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.

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. doi: 10.18178/ijpmbs.4.3.167-170