Models that contain the Modeling Application : NEST (Home Page)

("NEST is a simulator for spiking neural network models that focuses on the dynamics, size and structure of neural systems rather than on the exact morphology of individual neurons. The development of NEST is coordinated by the NEST Initiative. NEST is ideal for networks of spiking neurons of any size, for example: 1. Models of information processing e.g. in the visual or auditory cortex of mammals, 2. Models of network activity dynamics, e.g. laminar cortical networks or balanced random networks, 3. Models of learning and plasticity." )
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    Models
1. A spatial model of the intermediate superior colliculus (Moren et. al. 2013)
2. A spiking neural network model of model-free reinforcement learning (Nakano et al 2015)
3. A spiking NN for amplification of feature-selectivity with specific connectivity (Sadeh et al 2015)
4. Brain networks simulators - a comparative study (Tikidji-Hamburyan et al 2017)
5. Cortical feedback alters visual response properties of dLGN relay cells (Martínez-Cañada et al 2018)
6. Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)
7. Neuron-based control mechanisms for a robotic arm and hand (Singh et al 2017)
8. Noise promotes independent control of gamma oscillations and grid firing (Solanka et al 2015)
9. Orientation selectivity in inhibition-dominated recurrent networks (Sadeh and Rotter, 2015)
10. Sparsely connected networks of spiking neurons (Brunel 2000)
11. Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013)

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