Probabilistic Neural Computing with Stochastic Devices.

The brain has effectively proven a powerful inspiration for the development of computing architectures in which processing is tightly integrated with memory, communication is event-driven, and analog computation can be performed at scale. These neuromorphic systems increasingly show an ability to improve the efficiency and speed of scientific computing and artificial intelligence applications. Herein, it is proposed that the brain's ubiquitous stochasticity represents an additional source of inspiration for expanding the reach of neuromorphic computing to probabilistic applications.

Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing.

Neuromorphic computers could overcome efficiency bottlenecks inherent to conventional computing through parallel programming and readout of artificial neural network weights in a crossbar memory array. However, selective and linear weight updates and <10-nanoampere read currents are required for learning that surpasses conventional computing efficiency. We introduce an ionic floating-gate memory array based on a polymer redox transistor connected to a conductive-bridge memory (CBM).

Computing with Spikes: The Advantage of Fine-Grained Timing.

Neural-inspired spike-based computing machines often claim to achieve considerable advantages in terms of energy and time efficiency by using spikes for computation and communication. However, fundamental questions about spike-based computation remain unanswered. For instance, how much advantage do spike-based approaches have over conventional methods, and under what circumstances does spike-based computing provide a comparative advantage? Simply implementing existing algorithms using spikes as the medium of computation and communication is not guaranteed to yield an advantage.

Rapid Nucleic Acid Extraction and Purification Using a Miniature Ultrasonic Technique.

Miniature ultrasonic lysis for biological sample preparation is a promising technique for efficient and rapid extraction of nucleic acids and proteins from a wide variety of biological sources. Acoustic methods achieve rapid, unbiased, and efficacious disruption of cellular membranes while avoiding the use of harsh chemicals and enzymes, which interfere with detection assays. In this work, a miniature acoustic nucleic acid extraction system is presented.

Li-Ion Synaptic Transistor for Low Power Analog Computing.

Nonvolatile redox transistors (NVRTs) based upon Li-ion battery materials are demonstrated as memory elements for neuromorphic computer architectures with multi-level analog states, "write" linearity, low-voltage switching, and low power dissipation. Simulations of backpropagation using the device properties reach ideal classification accuracy. Physics-based simulations predict energy costs per "write" operation of <10 aJ when scaled to 200 nm × 200 nm.

A Combinatorial Model for Dentate Gyrus Sparse Coding.

The dentate gyrus forms a critical link between the entorhinal cortex and CA3 by providing a sparse version of the signal. Concurrent with this increase in sparsity, a widely accepted theory suggests the dentate gyrus performs pattern separation-similar inputs yield decorrelated outputs. Although an active region of study and theory, few logically rigorous arguments detail the dentate gyrus's (DG) coding.

Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution.

We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light.

Energy Scaling Advantages of Resistive Memory Crossbar Based Computation and Its Application to Sparse Coding.

The exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency.

Induction frequency affects cortico-striatal synaptic plasticity with implications for frequency filtering.

Long-term synaptic depression (LTD) in cortico-striatal circuits is initiated by depolarization of striatal medium spiny neurons through a convergent cortical glutamatergic input. This produces retrograde endocannabinoid signaling to presynaptic cortical terminals and eventually results in long term (>30 min) decreases in glutamate release. These same circuits can also undergo short-term depression (STD) through a less well-defined process in which the magnitude of postsynaptic responses returns to baseline levels within 10 min.

Isothermal switching and detailed filament evolution in memristive systems.

The steady-state solution of filamentary memristive switching may be derived directly from the heat equation, modelling vertical and radial heat flow. This solution is shown to provide a continuous and accurate description of the evolution of the filament radius, composition, heat flow, and temperature during switching, and is shown to apply to a large range of switching materials and experimental time-scales.

Combined chemical and topographical guidance cues for directing cytoarchitectural polarization in primary neurons.

Chemical and topographical cues can be used to guide dissociated neurons into user-defined network geometries on artificial substrates, yet control of neuron polarity (differentiation into axons and dendrites) remains an elusive goal. We developed a dual guidance cue strategy for directing morphological maturity in neurons in vitro using combined chemical and topographical guidance cues on glass substrates. The surface chemistry provides chemical attraction and repulsion for controlling neuron placement and outgrowth, while the topography provides additional surface area for neuron attachment.

Nuclear translocation kinetics of NF-kappaB in macrophages challenged with pathogens in a microfluidic platform.

We have developed a microfluidic platform for real-time imaging of host-pathogen interactions and cellular signaling events. Host cells are immobilized in a controlled environment for optical interrogation of the kinetics and stochasticity of immune response to pathogenic challenges. Here, we have quantitatively measured activation of the toll-like receptor 4 (TLR4) pathway in RAW264.

Impedimetric and optical interrogation of single cells in a microfluidic device for real-time viability and chemical response assessment.

We report here a non-invasive, reversible method for interrogating single cells in a microfluidic flow-through system. Impedance spectroscopy of cells held at a micron-sized pore under negative pressure is demonstrated and used to determine the presence and viability of the captured cell. The cell capture pore is optimized for electrical response and mechanical interfacing to a cell using a deposited layer of parylene.

Effects of substrate geometry on growth cone behavior and axon branching.

At the leading edge of a growing axon, the growth cone determines the path the axon takes and also plays a role in the formation of branches, decisions that are regulated by a complex array of chemical signals. Here, we used microfabrication technology to determine whether differences in substrate geometry, independent of changes in substrate chemistry, can modulate growth cone motility and branching, by patterning a polylysine grid of narrow (2 or 5 microm wide) intersecting lines. The shape of the intersections varied from circular nodes 15 microm in diameter to simple crossed lines (nodeless intersections).

Extracellular recordings from patterned neuronal networks using planar microelectrode arrays.

Neuronal cell networks have been reconstructed on planar microelectrode arrays (MEAs) from dissociated hippocampal pyramidal neurons. Microcontact printing (microCP) and a photoresist-liftoff method were used to selectively localize poly-L-lysine (PLL) on the surface of MEAs. Haptotaxis led to the organization of the neurons into networks localized adjacent to microelectrodes.

Patterning axonal guidance molecules using a novel strategy for microcontact printing.

We present here a two-step strategy for micropatterning proteins on a substrate to control neurite growth in culture. First, conventional microcontact printing is used to prepare a micropattern of protein A, which binds the Fc fragment of immunoglobulins. Then, a chimeric protein, consisting of the extracellular domain of a guidance protein recombinantly linked to the Fc fragment of IgG (prepared using conventional molecular techniques), is applied from solution.