Biomedical Engineering - Research Publications
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ItemAnalysis of extracellular spike waveforms and associated receptive fields of neurons in cat primary visual cortex(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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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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ItemNeural activity shaping utilizing a partitioned target pattern(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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ItemLearning receptive field properties of complex cells in V1(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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ItemHigh Fidelity Bidirectional Neural Interfacing with Carbon Fiber Microelectrodes Coated with Boron-Doped Carbon Nanowalls: An Acute Study(WILEY-V C H VERLAG GMBH, 2020-12)Abstract Implantable electrodes that can communicate with a small, selective group of neurons via both neural stimulation and recording are critical for the development of advanced neuroprosthetic devices. Microfiber electrodes with neuron‐scale cross‐sections have the potential to improve the spatial resolution for both stimulation and recording, while minimizing the chronic inflammation response after implantation. In this work, glass insulated microfiber electrodes are fabricated by coating carbon fibers with boron‐doped carbon nanowalls. The coating significantly improves the electrochemical properties of carbon fibers, leading to a charge injection capacity of 7.82 ± 0.35 mC cm−2, while retaining good flexibility, stability and biocompatibility. When used for neural interfacing, the coated microelectrodes successfully elicit localized stimulation responses in explanted retina, and are also able to detect signals from single neurons, in vivo with a signal‐to‐noise ratio as high as 6.7 in an acute study. This is the first report of using carbon nanowall coated carbon fibers for neural interfacing.
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ItemMechanisms of Feature Selectivity and Invariance in Primary Visual Cortex.(Oxford University Press (OUP), 2020-09)Visual object identification requires both selectivity for specific visual features that are important to the object's identity and invariance to feature manipulations. For example, a hand can be shifted in position, rotated, or contracted but still be recognized as a hand. How are the competing requirements of selectivity and invariance built into the early stages of visual processing? Typically, cells in the primary visual cortex are classified as either simple or complex. They both show selectivity for edge-orientation but complex cells develop invariance to edge position within the receptive field (spatial phase). Using a data-driven model that extracts the spatial structures and nonlinearities associated with neuronal computation, we quantitatively describe the balance between selectivity and invariance in complex cells. Phase invariance is frequently partial, while invariance to orientation and spatial frequency are more extensive than expected. The invariance arises due to two independent factors: (1) the structure and number of filters and (2) the form of nonlinearities that act upon the filter outputs. Both vary more than previously considered, so primary visual cortex forms an elaborate set of generic feature sensitivities, providing the foundation for more sophisticated object processing.
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ItemHybrid diamond/ carbon fiber microelectrodes enable multimodal electrical/chemical neural interfacing(Elsevier, 2020-02-01)Implantable medical devices are now in regular use to treat or ameliorate medical conditions, including movement disorders, chronic pain, cardiac arrhythmias, and hearing or vision loss. Aside from offering alternatives to pharmaceuticals, one major advantage of device therapy is the potential to monitor treatment efficacy, disease progression, and perhaps begin to uncover elusive mechanisms of diseases pathology. In an ideal system, neural stimulation, neural recording, and electrochemical sensing would be conducted by the same electrode in the same anatomical region. Carbon fiber (CF) microelectrodes are the appropriate size to achieve this goal and have shown excellent performance, in vivo. Their electrochemical properties, however, are not suitable for neural stimulation and electrochemical sensing. Here, we present a method to deposit high surface area conducting diamond on CF microelectrodes. This unique hybrid microelectrode is capable of recording single-neuron action potentials, delivering effective electrical stimulation pulses, and exhibits excellent electrochemical dopamine detection. Such electrodes are needed for the next generation of miniaturized, closed-loop implants that can self-tune therapies by monitoring both electrophysiological and biochemical biomarkers.
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ItemStimulation Strategies for Improving the Resolution of Retinal Prostheses.(Frontiers Media, 2020-03-26)Electrical stimulation using implantable devices with arrays of stimulating electrodes is an emerging therapy for neurological diseases. The performance of these devices depends greatly on their ability to activate populations of neurons with high spatiotemporal resolution. To study electrical stimulation of populations of neurons, retina serves as a useful model because the neural network is arranged in a planar array that is easy to access. Moreover, retinal prostheses are under development to restore vision by replacing the function of damaged light sensitive photoreceptors, which makes retinal research directly relevant for curing blindness. Here we provide a progress review on stimulation strategies developed in recent years to improve the resolution of electrical stimulation in retinal prostheses. We focus on studies performed with explanted retinas, in which electrophysiological techniques are the most advanced. We summarize achievements in improving the spatial and temporal resolution of electrical stimulation of the retina and methods to selectively stimulate neurons with different visual functions. Future directions for retinal prostheses development are also discussed, which could provide insights for other types of neuromodulatory devices in which high-resolution electrical stimulation is required.