consecutive steps: (i) independent component analysis was used to decompose MEG data to independent components (ICs); (ii) mutual information (MI) between stimulation signal and all ICs was calculated; (iii) artefactual ICs were identified by means of an MI threshold; and (iv) the MEG signal was reconstructed using only non-artefactual ICs. This approach was applied to MEG data from five Parkinson’s disease patients with implanted DBS stimulators. MEG was recorded with DBS ON (unilateral stimulation of the subthalamic nucleus) and DBS OFF during two experimental conditions: a visual attention task and alternating right and left median nerve stimulation. ResultsWith the presented approach most of the artefact could be removed. The signal of interest could be retrieved in both conditions. Comparison with existing methodsIn contrast to existing artefact rejection methods for MEG-DBS data (tSSS and S3P), the proposed method uses the actual artefact source, i.e. the stimulation signal, as reference signal. ConclusionsUsing the presented method, the DBS artefact can be significantly rejected and the physiological data can be restored. This will facilitate research addressing the impact of DBS on brain activity during rest and various tasks.

Physiological processes non-linearly affect electrophysiological recordings during transcranial electric stimulation

Transcranial electric stimulation (tES) is a promising tool to non-invasively manipulate neuronal activity in the human brain. Several studies have shown behavioral effects of tES, but stimulation artifacts complicate the simultaneous investigation of neural activity with EEG or MEG. Here, we first show for EEG and MEG, that contrary to previous assumptions, artifacts do not simply reflect stimulation currents, but that heartbeat and respiration non-linearly modulate stimulation artifacts. These modulations occur irrespective of the stimulation frequency, i.e. during both transcranial alternating and direct current stimulations (tACS and tDCS). Second, we show that, although at first sight previously employed artifact rejection methods may seem to remove artifacts, data are still contaminated by non-linear stimulation artifacts. Because of their complex nature and dependence on the subjects' physiological state, these artifacts are prone to be mistaken as neural entrainment. In sum, our results uncover non-linear tES artifacts, show that current techniques fail to fully remove them, and pave the way for new artifact rejection methods.

A Bidirectional Neural Interface Circuit With Active Stimulation Artifact Cancellation and Cross-Channel Common-Mode Noise Suppression

This work presents a bidirectional neural interface circuit that enables simultaneous recording and stimulation with a stimulation artifact cancellation circuit. The system employs a common average referencing (CAR) front-end circuit to suppress cross-channel environmental noise to further facilitate use in clinical environment. This paper also introduces a new range-adapting (RA) SAR ADC to lower the system power consumption. A prototype is fabricated in $0.18\;\mu {\rm{m}}$ CMOS and characterized and tested in vivo in an epileptic rat model. The prototype attenuates stimulation artifacts by up to 42 dB and suppresses cross-channel noise by up to 39.8 dB. The measured power consumption per channel is 330 nW, while the area per channel is 0.17 mm $^2$ .

Moving average template subtraction to remove stimulation artefacts in EEGs and LFPs recorded during deep brain stimulation

BackgroundDeep brain stimulation (DBS) is a well established therapy to treat movement disorders such as Parkinson's disease. More recently it has also been discussed as a therapy for certain psychiatric diseases. However, during active DBS the recordings of local field potentials (LFP) and the electroencephalogram (EEG) can be corrupted by substantial spike-type artefacts which need to be removed before any analysis. New methodHere, we present a new method that we term ' Moving Average Subtraction' (MAS) that removes DBS artefacts by subtracting adaptive DBS artefact templates from the artefact contaminated data. In particular we have developed a resampling technique which is more efficient than upsampling for a precise reconstruction of the artefact shape without the need to oversample the EEGs. ResultsBy applying this method we can derive undistorted signals even in case of the low sampling frequencies that are usual in clinical recordings. We applied the new technique to 12 data sets recorded at the surface and in various brain structures [subthalamic nucleus (STN), pedunculo pontine nucleus (PPN), Globus pallidus internus (GPi)] with 7 patients. Our results demonstrate the suppression of artefact related activity at the basic and harmonic frequencies of DBS. Comparison with existing method(s)The new technique outperforms the non-adaptive template subtraction technique for the removal of high frequency artefact residuals without producing the spectral dips that occur with notch filter approaches. ConclusionsThe new technique facilitates the analysis of higher frequency bands (Gamma activity) in LFPs and EEGs recorded during active DBS.

An Automated Method for Characterization of Evoked Single-Trial Local Field Potentials Recorded from Rat Barrel Cortex Under Mechanical Whisker Stimulation

Rodents explore their surroundings through whisking by localizing objects and detecting textures very precisely. During such tactile exploration, whisker deflection is first mechanically transduced by receptors and then information encoded throughout the somatosensory pathway ending in the somatosensory ‘barrel’ cortex. In the barrel cortex, tactile information from a single whisker is segregated and processed in a cortical column corresponding to the deflected whisker. Local Field Potentials (LFPs) generated by whisker deflection in the barrel cortex present typical signatures in terms of shape and amplitude that are related to the activation of the local neuronal populations. Therefore, rigorous analysis of such responses may reveal important features about the function of underlying neuronal microcircuits. In this context, software methods for characterizing single-trial LFPs are needed that are also suitable for online extraction of LFP features and for brain–machine interfacing applications. In this work, we present an automated and efficient method to analyze evoked LFP responses in the rat barrel cortex through automatic removal of stimulation artifacts, detection of single events and characterization of their relevant parameters. Evoked single-trial LFPs recorded under two different anesthetics are examined to demonstrate the feasibility, accuracy and applicability of the method.

Auditory steady-state responses in cochlear implant users: Effect of modulation frequency and stimulation artifacts

Previous studies have shown that objective measures based on stimulation with low-rate pulse trains fail to predict the threshold levels of cochlear implant (CI) users for high-rate pulse trains, as used in clinical devices. Electrically evoked auditory steady-state responses (EASSRs) can be elicited by modulated high-rate pulse trains, and can potentially be used to objectively determine threshold levels of CI users. The responsiveness of the auditory pathway of profoundly hearing-impaired CI users to modulation frequencies is, however, not known. In the present study we investigated the responsiveness of the auditory pathway of CI users to a monopolar 500 pulses per second (pps) pulse train modulated between 1 and 100 Hz. EASSRs to forty-three modulation frequencies, elicited at the subject's maximum comfort level, were recorded by means of electroencephalography. Stimulation artifacts were removed by a linear interpolation between a pre- and post-stimulus sample (i.e., blanking). The phase delay across modulation frequencies was used to differentiate between the neural response and a possible residual stimulation artifact after blanking. Stimulation artifacts were longer than the inter-pulse interval of the 500pps pulse train for recording electrodes ipsilateral to the CI. As a result the stimulation artifacts could not be removed by artifact removal on the bases of linear interpolation for recording electrodes ipsilateral to the CI. However, artifact-free responses could be obtained in all subjects from recording electrodes contralateral to the CI, when subject specific reference electrodes (Cz or Fpz) were used. EASSRs to modulation frequencies within the 30–50 Hz range resulted in significant responses in all subjects. Only a small number of significant responses could be obtained, during a measurement period of 5 min, that originate from the brain stem (i.e., modulation frequencies in the 80–100 Hz range). This reduced synchronized activity of brain stem responses in long-term severely-hearing impaired CI users could be an attribute of processes associated with long-term hearing impairment and/or electrical stimulation.

Stimulation artifact correction method for estimation of early cortico-cortical evoked potentials

BackgroundEffective connectivity can be explored using direct electrical stimulations in patients suffering from drug-resistant focal epilepsies and investigated with intracranial electrodes. Responses to brief electrical pulses mimic the physiological propagation of signals and manifest as cortico-cortical evoked potentials (CCEP). The first CCEP component is believed to reflect direct connectivity with the stimulated region but the stimulation artifact, a sharp deflection occurring during a few milliseconds, frequently contaminates it. New methodIn order to recover the characteristics of early CCEP responses, we developed an artifact correction method based on electrical modeling of the electrode–tissue interface. The biophysically motivated artifact templates are then regressed out of the recorded data as in any classical template-matching removal artifact methods. ResultsOur approach is able to make the distinction between the physiological responses time-locked to the stimulation pulses and the non-physiological component. We tested the correction on simulated CCEP data in order to quantify its efficiency for different stimulation and recording parameters. We demonstrated the efficiency of the new correction method on simulations of single trial recordings for early responses contaminated with the stimulation artifact. The results highlight the importance of sampling frequency for an accurate analysis of CCEP. We then applied the approach to experimental data. Comparison with existing methodThe model-based template removal was compared to a correction based on the subtraction of the averaged artifact. ConclusionsThis new correction method of stimulation artifact will enable investigators to better analyze early CCEP components and infer direct effective connectivity in future CCEP studies.

Intraoperative electrocorticography for physiological research in movement disorders: principles and experience in 200 cases.

OBJECTIVE Contemporary theories of the pathophysiology of movement disorders emphasize abnormal oscillatory activity in basal ganglia-thalamocortical loops, but these have been studied in humans mainly using depth recordings. Recording from the surface of the cortex using electrocorticography (ECoG) provides a much higher amplitude signal than depth recordings, is less susceptible to deep brain stimulation (DBS) artifacts, and yields a surrogate measure of population spiking via "broadband gamma" (50-200 Hz) activity. Therefore, a technical approach to movement disorders surgery was developed that employs intraoperative ECoG as a research tool. METHODS One hundred eighty-eight patients undergoing DBS for the treatment of movement disorders were studied under an institutional review board-approved protocol. Through the standard bur hole exposure that is clinically indicated for DBS lead insertion, a strip electrode (6 or 28 contacts) was inserted to cover the primary motor or prefrontal cortical areas. Localization was confirmed by the reversal of the somatosensory evoked potential and intraoperative CT or 2D fluoroscopy. The ECoG potentials were recorded at rest and during a variety of tasks and analyzed offline in the frequency domain, focusing on activity between 3 and 200 Hz. Strips were removed prior to closure. Postoperative MRI was inspected for edema, signal change, or hematoma that could be related to the placement of the ECoG strip. RESULTS One hundred ninety-eight (99%) strips were successfully placed. Two ECoG placements were aborted due to resistance during the attempted passage of the electrode. Perioperative surgical complications occurred in 8 patients, including 5 hardware infections, 1 delayed chronic subdural hematoma requiring evacuation, 1 intraparenchymal hematoma, and 1 venous infarction distant from the site of the recording. None of these appeared to be directly related to the use of ECoG. CONCLUSIONS Intraoperative ECoG has long been used in neurosurgery for functional mapping and localization of seizure foci. As applied during DBS surgery, it has become an important research tool for understanding the brain networks in movement disorders and the mechanisms of therapeutic stimulation. In experienced hands, the technique appears to add minimal risk to surgery.

Modelling And Removal Of Stimulation Artifact In MEA Recordings

Event Abstract Back to Event Modelling And Removal Of Stimulation Artifact In MEA Recordings Michał Czerwiński1*, Marinka Brouwer2, Dirk Schubert2 and Daniel K. Wójcik3 1 Nencki Institute of Experimental Biology of Polish Academy of Sciences, Laboratory of Neuroinformatics, Department of Neurophysiology, Poland 2 Radboud University Medical Centre, Donders Institute for Brain, Cognition, and Behaviour, The Netherlands 3 Nencki Institute of Experimental Biology, Laboratory of Neuroinformatics, Department of Neurophysiology, Poland Encountering a prominent stimulation artifact on Multi-Electrode Array (MEA) recordings one should study its properties and inquire if it is influencing the results of data analysis. Here we study an example experiment where a significant stimulation artifact was observed. We present an automatic method of artifact subtraction and differentiation of various physical phenomena recorded by a MEA in rat's barrel cortex slices. Keywords: barrel cortex, LFP, CSD, stimulation artifacts Conference: MEA Meeting 2016 | 10th International Meeting on Substrate-Integrated Electrode Arrays, Reutlingen, Germany, 28 Jun - 1 Jul, 2016. Presentation Type: Poster Presentation Topic: MEA Meeting 2016 Citation: Czerwiński M, Brouwer M, Schubert D and Wójcik DK (2016). Modelling And Removal Of Stimulation Artifact In MEA Recordings. Front. Neurosci. Conference Abstract: MEA Meeting 2016 | 10th International Meeting on Substrate-Integrated Electrode Arrays. doi: 10.3389/conf.fnins.2016.93.00029 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 22 Jun 2016; Published Online: 24 Jun 2016. * Correspondence: Dr. Michał Czerwiński, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Laboratory of Neuroinformatics, Department of Neurophysiology, Warsaw, Poland, m.czerwinski@nencki.gov.pl Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Michał Czerwiński Marinka Brouwer Dirk Schubert Daniel K Wójcik Google Michał Czerwiński Marinka Brouwer Dirk Schubert Daniel K Wójcik Google Scholar Michał Czerwiński Marinka Brouwer Dirk Schubert Daniel K Wójcik PubMed Michał Czerwiński Marinka Brouwer Dirk Schubert Daniel K Wójcik Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

A 3D-Capable, Flexible, Hybrid �ECoG Optrode

A 3D-Capable, Flexible, Hybrid �ECoG Optrode

Blanking circuits: Culprit or Savior?

Blanking circuits: Culprit or Savior?

Time Evolution Of Spike Activity In Hippocampal Neurons During Paired-Pulse Stimulation Of DG-CA3 Reconstructed Networks

Time Evolution Of Spike Activity In Hippocampal Neurons During Paired-Pulse Stimulation Of DG-CA3 Reconstructed Networks

Realtime EMG analysis for transcutaneous electrical stimulation assisted gait training in stroke patients

Abstract: This contribution describes a method for realtime analysis of muscle activity during application of Functional Electrical Stimulation (FES) to the assessed muscles. Inertial sensors at the foot are used for realtime gait phase detection in order to synchronize the stimulation with the gait. After detecting and muting stimulation artifacts and after extraction of Inputer-Pulse Intervals (IPIs), a non-causal high-pass filter is applied to a section of the IPI to extract the voluntary EMG activity. The filter suppresses FES-evoked EMG activity (M-wave) and electrode discharging artifacts. The initial filter states are chosen by an optimization procedure to minimize undesired filter transients. The obtained filtered EMG signal is then rectified and averaged to produce a scalar measure of the volitional EMG activity over the last IPI. The volitional EMG activity during four different detected gait phases is calculated after every completed step and displayed to the stroke patients for biofeedback or to the therapist in order to adjust the FES. The system has been initially evaluated with healthy subjects walking on a treadmill. It was demonstrated that different walking styles of an individual can be distinguished by the EMG analysis also during active FES support.

Modulation of local field potentials by high-frequency stimulation of afferent axons in the hippocampal CA1 region.

Modulation of the rhythmic activity of local field potentials (LFP) in neuronal networks could be a mechanism of deep brain stimulation (DBS). However, exact changes of LFP during the periods of high-frequency stimulation (HFS) of DBS are unclear because of the interference of dense stimulation artifacts with high amplitudes. In the present study, we investigated LFP changes induced by HFS of afferent axons in the hippocampal CA1 region of urethane-anesthetized rats by using a proper algorithm of artifact removal. Afterward, the LFP changes in the frequency bands of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] rhythms were studied by power spectrum analysis and coherence analysis for the recorded signals collected in the pyramidal layer and in the stratum radiatum of CA1 region before, during and after 1-min long 100 and 200[Formula: see text]Hz HFS. Results showed that the power of LFP rhythms in higher-frequency band ([Formula: see text] rhythm) increased in the pyramidal layer and the power of LFP rhythms in lower-frequency bands ([Formula: see text], [Formula: see text] and [Formula: see text] rhythms) decreased in the stratum radiatum during HFS. The synchronization of [Formula: see text] rhythm decreased and the synchronization of [Formula: see text] rhythm increased during HFS in the stratum radiatum. These results suggest that axonal HFS could modulate LFP rhythms in the downstream brain areas with a plausible underlying mechanism of partial axonal blockage induced by HFS. The study provides new evidence to support the mechanism of DBS modulating rhythmic activity of neuronal populations.

Removal of Transcranial a.c. Current Stimulation artifact from simultaneous EEG recordings by superposition of moving averages.

Transcranial Current Stimulation (tCS) is a recent development for non-invasive brain stimulation. At present tCS introduces large artifacts into simultaneous EEG (electroencephalogram) recordings, which must be removed to enable brain changes from during the stimulation to be monitored. This paper presents a new approach for removing artifacts of transcranial Alternating Current Stimulation (tACS) from simultaneous EEG. Termed the Superposition of Moving Averages (SMA) our approach is independent of the number of EEG channels used and has a low computational complexity for use in real-time online artifact removal and data responsive stimulation. Compared to a Principal Component Analysis (PCA) approach our results show that SMA achieves superior artifact removal performance, especially with regards to the use of low channel count EEG devices.

A wavelet based method for electrical stimulation artifacts removal in electromyogram

A technique for artifact removal based on the continuous wavelet transform is presented. It uses common mother wavelets to find the temporal localization of stimulation artifacts on electromyogram signal recording during an electrical surface evoked contraction of a muscle. This method is applied with different kinds of stimulation pulse parameters including shape and duration changes. This method is used with standard stimulation pulse waveforms such as monophasic or biphasic ones. It can also be applied when the artifacts and M waves are in the same range of amplitude where threshold techniques are inefficient. Lastly, a method to determine which mother wavelet efficiently removed artifacts is proposed, results indicate the Haar wavelet performs best among fourteen tested wavelets.

Reduction of stimulation coherent artifacts in electrically evoked auditory brainstem responses

Abstract The electrically evoked auditory brainstem response (eABR) is one of the clinically employed objective evaluation tools for cochlear implant (CI) subjects. It is commonly obtained by averaging responses, but because of the electric CI stimulation, some artifacts are phase locked to the stimulus and do not average out by increasing repetitions. A series of artifact reduction methods, such as general post-processing procedures for all subjects and individual post-processing procedures for some subjects, were developed in this study, aiming at reducing CI stimulation coherent artifacts. Seven bilateral CI subjects were recruited, and both monaural and binaural multi-channel eABRs were recorded in this study. The results show that the CI stimulation pulse artifacts can be efficiently removed by the general post-processing procedure, using alternating polarity stimuli combined with linear interpolation. Recordings obtained with non-alternating polarity show a strong exponential decay. Exponential fitting and subtraction worked reasonably well in this case. For eABR recordings contaminated with facial nerve stimulation (FNS) artifacts, principle component analysis was introduced to minimize the FNS artifacts for potential clinic application in the future.