Chi-Ming chen | National Taiwan University (original) (raw)
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Papers by Chi-Ming chen
Physical Review E, 2011
We use computer simulations to investigate the structural and dynamical properties of a developin... more We use computer simulations to investigate the structural and dynamical properties of a developing neural network whose activity is driven by noise. Structurally, the constructed neural networks in our simulations exhibit the small-world properties that have been observed in several neural networks. The dynamical change of neuronal membrane potential is described by the Hodgkin-Huxley model, and two types of learning rules, including spike-timing-dependent plasticity (STDP) and inverse STDP, are considered to restructure the synaptic strength between neurons. Clustered synchronized firing (SF) of the network is observed when the network connectivity (number of connections/maximal connections) is about 0.75, in which the firing rate of neurons is only half of the network frequency. At the connectivity of 0.86, all neurons fire synchronously at the network frequency. The network SF frequency increases logarithmically with the culturing time of a growing network and decreases exponentially with the delay time in signal transmission. These conclusions are consistent with experimental observations. The phase diagrams of SF in a developing network are investigated for both learning rules.
Physica A: Statistical Mechanics and its Applications, 2005
The driven translocation dynamics of a polynucleotide chain through a nanopore is studied using o... more The driven translocation dynamics of a polynucleotide chain through a nanopore is studied using off-lattice Monte-Carlo simulations, which plays an important role in the nanopore sequencing of polynucleotides. We report a detailed study on the dependence of translocation dynamics on the chain length and the local geometry near the nanopore. In particular, we find that the length dependence of the infection time of the chain could exhibit very different behaviors for different geometries.
Physical Review E, 2011
We use computer simulations to investigate the structural and dynamical properties of a developin... more We use computer simulations to investigate the structural and dynamical properties of a developing neural network whose activity is driven by noise. Structurally, the constructed neural networks in our simulations exhibit the small-world properties that have been observed in several neural networks. The dynamical change of neuronal membrane potential is described by the Hodgkin-Huxley model, and two types of learning rules, including spike-timing-dependent plasticity (STDP) and inverse STDP, are considered to restructure the synaptic strength between neurons. Clustered synchronized firing (SF) of the network is observed when the network connectivity (number of connections/maximal connections) is about 0.75, in which the firing rate of neurons is only half of the network frequency. At the connectivity of 0.86, all neurons fire synchronously at the network frequency. The network SF frequency increases logarithmically with the culturing time of a growing network and decreases exponentially with the delay time in signal transmission. These conclusions are consistent with experimental observations. The phase diagrams of SF in a developing network are investigated for both learning rules.
Physica A: Statistical Mechanics and its Applications, 2005
The driven translocation dynamics of a polynucleotide chain through a nanopore is studied using o... more The driven translocation dynamics of a polynucleotide chain through a nanopore is studied using off-lattice Monte-Carlo simulations, which plays an important role in the nanopore sequencing of polynucleotides. We report a detailed study on the dependence of translocation dynamics on the chain length and the local geometry near the nanopore. In particular, we find that the length dependence of the infection time of the chain could exhibit very different behaviors for different geometries.