Joshua S. Redford

Rhesus Monkeys (Macaca mulatta) Adaptively Monitor Uncertainty While Multi-Tasking

As researchers explore animals’ capacity for metacognition and uncertainty monitoring, some paradigms allow the criticism that animal participants—who are always extensively trained in one stimulus domain within which they learn to avoid difficult trials—use task-specific strategies to avoid aversive stimuli instead of responding to a generalized state of uncertainty like that humans might use. We addressed this criticism with an uncertainty-monitoring task environment in which four different task domains were interleaved randomly trial by trial. Four of five macaques (Macaca mulatta) were able to make adaptive uncertainty responses while multi-tasking, suggesting the generality of the psychological signal that occasions these responses. The findings suggest that monkeys may have an uncertainty-monitoring capacity that is like that of humans in transcending task-specific cues and extending simultaneously to multiple domains.

Visual Search and the Collapse of Categorization.

Categorization researchers typically present single objects to be categorized. But real-world categorization often involves object recognition within complex scenes. It is unknown how the processes of categorization stand up to visual complexity or why they fail facing it. The authors filled this research gap by blending the categorization and visual-search paradigms into a visual-search and categorization task in which participants searched for members of target categories in complex displays. Participants have enormous difficulty in this task. Despite intensive and ongoing category training, they detect targets at near-chance levels unless displays are extremely simple or target categories extremely focused. These results, discussed from the perspectives of categorization and visual search, might illuminate societally important instances of visual search (e.g., diagnostic medical screening).

The comparative psychology of same-different judgments by humans (Homo sapiens) and monkeys (Macaca mulatta).

The authors compared the performance of humans and monkeys in a Same-Different task. They evaluated the hypothesis that for humans the Same-Different concept is qualitative, categorical, and rule-based, so that humans distinguish 0-disparity pairs (i.e., same) from pairs with any discernible disparity (i.e., different); whereas for monkeys the Same-Different concept is quantitative, continuous, and similarity-based, so that monkeys distinguish small-disparity pairs (i.e., similar) from pairs with a large disparity (i.e., dissimilar). The results supported the hypothesis. Monkeys, more than humans, showed a gradual transition from same to different categories and an inclusive criterion for responding Same. The results have implications for comparing Same-Different performances across species--different species may not always construe or perform even identical tasks in the same way. In particular, humans may especially apply qualitative, rule-based frameworks to cognitive tasks like Same-Different.

Refining the Visual-Cortical Hypothesis in Category Learning

Participants produce steep typicality gradients and large prototype-enhancement effects in dot-distortion category tasks, showing that in these tasks to-be-categorized items are compared to a prototypical representation that is the central tendency of the participants exemplar experience. These prototype-abstraction processes have been ascribed to low-level mechanisms in primary visual cortex. Here we asked whether higher-level mechanisms in visual cortex can also sometimes support prototype abstraction. To do so, we compared dot-distortion performance when the stimuli were size constant (allowing some low-level repetition-familiarity to develop for similar shapes) or size variable (defeating repetition-familiarity effects). If prototype formation is only mediated by low-level mechanisms, stimulus-size variability should lessen prototype effects and flatten typicality gradients. Yet prototype effects and typicality gradients were the same under both conditions, whether participants learned the categories explicitly or implicitly and whether they received trial-by-trial reinforcement during transfer tests. These results broaden out the visual-cortical hypothesis because low-level visual areas, featuring retinotopic perceptual representations, would not support robust category learning or prototype-enhancement effects in an environment of pronounced variability in stimulus size. Therefore, higher-level cortical mechanisms evidently can also support prototype formation during categorization.

The interplay between uncertainty monitoring and working memory: Can metacognition become automatic?

The uncertainty response has grounded the study of metacognition in nonhuman animals. Recent research has explored the processes supporting uncertainty monitoring in monkeys. It has revealed that uncertainty responding, in contrast to perceptual responding, depends on significant working memory resources. The aim of the present study was to expand this research by examining whether uncertainty monitoring is also working memory demanding in humans. To explore this issue, human participants were tested with or without a cognitive load on a psychophysical discrimination task that included either an uncertainty response (allowing the participant to decline difficult trials) or a middle-perceptual response (labeling the same intermediate trial levels). The results demonstrated that cognitive load reduced uncertainty responding, but increased middle responding. However, this dissociation between uncertainty and middle responding was only observed when participants either lacked training or had very little training with the uncertainty response. If more training was provided, the effect of load was small. These results suggest that uncertainty responding is resource demanding, but with sufficient training, human participants can respond to uncertainty either by using minimal working memory resources or by effectively sharing resources. These results are discussed in relation to the literature on animal and human metacognition.

The comparative psychophysics of complex shape perception

The authors compared the complex shape perception of humans and monkeys. Members of both species participated in a Same–Different paradigm in which they judged the similarity of shape pairs that could be variations of the same underlying prototype. For both species, similarity gradients were found to be steep going out from the transformational center of psychological space. In contrast, similarity gradients were found to be flat going from the periphery in toward the center of psychological space. These results show that there are important common principles in the shape-perception and shape-comparison processes of humans and monkeys. The same general organization of psychological space is obtained. The same quantifiable metric of psychological distance is applied. Established methods for creating controlled shape variation have the same effect on both species’ similarity judgments. The member of the to-be-judged pair of shapes that is peripheral in psychological space controls the strength of the perceived similarity of the pair. The results have broader implications for the comparative study of perception and categorization.

Humans and Monkeys Exert Metacognitive Control Based on Learning Difficulty in a Perceptual Categorization Task

Recently, Redford (2010) found that monkeys seemed to exert meta-cognitive control in a category-learning paradigm. Specifically, they selected more trials to view as the difficulty of the category-learning task increased. However, category-learning difficulty was determined by manipulating the family resemblance across the to-be-learned exemplars. Although this effectively influenced the learning difficulty, difficulty was confounded with novelty. For instance, a weak family resemblance made category learning difficult, but also increased the amount of perceptual change from trial to trial. The current research rules out novelty in favor of difficulty by manipulating the number of dots involved in the dot distortions while controlling the amount of perceptual change.