
Detection of irregular, transient fMRI activity in normal controls using 2dTCA: Comparison to event‐related analysis using known timing
Author(s) -
Morgan Victoria L.,
Gore John C.
Publication year - 2009
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.20760
Subject(s) - hum , transient (computer programming) , functional magnetic resonance imaging , pattern recognition (psychology) , event (particle physics) , cluster analysis , neuroscience , computer science , artificial intelligence , psychology , physics , quantum mechanics , operating system , art , performance art , art history
When events occur spontaneously during the acquisition of a series of images, traditional modeling methods for detecting functional MRI activation detection cannot be employed. The two‐dimensional temporal clustering algorithm, 2dTCA, has been shown to accurately detect random, transient activations in computer simulations without the use of known event timings. In this study we applied the 2dTCA technique to detect the timings and spatial locations of sparse, irregular, transient activations of the visual, auditory, and motor cortices in 12 normal controls. Experiments with one and two independent types of stimuli were employed. Event‐related activation using known timing was compared with event‐related activation using 2dTCA‐detected timing in individuals and across groups. The 2dTCA algorithm detected the activation from all presented stimuli in every subject. When compared with block‐design results using a measure of correlation between activation maps, no significant difference was found between the 2dTCA activation maps and the event‐related maps using known timing across all subjects. Therefore, 2dTCA has the potential to be an accurate and more practical method for detection of spontaneous, transient events using fMRI. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.