Biomedical Engineering - Research Publications

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    Quantifying visual acuity for pre-clinical testing of visual prostheses
    Spencer, M ; Kameneva, T ; Grayden, DB ; Burkitt, AN ; Meffin, H (IOP Publishing Ltd, 2023-02-01)
    Objective.Visual prostheses currently restore only limited vision. More research and pre-clinical work are required to improve the devices and stimulation strategies that are used to induce neural activity that results in visual perception. Evaluation of candidate strategies and devices requires an objective way to convert measured and modelled patterns of neural activity into a quantitative measure of visual acuity.Approach.This study presents an approach that compares evoked patterns of neural activation with target and reference patterns. A d-prime measure of discriminability determines whether the evoked neural activation pattern is sufficient to discriminate between the target and reference patterns and thus provides a quantified level of visual perception in the clinical Snellen and MAR scales. The magnitude of the resulting value was demonstrated using scaled standardized 'C' and 'E' optotypes.Main results.The approach was used to assess the visual acuity provided by two alternative stimulation strategies applied to simulated retinal implants with different electrode pitch configurations and differently sized spreads of neural activity. It was found that when there is substantial overlap in neural activity generated by different electrodes, an estimate of acuity based only upon electrode pitch is incorrect; our proposed method gives an accurate result in both circumstances.Significance.Quantification of visual acuity using this approach in pre-clinical development will allow for more rapid and accurate prototyping of improved devices and neural stimulation strategies.
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    Preferential modulation of individual retinal ganglion cells by electrical stimulation
    Yunzab, M ; Soto-Breceda, A ; Maturana, M ; Kirkby, S ; Slattery, M ; Newgreen, A ; Meffin, H ; Kameneva, T ; Burkitt, AN ; Ibbotson, M ; Tong, W (IOP Publishing Ltd, 2022-08-01)
    Objective.Retinal prostheses have had limited success in vision restoration through electrical stimulation of surviving retinal ganglion cells (RGCs) in the degenerated retina. This is partly due to non-preferential stimulation of all RGCs near a single stimulating electrode, which include cells that conflict in their response properties and their contribution to visiual processing. Our study proposes a stimulation strategy to preferentially stimulate individual RGCs based on their temporal electrical receptive fields (tERFs).Approach.We recorded the responses of RGCs using whole-cell patch clamping and demonstrated the stimulation strategy, first using intracellular stimulation, then via extracellular stimulation.Main results. We successfully reconstructed the tERFs according to the RGC response to Gaussian white noise current stimulation. The characteristics of the tERFs were extracted and compared based on the morphological and light response types of the cells. By re-delivering stimulation trains that were composed of the tERFs obtained from different cells, we could preferentially stimulate individual RGCs as the cells showed lower activation thresholds to their own tERFs.Significance.This proposed stimulation strategy implemented in the next generation of recording and stimulating retinal prostheses may improve the quality of artificial vision.
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    Activity of Retinal Neurons Can Be Modulated by Tunable Near-Infrared Nanoparticle Sensors.
    Begeng, JM ; Tong, W ; Rosal, BD ; Ibbotson, M ; Kameneva, T ; Stoddart, PR (American Chemical Society (ACS), 2023-02-14)
    The vision of patients rendered blind by photoreceptor degeneration can be partially restored by exogenous stimulation of surviving retinal ganglion cells (RGCs). Whereas conventional electrical stimulation techniques have failed to produce naturalistic visual percepts, nanoparticle-based optical sensors have recently received increasing attention as a means to artificially stimulate the RGCs. In particular, nanoparticle-enhanced infrared neural modulation (NINM) is a plasmonically mediated photothermal neuromodulation technique that has a demonstrated capacity for both stimulation and inhibition, which is essential for the differential modulation of ON-type and OFF-type RGCs. Gold nanorods provide tunable absorption through the near-infrared wavelength window, which reduces interference with any residual vision. Therefore, NINM may be uniquely well-suited to retinal prosthesis applications but, to our knowledge, has not previously been demonstrated in RGCs. In the present study, NINM laser pulses of 100 μs, 500 μs and 200 ms were applied to RGCs in explanted rat retinae, with single-cell responses recorded via patch-clamping. The shorter laser pulses evoked robust RGC stimulation by capacitive current generation, while the long laser pulses are capable of inhibiting spontaneous action potentials by thermal block. Importantly, an implicit bias toward OFF-type inhibition is observed, which may have important implications for the feasibility of future high-acuity retinal prosthesis design based on nanoparticle sensors.
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    Dynamic optical clamp: A novel electrophysiology tool and a technique for closed-loop stimulation
    Hart, WL ; Needham, K ; Richardson, RT ; Stoddart, PR ; Kameneva, T (ELSEVIER SCI LTD, 2023-08)
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    Combining the neural mass model and Hodgkin-Huxley formalism: Neuronal dynamics modelling
    Ying, T ; Burkitt, AN ; Kameneva, T (Elsevier, 2023-01)
    Epilepsy is a neurological disorder that affects the nervous system and is characterized by recurrent seizures. Experimental data shows that increase in the extracellular potassium concentration can support the generation of seizures and that the T-type calcium channel antagonists can be effective as anti-epileptic drugs. To investigate these two phenomena in detail, we combine microscopic level modelling using Hodgkin–Huxley formalism and a macroscopic level approach using a neural mass model. The microscopic level approach describes the initiation of action potentials in individual neurons using conductance-based model. The macroscopic (neural mass model) approach is a low-dimensional phenomenological model that describes the activity of a large population of neurons. The neural mass model replicated the interactions between inhibitory and excitatory neuronal populations by using a sigmoidal function that converts neuronal postsynaptic potential into the average spiking rate of a given population. This sigmoidal function links two levels of modelling: microscopic and macroscopic. Our results are in agreement with experimental data and show that an increase in the extracellular potassium concentration or an increase in the T-type calcium conductance can cause brain network transitions from normal background to pathological seizure-like dynamics. In addition, the results show that these transitions only happen for a limited range of network parameters and that the slow-inhibitory synaptic gain has a stronger effect on network dynamics during transitions than the fast-inhibitory synaptic gain.
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    A comparison of open-loop and closed-loop stimulation strategies to control excitation of retinal ganglion cells
    Kameneva, T ; Zarelli, D ; Nesic, D ; Grayden, DB ; Burkitt, AN ; Meffin, H (Elsevier, 2014-11-01)
    Currently, open-loop stimulation strategies are prevalent in medical bionic devices. These strategies involve setting electrical stimulation that does not change in response to neural activity. We investigate through simulation the advantages of using a closed-loop strategy that sets stimulation level based on continuous measurement of the level of neural activity. We propose a model-based controller design to control activation of retinal neurons. To deal with the lack of controllability and observability of the whole system, we use Kalman decomposition and control only the controllable and observable part. We show that the closed-loop controller performs better than the open-loop controller when perturbations are introduced into the system. We envisage that our work will give rise to more investigations of the closed-loop techniques in basic neuroscience research and in clinical applications of medical bionics.
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    Analysis of extracellular spike waveforms and associated receptive fields of neurons in cat primary visual cortex
    Sun, SH ; Almasi, A ; Yunzab, M ; Zehra, S ; Hicks, DG ; Kameneva, T ; Ibbotson, MR ; Meffin, H (WILEY, 2021-04)
    KEY POINTS: Extracellular spikes recorded in the visual cortex (Area 17/18, V1) are commonly classified into either regular-spiking (RS) or fast-spiking (FS). Using multi-electrode arrays positioned in cat V1 and a broadband stimulus, we show that there is also a distinct class with positive-spiking (PS) waveforms. PS units were associated mainly with non-oriented receptive fields while RS and FS units had orientation-selective receptive fields. We suggest that PS units are recordings of axons originating from the thalamus. This conclusion was reinforced by our finding that we could record PS units after cortical silencing, but not record RS and FS units. The importance of our findings is that we were able to correlate spike shapes with receptive field characteristics with high precision using multi-electrode extracellular recording techniques. This allows considerable increases in the amount of information that can be extracted from future cortical experiments. ABSTRACT: Extracellular spike waveforms from recordings in the visual cortex have been classified into either regular-spiking (RS) or fast-spiking (FS) units. While both these types of spike waveforms are negative-dominant, we show that there are also distinct classes of spike waveforms in visual Area 17/18 (V1) of anaesthetised cats with positive-dominant waveforms, which are not regularly reported. The spatial receptive fields (RFs) of these different spike waveform types were estimated, which objectively revealed the existence of oriented and non-oriented RFs. We found that units with positive-dominant spikes, which have been associated with recordings from axons in the literature, had mostly non-oriented RFs (84%), which are similar to the centre-surround RFs observed in the dorsal lateral geniculate nucleus (dLGN). Thus, we hypothesise that these positive-dominant waveforms may be recordings from dLGN afferents. We recorded from V1 before and after the application of muscimol (a cortical silencer) and found that the positive-dominant spikes (PS) remained while the RS and FS cells did not. We also noted that the PS units had spiking characteristics normally associated with dLGN units (i.e. higher response spike rates, lower response latencies and higher proportion of burst spikes). Our findings show quantitatively that it is possible to correlate the RF properties of cortical neurons with particular spike waveforms. This has implications for how extracellular recordings should be interpreted and complex experiments can now be contemplated that would have been very challenging previously, such as assessing the feedforward connectivity between brain areas in the same location of cortical tissue.
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    Neural activity shaping utilizing a partitioned target pattern
    Spencer, MJ ; Kameneva, T ; Grayden, DB ; Burkitt, AN ; Meffin, H (IOP PUBLISHING LTD, 2021-08)
    Electrical stimulation of neural tissue is used in both clinical and experimental devices to evoke a desired spatiotemporal pattern of neural activity. These devices induce a local field that drives neural activation, referred to as an activating function or generator signal. In visual prostheses, the spread of generator signal from each electrode within the neural tissue results in a spread of visual perception, referred to as a phosphene.Objective.In cases where neighbouring phosphenes overlap, it is desirable to use current steering or neural activity shaping strategies to manipulate the generator signal between the electrodes to provide greater control over the total pattern of neural activity. Applying opposite generator signal polarities in neighbouring regions of the retina forces the generator signal to pass through zero at an intermediate point, thus inducing low neural activity that may be perceived as a high-contrast line. This approach provides a form of high contrast visual perception, but it requires partitioning of the target pattern into those regions that use positive or negative generator signals. This discrete optimization is an NP-hard problem that is subject to being trapped in detrimental local minima.Approach.This investigation proposes a new partitioning method using image segmentation to determine the most beneficial positive and negative generator signal regions. Utilizing a database of 1000 natural images, the method is compared to alternative approaches based upon the mean squared error of the outcome.Main results.Under nominal conditions and with a set computation limit, partitioning provided improvement for 32% of these images. This percentage increased to 89% when utilizing image pre-processing to emphasize perceptual features of the images. The percentage of images that were dealt with most effectively with image segmentation increased as lower computation limits were imposed on the algorithms.Significance.These results provide a new method to increase the resolution of neural stimulating arrays and thus improve the experience of visual prosthesis users.
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    Learning receptive field properties of complex cells in V1
    Lian, Y ; Almasi, A ; Grayden, DB ; Kameneva, T ; Burkitt, AN ; Meffin, H ; Einhäuser, W (PUBLIC LIBRARY SCIENCE, 2021-03)
    There are two distinct classes of cells in the primary visual cortex (V1): simple cells and complex cells. One defining feature of complex cells is their spatial phase invariance; they respond strongly to oriented grating stimuli with a preferred orientation but with a wide range of spatial phases. A classical model of complete spatial phase invariance in complex cells is the energy model, in which the responses are the sum of the squared outputs of two linear spatially phase-shifted filters. However, recent experimental studies have shown that complex cells have a diverse range of spatial phase invariance and only a subset can be characterized by the energy model. While several models have been proposed to explain how complex cells could learn to be selective to orientation but invariant to spatial phase, most existing models overlook many biologically important details. We propose a biologically plausible model for complex cells that learns to pool inputs from simple cells based on the presentation of natural scene stimuli. The model is a three-layer network with rate-based neurons that describes the activities of LGN cells (layer 1), V1 simple cells (layer 2), and V1 complex cells (layer 3). The first two layers implement a recently proposed simple cell model that is biologically plausible and accounts for many experimental phenomena. The neural dynamics of the complex cells is modeled as the integration of simple cells inputs along with response normalization. Connections between LGN and simple cells are learned using Hebbian and anti-Hebbian plasticity. Connections between simple and complex cells are learned using a modified version of the Bienenstock, Cooper, and Munro (BCM) rule. Our results demonstrate that the learning rule can describe a diversity of complex cells, similar to those observed experimentally.
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    The effect of morphology upon electrophysiological responses of retinal ganglion cells: simulation results
    Maturana, MI ; Kameneva, T ; Burkitt, AN ; Meffin, H ; Grayden, DB (SPRINGER, 2014-04)
    Retinal ganglion cells (RGCs) display differences in their morphology and intrinsic electrophysiology. The goal of this study is to characterize the ionic currents that explain the behavior of ON and OFF RGCs and to explore if all morphological types of RGCs exhibit the phenomena described in electrophysiological data. We extend our previous single compartment cell models of ON and OFF RGCs to more biophysically realistic multicompartment cell models and investigate the effect of cell morphology on intrinsic electrophysiological properties. The membrane dynamics are described using the Hodgkin - Huxley type formalism. A subset of published patch-clamp data from isolated intact mouse retina is used to constrain the model and another subset is used to validate the model. Two hundred morphologically distinct ON and OFF RGCs are simulated with various densities of ionic currents in different morphological neuron compartments. Our model predicts that the differences between ON and OFF cells are explained by the presence of the low voltage activated calcium current in OFF cells and absence of such in ON cells. Our study shows through simulation that particular morphological types of RGCs are capable of exhibiting the full range of phenomena described in recent experiments. Comparisons of outputs from different cells indicate that the RGC morphologies that best describe recent experimental results are ones that have a larger ratio of soma to total surface area.