Neural patterns associated with mixed valence feelings differ in consistency and predictability throughout the brain

First-person spoken narratives elicit consistent event structures in the angular gyrus

Event segmentation theory explains how we parse a stream of continuous information into meaningful event models. Narratives are useful stimuli for studying this phenomenon, as the flow of information and the way we make meaning of them mirrors how we comprehend and make sense of our daily lives. Many studies have investigated the segmentation of audiovisual stimuli, such as movies, but only a handful of studies focused on how the brain parses auditory-only narrative. Using two stories with rich narrative features, we asked participants to listen to the story-recordings while being scanned with fMRI. We then recruited two separate groups of behavioral participants to parse the stories, either via transcript (visual-only) or recording (audio-only). Annotated boundaries from the two modalities were analyzed and used as behavioral benchmarks for the neural-behavioral comparison of event structures. We examined four regions of interest (angular gyrus, posterior cingulate cortex, early auditory cortex, and early visual cortex) and found that only the angular gyrus produced neural event structures that significantly matched with the behavioral event structures across both modalities and both stories. Our results indicate that activity in the angular gyrus is associated with the neural processes involved in parsing continuous narratives, particularly when these narratives are audio-only and contain ambiguous event transitions, rather than with changes in sensory-related features.

Feelings are Messy: The Feelings We Study in Affective Science Should Be Too

Affective science has taken up the challenge of building a bridge between basic affective science and practical applications. The articles in the Future of Affective Science issue lay out methodological and conceptual frameworks that allow us to expand affective science into real-world settings and to handle naturalistic methods. Along with these advances, accomplishing this goal will require additionally refocusing the types of experiences we study, and the measures of experience we are interested in. This paper explores the necessity for basic affective science to embrace the messy and complex nature of human emotion in order to bridge the gap between theoretical concepts and real-world applicability. Specifically, this involves studying experiences that do not fit as neatly into dominant conceptual frameworks, such as valenced scales and the most common discrete emotion categories, and that may be more difficult to measure or experimentally control. This makes the gap between affective science and real-world feelings larger. To move the field towards incorporating emotional complexity in an empirical manner, I propose measurement standards that err on the side of less fixed-choice options and using stimuli chosen for their potential to elicit highly complex responses over time within the same individual. Designing studies that can measure these experiences will push emotion theories to explain data they were not originally designed for, likely leading to refinement and collaboration. These approaches will help capture the full spectrum of human emotional experience, leading to a more nuanced and applicable understanding of affective science.