A connectionist model of path integration with and without a representation of distance to the starting point

Maurer, Roland

doi:10.3758/bf03330587

Cited by 15 publications

(6 citation statements)

References 70 publications

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“…Wehner et al (1996) is cited in support of this view, despite the fact that the latter refers to the model suggested by Müller and Wehner (1988), who presented a geocentric PI model. Maurer (1998) presented a neural network PI model employing an EP-like HV. The magnitude and directional components of the HV were stored in separate neural structures, hence the HV can be classified as ED (since it contained more than two values representing the polar HV, it was not strictly a simple EP HV).…”

Section: Coordinate Systems In Existing Modelsmentioning

confidence: 99%

Which coordinate system for modelling path integration?

Vickerstaff

Cheung

2010

Journal of Theoretical Biology

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Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate, called the home vector, of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature, and has been studied for over a century. In that time, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural representation of space needed for biological path integration. This paper presents a scheme to classify path integration systems on the basis of the way the home vector records and updates the spatial relationship between the animal and its home location. Four extended classes of coordinate systems are used to unify and review both canonical and neural network models of path integration, from the arthropod and mammalian literature. This scheme demonstrates analytical equivalence between models which may otherwise appear unrelated, and distinguishes between models which may superficially appear similar. A thorough analysis is carried out of the equational forms of important facets of path integration including updating, steering, searching and systematic errors, using each of the four coordinate systems. The type of available directional cue, namely allothetic or idiothetic, is also considered. It is shown that on balance, the class of home vectors which includes the geocentric Cartesian coordinate system, appears to be the most robust for biological systems. A key conclusion is that deducing computational structure from behavioural data alone will be difficult or impossible, at least in the absence of an analysis of random errors. Consequently it is likely that further theoretical insights into path integration will require an in-depth study of the effect of noise on the four classes of home vectors.

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Section: Coordinate Systems In Existing Modelsmentioning

confidence: 99%

Which coordinate system for modelling path integration?

Vickerstaff

Cheung

2010

Journal of Theoretical Biology

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“…Second, damage to the vestibular system produces deficits in food-hoarding tasks when allothetic cues are either absent (testing under dark conditions) or allothetic cues conflict with previous experience (testing with the home base in a new location; Wallace, Hines, Pellis, & Whishaw, 2002). Third, many of the computational models that have been advanced to explain the errors observed in dead-reckoning-based navigation posit a role for the vestibular system in updating the animal's current position (Barlow, 1964; Benhamou, Sauve, & Bovet, 1990; Fujita, Klatzky, Loomis, & Golledge, 1993; Mittelstaedt & Mittelstaedt, 1973; Muller & Wehner, 1988; for a review of models see Maurer, 1998; Maurer & Seguinot, 1995). Most of these models assume that errors in detecting linear and angular accelerations while moving through an environment contribute to the error in returning to the starting location; however, only a few studies have been conducted to actually examine the kinematic and topographic characteristics of nonhuman animals' movements while using dead-reckoning-based navigation (Wallace, Hines, et al, 2002; Wallace & Whishaw, 2003).…”

mentioning

confidence: 99%

Comparative analysis of movement characteristics during dead-reckoning-based navigation in humans and rats.

Wallace

Choudhry

Martin

2006

Journal of Comparative Psychology

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Human and rat movement organization was investigated as they searched for randomly located rewards without access to visual information. Under dark conditions, rats foraged for randomly located food pellets (Experiment 1). Blindfolded humans were instructed to search for an ostensible hidden coin using a metal detector (Experiment 2). After locating the food pellet, rats carried it back to the refuge, and after a designated searching time, humans were instructed to return to the start location. Although both species exhibited a high degree of similarity in searching path movement organization and ability to return to the start location, disruption of human searching path organization was associated with impairments in returning to the start location. These results support the vestibular "gain" account of movement organization during dead-reckoning-based navigation.

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“…Path integration can be described as a computational process that allows an animal to keep track of its position relative to the starting point of its trip by using information about its own movement (Maurer, 1988). The two components of path integration are sense of direction and distance traveled.…”

Section: Discussionmentioning

confidence: 99%

“…room (Whishaw, 1998). Desert ants (Wehner & Srinivasan, 1981), gerbils (Mittelstaedt & Mittelstaedt, 1980), mice (Alyan & Jander, 1994), hamsters (Etienne, Teroni, Hurni, & Portenier, 1990), and rats (Whishaw & Brooks, 1999;Whishaw & Tomie, 1997) have all been shown to be capable of path integration, and a variety of models have been developed to explain how animals can process route-based information (summarized by Maurer &.…”

mentioning

confidence: 99%

A two-platform task reveals a deficit in the ability of rats to return to the start location in the water maze.

Skinner

Martin²,

Scanlon³

et al. 2001

Behavioral Neuroscience

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The ability of rats to return to the start location was examined with a 4-arm radial water maze. The task required rats to find 2 hidden platforms in sequence. Rats were released from 1 of 3 arms and there was a platform located in the fourth arm. Once a rat found this platform, a 2nd platform was raised in another location, which was either the start location, for 1 group, or another fixed location, for a control group. Across 3 experiments, all rats learned the location of the 1st fixed platform in 80 to 120 trials. However, rats had difficulty finding a 2nd platform if it was at the start location. Control groups revealed that rats could learn 2 platform locations and that the difficulty in learning to return to the start location did not seem to be attributable to its aversive nature. In separate groups, exposure to the start location was increased by starting the rats from an initially stable platform. Rats still did not readily learn to return to the start location. The authors suggest that start location, when varied, cannot readily be used to define the location of a hidden platform.

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A connectionist model of path integration with and without a representation of distance to the starting point

Cited by 15 publications

References 70 publications

Which coordinate system for modelling path integration?

Which coordinate system for modelling path integration?

Comparative analysis of movement characteristics during dead-reckoning-based navigation in humans and rats.

A two-platform task reveals a deficit in the ability of rats to return to the start location in the water maze.

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