A biophysically-based neuromorphic model of spike rate- and timing-dependent plasticity.

Current advances in neuromorphic engineering have made it possible to emulate complex neuronal ion channel and intracellular ionic dynamics in real time using highly compact and power-efficient complementary metal-oxide-semiconductor (CMOS) analog very-large-scale-integrated circuit technology. Recently, there has been growing interest in the neuromorphic emulation of the spike-timing-dependent plasticity (STDP) Hebbian learning rule by phenomenological modeling using CMOS, memristor or other analog devices. Here, we propose a CMOS circuit implementation of a biophysically grounded neuromorphic (iono-neuromorphic) model of synaptic plasticity that is capable of capturing both the spike rate-dependent plasticity (SRDP, of the Bienenstock-Cooper-Munro or BCM type) and STDP rules.

A picoampere A/D converter for biosensor applications.

Detection and analysis of biological and biochemical signals via compact sensor systems require low-power and compact analog-to-digital converter (ADC) systems. Here we present a highly sensitive flash current-mode ADC (IADC) design with resolution down to 15pA. The IADC's small-size and low-power capabilities allow integration for stand-alone biological or chemical microsensor applications.

Transistor analogs of emergent iono-neuronal dynamics.

Neuromorphic analog metal-oxide-silicon (MOS) transistor circuits promise compact, low-power, and high-speed emulations of iono-neuronal dynamics orders-of-magnitude faster than digital simulation. However, their inherently limited input voltage dynamic range vs power consumption and silicon die area tradeoffs makes them highly sensitive to transistor mismatch due to fabrication inaccuracy, device noise, and other nonidealities. This limitation precludes robust analog very-large-scale-integration (aVLSI) circuits implementation of emergent iono-neuronal dynamics computations beyond simple spiking with limited ion channel dynamics.

A component-based FPGA design framework for neuronal ion channel dynamics simulations.

Neuron-machine interfaces such as dynamic clamp and brain-implantable neuroprosthetic devices require real-time simulations of neuronal ion channel dynamics. Field-programmable gate array (FPGA) has emerged as a high-speed digital platform ideal for such application-specific computations. We propose an efficient and flexible component-based FPGA design framework for neuronal ion channel dynamics simulations, which overcomes certain limitations of the recently proposed memory-based approach.

The effect of hyperoxygenation on T1 relaxation time in vitro.

Rationale And Objectives: Ventilation with high oxygen (O2) concentrations has been shown to decrease T1 in blood and tissues of patients. This study aims to assess the effect of hyperoxygenation on the T1 relaxation time of blood and other physiologic solutions.

Materials And Methods: Varied gaseous mixtures of O2 and air between 21% and 100% O2 were created using an experimental circuit at room temperature, and used to saturate human blood, plasma, or normal saline.