In this Lab to Marketplace proposal, we aim to develop the MBF SpineStudio software incorporating the innovative, laboratory-based NeuronStudio software created at the Mount Sinai School of Medicine. Our SpineStudio software will enable automated detection, reconstruction and morphological classification of the structural analysis of dendritic spines. By creating this commercial software, we will improve the existing technology by providing validated, supported, and fully-documented software for automated 3D quantitative dendritic spine analysis. This software will integrate the specific advantages of the NeuronStudio software for a combination of neuron labeling, imaging (including in vivo), and image pre- processing techniques applied by the user without requiring expert knowledge in software programming. The software product will offer automated detection, reconstruction, and separate classification of complex spines (cup-shaped, multi-headed or branched, filopodia). Providing this innovative functionality will help research in important fields such as neurodegenerative diseases, learning, and memory.
Structural changes that occur in dendritic spines, the smallest element of neuronal anatomy, are hypothesized to underlie the processing and storage of information. Thus, dendritic spines have become a central target in research focusing on learning and memory and, in particular, on the prevention of cognitive decline in neurodegenerative diseases. Our proposed SpineStudio software will enable automated detection, reconstruction and morphological classification of the structural analysis of these dendritic spines. By creating a commercial product, incorporating the innovative NeuronStudio software, this will accelerate the pace of discovery and understanding of dendritic spines research by providing a reliable, robust and fully-supported research tool that is fully validated and continually developed.
| Dickstein, Dara L; Dickstein, Daniel R; Janssen, William G M et al. (2016) Automatic Dendritic Spine Quantification from Confocal Data with Neurolucida 360. Curr Protoc Neurosci 77:1.27.1-1.27.21 |
