Stopping an already initiated action is crucial for human everyday behavior and empirical evidence points toward the prefrontal cortex playing a key role in response inhibition. Two regions that have ...been consistently implicated in response inhibition are the right inferior frontal gyrus (IFG) and the more superior region of the dorsolateral prefrontal cortex (DLPFC). The present study investigated the effect of offline 1 Hz transcranial magnetic stimulation (TMS) over the right IFG and DLPFC on performance in a gamified stop-signal task (SSG). We hypothesized that perturbing each area would decrease performance in the SSG, albeit with a quantitative difference in the performance decrease after stimulation. After offline TMS, functional short-term reorganization is possible, and the domain-general area (i.e., the right DLPFC) might be able to compensate for the perturbation of the domain-specific area (i.e., the right IFG). Results showed that 1 Hz offline TMS over the right DLPFC and the right IFG at 110% intensity of the resting motor threshold had no effect on performance in the SSG. In fact, evidence in favor of the null hypothesis was found. One intriguing interpretation of this result is that within-network compensation was triggered, canceling out the potential TMS effects as has been suggested in recent theorizing on TMS effects, although the presented results do not unambiguously identify such compensatory mechanisms. Future studies may result in further support for this hypothesis, which is especially important when studying reactive response in complex environments.
When producing creative ideas (i.e., ideas that are original and useful) two main processes occur: ideation, where people brainstorm ideas, and evaluation, where they decide if the ideas are creative ...or not. While much is known about the ideation phase, the cognitive processes involved in creativity evaluation are less clear. In this article, we present a novel modeling approach for the evaluation phase of creativity. We apply the drift diffusion model (DDM) to the Creative-or-Not task (CON-task) to study the cognitive basis of evaluation and to examine individual differences in the extent to which people take originality and utility into account when evaluating creative ideas. The CON-task is a timed decision-making task where participants indicate whether they find uses for certain objects creative or not (e.g., using a book as a buoy). The different uses vary on the two creativity dimensions "originality" and "utility." In two studies (n = 293, 17,806 trials; n = 152, 9,291 trials), we found that stimulus originality was strongly related to participants' drift rates but found only weak evidence for an association between stimulus utility and the drift rate. However, participants differed substantially in the effects of originality and utility. Furthermore, the implicit weights assigned to originality and utility on the CON-task were associated with self-reported importance ratings of originality and utility and with divergent thinking performance in the Alternative Uses task (AUT). This research provides a cognitive modeling approach to creativity evaluation and underlines the importance of communicating rating criteria in divergent thinking tasks to ensure a fair assessment of creative ability.
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected \(350{,}757\) coin flips to test the ...counterintuitive prediction from a physics model of human coin tossing developed by Diaconis, Holmes, and Montgomery (DHM; 2007). The model asserts that when people flip an ordinary coin, it tends to land on the same side it started -- DHM estimated the probability of a same-side outcome to be about 51%. Our data lend strong support to this precise prediction: the coins landed on the same side more often than not, \(\text{Pr}(\text{same side}) = 0.508\), 95% credible interval (CI) \(0.506\), \(0.509\), \(\text{BF}_{\text{same-side bias}} = 2359\). Furthermore, the data revealed considerable between-people variation in the degree of this same-side bias. Our data also confirmed the generic prediction that when people flip an ordinary coin -- with the initial side-up randomly determined -- it is equally likely to land heads or tails: \(\text{Pr}(\text{heads}) = 0.500\), 95% CI \(0.498\), \(0.502\), \(\text{BF}_{\text{heads-tails bias}} = 0.182\). Furthermore, this lack of heads-tails bias does not appear to vary across coins. Additional exploratory analyses revealed that the within-people same-side bias decreased as more coins were flipped, an effect that is consistent with the possibility that practice makes people flip coins in a less wobbly fashion. Our data therefore provide strong evidence that when some (but not all) people flip a fair coin, it tends to land on the same side it started. Our data provide compelling statistical support for the DHM physics model of coin tossing.
