Linear Electrode Array Research Articles

Clustering index analysis on EMG-Torque relation-based representation of complex neuromuscular changes after spinal cord injury

Spinal cord injury (SCI) resulting in complex neuromuscular pathology is not sufficiently well understood. To better quantify neuromuscular changes after SCI, this study uses a clustering index (CI) method for surface electromyography (sEMG) clustering representation to investigate the relation between sEMG and torque in SCI survivors. The sEMG signals were recorded from 13 subjects with SCI and 13 gender-age matched able-bodied subjects during isometric contraction of the biceps brachii muscle at different torque levels using a linear electrode array. Two torque representations, maximum voluntary contraction (MVC%) and absolute torque, were used. CI values were calculated for sEMG. Regression analyses were performed on CI values and torque levels of elbow flexion, revealing a strong linear relationship. The slopes of regressions between SCI survivors and control subjects were compared. The findings indicated that the range of distribution of CI values and slopes was greater in subjects with SCI than in control subjects (p < 0.05). The increase or decrease in slope was also observed at the individual level. This suggests that the CI and its sEMG clustering-torque relation may serve as valuable quantitative indicators for determining neuromuscular lesions after SCI, contributing to the development of effective rehabilitation strategies for improving motor performance.

Towards standardisation of surface electromyography measurements in the horse: Bipolar electrode location

The use of surface electromyography in the field of animal locomotion has increased considerably over the past decade. However, no consensus exists on the methodology for data collection in horses. This study aimed to start the development of recommendations for bipolar electrode locations to collect surface electromyographic data from horses during dynamic tasks.Data were collected from 21 superficial muscles of three horses during trot on a treadmill using linear electrode arrays. The data were assessed both quantitatively (signal-to-noise ratio (SNR) and coefficient of variation (CoV)) and qualitatively (presence of crosstalk and activation patterns) to compare and select electrode locations for each muscle.For most muscles and horses, the highest SNR values were detected near or cranial/proximal to the central region of the muscle. Concerning the CoV, there were larger differences between muscles and horses than within muscles. Qualitatively, crosstalk was suspected to be present in the signals of twelve muscles but not in all locations in the arrays.With this study, a first attempt is made to develop recommendations for bipolar electrode locations for muscle activity measurements during dynamic contractions in horses. The results may help to improve the reliability and reproducibility of study results in equine biomechanics.

Muscle Fiber Conduction Velocity During Electrically Stimulated Contraction at Various Joint Angles, During Joint Movements, and During Voluntary Contractions.

Muscle fiber conduction velocity (MFCV) can be affected by muscle fiber geometry at different joint angles and during joint movements. This study aimed to investigate MFCV during electrically evoked contraction at different joint angles, during joint movements, and during voluntary contractions. Sixteen healthy young men participated. A stimulation electrode was attached on the innervation zone of the vastus lateralis, and a linear electrode array was attached on the vastus lateralis. Under a static condition, electrically evoked electromyography signals were recorded at knee joint angles set every 15° between 0° and 105°. Under a passive movement condition, signals were recorded during knee extension and flexion passively. Under a voluntary contraction condition, signals were recorded while performing 30% or 60% of maximum voluntary contraction. MFCV was calculated using cross-correlation coefficients. Under the static condition, there were no differences in MFCV among various joint angles. Under the passive movement condition, MFCV was significantly greater during high velocity or shortening. Under the voluntary contraction condition, MFCV was significantly greater during high-intensity voluntary contraction and with a shortened muscle length. Joint angles do not influence MFCV markedly during relaxation, but it is possible to overestimate MFCV during movement or voluntary contraction.

Electrophysiology of Laminar Cortical Activity in the Common Marmoset.

The marmoset monkey provides an ideal model for examining laminar cortical circuits due to its smooth cortical surface, which facilitates recordings with linear arrays. The marmoset has recently grown in popularity due to its similar neural functional organization to other primates and its technical advantages for recording and imaging. However, neurophysiology in this model poses some unique challenges due to the small size and lack of gyri as anatomical landmarks. Using custom-built micro-drives, researchers can manipulate linear array placement to sub-millimeter precision and reliably record at the same retinotopically targeted location across recording days. This protocol describes the step-by-step construction of the micro-drive positioning system and the neurophysiological recording technique with silicon linear electrode arrays. With precise control of electrode placement across recording sessions, researchers can easily traverse the cortex to identify areas of interest based on their retinotopic organization and the tuning properties of the recorded neurons. Further, using this laminar array electrode system, it is possible to apply a current source density analysis (CSD) to determine the recording depth of individual neurons. This protocol also demonstrates examples of laminar recordings, including spike waveforms isolated in Kilosort, which span multiple channels on the arrays.

Comparative Study of Terminal Cortical Potentials Using Iridium and Ag/AgCl Electrodes.

Brain ischemia induces slow voltage shifts in the cerebral cortex, including waves of spreading depolarization (SD) and negative ultraslow potentials (NUPs), which are considered as brain injury markers. However, different electrode materials and locations yield variable SD and NUP features. Here, we compared terminal cortical events during isoflurane or sevoflurane euthanasia using intracortical linear iridium electrode arrays and Ag/AgCl-based electrodes in the rat somatosensory cortex. Inhalation of anesthetics caused respiratory arrest, associated with hyperpolarization and followed by SD and NUP on both Ir and Ag electrodes. Ag-NUPs were bell shaped and waned within half an hour after death. Ir-NUPs were biphasic, with the early fast phase corresponding to Ag-NUP, and the late absent on Ag electrodes, phase of a progressive depolarizing voltage shift reaching -100 mV by two hours after death. In addition, late Ir-NUPs were more ample in the deep layers than at the cortical surface. Thus, intracortical Ag and Ir electrodes reliably assess early manifestations of terminal brain injury including hyperpolarization, SD and the early phase of NUP, while the late, giant amplitude phase of NUP, which is present only on Ir electrodes, is probably related to the sensitivity of Ir electrodes to a yet unidentified factor related to brain death.

Electromyography-Force Relation and Muscle Fiber Conduction Velocity Affected by Spinal Cord Injury.

A surface electromyography (EMG) analysis was performed in this study to examine central neural and peripheral muscle changes after a spinal cord injury (SCI). A linear electrode array was used to record surface EMG signals from the biceps brachii (BB) in 15 SCI subjects and 14 matched healthy control subjects as they performed elbow flexor isometric contractions from 10% to 80% maximum voluntary contraction. Muscle fiber conduction velocity (MFCV) and BB EMG-force relation were examined. MFCV was found to be significantly slower in the SCI group than the control group, evident at all force levels. The BB EMG-force relation was well fit by quadratic functions in both groups. All healthy control EMG-force relations were best fit with positive quadratic coefficients. In contrast, the EMG-force relation in eight SCI subjects was best fit with negative quadratic coefficients, suggesting impaired EMG modulation at high forces. The alterations in MFCV and EMG-force relation after SCI suggest complex neuromuscular changes after SCI, including alterations in central neural drive and muscle properties.

Using DC resistivity ring array surveys to resolve conductive structures around tunnels or mine-workings

In underground environments, conventional direct current (DC) resistivity surveys with a single linear array of electrodes produce fundamentally non-unique inversions. These non-uniqueness and model resolution issues stem from limitations placed on the location of transmitters (TXs) and receivers (RXs) by the geometry of existing tunnels and boreholes. Poor excitation and/or sampling of the region of interest (ROI) can create artifacts and reduce the resolution of the recovered model.To address these problems we propose the use of an ensemble of ring arrays, which are created by placing one or more electrodes in each face (sidewalls, floor, and ceiling) of the tunnel to form a ring of electrodes at each along-tunnel location. Using a series of increasingly complex synthetic models, we assess the benefits of ring arrays and show that they can be used to better constrain the location and shape of anomalous bodies around the tunnel.Although ring arrays significantly improve the resolution of the recovered model, the size of the comprehensive ring array survey increases rapidly with the number of electrodes used. To balance model resolution and survey size, we developed a physics-based survey design methodology. In this methodology, TXs are selected based upon secondary charge accumulations on a test block that is moved throughout the ROI. Although this survey design methodology does not produce a strictly optimal survey, it balances model resolution and survey size in a practical and computationally efficient manner.Since the ring array more accurately estimates the around-tunnel location of targets and ensures that targets on all sides of the tunnel are detected, it is ideally suited to tunnel-based environments. Our results show that only about 6% of the possible TXs and 0.5% of the RXs in the comprehensive ring array survey are needed to retain the improvements in resolution. Therefore, economical ring array surveys can be designed for both reconnaissance and target characterization. Following the inversion of the reconnaissance dataset, additional rings can be added to reduce the inter-ring spacing or off-tunnel boreholes can be added to the region around identified anomalies to increase resolution as required.

Sample Entropy-Based Surface Electromyographic Examination With a Linear Electrode Array in Survivors With Spinal Cord Injury.

This study aimed to evaluate the utility of sample entropy (SampEn) of surface electromyographic signals (sEMG) in quantifying neuromuscular changes after spinal cord injury (SCI). Using a linear electrode array, sEMG signals were obtained from the biceps brachii muscles of 13 healthy control subjects and 13 SCI subjects during isometric elbow flexion muscle contraction at various constant force levels. The SampEn analysis was performed on both the representative channel (emerging the largest signal amplitude) and the channel over muscle innervation zone (IZ) determined by the linear array. The SampEn values were further averaged across muscle force levels to examine difference between SCI survivors and control subjects. Results showed that SampEn values after SCI had a significantly greater range than those of the control subjects at the group level. Abnormal increases or decreases in SampEn were also found after SCI at the individual subject level. In addition, a significant difference was found between the representative channel and the IZ channel. SampEn is a valuable indicator for identifying neuromuscular changes after SCI, and the effect of the IZ on the sEMG examination is particularly noteworthy. The approach presented in this study may facilitate the development of appropriate rehabilitation methods to enhance motor recovery.

Bagged tree ensemble modelling with feature selection for isometric EMG-based force estimation

EMG-based force estimation is crucial in applications, such as control of powered prosthetic and rehabilitation devices. Most previous studies focus on intra-subject force modelling. However, a generalized EMG-force estimation model, which is capable of estimating force across users, is needed for surgical and rehabilitation robotics. In this study, EMG signals are recorded from the long head and short head of the biceps brachii, and brachioradialis using 3 linear surface electrode arrays, during isometric elbow flexions, at different joint angles and forearm postures, while recording the induced force at the wrist. The recorded EMGs are pre-processed and segmented, and 336 time and frequency domain features are extracted from 21 EMG channels. We explore developing a model that can perform well across subjects, where Bagged Tree Ensemble (BTE) models are used to learn the non-linear, complex relationships between the EMG and force data. The BTE models are compared with several machine learning approaches. The BTE model performs best, giving an average normalized mean squared error (%NMSE) of 5.65±16.24%. To reduce the dimensionality of the feature space and improve force estimation performance, a novel feature selection technique, called modified sequential feature selection (MSFS) is implemented and compared to other commonly used feature selection methods. Results show that the MSFS algorithm outperformed other methods tested, significantly reducing the force estimation error. We also found that there was no effect of forearm posture and joint angle on force modelling accuracy, permitting the development of an isometric force estimation model generalized across participants and arm positions.

A Comparison of Delay-and-Add and Maximum Likelihood Estimation for Velocity-Selective Recording Using Multi-Electrode Cuffs.

Extracting information from the peripheral nervous system with implantable devices remains a significant challenge that limits the advancement of closed-loop neural prostheses. Linear electrode arrays can record neural signals with both temporal and spatial selectivity, and velocity selective recording using the delay-and-add algorithm can enable classification based on fibre type. The maximum likelihood estimation method also measures velocity and is frequently used in electromyography but has never been applied to electroneurography. Therefore, this study compares the two algorithms using in-vivo recordings of electrically evoked compound action potentials from the ulnar nerve of a pig. The performance of these algorithms was assessed using the velocity quality factor (Q-factor), computational time and the influence of the number of channels. The results show that the performance of both algorithms is significantly influenced by the number of channels in the recording array, with accuracies ranging from 77% with only two channels to 98% for 11 channels. Both algorithms were comparable in accuracy and Q-factor for all channels, with the delay-and-add having a slight advantage in the Q-factor.

In vivo experimental validation of detection of gastric slow waves using a flexible multichannel electrogastrography sensor linear array

BackgroundCutaneous electrogastrography (EGG) is a non-invasive technique that detects gastric bioelectrical slow waves, which in part govern the motility of the stomach. Changes in gastric slow waves have been associated with a number of functional gastric disorders, but to date accurate detection from the body-surface has been limited due to the low signal-to-noise ratio. The main aim of this study was to develop a flexible active-electrode EGG array. Methods: Two Texas Instruments CMOS operational amplifiers: OPA2325 and TLC272BID, were benchtop tested and embedded in a flexible linear array of EGG electrodes, which contained four recording electrodes at 20-mm intervals. The cutaneous EGG arrays were validated in ten weaner pigs using simultaneous body-surface and serosal recordings, using the Cyton biosensing board and ActiveTwo acquisition systems. The serosal recordings were taken using a passive electrode array via surgical access to the stomach. Signals were filtered and compared in terms of frequency, amplitude, and phase-shift based on the classification of propagation direction from the serosal recordings. Results: The data were compared over 709 cycles of slow waves, with both active cutaneous EGG arrays demonstrating comparable performance. There was an agreement between frequencies of the cutaneous EGG and serosal recordings (3.01 ± 0.03 vs 3.03 ± 0.05 cycles per minute; p = 0.75). The cutaneous EGG also demonstrated a reduction in amplitude during abnormal propagation of gastric slow waves (310 ± 50 µV vs 277 ± 9 µV; p < 0.01), while no change in phase-shift was observed (1.28 ± 0.09 s vs 1.40 ± 0.10 s; p = 0.36). Conclusion: A sparse linear cutaneous EGG array was capable of reliably detecting abnormalities of gastric slow waves. For more accurate characterization of gastric slow waves, a two-dimensional body-surface array will be required.

Accurate Localization of Linear Probe Electrode Arrays across Multiple Brains.

Recently developed probes for extracellular electrophysiological recordings have large numbers of electrodes on long linear shanks. Linear electrode arrays, such as Neuropixels probes, have hundreds of recording electrodes distributed over linear shanks that span several millimeters. Because of the length of the probes, linear probe recordings in rodents usually cover multiple brain areas. Typical studies collate recordings across several recording sessions and animals. Neurons recorded in different sessions and animals thus have to be aligned to each other and to a standardized brain coordinate system. Here, we evaluate two typical workflows for localization of individual electrodes in standardized coordinates. These workflows rely on imaging brains with fluorescent probe tracks and warping 3D image stacks to standardized brain atlases. One workflow is based on tissue clearing and selective plane illumination microscopy (SPIM), whereas the other workflow is based on serial block-face two-photon (SBF2P) microscopy. In both cases electrophysiological features are then used to anchor particular electrodes along the reconstructed tracks to specific locations in the brain atlas and therefore to specific brain structures. We performed groundtruth experiments, in which motor cortex outputs are labeled with ChR2 and a fluorescence protein. Light-evoked electrical activity and fluorescence can be independently localized. Recordings from brain regions targeted by the motor cortex reveal better than 0.1-mm accuracy for electrode localization, independent of workflow used.

Neurophysiological Factors Affecting Muscle Innervation Zone Estimation Using Surface EMG: A Simulation Study.

Surface electromyography (EMG) recorded by a linear or 2-dimensional electrode array can be used to estimate the location of muscle innervation zones (IZ). There are various neurophysiological factors that may influence surface EMG and thus potentially compromise muscle IZ estimation. The objective of this study was to evaluate how surface-EMG-based IZ estimation might be affected by different factors, including varying degrees of motor unit (MU) synchronization in the case of single or double IZs. The study was performed by implementing a model simulating surface EMG activity. Three different MU synchronization conditions were simulated, namely no synchronization, medium level synchronization, and complete synchronization analog to M wave. Surface EMG signals recorded by a 2-dimensional electrode array were simulated from a muscle with single and double IZs, respectively. For each situation, the IZ was estimated from surface EMG and compared with the one used in the model for performance evaluation. For the muscle with only one IZ, the estimated IZ location from surface EMG was consistent with the one used in the model for all the three MU synchronization conditions. For the muscle with double IZs, at least one IZ was appropriately estimated from interference surface EMG when there was no MU synchronization. However, the estimated IZ was different from either of the two IZ locations used in the model for the other two MU synchronization conditions. For muscles with a single IZ, MU synchronization has little effect on IZ estimation from electrode array surface EMG. However, caution is required for multiple IZ muscles since MU synchronization might lead to false IZ estimation.

Assessing redistribution of muscle innervation zones after spinal cord injuries

This study aimed to examine the redistribution of neuromuscular junctions or innervation zones (IZs) after spinal cord injuries (SCI). Fifteen able-bodied subjects and 15 subjects with SCI (American Spinal Injury Association Impairment Scale A to D), participated in the study. Surface electromyography (EMG) signals were collected from the biceps brachii muscle by a customized linear electrode array when subjects generated maximal isometric voluntary contractions. The Radon transform was applied to detect the IZ locations in the multiple channel surface EMG signals which were differentiated between consecutive channels. The distribution of IZs was compared between the SCI and control groups using the student-t test. Statistical analysis disclosed a significantly wider range of IZs in the SCI group compared with the control group (SCI: 3.83 ± 1.32 IED, control: 2.83 ± 0. 87 IED, IED: inter-electrode distance, p < 0.05). No remarkable shifts of the center of the distribution were observed between the two groups (SCI: 9.23 ± 2.35 IED, control: 8.53 ± 2.33 IED, p = 0.42). Changes of IZ distribution in the paralyzed muscles could be associated with the complex neuromuscular reorganization after the SCI.

Abstract P730: MCA Stroke Chronically Disrupts Hippocampal Activity and Cortico-Hippocampal Communication

Introduction: Cognition and memory deficits are common sequelae following middle cerebral artery (MCA) stroke, one of the most common strokes in humans. However MCA stroke does not compromise the structural integrity of the hippocampus, which is highly involved in memory function, because the MCA does not supply blood flow to the hippocampus. We previously reported on the acute effect of MCA stroke, where we observed increased hippocampal activity and cortico-hippocampal communication. Here we investigate chronic changes to local oscillations and cortico-hippocampal communication following MCA occlusion in rats two weeks and one month following stroke. Hypothesis: Cortical stroke affects remote brain regions, disrupting hippocampal function and cortico-hippocampal communication. Methods: We subjected male rats (n=28) to distal MCA occlusion compared to controls (n=19). We recorded local field potentials simultaneously from cortex and hippocampus two weeks and one month following stroke using 16-site linear electrode arrays under urethane anesthesia. We analyzed signal power, brain state, CFC, and sharp wave SPW-Rs to assess hippocampal function and cortico-hippocampal communication. Results: Our results show disruptions to local oscillations; lowered delta (1-3 Hz) signal power in the cortex and hippocampus, increased signal power in gamma (30-60 Hz) and high gamma (60-200 Hz) in cortex and hippocampus. Theta/delta brain state is disrupted, and SPW-Rs increase in power at two weeks, before returning to baseline levels at one month. Communication is also disrupted; Theta-gamma coupling, a measure of information being communicated between regions, breaks down after stroke. Conclusions: These results suggest that chronic stroke causes significant changes to hippocampal function, which can be characterized by these electrophysiological biomarkers, establishing putative targets for targeted stimulation therapies.

Identification of muscle innervation zones using linear electrode arrays: a fundamental step to measure fibers conduction velocity

Fiber conduction velocity (CV) is a parameter correlated to the physiological membrane properties of the skeletal muscle fibers. Changes in muscle fiber CV are correlated to the gradation of force and fatigue, and can be measured by means of surface electromyography EMG (sEMG). sEMG measurement of CV during muscle contractions requires the correct identification of the skeletal muscle innervation zone (IZ). In superficial muscles, IZ location can be detected using linear electrode arrays and visually identified as the point of inversion of the detected motor unit action potential (MUAP) propagation. In the present work, we present a method for the effective and fast detection of the IZ location, through the following procedures: (1) identification of the target superficial muscle considering the muscle fiber architecture; (2) electrode array selection based on interelectrode distance and number of electrodes; (3) subject training to perform submaximal isometric contractions of the target muscle/s; (4) electrode array positioning along the muscle surface to investigate the IZ position during the contractions by visual identification of MUAP patterns.

The Referential Montage Inadequately Localizes Corticocortical Evoked Potentials in Stereoelectroencephalography.

Corticocortical evoked potentials (CCEPs) resulting from single pulse electrical stimulation are increasingly used to understand seizure networks, as well as normal brain connectivity. However, we observed that when using depth electrodes, traditional measures of CCEPs amplitude using a referential montage can be falsely localizing, often to white matter. We pooled 27 linear electrode arrays targeting the amygdala, hippocampus, or cingulate cortex from eight participants. Using postoperative imaging, we classified contacts as being in gray matter, white matter, or bordering each and measured the amplitude using the root-mean-squared deviation from baseline in a referential, common average, bipolar, or Laplacian montage. Of 27 electrode contacts, 25 (93%) had a significantly higher mean amplitude when in gray matter than in white matter using a Laplacian montage, which was significantly more than the 12 of 27 electrodes (44%) when using a referential montage ( P = 0.0003, Fisher exact test). The area under the curve for a receiver operating characteristic classifying contacts as gray or white matter was significantly higher for either the Laplacian (0.79) or the bipolar (0.72) montage when compared with either the common average (0.56) or the referential (0.51) montage ( P ≤ 0.005, bootstrap). Both the Laplacian and bipolar montages were superior to the common average or referential montage in localizing CCEPs to gray matter. These montages may be more appropriate for interpreting CCEPs when using depth electrodes than the referential montage, which has typically been used in prior studies of CCEPs with subdural grids.

Automated Channel Selection in High-Density sEMG for Improved Force Estimation.

Accurate and real-time estimation of force from surface electromyogram (EMG) signals enables a variety of applications. We developed and validated new approaches for selecting subsets of high-density (HD) EMG channels for improved and lower-dimensionality force estimation. First, a large dataset was recorded from a number of participants performing isometric contractions in different postures, while simultaneously recording HD-EMG channels and ground-truth force. The EMG signals were acquired from three linear surface electrode arrays, each with eight monopolar channels, and were placed on the long head and short head of the biceps brachii and brachioradialis. After data collection and pre-processing, fast orthogonal search (FOS) was employed for force estimation. To select a subset of channels, principal component analysis (PCA) in the frequency domain and a novel index called the power-correlation ratio (PCR), which maximizes the spectral power while minimizing similarity to other channels, were used. These approaches were compared to channel selection using time-domain PCA. We selected one, two, and three channels per muscle from the original seven differential channels to reduce the redundancy and correlation in the dataset. In the best case, we achieved an approximate improvement of for force estimation while reducing the dimensionality by for a subset of three channels.

Multi-Channel Surface EMG Spatio-Temporal Image Enhancement Using Multi-Scale Hessian-Based Filters

Surface electromyography (sEMG) signals acquired with linear electrode array are useful in analyzing muscle anatomy and physiology. Most algorithms for signal processing, detection, and estimation require adequate quality of the input signals, however, multi-channel sEMG signals are commonly contaminated due to several noise sources. The sEMG signal needs to be enhanced prior to the digital signal and image processing to achieve the best results. This study is using spatio-temporal images to represent surface EMG signals. The motor unit action potential (MUAP) in these images looks like a linear structure, making certain angles with the x-axis, depending on the conduction velocity of the MU. A multi-scale Hessian-based filter is used to enhance the linear structure, i.e., the MUAP region, and to suppress the background noise. The proposed framework is compared with some of the existing algorithms using synthetic, simulated, and experimental sEMG signals. Results show improved detection accuracy of the motor unit action potential after the proposed enhancement as a preprocessing step.

Color Columns in Visual Area V4

SummaryModels of the cerebral cortex propose a canonical columnar architecture preserved across the brain. Evidence for this model primarily stems from observations in primary sensory areas, such as the visual cortex, where neurons in an anatomical column respond preferentially to the same stimulus features. Similar columnar feature selectivity has been described for visual area V2, visual area V3 [9, 10], the middle temporal visual area (area V5), and inferotemporal cortex. The fourth visual area (V4) features color selective neurons, organized in clusters across its surface. However, whether these color-sensitive neurons are organized in a columnar fashion is debated and uncertain due to technical limitations. Here, we utilize laminar multielectrode recordings along V4 columns to resolve rival hypotheses. Linear electrode arrays were introduced orthogonally into area V4, spanning all cortical layers. Monkeys viewed color stimuli presented to the visual receptive field of the column of neurons. We found that preference for a specific color was conserved along depth but varied across columns. Interestingly, while color preference (e.g. red or green) was consistent along depth, color selectivity was significantly greater in upper layers relative to the input layer and was weakest in the lower layers. These findings demonstrate that area V4 is organized in functional columns like other visual areas.