A multi-channel wireless implantable neural recording (WINeR) system for electrophysiology and behavioral neuroscience research applications was proposed. The system is composed of two units: a system-on-a-chip (SoC) transmitter (Tx) unit and a receiver (Rx) unit. In the Tx unit, the outputs are combined with marker signals and modulated into pulse widths after the neural signals are amplified and filtered by an array of low-noise amplifiers (LNA). The next step involves time-division multiplexing (TDM) of pulse-width modulation (PWM) signals. The TDM-PWM signal drives RF transmitter block and is transmitted by an antenna. To satisfy the needs of neuroscientists during animal experiments, the proposed WINeR system provides long-term recording with inductive powering and stimulus-artifact rejection for closed-loop operations, which requires simultaneous stimulation and recording. The Rx is another critical unit for wireless-link communication. To increase the area of wireless coverage, multiple antennas are used for the Rx. In addition, the automatic frequency-tracking method is used to track free-running Tx frequencies, and a smart time-to-digital conversion method is used to reduce noise and interference. A high-throughput computer interface and software are also developed to continuously receive and store neural data. The WINeR system is a potential tool for neuroscientists due to several advantages, such as a reliable wireless link with large coverage and no blind spots, low power consumption, an unlimited power source, and a stimulation function.

One of the leading aims of systems biology is the complete delineation of the organization and architecture of signaling networks. Within this aim, characterizing integrated circuits is a particular challenge. Integrated circuits are the sites of information multiplexing, where input from multiple sources are combined into a single output or channel. A number of quantitative methods for analyzing epistasis within integrated pathways have been developed, with limited success. Here I present Expression Component Analysis, a novel approach for determining quantitative epistasis within an integrated signaling circuit, and describe the application of Expression Component Analysis in analyzing an interesting and important integrated signaling circuit in the model eukaryote, S.cerevisiae.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.