title: Cortical Response Similarities Predict which Audiovisual Clips Individuals Viewed, but Are Unrelated to Clip Preference.
abstract: Cortical responses to complex natural stimuli can be isolated by examining the relationship between neural measures obtained while multiple individuals view the same stimuli. These inter-subject correlation's (ISC's) emerge from similarities in individual's cortical response to the shared audiovisual inputs, which may be related to their emergent cognitive and perceptual experience. Within the present study, our goal is to examine the utility of using ISC's for predicting which audiovisual clips individuals viewed, and to examine the relationship between neural responses to natural stimuli and subjective reports. The ability to predict which clips individuals viewed depends on the relationship of the EEG response across subjects and the nature in which this information is aggregated. We conceived of three approaches for aggregating responses, i.e. three assignment algorithms, which we evaluated in Experiment 1A. The aggregate correlations algorithm generated the highest assignment accuracy (70.83% chance = 33.33%) and was selected as the assignment algorithm for the larger sample of individuals and clips within Experiment 1B. The overall assignment accuracy was 33.46% within Experiment 1B (chance = 06.25%), with accuracies ranging from 52.9% (Silver Linings Playbook) to 11.75% (Seinfeld) within individual clips. ISC's were significantly greater than zero for 15 out of 16 clips, and fluctuations within the delta frequency band (i.e. 0-4 Hz) primarily contributed to response similarities across subjects. Interestingly, there was insufficient evidence to indicate that individuals with greater similarities in clip preference demonstrate greater similarities in cortical responses, suggesting a lack of association between ISC and clip preference. Overall these results demonstrate the utility of using ISC's for prediction, and further characterize the relationship between ISC magnitudes and subjective reports.
authors.affiliation: The Mind Research Network, Albuquerque, New Mexico, United States of America.
authors.forename: David A
authors.initials: DA
authors.lastname: Bridwell
authors.affiliation: The Mind Research Network, Albuquerque, New Mexico, United States of America; Department of Mathematics and Statistics, University of New Mexico, Albuquerque, New Mexico, United States of America; Department of Biology, IMSD, University of New Mexico, Albuquerque, New Mexico, United States of America; Program in Genetics and Genomics, Duke University, North Carolina, United States of America.
authors.forename: Cullen
authors.initials: C
authors.lastname: Roth
authors.affiliation: The Mind Research Network, Albuquerque, New Mexico, United States of America.
authors.forename: Cota Navin
authors.initials: CN
authors.lastname: Gupta
authors.affiliation: The Mind Research Network, Albuquerque, New Mexico, United States of America; Department of ECE, University of New Mexico, Albuquerque, New Mexico, United States of America.
authors.forename: Vince D
authors.initials: VD
authors.lastname: Calhoun
mesh_terms: D000328:Adult; D000465:Algorithms; D001303:Auditory Cortex / Q000502:physiology*; D003071:Cognition / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D013525:Surgical Instruments; D014793:Visual Cortex / Q000502:physiology*; D055815:Young Adult