Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4351615 | Neuroscience Research | 2011 | 8 Pages |
In human brain imaging with naturalistic stimuli, hemodynamic responses are difficult to predict and thus data-driven approaches, such as independent component analysis (ICA), may be beneficial. Here we propose inter-subject correlation (ISC) maps as stimulus-sensitive functional templates for sorting the independent components (ICs) to identify the most stimulus-related networks without stimulus-dependent temporal covariates. We collected 3-T functional magnetic resonance imaging (fMRI) data during perception of continuous audiovisual speech. Ten adults viewed a video, in which speech intelligibility was varied by altering the sound level. Five ICs with strongest overlap with the ISC map comprised auditory and visual cortices, and the sixth was a left-hemisphere-dominant network (left posterior superior temporal sulcus, inferior frontal gyrus, anterior superior temporal pole, supplementary motor cortex, and right angular gyrus) that was activated stronger during soft than loud speech. Corresponding temporal-model-based analysis revealed only temporal- and parietal-lobe activations without involvement of the anterior areas. The performance of the ISC-based IC selection was confirmed with fMRI data collected during free viewing of movie. Since ISC–ICA requires no predetermined temporal models on stimulus timing, it seems feasible for fMRI studies where hemodynamic variations are difficult to model because of the complex temporal structure of the naturalistic stimulation.
► Inter-subject correlation map provides a data-driven functional template for ordering the ICs. ► ISC–ICA can distinguish brain networks, whose activity is modulated by external stimulation. ► Spatiotemporal sorting of ICs can further emphasize stimulus-related networks. ► During speech perception, ISC–ICA revealed activation of a left-hemisphere-dominant sensorimotor network, GLM only the posterior parts of it. ► ISC–ICA is especially useful for naturalistic setups applying continuous stimulation.