Acquisition of Knowledge about Spatial Location: Assessing the Generality of the Mechanism of Learning

Chamizo, Victoria D.

doi:10.1080/02724990244000205

Cited by 73 publications

(69 citation statements)

References 33 publications

(39 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…No changes need to be implemented in the selection network. Such an extended model can potentially be used to address the issue of blocking and overshadowing effects between different types of cues (Rescorla and Wagner 1972;Chamizo 2003;Shettleworth 2003, 2005;Stahlman and Blaisdell 2009). These effects are inherent to any learning algorithm which updates associative weights between cues and rewards so as to reduce reward prediction error (e.g., TDlearning) as is true for the selection network in our model.…”

Section: Resultsmentioning

confidence: 99%

Path planning versus cue responding: a bio-inspired model of switching between navigation strategies

et al. 2010

View full text Add to dashboard Cite

In this article, we describe a new computational model of switching between path-planning and cue-guided navigation strategies. It is based on three main assumptions: (i) the strategies are mediated by separate memory systems that learn independently and in parallel; (ii) the learning algorithms are different in the two memory systems-the cueguided strategy uses a temporal-difference (TD) learning rule to approach a visible goal, whereas the path-planning strategy relies on a place-cell-based graph-search algorithm to learn the location of a hidden goal; (iii) a strategy selection mechanism uses TD-learning rule to choose the most successful strategy based on past experience. We propose a novel criterion for strategy selection based on the directions of goal-oriented movements suggested by the different strategies. We show that the selection criterion based on this "common currency" is capable of choosing the best among TD-learning and planning strategies and can be used to solve navigational tasks in continuous state and action spaces. The model has been successfully applied to reproduce rat behavior in two water-maze tasks in which the two strategies were Laurent Dollé, Denis Sheynikhovich-First authorship shared.

show abstract

Section: Resultsmentioning

confidence: 99%

Path planning versus cue responding: a bio-inspired model of switching between navigation strategies

et al. 2010

View full text Add to dashboard Cite

show abstract

“…There has already been a fair amount of research demonstrating cue-competition effects, such as overshadowing (e.g., Cheng et al 1987;Cheng 1989;March et al 1992;Spetch 1995;Roberts and Pearce 1999;Sanchez-Moreno et al 1999) and blocking (Diez-Chamizo et al 1985;Rodrigo et al 1997), in the spatial domain (see reviews by Chamizo 2002Chamizo , 2003. Other well-established associative phenomena, such as generalization and peakshift, have been shown in the spatial domain as well (see review by Cheng and Spetch 1998).…”

Section: Discussionmentioning

confidence: 99%

Integration of spatial maps in pigeons

Blaisdell

Cook

2004

Anim Cogn

View full text Add to dashboard Cite

The integration of spatial maps in pigeons was investigated using a spatial analog to sensory preconditioning. The pigeons were tested in an open-field arena in which they had to locate hidden food among a 4×4 grid of gravel-filled cups. In phase 1, the pigeons were exposed to a consistent spatial relationship (vector) between landmark L (a red L-shaped block of wood), landmark T (a blue Tshaped block of wood) and the hidden food goal. In phase 2, the pigeons were then exposed to landmark T with a different spatial vector to the hidden food goal. Following phase 2, pigeons were tested with trials on which they were presented with only landmark L to examine the potential integration of the phase 1 and 2 vectors via their shared common elements. When these test trials were preceded by phase 1 and phase 2 reminder trials, pigeons searched for the goal most often at a location consistent with their integration of the L→T phase 1 and T→phase 2 goal vectors. This result indicates that integration of spatial vectors acquired during phases 1 and 2 allowed the pigeons to compute a novel L→goal vector. This suggests that spatial maps may be enlarged by successively integrating additional spatial information through the linkage of common elements.

show abstract

“…This suggests that for wide range of navigation tasks in which an animal has to remember the position of a hidden goal in a fixed environment, the navigation strategy that is often termed cognitive or map-based can be implemented by a simple, associative learning mechanism (Chamizo, 2003), based on place cells. It does not exclude, of course, that true planning abilities may be needed in other spatial tasks, such as those that require making shortcuts.…”

Section: Taxon and Locale Strategiesmentioning

confidence: 99%

Is there a geometric module for spatial orientation? Insights from a rodent navigation model.

Sheynikhovich¹,

Chavarriaga²,

Strösslin³

et al. 2009

Psychological Review

102

145

View full text Add to dashboard Cite

Modern psychological theories of spatial cognition postulate the existence of a geometric module for reorientation. This concept is derived from experimental data showing that in rectangular arenas with distinct landmarks in the corners, disoriented rats often make diagonal errors, suggesting their preference for the geometric (arena shape) over the nongeometric (landmarks) cues. Moreover, sensitivity of hippocampal cell firing to changes in the environment layout was taken in support of the geometric module hypothesis. Using a computational model of rat navigation, the authors proposed and tested the alternative hypothesis that the influence of spatial geometry on both behavioral and neuronal levels can be explained by the properties of visual features that constitute local views of the environment. Their modeling results suggest that the pattern of diagonal errors observed in reorientation tasks can be understood by the analysis of sensory information processing that underlies the navigation strategy employed to solve the task. In particular, 2 navigation strategies were considered: (a) a place-based locale strategy that relies on a model of grid and place cells and (b) a stimulus-response taxon strategy that involves direct association of local views with action choices. The authors showed that the application of the 2 strategies in the reorientation tasks results in different patterns of diagonal errors, consistent with behavioral data. These results argue against the geometric module hypothesis by providing a simpler and biologically more plausible explanation for the related experimental data. Moreover, the same model also describes behavioral results in different types of water-maze tasks.

show abstract

Acquisition of Knowledge about Spatial Location: Assessing the Generality of the Mechanism of Learning

Cited by 73 publications

References 33 publications

Path planning versus cue responding: a bio-inspired model of switching between navigation strategies

Path planning versus cue responding: a bio-inspired model of switching between navigation strategies

Integration of spatial maps in pigeons

Is there a geometric module for spatial orientation? Insights from a rodent navigation model.

Contact Info

Product

Resources

About