頁籤選單縮合
題 名 | A New Mathematical Approach for Detection of Active Area in Human Brain fMRI Using Nonlinear Model |
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作 者 | Taalimi, Ali; Fatemizadeh, Emad; | 書刊名 | Biomedical Engineering: Applications, Basis and Communications |
卷 期 | 22:5 2010.10[民99.10] |
頁 次 | 頁409-418 |
分類號 | 414.93 |
關鍵詞 | Functional magnetic resonance imaging; Activation detection; Nonlinear auto regressive model; |
語 文 | 英文(English) |
英文摘要 | Abstract: Functional magnetic resonance imaging (fMRI) is widely-used for detection of the brain's neural activity. The signals and images acquired through this imaging technique demonstrate the human brain's response to pre-scheduled tasks. Several studies on blood oxygenation level-dependent (BOLD) signal responses demonstrate nonlinear behavior in response to a stimulus. In this paper we propose a new mathematical approach for modeling BOLD signal activity, which is able to model nonlinear and time variant behaviors of this physiological system. We employ the Nonlinear Auto Regressive Moving Average (NARMA) model to describe the mathematical relationship between output signals and predesigned tasks. The model parameters can be used to distinguish between rest and active states of a brain region. We applied our proposed method for active region detection on real as well as simulated data sets. The results show superior performance in comparison with existing methods. |
本系統中英文摘要資訊取自各篇刊載內容。