" ... In this work, we develop and apply an automated, stepwise method for fitting a neuron model to data with fine spatial resolution, such as that achievable with voltage sensitive dyes (VSDs) and Ca2+ imaging. ... We apply our method to simulated data from layer 5 pyramidal cells (L5PCs) and construct a model with reduced neuronal morphology. We connect the reduced-morphology neurons into a network and validate against simulated data from a high-resolution L5PC network model. ..."
Model Type: Neuron or other electrically excitable cell
Region(s) or Organism(s): Neocortex
Cell Type(s): Neocortex L5/6 pyramidal GLU cell
Currents: I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I M; I h; I K,Ca; I Calcium; I A, slow
Simulation Environment: NEURON; NEURON (web link to model); Python; NeuroML
Implementer(s): Maki-Marttunen, Tuomo [tuomomm at uio.no]; Metzner, Christoph [c.metzner at herts.ac.uk]
References:
Hay E, Hill S, Schürmann F, Markram H, Segev I. (2011). Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties. PLoS computational biology. 7 [PubMed]
Hay E, Segev I. (2015). Dendritic Excitability and Gain Control in Recurrent Cortical Microcircuits. Cerebral cortex (New York, N.Y. : 1991). 25 [PubMed]
Mäki-Marttunen T et al. (2018). A stepwise neuron model fitting procedure designed for recordings with high spatial resolution: Application to layer 5 pyramidal cells. Journal of neuroscience methods. 293 [PubMed]