Human navigation network: the intrinsic functional organization and behavioral relevance

Abstract

Spatial navigation is a crucial ability for living. Previous work has revealed multiple distributed brain regions associated with human navigation. However, little is known about how these regions work together as a network (referred to as navigation network) to support flexible navigation. In a novel protocol, we combined neuroimaging meta-analysis, and functional connectivity and behavioral data from the same subjects. Briefly, we first constructed the navigation network for each participant, by combining a large-scale neuroimaging metaanalysis (with the Neurosynth) and resting-state functional magnetic resonance imaging. Then, we investigated multiple topological properties of the navigation networks, including small-worldness, modularity, and highly connected hubs. Finally, we explored the behavioral relevance of these intrinsic properties in a large sample of healthy young adults (N = 190). We found that navigation networks showed small-world and modular organization at global level. More importantly, we found that increased small-worldness and modularity of the navigation network were associated with better navigation ability. Finally, we found that the right retrosplenial complex (RSC) acted as one of the hubs in the navigation network, and that higher betweenness of this region correlated with better navigation ability, suggesting a critical role of the RSC in modulating the navigation network in human brain. Our study takes one of the first steps toward understanding the underlying organization of the navigation network. Moreover, these findings suggest the potential applications of the novel approach to investigating functionally meaningful networks in human brain and their relations to the behavioral impairments in the aging and psychiatric patients.

Gene Expression Correlates of the Cortical Network Underlying Sentence Processing

“…To compare to language-related networks, we also analyzed three other functional cortical networks: the spatial navigation network (SNN), fronto-parietal multiple demand network (MDN, similar to the dorsal attention network (Yeo et al, 2011)), and default mode network (DMN). The sets of cortical regions defined for these networks (see Methods) appeared consistent with previous literature (Buckner, Andrews-Hanna, & Schacter, 2008;Crittenden, Mitchell, & Duncan, 2016;Kong, Wang, et al, 2017) and showed little overlap with the sentence processing networks defined above (Fig. 2).…”

“…It uses text-mining techniques to detect frequently used terms as proxies for concepts of interest in the neuroimaging literature: terms that occur at a high frequency in a given study are associated with all activation coordinates in that publication, allowing for automated term-based metaanalysis. Despite the automaticity and potentially high noise resulting from the large-scale meta-analysis, this approach has been shown to be robust and meaningful (e.g., Helfinstein et al, 2014;Kong, Song, et al, 2017;Kong, Wang, et al, 2017;Yarkoni et al, 2011), due to the high number of studies included. We used database version 0.6 (current as of July 2018) which included 413,429 activation peaks reported in 11,406 studies (see below for the search terms employed).…”

“…During the scan, participants were instructed to relax and remain still, with their eyes closed. The dataset has high quality in terms of minimal head motion and registration errors, and has been used in several previous studies (e.g., Kong, Wang, et al, 2017;Wang et al, 2016).…”

“…Functional connectivity of regions during task performance is correlated with that observed at rest, which suggests an "intrinsic" architecture of functional organization (Blank et al, 2014;Cole et al, 2014;, which may also be linked to individual differences in behaviour (Arnold, Protzner, Bray, Levy, & Iaria, 2014;Kong, Wang, et al, 2017). Thus, the set of regions for sentence processing defined here could be used in future studies of very large datasets, such as the UK Biobank (Sudlow et al, 2015) or ENIGMA Consortium , which include neuroanatomical and/or intrinsic connectivity data but limited task fMRI data for language functions.…”

Self‐reported navigation ability is associated with optic flow‐sensitive regions’ functional connectivity patterns during visual path integration

“…Arnold, Burles, Bray, Levy, and Iaria () examined this in the context of visual path integration and found that individuals with stronger interactions among frontal and parietal areas performed more accurately. More recently, stronger interaction between right posterior hippocampus and right retrosplenial cortex at rest (Sulpizio, Boccia, Guariglia, & Galati, ) and greater betweenness centrality of right retrosplenial cortex within a network of regions involved in navigation tasks (Kong et al, ) at rest were found to be associated with better self‐reported navigation ability. These studies show that task‐related communication between brain regions, as well as their interactions at rest, hold information about the variation in spatial navigation ability between individuals.…”