Spatial navigation is the process on which we rely to orient ourselves within the environment and to negotiate our way through it. Our ability to do so depends upon cognitive maps, mental representations of the surrounding spaces, which are constructed by the brain and are used by it to calculate one’s present location, based on landmarks in the environment and on our movements within it, and to plan future movements.
The term “cognitive map” was first used in a landmark 1948 paper, in which the behavioural psychologist Edward Tolman described his now famous studies of rats in mazes. In that paper, Tolman postulated that “incoming impulses are usually worked over and elaborated…into a tentative, cognitive-like map of the environment…indicating routes and paths and environmental relationships.” The paper provided a starting point for modern research into spatial navigation, and after decades of research, much progress has been made in our understanding of how the brain forms cognitive maps.
We now know that the circuitry encoding the cognitive map lies in the hippocampus and surrounding areas, and that these parts of the brain contain at least 3 distinct types of neurons which together encode an organism’s location within its environment and the paths it takes to move through it. In the current issue of Science, researchers from the Norwegian University of Science and Technology in Trondheim report that they have discovered a fourth class of neuron involved in spatial navigation.
Research into the cellular basis of spatial navigation began in the early 1970s, with the discovery of place cells by John O’Keefe and Jonathan Dostrovsky. Place cells were initally found in the hippocampus of the rat, and have since been found in other organisms, including humans; each fires only when an animal is in a specific location within its environment. Then, in 1984, James Ranck of SUNY Health Sciences Center in New York identified head direction cells in the presubiculum, which is adjacent to the hippocampus. As their name suggests, these neurons fire only when an animal is facing a certain direction.
The third type of neuron involved in spatial navigation is the grid cell, which was first identified in 2005, and is found in the entorhinal cortex, which also lies next to the hippocampus, and in rodents is located at the caudal (back) end of the temporal lobe. Unlike place cells, grid cells fire when the animal is at multiple locations in its environment. These locations are evenly spaced, so that a grid cell increases its firing rate periodically as the animal traverses a space. Grid cells encode different scales, such that small groups of grid cells have a unique periodicity; this scaling is mapped onto the entorhinal cortex, so that the scale encoded increases systematically along its top-to-bottom axis.
In a paper published in 2000, Neil Burgess predicted the existence of what he called boundary vector cells, which encode the organism’s distance from geometric borders surrounding its environment. The prediction was based on a computational model of place cell activity, but until now there has been no experimental evidence for such cells. Edvard Moser and his colleagues, who first described grid cells in 2005, now confirm the existence of these neurons in the rat brain.
Moser’s group used chronically embedded electrode arrays into the brains of rats, so that they could monitor and record the activity of single neurons for long periods of time in the freely moving animals. Using this standard experimental set-up in 13 animals, they recorded the activity of more than 600 individual neurons in the entorhinal cortex. The majority of the neurons exhibited properties which are characteristic of place cells and grid cells, but a small number of cells – 69 out of 624, or approximately 11% – exhibited an unusual firing pattern which had not been observed before.
Representative location of recording electrodes in the medial entorhinal cortex (red dot, left) and four examples of border cell firing fields (right), in which firing rate is colour-coded, with highest frequency shown in red, and superimposed onto a square representing the animals’ enclosure
(From Solstad et al 2008).
Initially, the researchers paid little attention to these unusual firing patterns, and dismissed them as recording artifacts. Then they realized that they may have identified the border cells predicted by Burgess. And indeed, when they reanalyzed the activity patterns, they found that the firing rates of the cells increased only when the animals were at one or several of the walls of the enclosure, irrespective of the length of the border or its relationship with other borders in the surroundings.
To determine whether these neurons also respond to other kinds of boundaries, the researchers removed the walls of the box, so that open surface which remained was surrounded on all sides by a vertical 60 cm drop. The same results were obtained when the animals were tested under these conditions. Thus the cells are responsive to borders in general, and not just walls.
The activity of these “border cells” was also found to be consistent across enclosures of different shapes and sizes, and further investigation revealed that they have other interesting properties. When, for example, a cue card on the wall of a circular enclosure was rotated by 90°, the field of the border cells (that is, the precise location in the environment at which the cells increase their firing rate) rotated accordingly. Also, when two simultaneously recorded neurons were found to respond to opposite borders, the difference in relative orientation was retained across different enclosures.
Now Moser and his colleagues plan to investigate how the activity of the four cell types in the hippocampal formation is integrated to form the cognitive map. Moser suspects that border cells align grid cells to borders, and are thus involved in defining the perimeter of the animals’ environment. He also suggests that they are involved in route-planning – although they are sparse in number, they are distributed widely throughout the entorhinal cortex, in such a way that they could provide grid cells with information about approaching obstacles and borders.
Solstad, T. et al (2008). Representation of Geometric Borders in the Entorhinal Cortex. Science 322: 1865-1868. DOI: 10.1126/science.1166466