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NAS: Neuron Analyzer Suite for Automatic Analysis of Neuronal Activities from Calcium Imaging Data

Mohamed Hamed1, Jonathan Odul2, Andrew Steven Miller3, Koichi Kawakami3, and Kitamoto Asanobu3
1 Center for bioinformatics (CBI), Saarland University, Saarbrucken, Germany
Institute for Biostatistics and Informatics and Ageing Research, Rostock Uni Medical Center, Rostock, Germany
2 National Institute of Informatics (NII), Tokyo, Japan
3 National Institute of Genetics (NIG), Mishima, Japan
Abstract—Neuronal activities can be visualized through functional Multi-neuron Calcium Imaging (fMCI) using fluorescence microscopes. However, the necessary components of data processing pipelines have been separately implemented and not well integrated previously. To this end, this paper introduces a Neuron Analyzer Suite (NAS) that integrates several components, from image preprocessing to inferred functional connectivity, in order to establish a processing pipeline for calcium imaging data. NAS is composed of three main modules. First, a motion removal module employing image registration is applied to raw images to remove artifacts caused by the motion of model organisms. Second, a neuron segmentation module is utilized to segment neurons and to extract their time series signals. Third, a neuron connectivity module is applied to time series signals to bi/cluster neurons based on their activity patterns and to reverse engineer their putative functional connectivity using a Bayesian learning approach. The NAS suite was tested on zebrafish calcium images to infer functional connectivity that may change over time.

Index Terms—calcium imaging data, neuron activity, neuron connectivity, and bayesian network

Cite: Mohamed Hamed, Jonathan Odul, Andrew Steven Miller, Koichi Kawakami, and Kitamoto Asanobu, "NAS: Neuron Analyzer Suite for Automatic Analysis of Neuronal Activities from Calcium Imaging Data" International Journal of Pharma Medicine and Biological Sciences, Vol. 4, No. 3, pp. 167-170, July 2015.
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