Publications by authors named "Martin J Spencer"

5 Publications

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Neural activity shaping utilizing a partitioned target pattern.

J Neural Eng 2021 Mar 8. Epub 2021 Mar 8.

Australian College of Optometry, Parkville, Carlton, Victoria, 3010, AUSTRALIA.

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 cases where neighboring 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 neighboring 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. 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. 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.
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http://dx.doi.org/10.1088/1741-2552/abecc4DOI Listing
March 2021

Global activity shaping strategies for a retinal implant.

J Neural Eng 2019 04 13;16(2):026008. Epub 2018 Nov 13.

Department of Biomedical Engineering, The University of Melbourne, Parkville, Victoria, Australia.

Objective: 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.

Approach: 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.

Main Results: Under wide activation spreads the linear inversion algorithm gave improved solutions but faced two limitations: under low-noise conditions the electrode amplitudes 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.

Significance: This provides a framework for improving the resolution of future retinal implants, especially those with high density electrode arrays.
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http://dx.doi.org/10.1088/1741-2552/aaf071DOI Listing
April 2019

Compensation for Traveling Wave Delay Through Selection of Dendritic Delays Using Spike-Timing-Dependent Plasticity in a Model of the Auditory Brainstem.

Front Comput Neurosci 2018 5;12:36. Epub 2018 Jun 5.

NeuroEngineering Laboratory, Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australia.

Asynchrony among synaptic inputs may prevent a neuron from responding to behaviorally relevant sensory stimuli. For example, "octopus cells" are monaural neurons in the auditory brainstem of mammals that receive input from auditory nerve fibers (ANFs) representing a broad band of sound frequencies. Octopus cells are known to respond with finely timed action potentials at the onset of sounds despite the fact that due to the traveling wave delay in the cochlea, synaptic input from the auditory nerve is temporally diffuse. This paper provides a proof of principle that the octopus cells' dendritic delay may provide compensation for this input asynchrony, and that synaptic weights may be adjusted by a spike-timing dependent plasticity (STDP) learning rule. This paper used a leaky integrate and fire model of an octopus cell modified to include a "rate threshold," a property that is known to create the appropriate onset response in octopus cells. Repeated audio click stimuli were passed to a realistic auditory nerve model which provided the synaptic input to the octopus cell model. A genetic algorithm was used to find the parameters of the STDP learning rule that reproduced the microscopically observed synaptic connectivity. With these selected parameter values it was shown that the STDP learning rule was capable of adjusting the values of a large number of input synaptic weights, creating a configuration that compensated the traveling wave delay of the cochlea.
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http://dx.doi.org/10.3389/fncom.2018.00036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5996126PMC
June 2018

Broadband onset inhibition can suppress spectral splatter in the auditory brainstem.

PLoS One 2015 15;10(5):e0126500. Epub 2015 May 15.

NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, Australia; National ICT Australia, Department of Electrical and Electronic Engineering, University of Melbourne, Melbourne, Australia; Centre for Neural Engineering, University of Melbourne, Melbourne, Australia; Bionics Institute, Melbourne, Australia.

In vivo intracellular responses to auditory stimuli revealed that, in a particular population of cells of the ventral nucleus of the lateral lemniscus (VNLL) of rats, fast inhibition occurred before the first action potential. These experimental data were used to constrain a leaky integrate-and-fire (LIF) model of the neurons in this circuit. The post-synaptic potentials of the VNLL cell population were characterized using a method of triggered averaging. Analysis suggested that these inhibited VNLL cells produce action potentials in response to a particular magnitude of the rate of change of their membrane potential. The LIF model was modified to incorporate the VNLL cells' distinctive action potential production mechanism. The model was used to explore the response of the population of VNLL cells to simple speech-like sounds. These sounds consisted of a simple tone modulated by a saw tooth with exponential decays, similar to glottal pulses that are the repeated impulses seen in vocalizations. It was found that the harmonic component of the sound was enhanced in the VNLL cell population when compared to a population of auditory nerve fibers. This was because the broadband onset noise, also termed spectral splatter, was suppressed by the fast onset inhibition. This mechanism has the potential to greatly improve the clarity of the representation of the harmonic content of certain kinds of natural sounds.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0126500PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433210PMC
April 2016

An investigation of dendritic delay in octopus cells of the mammalian cochlear nucleus.

Front Comput Neurosci 2012 22;6:83. Epub 2012 Oct 22.

NeuroEngineering Laboratory, Department of Electrical and Electronic Engineering, University of Melbourne Melbourne, VIC, Australia ; National ICT Australia Melbourne, VIC, Australia ; Centre for Neural Engineering, University of Melbourne VIC, Australia.

Octopus cells, located in the mammalian auditory brainstem, receive their excitatory synaptic input exclusively from auditory nerve fibers (ANFs). They respond with accurately timed spikes but are broadly tuned for sound frequency. Since the representation of information in the auditory nerve is well understood, it is possible to pose a number of questions about the relationship between the intrinsic electrophysiology, dendritic morphology, synaptic connectivity, and the ultimate functional role of octopus cells in the brainstem. This study employed a multi-compartmental Hodgkin-Huxley model to determine whether dendritic delay in octopus cells improves synaptic input coincidence detection in octopus cells by compensating for the cochlear traveling wave delay. The propagation time of post-synaptic potentials from synapse to soma was investigated. We found that the total dendritic delay was approximately 0.275 ms. It was observed that low-threshold potassium channels in the dendrites reduce the amplitude dependence of the dendritic delay of post-synaptic potentials. As our hypothesis predicted, the model was most sensitive to acoustic onset events, such as the glottal pulses in speech when the synaptic inputs were arranged such that the model's dendritic delay compensated for the cochlear traveling wave delay across the ANFs. The range of sound frequency input from ANFs was also investigated. The results suggested that input to octopus cells is dominated by high frequency ANFs.
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http://dx.doi.org/10.3389/fncom.2012.00083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3486622PMC
November 2012