Characterization and Validation of CMOS Spiking Neuron Circuits

Faculty Mentor Information

Kurtis D. Cantley

Presentation Date

7-2016

Abstract

Brain-inspired chips are being designed to efficiently process complex information and accomplish tasks such as pattern recognition, object detection, and noise reduction and filtering. For this research, we are testing complementary metal-oxide-semiconductor (CMOS) devices such as transistors. We are also examining different CMOS circuits including inverters and leaky integrate-and-fire neurons using a microprobe station. The neuron circuits are expected to generate voltage pulses that mimic the action potentials of neurons found in the brain. The frequency of these pulses changes with input stimulus but pulse widths remain constant. This stimulus is directly proportional to the frequency at which spikes are generated and if this increase the frequency will increase too. We analyze the behavior by examining the generated voltage versus time and frequency versus current graphs. Extracted data is then compared to simulation as well as biological measurements obtained from the literature to demonstrate the effectiveness of the chip.

Comments

Poster #W20

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Characterization and Validation of CMOS Spiking Neuron Circuits

Brain-inspired chips are being designed to efficiently process complex information and accomplish tasks such as pattern recognition, object detection, and noise reduction and filtering. For this research, we are testing complementary metal-oxide-semiconductor (CMOS) devices such as transistors. We are also examining different CMOS circuits including inverters and leaky integrate-and-fire neurons using a microprobe station. The neuron circuits are expected to generate voltage pulses that mimic the action potentials of neurons found in the brain. The frequency of these pulses changes with input stimulus but pulse widths remain constant. This stimulus is directly proportional to the frequency at which spikes are generated and if this increase the frequency will increase too. We analyze the behavior by examining the generated voltage versus time and frequency versus current graphs. Extracted data is then compared to simulation as well as biological measurements obtained from the literature to demonstrate the effectiveness of the chip.