A neural network approach to detect functional MRI signal

被引：0

作者：

Frisone, F ^{[1
]}

Morasso, PG ^{[1
]}

Vitali, P ^{[1
]}

Rodriguez, G ^{[1
]}

Pilot, A ^{[1
]}

Sardanelli, F ^{[1
]}

Rosa, M ^{[1
]}

机构：

[1] Univ Genoa, DIST, I-16145 Genoa, Italy

来源：

NEURAL NETS - WIRN VIETRI-99 | 1999年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In fMRI the key problem of data analysis is to detect the weak BOLD signal component (about 2-5%) in the MR signal. Standard approaches, that typically use cross-correlation analysis or statistical parametric mapping, imply a presumptive knowledge of the expected stimulus-response pattern, which is not available in spontaneous events like hallucinations, sleep, or epileptic seizures. To evidence the possibility of analyzing these events by means of fMRI, we investigated a computational approach based on a self-organizing neural network (Neural Gas) that detects time-dependent alterations in the regional intensity of the functional signal.

引用

页码：127 / 132

页数：6

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