An fMRI dataset in response to “The Grand Budapest Hotel”, a socially-rich, naturalistic movie

Naturalistic stimuli evoke strong, consistent, and information-rich patterns of brain activity, and engage large extents of the human brain. They allow researchers to compare highly similar brain responses across subjects, and to study how complex representations are encoded in brain activity. Here, we describe and share a dataset where 25 subjects watched part of the feature film “The Grand Budapest Hotel” by Wes Anderson. The movie has a large cast with many famous actors. Throughout the story, the camera shots highlight faces and expressions, which are fundamental to understand the complex narrative of the movie. This movie was chosen to sample brain activity specifically related to social interactions and face processing. This dataset provides researchers with fMRI data that can be used to explore social cognitive processes and face processing, adding to the existing neuroimaging datasets that sample brain activity with naturalistic movies

The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension

The “Narratives” collection aggregates a variety of functional MRI datasets collected while human subjects listened to naturalistic spoken stories. The current release includes 345 subjects, 891 functional scans, and 27 diverse stories of varying duration totaling ~4.6 hours of unique stimuli (~43,000 words). This data collection is well-suited for naturalistic neuroimaging analysis, and is intended to serve as a benchmark for models of language and narrative comprehension. We provide standardized MRI data accompanied by rich metadata, preprocessed versions of the data ready for immediate use, and the spoken story stimuli with time-stamped phoneme- and word-level transcripts. All code and data are publicly available with full provenance in keeping with current best practices in transparent and reproducible neuroimaging

Unsupervised Classification Reveals Degenerate Neural Representations of Emotion

Neural degeneracy refers to the idea that distinct neural systems are capable of performing the same functions (Noppeney, Friston, & Price, 2004). Consistent with neural degeneracy, the Theory of Constructed Emotion (TCE) suggests that emotions and other mental states arise from combinations of the brain’s domain-general intrinsic networks such as the default mode network, salience network, and frontoparietal control network (Clark-Polner, Johnson, & Barrett, 2017). A key prediction of degeneracy and the TCE is that the same emotion can emerge from distinct patterns of connectivity across time or across individuals (Barrett, 2017). This project specifically investigates the principle of neural degeneracy in emotion for the first time using a data-driven model building algorithm with unsupervised classification (S-GIMME; Gates, Lane, Varangis, Giovanello, & Guskiewicz, 2017) to quantify distinct patterns of between-network connectivity during self-generated experiences of anxiety and anger. Twenty-four subjects underwent an fMRI experiment in which they listened to unpleasant music and self-generated experiences of anxiety and anger. The hypotheses of this experiment were tested in four consecutive analysis steps. The first analysis step revealed that the S-GIMME procedure could roughly reproduce the experimental conditions in the present experiment by subgrouping individuals based on patterns of connectivity that differentiated anger and anxiety. The second analysis step revealed that this variation could be further subdivided into degenerate neural pathways within each emotion category. The third analysis step showed that subgroups revealed during the anger and anxiety conditions are distinct from those found during a task-positive control condition in which participants listened to neutral music but did not generate an emotional experience. Finally, the fourth analysis step provided a more stringent test of the degeneracy hypothesis by showing that distinct patterns of connectivity revealed in the previous analyses are not the result of stable individual differences that would also be present at rest. Taken together, these analyses show that different patterns of connectivity are associated with the experience of the same emotion.Doctor of Philosoph