Foutz TJ, Arlow RL, McIntyre CC. (2012). Theoretical principles underlying optical stimulation of a channelrhodopsin-2 positive pyramidal neuron. Journal of neurophysiology. 107 [PubMed]

• Optical stimulation of a channelrhodopsin-2 positive pyramidal neuron model (Foutz et al 2012) [Model]

Stefanescu RA, Shivakeshavan RG, Khargonekar PP, Talathi SS. (2013). Computational modeling of channelrhodopsin-2 photocurrent characteristics in relation to neural signaling. Bulletin of mathematical biology. 75 [PubMed]

• Computational modelling of channelrhodopsin-2 photocurrent characteristics (Stefanescu et al. 2013) [Model]

Talathi SS, Carney PR, Khargonekar PP. (2011). Control of neural synchrony using channelrhodopsin-2: a computational study. Journal of computational neuroscience. 31 [PubMed]

• Wang-Buzsaki Interneuron (Talathi et al., 2010) [Model]

Tomm C, Avermann M, Petersen C, Gerstner W, Vogels TP. (2014). Connection-type-specific biases make uniform random network models consistent with cortical recordings. Journal of neurophysiology. 112 [PubMed]

Vierling-Claassen D, Cardin JA, Moore CI, Jones SR. (2010). Computational modeling of distinct neocortical oscillations driven by cell-type selective optogenetic drive: separable resonant circuits controlled by low-threshold spiking and fast-spiking interneurons. Frontiers in human neuroscience. 4 [PubMed]

• Engaging distinct oscillatory neocortical circuits (Vierling-Claassen et al. 2010) [Model]

Williams JC et al. (2013). Computational optogenetics: empirically-derived voltage- and light-sensitive channelrhodopsin-2 model. PLoS computational biology. 9 [PubMed]

• Voltage and light-sensitive Channelrhodopsin-2 model (ChR2) (Williams et al. 2013) [Model]
• Voltage and light-sensitive Channelrhodopsin-2 model (ChR2-H134R) (Williams et al. 2013) (NEURON) [Model]