A comparison of manual neuronal reconstruction from biocytin histology or 2-photon imaging: morphometry and computer modeling

Abstract

Accurate 3D reconstruction of neurons is vital for applications linking anatomy and physiology. Reconstructions are typically created using Neurolucida after biocytin histology (BH). An alternative inexpensive and fast method is to use freeware such as Neuromantic to reconstruct from fluorescence imaging (FI) stacks acquired using 2-photon laser-scanning microscopy during physiological recording. We compare these two methods with respect to morphometry, cell classification, and multicompartmental modeling in the NEURON simulation environment. Quantitative morphological analysis of the same cells reconstructed using both methods reveals that whilst biocytin reconstructions facilitate tracing of more distal collaterals, both methods are comparable in representing the overall morphology: automated clustering of reconstructions from both methods successfully separates neocortical basket cells from pyramidal cells but not BH from FI reconstructions. BH reconstructions suffer more from tissue shrinkage and compression artifacts than FI reconstructions do. FI reconstructions, on the other hand, consistently have larger process diameters. Consequently, significant differences in NEURON modeling of excitatory post-synaptic potential (EPSP) forward propagation are seen between the two methods, with FI reconstructions exhibiting smaller depolarizations. Simulated action potential backpropagation (bAP), however, is indistinguishable between reconstructions obtained with the two methods. In our hands, BH reconstructions are necessary for NEURON modeling and detailed morphological tracing, and thus remain state of the art, although they are more labor intensive, more expensive, and suffer from a higher failure rate due to the occasional poor outcome of histological processing. However, for a subset of anatomical applications such as cell type identification, FI reconstructions are superior, because of indistinguishable classification performance with greater ease of use, essentially 100% success rate, and lower cost.

AII amacrine cells: quantitative reconstruction and morphometric analysis of electrophysiologically identified cells in live rat retinal slices imaged with multi-photon excitation microscopy

“…However, because AII amacrine cells are coupled to each other and to ON-cone bipolar cells via gap junctions, it is a problem to use tracers like biocytin and Neurobiotin for single-cell visualization because they can diffuse into the network of coupled cells. In a recent study of visual cortical neurons (Blackman et al 2014) it was found that with respect to representing the overall morphology, the results obtained by biocytin histology and MPE imaging were very similar when the same cells were filled with both biocytin and a fluorescent dye during whole-cell recording. It was consistently found, however, that reconstructions based on biocytin histology facilitated tracing of more distal collaterals.…”

“…It was consistently found, however, that reconstructions based on biocytin histology facilitated tracing of more distal collaterals. It should be noted, however, that the fluorescent images used by Blackman et al (2014) were not processed with postacquisition deconvolution before reconstruction.…”

“…Cells can also be filled in live tissue (in vitro or in vivo) with tracers such as biocytin (Horikawa and Armstrong 1988) and Neurobiotin (Kita and Armstrong 1991) or with fluorescent dyes, using either sharp microelectrodes or patch pipettes. Importantly, these techniques offer the opportunity of correlated morphological and physiological investigations (Jaeger 2001; Blackman et al 2014). The use of tracers, however, requires post-processing with tissue fixation before the filled cells can be visualized, and is therefore often accompanied by variable tissue shrinkage which can compromise and distort exact morphological reconstruction (Jaeger 2001).…”

OFN-Based Brain Function Modeling

“…• Neurolucida after biocytin histology • Neuromantic to reconstruct from fluorescence imaging (FI) stacks acquired using 2-photon laser-scanning microscopy during physiological recording [3] …”

Error Analysis and Quantification in Neuron Simulations

“…Unfortunately, during staining an error due to tissue shrinkage can be introduced; [18], for example, observed a shrinkage of approximately 10% in the X and Y directions and 25% in slice thickness. The work of Blackman et al [1] investigated the effects of shrinkage and other reconstruction artefacts on the results of computer simulations conducted using the NEURON software. They consider two popular reconstruction techniques: biocytin histology and two-photon imaging.…”