Abstract
Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.
Highlights
The ability to reliably decode brain state from recordings of neural activity represents a major neuroscientific frontier
The hemodynamic response measured in functional magnetic resonance imaging (fMRI) only indirectly captures neural activity and does not allow for analysis of fast oscillatory activity
Low-resolution source localization analysis suggests that the components of correlated scalp activity are consistent with sources in the cingulate and orbitofrontal cortices. These results suggest that modulation of cortical processing during attentionand emotion-laden states leads to the observed between-view correlation, and such moments of “engagement”may be decoded from the EEG down to a 1-s time resolution
Summary
The ability to reliably decode brain state from recordings of neural activity represents a major neuroscientific frontier. The majority of brain decoding research has employed the event-related design (Spiers and Maguire, 2007) in which neural activity is regressed onto discrete event variables, allowing one to compute the neural correlates of a predefined and presumably fixed brain state. In the absence of event markers, one possible solution is to regress the neural activity of one subject onto that of another, utilizing the correlation between multiple records to inform the state variables. Recent studies employing functional magnetic resonance imaging (fMRI) have revealed strong voxel-wise inter-subject correlations (ISC) across participants exposed to a common naturalistic stimulus (i.e., movie clips; Hasson et al, 2004, 2010; Hanson et al, 2009). The hemodynamic response measured in fMRI only indirectly captures neural activity and does not allow for analysis of fast oscillatory activity ( it does correlate with oscillatory activity in the gamma band; Mukamel et al, 2005)
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