Abstract
Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.
Highlights
Understanding how the human brain processes information in complex everyday situations presents one of the ultimate challenges in cognitive neuroscience
Since we aimed to compare the results of independent component analysis (ICA) and voxel-wise analysis, we did not perform explicit multiple comparisons correction between the models in our analyses to avoid overestimating the differences of the two methods
Activation time course of IC1 follows smoothly that of the model of the auditory stimulus, the fit (R2) between the two being 0.6353 (p, 0.001)
Summary
Understanding how the human brain processes information in complex everyday situations presents one of the ultimate challenges in cognitive neuroscience. There are reports showing that results obtained under such settings do not always generalize to real life conditions. Using more natural stimuli assists in observing patterns of brain activation that are difficult to observe using simple stimuli. Bartels and Zeki [3] demonstrated that distinct brain areas exhibit more independent activity patterns while subjects are watching natural movies when compared to results obtained using short video clips and a blocked paradigm. What are currently lacking, and what has deterred neuroimaging studies using naturalistic stimuli, are wellestablished methods that allow analysis of the multidimensional brain responses to the features of the highly complex naturalistic stimulus. Our goal was to develop models and compare tools that enable one to study the human brain under ecologically valid naturalistic stimulus and task conditions
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call