Neuronal Spines Tracking and Analysis for Time-Lapse, 3D Optical Microscopy

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We propose to develop an integrated computational system to track and analyze neuronal dendrites and spines observed in 3D time-lapse optical microscopy and manage all the data. The proposed work will overcome one barrier in neuroscience research, i.e.,lack of computational method to quantitatively analyze large-scale time-lapse image data. Current manual analysis is confined to small datasets and qualitatively interpretation of 3D images. Detailed neurological changes may be missed by manual analysis. Also results of manual analysis are not immediately ready for data management and analysis because of long hours it takes to store manual analysis results to a database. Thus searches for treatment of neurodegenerative conditions and so on may be hindered. Our plan to develop the integrated computational system can increase the throughput of neuronal image analysis in neuroscience. The system will automatically track and analyze neuronal dendrites and spines. Dendrites and spines are two structures of neuronal cell that manifest changes in neurodegenerative conditions. For example, researches have shown that spines change over time, may appear and disappear entirely. The newest technology is to perform time-lapse imaging of the dendrites and spines to obtain their temporal behavior. The integrated computational system can track multiple spines over the time course and extract important features about them. The features include their length, width, volume, etc. All these features are then saved in common file format and can readily be ported into the built-in database for statistical analysis. Therefore, the proposed work enables neuroscientists to conduct large-scale time-lapse study and track neuronal changes at more time points. All can be critical to finding a cure to neurological conditions. Today's microscopy can image neuronal cells in three-dimensions over a period of time. However use of data is limited because there is no computer-based tool to analyze and systematically manage the data. We plan to develop a computed-based tool to increase the efficiency and effectiveness of the data. Public Health Relevance: This project enables researchers to quickly screen hundreds of neuron images to study diseases and identify possible new drugs. Overall, the project has the impact of facilitating therapy development for neurological conditions such as Alzheimer's disease.