9 citations · 33 across the 17 of their papers we have counts for
17 papers
Dendritic Integration Based Quadratic Neural Networks Outperform Traditional Aritificial Ones
Chongming Liu, Songting Li, Douglas Zhou
Incorporating biological neuronal properties into Artificial Neural Networks (ANNs) to enhance computational capabilities poses a formidable challenge in the field of machine learn…
Mapping Biological Neuron Dynamics into an Interpretable Two-layer Artificial Neural Network
Jingyang Ma, Songting Li, Douglas Zhou
Dendrites are crucial structures for computation of an individual neuron. It has been shown that the dynamics of a biological neuron with dendrites can be approximated by artificia…
Quantitative relations among causality measures with applications to nonlinear pulse-output network reconstruction
Zhong-qi K. Tian, Kai Chen, Songting Li +2
The causal connectivity of a network is often inferred to understand the network function. It is arguably acknowledged that the inferred causal connectivity relies on causality mea…
Library-based Fast Algorithm for Simulating the Hodgkin-Huxley Neuronal Networks
Zhong-Qi Kyle Tian, Douglas Zhou
We present a modified library-based method for simulating the Hodgkin-Huxley (HH) neuronal networks. By pre-computing a high resolution data library during the interval of an actio…
Design Fast Algorithms For Hodgkin-Huxley Neuronal Networks
Zhong-Qi Kyle Tian, Douglas Zhou
The stiffness of the Hodgkin-Huxley (HH) equations during an action potential (spike) limits the use of large time steps. We observe that the neurons can be evolved independently b…
Design Efficient Exponential Time Differencing method For Hodgkin-Huxley Neural Networks
Zhong-Qi Kyle Tian, Douglas Zhou
The exponential time differencing (ETD) method allows using a large time step to efficiently evolve the stiff system such as Hodgkin-Huxley (HH) neural networks. For pulse-coupled…