Social cerebellum in goal-directed navigation

ABSTRACT

The posterior cerebellum is responsible for the understanding and learning of sequences of actions by others, which are a prerequisite for social understanding. This study investigates this cerebellar function while navigating toward a goal in a social context. Participants undertook a novel social navigation task requiring them to memorize and subsequently reproduce a protagonist’s trajectory through a grid toward a desirable goal. As a nonsocial control condition, a ball underwent the same trajectory by passively rolling through the grid toward the same endpoint. To establish that memorizing and reproducing a trajectory is a critical cerebellar function, two non-sequencing control conditions were created, which involved the observation only of the trajectory by the protagonist or ball. Our results showed that the posterior cerebellar Crus II was involved in memorizing both social and nonsocial trajectories, along with the parahippocampal gyrus and other cortical areas involved in social cognition. As hypothesized, cerebellar Crus I was more active when memorizing social as opposed to nonsocial trajectories. Moreover, cerebellar Crus I and II, and lobule VI, were activated when reproducing both social and nonsocial trajectories. These findings highlight the involvement of the posterior cerebellar Crus in supporting human goal-directed social navigation.

KEYWORDS:

• Social navigating
• social sequence learning
• mentalizing
• posterior cerebellum
• goal-directed behavior

Highlights

• The posterior cerebellar Crus is involved in sequence-based social navigation, along with the parahippocampal gyrus and social cortical areas.

• Crus II is recruited during memorizing social and non-social sequential trajectories

• Crus I is specifically recruited to memorize social trajectories.

• Cerebellar Crus I and II, and lobules VI are recruited when reproducing social and non-social sequencing trajectories.

Supplementary material

Supplemental data for this article can be accessed here.

CRediT authorship contribution statement

Meijia Li: Conceptualization, Methodology, Software, Formal analysis, Investigation, Visualization, Writing - original draft, Writing - review & editing. Qianying Ma: Writing - review & editing. Kris Baetens: Writing - review & editing. Min Pu: Writing - review & editing. Natacha Deroost: Writing - review & editing. Chris Baeken: Writing - review & editing. Elien Heleven: Writing - review & editing. Frank Van Overwalle: Conceptualization, Methodology, Software, Writing - Review & Editing, Supervision, Funding acquisition.

Acknowledgments

The authors gratefully acknowledge Naem Patemoshela Haihambo and Eline Maesschalck Cornand for their contribution to the acquisition of the MR data.

Disclosure statement

The authors report no personal or financial conflicts of interest related to the research reported herein.

Data and code are available

All requested (pseudonymized or anonymous) data are available upon request to Meijia Li at [email protected], excluding data that allow identifying individual participants. If relevant, all manuals and code for processing the data is also available together with the data. The (pseudonymized) data are stored at a digital archive of the Vrije Universiteit Brussel, Belgium.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the China Scholarship Council (CSC) award to Meijia Li and Strategic Research Program SRP57 from the Vrije Universiteit Brussel awarded to Frank Van Overwalle;China Scholarship Council;Strategic Research Program [57];