Modeling neuromorphic persistent firing networks

• Main Authors: NING, Ning, LI, Guoqi, HE, Wei, HUANG, Kejie, PAN, Li, RAMANATHAN, Kiruthika, ZHAO, Rong, SHI, Luping
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Neuron Model; Neuromorphic; Persistent Firing; Slow Integration; Spiking Network; Working Memory; Databases and Information Systems; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/7389; https://ink.library.smu.edu.sg/context/sis_research/article/8392/viewcontent/IJIS_2015013016221485.pdf
• Institution: Singapore Management University

Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or den...