No abstract

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.

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.

for providing valuable consultation, as well as Chan Bee Ting, MS, for helping in construction of the computational models. ABSTRACTInfarct extension, a process involving progressive extension of the infarct zone (IZ) into the normally perfused border zone (BZ), leads to continuous degradation of the myocardial function and adverse remodeling. Despite carrying a high risk of mortality, detailed understanding of the mechanisms leading to BZ hypoxia and infarct extension remains unexplored. In the present study, we developed a 3D truncated ellipsoidal left ventricular (LV) model incorporating realistic electromechanical properties and fiber orientation to examine This article is protected by copyright. All rights reserved.the mechanical interaction among the remote, infarct and border zones in the presence of varying infarct transmural extent (TME). Localized highly abnormal systolic fiber stress was observed at the BZ, owing to the simultaneous presence of moderately increased stiffness and fiber strain at this region, caused by the mechanical tethering effect imposed by the overstretched IZ. Our simulations also demonstrated the greatest tethering effect and stress in BZ regions with fiber direction tangential to the BZ-RZ boundary. This can be explained by the lower stiffness in the cross-fiber direction, which gave rise to a greater stretching of the IZ in this direction. The average fiber strain of the IZ, as well as the maximum stress in the subendocardial layer increased steeply from 10% to 50% infarct TME, and slower thereafter. Based on our stress-strain loop analysis, we found impairment in the myocardial energy efficiency and elevated energy expenditure with increasing infarct TME, which we believe to place the BZ at further risk of hypoxia.

A generic cardiomyocyte ionic model, whose complexity lies between a simple phenomenological formulation and a biophysically detailed ionic membrane current description, is presented. The model provides a user-defined number of ionic currents, employing two-gate Hodgkin-Huxley type kinetics. Its generic nature allows accurate reconstruction of action potential waveforms recorded experimentally from a range of cardiac myocytes. Using a multiobjective optimisation approach, the generic ionic model was optimised to accurately reproduce multiple action potential waveforms recorded from central and peripheral sinoatrial nodes and right atrial and left atrial myocytes from rabbit cardiac tissue preparations, under different electrical stimulus protocols and pharmacological conditions. When fitted simultaneously to multiple datasets, the time course of several physiologically realistic ionic currents could be reconstructed. Model behaviours tend to be well identified when extra experimental information is incorporated into the optimisation.