Neural Encoding of Objects Relevant for Navigation and Resting State Correlations with Navigational Ability

Abstract

Abstract■ Objects along a route can help us to successfully navigate through our surroundings. Previous neuroimaging research has shown that the parahippocampal gyrus (PHG) distinguishes between objects that were previously encountered at navigationally relevant locations (decision points) and irrelevant locations (nondecision points) during simple object recognition. This study aimed at unraveling how this neural marking of objects relevant for navigation is established during learning and postlearning rest. Twenty-four participants were scanned using fMRI while they were viewing a route through a virtual environment. Eye movements were measured, and brain responses were time-locked to viewing each object. The PHG showed increased responses to decision point objects compared with nondecision point objects during route learning. We compared functional connectivity between the PHG and the rest of the brain in a resting state scan postlearning with such a scan prelearning. Results show that functional connectivity between the PHG and the hippocampus is positively related to participantsʼ self-reported navigational ability. On the other hand, connectivity with the caudate nucleus correlated negatively with navigational ability. These results are in line with a distinction between egocentric and allocentric spatial representations in the caudate nucleus and the hippocampus, respectively. Our results thus suggest a relation between navigational ability and a neural preference for a specific type of spatial representation. Together, these results show that the PHG is immediately involved in the encoding of navigationally relevant object information. Furthermore, they provide insight into the neural correlates of individual differences in spatial ability. ■

Human navigation network: the intrinsic functional organization and behavioral relevance

“…Santa Barbara Sense of Direction scale (SBSOD) Navigation ability was measured using the SBSOD scale (Hegarty et al 2002), which is a standard questionnaire on sense of direction in a large-scale environment, and is increasingly used as a reliable proxy for actual navigation ability (Janzen et al 2008;Wegman and Janzen 2011). SBSOD consists of 15 items.…”

“…Moreover, this scale has been increasingly used as a reliable proxy for real-world navigation performance in recent structural and functional neuroimaging literature (Janzen et al 2008;Wegman and Janzen 2011;Wegman et al 2014;Auger et al 2012;Epstein et al 2005). Therefore, SBSOD score, although based on participants' subjective experiences, is a valid index of the participants' real-world spatial navigation ability (see below for more discussion).…”

“…Therefore, it is possible that the variability in human navigation may be better reflected by the underlying functional organization of the navigation network. A resting-state neuroimaging study has shown a positive correlation of navigation ability with the learning-induced changes in the functional connectivity between the parahippocampal cortex and the hippocampus (Wegman and Janzen 2011). Moreover, with spatial memory tasks, previous studies have shown that the dynamic interplay between multiple brain areas contributes to the behavioral outputs (Watrous et al 2013;Arnold et al 2014;Schedlbauer et al 2014).…”

Caudate Resting Connectivity Predicts Implicit Probabilistic Sequence Learning

“…Indeed, rsFC of task-relevant networks relates to individual differences in the consolidation of learned information, such that individuals with superior performance on a preceding learning task display the greatest changes in rsFC from a pre-to postlearning resting scan (e.g., Albert et al, 2009;Vahdat et al, 2011;Wegman and Janzen, 2011). In addition, the baseline (i.e., pretask) strength of rsFC in task-relevant networks can predict individual differences in subsequent performance, by which individual differences in the strength of selective resting-state networks relate to learning and memory ability (Baldassarre et al, 2012;Gordon et al, 2013;Wang et al, 2010aWang et al, , 2010bYstad et al, 2010).…”

Functional connectivity changes in the entorhinal cortex of taxi drivers

“…Several previous studies showed an increase in functional connectivity between hippocampal and extrahippocampal regions as a function of experience (Aly, Ranganath, & Yonelinas, 2013; Joost & Gabriele, 2011; Sulpizio, Boccia, Guariglia, & Galati, 2016), but there is evidence suggesting that training with lower intensity may lead to enhancement of previously established functional connections, while training with higher intensity may lead to increased efficiency (Karim et al., 2017; Penhune & Steele, 2012). Furthermore, a recent study focusing on the changes in functional connectivity and GABA levels with long‐term motor learning indicated that lower amounts of practice might rely mostly on the established connections by increasing the functional connectivity, whereas higher amounts of practice might cause formation of new connections and result in increased circuit efficiency reflected by decreased functional connectivity (Sampaiobaptista et al., 2015).…”