The design and manufacture of 3D-printed adjuncts for powered air-purifying respirators.

Spurred in part by literature published in the immediate aftermath of the severe acute respiratory syndrome epidemic in 2003, powered air-purifying respirators have seen increased use worldwide during the COVID-19 pandemic. Whereas these devices provide excellent protection of the user, there is an added element of risk during doffing and cleaning of the device. An additional layer of barrier protection, in the form of a polypropylene gown, to be worn over the hood and motor belt, can be used to minimise this risk. However, the device entrains air perpendicular to the lie of the gown, resulting in the impermeable material being sucked into the air intake, and partial occlusion of flow. In this report, we describe a clinical-academic partnership whereby a bespoke filter guard was designed to disrupt airflow and prevent gown entrainment, thereby enabling full barrier protection of both the device and user. This intervention was simple, cheap, scalable and able to be mass produced.

Cortical Brain Stimulation with Endovascular Electrodes.

Electrical stimulation of neural tissue and recording of neural activity are the bases of emerging prostheses and treatments for spinal cord injury, stroke, sensory deficits, and drug-resistant neurological disorders. Safety and efficacy are key aspects for the clinical acceptance of therapeutic neural stimulators. The cortical vasculature has been shown to be a safe site for implantation of electrodes for chronically recording neural activity, requiring no craniotomy to access high-bandwidth, intracranial EEG. This work presents the first characterization of endovascular cortical stimulation measured using cortical subdural surface recordings. Visual stimulation was used to verify electrode viability and cortical activation was compared with electrically evoked activity. Due to direct activation of the neural tissue, the latency of responses to electrical stimulation was shorter than for that of visual stimulation. We also found that the center of neural activation was different for visual and electrical stimulation indicating an ability of the stentrode to provide localized activation of neural tissue.

Ring and peg electrodes for minimally-Invasive and long-term sub-scalp EEG recordings.

OBJECTIVE: Minimally-invasive approaches are needed for long-term reliable Electroencephalography (EEG) recordings to assist with epilepsy diagnosis, investigation and more naturalistic monitoring. This study compared three methods for long-term implantation of sub-scalp EEG electrodes. METHODS: Three types of electrodes (disk, ring, and peg) were fabricated from biocompatible materials and implanted under the scalp in five ambulatory ewes for 3months. Disk electrodes were inserted into sub-pericranial pockets. Ring electrodes were tunneled under the scalp. Peg electrodes were inserted into the skull, close to the dura. EEG was continuously monitored wirelessly. High resolution CT imaging, histopathology, and impedance measurements were used to assess the status of the electrodes at the end of the study. RESULTS: EEG amplitude was larger in the peg compared with the disk and ring electrodes (p<0.05). Similarly, chewing artifacts were lower in the peg electrodes (p<0.05). Electrode impedance increased after long-term implantation particularly for those within the bone (p<0.01). Micro-CT scans indicated that all electrodes stayed within the sub-scalp layers. All pegs remained within the burr holes as implanted with no evidence of extrusion. Eight of 10 disks partially eroded into the bone by 1.0mm from the surface of the skull. The ring arrays remained within the sub-scalp layers close to implantation site. Histology revealed that the electrodes were encapsulated in a thin fibrous tissue adjacent to the pericranium. Overlying this was a loose connective layer and scalp. Erosion into the bone occurred under the rim of the sub-pericranial disk electrodes. CONCLUSIONS: The results indicate that the peg electrodes provided high quality EEG, mechanical stability, and lower chewing artifact. Whereas, ring electrode arrays tunneled under the scalp enable minimal surgical techniques to be used for implantation and removal.

Retinal ganglion cells: mechanisms underlying depolarization block and differential responses to high frequency electrical stimulation of ON and OFF cells.

OBJECTIVE: ON and OFF retinal ganglion cells (RGCs) are known to have non-monotonic responses to increasing amplitudes of high frequency (2 kHz) biphasic electrical stimulation. That is, an increase in stimulation amplitude causes an increase in the cell's spike rate up to a peak value above which further increases in stimulation amplitude cause the cell to decrease its activity. The peak response for ON and OFF cells occurs at different stimulation amplitudes, which allows differential stimulation of these functional cell types. In this study, we investigate the mechanisms underlying the non-monotonic responses of ON and OFF brisk-transient RGCs and the mechanisms underlying their differential responses. APPROACH: Using in vitro patch-clamp recordings from rat RGCs, together with simulations of single and multiple compartment Hodgkin-Huxley models, we show that the non-monotonic response to increasing amplitudes of stimulation is due to depolarization block, a change in the membrane potential that prevents the cell from generating action potentials. MAIN RESULTS: We show that the onset for depolarization block depends on the amplitude and frequency of stimulation and reveal the biophysical mechanisms that lead to depolarization block during high frequency stimulation. Our results indicate that differences in transmembrane potassium conductance lead to shifts of the stimulus currents that generate peak spike rates, suggesting that the differential responses of ON and OFF cells may be due to differences in the expression of this current type. We also show that the length of the axon's high sodium channel band (SOCB) affects non-monotonic responses and the stimulation amplitude that leads to the peak spike rate, suggesting that the length of the SOCB is shorter in ON cells. SIGNIFICANCE: This may have important implications for stimulation strategies in visual prostheses.

Model-based estimation of intra-cortical connectivity using electrophysiological data.

This paper provides a new method for model-based estimation of intra-cortical connectivity from electrophysiological measurements. A novel closed-form solution for the connectivity function of the Amari neural field equations is derived as a function of electrophysiological observations. The resultant intra-cortical connectivity estimate is driven from experimental data, but constrained by the mesoscopic neurodynamics that are encoded in the computational model. A demonstration is provided to show how the method can be used to image physiological mechanisms that govern cortical dynamics, which are normally hidden in clinical data from epilepsy patients. Accurate estimation performance is demonstrated using synthetic data. Following the computational testing, results from patient data are obtained that indicate a dominant increase in surround inhibition prior to seizure onset that subsides in the cases when the seizures spread.

Spatiotemporal multi-resolution approximation of the Amari type neural field model.

Neural fields are spatially continuous state variables described by integro-differential equations, which are well suited to describe the spatiotemporal evolution of cortical activations on multiple scales. Here we develop a multi-resolution approximation (MRA) framework for the integro-difference equation (IDE) neural field model based on semi-orthogonal cardinal B-spline wavelets. In this way, a flexible framework is created, whereby both macroscopic and microscopic behavior of the system can be represented simultaneously. State and parameter estimation is performed using the expectation maximization (EM) algorithm. A synthetic example is provided to demonstrate the framework.

Optimized single pulse stimulation strategy for retinal implants.

Retinal implants offer prospects of vision restoration for some blind patients by eliciting visual percepts of spots of light called 'phosphenes'. Recently, a mathematical model has been developed that predicts patients' perception of phosphene brightness for current-driven electrical stimulation of the retina. This model is explored for different stimulation parameters on a single electrode, including safety and hardware limitations, to produce phosphenes of specified brightness. We describe a procedure to derive stimulation parameters to account for such constraints, and describe methods to construct optimal stimuli in terms of producing maximal perceived brightness and efficient generation of phosphenes of a given brightness by employing minimal energy. In both cases, it is found that the resulting optimized stimulation waveforms consist of a long stimulation period, and interphase delays between initial and charge-balancing phases.

A fully implantable rodent neural stimulator.

The ability to electrically stimulate neural and other excitable tissues in behaving experimental animals is invaluable for both the development of neural prostheses and basic neurological research. We developed a fully implantable neural stimulator that is able to deliver two channels of intra-cochlear electrical stimulation in the rat. It is powered via a novel omni-directional inductive link and includes an on-board microcontroller with integrated radio link, programmable current sources and switching circuitry to generate charge-balanced biphasic stimulation. We tested the implant in vivo and were able to elicit both neural and behavioural responses. The implants continued to function for up to five months in vivo. While targeted to cochlear stimulation, with appropriate electrode arrays the stimulator is well suited to stimulating other neurons within the peripheral or central nervous systems. Moreover, it includes significant on-board data acquisition and processing capabilities, which could potentially make it a useful platform for telemetry applications, where there is a need to chronically monitor physiological variables in unrestrained animals.

A data-driven framework for neural field modeling.

This paper presents a framework for creating neural field models from electrophysiological data. The Wilson and Cowan or Amari style neural field equations are used to form a parametric model, where the parameters are estimated from data. To illustrate the estimation framework, data is generated using the neural field equations incorporating modeled sensors enabling a comparison between the estimated and true parameters. To facilitate state and parameter estimation, we introduce a method to reduce the continuum neural field model using a basis function decomposition to form a finite-dimensional state-space model. Spatial frequency analysis methods are introduced that systematically specify the basis function configuration required to capture the dominant characteristics of the neural field. The estimation procedure consists of a two-stage iterative algorithm incorporating the unscented Rauch-Tung-Striebel smoother for state estimation and a least squares algorithm for parameter estimation. The results show that it is theoretically possible to reconstruct the neural field and estimate intracortical connectivity structure and synaptic dynamics with the proposed framework.

A fully flexible stimulator using 65 nm CMOS process for 1024-electrode epi-retinal prosthesis.

This paper presents a fully flexible stimulator using 65 nm CMOS process for a 1024-electrode epi-retinal prosthesis. The stimulator can select any number of electrodes at any time and also supports both mono-polar and multi-polar stimulation. Furthermore, the stimulator supports a wide range of stimulus parameters. A novel feature is that the electrode driver operates in an alternately pull-push manner, which helps reduce headroom voltage while guaranteeing charge balance at the active electrode. The use of positive supplies instead of both positive and negative supplies simplifies CMOS circuit design. The current distribution between two nearby simultaneously active electrode groups was investigated and measurement result showed a maximum current crosstalk of 8%.

Learning the structure of correlated synaptic subgroups using stable and competitive spike-timing-dependent plasticity.

Synaptic plasticity must be both competitive and stable if ongoing learning of the structure of neural inputs is to occur. In this paper, a wide class of spike-timing-dependent plasticity (STDP) models is identified that have both of these desirable properties in the case in which the input consists of subgroups of synapses that are correlated within the subgroup through the occurrence of simultaneous input spikes. The process of synaptic structure formation is studied, illustrating one particular class of these models. When the learning rate is small, multiple alternative synaptic structures are possible given the same inputs, with the outcome depending on the initial weight configuration. For large learning rates, the synaptic structure does not stabilize, resulting in neurons without consistent response properties. For learning rates in between, a unique and stable synaptic structure typically forms. When this synaptic structure exhibits a bimodal distribution, the neuron will respond selectively to one or more of the subgroups. The robustness with which this selectivity develops during learning is largely determined by the ratio of the subgroup correlation strength to the number of subgroups. The fraction of potentiated subgroups is primarily determined by the balance between potentiation and depression.

Study of neuronal gain in a conductance-based leaky integrate-and-fire neuron model with balanced excitatory and inhibitory synaptic input.

Neurons receive a continual stream of excitatory and inhibitory synaptic inputs. A conductance-based neuron model is used to investigate how the balanced component of this input modulates the amplitude of neuronal responses. The output spiking rate is well described by a formula involving three parameters: the mean mu and variance sigma of the membrane potential and the effective membrane time constant tauQ. This expression shows that, for sufficiently small tauQ, the level of balanced excitatory-inhibitory input has a nonlinear modulatory effect on the neuronal gain.

Electrode discrimination and speech perception in young children using cochlear implants.

OBJECTIVE: The aim was to determine the efficacy of a child-appropriate procedure to assess electrode discrimination ability in young children using cochlear implants and to investigate the relationship of electrode discrimination ability and speech perception performance in children implanted at a young age. DESIGN: An adaptation of the play audiometry procedure was used to assess electrode discrimination in seventeen 4- to 10-yr-old children. The children were required to respond with a game-like motor response when a repeating stimulation on a reference electrode "changed" to a different electrode. They were also assessed on a speech feature discrimination test, a closed-set word recognition test and a nonverbal intelligence task. RESULTS: Sixty-five percent of subjects demonstrated ability to discriminate adjacent electrodes in mid and apical regions of the cochlea, whilst the remaining subjects needed electrode separations of between two and nine electrodes for successful discrimination. In a forward stepwise regression analysis electrode discrimination ability was found to be the strongest factor in accounting for variance in the speech perception scores. Subject variables such as duration of deafness, nonverbal intelligence and implant experience did not significantly account for further variance in the speech perception scores for this group of children. CONCLUSIONS: Electrode discrimination ability was the strongest factor in predicting performance on speech perception measures in a group of children using cochlear implants.