Morphological reconstructions were produced manually from multiple image stacks.
We examined this possibility by modeling the response to WD in 6 different L2/3 PCs for which full morphological reconstructions were obtained in vitro.
Imaging and morphological reconstructions were performed as previously described (Suter et al., 2013), by acquiring two-photon image stacks of neurons that had been biocytin filled during slice recordings, fixed, and processed for fluorescent labeling.
Numerical simulations for the single-compartment model were performed using code written in MatLab (MathWorks), whereas simulations for the multi-compartmental model based on the morphological reconstruction were performed using the simulation package NEURON [37, 38].
Fast algorithms use the comparison of the candidate extreme with its nearest 8-connected neighbors, while more sophisticated methods, like morphological reconstruction, are based on geodesic operators [8].
In some somatic whole-cell recording and all dendritic recording experiments, neurons were filled with biocytin (0.2 1 %, Sigma, St . Louis MO) during recording and morphological reconstruction was subsequently performed for further verification.
Biocytin-based morphological reconstructions would be necessary to test for differences in axonal anatomy, like the distinct flavors of L1 neurons that innervate the same or different cortical columns (Jiang et al. 2012. Nat Neuro. doi: 10.1038/nn.3305).
To quantify the degree of morphological disruption in eye epithelia, confocal stacks were imported into Image J (NIH), 3D reconstructions were made using Volume Viewer, and images were thresholded to gain area measurements of deep ElaV cells.
ML reconstructions were conducted using a single-rate Mk likelihood model for discrete morphological characters [ 96], which assumes that any particular change is equally probable.
Due to the tenuous nature of morphological characters, phylogenetic reconstructions are extremely difficult [ 6, 11].
The reconstructions were stable.
