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Background:Electroconvulsive therapy (ECT) is a highly effective treatment for severe psychiatric disorders. Despite its high efficacy, the use of ECT would be greater if the risk of cognitive side effects were reduced. Over the last 20 years, developments in ECT technique, including improvements in the dosing methodology and modification of the stimulus waveform, have allowed for improved treatment methods with reduced adverse cognitive effects. There is increasing evidence that the electrode placement is important for orienting the electrical stimulus and therefore modifying treatment outcomes, with potential for further improvement of the placements currently used in ECT.Objective:We used computational modelling to perform an in-depth examination into regional differences in brain excitation by the ECT stimulus for several lesser known and novel electrode placements, in order to investigate the potential for an electrode placement that may optimise clinical outcomes.Methods:High resolution finite element human head models were generated from MRI scans of three subjects. The models were used to compare regional differences in average electric field (EF) magnitude among a total of thirteen bipolar ECT electrode placements, i.e. three conventional placements as well as ten lesser known and novel placements.Results and conclusion:In this exploratory study on a systemic comparison of thirteen ECT electrode placements, the EF magnitude at regions of interest (ROIs) was highly dependent upon the position of both electrodes, especially the ROIs close to the cortical surface. Compared to conventional right-unilateral (RUL) ECT using a temporo-parietal placement, fronto-parietal and supraorbito-parietal RUL also robustly stimulated brain regions considered important for efficacy, while sparing regions related to cognitive functions, and may be a preferrable approach to the currently used placement for RUL ECT. The simulations also found that regional average EF magnitude varied between individual subjects, due to factors such as head size, and results also depended on the size of the defined ROI.

Cervical vagus nerve stimulation (VNS) is a neuromodulation therapy used in the treatment of several chronic disorders. In order to maximize the therapeutic effectiveness of VNS, it has become increasingly important to deliver fiber-specific neurostimulation, so that undesired effects can be minimized. Assessing the activation of different vagal fiber types through electrical stimulation is therefore essential for developing fiber-selective VNS therapies. Towards this goal, we conducted in silico investigations using a generic model of functionally distinct nerve fibers and clinically relevant cuff electrodes using COMSOL. Our model is constrained by histological observations from rat cervical vagus nerves and its outputs are validated against averaged compound nerve action potentials (CNAPs) obtained from rat vagus nerve recordings. We propose this model as an effective tool to design fiber-specific stimulation protocols before testing them in experimental animals.

Improvements to the efficacy of retinal neuroprostheses can be achieved by developing more sophisticated neural stimulation strategies to enable selective or differential activation of specific retinal ganglion cells (RGCs). Recent retinal studies have demonstrated the ability to differentially recruit ON and OFF RGCs – the two major information pathways of the retina – using high-frequency electrical stimulation (HFS). However, there remain many unknowns, since this is a relatively unexplored field. For example, can we achieve ON/OFF selectivity over a wide range of stimulus frequencies and amplitudes? Furthermore, existing demonstrations of HFS efficacy in retinal prostheses have been based on epiretinal placement of electrodes. Other clinically popular techniques include subretinal or suprachoroidal placement, where electrodes are located at the photoreceptor layer or in the suprachoroidal space, respectively, and these locations are quite distant from the RGC layer. Would HFS-based differential activation work from these locations? In this chapter, we conducted in silico investigations to explore the generalizability of HFS to differentially active ON and OFF RGCs. Computational models are particularly well suited for these investigations. The electric field can be accurately described by mathematical formulations, and simulated neurons can be “probed” at resolutions well beyond those achievable by today’s state-of-the-art experimental techniques.

Present retinal neuroprostheses have limited performance capabilities due to indiscriminate activation of different neural pathways. Based on our success in differentially activating ON and OFF cells using high frequency stimuli in a healthy retina, in this study we explored whether we could achieve similar differential activation between these two cell types but in degenerate retina. We found that after blocking the synaptic network, ON retinal ganglion cells (RGCs) could be differentially activated at higher frequencies (4 - 6 kHz) and amplitudes (200 - 240 µA), and OFF RGCs at relatively lower amplitudes (80 - 160 µA) across all tested frequencies. We further found that both cell types could be controlled by quickly modulating the frequency using short stimulation bursts. This work takes us one step closer to reducing the likelihood of indiscriminate activation of RGCs by accurately controlling the activation of functionally-distinct neural pathways.

Retinal prostheses face with the problem of low resolution in clinical trial. Current steering is an effective way to produce extra perceptual channels called virtual electrodes (VEs) and therefore improve the perceptual resolution, without increasing the number of stimulating electrodes. However, little research has been reported about applying this method to subretinal prostheses. In this study, multilayer models of normal human retina and degenerated human retina with retinitis pigmentosa (RP) were established. The configuration and parameter of stimulating electrodes were studied for generating focal VEs. Our stimulated results showed that distant sclera is a suitable site set as ground compared to distant vitreous body. Simultaneous stimulating of adjacent electrodes can generate focal VEs in the target retinal layer that subretinal prostheses prefer to stimulating, when parameters of the stimulating electrode (diameter and edge-to-edge distance) were selected appropriately. This study may provide theoretical support for future application of VEs in subretinal prostheses.

Recent retinal studies have directed more attention to sophisticated stimulation strategies based on high-frequency (>1.0 kHz) electrical stimulation (HFS). In these studies, each retinal ganglion cell (RGC) type demonstrated a characteristic stimulus-strength-dependent response to HFS, offering the intriguing possibility of focally targeting retinal neurons to provide useful visual information by retinal prosthetics. Ionic mechanisms are known to affect the responses of electrogenic cells during electrical stimulation. However, how these mechanisms affect RGC responses is not well understood at present, particularly when applying HFS. Here, we investigate this issue via an in silico model of the RGC. We calibrate and validate the model using an in vitro retinal preparation. An RGC model based on accurate biophysics and realistic representation of cell morphology, was used to investigate how RGCs respond to HFS. The model was able to closely replicate the stimulus-strength-dependent suppression of RGC action potentials observed experimentally. Our results suggest that spike inhibition during HFS is due to local membrane hyperpolarization caused by outward membrane currents near the stimulus electrode. In addition, the extent of HFS-induced inhibition can be largely altered by the intrinsic properties of the inward sodium current. Finally, stimulus-strength-dependent suppression can be modulated by a wide range of stimulation frequencies, under generalized electrode placement conditions. In vitro experiments verified the computational modeling data. This modeling and experimental approach can be extended to further our understanding on the effects of novel stimulus strategies by simulating RGC stimulus-response profiles over a wider range of stimulation frequencies and electrode locations than have previously been explored.

Background Significant progress has been made over the last 50 years in the design, development and testing of transcutaneous electrical nerve stimulation (TENS) in mediating different levels of tactile sensations. However, without knowing how best to stimulate the nerve fibers, the elicited sensation quality will always remain poor and unnatural. New Method A new biomimetic 3D TENS computational model is developed to quantify the neural activation mechanism with varied surface electrodes. This model includes seven-layered anatomical structure of the forearm and biophysically-detailed myelinated Aβ fibers. The Aβ-fiber diameters from 1.5 - 7.5 μm were randomly distributed beneath the skin to mimic the physiologically-realistic fiber population. The arithmetic averaging algorithm and Gaussian filter were adopted to identify the sensation center and to quantify sensation intensities under different stimulation conditions. Results Fibers larger than 4.5 μm can usually be activated producing tactile sensations such as light touch, pressure, buzz, and vibration. While, fibers with diameters of 3.5 and 3 μm can only be excited at uncomfortable numb and pain sensations. The resulted modelling predictions match the recent psychophysical experimental data. Comparison with Existing Method(s) The new TENS model is more physiologically-realistic by introducing a detailed morphological information and key ionic mechanisms in nerve fibers. Conclusions Our results indicate that TENS may be a promising method to target functionally-distinct neural pathways in an effort to improve the elicited tactile sensations quality with electrical stimulation. This work provides a promising platform of discovering neural mechanisms under TENS.

Objective. The spatial resolution of an implantable neural stimulator can be improved by creation of virtual channels (VCs). VCs are commonly achieved through synchronized stimulation of multiple electrodes. It remains unknown whether asynchronous stimulation is able to generate comparable VC performance in retinal stimulation, and how VC can be optimized by re-designing stimulation settings. This study begins with exploring the feasibility of creating VCs using synchronous and asynchronous epiretinal stimulation, and ending with predicting the possible VC performance with a thorough exploration of stimulation parameter space. Approach. A computational model of epiretinal dual-electrode stimulation is developed to simulate the neural activity of a population of retinal ganglion cells (RGCs) under both synchronous and asynchronous stimulation conditions. The interaction between the electrode and RGCs under a range of stimulation parameters are simulated. Main results. Our simulation based on direct RGC activation suggests that VCs can be created using asynchronous stimulation. Two VC performance measures: 1) linearity in the change in centroid location of activated RGC populations, and 2) consistency in the size of activated RGC populations, have comparable performance under asynchronous and synchronous stimulation with appropriately selected stimulation parameters. Significance. Our findings support the possibility of creating VCs by directly activating RGCs under synchronous and asynchronous stimulation conditions. This study establishes the fundamental capability of VC creation based on temporal interactions within the RGC population alone and does not include the effects of potential indirect activation of any surviving inner retinal network neurons. Our results provide theoretical evidence for designing next-generation retinal prosthesis with higher spatial resolution.

Objective This study focused on characterising the response of four major functionally-different retinal ganglion cells (RGCs) to a high frequency stimulus (HFS) paradigm. Approach We used in vitro patch clamp experiments to assess the viability of evoking a differential response between different RGC types-OFF-Sustained, OFF-Transient, ON-Sustained and ON-Transient-under a wide range of HFS and stimulation amplitude combinations. Main results Of the four types, we found that the OFF-Sustained, OFF-Transient and ON-Transient RGCs could be differentially activated at various frequency and amplitude combinations, in particular, OFF-Sustained cells can be differentially targeted between 20-100 µA at all frequencies, OFF-Transient cells between 150-240 µA at 1 kHz and ON-Transient between 180-240 µA and 4-6 kHz. We further found that this differential activation held true when the stimulus duration was reduced from 300 ms to 50 ms. Finally, we found that the cell spiking response was not primarily dependent on total charge contained in the pulse train or current amplitude alone, but a combination of amplitude and frequency. Significance These results indicate that HFS may be a promising method to target functionally-distinct neural pathways in the retina in an effort to improve the vision quality with retinal prostheses.

The ability for visual prostheses to preferentially activate functionally-distinct retinal ganglion cells (RGCs) is important for improving visual perception. This study investigates the use of high frequency stimulation (HFS) to elicit RGC activation, using a closed-loop algorithm to search for optimal stimulation parameters for preferential ON and OFF RGC activation, resembling natural physiological neural encoding in response to visual stimuli. We evaluated the performance of a wide range of electrical stimulation amplitudes and frequencies on RGC responses in vitro using murine retinal preparations. It was possible to preferentially excite either ON or OFF RGCs by adjusting amplitudes and frequencies in HFS. ON RGCs can be preferentially activated at relatively higher stimulation amplitudes (>150 μA) and frequencies (2–6.25 kHz) while OFF RGCs are activated by lower stimulation amplitudes (40–90 μA) across all tested frequencies (1–6.25 kHz). These stimuli also showed great promise in eliciting RGC responses that parallel natural RGC encoding: ON RGCs exhibited an increase in spiking activity during electrical stimulation while OFF RGCs exhibited decreased spiking activity, given the same stimulation amplitude. In conjunction with the in vitro studies, in silico simulations indicated that optimal HFS parameters could be rapidly identified in practice, whilst sampling spiking activity of relevant neuronal subtypes. This closed-loop approach represents a step forward in modulating stimulation parameters to achieve appropriate neural encoding in retinal prostheses, advancing control over RGC subtypes activated by electrical stimulation.

Singular spectrum analysis (SSA) is widely applied to de-noise noisy biomedical signals in a broad range of applications. The major idea behind SSA de-noising is to divide the noisy signal into signal and noise subspaces by truncation of singular spectrum at a certain order. However, there is no clear ‘noise floor’ for many real-world biomedical signals. In addition, such de-noised signal contains the highest possible residual noise level. In this study, fuzzy entropy (FuzzyEn), a robust measure to quantify the signal complexity in chaos theory, is introduced to provide a genuine noise floor, which indicates the noise level of each SSA components relative to white noise and original noisy signal. Based on the FuzzyEn spectrum and filter bank characteristics of SSA, an iterative soft threshold SSA approach (SSA-IST) is then proposed to remove the noise in each component. The experimental results of de-noising speech and electromyographic (EMG) signals using the proposed approach are presented and compared with the results obtained using existing truncated SSA, wavelet transform (WT), and empirical mode decomposition (EMD) techniques.

A continuum multi-domain model of electrical stimulation of the retina is presented. Each point in the retinal ganglion cell layer could be thought of as representing a single cell, whose biophysics is described using a four-compartment formulation incorporating varying ion channel expressions in the soma, axon initial segment, dendrites and axon. Our continuum model was validated against a discrete morphologically-realistic OFF RGC model, using intra- and extra-cellular electrical stimulation scenarios. Simulations from the continuum model reproduced the same results as that of the discrete model. Our continuum model is the first multi-domain model to represent all main RGC compartments, not just the soma. Moreover, we demonstrated that this model allows the investigation of axonal activation which has been observed to influence the perception of phosphenes.

Retinal neuromodulation is an emerging therapeutic approach to restore functional vision to those suffering retinal photoreceptor degeneration. The retina encodes visual information and transmits it to the brain. Replicating this retinal code through electrical stimulation is essential to improving the performance of visual prostheses. In doing so, the first step relies on precise neural recordings from visual centers that allow studying the response of these neurons to electrical stimulation of the retina. This paper demonstrates the feasibility of a rat model to conduct highly reliable electrophysiological studies in the field of retinal neuromodulation. A disc electrode, implanted in the retrobulbar space was used to stimulate the retina of Long-Evans rats. Buzsaki multi-electro arrays were inserted in the superior colliculus (SC) to record electrical activity propagated from the retinal ganglion cells (RGCs). Activation thresholds calculated from local field potentials (visual cortex) and from neural spikes (SC) were contrasted. Both values were comparable to those in humans and in other animal models, and were slightly higher when estimated from SC recordings. However, differences were not statistically significant.

Retinal neuroprostheses or ‘bionic eyes’, aim to restore patterned vision to those with vision loss by electrically stimulating the remaining neurons in the degenerate retina. Despite considerable progress over the last two decades, such devices generally stimulate indiscriminately both the ‘ON’ and ‘OFF’ visual pathways in the retina, conveying highly non-physiological signals to the brain.

Retinal electrostimulation is promising a successful therapy to restore functional vision. However, a narrow stimulating current range exists between retinal neuron excitation and inhibition which may lead to misperformance of visual prostheses. As the conveyance of representation of complex visual scenes may require neighbouring electrodes to be activated simultaneously, electric field summation may contribute to reach this inhibitory threshold. This study used three approaches to assess the implications of relatively high stimulating conditions in visual prostheses: (1) in vivo, using a suprachoroidal prosthesis implanted in a feline model, (2) in vitro through electrostimulation of murine retinal preparations, and (3) in silico by computing the response of a population of retinal ganglion cells. Inhibitory stimulating conditions led to diminished cortical activity in the cat. Stimulus-response relationships showed non-monotonic profiles to increasing stimulating current. This was observed in vitro and in silico as the combined response of groups of neurons (close to the stimulating electrode) being inhibited at certain stimulating amplitudes, whilst other groups (far from the stimulating electrode) being recruited. These findings may explain the halo-like phosphene shapes reported in clinical trials and suggest that simultaneous stimulation in retinal prostheses is limited by the inhibitory threshold of the retinal ganglion cells.

OBJECTIVE Visual prostheses have shown promising results in restoring visual perception to blind patients. The ability to differentially activate retinal ganglion cell (RGC) subtypes could further improve the efficacy of these medical devices. APPROACH Using whole-cell patch clamp, we investigated membrane potential differences between ON and OFF RGCs in the mouse retina when their synaptic inputs were blocked by synaptic blockers, and examined the differences in stimulation thresholds under such conditions. By injecting intracellular current, we further confirmed the relationship between RGC stimulation thresholds and resting membrane potentials (RMPs). In addition, we investigated the effects of stimulating electrode location on the differences in stimulation thresholds between ON and OFF RGCs. MAIN RESULTS With synaptic blockade, ON RGCs became significantly more hyperpolarized (from -61.8 ± 1.4 mV to -70.8 ± 1.6 mV), while OFF RGCs depolarized slightly (from -60.5 ± 0.7 mV to -58.6 ± 0.9 mV). RGC stimulation thresholds were negatively correlated with their RMPs (Pearson r value: -0.5154; p-value: 0.0042). Thus, depriving ON RGCs of synaptic inputs significantly increased their thresholds (from 14.7 ± 1.3 µA to 22.3 ± 2.1 µA) over those of OFF RGCs (from 13.2 ± 0.7 µA to 13.1 ± 1.1 µA). However, with control solution, ON and OFF RGC stimulation thresholds were not significantly different. Finally, placement of the stimulating electrode away from the axon enhanced differences in stimulation thresholds between ON and OFF RGCs, facilitating preferential activation of OFF RGCs. SIGNIFICANCE Since ON and OFF RGCs have antagonistic responses to natural light, achieving differential RGC activation could convey more natural visual information, leading to better visual prosthesis outcomes.

A 3D model of atrial electrical activity has been developed with spatially heterogeneous electrophysiological properties. The atrial geometry, reconstructed from the male Visible Human dataset, included gross anatomical features such as the central and peripheral sinoatrial node (SAN), intra-atrial connections, pulmonary veins, inferior and superior vena cava, and the coronary sinus. Membrane potentials of myocytes from spontaneously active or electrically pacedin vitrorabbit cardiac tissue preparations were recorded using intracellular glass microelectrodes. Action potentials of central and peripheral SAN, right and left atrial, and pulmonary vein myocytes were each fitted using a generic ionic model having three phenomenological ionic current components: one time-dependent inward, one time-dependent outward, and one leakage current. To bridge the gap between the single-cell ionic models and the gross electrical behaviour of the 3D whole-atrial model, a simplified 2D tissue disc with heterogeneous regions was optimised to arrive at parameters for each cell type under electrotonic load. Parameters were then incorporated into the 3D atrial model, which as a result exhibited a spontaneously active SAN able to rhythmically excite the atria. The tissue-based optimisation of ionic models and the modelling process outlined are generic and applicable to image-based computer reconstruction and simulation of excitable tissue.

Objective Retinal ganglion cells (RGCs) demonstrate a large range of variation in their ionic channel properties and morphologies. Cell-specific properties are responsible for the unique way RGCs process synaptic inputs, as well as artificial electrical signals such as that from a visual prosthesis. A cell-specific computational modelling approach allows us to examine the functional significance of regional membrane channel expression and cell morphology. Approach In this study, an existing RGC ionic model was extended by including a hyperpolarization activated non-selective cationic current as well as a T-type calcium current identified in recent experimental findings. Biophysically-defined model parameters were simultaneously optimized against multiple experimental recordings from ON and OFF RGCs. Main results With well-defined cell-specific model parameters and the incorporation of detailed cell morphologies, these models were able to closely reconstruct and predict ON and OFF RGC response properties recorded experimentally. Significance The resulting models were used to study the contribution of different ion channel properties and spatial structure of neurons to RGC activation. The techniques of this study are generally applicable to other excitable cell models, increasing the utility of theoretical models in accurately predicting the response of real biological neurons.