How we navigate using cognitive maps

By Anastasia Alenova

Navigating from your student accommodation to university might seem like second nature now, but this route became familiar as you formed a cognitive map of the environment. 

A cognitive map is defined as a process of psychological transformations by which an individual acquires, stores, recalls and decodes information about their everyday spatial environment (Kitchin, 1994). In other words, it’s what enables you to navigate. 

This process was first described by Tolman in 1948, while he was observing rats. He hypothesised that humans, as well as rats, construct map-like representations within a “black box” of the nervous system which guides everyday movement. (Kitchin, 1994; Behrens et al., 2018) This “black box” is more complex than Tolman could have imagined, and the process of cognitive mapping is still not fully understood. 

When navigating, one can either keep track of their movement, such as number of turns or distance travelled, or use their surroundings, such as landmarks, to orient themselves. Navigation without landmarks uses self-motion cues, such as vestibular and proprioceptive information which keeps track of displacement. Landmark anchoring, on the other hand, uses environmental cues to determine the orientation of the cognitive map (Epstein et al., 2017). So that travelling can be completed with a degree of assurance, cognitive maps also rehearse spatial behaviour. However, due to possible obstacles and path changes, these cognitive maps need to permit flexible behaviour. By exploiting past experiences and imagining consequences of new choices, cognitive maps allow flexible inferences and influence behaviour in the environment (Kitchin, 2019; Behrens et al., 2018).

While navigating, the brain learns information about our environment in a specific way. Humans, and most mammals, learn the spatial relations between the starting point and destination, while integrating the surrounding images and information. For this, many other cognitive processes come into play, such as perception, information reorganisation and memory (Kitchin, 1994). This spatial knowledge acquisition can be divided into two types. It can be done in a “discrete” framework, where first landmarks are learned, then connected via routes to form a cognitive map and establish a frame of reference, or within a “continuous” framework where landmark and route information is encoded simultaneously (Shinazi et al., 2016). In both scenarios, the brain learns structural representations, rather than building new ones each time, as there are many repeated patterns in the environment. To generalise across many tasks and remain applicable to any new environment, each representation is separated of any sensory properties. This learning is facilitated when there are many past experiences involving learning new representations. However, the learning rate is heavily influenced by network weights which maximise reward, obtained when reaching a goal or destination. Dopamine is produced when the task is reached and promotes positive change in the learning algorithm (Behrens et al., 2018). 

The main player supporting the learning process during cognitive map formation is the hippocampal-entorhinal system. Within this system, specific cells provide information about the spatial environment and enable to plan the route to a destination while avoiding obstacles. 

Place cells in the hippocampus restrict activity to a single location in space and represent distance between locations. Grid cells in the entorhinal cortex fire on a grid representing distances between spatial locations. This is done using vector relationships made of Euclidean distances via a coding mechanism (Behrens et al., 2018; Epstein et al., 2017). Grid cells also provide place cells with coordinate systems required for location-specific encoding (Shinazi et al., 2016). Other cells such as head direction cells in cortical and subcortical structures track head direction by firing on the basis of the orientation of the head in the navigational plane. Border cells in the entorhinal cortex and boundary cells in the subiculum fire when the individual is a set distance from navigational boundaries at specific distances. These borders help relate the firing fields of place and grid cells to fixed features of the environment, as environmental boundaries are the primary cue to determine map orientation (Epstein et al., 2017). 

These same brain structures are involved in multiple other processes. The hippocampus and prefrontal cortex are active during reconstructive memory and imagination (Behrens et al., 2018). The hippocampus can also store multiple maps, but during learning may fail to distinguish similar contexts due to an all-or-nothing response used for information retrieval. This means that when there are overlapping features, either one or the other context is presented. Over time, patterns are separated (Epstein et al., 2017). 

Other key regions include the post parahippocampal area (PPA), retrosplenial cortex (RSC) and medial parietal region, which process navigation related stimuli during passive viewing of the environment. These regions also process spatially stable elements, such as landmarks. Particularly, the PPA is responsible for analysing and visually recognising landmarks as well as spatial structures of local scenes. The RSC situates these local scenes within the broader spatial environment, by integrating egocentric spatial navigation information into allocentric code, such as direction of travel and the observer’s position. Meanwhile, frontal lobe regions mostly respond during active navigation and play a role in planning (Epstein et al., 2017; Shinazi et al., 2016).

Often, navigational ability is taken for granted, but cognitive maps play a key role in spatial behaviour, spatial decision making and learning in real world environments. During navigational studies, however, most experiments rely on virtual or imaged navigation meaning vestibular and proprioceptive inputs are absent (Epstein et al., 2017). Thus, the processes underlying active navigation are still unclear. 

However, better understanding of how we navigate is crucial, as it could heavily influence how the surrounding environment should be built. For instance, poor design of key structures such as a hospitals can cause stress to staff, patients and visitors. Better design of buildings and even cities centred around navigational ability could increase quality of life. (Kitchin, 1994).

References:

Kitchin, R. M. (1994) Cognitive maps: What are they and why study them? Journal of Environmental Psychology. 14 (1), 1-19. Available from: http://dx.doi.org/10.1016/S0272-4944(05)80194-X. Available from: doi: 10.1016/S0272-4944(05)80194-X. 

Behrens, T. E. J., Muller, T. H., Whittington, J. C. R., Mark, S., Baram, A. B., Stachenfeld, K. L. & Kurth-Nelson, Z. (2018) What Is a Cognitive Map? Organizing Knowledge for Flexible Behavior. Neuron (Cambridge, Mass.). 100 (2), 490-509. Available from: http://dx.doi.org/10.1016/j.neuron.2018.10.002. Available from: doi: 10.1016/j.neuron.2018.10.002. 

Epstein, R. A., Patai, E. Z., Julian, J. B. & Spiers, H. J. (2017) The cognitive map in humans: Spatial navigation and beyond. Nature Neuroscience. 20 (11), 1504-1513. Available from: https://www.ncbi.nlm.nih.gov/pubmed/29073650. Available from: doi: 10.1038/nn.4656.

Schinazi, V. R., Thrash, T. & Chebat, D. (2016) Spatial navigation by congenitally blind individuals. Wiley Interdisciplinary Reviews. Cognitive Science. 7 (1), 37-58. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/wcs.1375. Available from: doi: 10.1002/wcs.1375. 

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