Spatial Navigation: A question of scale
Just like our ancestors before us, humans must be able to navigate within both familiar and new environments, whether this involves driving to work or finding our way around a new city. Successful spatial navigation depends on many cognitive processes including memory, attention, and our perception of direction and distance (Epstein et al., 2017). A key issue, however, is that spatial environments vary considerably in terms of their size and complexity. To date most research on spatial navigation has focused on small spatial scales, such as navigating within a room or a building (Wolbers and Wiener, 2014). But it remains unclear how accurately we can estimate distances between locations on a larger scale, such as whether the Taj Mahal is closer to the Pyramids of Giza or the Great Wall of China, and how these different spatial scales are represented in the brain.
Now, in eLife, Michael Peer, Yorai Ron, Rotem Monsa and Shahar Arzy – who are based at the Hebrew University of Jerusalem, the Hadassah Medical Center and the University of Pennsylvania – report a simple but elegant experiment that teases apart which brain regions are recruited when we process information about environments that are on different spatial scales (Peer et al., 2019). Peer et al. asked internationally-travelled adults to provide the names of two locations they were personally familiar with across six spatial ‘scales’. These scales varied from small, spatially-confined areas (e.g. rooms and buildings) through medium-sized regions (e.g. local neighborhoods and cities) to expansive geographical locations (e.g. countries and continents; Figure 1A). The experiment was then personalized by asking each participant to provide the names of eight items that were personally familiar to them within each location.
A few days later, participants underwent a functional magnetic resonance imaging experiment to determine which areas of the brain are selectively involved during spatial processing. This technique enables researchers to measure increases in blood flow and oxygen delivery to parts of the brain, and determine which regions are more ‘active’ when engaging in a cognitive task. During the experiment, participants were asked to judge distances between a ‘target’ item from their personal list (e.g. a table in their bedroom) and two other items from the same location (e.g. a chair or a bed in their bedroom). This allowed Peer et al. to investigate which brain regions respond to small, medium, and large spatial scales, and which regions are insensitive to scale but respond to other location or proximity information.
The experiment identified three main clusters of brain regions that are important for processing different spatial scales. What was unique about all three clusters was that activity within them shifted in a ‘graded’ manner depending on whether participants were processing spatial information on a local or more global scale. For example, when participants judged distances on a small scale in local environments, this engaged the posterior portions of all three clusters. On the other hand, when participants judged distances on a larger scale, the pattern of activity shifted towards the anterior portions of the clusters (Figure 1B).
These findings align remarkably well with previous work showing that the human hippocampus – a region of the brain involved in spatial navigation (Burgess et al., 2002) – represents object position and spatial information, such as direction and distance between objects, as a graded pattern of activity (Evensmoen et al., 2015; Evensmoen et al., 2013). The latest study, however, extends our understanding by highlighting how graded patterns of activity move from posterior to anterior regions of the spatial processing network outside of the hippocampus, depending on the spatial scale being processed (Figure 1).
The work presented here provides new insights into how humans navigate within different environments. From a clinical perspective, appreciating how humans dynamically zoom in or out of different spatial scales could help refine how various neurological conditions are diagnosed. This is most relevant for neurodegenerative disorders, such as Alzheimer’s disease, in which disorientation and a distorted sense of direction are often early symptoms (Coughlan et al., 2018; Tu et al., 2015). Whether the altered sense of direction and difficulties in judging proximity that are associated with Alzheimer’s disease are due to changes in the way that regions of the brain represent spatial scale is an important question for future studies to address.
References
-
Spatial navigation deficits - overlooked cognitive marker for preclinical Alzheimer disease?Nature Reviews Neurology 14:496–506.https://doi.org/10.1038/s41582-018-0031-x
-
The cognitive map in humans: spatial navigation and beyondNature Neuroscience 20:1504–1513.https://doi.org/10.1038/nn.4656
Article and author information
Author details
Publication history
- Version of Record published: September 10, 2019 (version 1)
Copyright
© 2019, Irish and Ramanan
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,817
- views
-
- 111
- downloads
-
- 1
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Obstructive sleep apnea (OSA) is a prevalent sleep-related breathing disorder that results in multiple bouts of intermittent hypoxia. OSA has many neurological and systemic comorbidities, including dysphagia, or disordered swallow, and discoordination with breathing. However, the mechanism in which chronic intermittent hypoxia (CIH) causes dysphagia is unknown. Recently, we showed the postinspiratory complex (PiCo) acts as an interface between the swallow pattern generator (SPG) and the inspiratory rhythm generator, the preBötzinger complex, to regulate proper swallow-breathing coordination (Huff et al., 2023). PiCo is characterized by interneurons co-expressing transporters for glutamate (Vglut2) and acetylcholine (ChAT). Here we show that optogenetic stimulation of ChATcre:Ai32, Vglut2cre:Ai32, and ChATcre:Vglut2FlpO:ChR2 mice exposed to CIH does not alter swallow-breathing coordination, but unexpectedly disrupts swallow behavior via triggering variable swallow motor patterns. This suggests that glutamatergic–cholinergic neurons in PiCo are not only critical for the regulation of swallow-breathing coordination, but also play an important role in the modulation of swallow motor patterning. Our study also suggests that swallow disruption, as seen in OSA, involves central nervous mechanisms interfering with swallow motor patterning and laryngeal activation. These findings are crucial for understanding the mechanisms underlying dysphagia, both in OSA and other breathing and neurological disorders.
-
- Neuroscience
The central tendency bias, or contraction bias, is a phenomenon where the judgment of the magnitude of items held in working memory appears to be biased toward the average of past observations. It is assumed to be an optimal strategy by the brain and commonly thought of as an expression of the brain’s ability to learn the statistical structure of sensory input. On the other hand, recency biases such as serial dependence are also commonly observed and are thought to reflect the content of working memory. Recent results from an auditory delayed comparison task in rats suggest that both biases may be more related than previously thought: when the posterior parietal cortex (PPC) was silenced, both short-term and contraction biases were reduced. By proposing a model of the circuit that may be involved in generating the behavior, we show that a volatile working memory content susceptible to shifting to the past sensory experience – producing short-term sensory history biases – naturally leads to contraction bias. The errors, occurring at the level of individual trials, are sampled from the full distribution of the stimuli and are not due to a gradual shift of the memory toward the sensory distribution’s mean. Our results are consistent with a broad set of behavioral findings and provide predictions of performance across different stimulus distributions and timings, delay intervals, as well as neuronal dynamics in putative working memory areas. Finally, we validate our model by performing a set of human psychophysics experiments of an auditory parametric working memory task.