Browsing by Author "Burkitt, Anthony"

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    Broadband Onset Inhibition Can Suppress Spectral Splatter in the Auditory Brainstem
    (2015-05-15) Spencer, Martin; Nayagam, David; Clarey, Janine; Paolini, Antonio; Meffin, Hamish; Burkitt, Anthony; Grayden, David
    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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    Changes in ganglion cells during retinal degeneration
    (IOP Publishing, 2016-04) Saha, Susmita; Greferath, Ursula; Vessey, Kirstan; Grayden, David; Burkitt, Anthony; Fletcher, Erica
    Inherited retinal degeneration such as retinitis pigmentosa (RP) is associated with photoreceptor loss and concomitant morphological and functional changes in the inner retina. It is not known whether these changes are associated with changes in the density and distribution of synaptic inputs to retinal ganglion cells (RGCs). We quantified changes in ganglion cell density in rd1 and age-matched C57BL/6J-(wildtype, WT) mice using the immunocytochemical marker, RBPMS. Our data revealed that following complete loss of photoreceptors, (approximately 3months of age), there was a reduction in ganglion cell density in the peripheral retina. We next examined changes in synaptic inputs to A type ganglion cells by performing double labeling experiments in mice with the ganglion cell reporter lines, rd1-Thy1 and age-matched wildtype-Thy1. Ribbon synapses were identified by co-labelling with CtBP2 (RIBEYE) and conventional synapses with the clustering molecule, gephyrin. ON RGCs showed a significant reduction in RIBEYE-immunoreactive synapse density while OFF RGCs showed a significant reduction in the gephyrin-immmunoreactive synapse density. Distribution patterns of both synaptic markers across the dendritic trees of RGCs were unchanged. The change in synaptic inputs to RGCs was associated with a reduction in the number of immunolabeled rod bipolar and ON cone bipolar cells. These results suggest that functional changes reported in ganglion cells during retinal degeneration could be attributed to loss of synaptic inputs.
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    Coexistence of reward and unsupervised learning during the operant conditioning of neural firing rates
    (PLoS ONE, 2014-01-27) Kerr, Robert; Grayden, David; Thomas, Doreen; Gilson, Matthieu; Burkitt, Anthony
    A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditioning, are performed by the brain. Typical and well studied examples of operant conditioning, in which the firing rates of individual cortical neurons in monkeys are increased using rewards, provide an opportunity for insight into this. Studies of reward-modulated spike-timing-dependent plasticity (RSTDP), and of other models such as R-max, have reproduced this learning behavior, but they have assumed that no unsupervised learning is present (i.e., no learning occurs without, or independent of, rewards). We show that these models cannot elicit firing rate reinforcement while exhibiting both reward learning and ongoing, stable unsupervised learning. To fix this issue, we propose a new RSTDP model of synaptic plasticity based upon the observed effects that dopamine has on long-term potentiation and depression (LTP and LTD). We show, both analytically and through simulations, that our new model can exhibit unsupervised learning and lead to firing rate reinforcement. This requires that the strengthening of LTP by the reward signal is greater than the strengthening of LTD and that the reinforced neuron exhibits irregular firing. We show the robustness of our findings to spike-timing correlations, to the synaptic weight dependence that is assumed, and to changes in the mean reward. We also consider our model in the differential reinforcement of two nearby neurons. Our model aligns more strongly with experimental studies than previous models and makes testable predictions for future experiments.
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    Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs
    (PLOS, 2013-02-07) Kerr, Robert; Burkitt, Anthony; Thomas, Doreen; Gilson, Matthieu; Grayden, David
    Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.
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    Goal-directed control with cortical units that are gated by both top-down feedback and oscillatory coherence
    (2014-08) Kerr, Robert; Grayden, David; Thomas, Doreen; Gilson, Matthieu; Burkitt, Anthony
    The brain is able to flexibly select behaviors that adapt to both its environment and its present goals. This cognitive control is understood to occur within the hierarchy of the cortex and relies strongly on the prefrontal and premotor cortices, which sit at the top of this hierarchy. Pyramidal neurons, the principal neurons in the cortex, have been observed to exhibit much stronger responses when they receive inputs at their soma/basal dendrites that are coincident with inputs at their apical dendrites. This corresponds to inputs from both lower-order regions (feedforward) and higher-order regions (feedback), respectively. In addition to this, coherence between oscillations, such as gamma oscillations, in different neuronal groups has been proposed to modulate and route communication in the brain. In this paper, we develop a simple, but novel, neural mass model in which cortical units (or ensembles) exhibit gamma oscillations when they receive coherent oscillatory inputs from both feedforward and feedback connections. By forming these units into circuits that can perform logic operations, we identify the different ways in which operations can be initiated and manipulated by top-down feedback. We demonstrate that more sophisticated and flexible top-down control is possible when the gain of units is modulated by not only top-down feedback but by coherence between the activities of the oscillating units. With these types of units, it is possible to not only add units to, or remove units from, a higher-level unit's logic operation using top-down feedback, but also to modify the type of role that a unit plays in the operation. Finally, we explore how different network properties affect top-down control and processing in large networks. Based on this, we make predictions about the likely connectivities between certain brain regions that have been experimentally observed to be involved in goal-directed behavior and top-down attention.
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    Improved visual performance in letter perception through edge orientation encoding in a retinal prosthesis simulation
    (IOP Publishing, 2014-10) Kiral-Kornek, Isabell; O'Sullivan-Green, Elma; Savage, Craig; McCarthy, Chris; Grayden, David; Burkitt, Anthony
    Objective. Stimulation strategies for retinal prostheses predominately seek to directly encode image brightness values rather than edge orientations. Recent work suggests that the generation of oriented elliptical phosphenes may be possible by controlling interactions between neighboring electrodes. Based on this, we propose a novel stimulation strategy for prosthetic vision that extracts edge orientation information from the intensity image and encodes it as oriented elliptical phosphenes. We test the hypothesis that encoding edge orientation via oriented elliptical phosphenes leads to better alphabetic letter recognition than standard intensity-based encoding. Approach. We conduct a psychophysical study with simulated phosphene vision with 12 normal-sighted volunteers. The two stimulation strategies were compared with variations of letter size, electrode drop-out and spatial offsets of phosphenes. Main results. Mean letter recognition accuracy was significantly better with the new proposed stimulation strategy (65%) compared to direct grayscale encoding (47%). All examined parameters-stimulus size, phosphene dropout, and location shift-were found to influence the performance, with significant two-way interactions between phosphene dropout and stimulus size as well as between phosphene dropout and phosphene location shift. The analysis delivers a model of perception performance. Significance. Displaying available directional information to an implant user may improve their visual performance. We present a model for designing a stimulation strategy under the constraints of existing retinal prostheses that can be exploited by retinal implant developers to strategically employ oriented phosphenes.
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    In Vivo Feasibility of Epiretinal Stimulation Using Ultrananocrystalline Diamond 1 Electrodes
    (IOP Publishing, 2020-07) Shivdasani, Mohit; Evans, Mihailo; Burns, Owen; Yeoh, Jonathon; Allen, Penelope; Nayagam, David; Villalobos, Joel; Abbott, Carla; Luu, Chi; Opie, Nicholas; Sabu, Anu; Saunders, Alexia; McPhedran, Michelle; Cardamone, Lisa; McGowan, Ceara; Maxim, Vanessa; Williams, Richard; Fox, Kate; Cicione, Rosemary; Garrett, David; Ahnood, Arman; Ganesan, Kumaravelu; Meffin, Hamish; Burkitt, Anthony; Prawer, Steven; Williams, Chris; Shepherd, Robert
    PURPOSE: Due to their increased proximity to retinal ganglion cells (RGCs), epiretinal visual prostheses present the opportunity for eliciting phosphenes with low thresholds through direct RGC activation. This study characterised the in vivo performance of a novel prototype monolithic epiretinal prosthesis, containing Nitrogen incorporated ultrananocrystalline (N-UNCD) diamond electrodes. METHODS: A prototype implant containing up to twenty-five 120×120 µm N-UNCD electrodes was implanted into 16 anaesthetised cats and attached to the retina either using a single tack or via magnetic coupling with a suprachoroidally placed magnet. Multiunit responses to retinal stimulation using charge-balanced biphasic current pulses were recorded acutely in the visual cortex using a multichannel planar array. Several stimulus parameters were varied including; the stimulating electrode, stimulus polarity, phase duration, return configuration and the number of electrodes stimulated simultaneously. RESULTS: The rigid nature of the device and its form factor necessitated complex surgical procedures. Surgeries were considered successful in 10/16 animals and cortical responses to single electrode stimulation obtained in 8 animals. Clinical imaging and histological outcomes showed severe retinal trauma caused by the device in-situ in many instances. Cortical measures were found to significantly depend on the surgical outcomes of individual experiments, phase duration, return configuration and the number of electrodes stimulated simultaneously, but not stimulus polarity. Cortical thresholds were also found to increase over time within an experiment. CONCLUSIONS: The study successfully demonstrated that an epiretinal prosthesis containing diamond electrodes could produce cortical activity with high precision, albeit only in a small number of cases. Both surgical approaches were highly challenging in terms of reliable and consistent attachment to and stabilisation against the retina, and often resulted in severe retinal trauma. There are key challenges (device form factor and attachment technique) to be resolved for such a device to progress towards clinical application, as current surgical techniques are unable to address these issues.
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    An integrated model of pitch perception incorporating place and temporal pitch codes with application to cochlear implant research
    (Elsevier Ltd., 2016-11) Saeedi, Nafise Erfanian; Blamey, Peter; Burkitt, Anthony; Grayden, David
    Although the neural mechanisms underlying pitch perception are not yet fully understood, there is general agreement that place and temporal representations of pitch are both used by the auditory system. This paper describes a neural network model of pitch perception that integrates both codes of pitch and explores the contributions of, and the interactions between, the two representations in simulated pitch ranking trials in normal and cochlear implant hearing. The model can replicate various psychophysical observations including the perception of the missing fundamental pitch and sensitivity to pitch interval sizes. As a case study, the model was used to investigate the efficiency of pitch perception cues in a novel sound processing scheme, Stimulation based on Auditory Modelling (SAM), that aims to improve pitch perception in cochlear implant hearing. Results showed that enhancement of the pitch perception cues would lead to better pitch ranking scores in the integrated model only if the place and temporal pitch cues were consistent.
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    Interplay of Intrinsic and Synaptic Conductances in the Generation of High-Frequency Oscillations in Interneuronal Networks with Irregular Spiking
    (2014-05-03) Baroni, Fabiano; Burkitt, Anthony; Grayden, David
    High-frequency oscillations (above 30 Hz) have been observed in sensory and higher-order brain areas, and are believed to constitute a general hallmark of functional neuronal activation. Fast inhibition in interneuronal networks has been suggested as a general mechanism for the generation of high-frequency oscillations. Certain classes of interneurons exhibit subthreshold oscillations, but the effect of this intrinsic neuronal property on the population rhythm is not completely understood. We study the influence of intrinsic damped subthreshold oscillations in the emergence of collective high-frequency oscillations, and elucidate the dynamical mechanisms that underlie this phenomenon. We simulate neuronal networks composed of either Integrate-and-Fire (IF) or Generalized Integrate-and-Fire (GIF) neurons. The IF model displays purely passive subthreshold dynamics, while the GIF model exhibits subthreshold damped oscillations. Individual neurons receive inhibitory synaptic currents mediated by spiking activity in their neighbors as well as noisy synaptic bombardment, and fire irregularly at a lower rate than population frequency. We identify three factors that affect the influence of single-neuron properties on synchronization mediated by inhibition: i) the firing rate response to the noisy background input, ii) the membrane potential distribution, and iii) the shape of Inhibitory Post-Synaptic Potentials (IPSPs). For hyperpolarizing inhibition, the GIF IPSP profile (factor iii)) exhibits post-inhibitory rebound, which induces a coherent spike-mediated depolarization across cells that greatly facilitates synchronous oscillations. This effect dominates the network dynamics, hence GIF networks display stronger oscillations than IF networks. However, the restorative current in the GIF neuron lowers firing rates and narrows the membrane potential distribution (factors i) and ii), respectively), which tend to decrease synchrony. If inhibition is shunting instead of hyperpolarizing, post-inhibitory rebound is not elicited and factors i) and ii) dominate, yielding lower synchrony in GIF networks than in IF networks.
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    An investigation of dendritic delay in octopus cells of the mammalian cochlear nucleus
    (Frontiers in Computational Neuroscience, 2012-10-22) Spencer, Martin; Grayden, David; Bruce, Ian; Meffin, Hamish; Burkitt, Anthony
    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 question 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 models dendritic delay compensated for the cochlear travelling wave delay across the ANFs. The range of sound frequency input from ANFs was also investigated. The results suggested that input octopus cells is dominated by high frequency ANfs.
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    Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks
    (PLOS Computational Biology, 2016-04) Saeedi, Nafise; Blamey, Peter; Burkitt, Anthony; Grayden, David
    Pitch perception is important for understanding speech prosody, music perception, recognizing tones in tonal languages, and perceiving speech in noisy environments. The two principal pitch perception theories consider the place of maximum neural excitation along the auditory nerve and the temporal pattern of the auditory neurons’ action potentials (spikes) as pitch cues. This paper describes a biophysical mechanism by which fine-structure temporal information can be extracted from the spikes generated at the auditory periphery. Deriving meaningful pitch-related information from spike times requires neural structures specialized in capturing synchronous or correlated activity from amongst neural events. The emergence of such pitch-processing neural mechanisms is described through a computational model of auditory processing. Simulation results show that a correlation-based, unsupervised, spike-based form of Hebbian learning can explain the development of neural structures required for recognizing the pitch of simple and complex tones, with or without the fundamental frequency. The temporal code is robust to variations in the spectral shape of the signal and thus can explain the phenomenon of pitch constancy.
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    Minimally invasive endovascular stent-electrode array for high-fidelity, chronic recordings of cortical neural activity
    (Nature Publishing Group, 2016-02-08) Oxley, Thomas; Opie, Nicholas; John, Sam; Rindl, Gil; Ronayne, Stephen; Wheeler, Tracey; Judy, Jack; McDonald, Alan; Dornom, Anthony; Lovell, Timothy; Steward, Christopher; Garrett, David; Moffat, Bradford; Lui, Elaine; Yassi, Nawaf; Campbell, Bruce; Wong, Yan; Fox, Kate; Nurse, Ewan; Bennett, Iwan; Bauquier, Sebastien; Lyanage, Kishan; van de Nagel, Nicole; Perucca, Piero; Ahnood, Arman; Gill, Katherine; Yan, Bernard; Churilov, Leonid; French, Christopher; Desmond, Patricia; Horne, Malcolm; Kiers, Lynette; Prawer, Steven; Davis, Stephen; Burkitt, Anthony; Mitchell, Peter; Grayden, David; May, Clive; O'Brien, Terence
    High-fidelity intracranial electrode arrays for recording and stimulating brain activity have facilitated major advances in the treatment of neurological conditions over the past decade. Traditional arrays require direct implantation into the brain via open craniotomy, which can lead to inflammatory tissue responses, necessitating development of minimally invasive approaches that avoid brain trauma. Here we demonstrate the feasibility of chronically recording brain activity from within a vein using a passive stent-electrode recording array (stentrode). We achieved implantation into a superficial cortical vein overlying the motor cortex via catheter angiography and demonstrate neural recordings in freely moving sheep for up to 190 d. Spectral content and bandwidth of vascular electrocorticography were comparable to those of recordings from epidural surface arrays. Venous internal lumen patency was maintained for the duration of implantation. Stentrodes may have wide ranging applications as a neural interface for treatment of a range of neurological conditions.
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    Modelling extracellular electrical stimulation: part 3. Derivation and interpretation of neural tissue equations
    (IOP Publishing, 2014-11) Meffin, Hamish; Tahayori, Bahman; Sergeev, Evgeni; Mareels, Iven; Grayden, David; Burkitt, Anthony
    OBJECTIVE: A common approach in modelling extracellular electrical stimulation is to represent neural tissue by a volume conductor when calculating the activating function as the driving term in a cable equation for the membrane potential. This approach ignores the cellular composition of tissue, including the neurites and their combined effect on the extracellular potential. This has a number of undesirable consequences. First, the two natural and equally valid choices of boundary conditions for the cable equation (i.e. using either voltage or current) lead to two mutually inconsistent predictions of the membrane potential. Second, the spatio-temporal distribution of the extracellular potential can be strongly affected by the combined cellular composition of the tissue. In this paper, we develop a mean field volume conductor theory to overcome these shortcomings of available models. APPROACH: This method connects the microscopic properties of the constituent fibres to the macroscopic electrical properties of the tissue by introducing an admittivity kernel for the neural tissue that is non-local, non-instantaneous and anisotropic. This generalizes the usual tissue conductivity. A class of bidomain models that is mathematically equivalent to this class of self-consistent volume conductor models is also presented. The bidomain models are computationally convenient for simulating the activation map of neural tissue using numerical methods such as finite element analysis. MAIN RESULTS: The theory is first developed for tissue composed of identical, parallel fibres and then extended to general neural tissues composed of mixtures of neurites with different and arbitrary orientations, arrangements and properties. Equations describing the extracellular and membrane potential for the longitudinal and transverse modes of stimulation are derived. SIGNIFICANCE: The theory complements our earlier work, which developed extensions to cable theory for the micro-scale equations of neural stimulation that apply to individual fibres. The modelling framework provides a number of advantages over other approaches currently adopted in the literature and, therefore, can be used to accurately estimate the membrane potential generated by extracellular electrical stimulation.
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    Modelling extracellular electrical stimulation: part 4. Effect of the cellular composition of neural tissue on its spatio-temporal filtering properties
    (IOP Publishing, 2014-11) Tahayori, Bahman; Meffin, Hamish; Sergeev, Evgeni; Mareels, Iven; Burkitt, Anthony; Grayden, David
    OBJECTIVE: The objective of this paper is to present a concrete application of the cellular composite model for calculating the membrane potential, described in an accompanying paper. APPROACH: A composite model that is used to determine the membrane potential for both longitudinal and transverse modes of stimulation is demonstrated. MAIN RESULTS: Two extreme limits of the model, near-field and far-field for an electrode close to or distant from a neuron, respectively, are derived in this paper. Results for typical neural tissue are compared using the composite, near-field and far-field models as well as the standard isotropic volume conductor model. The self-consistency of the composite model, its spatial profile response and the extracellular potential time behaviour are presented. The magnitudes of the longitudinal and transverse components for different values of electrode-neurite separations are compared. SIGNIFICANCE: The unique features of the composite model and its simplified versions can be used to accurately estimate the spatio-temporal response of neural tissue to extracellular electrical stimulation.
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    Neural Responses to Multielectrode Stimulation of Healthy and Degenerate Retina
    (IOVS, 2017-07) Halupka, Kerry; Abbott, Carla; Wong, Yan; Cloherty, Shaun; Grayden, David; Burkitt, Anthony; Sergeev, Evgeni; Brandli, Alice; Allen, Penelope; Meffin, Hamish; Shivdasani, Mohit
    Purpose: Simultaneous stimulation of multiple retinal electrodes in normally sighted animals shows promise in improving the resolution of retinal prostheses. However, the effects of simultaneous stimulation on degenerate retinae remain unknown. Therefore, we investigated the characteristics of cortical responses to multielectrode stimulation of the degenerate retina. Methods: Four adult cats were bilaterally implanted with retinal electrode arrays in the suprachoroidal space after unilateral adenosine triphosphate (ATP)-induced retinal photoreceptor degeneration. Functional and structural changes were characterized by using electroretinogram a-wave amplitude and optical coherence tomography. Multiunit activity was recorded from both hemispheres of the visual cortex. Responses to single- and multielectrode stimulation of the ATP-injected and fellow control eyes were characterized and compared. Results: The retinae of ATP-injected eyes displayed structural and functional changes consistent with mid- to late-stage photoreceptor degeneration and remodeling. Responses to multielectrode stimulation of the ATP-injected eyes exhibited shortened latencies, lower saturated spike counts, and higher thresholds, compared to stimulation of the fellow control eyes. Electrical receptive field sizes were significantly larger in the ATP-injected eye than in the control eye, and positively correlated with the extent of degeneration. Conclusions: Significant differences exist between cortical responses to stimulation of healthy and degenerate retinae. Our results highlight the importance of using a retinal degeneration model when evaluating the efficacy of novel stimulation paradigms.
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    Prediction of cortical responses to simultaneous electrical stimulation of the retina
    (IOP Publishing, 2016-11) Halupka, Kerry; Shivdasani, Mohit; Cloherty, Shaun; Grayden, David; Wong, Yan; Burkitt, Anthony; Meffin, Hamish
    OBJECTIVE: Simultaneous electrical stimulation of multiple electrodes has shown promise in diversifying the responses that can be elicited by retinal prostheses compared to interleaved single electrode stimulation. However, the effects of interactions between electrodes are not well understood and clinical trials with simultaneous stimulation have produced inconsistent results. We investigated the effects of multiple electrode stimulation of the retina by developing a model of cortical responses to retinal stimulation. APPROACH: Electrical stimuli consisting of temporally sparse, biphasic current pulses, with amplitudes sampled from a bi-dimensional Gaussian distribution, were simultaneously delivered to the retina across a 42-channel electrode array implanted in the suprachoroidal space of anesthetized cats. Visual cortex activity was recorded using penetrating microelectrode arrays. These data were used to identify a linear-nonlinear model of cortical responses to retinal stimulation. The ability of the model to generalize was tested by predicting responses to non-white patterned stimuli. MAIN RESULTS: The model accurately predicted two cortical activity measures: multi-unit neural responses and evoked potential responses to white noise stimuli. The model also provides information about electrical receptive fields, including the relative effects of each stimulating electrode on every recording site. SIGNIFICANCE: We have demonstrated a simple model that accurately describes cortical responses to simultaneous stimulation of a suprachoroidal retinal prosthesis. Overall, our results demonstrate that cortical responses to simultaneous multi-electrode stimulation of the retina are repeatable and predictable, and that interactions between electrodes during simultaneous stimulation are predominantly linear. The model shows promise for determining optimal stimulation paradigms for exploiting interactions between electrodes to shape neural activity, thereby improving outcomes for patients with retinal prostheses.
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    Spectral distribution of local field potential responses to electrical stimulation of the retina
    (IOP Publishing, 2016-03) Wong, Yan; Halupka, Kerry; Kameneva, Tatiana; Cloherty, Shaun; Grayden, David; Burkitt, Anthony; Meffin, Hamish; Shivdasani, Mohit
    OBJECTIVE: Different frequency bands of the local field potential (LFP) have been shown to reflect neuronal activity occurring at varying cortical scales. As such, recordings of the LFP may offer a novel way to test the efficacy of neural prostheses and allow improvement of stimulation strategies via neural feedback. Here we use LFP measurements from visual cortex to characterize neural responses to electrical stimulation of the retina. We aim to show that the LFP is a viable signal that contains sufficient information to optimize the performance of sensory neural prostheses. APPROACH: Clinically relevant electrode arrays were implanted in the suprachoroidal space of one eye in four felines. LFPs were simultaneously recorded in response to stimulation of individual electrodes using penetrating microelectrode arrays from the visual cortex. The frequency response of each electrode was extracted using multi-taper spectral analysis and the uniqueness of the responses was determined via a linear decoder. MAIN RESULTS: We found that cortical LFPs are reliably modulated by electrical stimulation of the retina and that the responses are spatially localized. We further characterized the spectral distribution of responses, with maximum information being contained in the low and high gamma bands. Finally, we found that LFP responses are unique to a large range of stimulus parameters ( approximately 40) with a maximum conveyable information rate of 6.1 bits. SIGNIFICANCE: These results show that the LFP can be used to validate responses to electrical stimulation of the retina and we provide the first steps towards using these responses to provide more efficacious stimulation strategies.
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    Spike history neural response model
    (Springer US, 2015-06) Kameneva, Tatiana; Abramain, Miganoosh; Zarelli, Daniele; Nesic, Dragan; Burkitt, Anthony; Meffin, Hamish; Grayden, David
    There is a potential for improved efficacy of neural stimulation if stimulation levels can be modified dynamically based on the responses of neural tissue in real time. A neural model is developed that describes the response of neurons to electrical stimulation and that is suitable for feedback control neuroprosthetic stimulation. Experimental data from NZ white rabbit retinae is used with a data-driven technique to model neural dynamics. The linear-nonlinear approach is adapted to incorporate spike history and to predict the neural response of ganglion cells to electrical stimulation. To validate the fitness of the model, the penalty term is calculated based on the time difference between each simulated spike and the closest spike in time in the experimentally recorded train. The proposed model is able to robustly predict experimentally observed spike trains.