Miller Shettleworth
Journal of Experimental Psychology: Animal Behavior Processes 2007, Vol. 33, No. 3, 191–212
Copyright 2007 by the American Psychological Association 0097-7403/07/$12.00 DOI: 10.1037/0097-7403.33.3.191
Learning About Environmental Geometry: An Associative Model
Noam Y. Miller and Sara J. Shettleworth
University of Toronto
K. Cheng (1986) suggested that learning the geometry of enclosing surfaces takes place in a geometric module blind to other spatial information. Failures to find blocking or overshadowing of geometry learning by features near a goal seem consistent with this view. The authors present an operant model in which learning spatial features competes with geometry learning, as in the Rescorla–Wagner model. Relative total associative strength of cues at a location determines choice of that location and thus the frequencies of reward paired with each cue. The model shows how competitive learning of local features and geometry can appear to result in potentiation, blocking, or independence, depending on enclosure shape and kind of features. The model reproduces numerous findings from dry arenas and water mazes. Keywords: spatial learning, geometric module, Rescorla–Wagner model, associative learning, water maze
Cheng (1986) was the first to show that animals can use the geometry of an enclosure to locate a hidden goal. In a working memory task, he found that distinctive corner panels did not prevent rats from learning about the shape of a rectangular enclosure and that rats sometimes ignored the panels and searched for a hidden reward at the diagonally opposite, geometrically identical, corner of the enclosure, dubbed the rotational corner (see Figure 1). Cheng concluded that shape parameters of the enclosure are learned separately from featural information in a specialized geometric module. Later studies have shown that, in a reference memory version of Cheng’s task, features are also eventually learned (e.g., Cheng, 1986, Experiments 2 and 3;
Copyright 2007 by the American Psychological Association 0097-7403/07/$12.00 DOI: 10.1037/0097-7403.33.3.191
Learning About Environmental Geometry: An Associative Model
Noam Y. Miller and Sara J. Shettleworth
University of Toronto
K. Cheng (1986) suggested that learning the geometry of enclosing surfaces takes place in a geometric module blind to other spatial information. Failures to find blocking or overshadowing of geometry learning by features near a goal seem consistent with this view. The authors present an operant model in which learning spatial features competes with geometry learning, as in the Rescorla–Wagner model. Relative total associative strength of cues at a location determines choice of that location and thus the frequencies of reward paired with each cue. The model shows how competitive learning of local features and geometry can appear to result in potentiation, blocking, or independence, depending on enclosure shape and kind of features. The model reproduces numerous findings from dry arenas and water mazes. Keywords: spatial learning, geometric module, Rescorla–Wagner model, associative learning, water maze
Cheng (1986) was the first to show that animals can use the geometry of an enclosure to locate a hidden goal. In a working memory task, he found that distinctive corner panels did not prevent rats from learning about the shape of a rectangular enclosure and that rats sometimes ignored the panels and searched for a hidden reward at the diagonally opposite, geometrically identical, corner of the enclosure, dubbed the rotational corner (see Figure 1). Cheng concluded that shape parameters of the enclosure are learned separately from featural information in a specialized geometric module. Later studies have shown that, in a reference memory version of Cheng’s task, features are also eventually learned (e.g., Cheng, 1986, Experiments 2 and 3;