Electrode Location Research Articles

The vitals for steady nucleation maps of spontaneous spiking coherence in autonomous two-dimensional neuronal networks

Thin pancake-like neuronal networks cultured on top of a planar microelectrode array have been extensively tried out in neuroengineering, as a substrate for the mobile robot’s control unit, i.e., as a cyborg’s brain. Most of these attempts failed due to intricate self-organizing dynamics in the neuronal systems. In particular, the networks may exhibit an emergent spatial map of steady nucleation sites (“n-sites”) of spontaneous population spikes. Being unpredictable and independent of the surface electrode locations, the n-sites drastically change local ability of the network to generate spikes. Here, using a spiking neuronal network model with generative spatially-embedded connectome, we systematically show in simulations that the number, location, and relative activity of spontaneously formed n-sites (“the vitals”) crucially depend on the samplings of three distributions: (1) the network distribution of neuronal excitability, (2) the distribution of connections between neurons of the network, and (3) the distribution of maximal amplitudes of a single synaptic current pulse. Moreover, blocking the dynamics of a small fraction (about 4%) of non-pacemaker neurons having the highest excitability was enough to completely suppress the occurrence of population spikes and their n-sites. This key result is explained theoretically. Remarkably, the n-sites occur taking into account only short-term synaptic plasticity, i.e., without a Hebbian-type plasticity. As the spiking network model used in this study is strictly deterministic, all simulation results can be accurately reproduced. The model, which has already demonstrated a very high richness-to-complexity ratio, can also be directly extended into the three-dimensional case, e.g., for targeting peculiarities of spiking dynamics in cerebral (or brain) organoids. We recommend the model as an excellent illustrative tool for teaching network-level computational neuroscience, complementing a few benchmark models.

Earthing System Analysis for Steel Tower Carrying 33kV Line

This study examines the critical analysis of earthing systems connected to steel towers that carry 33 kV power lines. Ensuring the safety and dependability of power transmission infrastructure becomes crucial in light of the growing demand for energy. By utilizing sophisticated computational methodologies and simulation approaches, this research carefully investigates how well the earthing system performs in various operational circumstances and fault scenarios. A thorough modeling technique is used in the analysis, which considers a number of variables including fault currents, tower design, soil resistivity, and grounding electrode configurations. In order to give a comprehensive understanding of the behavior of the system and its consequences for operational reliability, the study simulates many situations, including normal operation and fault occurrences. By using sophisticated numerical simulations and sensitivity analysis, the research pinpoints important factors affecting the earthing system's efficiency and suggests creative optimization techniques. These optimization techniques could involve changing the location of the grounding electrode, improving the materials used in the conductor, or putting additional safety precautions in place. The researcher's conclusions have important ramifications for the engineering community since they provide practical advice on how to strengthen the security and robustness of power transmission networks. The study adds to the continuous efforts to improve the efficiency and dependability of electrical grids by addressing potential weaknesses in the architecture of the earthing system. This thorough study advances the field of earthing system engineering by offering a solid platform for next studies and real-world implementations. Through this work, we can better understand the dynamics of earthing systems and optimization methodologies, which will help build more resilient and sustainable power transmission infrastructure that can adapt to society's changing energy needs.

Redox-mediated Biomolecular information transfer in single electrogenetic biological cells

Electronic communication in natural systems makes use, inter alia, of molecular transmission, where electron transfer occurs within networks of redox reactions, which play a vital role in many physiological systems. In view of the limited understanding of redox signaling, we developed an approach and an electrochemical–optical lab-on-a-chip to observe cellular responses in localized redox environments. The developed fluidic micro-system uses electrogenetic bacteria in which a cellular response is activated to electrically and chemically induced stimulations. Specifically, controlled environments for the cells are created by using microelectrodes to generate spatiotemporal redox gradients. The in-situ cellular responses at both single-cell and population levels are monitored by optical microscopy. The elicited electrogenetic fluorescence intensities after 210 min in response to electrochemical and chemical activation were 1.3 × 108±0.30 × 108 arbitrary units (A.U.) and 1.2 × 108±0.30 × 108 A.U. per cell population, respectively, and 1.05 ± 0.01 A.U. and 1.05 ± 0.01 A.U. per-cell, respectively. We demonstrated that redox molecules' mass transfer between the electrode and cells – and not the applied electrical field – activated the electrogenetic cells. Specifically, we found an oriented amplified electrogenetic response on the charged electrodes' downstream side, which was determined by the location of the stimulating electrodes and the flow profile. We then focused on the cellular responses and observed distinct subpopulations that were attributed to electrochemical rather than chemical stimulation, with the distance between the cells and the stimulating electrode being the main determinant. These observations provide a comprehensive understanding of the mechanisms by which diffusible redox mediators serve as electron shuttles, imposing context and activating electrogenetic responses.

Worldwide differences in surgeon intraoperative practices for cochlear implantation

Objective To characterize practice patterns of intraoperative imaging and/or functional confirmation of cochlear implant electrode location worldwide. Methods A cross-sectional survey of otolaryngologists performing cochlear implantation was conducted between March 1 and May 6, 2023. Participants were recruited worldwide using an international otologic society membership email list and at professional meetings. Ninety-seven of the 125 invited participants (78%) completed the survey. Participants were categorized by continent. Results North American surgeons use intraoperative X-rays more frequently than surgeons in Europe and Asia (p < 0.001). Otolaryngologists in Europe and Asia more frequently use no intraoperative imaging (p = 0.02). There is no regional difference between the intraoperative use of electrophysiologic instruments. European and Asian surgeons implant MED-EL devices (p = 0.012) more frequently than North American surgeons, who more frequently use Cochlear Corporation devices (p = 0.003). MED-EL use is related to less frequent intraoperative X-ray use (p = 0.02). Advanced Bionics use is related to more frequent intraoperative CT use (p = 0.03). No significant association existed between years of practice, number of cochlear implantation surgeries performed yearly, volume of pediatric CI practice, and use of intraoperative tools. Conclusion Intraoperative practice for radiologic and functional verification of cochlear implant electrode positioning varies worldwide. Practice guidelines may help establish a standard of care for cochlear implantation.

Temporal-Posterior Alpha Power in Resting-State Electroencephalography as a Potential Marker of Complex Childhood Trauma in Institutionalized Adolescents.

The present study explored whether, given the association of temporal alpha with fear circuitry (learning and conditioning), exposure to complex childhood trauma (CCT) is reflected in the temporal-posterior alpha power in resting-state electroencephalography (EEG) in complex trauma-exposed adolescents in a sample of 25 adolescents and similar controls aged 12-17 years. Both trauma and psychopathology were screened or assessed, and resting-state EEG was recorded following a preregistered protocol for data collection. Temporal-posterior alpha power, corresponding to the T5 and T6 electrode locations (international 10-20 system), was extracted from resting-state EEG in both eyes-open and eyes-closed conditions. We found that in the eyes-open condition, temporal-posterior alpha was significantly lower in adolescents exposed to CCT relative to healthy controls, suggesting that childhood trauma exposure may have a measurable impact on alpha oscillatory patterns. Our study highlights the importance of considering potential neural markers, such as temporal-posterior alpha power, to understanding the long-term consequences of CCT exposure in developmental samples, with possible important clinical implications in guiding neuroregulation interventions.

Predicting Postoperative Speech Perception and Audiometric Thresholds Using Intracochlear Electrocochleography in Cochlear Implant Recipients.

Electrocochleography (ECochG) appears to offer the most accurate prediction of post-cochlear implant hearing outcomes. This may be related to its capacity to interrogate the health of underlying cochlear tissue. The four major components of ECochG (cochlear microphonic [CM], summating potential [SP], compound action potential [CAP], and auditory nerve neurophonic [ANN]) are generated by different cochlear tissue components. Analyzing characteristics of these components can reveal the state of hair and neural cell in a cochlea. There is limited evidence on the characteristics of intracochlear (IC) ECochG recordings measured across the array postinsertion but compared with extracochlear recordings has better signal to noise ratio and spatial specificity. The present study aimed to examine the relationship between ECochG components recorded from an IC approach and postoperative speech perception or audiometric thresholds. In 113 human subjects, responses to 500 Hz tone bursts were recorded at 11 IC electrodes across a 22-electrode cochlear implant array immediately following insertion. Responses to condensation and rarefaction stimuli were then subtracted from one another to emphasize the CM and added to one another to emphasize the SP, ANN, and CAP. Maximum amplitudes and extracochlear electrode locations were recorded for each of these ECochG components. These were added stepwise to a multi-factor generalized additive model to develop a best-fit model predictive model for pure-tone audiometric thresholds (PTA) and speech perception scores (speech recognition threshold [SRT] and consonant-vowel-consonant phoneme [CVC-P]) at 3- and 12-month postoperative timepoints. This best-fit model was tested against a generalized additive model using clinical factors alone (preoperative score, age, and gender) as a null model proxy. ECochG-factor models were superior to clinical factor models in predicting postoperative PTA, CVC-P, and SRT outcomes at both timepoints. Clinical factor models explained a moderate amount of PTA variance ( r2 = 45.9% at 3-month, 31.8% at 12-month, both p < 0.001) and smaller variances of CVC-P and SRT ( r2 range = 6 to 13.7%, p = 0.008 to 0.113). Age was not a significant predictive factor. ECochG models explained more variance at the 12-month timepoint ( r2 for PTA = 52.9%, CVC-P = 39.6%, SRT = 36.4%) compared with the 3-month one timepoint ( r2 for PTA = 49.4%, CVC-P = 26.5%, SRT = 22.3%). The ECochG model was based on three factors: maximum SP deflection amplitude, and electrode position of CM and SP peaks. Adding neural (ANN and/or CAP) factors to the model did not improve variance explanation. Large negative SP deflection was associated with poorer outcomes and a large positive SP deflection with better postoperative outcomes. Mid-array peaks of SP and CM were both associated with poorer outcomes. Postinsertion IC-ECochG recordings across the array can explain a moderate amount of postoperative speech perception and audiometric thresholds. Maximum SP deflection and its location across the array appear to have a significant predictive value which may reflect the underlying state of cochlear health.

Structural Brain Connectivity Guided Optimal Contact Selection for Deep Brain Stimulation of the Subthalamic Nucleus

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy in ameliorating the motor symptoms of Parkinson disease. However, postoperative optimal contact selection is crucial for achieving the best outcome of deep brain stimulation of the subthalamic nucleus surgery, but the process is currently a trial-and-error and time-consuming procedure that relies heavily on surgeons' clinical experience. In this study, we propose a structural brain connectivity guided optimal contact selection method for deep brain stimulation of the subthalamic nucleus. Firstly, we reconstruct the DBS electrode location and estimate the stimulation range using volume of tissue activated from each DBS contact. Then, we extract the structural connectivity features by concatenating fractional anisotropy and the number of streamlines features of activated regions and the whole brain regions. Finally, we use a convolutional neural network with convolutional block attention module to identify the structural connectivity features for the optimal contact selection. We review the data of 800 contacts from 100 patients with Parkinson disease for the experiment. The proposed method achieves promising results, with the average accuracy of 97.63%, average precision of 94.50%, average recall of 94.46%, and average specificity of 98.18%, respectively. Our method can provide the suggestion for optimal contact selection. Our proposed method can improve the efficiency and accuracy of DBS optimal contact selection, reduce the dependence on surgeons' experience, and has the potential to facilitate the development of advanced DBS technology.

Optimal Channel Selection of Multiclass Motor Imagery Classification Based on Fusion Convolutional Neural Network with Attention Blocks.

The widely adopted paradigm in brain-computer interfaces (BCIs) involves motor imagery (MI), enabling improved communication between humans and machines. EEG signals derived from MI present several challenges due to their inherent characteristics, which lead to a complex process of classifying and finding the potential tasks of a specific participant. Another issue is that BCI systems can result in noisy data and redundant channels, which in turn can lead to increased equipment and computational costs. To address these problems, the optimal channel selection of a multiclass MI classification based on a Fusion convolutional neural network with Attention blocks (FCNNA) is proposed. In this study, we developed a CNN model consisting of layers of convolutional blocks with multiple spatial and temporal filters. These filters are designed specifically to capture the distribution and relationships of signal features across different electrode locations, as well as to analyze the evolution of these features over time. Following these layers, a Convolutional Block Attention Module (CBAM) is used to, further, enhance EEG signal feature extraction. In the process of channel selection, the genetic algorithm is used to select the optimal set of channels using a new technique to deliver fixed as well as variable channels for all participants. The proposed methodology is validated showing 6.41% improvement in multiclass classification compared to most baseline models. Notably, we achieved the highest results of 93.09% for binary classes involving left-hand and right-hand movements. In addition, the cross-subject strategy for multiclass classification yielded an impressive accuracy of 68.87%. Following channel selection, multiclass classification accuracy was enhanced, reaching 84.53%. Overall, our experiments illustrated the efficiency of the proposed EEG MI model in both channel selection and classification, showing superior results with either a full channel set or a reduced number of channels.

Accurate digitization of EEG electrode locations by electromagnetic tracking system: The proposed head rotation method and comparison against optical system

Electroencephalogram (EEG) electrode digitization is crucial for accurate EEG source estimation, and several commercial systems are available for this purpose. The present study aimed to evaluate the digitizing accuracy of electromagnetic and optical systems. Additionally, we introduced a novel rotation method for the electromagnetic system and compared its accuracy with the conventional method of electromagnetic and optical systems. In the conventional method, the operator moves around a stationary participant to digitize, while the participant does not move their head or body. In contrast, in our proposed rotation method with an electromagnetic system, the operator rotates the participant sitting on a swivel chair to digitize in a consistent position. We showed high localization accuracy in both the optical and electromagnetic systems, with an average localization error of less than 3.6 mm. Comparisons of the digitization methods revealed that the electromagnetic system demonstrates superior digitizing accuracy compared to the optical system. Notably, the proposed rotational method is the most accurate among the three methods, which can be attributed to the consistent positioning of EEG electrode digitization within the electromagnetic field. Considering the affordability of the electromagnetic system, our findings provide valuable insights for researchers aiming for precise EEG source estimation.•The study compares the accuracy of electromagnetic and optical systems for EEG electrode digitization, introducing a novel rotation method for improved consistency and precision.•The electromagnetic system, especially with the proposed rotation method, achieves superior digitizing accuracy over the optical system.•Highlighting the cost-effectiveness and precision of the electromagnetic system with the rotation method, this research offers significant insights for achieving precise EEG source estimation.

Multi-scale 3D-CRU for EEG emotion recognition* *This research has been supported by the National Natural Science Foundation of China Joint Fund Key Project (U2003207), National Natural Science Foundation of China (6220100261902064), Natural Science Foundation of Anhui Province (No. 1908085MF209), Key Projects of Natural Science Foundation of Anhui Province Universities (No. KJ2018A0018).

In this paper, we propose a novel multi-scale 3D-CRU model, with the goal of extracting more discriminative emotion feature from EEG signals. By concurrently exploiting the relative electrode locations and different frequency subbands of EEG signals, a three-dimensional feature representation is reconstructed wherein the Delta (δ) frequency pattern is included. We employ a multi-scale approach, termed 3D-CRU, to concurrently extract frequency and spatial features at varying levels of granularity within each time segment. In the proposed 3D-CRU, we introduce a multi-scale 3D Convolutional Neural Network (3D-CNN) to effectively capture discriminative information embedded within the 3D feature representation. To model the temporal dynamics across consecutive time segments, we incorporate a Gated Recurrent Unit (GRU) module to extract temporal representations from the time series of combined frequency-spatial features. Ultimately, the 3D-CRU model yields a global feature representation, encompassing comprehensive information across time, frequency, and spatial domains. Numerous experimental assessments conducted on publicly available DEAP and SEED databases provide empirical evidence supporting the enhanced performance of our proposed model in the domain of emotion recognition. These findings underscore the efficacy of the features extracted by the proposed multi-scale 3D-GRU model, particularly with the incorporation of the Delta (δ) frequency pattern. Specifically, on the DEAP dataset, the accuracy of Valence and Arousal are 93.12% and 94.31%, respectively, while on the SEED dataset, the accuracy is 92.25%.

Modulation of Diamond PN Junction Diode with Double-Layered n-Type Diamond by Using TCAD Simulation

This study proposed a novel double-layer junction termination structure for vertical diamond-based PN junction diodes (PND). The effects of the geometry and doping concentration of the junction termination structure on the PNDs’ electrical properties are investigated using Silvaco TCAD software (Version 5.0.10.R). It demonstrates that the electric performances of PND with a single n-type diamond layer are sensitive to the doping concentration and electrode location of the n-type diamond. To further suppress the electric field crowding and obtain a better balance between breakdown voltage and on-resistance, a double-layer junction termination structure is introduced and evaluated, yielding significantly improved electronic performances. Those results provide some useful thoughts for the design of vertical diamond PND devices.

The TD Drive: A Parametric, Open-Source Implant for Multi-Area Electrophysiological Recordings in Behaving and Sleeping Rats.

Intricate interactions between multiple brain areas underlie most functions attributed to the brain. The process of learning, as well as the formation and consolidation of memories, are two examples that rely heavily on functional connectivity across the brain. In addition, investigating hemispheric similarities and/or differences goes hand in hand with these multi-area interactions. Electrophysiological studies trying to further elucidate these complex processes thus depend on recording brain activity at multiple locations simultaneously and often in a bilateral fashion. Presented here is a 3D-printable implant for rats, named TD Drive, capable of symmetric, bilateral wire electrode recordings, currently in up to ten distributed brain areas simultaneously. The open-source design was created employing parametric design principles, allowing prospective users to easily adapt the drive design to their needs by simply adjusting high-level parameters, such as anterior-posterior and mediolateral coordinates of the recording electrode locations. The implant design was validated in n = 20 Lister Hooded rats that performed different tasks. The implant was compatible with tethered sleep recordings and open field recordings (Object Exploration) as well as wireless recording in a large maze using two different commercial recording systems and headstages. Thus, presented here is the adaptable design and assembly of a new electrophysiological implant, facilitating fast preparation and implantation.

The comparison and processing of Electromyography (EMG) signals under different actions

The experiment first investigates the working principle and the applications of Electromyography (EMG). Then, the effect of electrode location and electrode size on the EMG signal is explored by the raw data and theory. The reasons for choosing generic surface Ag/AgCl adhesive electrodes are also described. After obtaining the raw EMG signals, suitable data processing methods, such as Root Mean Square (RMS) and digital filtering are applied to generate signals that can drive the motor of a prosthetic arm. The results obtained by the two methods are also compared, where RMS can provide larger peak and mean values, and the digital filtering method can minimise the phase shift. Finally, the limitations of the EMG for prostheses are also analysed by three aspects: different flexion forces, individual finger motion and different reference locations.

Connectomic deep brain stimulators in Parkinson`s sub cortical functional zones

Shaking palsy is a brain disease involving motor and non motor zones affecting circa 1 to 2%of humans&amp;#62;60 years age. To date there has been no invention for curing this chronic disease and to stop its progression. But existing therapeutic procedures can offer symptomatic relief to Parkinson patients. DBS is most successful therapy for the Parkinson`s yet depends on the accuracy of electrode implantation and location within the anatomical subcortical neural-structures. This study examines the likelihood of net-work-based induced stimuli and the application of connectomic DBS in Parkinson`s. The subthalamic nucleus is divided into3 sub zones, namely, limbic (anterior), associative (middle) and motor (posterior) as well as diffusion weighted imaging (D W I). The surgical targets are tiny (few millimeters) and good enough to neuroanatomical-structures within the b r a i n. STN (size:12×5×3mm3) and lies nearby internal capsule, medial lemniscus, corticospinal tract, plus red-nucleus. Through sub optimal lead insertion and over stimuli, flow of electrons can spread to these adjoining sucortics, thereby developing dyskinesias ( ). With time, DW-MRI plus f-MRI is used to study the anatomical-structural functional connectivity in advanced idiopathic Parkinson`s. Contrasting conventional lesion based stimulus hypothesis, the novel net stimulus hypothesis advocated that induced stimulus of exact circuits of b r a i n can modulate pathophysiological net-work, reinstate near the tissue region, thus producing stabilization-of human-brain-connectome within Parkinson`s. The DBS connectomes makes use of circuit based stimulus procedure instead of lesion-based stimulus, has transformed neuromodulation. Connectomes via DBS can be tailor made for every Parkinson plus enhance the operation. It`s just a sketch for human-brain-connectivity (HMC) transversely compound longitudinal-scales. Yet, it won`t yield cell information plus cotacts with cells at the level of micro scale.

Analysis of reading-task-based brain connectivity in dyslexic children using EEG signals.

Developmental dyslexia, a neurodevelopment reading disorder, can impact even children with average intelligence. The present study examined the brain connectivity in dyslexic and control children during the reading task using graph theory. 19-channel electroencephalogram (EEG) signals were recorded from 15 dyslexic children and 15 control children. Functional connectivity was estimated by measuring the EEG coherence at 19 electrode locations, and graph measures were calculated using the graph theory method. Reading task results identified deprived task performance in dyslexic children against controls. Graph measures revealed longer path length, reduced clustering coefficient and reduced network efficiencies (in theta and alpha bands) of dyslexic group. At the nodal level, we found a significant increase in delta strength (T4 and T5 electrode locations) and reduced strength in theta (T6, P4, Fp1, F8 and F3) and alpha bands (T4, T3, P4 and F3) during the reading task in dyslexic group. In conclusion, the present study identified distinct graph measures between groups when performing a reading task and showed possible evidence for compromised brain networks in dyslexic group.

Assessing the Accuracy of ECG Chest Electrode Placement by EMS and Clinical Personnel Using Two Evaluation Methods

Background and purpose: A valid 12-lead electrocardiogram (ECG) depends on correct acquisition technique, particularly on the accurate location of precordial (chest) electrodes. The emergency medical services (EMS) segment of the care continuum is under-represented in previous clinically oriented studies of electrode placement. This study sought to assess the accuracy of chest electrode placement by EMS and clinical personnel in one geographic area, to identify patterns of misplacement to inform future training and continuing education, and to compare two methods of assessing electrode placement. Methods: This prospective observational study recruited a convenience sample of EMS and clinical personnel. Participants placed simulated electrodes on a CPR-style manikin and completed a questionnaire about their training and experience. A subset also marked electrode locations on a printed diagram of the ribcage. Digitized placement data and questionnaire responses were analysed statistically. Results: Findings from 149 participants showed misplacement patterns consistent with prior studies, with 41.6% rated as “acceptable” and 34.2% placing £ 3 electrodes acceptably. Correctness of electrode placement was comparable between EMS and clinical participants. More correct electrode placement correlated with classroom vs. on-the-job training, frequent vs. infrequent practice, and greater self-confidence. The diagram data collection method proved not equivalent to, and probably less reliable than, the hands-on manikin method for assessing placement skills. Conclusions: Significant variation in ECG chest electrode placement by EMS personnel was comparable to that previously reported for clinical personnel, suggesting that existing concerns about placement errors by clinical personnel may apply equally to EMS personnel. More frequent practice and classroom-based initial ECG training were associated with significantly greater placement accuracy. Participants used diverse strategies to identify electrode locations. Further research is warranted to clarify optimal strategies for placing chest electrodes, especially on diverse body types. Sound initial ECG training and continuing education are necessary to reinforce high-quality ECG skills.

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.

Axonal stimulation affects the linear summation of single-point perception in three Argus II users.

Objective.Retinal implants use electrical stimulation to elicit perceived flashes of light ('phosphenes'). Single-electrode phosphene shape has been shown to vary systematically with stimulus parameters and the retinal location of the stimulating electrode, due to incidental activation of passing nerve fiber bundles. However, this knowledge has yet to be extended to paired-electrode stimulation.Approach.We retrospectively analyzed 3548 phosphene drawings made by three blind participants implanted with an Argus II Retinal Prosthesis. Phosphene shape (characterized by area, perimeter, major and minor axis length) and number of perceived phosphenes were averaged across trials and correlated with the corresponding single-electrode parameters. In addition, the number of phosphenes was correlated with stimulus amplitude and neuroanatomical parameters: electrode-retina and electrode-fovea distance as well as the electrode-electrode distance to ('between-axon') and along axon bundles ('along-axon'). Statistical analyses were conducted using linear regression and partial correlation analysis.Main results.Simple regression revealed that each paired-electrode shape descriptor could be predicted by the sum of the two corresponding single-electrode shape descriptors (p < .001). Multiple regression revealed that paired-electrode phosphene shape was primarily predicted by stimulus amplitude and electrode-fovea distance (p < .05). Interestingly, the number of elicited phosphenes tended to increase with between-axon distance (p < .05), but not with along-axon distance, in two out of three participants.Significance.The shape of phosphenes elicited by paired-electrode stimulation was well predicted by the shape of their corresponding single-electrode phosphenes, suggesting that two-point perception can be expressed as the linear summation of single-point perception. The impact of the between-axon distance on the perceived number of phosphenes provides further evidence in support of the axon map model for epiretinal stimulation. These findings contribute to the growing literature on phosphene perception and have important implications for the design of future retinal prostheses.

Sensitivity of Electrocardiogram on Electrode-Pair Locations for Wearable Devices: Computational Analysis of Amplitude and Waveform Distortion.

An electrocardiogram (ECG) is used to observe the electrical activity of the heart via electrodes on the body surface. Recently, an ECG with fewer electrodes, such as a bipolar ECG in which two electrodes are attached to the chest, has been employed as wearable devices. However, the effect of different geometrical factors and electrode-pair locations on the amplitude and waveform of ECG signals remains unclear. In this study, we computationally evaluated the effects of body morphology, heart size and orientation, and electrode misalignment on ECG signals for 48 scenarios using 35 bipolar electrode pairs (1680 waveforms) with a dynamic time warping (DTW) algorithm. It was observed that the physique of the human body model predominantly affected the amplitude and waveform of the ECG signals. A multivariate analysis indicated that the heart-electrode distance and the solid angle of the heart from the electrode characterized the amplitude and waveform of the ECG signals, respectively. Furthermore, the electrode locations for less individual variability and less waveform distortion were close to the location of electrodes V2 and V3 in the standard 12-lead. These findings will facilitate the placement of ECG electrodes and interpretation of the measured ECG signals for wearable devices.

Peripheral Neural Synchrony in Postlingually Deafened Adult Cochlear Implant Users.

This paper reports a noninvasive method for quantifying neural synchrony in the cochlear nerve (i.e., peripheral neural synchrony) in cochlear implant (CI) users, which allows for evaluating this physiological phenomenon in human CI users for the first time in the literature. In addition, this study assessed how peripheral neural synchrony was correlated with temporal resolution acuity and speech perception outcomes measured in quiet and in noise in postlingually deafened adult CI users. It tested the hypothesis that peripheral neural synchrony was an important factor for temporal resolution acuity and speech perception outcomes in noise in postlingually deafened adult CI users. Study participants included 24 postlingually deafened adult CI users with a Cochlear™ Nucleus® device. Three study participants were implanted bilaterally, and each ear was tested separately. For each of the 27 implanted ears tested in this study, 400 sweeps of the electrically evoked compound action potential (eCAP) were measured at four electrode locations across the electrode array. Peripheral neural synchrony was quantified at each electrode location using the phase-locking value (PLV), which is a measure of trial-by-trial phase coherence among eCAP sweeps/trials. Temporal resolution acuity was evaluated by measuring the within-channel gap detection threshold (GDT) using a three-alternative, forced-choice procedure in a subgroup of 20 participants (23 implanted ears). For each ear tested in these participants, GDTs were measured at two electrode locations with a large difference in PLVs. For 26 implanted ears tested in 23 participants, speech perception performance was evaluated using consonant-nucleus-consonant (CNC) word lists presented in quiet and in noise at signal to noise ratios (SNRs) of +10 and +5 dB. Linear Mixed effect Models were used to evaluate the effect of electrode location on the PLV and the effect of the PLV on GDT after controlling for the stimulation level effects. Pearson product-moment correlation tests were used to assess the correlations between PLVs, CNC word scores measured in different conditions, and the degree of noise effect on CNC word scores. There was a significant effect of electrode location on the PLV after controlling for the effect of stimulation level. There was a significant effect of the PLV on GDT after controlling for the effects of stimulation level, where higher PLVs (greater synchrony) led to lower GDTs (better temporal resolution acuity). PLVs were not significantly correlated with CNC word scores measured in any listening condition or the effect of competing background noise presented at an SNR of +10 dB on CNC word scores. In contrast, there was a significant negative correlation between the PLV and the degree of noise effect on CNC word scores for a competing background noise presented at an SNR of +5 dB, where higher PLVs (greater synchrony) correlated with smaller noise effects on CNC word scores. This newly developed method can be used to assess peripheral neural synchrony in CI users, a physiological phenomenon that has not been systematically evaluated in electrical hearing. Poorer peripheral neural synchrony leads to lower temporal resolution acuity and is correlated with a larger detrimental effect of competing background noise presented at an SNR of 5 dB on speech perception performance in postlingually deafened adult CI users.