Parametric fMRI analysis of videos of variable arousal levels reveals different dorsal vs ventral activation preferences between autism and controls

Author(s):  
Daniel Agostinho ◽  
Rita Correia ◽  
Isabel Catarina Duarte ◽  
Daniela Sousa ◽  
Rodolfo Abreu ◽  
...  
Keyword(s):  
Author(s):  
Anders Eklund ◽  
Paul Dufort ◽  
Mattias Villani ◽  
Stephen LaConte
Keyword(s):  

1999 ◽  
Vol 44 (s2) ◽  
pp. 181-183
Author(s):  
S.N. Erné ◽  
H.-P. Müller ◽  
H.G. Kammrath ◽  
R. Tomczak ◽  
A. Wunderlich

2004 ◽  
Vol 14 (04) ◽  
pp. 217-228 ◽  
Author(s):  
ANKE MEYER-BÄSE ◽  
OLIVER LANGE ◽  
AXEL WISMÜLLER ◽  
HELGE RITTER

Data-driven fMRI analysis techniques include independent component analysis (ICA) and different types of clustering in the temporal domain. Since each of these methods has its particular strengths, it is natural to look for an approach that unifies Kohonen's self-organizing map and ICA. This is given by the topographic independent component analysis. While achieved by a slight modification of the ICA model, it can be at the same time used to define a topographic order (clusters) between the components, and thus has the usual computational advantages associated with topographic maps. In this contribution, we can show that when applied to fMRI analysis it outperforms FastICA.


PLoS ONE ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. e0191098 ◽  
Author(s):  
Léa A. S. Chauvigné ◽  
Michel Belyk ◽  
Steven Brown

NeuroImage ◽  
2005 ◽  
Vol 24 (2) ◽  
pp. 603-606 ◽  
Author(s):  
Daniel B. Rowe ◽  
Brent R. Logan
Keyword(s):  

2011 ◽  
Vol 42 (2) ◽  
pp. 98-106 ◽  
Author(s):  
Ali Bayram ◽  
Zubeyir Bayraktaroglu ◽  
Esin Karahan ◽  
Basri Erdogan ◽  
Basar Bilgic ◽  
...  

Sankhya B ◽  
2017 ◽  
Vol 79 (2) ◽  
pp. 361-388 ◽  
Author(s):  
Nilotpal Sanyal ◽  
Marco A. R. Ferreira

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