Tianjiao Zhang¹, Jack Gallant¹; ¹UC Berkeley

Actively navigating through the natural world requires close coordination of perception, planning, and motor actions. Multiple regions in the human cerebral cortex have been implicated in representing navigation-related information. Rodent studies suggest that navigation-related information is represented in multiple overlapping spatial gradients that extend across functional regions (Minderer et al., 2019, Tseng et al., 2022). Is this organizational principle shared by the navigation network in the human cerebral cortex? How is the navigation network related to other networks, such as those that process visual inputs and produce motor outputs? To address these questions, we used fMRI to record brain activity from six subjects performing a taxi-driver task in a naturalistic virtual world (110-180 minutes of data per subject). We extracted 28,161 features across 38 visual-, motor-, and navigation-related feature spaces from the experiment recordings, and used banded ridge regression to fit encoding models for all feature spaces simultaneously. To identify the network of cortical regions that represent navigation-related information, model connectivity (MC) was used to hierarchically cluster the voxel weight vectors. MC identified a network of 11 regions in the visual, parietal, and prefrontal cortices that each represent a distinct combination of navigation-related features. To determine its organizational principles, UMAP was used to recover a functional space for the navigation network. In this space, the navigation regions are organized into a continuous functional distribution, and this distribution maps to continuous spatial gradients on the cortical surface. Finally, to relate the navigation network to other networks, UMAP was used to recover a functional space for the whole cortex. In this space, the navigation network appears to be positioned in the middle of a broad gradient extending from visual to motor networks. These results provide a detailed characterization of the functional gradients underlying the cortical network that mediate active, naturalistic navigation.

Acknowledgements: This work is funded by the NIH, ONR, the NSF GRFP, and Ford