Passive Focusing of Single Cells Using Microwell Arrays for High-Accuracy Image-Activated Sorting.

Sorting single cells from a population was of critical importance in areas such as cell line development and cell therapy. Image-based sorting is becoming a promising technique for the nonlabeling isolation of cells due to the capability of providing the details of cell morphology. This study reported the focusing of cells using microwell arrays and the following automatic size sorting based on the real-time recognition of cells. The simulation first demonstrated the converged streamlines to the symmetrical plane contributed to the focusing effect. Then, the influence of connecting microchannel, flowing length, particle size, and the sample flow rate on the focusing effect was experimentally analyzed. Both microspheres and cells could be aligned in a straight line at the Reynolds number (Re) of 0.027-0.187 and 0.027-0.08, respectively. The connecting channel was proved to drastically improve the focusing performance. Afterward, a tapered microwell array was utilized to focus sphere/cell spreading in a wide channel to a straight line. Finally, a custom algorithm was employed to identify and sort the size of microspheres/K562 cells with a throughput of 1 event/s and an accuracy of 97.8/97.1%. The proposed technique aligned cells to a straight line at low Reynolds numbers and greatly facilitated the image-activated sorting without the need for a high-speed camera or flow control components with high frequency. Therefore, it is of enormous application potential in the field of nonlabeled separation of single cells.

A tempo-spatial controllable microfluidic shear-stress generator for in-vitro mimicking of the thrombus.

Pathological conditions linked to shear stress have been identified in hematological diseases, cardiovascular diseases, and cancer. These conditions often exhibit significantly elevated shear stress levels, surpassing 1000 dyn/cm2 in severely stenotic arteries. Heightened shear stress can induce mechanical harm to endothelial cells, potentially leading to bleeding and fatal consequences. However, current technology still grapples with limitations, including inadequate flexibility in simulating bodily shear stress environments, limited range of shear stress generation, and spatial and temporal adaptability. Consequently, a comprehensive understanding of the mechanisms underlying the impact of shear stress on physiological and pathological conditions, like thrombosis, remains inadequate. To address these limitations, this study presents a microfluidic-based shear stress generation chip as a proposed solution. The chip achieves a substantial 929-fold variation in shear stress solely by adjusting the degree of constriction in branch channels after PDMS fabrication. Experiments demonstrated that a rapid increase in shear stress up to 1000 dyn/cm2 significantly detached 88.2% cells from the substrate. Long-term exposure (24 h) to shear stress levels below 8.3 dyn/cm2 did not significantly impact cell growth. Furthermore, cells exposed to shear stress levels equal to or greater than 8.3 dyn/cm2 exhibited significant alterations in aspect ratio and orientation, following a normal distribution. This microfluidic chip provides a reliable tool for investigating cellular responses to the wide-ranging shear stress existing in both physiological and pathological flow conditions.

Understanding the retina: a review of computational models of the retina from the single cell to the network level.

The vertebrate retina is a clearly organized signal-processing system. It contains more than 60 different types of neurons, arranged in three distinct neural layers. Each cell type is believed to serve unique role(s) in encoding visual information. While we now have a relatively good understanding of the constituent cell types in the retina and some general ideas of their connectivity, with few exceptions, how the retinal circuitry performs computation remains poorly understood. Computational modeling has been commonly used to study the retina from the single cell to the network level. In this article, we begin by reviewing retinal modeling strategies and existing models. We then discuss in detail the significance and limitations of these models, and finally, we provide suggestions for the future development of retinal neural modeling.

Hybrid soft computing systems for electromyographic signals analysis: a review.

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

Selective intrafascicular stimulation of myelinated and unmyelinated nerve fibers through a longitudinal electrode: A computational study.

Carbon nanotube (CNT) fiber electrodes have demonstrated exceptional spatial selectivity and sustained reliability in the context of intrafascicular electrical stimulation, as evidenced through rigorous animal experimentation. A significant presence of unmyelinated C fibers, known to induce uncomfortable somatosensory experiences, exists within peripheral nerves. This presence poses a considerable challenge to the excitation of myelinated Aß fibers, which are crucial for tactile sensation. To achieve nuanced tactile sensory feedback utilizing CNT fiber electrodes, the selective stimulation of Aß sensory afferents emerges as a critical factor. In confronting this challenge, the present investigation sought to refine and apply a rat sciatic-nerve model leveraging the capabilities of the COMSOL-NEURON framework. This approach enables a systematic evaluation of the influence exerted by stimulation parameters and electrode geometry on the activation dynamics of both myelinated Aß and unmyelinated C fibers. The findings advocate for the utilization of current pulses featuring a pulse width of 600 µs, alongside the deployment of CNT fibers characterized by a diminutive diameter of 10 µm, with an exclusively exposed cross-sectional area, to facilitate reduced activation current thresholds. Comparative analysis under monopolar and bipolar electrical stimulation conditions revealed proximate activation thresholds, albeit with bipolar stimulation exhibiting superior fiber selectivity relative to its monopolar counterpart. Concerning pulse waveform characteristics, the adoption of an anodic-first biphasic stimulation modality is favored, taking into account the dual criteria of activation threshold and fiber selectivity optimization. Consequently, this investigation furnishes an efficacious stimulation paradigm for the selective activation of touch-related nerve fibers, alongside provisioning a comprehensive theoretical foundation for the realization of natural tactile feedback within the domain of prosthetic hand applications.

Neural activity of retinal ganglion cells under continuous, dynamically-modulated high frequency electrical stimulation.

Objective.Current retinal prosthetics are limited in their ability to precisely control firing patterns of functionally distinct retinal ganglion cell (RGC) types. The aim of this study was to characterise RGC responses to continuous, kilohertz-frequency-varying stimulation to assess its utility in controlling RGC activity.Approach.We usedin vitropatch-clamp experiments to assess electrically-evoked ON and OFF RGC responses to frequency-varying pulse train sequences. In each sequence, the stimulation amplitude was kept constant while the stimulation frequency (0.5-10 kHz) was changed every 40 ms, in either a linearly increasing, linearly decreasing or randomised manner. The stimulation amplitude across sequences was increased from 10 to 300µA.Main results.We found that continuous stimulation without rest periods caused complex and irreproducible stimulus-response relationships, primarily due to strong stimulus-induced response adaptation and influence of the preceding stimulus frequency on the response to a subsequent stimulus. In addition, ON and OFF populations showed different sensitivities to continuous, frequency-varying pulse trains, with OFF cells generally exhibiting more dependency on frequency changes within a sequence. Finally, the ability to maintain spiking behaviour to continuous stimulation in RGCs significantly reduced over longer stimulation durations irrespective of the frequency order.Significance.This study represents an important step in advancing and understanding the utility of continuous frequency modulation in controlling functionally distinct RGCs. Our results indicate that continuous, kHz-frequency-varying stimulation sequences provide very limited control of RGC firing patterns due to inter-dependency between adjacent frequencies and generally, different RGC types do not display different frequency preferences under such stimulation conditions. For future stimulation strategies using kHz frequencies, careful consideration must be given to design appropriate pauses in stimulation, stimulation frequency order and the length of continuous stimulation duration.

A Self-powered Neural Stimulator Based on Programmable Triboelectric Nanogenerators.

Modulation of peripheral nerve is an emerging field for neuroprosthesis and bioelectronic medicine. With the developing neural interfacing technology that directly communicates with peripheral nerves, several powering schemes have been investigated for long-term use of implantable devices such as wireless and conversion of human body energy. But due to the limitations such as energy conversion efficiency and complexity, none of these methods can fully replace the current battery-based neuroprosthetic systems. This study proposes a new scheme based on programmable triboelectric nanogenerators for self-powered neural stimulations. The device can generate current pulses of more than 100 V by slightly shaking the device. The capability of neural stimulation is validated by sciatic nerve stimulation. Furthermore, the shaking frequency can control the measured kicking force of the rat leg. This prototype can be further minimized and optimized for a fully implantable self-powered/wireless neuroprosthetic system.

Automatic elasticity measurement of single cells using a microfluidic system with real-time image processing.

The mechanical properties of cells are closely related to their physiological states and functions. Due to the limitations of conventional cell elasticity measurement technologies such as low throughput, cell-invasiveness, and high cost, microfluidic systems are emerging as powerful tools for high-throughput cell mechanical property studies. This paper introduces a microfluidic system to automatically measure the elastic modulus of single cells in real time. The system integrated a microfluidic chip with a microchannel for cell constriction, a pressure pump, a precision differential pressure sensor, and a program for online analysis of cell deformation. The program used a fast U-net to segment cell images and measure protrusion length during cell deformation. Subsequently, the cell elasticity was determined in real-time based on the deformation and required pressure using the power law rheological model. Finally, Young's modulus of BMSCs, Huh-7 cells, EMSCs, and K562 cells was measured as 25.13 ± 15.19 Pa, 69.74 ± 92.01 Pa, 54.50 ± 59.31 Pa and 58.43 ± 27.27 Pa, respectively. The microfluidic system has significant application potential in the automated evaluation of cell mechanical properties.Clinical Relevance-The technique in this paper may be used for the automatic and high throughput study of the stiffness of cells, such as stem cells and cancer cells. The stiffness data may contribute to stem cell therapy and cancer research.

Modulating individual axons and axonal populations in the peripheral nerve using transverse intrafascicular multichannel electrodes.

Objective.A transverse intrafascicular multichannel electrode (TIME) may offer advantages over more conventional cuff electrodes including higher spatial selectivity and reduced stimulation charge requirements. However, the performance of TIME, especially in the context of non-conventional stimulation waveforms, remains relatively unexplored. As part of our overarching goal of investigating stimulation efficacy of TIME, we developed a computational toolkit that automates the creation and usage ofin siliconerve models with TIME setup, which solves nerve responses using cable equations and computes extracellular potentials using finite element method.Approach.We began by implementing a flexible and scalable Python/MATLAB-based toolkit for automatically creating models of nerve stimulation in the hybrid NEURON/COMSOL ecosystems. We then developed a sciatic nerve model containing 14 fascicles with 1,170 myelinated (A-type, 30%) and unmyelinated (C-type, 70%) fibers to study fiber responses over a variety of TIME arrangements (monopolar and hexapolar) and stimulation waveforms (kilohertz stimulation and cathodic ramp modulation).Main results.Our toolkit obviates the conventional need to re-create the same nerve in two disparate modeling environments and automates bi-directional transfer of results. Our population-based simulations suggested that kilohertz stimuli provide selective activation of targeted C fibers near the stimulating electrodes but also tended to activate non-targeted A fibers further away. However, C fiber selectivity can be enhanced by hexapolar TIME arrangements that confined the spatial extent of electrical stimuli. Improved upon prior findings, we devised a high-frequency waveform that incorporates cathodic DC ramp to completely remove undesirable onset responses.Conclusion.Our toolkit allows agile, iterative design cycles involving the nerve and TIME, while minimizing the potential operator errors during complex simulation. The nerve model created by our toolkit allowed us to study and optimize the design of next-generation intrafascicular implants for improved spatial and fiber-type selectivity.

Improving Spatial Resolution and Selectivity of Transcorneal Electrical Stimulation by Temporal Interference Technology.

Transcorneal electrical stimulation (TES) used in a therapeutic device has been demonstrated significant neuroprotective effect for rescuing retinal function. However, the diffuse electric field induced by conventional TES devices reduced their spatial resolution and selectivity, limiting their capability of actively stimulating a severely diseased retina. A cutting-edge neuromodulation approach named temporal interference stimulation (TIS) was reported to induce electric fields focalizing on local neuronal targets. Despite the competent feasibility of application in retinal TIS, the interpretation of characteristics of spatial resolution and selectivity under TIS remains rudimentary. In this study, we conduct in silico investigations to understand the characteristics of spatial selectivity and resolution using a finite element model of a multi-layered eyeball and multiple electrode configuration. By simulating different metrics of electric potentials envelope modulated by TIS, our model supports the possibility of achieving mini-invasive and spatially selective electrical stimulation using retinal TIS. These simulations provide theoretical evidence on the basis of which sophisticated devices for improved spatial selectivity can be designed.Clinical Relevance- This study provides a theoretical basis for understanding how the design of electrode configuration impacts transcorneal TIS performance. This model can guide future development of transcorneal TIS configurations and stimulation strategies that may benefit patients with inherited retinal diseases.

Probing the Contribution of Vertical Processing Layers of the Retina to White-Noise Electrical Stimulation Responses.

Optimal stimulus parameters for epiretinal prostheses have been investigated by analyzing retinal ganglion cell (RGC) spiking responses to white-noise electrical stimulation, through a spike-triggered average (STA) analysis technique. However, it is currently unknown as to activation of which retinal cells contribute to features of the STA. We conducted whole-cell patch clamping recordings in ON and OFF RGCs in response to white-noise epiretinal electrical stimulation by using different inhibitors of synaptic transmission in a healthy retina. An mGluR6 agonist, L-AP4, was firstly used to selectively block the output of photoreceptors (PRs) to ON bipolar cells (BCs). We subsequently fully blocked all synaptic inputs to RGCs using a combination of pharmacological agents. Our data shows that PRs dominate the ability of ON RGCs to integrate electrical pulses and form a unique STA shape, while BCs do not contribute in any way. In addition, our results demonstrate that the ability of OFF RGCs to integrate pulses is consistently impaired after blocking the PR to ON BC pathway. We hypothesise that the mechanisms underlying this co-effect are related to the narrow field AII amacrine cells connecting ON and OFF pathways.Clinical Relevance-Recent retinal studies recorded mirror-inverted STAs in ON and OFF retinal pathways, thus raising the possibility of designing a stimulation approach that can differentially activate ON and OFF pathways with electrical stimulation. However, the detailed contribution of three major retinal cell layers in forming characteristic STAs is still unclear. It is of great clinical relevance to investigate the isolated contribution of PRs to the electrically driven STA since PRs progressively degenerate in the course of retinal disease.

The direct influence of retinal degeneration on electrical stimulation efficacy: Significant implications for retinal prostheses.

Photoreceptor loss and inner retinal network remodeling severely impacts the ability of retinal prosthetic devices to create artificial vision. We developed a computational model of a degenerating retina based on rodent data and tested its response to retinal electrical stimulation. This model includes detailed network connectivity and diverse neural intrinsic properties, capable of exploring how the degenerated retina influences the performance of electrical stimulation during the degeneration process. Our model suggests the possibility of quantitatively modulating retinal ON and OFF pathways between phase II and III of retinal degeneration without requiring any differences between ON and OFF RGC intrinsic cellular properties. The model also provided insights about how remodeling events influence stage-dependent differential electrical responses of ON and OFF pathways.Clinical Relevance-This data-driven model can guide future development of retinal prostheses and stimulation strategies that may benefit patients at different stages of retinal disease progression, particularly in the early and mid-stages, thus increasing their global acceptance.

The effect of the subthreshold oscillation induced by the neurons' resonance upon the electrical stimulation-dependent instability.

Repetitive electrical nerve stimulation can induce a long-lasting perturbation of the axon's membrane potential, resulting in unstable stimulus-response relationships. Despite being observed in electrophysiology, the precise mechanism underlying electrical stimulation-dependent (ES-dependent) instability is still an open question. This study proposes a model to reveal a facet of this problem: how threshold fluctuation affects electrical nerve stimulations. This study proposes a new method based on a Circuit-Probability theory (C-P theory) to reveal the interlinkages between the subthreshold oscillation induced by neurons' resonance and ES-dependent instability of neural response. Supported by in-vivo studies, this new model predicts several key characteristics of ES-dependent instability and proposes a stimulation method to minimize the instability. This model provides a powerful tool to improve our understanding of the interaction between the external electric field and the complexity of the biophysical characteristics of axons.

Modulating functionally-distinct vagus nerve fibers using microelectrodes and kilohertz frequency electrical stimulation.

Modulation of functionally distinct nerve fibers with bioelectronic devices provides a therapeutic opportunity for various diseases. In this study, we began by developing a computational model including four major subtypes of myelinated fibers and one unmyelinated fiber. Second, we used an intrafascicular electrode to perform kHz-frequency electric stimulation to preferentially modulate a population of fibers. Our model suggests that fiber physical properties and electrode-to-fascicle distance severely impacts stimulus-response relationships. Large diameter fibers (Aα- and Aß-) were only minimally influenced by the fascicle size and electrode location, while smaller diameter fibers (Aδ-, B- and C-) indicated a stronger dependency.Clinical Relevance- Our findings support the possibility of selectively modulating functionally-distinct nerve fibers using electrical stimulation in a small, localized region. Our model provides an effective tool to design next-generation implantable devices and therapeutic stimulation strategies toward minimizing off-target effects.

Improving the spatial resolution of artificial vision using midget retinal ganglion cell populations modeled at the human fovea.

Objective. Retinal prostheses seek to create artificial vision by stimulating surviving retinal neurons of patients with profound vision impairment. Notwithstanding tremendous research efforts, the performance of all implants tested to date has remained rudimentary, incapable of overcoming the threshold for legal blindness. To maximize the perceptual efficacy of retinal prostheses, a device must be capable of controlling retinal neurons with greater spatiotemporal precision. Most studies of retinal stimulation were derived from either non-primate species or the peripheral primate retina. We investigated if artificial stimulation could leverage the high spatial resolution afforded by the neural substrates at the primate fovea and surrounding regions to achieve improved percept qualities.Approach.We began by developing a new computational model capable of generating anatomically accurate retinal ganglion cell (RGC) populations within the human central retina. Next, multiple RGC populations across the central retina were stimulatedin-silicoto compare clinical and recently proposed neurostimulation configurations based on their ability to improve perceptual efficacy and reduce activation thresholds.Main results.Our model uniquely upholds eccentricity-dependent characteristics such as RGC density and dendritic field diameter, whilst incorporating anatomically accurate features such as axon projection and three-dimensional (3D) RGC layering, features often forgone in favor of reduced computational complexity. Following epiretinal stimulation, the RGCs in our model produced response patterns in shapes akin to the complex and non-trivial percepts reported in clinical trials. Our results also demonstrated that even within the neuron-dense central retina, epiretinal stimulation using a multi-return hexapolar electrode arrangement could reliably achieve spatially focused RGC activation and could achieve single-cell excitation in 56% of all tested locations.Significance. This study establishes an anatomically accurate 3D model of RGC populations within the human central retina and demonstrates the potential for an epiretinal hexapolar configuration to achieve consistent, spatially confined retinal responses, even within the unique and neuron-dense foveal region. Our results and model promote the prospect and optimization of higher spatial resolution in future epiretinal implants.

Development of Paper Microfluidics with 3D-Printed PDMS Barriers for Flow Control.

Paper microfluidics has been extensively exploited as a powerful tool for environmental and medical detection applications. Both flow delay and compatibility with either polar or non-polar reagents are indispensable for the automation of detections requiring multiple reaction steps. This article reports the systematic studies of a 3D-printing protocol, characterization, and application of both the partially and fully penetrated polydimethylsiloxane (PDMS) barriers for flexible flow control in paper microfluidics. The physical parameters of PDMS barriers printed using a simple liquid dispenser were found related to the printing pressure, speed, diffusion time after printing, baking temperature, and PDMS viscosity. The capability of PDMS barriers to confine the flow of non-polar solvents was demonstrated using oil flow in both wax- and PDMS-surrounded channels. It was identified that the minimum width of channels to prevent leakage was 470 ± 54 µm, which was as narrow as that fabricated using stamps from lithography. Both the partially penetrated barriers (PPBs) and constriction channels were of the capability to delay flow in paper microfluidics. Additionally, an in silico investigation led to the further understanding that the reduction of channel cross-section resulting from PPBs was the primary reason for flow delay. Our results suggest that increasing the penetration depth of the barriers is more efficient in delaying flow than increasing the PPB length. Finally, devices with four inlet channels and 0-6 PPBs across each channel were successfully applied in flow delay for sequential fluid delivery. These results improve the understanding of the major factors, affecting the 3D PDMS barrier fabrication and the resulting flow control in paper microfluidics, providing practical implications for applications in various fields.

Simulating the impact of photoreceptor loss and inner retinal network changes on electrical activity of the retina.

Objective.A major reason for poor visual outcomes provided by existing retinal prostheses is the limited knowledge of the impact of photoreceptor loss on retinal remodelling and its subsequent impact on neural responses to electrical stimulation. Computational network models of the neural retina assist in the understanding of normal retinal function but can be also useful for investigating diseased retinal responses to electrical stimulation.Approach.We developed and validated a biophysically detailed discrete neuronal network model of the retina in the software package NEURON. The model includes rod and cone photoreceptors, ON and OFF bipolar cell pathways, amacrine and horizontal cells and finally, ON and OFF retinal ganglion cells with detailed network connectivity and neural intrinsic properties. By accurately controlling the network parameters, we simulated the impact of varying levels of degeneration on retinal electrical function.Main results.Our model was able to reproduce characteristic monophasic and biphasic oscillatory patterns seen in ON and OFF neurons during retinal degeneration (RD). Oscillatory activity occurred at 3 Hz with partial photoreceptor loss and at 6 Hz when all photoreceptor input to the retina was removed. Oscillations were found to gradually weaken, then disappear when synapses and gap junctions were destroyed in the inner retina. Without requiring any changes to intrinsic cellular properties of individual inner retinal neurons, our results suggest that changes in connectivity alone were sufficient to give rise to neural oscillations during photoreceptor degeneration, and significant network connectivity destruction in the inner retina terminated the oscillations.Significance.Our results provide a platform for further understanding physiological retinal changes with progressive photoreceptor and inner RD. Furthermore, our model can be used to guide future stimulation strategies for retinal prostheses to benefit patients at different stages of disease progression, particularly in the early and mid-stages of RD.

Generation of Dynamic Concentration Profile Using A Microfluidic Device Integrating Pneumatic Microvalves.

Generating and maintaining the concentration dilutions of diffusible molecules in microchannels is critical for high-throughput chemical and biological analysis. Conventional serial network microfluidic technologies can generate high orders of arbitrary concentrations by a predefined microchannel network. However, a previous design requires a large occupancy area and is unable to dynamically generate different profiles in the same chip, limiting its applications. This study developed a microfluidic device enabling dynamic variations of both the concentration in the same channel and the concentration distribution in multiple channels by adjusting the flow resistance using programmable pneumatic microvalves. The key component (the pneumatic microvalve) allowed dynamic adjustment of the concentration profile but occupied a tiny space. Additionally, a Matlab program was developed to calculate the flow rates and flow resistance of various sections of the device, which provided theoretical guidance for dimension design. In silico investigations were conducted to evaluate the microvalve deformation with widths from 100 to 300 µm and membrane thicknesses of 20 and 30 µm under the activation pressures between 0 and 2000 mbar. The flow resistance of the deformed valve was studied both numerically and experimentally and an empirical model for valve flow resistance with the form of Rh=aebP was proposed. Afterward, the fluid flow in the valve region was characterized using Micro PIV to further demonstrate the adjustment mechanism of the flow resistance. Then, the herringbone structures were employed for fast mixing to allow both quick variation of concentration and minor space usage of the channel network. Finally, an empirical formula-supported computational program was developed to provide the activation pressures required for the specific concentration profile. Both linear (Ck = -0.2k + 1) and nonlinear (Ck = (110)k) concentration distribution in four channels were varied using the same device by adjusting microvalves. The device demonstrated the capability to control the concentration profile dynamically in a small space, offering superior application potentials in analytical chemistry, drug screening, and cell biology research.

Anin-silicoanalysis of electrically evoked responses of midget and parasol retinal ganglion cells in different retinal regions.

Objective. Visual outcomes provided by present retinal prostheses that primarily target retinal ganglion cells (RGCs) through epiretinal stimulation remain rudimentary, partly due to the limited knowledge of retinal responses under electrical stimulation. Better understanding of how different retinal regions can be quantitatively controlled with high spatial accuracy, will be beneficial to the design of micro-electrode arrays and stimulation strategies for next-generation wide-view, high-resolution epiretinal implants.Approach. A computational model was developed to assess neural activity at different eccentricities (2 mm and 5 mm) within the human retina. This model included midget and parasol RGCs with anatomically accurate cell distribution and cell-specific morphological information. We then performedin silicoinvestigations of region-specific RGC responses to epiretinal electrical stimulation using varied electrode sizes (5-210µm diameter), emulating both commercialized retinal implants and recently developed prototype devices.Main results. Our model of epiretinal stimulation predicted RGC population excitation analogous to the complex percepts reported in human subjects. Following this, our simulations suggest that midget and parasol RGCs have characteristic regional differences in excitation under preferred electrode sizes. Relatively central (2 mm) regions demonstrated higher number of excited RGCs but lower overall activated receptive field (RF) areas under the same stimulus amplitudes (two-way analysis of variance (ANOVA),p< 0.05). Furthermore, the activated RGC numbers per unit active RF area (number-RF ratio) were significantly higher in central than in peripheral regions, and higher in the midget than in the parasol population under all tested electrode sizes (two-way ANOVA,p< 0.05). Our simulations also suggested that smaller electrodes exhibit a higher range of controllable stimulation parameters to achieve pre-defined performance of RGC excitation. An empirical model:I=a· exp (b·D) +cof the stimulus amplitude (I)-electrode diameter (D) relationship was constructed to achieve the pre-defined objective function values in different retinal regions, indicating the ability of controlling retinal outputs by fine-tuning the stimulation amplitude with different electrode sizes. Finally, our multielectrode simulations predicted differential neural crosstalk between adjacent electrodes in central temporal and peripheral temporal regions, providing insights towards establishing a non-uniformly distributed multielectrode array geometry for wide-view retinal implants.Significance.Stimulus-response properties in central and peripheral retina can provide useful information to estimate electrode parameters for region-specific activation by retinal stimulation. Our findings support the possibility of improving the performance of epiretinal prostheses by exploring the influence of electrode array geometry on activation of different retinal regions.

An in-silicoanalysis of retinal electric field distribution induced by different electrode design of trans-corneal electrical stimulation.

Objective.Trans-corneal electrical stimulation (TcES) produces therapeutic effects on many ophthalmic diseases non-invasively. Existing clinical TcES devices use largely variable design of electrode distribution and stimulation parameters. Better understanding of how electrode configuration paradigms and stimulation parameters influence the electric field distribution on the retina, will be beneficial to the design of next-generation TcES devices.Approach.In this study, we constructed a realistic finite element human head model with fine eyeball structure. Commonly used DTL-Plus and ERG-Jet electrodes were simulated. We then conductedin silicoinvestigations of retina observation surface (ROS) electric field distributions induced by different return electrode configuration paradigms and different stimulus intensities.Main results.Our results suggested that the ROS electric field distribution could be modulated by re-designing TcES electrode settings and stimulus parameters. Under far return location paradigms, either DTL-Plus or ERG-Jet approach could induce almost identical ROS electric field distribution regardless where the far return was located. However, compared with the ERG-Jet mode, DTL-Plus stimulation induced stronger nasal lateralization. In contrast, ERG-Jet stimulation induced relatively stronger temporal lateralization. The ROS lateralization can be further tweaked by changing the DTL-Plus electrode length.Significance.These results may contribute to the understanding of the characteristics of DTL-Plus and ERG-Jet electrodes based electric field distribution on the retina, providing practical implications for the therapeutic application of TcES.