Spike-Timing-Dependent Plasticity Using Biologically Realistic Action Potentials and Low-Temperature Materials

Anand Subramaniam, Kurtis D. Cantley, Gennadi Bersuker, David C. Gilmer, Eric M. Vogel

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Spike-timing-dependent plasticity (STDP) is a fundamental learning rule observed in biological synapses that is desirable to replicate in neuromorphic electronic systems. Nanocrystalline-silicon thin film transistors (TFTs) and memristors can be fabricated at low temperatures, and are suitable for use in such systems because of their potential for high density, 3-D integration. In this paper, a compact and robust learning circuit that implements STDP using biologically realistic nonmodulated rectangular voltage pulses is demonstrated. This is accomplished through the use of a novel nanoparticle memory-TFT with short retention time at the output of the neuron circuit that drives memristive synapses. Similarities to biological measurements are examined with single and repeating spike pairs or different timing intervals and frequencies, as well as with spike triplets.
Original languageAmerican English
JournalIEEE Transactions on Nanotechnology
Volume12
Issue number3
StatePublished - May 2013
Externally publishedYes

Keywords

  • Low-temperature nanoelectronics
  • memristor
  • neuromorphic circuit
  • spike-timing-dependent plasticity
  • synapse

EGS Disciplines

  • Electrical and Computer Engineering

Fingerprint

Dive into the research topics of 'Spike-Timing-Dependent Plasticity Using Biologically Realistic Action Potentials and Low-Temperature Materials'. Together they form a unique fingerprint.

Cite this