In-vivo blood pressure sensing with bi-filler nanocomposite.

Conductive elastomers present desirable qualities for sensing pressure in-vivo, such as high piezoresistance in tiny volumes, conformability and, biocompatibility. Many electrically conductive nanocomposites however, are susceptible to electrical drift following repeated stress cycles and chemical aging. Here we propose an innovative approach to stabilize nanocomposite percolation network against incomplete recovery to improve reproducibility and facilitate sensor calibration.

Single shot detection of alterations across multiple ionic currents from assimilation of cell membrane dynamics.

The dysfunction of ion channels is a causative factor in a variety of neurological diseases, thereby defining the implicated channels as key drug targets. The detection of functional changes in multiple specific ionic currents currently presents a challenge, particularly when the neurological causes are either a priori unknown, or are unexpected. Traditional patch clamp electrophysiology is a powerful tool in this regard but is low throughput.

Noise-activated barrier crossing in multiattractor dissipative neural networks.

Noise-activated transitions between coexisting attractors are investigated in a chaotic spiking network. At low noise level, attractor hopping consists of discrete bifurcation events that conserve the memory of initial conditions. When the escape probability becomes comparable to the intrabasin hopping probability, the lifetime of attractors is given by a detailed balance where the less coherent attractors act as a sink for the more coherent ones.

Reverse re-modelling chronic heart failure by reinstating heart rate variability.

Heart rate variability (HRV) is a crucial indicator of cardiovascular health. Low HRV is correlated with disease severity and mortality in heart failure. Heart rate increases and decreases with each breath in normal physiology termed respiratory sinus arrhythmia (RSA).

Robust neuromorphic coupled oscillators for adaptive pacemakers.

Neural coupled oscillators are a useful building block in numerous models and applications. They were analyzed extensively in theoretical studies and more recently in biologically realistic simulations of spiking neural networks. The advent of mixed-signal analog/digital neuromorphic electronic circuits provides new means for implementing neural coupled oscillators on compact, low-power, spiking neural network hardware platforms.

Ballistic Hall Photovoltammetry of Magnetic Resonance in Individual Nanomagnets.

We report on ballistic Hall photovoltammetry as a contactless probe of localized spin excitations. Spins resonating in the near field of a two-dimensional electron system are shown to induce a long range electromotive force that we calculate. We use this coupling mechanism to detect the spin wave eigenmodes of a single ferromagnet of sub-100 nm size.

Estimation of neuron parameters from imperfect observations.

The estimation of parameters controlling the electrical properties of biological neurons is essential to determine their complement of ion channels and to understand the function of biological circuits. By synchronizing conductance models to time series observations of the membrane voltage, one may construct models capable of predicting neuronal dynamics. However, identifying the actual set of parameters of biological ion channels remains a formidable theoretical challenge.

Optimal solid state neurons.

Bioelectronic medicine is driving the need for neuromorphic microcircuits that integrate raw nervous stimuli and respond identically to biological neurons. However, designing such circuits remains a challenge. Here we estimate the parameters of highly nonlinear conductance models and derive the ab initio equations of intracellular currents and membrane voltages embodied in analog solid-state electronics.

Enhancing respiratory sinus arrhythmia increases cardiac output in rats with left ventricular dysfunction.

Key Points: Respiratory sinus arrhythmia is physiological pacing of the heart that disappears in cardiovascular disease and is associated with poor cardiac prognosis. In heart failure, cardiac pacing has little, if any, variation in rate at rest. We proposed that reinstatement of respiratory sinus arrhythmia would improve cardiac function in rats with heart failure.

Dual Mechanism for the Emergence of Synchronization in Inhibitory Neural Networks.

During cognitive tasks cortical microcircuits synchronize to bind stimuli into unified perception. The emergence of coherent rhythmic activity is thought to be inhibition-driven and stimulation-dependent. However, the exact mechanisms of synchronization remain unknown.

Inhibition delay increases neural network capacity through Stirling transform.

Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors.

Ultrafast pressure sensing with transient tunnelling currents.

We report and systematically study large amplitude piezoresistance spikes in thin composite films under stress. These spikes are characterized by a unique double exponential decay which we demonstrate to be the signature of transient tunnelling currents. We establish an expression that predicts the dynamic conductivity of the composite with only three material parameters and use it to infer the magnitude of applied stress from resistance spikes, thus achieving quasi-instantaneous readout unhindered by viscoelastic relaxation.

Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data.

We report on the construction of neuron models by assimilating electrophysiological data with large-scale constrained nonlinear optimization. The method implements interior point line parameter search to determine parameters from the responses to intracellular current injections of zebra finch HVC neurons. We incorporated these parameters into a nine ionic channel conductance model to obtain completed models which we then use to predict the state of the neuron under arbitrary current stimulation.

Utility of a Novel Biofeedback Device for Within-Breath Modulation of Heart Rate in Rats: A Quantitative Comparison of Vagus Nerve vs. Right Atrial Pacing.

In an emerging bioelectronics era, there is a clinical need for physiological devices incorporating biofeedback that permits natural and demand-dependent control in real time. Here, we describe a novel device termed a central pattern generator (CPG) that uses cutting edge analog circuitry producing temporally controlled, electrical stimulus outputs based on the real time integration of physiological feedback. Motivated by the fact that respiratory sinus arrhythmia (RSA), which is the cyclical changes in heart rate every breath, is an essential component of heart rate variability (HRV) (an indicator of cardiac health), we have explored the versatility and efficiency of the CPG for producing respiratory modulation of heart rate in anesthetized, spontaneously breathing rats.

Experimental observation of multistability and dynamic attractors in silicon central pattern generators.

We report on the multistability of chaotic networks of silicon neurons and demonstrate how spatiotemporal sequences of voltage oscillations are selected with timed current stimuli. A three neuron central pattern generator was built by interconnecting Hodgkin-Huxley neurons with mutually inhibitory links mimicking gap junctions. By systematically varying the timing of current stimuli applied to individual neurons, we generate the phase lag maps of neuronal oscillators and study their dependence on the network connectivity.

Estimating parameters and predicting membrane voltages with conductance-based neuron models.

Recent results demonstrate techniques for fully quantitative, statistical inference of the dynamics of individual neurons under the Hodgkin-Huxley framework of voltage-gated conductances. Using a variational approximation, this approach has been successfully applied to simulated data from model neurons. Here, we use this method to analyze a population of real neurons recorded in a slice preparation of the zebra finch forebrain nucleus HVC.

Modulation of respiratory sinus arrhythmia in rats with central pattern generator hardware.

We report on the modulation of respiratory sinus arrhythmia in rats with central pattern generator (CPG) hardware made of silicon neurons. The neurons are made to compete through mutually inhibitory synapses to provide timed electrical oscillations that stimulate the peripheral end of vagus nerve at specific points of the respiratory cycle: the inspiratory phase (φ(1)), the early expiratory phase (φ(2)) and the late expiratory phase (φ(3)). In this way the CPG hardware mimics the neuron populations in the brainstem which through connections with cardiac vagal motoneurones control respiratory sinus arrhythmia (RSA).

Electron dynamics in inhomogeneous magnetic fields.

This review explores the dynamics of two-dimensional electrons in magnetic potentials that vary on scales smaller than the mean free path. The physics of microscopically inhomogeneous magnetic fields relates to important fundamental problems in the fractional quantum Hall effect, superconductivity, spintronics and graphene physics and spins out promising applications which will be described here. After introducing the initial work done on electron localization in random magnetic fields, the experimental methods for fabricating magnetic potentials are presented.

Noise-controlled signal transmission in a multithread semiconductor neuron.

We report on stochastic effects in a new class of semiconductor structures that accurately imitate the electrical activity of biological neurons. In these devices, electrons and holes play the role of K+ and Na+ ions that give the action potentials in real neurons. The structure propagates and delays electrical pulses via a web of spatially distributed transmission lines.

Quantum interference of magnetic edge channels activated by intersubband optical transitions in magnetically confined quantum wires.

We investigate the photoresistance of a magnetically confined quantum wire in which microwave-coupled edge channels interfere at two pinning sites in the fashion of a Mach-Zehnder interferometer. The conductance is strongly enhanced by microwave power at B = 0 and develops a complex series of oscillations when the magnetic confinement increases. Both results are quantitatively explained by the activation of forward scattering in a multimode magnetically confined quantum wire.

Electrically induced Raman emission from planar spin oscillator.

We predict that two-dimensional electrons confined by a magnetic field gradient resonantly transfer energy to the electromagnetic field by a process of inverse electron spin resonance that is realized when the frequency of an open orbit equals the Larmor frequency. The calculated emission spectra show multiple peaks modulated by strong optical nonlinearities whose frequencies may be tuned by the magnetic field gradient and the electron concentration.

Resistance resonance effects through magnetic edge states.

We report on the magnetoresistance of a two-dimensional electron gas subjected to an abrupt magnetic field gradient arising from a ferromagnetic stripe fabricated at its surface. A sharp resistance resonance effect is observed at B(p) due to the formation of two types of magnetic edge states that drift in opposite directions perpendicular to the magnetic field gradient for BB(p). A semiclassical drift-diffusion model gives a good description of the effects of the magnetic confinement on both the diagonal and off-diagonal components of the resistivity tensor.