| 1961 | -- | 1992 | Lars Buesing, Wolfgang Maass. A Spiking Neuron as Information Bottleneck |
| 1993 | -- | 2001 | Ke Yuan, Mahesan Niranjan. Estimating a State-Space Model from Point Process Observations: A Note on Convergence |
| 2002 | -- | 2030 | Todd P. Coleman, Sridevi S. Sarma. A Computationally Efficient Method for Nonparametric Modeling of Neural Spiking Activity with Point Processes |
| 2031 | -- | 2058 | Angelo Arleo, Thierry Nieus, Michele Bezzi, Anna D Errico, Egidio D Angelo, Olivier J. M. D. Coenen. How Synaptic Release Probability Shapes Neuronal Transmission: Information-Theoretic Analysis in a Cerebellar Granule Cell |
| 2059 | -- | 2085 | Daniel Bush, Andrew Philippides, Phil Husbands, Michael O Shea. Reconciling the STDP and BCM Models of Synaptic Plasticity in a Spiking Recurrent Neural Network |
| 2086 | -- | 2112 | Yingxue Wang, Shih-Chii Liu. Multilayer Processing of Spatiotemporal Spike Patterns in a Neuron with Active Dendrites |
| 2113 | -- | 2136 | Ahmet Omurtag, William W. Lytton. Spectral Method and High-Order Finite Differences for the Nonlinear Cable Equation |
| 2137 | -- | 2160 | Wei Zhou, Jacek M. Zurada. Competitive Layer Model of Discrete-Time Recurrent Neural Networks with LT Neurons |
| 2161 | -- | 2191 | Yansheng Ming, Zhanyi Hu. Modeling Stereopsis via Markov Random Field |
| 2192 | -- | 2207 | Nicolas Le Roux, Yoshua Bengio. Deep Belief Networks Are Compact Universal Approximators |
| 2208 | -- | 2227 | Intae Lee. Sample-Spacings-Based Density and Entropy Estimators for Spherically Invariant Multidimensional Data |