ORCID Profile
0000-0003-0081-8569
Current Organisation
Swinburne University of Technology
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Signal Processing | Biological Mathematics | Pharmacology and Pharmaceutical Sciences | Applied Mathematics | Medical Devices | Biomaterials | Biomechanical Engineering | Biomedical Engineering | Applied Mathematics not elsewhere classified | Electrical and Electronic Engineering | Pharmaceutical Sciences | Biomedical Engineering not elsewhere classified | Regenerative Medicine (incl. Stem Cells and Tissue Engineering) |
ANZSRC Socio-Economic Objective (SEO)
Expanding Knowledge in Engineering | Hearing, Vision, Speech and Their Disorders | Human Pharmaceutical Treatments (e.g. Antibiotics) | Nervous System and Disorders | Human Biological Preventatives (e.g. Vaccines) | Human Diagnostics | Expanding Knowledge in the Medical and Health Sciences | Expanding Knowledge in Technology
Related Links
Publications
Upper stimulation threshold for retinal ganglion cell activation
Publisher: IOP Publishing
Date: 09-05-2018
Abstract: The existence of an upper threshold in electrically stimulated retinal ganglion cells (RGCs) is of interest because of its relevance to the development of visual prosthetic devices, which are designed to restore partial sight to blind patients. The upper threshold is defined as the stimulation level above which no action potentials (direct spikes) can be elicited in electrically stimulated retina. We collected and analyzed in vitro recordings from rat RGCs in response to extracellular biphasic (anodic-cathodic) pulse stimulation of varying litudes and pulse durations. Such responses were also simulated using a multicompartment model. We identified the in idual cell variability in response to stimulation and the phenomenon known as upper threshold in all but one of the recorded cells (n = 20/21). We found that the latencies of spike responses relative to stimulus litude had a characteristic U-shape. In silico, we showed that the upper threshold phenomenon was observed only in the soma. For all tested biphasic pulse durations, electrode positions, and pulse litudes above lower threshold, a propagating action potential was observed in the distal axon. For litudes above the somatic upper threshold, the axonal action potential back-propagated in the direction of the soma, but the soma's low level of hyperpolarization prevented action potential generation in the soma itself. An upper threshold observed in the soma does not prevent spike conductance in the axon.
Vision Processing for Assistive Vision: A Deep Reinforcement Learning Approach
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Quantifying visual acuity for pre-clinical testing of visual prostheses
Publisher: IOP Publishing
Date: 27-01-2023
Abstract: 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.
Learning receptive field properties of complex cells in V1
Publisher: Cold Spring Harbor Laboratory
Date: 18-05-2020
DOI: 10.1101/2020.05.18.101873
Abstract: The authors have withdrawn their manuscript due to a duplicate posting on our website. Please visit 0.1101/2020.05.18.101881 to access the current version of this preprint on bioRxiv
Combining the neural mass model and Hodgkin–Huxley formalism: Neuronal dynamics modelling
Publisher: Elsevier BV
Date: 2023
Classification of Epileptic and Psychogenic Non-Epileptic Seizures Using Electroencephalography and Electrocardiography
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Combined optogenetic and electrical stimulation of auditory neurons increases effective stimulation frequency—an in vitro study
Publisher: IOP Publishing
Date: 19-02-2020
Abstract: The performance of neuroprostheses, including cochlear and retinal implants, is currently constrained by the spatial resolution of electrical stimulation. Optogenetics has improved the spatial control of neurons in vivo but lacks the fast-temporal dynamics required for auditory and retinal signalling. The objective of this study is to demonstrate that combining optical and electrical stimulation in vitro could address some of the limitations associated with each of the stimulus modes when used independently. The response of murine auditory neurons expressing ChR2-H134 to combined optical and electrical stimulation was characterised using whole cell patch cl electrophysiology. Optogenetic costimulation produces a three-fold increase in peak firing rate compared to optical stimulation alone and allows spikes to be evoked by combined subthreshold optical and electrical inputs. Subthreshold optical depolarisation also facilitated spiking in auditory neurons for periods of up to 30 ms without evidence of wide-scale Na These findings may contribute to the development of spatially and temporally selective optogenetic-based neuroprosthetics and complement recent developments in 'fast opsins'.
Learning receptive field properties of complex cells in V1
Publisher: Cold Spring Harbor Laboratory
Date: 18-05-2020
DOI: 10.1101/2020.05.18.101881
Abstract: 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 erse 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 ersity of complex cells, similar to those observed experimentally. Many cortical functions originate from the learning ability of the brain. How the properties of cortical cells are learned is vital for understanding how the brain works. There are many models that explain how V1 simple cells can be learned. However, how V1 complex cells are learned still remains unclear. In this paper, we propose a model of learning in complex cells based on the Bienenstock, Cooper, and Munro (BCM) rule. We demonstrate that properties of receptive fields of complex cells can be learned using this biologically plausible learning rule. Quantitative comparisons between the model and experimental data are performed. Results show that model complex cells can account for the ersity of complex cells found in experimental studies. In summary, this study provides a plausible explanation for how complex cells can be learned using biologically plausible plasticity mechanisms. Our findings help us to better understand biological vision processing and provide us with insights into the general signal processing principles that the visual cortex employs to process visual information.
Response of primary auditory neurons to stimulation with infrared light in vitro.
Publisher: IOP Publishing
Date: 18-03-2021
Abstract: Objective. Infrared light can be used to modulate the activity of neuronal cells through thermally-evoked capacitive currents and thermosensitive ion channel modulation. The infrared power threshold for action potentials has previously been found to be far lower in the in vivo cochlea when compared with other neuronal targets, implicating spiral ganglion neurons (SGNs) as a potential target for infrared auditory prostheses. However, conflicting experimental evidence suggests that this low threshold may arise from an intermediary mechanism other than direct SGN stimulation, potentially involving residual hair cell activity. Approach. Patch-cl recordings from cultured SGNs were used to explicitly quantify the capacitive and ion channel currents in an environment devoid of hair cells. Neurons were irradiated by a 1870 nm laser with pulse durations of 0.2–5.0 ms and powers up to 1.5 W. A Hodgkin-Huxley-type model was established by first characterising the voltage dependent currents, and then incorporating laser-evoked currents separated into temperature-dependent and temperature-gradient-dependent components. This model was found to accurately simulate neuronal responses and allowed the results to be extrapolated to stimulation parameter spaces not accessible during this study. Main results. The previously-reported low in vivo SGN stimulation threshold was not observed, and only subthreshold depolarisation was achieved, even at high light exposures. Extrapolating these results with our Hodgkin-Huxley-type model predicts an action potential threshold which does not deviate significantly from other neuronal types. Significance. This suggests that the low-threshold response that is commonly reported in vivo may arise from an alternative mechanism, and calls into question the potential usefulness of the effect for auditory prostheses. The step-wise approach to modelling optically-evoked currents described here may prove useful for analysing a wider range of cell types where capacitive currents and conductance modulation are dominant.
Erratum: Global activity shaping strategies for a retinal implant (2019 J. Neural Eng. 16 026008)
Publisher: IOP Publishing
Date: 17-09-2019
Measuring brain response to transcutaneous vagus nerve stimulation (tVNS) using simultaneous magnetoencephalography (MEG)
Publisher: IOP Publishing
Date: 04-2022
Abstract: Objective. Transcutaneous vagus nerve stimulation (tVNS) is a form of non-invasive brain stimulation that delivers a sequence of electrical pulses to the auricular branch of the vagus nerve and is used increasingly in the treatment of a number of health conditions such as epilepsy and depression. Recent research has focused on the efficacy of tVNS to treat different medical conditions, but there is little conclusive evidence concerning the optimal stimulation parameters. There are relatively few studies that have combined tVNS with a neuroimaging modality, and none that have attempted simultaneous magnetoencephalography (MEG) and tVNS due to the presence of large stimulation artifacts produced by the electrical stimulation which are many orders of magnitude larger than underlying brain activity. Approach. The aim of this study is to investigate the utility of MEG to gain insight into the regions of the brain most strongly influenced by tVNS and how variation of the stimulation parameters can affect this response in healthy participants. Main results. We have successfully demonstrated that MEG can be used to measure brain response to tVNS. We have also shown that varying the stimulation frequency can lead to a difference in brain response, with the brain also responding in different anatomical regions depending on the frequency. Significance. The main contribution of this paper is to demonstrate the feasibility of simultaneous pulsed tVNS and MEG recording, allowing direct investigation of the changes in brain activity that result from different stimulation parameters. This may lead to the development of customised therapeutic approaches for the targeted treatment of different conditions.
Neural mass models as a tool to investigate neural dynamics during seizures
Publisher: Springer Science and Business Media LLC
Date: 19-01-2017
DOI: 10.1007/S10827-017-0636-X
Abstract: Epilepsy is one of the most common neurological disorders and is characterized by recurrent seizures. We use theoretical neuroscience tools to study brain dynamics during seizures. We derive and simulate a computational model of a network of hippoc al neuronal populations. Each population within the network is based on a model that has been shown to replicate the electrophysiological dynamics observed during seizures. The results provide insights into possible mechanisms for seizure spread. We observe that epileptiform activity remains localized to a pathological region when a global connectivity parameter is less than a critical value. After establishing the critical value for seizure spread, we explored how to correct the effect by altering particular synaptic gains. The spreading of seizures is quantified using numerical methods for seizure detection. The results from this study provide a new avenue of exploration for seizure control.
Single-compartment models of retinal ganglion cells with different electrophysiologies
Publisher: Informa UK Limited
Date: 02-10-2017
Irregularly timed electrical pulses reduce adaptation of retinal ganglion cells
Publisher: IOP Publishing
Date: 03-08-2018
Abstract: Retinal prostheses aim to provide visual percepts to blind people affected by diseases caused by photoreceptor degeneration. One of the main challenges presented by current devices is 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 understand the neural adaptation generated in retinal ganglion cells (RGCs) during electrical stimulation. Current visual prostheses use electrical pulses with fixed frequencies and litudes 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 litude 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.
Acute effects of resonance frequency breathing on cardiovascular regulation
Publisher: Wiley
Date: 11-2019
DOI: 10.14814/PHY2.14295
Neural activity shaping utilizing a partitioned target pattern
Publisher: IOP Publishing
Date: 31-03-2021
Abstract: 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.
In vitro assessment of the differences in retinal ganglion cell responses to intra- and extracellular electrical stimulation
Publisher: IOP Publishing
Date: 06-06-2018
Abstract: To compare responses of retinal ganglion cells (RGCs) to intracellular and extracellular electrical stimulation of varying frequency and litude. In vitro patch cl was used to record the responses of RGCs to sinusoidal current stimulation of varying frequency and litude. The results were simulated using the Neuron software package. The stimulation frequency yielding the greatest response was higher for extracellular stimulation compared to intracellular stimulation in the same cells (256 Hz versus 64 Hz). In fact, at the high end of the frequency range, where extracellular stimulation was highly efficacious, no responses could be generated using intracellular stimulation. A region in the litude-frequency stimulation space was identified where OFF-RGCs could be preferentially stimulated over ON-RGCs. We found that the inability of RGCs to respond at high frequencies of intracellular stimulation is likely the result of the axon acting as a low pass filter. There is no direct translation of the results obtained with intracellular stimulation to those that employ extracellular stimulation.
Dynamic optical clamp: A novel electrophysiology tool and a technique for closed-loop stimulation
Publisher: Elsevier BV
Date: 08-2023
Global activity shaping strategies for a retinal implant
Publisher: IOP Publishing
Date: 23-01-2019
Abstract: Retinal prostheses provide visual perception via electrical stimulation of the retina using an implanted array of electrodes. The retinal activation resulting from each electrode is not point-like instead each electrode introduces a spread of retinal activation that may overlap with activations from other electrodes. With most conventional stimulation strategies this overlap leads to image blur. Here we propose a 'shaping' algorithm that uses multiple electrodes to manipulate the current between electrodes in a desired way. We assume a forward model for the conversion of electrode strengths to retinal activation. Three alternative global shaping algorithms are developed by calculating reverse models under different assumptions: linear inversion using singular value decomposition to produce the pseudoinverse, a linearly constrained quadratic program, and a binary quadratic program to partition the target pattern. The algorithms were assessed using both the mean squared error between the resulting images and desired images, as well as their adherence to the maximum allowed electrode currents. Under wide activation spreads the linear inversion algorithm gave improved solutions but faced two limitations: under low-noise conditions the electrode litudes exceeded their set limit the set of solutions did not include the possibility of using negative local currents to induce retinal activation. The linearly constrained quadratic program and binary quadratic program respectively addressed these problems, but required much greater computation time. This provides a framework for improving the resolution of future retinal implants, especially those with high density electrode arrays.
Modeling experimental recordings of vagal afferent signaling of intestinal inflammation for neuromodulation
Publisher: IOP Publishing
Date: 05-09-2018
Abstract: Artificial modulation of peripheral nerve signals (neuromodulation) by electrical stimulation is an innovation with potential to develop treatments that replace or supplement drugs. One function of the nervous system that can be exploited by neuromodulation is regulation of disease intensity. Optimal interfacing of devices with the nervous system requires suitable models of peripheral nerve systems so that closed-loop control can be utilized for therapeutic benefit. We use physiological data to model afferent signaling in the vagus nerve that carries information about inflammation in the small intestine to the brain. The vagal nerve signaling system is distributed and complex however, we propose a class of reductive models using a state-space formalism that can be tuned in a patient-specific manner. These models provide excellent fits to a large range of nerve recording data but are computationally simple enough for feedback control in implantable neuromodulation devices.
Learning receptive field properties of complex cells in V1
Publisher: Public Library of Science (PLoS)
Date: 02-03-2021
DOI: 10.1371/JOURNAL.PCBI.1007957
Abstract: 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 erse 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 ersity of complex cells, similar to those observed experimentally.
Forecasting psychogenic non-epileptic seizure likelihood from ambulatory EEG and ECG
Publisher: IOP Publishing
Date: 10-2022
Abstract: Objective. Critical slowing features (variance and autocorrelation) of long-term continuous electroencephalography (EEG) and electrocardiography (ECG) data have previously been used to forecast epileptic seizure onset. This study tested the feasibility of forecasting non-epileptic seizures using the same methods. In doing so, we examined if long-term cycles of brain and cardiac activity are present in clinical physiological recordings of psychogenic non-epileptic seizures (PNES). Approach. Retrospectively accessed ambulatory EEG and ECG data from 15 patients with non-epileptic seizures and no background of epilepsy were used for developing the forecasting system. The median period of recordings was 161 h, with a median of 7 non-epileptic seizures per patient. The phases of different cycles (5 min, 1 h, 6 h, 12 h, 24 h) of EEG and RR interval (RRI) critical slowing features were investigated. Forecasters were generated using combinations of the variance and autocorrelation of both EEG and the RRI of the ECG at each of the aforementioned cycle lengths. Optimal forecasters were selected as those with the highest area under the receiver-operator curve (AUC). Main results. It was found that PNES events occurred in the rising phases of EEG feature cycles of 12 and 24 h in duration at a rate significantly above chance. We demonstrated that the proposed forecasters achieved performance significantly better than chance in 8/15 of patients, and the mean AUC of the best forecaster across patients was 0.79. Significance. To our knowledge, this is the first study to retrospectively forecast non-epileptic seizures using both EEG and ECG data. The significance of EEG in the forecasting models suggests that cyclic EEG features of non-epileptic seizures exist. This study opens the potential of seizure forecasting beyond epilepsy, into other disorders of episodic loss of consciousness or dissociation.
Functional Connectivity Analysis of Transcutaneous Vagus Nerve Stimulation (tVNS) Using Magnetoencephalography (MEG)
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Electrical receptive fields of retinal ganglion cells: Influence of presynaptic neurons
Publisher: Public Library of Science (PLoS)
Date: 12-02-2018
Related Organisations
Related Funding Activities
Discovery Projects - Grant ID: DP140104533
Start Date: 2014
End Date: 12-2017
Amount: $506,661.00
Funder: Australian Research Council
View Funded ActivityDiscovery Early Career Researcher Award - Grant ID: DE120102210
Start Date: 06-2012
End Date: 07-2016
Amount: $350,333.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP170101162
Start Date: 12-2018
End Date: 12-2021
Amount: $196,570.00
Funder: Australian Research Council
View Funded ActivityIndustrial Transformation Training Centres - Grant ID: IC170100016
Start Date: 05-2018
End Date: 12-2024
Amount: $3,123,492.00
Funder: Australian Research Council
View Funded Activity