Naturalistic assessment of language and emotion

FNIBI / Current Projects, Grants / Aphasia, Current Projects, Diffusion MRI, Eye-tracking, Facial Recording, Functional MRI, Language Task, Neuroimaging, Participate in a Study, Presurgical Planning /

September 26, 2023

Naturalistic paradigms hold enormous potential for studying abnormal brain function. However, the development of clinical applications based on naturalistic approaches is still in its infancy. Our symposium at OHBM 2023 presented the challenges and recent advances in research directed at clinical translation of naturalistic paradigms for brain mapping. See here if you are interested in participating.

The project titled “Naturalistic Neuroimaging for Presurgical Language Mapping” funded by the NIH/NIDCD, aims to evaluate movie fMRI language mapping in neurosurgical patients with varying levels of language function. As part of this project, we evaluate the comprehension and expression elicited by movie-watching, versus conventional language mapping paradigms (covert sentence completion, covert antonym generation, passive story listening), in individuals with stroke-induced aphasia and healthy controls. Language performance is assessed after each paradigm with explicit language tasks based on the stimulus material presented in the paradigm, as well as with implicit measures. We predict that language performance will be comparable, and in most individuals with aphasia superior, for movie-watching relative to the other paradigms. See, our pilot data for this project in this paper.

DynAMos: “The Dynamic Affective Movie Clip Database for Subjectivity Analysis” is a new video database that includes holistic and dynamic emotion ratings from over 100 participants watching 22 affective movie clips. Recognizing the subjectivity inherent to emotional experiences, we provide in the database the full distribution of all participants’ ratings. We argue that this choice represents a paradigm shift with the potential to unlock new research directions, generate new hypotheses, and inspire novel methods in the Affective Computing community. There are several interdisciplinary use cases for the database: to provide dynamic norms for emotion elicitation studies (e.g., in psychology, medicine, and neuroscience), to train and test affective content analysis algorithms (e.g., for dynamic emotion recognition, video summarization, and movie recommendation), and to study subjectivity in emotional reactions (e.g., to identify moments of emotional ambiguity or ambivalence within movies, identify predictors of subjectivity, and develop personalized affective content analysis algorithms). The database is made freely available to researchers for noncommercial use at https://dynamos.mgb.org.