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...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 dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon as a slow leaky integrator, which captures almost all-known neural behaviors. The model controls the switching of axonal firing dynamics between passive conduction mode and persistent firing mode. The interplay between the axonal integrated potential and its multiple thresholds in axon precisely determines the persistent firing dynamics of neurons. We also present a persistent firing polychronous spiking network which exhibits asynchronous dynamics indicating that this computationally efficient model is not only bio-plausible, but also suitable for large scale spiking network simulations. The implications of this network and the analog circuit design for exploring the relationship between working memory and persistent firing enable developing a spiking network-based memory and bio-inspired computer systems.展开更多
A superlattice-like (SLL) structure was applied to phase-change optical recording. The recording layer consisting of alternating thin layers of two different phase-change materials, GeTe and Sb2Te3, were grown by magn...A superlattice-like (SLL) structure was applied to phase-change optical recording. The recording layer consisting of alternating thin layers of two different phase-change materials, GeTe and Sb2Te3, were grown by magnetron sputtering on polycarbonate substrates. Land/groove optical recording was adopted to suppress crosstalk and obtain a large track density. Dynamic properties of the SLL disc were investigated with the shortest 1T pulse duration of 8 ns. Clear eye pattern was observed after 10000 direct overwrite cycles. Erasability above 20 dB was achieved at a constant linear velocity of 19 m/s. Carrier-noise ratio (CNR) kept above 46 dB when the recording frequency reaches 21 VIHz. The SLL phase change optical disc demonstrates a better recording performance than the Ge1Sb2Te4 and Ge1Sb4Te7 discs in terms of CNR, erasability, and overwrite jitter.展开更多
文摘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 dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon as a slow leaky integrator, which captures almost all-known neural behaviors. The model controls the switching of axonal firing dynamics between passive conduction mode and persistent firing mode. The interplay between the axonal integrated potential and its multiple thresholds in axon precisely determines the persistent firing dynamics of neurons. We also present a persistent firing polychronous spiking network which exhibits asynchronous dynamics indicating that this computationally efficient model is not only bio-plausible, but also suitable for large scale spiking network simulations. The implications of this network and the analog circuit design for exploring the relationship between working memory and persistent firing enable developing a spiking network-based memory and bio-inspired computer systems.
基金Work described in the letter was performed at Data Storage Institute, Singapore. The authors gratefully acknowledge the financial support by the National Natural Science Foundation of China under Grant No. 60132030.
文摘A superlattice-like (SLL) structure was applied to phase-change optical recording. The recording layer consisting of alternating thin layers of two different phase-change materials, GeTe and Sb2Te3, were grown by magnetron sputtering on polycarbonate substrates. Land/groove optical recording was adopted to suppress crosstalk and obtain a large track density. Dynamic properties of the SLL disc were investigated with the shortest 1T pulse duration of 8 ns. Clear eye pattern was observed after 10000 direct overwrite cycles. Erasability above 20 dB was achieved at a constant linear velocity of 19 m/s. Carrier-noise ratio (CNR) kept above 46 dB when the recording frequency reaches 21 VIHz. The SLL phase change optical disc demonstrates a better recording performance than the Ge1Sb2Te4 and Ge1Sb4Te7 discs in terms of CNR, erasability, and overwrite jitter.
