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Memory for spatial location is typically biased, with errors trending toward the center of a surrounding region. According to the category adjustment model (CAM), this bias reflects the optimal, Bayesian combination of fine-grained and categorical representations of a location. However, there is disagreement about whether categories are malleable. For instance, can categories be redefined based on expert-level conceptual knowledge? Furthermore, if expert knowledge is used, does it dominate other information sources, or is it used adaptively so as to minimize overall error, as predicted by a Bayesian framework? We address these questions using images of geological interest. The participants were experts in structural geology, organic chemistry, or English literature. Our data indicate that expertise-based categories influence estimates of location memory--particularly when these categories better constrain errors than alternative ("novice") categories. Results are discussed with respect to the CAM.

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. The Category Adjustment (CA) model suggests that this bias is due to a Bayesian combination of categorical and metric information, which offers an optimal solution under conditions of uncertainty (Huttenlocher, Hedges, & Duncan, 1991). A fundamental assumption of this model is that representations of locations are unbiased but uncertain; during combination, greater metric uncertainty results in relatively greater emphasis on categorical information, ultimately leading to increased bias (but also minimizing error across multiple estimates). Sampaio and Wang (2009) have demonstrated that metric information is not lost during this combination process, supporting the CA model's assumption that underlying spatial representations are undistorted. Here, we examine the 2nd half of the CA model's central assumption: that increasing metric uncertainty drives the combination process. Participants recognized point locations within visually complex images in a 4-choice task. Our results indicate that individuals recognized the correct location over other, biased alternatives, confirming that metric information is unbiased at the time of retrieval. In addition, we found that, when participants make errors, they are more likely to select locations that are biased toward the category prototype. In Experiment 2, we demonstrate that categorically biased locations are most likely to be chosen under conditions of uncertainty. Indeed, under these conditions, categorically biased locations were chosen more frequently than the correct location. These results suggest that systematic errors are the result of combination across multiple levels of spatial representations that are undistorted but somewhat uncertain.

The ability to remember spatial locations is critical to human functioning, both in an evolutionary and in an everyday sense. Yet spatial memories and judgments often show systematic errors and biases. Bias has been explained by models such as the Category Adjustment model (CAM), in which fine-grained and categorical information about locations are combined in a Bayesian manner (Huttenlocher, Hedges, & Duncan, 1991). However, experiments testing this model have largely used locations contained in simple geometric shapes and, more recently, 2D scenes. Do the results generalize to location memory in the complex natural world, as they should if the CAM is to provide an over-arching framework for thinking about spatial memory? Here, this issue is addressed using a novel extension of the location memory paradigm that allows for testing of location memory in an everyday, 3D environment. The results support two predictions of the CAM: that memory for locations is biased toward central values, and that the magnitude of error increases with the retention interval. (Contains 1 table and 5 figures.)

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. This bias has been explained using a Bayesian model in which fine-grained and categorical information are combined (Huttenlocher, Hedges, & Duncan, 1991). However, experiments testing this model have largely used locations contained in simple geometric shapes. Use of this paradigm raises 2 issues. First, do results generalize to the complex natural world? Second, what types of information might be used to segment complex spaces into constituent categories? Experiment 1 addressed the 1st question by showing a bias toward prototypical values in memory for spatial locations in complex natural scenes. Experiment 2 addressed the 2nd question by manipulating the availability of basic visual cues (using color negatives) or of semantic information about the scene (using inverted images). Error patterns suggest that both perceptual and conceptual information are involved in segmentation. The possible neurological foundations of location memory of this kind are discussed. (Contains 6 figures and 1 footnote.)

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. This bias has been explained using a Bayesian model in which fine-grained and categorical information are combined (Huttenlocher, Hedges, & Duncan, 1991). However, experiments testing this model have largely used locations contained in simple geometric shapes. Use of this paradigm raises 2 issues. First do results generalize to the complex natural world? Second, what types of information might be used to segment complex spaces into constituent categories? Experiment 1 addressed the 1st question by showing a bias toward prototypical values in memory for spatial locations in complex natural scenes. Experiment 2 addressed the 2nd question by manipulating the availability of basic visual cues (using color negatives) or of semantic information about the scene (using inverted images). Error patterns suggest that both perceptual and conceptual information are involved in segmentation. The possible neurological foundations of location memory of this kind are discussed. Keywords: category adjustment, scenes, inversion, contrast reversal, categorization DOI 10.1037/a0019293

The bulk of the research in spatial reorientation has studied how visual cues guide behavior. This project aims to explore the role of auditory cues. Using a find-and-replace paradigm in a circular search space, blindfolded sighted participants were able to reorient successfully using only auditory landmarks, albeit with errors larger than those found in visual-based reorientation. Importantly, for the first time, it was found that people encoded an ambiguous cue in addition to the certain cue, even though it was unnecessary and insufficient for solving the task. Results are discussed in the context of the resistance to using auditory cues spontaneously and the theory of functional equivalence. [ABSTRACT FROM AUTHOR]

Abstract: There are several models of the use of geometric and feature cues in reorientation (Cheng, Huttenlocher, & Newcombe, ). The adaptive combination approach posits that people integrate cues with weights that depend on cue salience and learning, or, when discrepancies are large, they choose between cues based on these variables (Cheng, Shettleworth, Huttenlocher, & Rieser, ; Newcombe & Huttenlocher, ). In a new paradigm designed to evaluate integration and choice, disoriented participants attempted to return to a heading direction, in a trapezoidal enclosure in which feature and geometric cues both unambiguously specified a heading, but later the feature was moved. With discrepancies greater than 90 degrees, participants choose geometry. With smaller discrepancies, integration appeared in three of five situations; otherwise, participants used geometry alone. Variation depended on direction of feature movement and whether the nearest corner was acute or obtuse. The results have implications for contrasting adaptive combination and modularity theory, and for future research, offering a new paradigm for reorientation research, and for testing cue integration more broadly. [ABSTRACT FROM AUTHOR]

Memory for spatial location is typically biased, with errors trending toward the center of a surrounding region. According to the category adjustment model ( CAM), this bias reflects the optimal, Bayesian combination of fine-grained and categorical representations of a location. However, there is disagreement about whether categories are malleable. For instance, can categories be redefined based on expert-level conceptual knowledge? Furthermore, if expert knowledge is used, does it dominate other information sources, or is it used adaptively so as to minimize overall error, as predicted by a Bayesian framework? We address these questions using images of geological interest. The participants were experts in structural geology, organic chemistry, or English literature. Our data indicate that expertise-based categories influence estimates of location memory-particularly when these categories better constrain errors than alternative ('novice') categories. Results are discussed with respect to the CAM. [ABSTRACT FROM AUTHOR]

The article presents a case study on a theory of agency interaction in cases involving shared regulatory jurisdiction in America, and it mentions the interactions between the U.S. Food and Drug Administration (FDA) and the nation's Environmental Protection Agency (EPA), as well as public health advice regarding the health risks posed by mercury in fish. U.S. federal regulations are mentioned, along with issues associated with overlapping delegations and interagency cooperation.