Many neuron morphologies in NeuroMorpho.org do not contain accurate dendritic diameters that are needed for simulations. We used a set of archives which did have realistic morphologies to derive equations predicting dendritic diameter, and to create morphologies using the predictions. The equations and new morphologies are derived by 1. extracting morphology features from swc files (morph_feature_extract.py) 2. using multiple regression to derive equations predicting diameter, (morph_feature_extract.py ) 3. using the equations to create the new morphology files from original swc file (shape_shifter.py). The python programs are all available from github.com/neurord/ShapeShifter We simulated the original morphologies and the morphologies with predicted diameter in Moose, evaluating the response to current injection and synaptic input. The code provided implements those simulations
Model Type: Neuron or other electrically excitable cell
Cell Type(s): Hippocampus CA1 pyramidal GLU cell; Cerebellum Purkinje GABA cell; Striatal projection neuron
Receptors: AMPA
Simulation Environment: MOOSE/PyMOOSE
Implementer(s): Blackwell, Avrama [avrama at gmu.edu]; Reed, Jonathon
References:
Reed JD, Blackwell KT. (2021). Prediction of Neural Diameter From Morphology to Enable Accurate Simulation. Frontiers in neuroinformatics. 15 [PubMed]