Consistent resting-state networks across healthy subjects

Towards natural stimulation in fMRI--issues of data analysis

In search for suitable tools to study brain activation in natural environments, where the stimuli are multimodal, poorly predictable and irregularly varying, we collected functional magnetic resonance imaging data from 6 subjects during a continuous 8-min stimulus sequence that comprised auditory (speech or tone pips), visual (video clips dominated by faces, hands, or buildings), and tactile finger stimuli in blocks of 6-33 s. Results obtained by independent component analysis (ICA) and general-linear-model-based analysis (GLM) were compared. ICA separated in the superior temporal gyrus one independent component (IC) that reacted to all auditory stimuli and in the superior temporal sulcus another IC responding only to speech. Several distinct and rather symmetric vision-sensitive ICs were found in the posterior brain. An IC in the V5/MT region reacted to videos depicting faces or hands, whereas ICs in the V1/V2 region reacted to all video clips, including buildings. The corresponding GLM-derived activations in the auditory and early visual cortices comprised sub-areas of the ICA-revealed activations. ICA separated a prominent IC in the primary somatosensory cortex whereas the GLM-based analysis failed to show any touch-related activation. "Intrinsic" components, unrelated to the stimuli but spatially consistent across subjects, were discerned as well. The individual time courses were highly consistent in sensory projection cortices and more variable elsewhere. The ability to differentiate functionally meaningful composites of activated brain areas and to straightforwardly reveal their temporal dynamics renders ICA a sensitive tool to study brain responses to complex natural stimuli.