Presenting SpikeE

This is a post for all Neurosciences folks that are attending the Society for Neuroscience 2012 meeting at New Orleans. I (along with some of my lab colleagues) will be presenting SpikeE (SpikeExtractor) over there. SpikeE is a general Matlab framework to perform data analysis on imaging data. But it is also a complete developing environment for Matlab programmers to develop elementary pieces of computations that can be batch process on large datasets. It provides all the tools to only focus on your particular computational task and forget about developing all time consuming steps (like data loading, saving or visualization).

To locate my poster, please visit SFN abstract planner. I am very excited to meet you all and discuss potential application of SpikeE.

Here is a copy of our abstract :

The combination of new genetically encoded fluorescent calcium-indicators, fluorescence imaging techniques, and neuronal labeling strategies has made it possible to monitor the calcium dynamics of hundreds of individual neurons over days and weeks in awake behaving animals. Analyses of the resulting data sets are often challenging due to the high dimensionality of the movie data and the number of image processing steps required to extract neuronal traces. Standardized algorithms and image analysis procedures for extraction of neuronal activity would not only ease the burden of analysis but also facilitate comparisons across experiments and different laboratories.
Here we present SpikeExtractor (SpikeE), a generalized MATLAB graphical user interface (GUI) platform for analysis of neuronal imaging data that may be obtained using any of a variety of imaging modalities. SpikeE establishes a standardized data format and a set of rules for the interaction of individual analysis programs termed Apps. Each App performs an elemental piece of the computation and comes with its own control GUI. The SpikeE core handles communication between the various Apps. We have developed a substantial set of Apps to load data from multiple image acquisition streams, extract neurons’ dynamical traces, and display the data interactively. SpikeE also allows batch processing of Apps, whereby the user can create a list of programs and settings and run these via a ‘single-click’ automated analysis. To ensure flexibility and accessibility for many users, Apps are intuitive and simple to design, placing a wide variety of analysis functions within reach of users who may not be expert at computer programming. Thus, SpikeE should help reduce the duplication of efforts across multiple laboratories, makes advanced capabilities for analysis of movie data and neuronal dynamics readily available to non-experts, and provides a standardized interface and set of analysis routines that will ease comparisons across research groups.

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