Ermentrout GB, Terman DH. (2010). Mathematical Foundations of Neuroscience Interdisciplinary Applied Mathematics. 35

• Mathematical Foundations of Neuroscience (Ermentrout and Terman 2010) [Model]

Goldwyn JH, Shea-Brown E. (2011). The what and where of adding channel noise to the Hodgkin-Huxley equations. PLoS computational biology. 7 [PubMed]

• Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011) [Model]
• Stochastic versions of the Hodgkin-Huxley equations (Goldwyn, Shea-Brown 2011) (pylab) [Model]

Rakowski F, Karbowski J. (2017). Optimal synaptic signaling connectome for locomotory behavior in Caenorhabditis elegans: Design minimizing energy cost. PLoS computational biology. 13 [PubMed]

• Optimal synaptic assignment for locomotory behavior in C. elegans (Rakowski & Karbowski 2017) [Model]

Schmandt NT, Galán RF. (2012). Stochastic-shielding approximation of Markov chains and its application to efficiently simulate random ion-channel gating. Physical review letters. 109 [PubMed]

• Markov Chain-based Stochastic Shielding Hodgkin Huxley Model (Schmandt, Galan 2012) [Model]

Soudry D, Meir R. (2014). The neuronal response at extended timescales: a linearized spiking input-output relation. Frontiers in computational neuroscience. 8 [PubMed]

• Method for deriving general HH neuron model`s spiking input-output relation (Soudry & Meir 2014) [Model]