Endogenous variation in estradiol in women affects the weighting of metric and categorical information in spatial location memory.

Recent work has suggested that sex differences may exist in the strategies or types of cues that are utilized by men and women to remember discrete spatial locations or routes through a visual environment. The current study investigated the effects of circulating estradiol levels in women on the relative weighting of categorical versus fine-grained 'metric' information in a test of short-term memory for spatial locations, either presented within a simple geometric surround (a circular enclosure) or within more visually complex landscape scenes. Patterns of displacement error in the point location estimates made by men and women were analyzed. Results confirmed a sex difference in the weighting of metric versus categorical cues. Relative to men, women's estimates of locations were more strongly biased toward the center of the surrounding category (i.e., toward the category 'prototype'). Furthermore, objective measures of estradiol via saliva collected at the time of memory testing showed that, among naturally-cycling women, estradiol concentrations correlated in a positive, graded, fashion with the degree of emphasis that women placed on categorical information when estimating point locations. No associations were found for progesterone. These findings are consistent with a wider body of research showing that biological sex and reproductive hormone levels, including 17ß-estradiol, can subtly influence performance on certain spatial tasks. This is the first study to show that circulating estradiol levels may influence the relative emphasis placed on categorical versus metric cues when remembering simple point locations.

First Direct Evidence of Cue Integration in Reorientation: A New Paradigm.

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.

Seeing Like a Geologist: Bayesian Use of Expert Categories in Location Memory.

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.

Categorical biases in spatial memory: the role of certainty.

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.

Sex differences in the weighting of metric and categorical information in spatial location memory.

According to the Category Adjustment model, remembering a spatial location involves the Bayesian combination of fine-grained and categorical information about that location, with each cue weighted by its relative certainty. However, individuals may differ in terms of their certainty about each cue, resulting in estimates that rely more or less on metric or categorical representations. To date, though, very little research has examined individual differences in the relative weighting of these cues in spatial location memory. Here, we address this gap in the literature. Participants were asked to recall point locations in uniform geometric shapes and in photographs of complex, natural scenes. Error patterns were analyzed for evidence of a sex difference in the relative use of metric and categorical information. As predicted, women placed relatively more emphasis on categorical cues, while men relied more heavily on metric information. Location reproduction tasks showed a similar effect, implying that the sex difference arises early in spatial processing, possibly during encoding.

Location memory in the real world: category adjustment effects in 3-dimensional space.

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.

A category adjustment approach to memory for spatial location in natural scenes.

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.