Biomedical Engineering - Research Publications
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ItemFrequency set selection for multi-frequency steady-state visual evoked potential-based brain-computer interfaces(FRONTIERS MEDIA SA, 2022-12-21)OBJECTIVE: Multi-frequency steady-state visual evoked potential (SSVEP) stimulation and decoding methods enable the representation of a large number of visual targets in brain-computer interfaces (BCIs). However, unlike traditional single-frequency SSVEP, multi-frequency SSVEP is not yet widely used. One of the key reasons is that the redundancy in the input options requires an additional selection process to define an effective set of frequencies for the interface. This study investigates systematic frequency set selection methods. METHODS: An optimization strategy based on the analysis of the frequency components in the resulting multi-frequency SSVEP is proposed, investigated and compared to existing methods, which are constructed based on the analysis of the stimulation (input) signals. We hypothesized that minimizing the occurrence of common sums in the multi-frequency SSVEP improves the performance of the interface, and that selection by pairs further increases the accuracy compared to selection by frequencies. An experiment with 12 participants was conducted to validate the hypotheses. RESULTS: Our results demonstrated a statistically significant improvement in decoding accuracy with the proposed optimization strategy based on multi-frequency SSVEP features compared to conventional techniques. Both hypotheses were validated by the experiments. CONCLUSION: Performing selection by pairs and minimizing the number of common sums in selection by pairs are effective ways to select suitable frequency sets that improve multi-frequency SSVEP-based BCI accuracies. SIGNIFICANCE: This study provides guidance on frequency set selection in multi-frequency SSVEP. The proposed method in this study shows significant improvement in BCI performance (decoding accuracy) compared to existing methods in the literature.
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ItemNo Preview AvailableEvidence of Onset and Sustained Neural Responses to Isolated Phonemes from Intracranial Recordings in a Voice-based Cursor Control Task(ISCA-INT SPEECH COMMUNICATION ASSOC, 2022)
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ItemNo Preview AvailableVascular remodeling in sheep implanted with endovascular neural interface(IOP Publishing Ltd, 2022-10-01)Objective.The aim of this work was to assess vascular remodeling after the placement of an endovascular neural interface (ENI) in the superior sagittal sinus (SSS) of sheep. We also assessed the efficacy of neural recording using an ENI.Approach.The study used histological analysis to assess the composition of the foreign body response. Micro-CT images were analyzed to assess the profiles of the foreign body response and create a model of a blood vessel. Computational fluid dynamic modeling was performed on a reconstructed blood vessel to evaluate the blood flow within the vessel. Recording of brain activity in sheep was used to evaluate efficacy of neural recordings.Main results.Histological analysis showed accumulated extracellular matrix material in and around the implanted ENI. The extracellular matrix contained numerous macrophages, foreign body giant cells, and new vascular channels lined by endothelium. Image analysis of CT slices demonstrated an uneven narrowing of the SSS lumen proportional to the stent material within the blood vessel. However, the foreign body response did not occlude blood flow. The ENI was able to record epileptiform spiking activity with distinct spike morphologies.Significance. This is the first study to show high-resolution tissue profiles, the histological response to an implanted ENI and blood flow dynamic modeling based on blood vessels implanted with an ENI. The results from this study can be used to guide surgical planning and future ENI designs; stent oversizing parameters to blood vessel diameter should be considered to minimize detrimental vascular remodeling.
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ItemEmergence of radial orientation selectivity: Effect of cell density changes and eccentricity in a layered network.(Frontiers Media SA, 2022)We establish a simple mechanism by which radially oriented simple cells can emerge in the primary visual cortex. In 1986, R. Linsker. proposed a means by which radially symmetric, spatial opponent cells can evolve, driven entirely by noise, from structure in the initial synaptic connectivity distribution. We provide an analytical derivation of Linsker's results, and further show that radial eigenfunctions can be expressed as a weighted sum of degenerate Cartesian eigenfunctions, and vice-versa. These results are extended to allow for radially dependent cell density, from which we show that, despite a circularly symmetric synaptic connectivity distribution, radially biased orientation selectivity emerges in the third layer when cell density in the first layer, or equivalently, synaptic radius, changes with eccentricity; i.e., distance to the center of the lamina. This provides a potential mechanism for the emergence of radial orientation in the primary visual cortex before eye opening and the onset of structured visual input after birth.
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ItemNo Preview AvailableAmbient air pollution and epileptic seizures: A panel study in Australia(WILEY, 2022-07)OBJECTIVE: Emerging evidence has shown that ambient air pollution affects brain health, but little is known about its effect on epileptic seizures. This work aimed to assess the association between daily exposure to ambient air pollution and the risk of epileptic seizures. METHODS: This study used epileptic seizure data from two independent data sources (NeuroVista and Seer App seizure diary). In the NeuroVista data set, 3273 seizures were recorded using intracranial electroencephalography (iEEG) from 15 participants with refractory focal epilepsy in Australia in 2010-2012. In the seizure diary data set, 3419 self-reported seizures were collected through a mobile application from 34 participants with epilepsy in Australia in 2018-2021. Daily average concentrations of carbon monoxide (CO), nitrogen dioxide (NO2 ), ozone (O3 ), particulate matter ≤10 μm in diameter (PM10 ), and sulfur dioxide (SO2 ) were retrieved from the Environment Protection Authority (EPA) based on participants' postcodes. A patient-time-stratified case-crossover design with the conditional Poisson regression model was used to determine the associations between air pollutants and epileptic seizures. RESULTS: A significant association between CO concentrations and epileptic seizure risks was observed, with an increased seizure risk of 4% (relative risk [RR]: 1.04, 95% confidence interval [CI]: 1.01-1.07) for an interquartile range (IQR) increase of CO concentrations (0.13 parts per million), whereas no significant associations were found for the other four air pollutants in the whole study population. Female participants had a significantly increased risk of seizures when exposed to elevated CO and NO2 , with RRs of 1.05 (95% CI: 1.01-1.08) and 1.09 (95% CI: 1.01-1.16), respectively. In addition, a significant association was observed between CO and the risk of subclinical seizures (RR: 1.20, 95% CI: 1.12-1.28). SIGNIFICANCE: Daily exposure to elevated CO concentrations may be associated with an increased risk of epileptic seizures, especially for subclinical seizures.
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ItemNo Preview AvailableNon-Invasive Measurement of Intracranial Pressure Through Application of Venous Ophthalmodynamometry.(IEEE, 2021-11)Non-invasive intracranial pressure (ICP) monitoring is possible using venous ophthalmodynamometry to observe a pulsation in retinal blood vessels when intraocular pressure (IOP) exceeds ICP. Here, we identify features in the eye - optic disc and retinal blood vessel locations - and identify pulsation in large retinal blood vessels. The relationship between force and the magnitude of pulsation is used to estimate ICP when force is applied to the eye to gradually increase IOP over time. This approach yields 77% accuracy in automatically observing vessel pulsation.Clinical Relevance - Non-invasive ICP monitoring is desirable to improve patient outcome by reducing potential trauma and complications associated with invasive assessment with intracranial sensors or lumbar puncture.
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ItemWhite matter tract conductivity is resistant to wide variations in paranodal structure and myelin thickness accompanying the loss of Tyro3: an experimental and simulated analysis(SPRINGER HEIDELBERG, 2022-07)Myelination within the central nervous system (CNS) is crucial for the conduction of action potentials by neurons. Variation in compact myelin morphology and the structure of the paranode are hypothesised to have significant impact on the speed of action potentials. There are, however, limited experimental data investigating the impact of changes in myelin structure upon conductivity in the central nervous system. We have used a genetic model in which myelin thickness is reduced to investigate the effect of myelin alterations upon action potential velocity. A detailed examination of the myelin ultrastructure of mice in which the receptor tyrosine kinase Tyro3 has been deleted showed that, in addition to thinner myelin, these mice have significantly disrupted paranodes. Despite these alterations to myelin and paranodal structure, we did not identify a reduction in conductivity in either the corpus callosum or the optic nerve. Exploration of these results using a mathematical model of neuronal conductivity predicts that the absence of Tyro3 would lead to reduced conductivity in single fibres, but would not affect the compound action potential of multiple myelinated neurons as seen in neuronal tracts. Our data highlight the importance of experimental assessment of conductivity and suggests that simple assessment of structural changes to myelin is a poor predictor of neural functional outcomes.
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ItemDetermination of the electrical impedance of neural tissue from its microscopic cellular constituents(IOP Publishing, 2020-02-01)The electrical properties of neural tissue are important in a range of different applications in biomedical engineering and basic science. These properties are characterized by the electrical admittivity of the tissue, which is the inverse of the specific tissue impedance. Objective. Here we derived analytical expressions for the admittivity of various models of neural tissue from the underlying electrical and morphological properties of the constituent cells. Approach. Three models are considered: parallel bundles of fibers, fibers contained in stacked laminae and fibers crossing each other randomly in all three-dimensional directions. Main results. An important and novel aspect that emerges from considering the underlying cellular composition of the tissue is that the resulting admittivity has both spatial and temporal frequency dependence, a property not shared with conventional conductivity-based descriptions. The frequency dependence of the admittivity results in non-trivial spatiotemporal filtering of electrical signals in the tissue models. These effects are illustrated by considering the example of pulsatile stimulation with a point source electrode. It is shown how changing temporal parameters of a current pulse, such as pulse duration, alters the spatial profile of the extracellular potential. In a second example, it is shown how the degree of electrical anisotropy can change as a function of the distance from the electrode, despite the underlying structurally homogeneity of the tissue. These effects are discussed in terms of different current pathways through the intra- and extra-cellular spaces, and how these relate to near- and far-field limits for the admittivity (which reduce to descriptions in terms of a simple conductivity). Significance. The results highlight the complexity of the electrical properties of neural tissue and provide mathematical methods to model this complexity.
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ItemState transitions through inhibitory interneurons in a cortical network model(PUBLIC LIBRARY SCIENCE, 2021-10)Inhibitory interneurons shape the spiking characteristics and computational properties of cortical networks. Interneuron subtypes can precisely regulate cortical function but the roles of interneuron subtypes for promoting different regimes of cortical activity remains unclear. Therefore, we investigated the impact of fast spiking and non-fast spiking interneuron subtypes on cortical activity using a network model with connectivity and synaptic properties constrained by experimental data. We found that network properties were more sensitive to modulation of the fast spiking population, with reductions of fast spiking excitability generating strong spike correlations and network oscillations. Paradoxically, reduced fast spiking excitability produced a reduction of global excitation-inhibition balance and features of an inhibition stabilised network, in which firing rates were driven by the activity of excitatory neurons within the network. Further analysis revealed that the synaptic interactions and biophysical features associated with fast spiking interneurons, in particular their rapid intrinsic response properties and short synaptic latency, enabled this state transition by enhancing gain within the excitatory population. Therefore, fast spiking interneurons may be uniquely positioned to control the strength of recurrent excitatory connectivity and the transition to an inhibition stabilised regime. Overall, our results suggest that interneuron subtypes can exert selective control over excitatory gain allowing for differential modulation of global network state.