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In the task-switching paradigm, the latency switch-cost score-the difference in mean reaction time between switch and nonswitch trials-is the traditional measure of task-switching ability. However, this score does not reflect accuracy, where switch costs may also emerge. In two experiments that varied in response deadlines (unlimited vs. limited time), we evaluated the measurement properties of two traditional switch-cost scoring methods (the latency switch-cost score and the accuracy switch-cost score) and three alternatives (a rate residual score, a bin score, and an inverse efficiency score). Scores from the rate residual, bin score, and inverse efficiency methods had comparable reliability for latency switch-cost scores without response deadlines but were more reliable than latency switch-cost scores when higher error rates were induced with a response deadline. All three alternative scoring methods appropriately accounted for differences in accuracy switch costs when higher error rates were induced, whereas pure latency switch-cost scores did not. Critically, only the rate residual and bin score methods were more valid indicators of task-switching ability; they demonstrated stronger relationships with performance on an independent measure of executive functioning (the antisaccade analogue task), and they allowed the detection of larger effect sizes when examining within-task congruency effects. All of the three alternative scoring methods provide researchers with a better measure of task-switching ability than do traditional scoring methods, because they each simultaneously account for latency and accuracy costs. Overall, the three alternative scoring methods were all superior to the traditional latency switch-cost scoring method, but the strongest methods were the rate residual and bin score methods.

Tone languages such as Mandarin use voice pitch to signal lexical contrasts, presenting a challenge for second/foreign language (L2) learners whose native languages do not use pitch in this manner. The present study examined components of an aptitude for mastering L2 lexical tone. Native English speakers with no previous tone language experience completed a Mandarin word learning task, as well as tests of pitch ability, musicality, L2 aptitude, and general cognitive ability. Pitch ability measures improved predictions of learning performance beyond musicality, L2 aptitude, and general cognitive ability and also predicted transfer of learning to new talkers.In sum, although certain non-tonal measures help predict successful tone learning, the central components of tonal aptitude are pitch-specific perceptual measures.

What makes a metaphor difficult to understand?There exists a considerable and convincing body of research in cognitive psychology and cognitive science that indicates that people understand metaphors in much the same way as they understand literal sentences (Cacciari &Glucksberg, 1994; Gibbs,1994Gibbs, , 2001Glucksberg, 1998). Some metaphors are easier to understand than others, but the same can be said for literal sentences. On the whole, the view that understanding metaphors is a more complex process than understanding literal sentences is not supported by this body of research. In particular, it does not appear that metaphor comprehension first involves an attempt at literal comprehension, and when that fails, a metaphoric reinterpretation. Certainly, that is sometimes the case for complex, often literary metaphors, but most ordinary metaphors encountered in common speech and writing are simply understood without any need to figure them out. Some literal sentences, too, challenge comprehension and require a certain amount of problem solving for their comprehension. But most of the time the sentences that we hear and read are understood without deliberate reasoning, whether they are metaphorical or literal.Of course, claiming that metaphorical sentences are understood in the same way as literal sentences does not tell us how either one is understood. Here, we describe a model of text comprehension (Kintsch, 1998(Kintsch, , 2001) that attempts to specify the process of comprehension for both literal and metaphorical sentences, simulate the computations involved, and evaluate the model empirically.A basic assumption of this model is that the meaning of a word, sentence, or text is given by the set of relationships between it and everything else that is known. This idea is operationalized in terms of a high-dimensional semantic space. Words, sentences, and texts are represented as vectors in this space; that is, meaning is a position in this huge semantic space, which is defined relative to all other positions that constitute this space.We thus represent meaning geometrically, i.e. mathematically, which means that we can calculate with meanings. For instance, we can readily calculate how close or far apart two vectors are in this semantic space -hence, the degree of semantic relationship between any words, sentences, or texts. Metaphor Difficulty 4The technique that allows us to construct such a semantic space is Latent Semantic Analysis (LSA), as developed by Landauer and his coworkers (for introductions, see Landauer, 1998;Landauer & Dumais, 1997;Landauer, Foltz & Laham,

Studies of lexical tone  learning generally focus on monosyllabic contexts, while reports of phonetic learning benefits associated with input variability are based largely on experienced learners. This study trained inexperienced learners on Mandarin tonal contrasts to test two hypotheses regarding the influence of context and variability on tone  learning. The first hypothesis was that increased phonetic variability of tones in disyllabic contexts makes initial tone  learning more challenging in disyllabic than monosyllabic words. The second hypothesis was that the learnability of a given tone varies across contexts due to differences in tonal variability. Results of a word learning experiment supported both hypotheses: tones were acquired less successfully in disyllables than in monosyllables, and the relative difficulty of disyllables was closely related to contextual tonal variability. These results indicate limited relevance of monosyllable-based data on Mandarin learning for the disyllabic majority of the Mandarin lexicon. Furthermore, in the short term, variability can diminish learning; its effects are not necessarily beneficial but dependent on acquisition stage and other learner characteristics. These findings thus highlight the importance of considering contextual variability and the interaction between variability and type of learner in the design, interpretation, and application of research on phonetic learning.