2018 Conference on Cognitive Computational Neuroscience

5-8 September 2018    Philadelphia, Pennsylvania

Technical Program

Paper Detail

Paper: PS-2A.40
Session: Poster Session 2A
Location: Symphony/Overture
Session Time: Friday, September 7, 17:15 - 19:15
Presentation Time:Friday, September 7, 17:15 - 19:15
Presentation: Poster
Publication: 2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania
Paper Title: Mapping the Human Cerebellum
Manuscript:  Click here to view manuscript
DOI: https://doi.org/10.32470/CCN.2018.1146-0
Authors: Maedbh King, Rich Ivry, University of California, Berkeley, United States; Joern Diedrichsen, Western University, Canada
Abstract: Thirty years of research have provided compelling evidence that the human cerebellum is engaged in a wide array of cognitive tasks. Understanding the functional contributions of this structure to cognition remains a subject of considerable debate. Previous studies have generally taken a piecemeal approach, employing a limited number of tasks to test specific hypotheses. Here we take a different approach, seeking to identify a detailed characterization of functional subdivisions across the extent of the cerebellar cortex. During fMRI scanning, 24 participants performed a large task battery designed to tap into a broad range of cognitive processes (e.g., attention, memory, social cognition). These heterogeneous task patterns were leveraged to derive a multi-task parcellation of the cerebellum. We then developed a novel tool to evaluate the strength of functional boundaries, employing out-of-sample generalization. We tested our novel, multi-task parcellation, along with existing resting state and anatomical parcellations. We find that the multi-task parcellation successfully identifies functional sub-regions within the cerebellum, and provides a significant improvement over boundaries identified with resting state data. Surprisingly, lobular boundaries, the current standard for assigning functional activations, do not coincide with functional boundaries. The multi-task parcellation offers a novel functional map for analyzing and reporting cerebellar activations.