City rats: From rat behaviour to human spatial cognition in urban environments

The structure and shape of an urban environment influence our ability to find our way about in the city^1-2^. Indeed, urban designers who face the challenge of planning environments that facilitate wayfinding^3^, have a consequent need to understand the relations between the urban environment and spatial cognition^4^. Previous studies have suggested that certain qualities of city elements, such as a distinct contrast with the background (e.g. The Eiffel Tower in Paris), or a clear morphology (e.g. the grid layout of Manhattan's streets) affect spatial behaviour and cognition^1,5-7^. However, only a few empirical studies have examined the relations between the urban environment and spatial cognition. Here we suggest that testing rats in experimental environments that simulate certain facets of urban environment can provide an insight into human spatial behaviour in urban environments with a similar layout. Specifically, we simulated two city layouts: (1) a grid street layout such as that of Manhattan; and (2) an irregular street layout such as that of Jerusalem. We found that the rats that were tested in the grid layout covered more ground and visited more locations, compared with the restricted movement demonstrated by the rats tested in the irregular layout. This finding in rats is in accordance with previous findings that urban grids conduce to high movement flow throughout the city, compared to low movement flow in irregular urban layouts^8-9^. Previous studies revealed that the spatial behaviour of rats and humans is controlled by the same underlying mechanisms^10-11^. In the same vein, we show that rats demonstrate spatial movement patterns that recall those of humans in similar urban environments. Rat behaviour may thus offer an in-vivo means for testing and analyzing the spatial cognitive principles of specific urban designs and for inferring how humans may perceive a particular urban environment and orient in it

Network Analysis of Rat Spatial Cognition: Behaviorally-Established Symmetry in a Physically Asymmetrical Environment

<div><h3>Background</h3><p>We set out to solve two inherent problems in the study of animal spatial cognition (i) What is a “place”?; and (ii) whether behaviors that are not revealed as differing by one methodology could be revealed as different when analyzed using a different approach.</p> <h3>Methodology</h3><p>We applied network analysis to scrutinize spatial behavior of rats tested in either a symmetrical or asymmetrical layout of 4, 8, or 12 objects placed along the perimeter of a round arena. We considered locations as the units of the network (nodes), and passes between locations as the links within the network.</p> <h3>Principal Findings</h3><p>While there were only minor activity differences between rats tested in the symmetrical or asymmetrical object layouts, network analysis revealed substantial differences. Viewing ‘location’ as a cluster of stopping coordinates, the key locations (large clusters of stopping coordinates) were at the objects in both layouts with 4 objects. However, in the asymmetrical layout with 4 objects, additional key locations were spaced by the rats between the objects, forming symmetry among the key locations. It was as if the rats had behaviorally imposed symmetry on the physically asymmetrical environment. Based on a previous finding that wayfinding is easier in symmetrical environments, we suggest that when the physical attributes of the environment were not symmetrical, the rats established a symmetric layout of key locations, thereby acquiring a more legible environment despite its complex physical structure.</p> <h3>Conclusions and Significance</h3><p>The present study adds a behavioral definition for “location”, a term that so far has been mostly discussed according to its physical attributes or neurobiological correlates (e.g. - place and grid neurons). Moreover, network analysis enabled the assessment of the importance of a location, even when that location did not display any distinctive physical properties.</p> </div

The distinction between key-nodes and other nodes.

<p>The nodes for each rat in the 4-object layout were ranked from high to low according to the number of stopping coordinates. The rank is depicted on the x-axis, whereas the mean (±SEM) number of stopping coordinates in each rank is depicted on the y-axis. Scale for both axes is logarithmic. The nodes above the dashed horizontal line are those that were considered as key nodes. As shown, there were four key nodes in the symmetrical layout compared with five key nodes in the asymmetrical object layout.</p

Building a network of places.

<p>The rationale for establishing the criterion of 12 cm diameter and the transformation of stopping coordinates into a network is illustrated for one rat. a. <i>Stopping coordinates: -</i> these are as the x-y coordinates of a single rat, as extracted from the tracking system (Ethovision). The large black circle represents the arena perimeter, each red dot represents a stopping coordinate at which the rat stopped for one second or longer, and the black squares represent the location of the objects. b. <i>Nodes under the application of a 12-cm circle around the additional stopping coordinate:-</i> As shown, with this diameter the nodes (circles) coincide with the objects and behavior. c. <i>Nodes under the application of a 9-cm circle around the additional stopping coordinate:-</i> As shown, with this diameter stopping coordinates around the same object split into several nodes, resulting in a mismatch between behavior and nodes. d. <i>Nodes under the application of a 14-cm circle around the additional stopping coordinate:-</i> As shown, with this diameter the bottom node encompasses the stopping coordinates of two objects (see the red dots of these objects in a.). e. <i>Topologic graph:-</i> The presentation of the network after the transformation of stopping coordinates into nodes (red circles). Arrows between nodes represent the links (passes) between nodes. Note that the location of a red circle does not represent the physical location of that node. Likewise, the circles that represent the nodes in b-d do not represent the real size of the node but the number of stopping coordinates included in that node.</p

Building a node from stopping coordinates.

<p>The algorithm for transforming stopping coordinates into a network node (a) and a visualized process of building a single node (b).</p

Object layout and paths of locomotion for an exemplary rat in each group.

<p>The location of 4, 8, and 12 objects in a symmetrical (left) and an asymmetrical (right) layout is depicted in the top row (a). The paths of locomotion for a single exemplary rat in depicted below for each layout (b).</p

Physical location of the network nodes.

<p>For both the symmetrical (left) and asymmetrical arenas (right), the object layout is depicted in the left-hand column. The network nodes were placed in their respective physical location in the arena, and are shown for 3 rats in each object layout and object number. For each rat, the open circles represent the nodes in their physical location in the arena, and the diameter of the circle represents the number of stopping coordinates within each node (and not the physical area of the node). Key nodes are depicted in open red circles, whereas key nodes that are not located on objects are depicted in red circles filled with green. The rest of the nodes are depicted in light blue. As shown, in the asymmetrical layout with 4 objects, rats established a fifth node that is not located on an object.</p