How brain asymmetry relates to performance – a large scale dichotic listening study

All major mental functions including language, spatial and emotional processing are lateralized but how strongly and to which hemisphere is subject to inter- and intraindividual variation. Relatively little, however, is known about how the degree and direction of lateralization affect how well the functions are carried out, i.e., how lateralization and task performance are related. The present study therefore examined the relationship between lateralization and performance in a dichotic listening task for which we had data available from 1839 participants. In this task, consonant-vowel syllables are presented simultaneously to the left and right ear, such that each ear receives a different syllable. When asked which of the two they heard best, participants typically report more syllables from the right ear, which is a marker of left-hemispheric speech dominance. We calculated the degree of lateralization (based on the difference between correct left and right ear reports) and correlated it with overall response accuracy (left plus right ear reports). In addition, we used reference models to control for statistical interdependency between left and right ear reports. The results revealed a u-shaped relationship between degree of lateralization and overall accuracy: the stronger the left or right ear advantage, the better the overall accuracy. This u-shaped asymmetry-performance relationship consistently emerged in males, females, right-/non-right-handers, and different age groups. Taken together, the present study demonstrates that performance on lateralized language functions depends on how strongly these functions are lateralized. The present study further stresses the importance of controlling for statistical interdependency when examining asymmetry-performance relationships in general

Argument as an Act of Friendship

Those who are said to argue are typically seen as annoying, domineering types who treat conversation as a duel in which the goal is in the words of Gerry Spence\u27s recent bestseller, to win every time. The most immediate manifestation of this resistance to argument as both inescapable and healthful comes from our students; even when they learn to appreciate and evaluate tropes at an advanced level, they still often wonder aloud, Should I engage openly in argument? This paper aspires to paste a happy face on the practice of argument as a partial antidote to this resistance

Models of hemispheric specialization in facial emotion perception - a reevaluation

A considerable amount of research on functional cerebral asymmetries (FCAs) for facial emotion perception has shown conflicting support for three competing models: (i) the Right Hemisphere Hypothesis, (ii) the Valence-Specific Hypothesis, and (iii) the Approach/Withdrawal model. However, the majority of studies evaluating the Right Hemisphere or the Valence-Specific Hypotheses are rather limited by the small number of emotional expressions used. In addition, it is difficult to evaluate the Approach/Withdrawal Hypothesis due to insufficient data on anger and FCAs. The aim of the present study was (a) to review visual half field (VHF) studies of hemispheric specialization in facial emotion perception and (b) to reevaluate empirical evidence with respect to all three partly conflicting hypotheses. Results from the present study revealed a left visual field (LVF)/right hemisphere advantage for the perception of angry, fearful, and sad facial expressions and a right visual field (RVF)/left hemisphere advantage for the perception of happy expressions. Thus, FCAs for the perception of specific facial emotions do not fully support the Right Hemisphere Hypothesis, the Valence-Specific Hypothesis, or the Approach/Withdrawal model. A systematic literature review, together with the results of the present study, indicate a consistent LVF/right hemisphere advantage only for a subset of negative emotions including anger, fear and sadness, rather suggesting a “negative (only) valence model.