Kernel methods for fMRI pattern prediction

In this paper, we present an effective computational approach for learning patterns of brain activity from the fMRI data. The procedure involved correcting motion artifacts, spatial smoothing, removing low frequency drifts and applying multivariate linear and non-linear kernel methods. Two novel tec...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Yizhao Ni, Chu, C., Saunders, C.J., Ashburner, J.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Biological neural networks Brain Discrete cosine transforms Feature extraction Kernel Noise Training
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