Biomedical Engineering - Theses
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ItemAdjusting the parameters of electrical stimulation of retinal ganglion cells to reduce neural adaptation and improve efficacy of retinal prostheses( 2018)Retinal prostheses aim to provide visual percepts through electrical stimulation of the retina to blind people affected by diseases caused by photoreceptor degeneration. Two challenges presented by current devices are a lack of selectivity in the activation of retinal ganglion cells (RGCs) and neural adaptation in the retina, which is believed to be the cause of fading—an effect where artificially produced percepts disappear over a short period of time, despite continuous stimulation of the retina. We aim to (1) understand the neural adaptation generated in RGCs during electrical stimulation, (2) obtain the preferred stimulation parameters (waveform) of each morphological class of RGCs and (3) use the preferred waveform of each morphological class to selectively activate different neurons. RGCs have been classified by morphology into 4 main groups: A, B, C and D. We performed an spike-triggered covariance (STC) analysis on the responses of 44 RGCs to extracellular electrical white noise and 43 RGCs to intracellular white noise. We then recovered their temporal electrical receptive fields (tERF), or waveform. A number of RGCs were stimulated with all the previously recovered waveforms to test the efficacy of each waveform on each other. The waveform recovered from the responses to intracellular stimulation have shown that RGCs can be classified into their respective morphological types by using a K-means clustering algorithm. Extracellular stimulation did not result in waveforms with a clear correlation between clusters and morphological classes. Cells from B and D morphological types had lower thresholds when stimulated with the waveform recovered from cells in the same morphological class. A-RGCs on the contrary, did not seem to share the same temporal features in their waveform with other A-type neurons. Further studies involving a larger data set might determine whether the waveform could preferentially stimulate cells from a specific morphological class. Current visual prostheses use electrical pulses with fixed frequencies and amplitudes modulated over hundreds of milliseconds to stimulate the retina. However, in nature, neuronal spiking occurs with stochastic timing, hence the information received naturally from other neurons by RGCs is irregularly timed. We used a single epiretinal electrode to stimulate and compare rat RGC responses to stimulus trains of biphasic pulses delivered at regular and random inter-pulse intervals (IPI), the latter taken from an exponential distribution. Our observations suggest that stimulation with random IPIs result in lower adaptation rates than stimulation with constant IPIs at frequencies of 50 Hz and 200 Hz. We also found a high proportion of lower amplitude action potentials, or spikelets. The spikelets were more prominent at high stimulation frequencies (50 Hz and 200 Hz) and were less susceptible to adaptation, but it was not clear if they propagated along the axon. Using random IPI stimulation in retinal prostheses reduces the decay of RGCs and this could potentially reduce fading of electrically induced visual perception.
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ItemSimulating and optimizing electrical current flow and neuronal activation in retinal implants( 2018)[Abstract Withheld]
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ItemTracking the changes of brain states during epileptogenesis by probing( 2017)Epilepsy affects around 50 million people worldwide. Brain injuries and lesions, such as traumatic brain injury, central nervous system infection and stroke, are associated with higher risk of developing epilepsy. It is hypothesised that electrically-induced brain responses (probing responses) can reflect physiological changes during epileptogenesis, which may provide insights into epileptogenesis and possible new therapies. A systematic continuous longitudinal study of probing responses in a well-controlled environment with both normal and epileptic brains is presented. The objective of this study is to demonstrate how electrically-induced neural responses (probing) track the physiological changes in the brain during epileptogenesis. Intrahippocampal tetanus toxin rat models were used as the model of epilepsy. Control rats received injections without tetanus toxin. Epidural electrodes were implanted to deliver electrical stimulation and record EEG over periods of 9 to 10 weeks in a room with controlled temperature and automatic dark/light switching. It is demonstrated that probing responses can expose sleep/wake cycles, recovery from surgery and epileptogenesis over the study period. The differences between probing responses in sleep and wake states are quantified by a two-level mixed-effects linear regression model. The changes of probing responses related to the recovery from surgery are modelled by a modified logistic function. The probing responses related to epileptogenesis in tetanus toxin models are uncovered after the effects of surgical recovery and sleep/wake cycle are removed. The changes can be observed in the infradian time scale and several markers are found that are associated with the time of the peak of seizure occurrence and the time of seizure remission. This study is the first step to identify stages of epileptogenesis using probing responses. The potential clinical application of probing can be a biomarker for epileptogenesis, a prognostic tool to assess whether epilepsy will develop after a trauma, a way to predict whether remission will occur after posttraumatic epilepsy has developed or a biomarker to assess the effectiveness of traumatic brain injury therapies.
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ItemPrediction and shaping of visual cortex activity for retinal prostheses( 2017)Retinal prostheses are a promising treatment for blindness caused by photoreceptor degeneration. Electrodes implanted in the retina deliver electrical stimuli in the form of current pulses that activate surviving neurons to restore a sense of vision. Clinical trials for such devices have shown that the visual percepts evoked are informative, and can improve the day-to-day life of recipients. However, the spatial resolution of retinal prostheses is a limiting factor, with those who have the highest reported acuity measures still classified as legally blind. Simultaneous stimulation of multiple electrodes is a possible strategy to improve device resolution without increasing the number of physical electrodes. However, electrode interactions that occur during simultaneous stimulation are not well understood. This thesis investigates the characteristics of cortical responses to simultaneous stimulation of multiple electrodes. We formulated a quantitative model to characterise the responses of visual cortex neurons to multi-electrode stimulation of the retina to understand how simultaneous stimulation can improve resolution. Activity was recorded in the visual cortex of normally sighted, anaesthetised cats in response to temporally sparse, spatially white stimulation with 21 or 42 electrodes in the suprachoroidal space of the retina. These data were used to constrain the parameters of a linear-nonlinear model using a spike-triggered covariance technique. The recovered model accurately predicted cortical responses to arbitrary patterns of stimulation, and demonstrated that interactions between electrodes are predominantly linear. The linear filters of the model, which can be considered as weighting matrices for the effect of the stimulating electrodes on each cortical site, showed that cortical responses were topographically organised. Photoreceptor degeneration results in a number of changes in the surviving cells of the retina that can negatively impact stimulation strategies. Therefore, in the second study, we investigated the effect of multi-electrode stimulation on the degenerate retina. Characteristics of cortical responses to simultaneous stimulation of multiple electrodes were evaluated in unilaterally, chronically blind anaesthetised cats, bilaterally implanted with suprachoroidal retinal prostheses. Significant differences were found between responses to stimulation of the normally sighted and blind eyes, which may help to explain the varied perceptual observations in clinical trials with simultaneous stimulation. The success of the linear-nonlinear model in predicting responses to arbitrary patterns of stimulation indicated that it may provide a basis for optimising stimulation strategies to shape cortical activity. Therefore, we investigated the possibility of inverting the model to generate stimuli aimed at reliably altering the spatial characteristics of cortical responses. An in vivo preparation with a normally sighted, anaesthetised cat showed that the response characteristics derived by the model could be exploited to steer current and evoke predictable cortical activity. Overall, these results demonstrate that cortical responses to simultaneous stimulation of both the normal and degenerate retina are repeatable, and can be predicted by a simple linear-nonlinear model. Furthermore, the interactions between electrodes are predominantly linear, and can be harnessed to shape cortical activity through inversion of the model. The method shows promise for improving the efficacy of retinal prostheses and patient outcomes.
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ItemModeling electrical properties of neural tissue using a cellular composite approach( 2017)This research develops a framework for modeling the electrical properties of neu- ral tissue based on its cellular constituents. This has application to modeling of electrical stimulation of neural tissue, including for therapeutic purposes. It also has application to the modeling and interpretation of intrinsic electrical signals in the brain such as spiking, multi-unit activity, local field potential and electroencephalogram (EEG). Standard volume conductor models of neural tissue approximate the electrical properties of tissue with a locally homogeneous conductivity. This is despite the fact that realistic neural tissue is composed of cells with different geometries, orientations and electrical properties. The framework presented here suggests that these cellular level properties have a profound effect on the bulk electrical properties of tissue that cannot be captured by a simple conductivity. The membrane lipid bilayer structure behaves as a capacitance that relates the applied current density to the extracellular potential at previous times. Also, the cells within tissue are tightly packed causing higher resistance in the extracellular space compared with the wider intracellular space, which creates different current paths for the passage of electrical current flow in these spaces. In this mathematical and computational study, we replace the conductivity of tissue in the standard volume conductor approach with an admittivity which depends on spatial and temporal frequencies. Our expressions for bulk tissue admittivity, are derived from single cell properties by using a mean-field approach. The temporal frequency dependence arises through the capacitance of the membrane lipid bilayer and is related to the membrane time constant. The spatial frequency arises due to the passage of current from the highly confined extracellular space into the less confined intracellular space of a neuron and is related to the electrotonic length constant of neurites. Expressions for the admittivity are calculated for tissue consisting of a variety of morphological cell types. These include fiber bundles, layered structures in which the dendrites are confined to a plane and tissue composed of cells with a stellate morphology. Finally, these morphological types are combined in model of cortical grey matter that include the effect of glia as well as neurons on the tissue admittivity. The results show that the effective admittivity changes depending on whether tissue is in the near-, intermediate- or far-field regions relative to a stimulating electrode. The definition of the limits of these regions depends on both spatial and temporal frequencies being applied. The magnitude of the admittivity is smaller in the near-field than the far-field. It is also shown how anisotropic tissue responds to the electrical stimulation depending on the distance of fibers from an electrode. Anisotropic behavior is more prevalent in the far-field region compared to the near-field range in cases where the distribution of fiber orientations shows a bias. The effect of pulse width on tissue response is also investigated and our results demonstrate that for longer pulse widths the transition between near-field to far-field is displaced away from the electrode compared to shorter pulse widths. These results are all explained in details in Chapters 3 and 4 of the thesis. The glia influence on shaping the admittivity response of tissue based on their population is considered in Chapter 5. The new, more realistic model will facilitate a more accurate application of electrical stimulation to any neural tissue and specifically the brain. More accurate stimulation will improve emerging neurological therapies, such as deep brain stimulation for epilepsy and Parkinson’s disease.