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IABC: A Toolbox for Intelligent Analysis of Brain Connectivity

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Abstract

Brain functional networks and connectivity have played an important role in exploring brain function for understanding the brain and disclosing the mechanisms of brain disorders. Independent component analysis (ICA) is one of the most widely applied data-driven methods to extract brain functional networks/connectivity. However, it is hard to guarantee the reliability of networks/connectivity due to the randomness of component order and the difficulty in selecting an optimal component number in ICA. To facilitate the analysis of brain functional networks and connectivity using ICA, we developed a MATLAB toolbox called Intelligent Analysis of Brain Connectivity (IABC). IABC incorporates our previously proposed group information guided independent component analysis (GIG-ICA), NeuroMark, and splitting-merging assisted reliable ICA (SMART ICA) methods, which can estimate reliable individual-subject neuroimaging measures for further analysis. After user inputs functional magnetic resonance imaging (fMRI) data of multiple subjects that are regularly organized (e.g., in Brain Imaging Data Structure (BIDS)) and clicks a few buttons to set parameters, IABC automatically outputs brain functional networks, their related time courses, and functional network connectivity of each subject. All these neuroimaging measures are promising for providing clues in understanding brain function and differentiating brain disorders.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 62076157 and 61703253 to YHD), Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province (to YHD), and the 1331 Engineering Project of Shanxi Province of China.

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  1. School of Computer and Information Technology, Shanxi University, Taiyuan, China

    Yuhui Du, Yanshu Kong & Xingyu He

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  1. Yuhui Du
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  2. Yanshu Kong
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Y.D. and Y.K. wrote the main manuscript text. All authors reviewed the manuscript.

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Du, Y., Kong, Y. & He, X. IABC: A Toolbox for Intelligent Analysis of Brain Connectivity. Neuroinform 21, 303–321 (2023). https://doi.org/10.1007/s12021-022-09617-z

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