Amatrudo JM et al. (2012). Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]

• Rhesus Monkey Layer 3 Pyramidal Neurons: V1 vs PFC (Amatrudo, Weaver et al. 2012) [Model]

Bauer R, Clowry GJ, Kaiser M. (2021). Creative destruction: a basic computational model of cortical layer formation Cerebral cortex (New York, N.Y. : 1991). 31 [PubMed]

• An agent-based computational model for cortical layer formation (Bauer et al 2021) [Model]

Bingham CS et al. (2020). ROOTS: An Algorithm to Generate Biologically Realistic Cortical Axons and an Application to Electroceutical Modeling Frontiers in Computational Neuroscience. 14

• ROOTS: An Algorithm to Generate Biologically Realistic Cortical Axons (Bingham et al 2020) [Model]

Bird AD, Cuntz H. (2016). Optimal Current Transfer in Dendrites. PLoS computational biology. 12 [PubMed]

Dan O, Hopp E, Borst A, Segev I. (2018). Non-uniform weighting of local motion inputs underlies dendritic computation in the fly visual system. Scientific reports. 8 [PubMed]

• Vertical system (VS) fly cells with biophysics (Dan et al 2018) [Model]

Deitcher Y et al. (2017). Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex. Cerebral cortex (New York, N.Y. : 1991). 27 [PubMed]

• 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex (Deitcher et al 2017) [Model]

Gruntman E, Romani S, Reiser MB. (2018). Simple integration of fast excitation and offset, delayed inhibition computes directional selectivity in Drosophila. Nature neuroscience. 21 [PubMed]

• Drosophila T4 neuron (Gruntman et al 2018) [Model]

Masoli S et al. (2024). Human Purkinje cells outperform mouse Purkinje cells in dendritic complexity and computational capacity. Communications biology. 7 [PubMed]

• Human and mouse Purkinje cell models (Masoli et al., 2024) [Model]

McColgan T et al. (2017). Dipolar extracellular potentials generated by axonal projections. eLife. 6 [PubMed]

• Dipolar extracellular potentials generated by axonal projections (McColgan et al 2017) [Model]

McDougal RA, Hines ML, Lytton WW. (2013). Water-tight membranes from neuronal morphology files. Journal of neuroscience methods. 220 [PubMed]

• Constructed Tessellated Neuronal Geometries (CTNG) (McDougal et al. 2013) [Model]

McDougal RA, Shepherd GM. (2015). 3D-printer visualization of neuron models. Frontiers in neuroinformatics. 9 [PubMed]

• 3D-printer visualization of NEURON models (McDougal and Shepherd, 2015) [Model]

Migliore M, Cavarretta F, Hines ML, Shepherd GM. (2014). Distributed organization of a brain microcircuit analyzed by three-dimensional modeling: the olfactory bulb. Frontiers in computational neuroscience. 8 [PubMed]

• 3D model of the olfactory bulb (Migliore et al. 2014) [Model]

Nanda S, Das R, Bhattacharjee S, Cox DN, Ascoli GA. (2018). Morphological determinants of dendritic arborization neurons in Drosophila larva. Brain structure & function. 223 [PubMed]

• Morphological determinants of dendritic arborization neurons in Drosophila larva (Nanda et al 2018) [Model]

Otopalik AG et al. (2017). Sloppy morphological tuning in identified neurons of the crustacean stomatogastric ganglion. eLife. 6 [PubMed]

• Sloppy morphological tuning in identified neurons of the crustacean STG (Otopalik et al 2017) [Model]

Papoutsi A, Kastellakis G, Poirazi P. (2017). Basal tree complexity shapes functional pathways in the prefrontal cortex. Journal of neurophysiology. 118 [PubMed]

• L5 PFC pyramidal neurons (Papoutsi et al. 2017) [Model]

Reed JD, Blackwell KT. (2021). Prediction of Neural Diameter From Morphology to Enable Accurate Simulation. Frontiers in neuroinformatics. 15 [PubMed]

• Reconstructed neuron (cerebellar, hippocampal, striatal) sims using predicted diameters (Reed et al) [Model]

Remme MWH, Rinzel J, Schreiber S. (2018). Function and energy consumption constrain neuronal biophysics in a canonical computation: Coincidence detection. PLoS computational biology. 14 [PubMed]

• Function and energy constrain neuronal biophysics in coincidence detection (Remme et al 2018) [Model]

Schneider CJ, Cuntz H, Soltesz I. (2014). Linking macroscopic with microscopic neuroanatomy using synthetic neuronal populations. PLoS computational biology. 10 [PubMed]

• Generation of granule cell dendritic morphology (Schneider et al. 2014) [Model]

Schwarzacher SW, Cuntz H, Jedlicka P, Beining M, Mongiat LA. (2017). T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells eLife.

• GC model (Beining et al 2017) [Model]
• Mature and young adult-born dentate granule cell models (T2N interface) (Beining et al. 2017) [Model]

Vladimirov N, Tu Y, Traub RD. (2012). Shortest Loops are Pacemakers in Random Networks of Electrically Coupled Axons. Frontiers in computational neuroscience. 6 [PubMed]

• CA1 pyramidal cell: reconstructed axonal arbor and failures at weak gap junctions (Vladimirov 2011) [Model]