Alle H, Roth A, Geiger JR. (2009). Energy-efficient action potentials in hippocampal mossy fibers. Science (New York, N.Y.). 325 [PubMed]

• Action potential reconstitution from measured current waveforms (Alle et al. 2009) [Model]

Falconbridge MS, Stamps RL, Badcock DR. (2005). A Simple Hebbian/Anti-Hebbian Network Learns the Sparse, Independent Components of Natural Images Neural Comput. 18

Hallermann S, de Kock CP, Stuart GJ, Kole MH. (2012). State and location dependence of action potential metabolic cost in cortical pyramidal neurons. Nature neuroscience. 15 [PubMed]

• State and location dependence of action potential metabolic cost (Hallermann et al., 2012) [Model]

Johansson C, Lansner A. (2007). Towards cortex sized artificial neural systems. Neural networks : the official journal of the International Neural Network Society. 20 [PubMed]

Johansson C, Lansner A. (2007). Imposing biological constraints onto an abstract neocortical attractor network model. Neural computation. 19 [PubMed]

Ju H, Hines ML, Yu Y. (2016). Cable energy function of cortical axons. Scientific reports. 6 [PubMed]

Kelley C, Newton AJH, Hrabetova S, McDougal RA, Lytton WW. (2022). Multiscale Computer Modeling of Spreading Depolarization in Brain Slices eNeuro. 9 [PubMed]

• Spreading Depolarization in Brain Slices (Kelley et al. 2022) [Model]

Kilinc D, Demir A. (2017). Noise in Neuronal and Electronic Circuits: A General Modeling Framework and Non-Monte Carlo Simulation Techniques. IEEE transactions on biomedical circuits and systems. 11 [PubMed]

• A neuronal circuit simulator for non Monte Carlo analysis of neuronal noise (Kilinc & Demir 2018) [Model]

Kilinc D, Demir A. (2018). Spike timing precision of neuronal circuits. Journal of computational neuroscience. 44 [PubMed]

• A neuronal circuit simulator for non Monte Carlo analysis of neuronal noise (Kilinc & Demir 2018) [Model]

King PD, Zylberberg J, DeWeese MR. (2013). Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1. The Journal of neuroscience : the official journal of the Society for Neuroscience. 33 [PubMed]

• Inhibitory cells enable sparse coding in V1 model (King et al. 2013) [Model]

Latham PE, Nirenberg S. (2004). Computing and stability in cortical networks. Neural computation. 16 [PubMed]

Lundqvist M, Rehn M, Djurfeldt M, Lansner A. (2006). Attractor dynamics in a modular network model of neocortex. Network (Bristol, England). 17 [PubMed]

Olshausen BA, Field DJ. (2005). How close are we to understanding v1? Neural computation. 17 [PubMed]

Platkiewicz J, Brette R. (2011). Impact of fast sodium channel inactivation on spike threshold dynamics and synaptic integration. PLoS computational biology. 7 [PubMed]

• Impact of fast Na channel inact. on AP threshold & synaptic integration (Platkiewicz & Brette 2011) [Model]

Rehn M, Sommer FT. (2007). A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. Journal of computational neuroscience. 22 [PubMed]

Uchizawa K, Douglas R, Maass W. (2006). On the computational power of threshold circuits with sparse activity. Neural computation. 18 [PubMed]

Wei Y, Ullah G, Ingram J, Schiff SJ. (2014). Oxygen and seizure dynamics: II. Computational modeling. Journal of neurophysiology. 112 [PubMed]