Note: this list includes both models hosted here at ModelDB and models where have metadata and link to the sourcecode somewhere else. These may also be viewed separately; see the browse by simulator page.

- A spatial model of the intermediate superior colliculus (Moren et. al. 2013)
- A spiking neural network model of model-free reinforcement learning (Nakano et al 2015)
- A spiking NN for amplification of feature-selectivity with specific connectivity (Sadeh et al 2015)
- Adaptive Generalized Leaky Integrate-and-Fire Model (AGLIF) (Marasco et al., 2023)
- An electrophysiological model of GABAergic double bouquet cells (Chrysanthidis et al. 2019)
- Brain networks simulators - a comparative study (Tikidji-Hamburyan et al 2017)
- Complex dynamics: reproducing Golgi cell electroresponsiveness (Geminiani et al 2018, 2019ab)
- Cortical feedback alters visual response properties of dLGN relay cells (Martínez-Cañada et al 2018)
- eLIF and mAdExp: energy-based integrate-and-fire neurons (Fardet and Levina 2020)
- Emergence of spatiotemporal sequences in spiking neuronal networks (Spreizer et al 2019)
- GLMCC validation neural network model (Kobayashi et al. 2019)
- Growth Rules for Repair of Asynch Irregular Networks after Peripheral Lesions (Sinha et al 2021)
- Modeling realistic synaptic inputs of CA1 hippocampal pyramidal neurons and interneurons via Adaptive Generalized Leaky Integrate-and-Fire models (Marascoa et al., 2024)
- Multi-area layer-resolved spiking network model of resting-state dynamics in macaque visual cortex
- Networks of spiking neurons: a review of tools and strategies (Brette et al. 2007)
- Neuromorphic muscle spindle model (Vannucci et al 2017)
- On the structural connectivity of large-scale models of brain networks (Giacopelli et al 2021)
- Orientation selectivity in inhibition-dominated recurrent networks (Sadeh and Rotter, 2015)
- Sparsely connected networks of spiking neurons (Brunel 2000)
- Structure-dynamics relationships in bursting neuronal networks revealed (Mäki-Marttunen et al. 2013)
- Neuron-based control mechanisms for a robotic arm and hand (Singh et al 2017)
- Noise promotes independent control of gamma oscillations and grid firing (Solanka et al 2015)
- Systematic integration of data into multi-scale models of mouse primary V1 (Billeh et al 2020)

"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."

Top authors for NEST:

- Diesmann M (5)
- Migliore M (3)
- Geminiani A (3)
- Casellato C (3)
- Pedrocchi A (3)
- D'Angelo E (3)
- Schmidt M (3)
- van Albada SJ (3)
- Doya K (2)
- Sadeh S (2)

Top concepts studied with NEST:

- Activity Patterns (7)
- Methods (5)
- Spatio-temporal Activity Patterns (4)
- Simplified Models (4)
- Bursting (3)
- Oscillations (3)
- Connectivity matrix (3)
- Synchronization (3)
- Sensory processing (2)
- Orientation selectivity (2)

Top neurons studied with NEST:

- Abstract integrate-and-fire leaky neuron (11)
- Abstract integrate-and-fire adaptive exponential (AdEx) neuron (4)
- Hippocampus CA1 pyramidal GLU cell (2)
- Neocortex layer 2-3 interneuron (2)
- Abstract integrate-and-fire neuron (2)
- Abstract integrate-and-fire leaky neuron with exponential post-synaptic current (2)
- Neocortex L5/6 pyramidal GLU cell (2)
- Neocortex U1 interneuron basket PV GABA cell (1)
- Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell (1)
- Neocortex bitufted interneuron (1)

Top currents studied with NEST:

- I Na,p (2)
- I Na,t (2)
- I K (2)
- I M (2)
- I K,leak (1)
- I L high threshold (1)
- I h (1)
- I T low threshold (1)
- I Krp (1)
- I A (1)

Top references cited by these models:

- Diesmann M, Gewaltig M-O. (2007). NEST (Neural Simulation Tool) Scholarpedia. 2 (10)
- Brette R, Gerstner W. (2005). Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. Journal of neurophysiology. 94 (7)
- Brunel N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. Journal of computational neuroscience. 8 (6)
- Izhikevich EM. (2003). Simple model of spiking neurons. IEEE transactions on neural networks. 14 (5)
- Potjans TC, Diesmann M. (2014). The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model. Cerebral cortex (New York, N.Y. : 1991). 24 (5)