标题：
Multi-Objective Cognitive Model: a Supervised Approach for Multi-subject fMRI Analysis
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所属单位：
计算机科学与技术学院/人工智能学院/软件学院
发表刊物：
NEUROINFORMATICS
关键字：
Multi-objective cognitive model fMRI analysis Multivariate pattern Multi-objective optimization
摘要：
In order to decode human brain, Multivariate Pattern (MVP) classification generates cognitive models by using functional Magnetic Resonance Imaging (fMRI) datasets. As a standard pipeline in the MVP analysis, brain patterns in multi-subject fMRI dataset must be mapped to a shared space and then a classification model is generated by employing the mapped patterns. However, the MVP models may not provide stable performance on a new fMRI dataset because the standard pipeline uses disjoint steps for generating these models. Indeed, each step in the pipeline includes an objective function with independent optimization approach, where the best solution of each step may not be optimum for the next steps. For tackling the mentioned issue, this paper introduces Multi-Objective Cognitive Model (MOCM) that utilizes an integrated objective function for MVP analysis rather than just using those disjoint steps. For solving the integrated problem, we proposed a customized multi-objective optimization approach, where all possible solutions are firstly generated, and then our method ranks and selects the robust solutions as the final results. Empirical studies confirm that the proposed method can generate superior performance in comparison with other techniques.
ISSN号：
1539-2791
是否译文：
否
发表时间：
2019-04-01
合写作者：
张道强
通讯作者：
YOUSEFNEZHAD MUHAMMAD
发表时间：
2019-04-01
学位：工学博士学位
所在单位：计算机科学与技术学院/人工智能学院/软件学院