‘No Man is an Island’: Effects of social seclusion on social dream content and REM sleep

Based on the Social Simulation Theory of dreaming (SST), we studied the effects of voluntary social seclusion on dream content and sleep structure. Specifically, we studied the Compensation Hypothesis, which predicts social dream contents to increase during social seclusion, the Sociality Bias – a ratio between dream and wake interactions – and the Strengthening Hypothesis, which predicts an increase in familiar dream characters during seclusion. Additionally, we assessed changes in the proportion of REM sleep. Sleep data and dream reports from 18 participants were collected preceding (n = 94), during (n = 90) and after (n = 119) a seclusion retreat. Data were analysed using linear mixed-effects models. We failed to support the Compensation Hypothesis, with dreams evidencing fewer social interactions during seclusion. The Strengthening Hypothesis was supported, with more familiar characters present in seclusion dreams. Dream social interactions maintained the Sociality Bias even under seclusion. Additionally, REM sleep increased during seclusion, coinciding with previous literature and tentatively supporting the proposed attachment function for social REM sleep.     

When and how less is more: reply to Tharp and Pickering

In DeCaro et al. [DeCaro, M. S., Thomas, R. D., & Beilock, S. L. (2008). Individual differences in category learning: Sometimes less working memory capacity is better than more. Cognition, 107, 284-294] we demonstrated that sometimes less working memory (WM) has its advantages. The lower individuals’ WM, the faster they achieved success on an information-integration (II) category learning task adopted from Waldron and Ashby [Waldron, E. M., & Ashby, F. G. (2001). The effects of concurrent task interference on category learning: Evidence for multiple category learning systems. Psychonomic Bulletin & Review, 8, 168-176]. We attributed this success to the inability of lower WM individuals to employ explicit learning strategies heavily reliant on executive control. This in turn, we hypothesized, might push lower WM individuals to readily adopt procedural-based strategies thought to lead to success on the II task. Tharp and Pickering [Tharp, I. J., & Pickering, A. D. (2009). A note on DeCaro, Thomas, and Beilock (2008): Further data demonstrate complexities in the assessment of information-integration category learning. Cognition] recently questioned whether the II category learning task DeCaro et al. used really reflects procedural learning. In an effort to investigate Tharp and Pickering’s assertions with respect to individual differences in WM, we replicate and extend our previous work, in part by modeling participants’ response strategies during learning. We once again reveal that lower WM individuals demonstrate earlier II learning than their higher WM counterparts. However, we also show that low WM individuals’ initial success is not because of procedural-based responding. Instead, individuals lower in WM capacity perseverate in using simple rule-based strategies that circumvent heavy demands on WM while producing above-chance accuracy.     

Hazard perception abilities of experienced and novice motorcyclists: An interactive simulator experiment

This study reports an experiment that compared the hazard perception abilities of experienced and novice motorcycle riders using an interactive, closed-loop, simulator. Participants (n = 49) were categorized into four groups: experienced motorcycle riders with full driver licence, inexperienced motorcycle riders with full driver licence, novice motorcycle riders with full driver licence, and novice motorcycle riders with probationary driver licence. The participants were tested on three scenarios, each consisting of eight hazardous events. They were instructed to ride normally, but to respond appropriately to avoid the hazards. Under certain conditions in the simulator, we found that experienced riders (relative to inexperienced or novice riders) crashed less often, received better performance evaluations, and approached hazards at more appropriate speeds. Interestingly, we also found that some novice riders were overconfident in their riding ability. We discuss how this overconfidence might be related to hazard perception.