Discordant evaluations of Blacks affect nonverbal behavior

Previous research suggests that automatic prejudice directly manifests in nonverbal behavior. The authors offer a more complex picture of the relation between automatic processes and nonverbal behavior by suggesting that any discomfort that appears in nonverbal behavior stems not from negative attitudes per se but from discordance between automatically activated attitudes toward Blacks and the specific evaluations being expressed. White participants for whom estimates of automatic prejudice were available provided videotaped evaluations of several individuals, including two matched Black and White males. Discordance between general racial attitudes and evaluations of specific targets manifested in discomfort-related nonverbal behavior. Moreover, na?ve Black judges, but not White judges, doubted the sincerity of individuals characterized by discordance. The nature of the nonverbal "leakage" that automatic prejudice produces is discussed.     

On No-KR tests in motor learning, retention and transfer

In this paper we examine the role of no-knowledge of results (KR) tests in motor learning, retention and transfer. A distinction is drawn between studies of KR and studies of other issues in motor learning that use a No-KR test. Arguments are presented against the currently received position that a No-KR test is an essential protocol to examine motor learning, although a No-KR test is most relevant in the few contexts where the outcome information is not naturally available. Perspectives are provided on the limited though proper role of No-KR tests in motor learning, retention and transfer and these are illustrated through experimental examples. It is proposed that the current restrictive interpretation of KR as only augmented outcome information is narrowing not only the context of KR research but also the study of motor learning in general.     

Specialised higher-level mechanisms for facial-symmetry perception: evidence from orientation-tuning functions

Bilateral symmetry is important in many perceptual analyses from low-level figure-ground segmentation to higher-level face and object perception. Despite the success of low-level, image-based symmetry-detection models, these may not provide a complete account of symmetry perception. Better symmetry detection and stronger preferences for symmetry in upright faces than comparable patterns (e.g. inverted faces) that do not engage specialised face-coding mechanisms suggest a contribution of higher-level mechanisms to symmetry perception. We replicated better symmetry detection and stronger symmetry preferences for upright than inverted faces in experiment 1, and examined their orientation tuning in more detail in experiment 2. Decreasing performance as faces are mis-oriented away from the canonical upright orientation is the signature of specialised face-processing mechanisms, which are engaged less effectively as faces are mis-oriented. Lower-level symmetry-detection mechanisms, which operate better with vertical than horizontal, and horizontal than oblique, axes of symmetry would produce a W-shaped orientation-tuning function. Identical orientation-tuning functions were obtained for symmetry detection and preferences. Both declined with increasing mis-orientation over the 0 degrees-135 degrees range, consistent with a contribution from specialised face-coding mechanisms. Both increased from 135 degrees to 180 degrees, consistent with reliance on lower-level image-based mechanisms for severely misoriented faces. Taken together, the results implicate specialised, higher-level mechanisms in the detection of, and preference for, facial symmetry.     

Exploring the specificity of age-related differences in theory of mind tasks

Tasks assessing theory of mind (ToM) and non-mental state control tasks were administered to young and older adults to examine previous contradictory findings about age differences in mental state decoding. Age differences were found on a verbal ToM task after controlling for vocabulary levels. Older adults achieved significantly lower scores than did younger adults on static and dynamic visual ToM tasks, and a similar pattern was found on non-ToM control tasks. Rather than a specific ToM deficit, older adults exhibited a more general impairment in the ability to decode cues from verbal and visual information about people.     

Attitude generalization: Similarity, valence, and extremity

Attitude generalization was explored as a function of object similarity and attitude valence and extremity. Participants in a computer game formed attitudes toward positive and negative, mild or extreme stimuli. How well these attitudes generalized to similar, novel stimuli was then examined. Visual similarity to game targets affected categorization of novel stimuli, such that greater resemblance resulted in more similar classification. However, generalization varied by valence and extremity. Negative attitudes generalized more than positive attitudes, requiring less resemblance for a novel target to be classified as negative. This pattern was more obvious with extreme attitudes than mild attitudes. That is, extreme attitudes were more influential and given more weight than mild attitudes. Also, specific conditions were identified under which positive attitudes proved more influential than negative attitudes.     

A modular theory of learning and performance

We describe a theory to account for the acquisition and extinction of response rate (conditioning) and pattern (timing). This modular theory is a development of packet theory (Kirkpatrick, 2002; Kirkpatrick & Church, 2003) that adds a distinction between pattern and strength memories, as well as contributing closed-form equations. We describe the theory using equations related to a flow diagram and illustrate it by an application to an experiment with repeated acquisitions and extinctions of a multiple-cued-interval procedure using rats. The parameter estimates for the theory were based on a calibration sample from the data, and the predictions for different measures of performance on a validation sample from the same data (cross-validation). The theory’s predictions were similar to predictions based on the reliability of the behavior.     

Decoding the Large-Scale Structure of Brain Function by Classifying Mental States Across Individuals

ABSTRACT— Brain-imaging research has largely focused on localizing patterns of activity related to specific mental processes, but recent work has shown that mental states can be identified from neuroimaging data using statistical classifiers. We investigated whether this approach could be extended to predict the mental state of an individual using a statistical classifier trained on other individuals, and whether the information gained in doing so could provide new insights into how mental processes are organized in the brain. Using a variety of classifier techniques, we achieved cross-validated classification accuracy of 80% across individuals (chance = 13%). Using a neural network classifier, we recovered a low-dimensional representation common to all the cognitive-perceptual tasks in our data set, and we used an ontology of cognitive processes to determine the cognitive concepts most related to each dimension. These results revealed a small organized set of large-scale networks that map cognitive processes across a highly diverse set of mental tasks, suggesting a novel way to characterize the neural basis of cognition.