Virtual reality (VR) systems offer a powerful tool for human behavior research. The ability to create three-dimensional visual scenes and to measure responses to the visual stimuli enables the behavioral researcher to test hypotheses in a manner and scale that were previously unfeasible. For example, a researcher wanting to understand interceptive timing behavior might wish to violate Newtonian mechanics so that objects can move in novel 3-D trajectories. The same researcher might wish to collect such data with hundreds of participants outside the laboratory, and the use of a VR headset makes this a realistic proposition. The difficulty facing the researcher is that sophisticated 3-D graphics engines (e.g., Unity) have been created for game designers rather than behavioral scientists. To overcome this barrier, we have created a set of tools and programming syntaxes that allow logical encoding of the common experimental features required by the behavioral scientist. The Unity Experiment Framework (UXF) allows researchers to readily implement several forms of data collection and provides them with the ability to easily modify independent variables. UXF does not offer any stimulus presentation features, so the full power of the Unity game engine can be exploited. We use a case study experiment, measuring postural sway in response to an oscillating virtual room, to show that UXF can replicate and advance upon behavioral research paradigms. We show that UXF can simplify and speed up the development of VR experiments created in commercial gaming software and facilitate the efficient acquisition of large quantities of behavioral research data.

Virtual reality simulators are becoming increasingly popular in dental schools across the world. But to what extent do these systems reflect actual dental ability? Addressing this question of construct validity is a fundamental step that is necessary before these systems can be fully integrated into a dental school's curriculum. In this study, we examined the sensitivity of the Simodont (a haptic virtual reality dental simulator) to differences in dental training experience. Two hundred and eighty-nine participants, with 1 (n = 92), 3 (n = 79), 4 (n = 57) and 5 (n = 61) years of dental training, performed a series of tasks upon their first exposure to the simulator. We found statistically significant differences between novice (Year 1) and experienced dental trainees (operationalised as 3 or more years of training), but no differences between performance of experienced trainees with varying levels of experience. This work represents a crucial first step in understanding the value of haptic virtual reality simulators in dental education.

Aim To investigate the effect of qualitatively different types of pedagogical feedback (FB) on the training, transfer and retention of basic manual dexterity dental skills using a virtual reality (VR) haptic dental simulator. Methods Sixty‐three participants (M = 22.7 years; SD = 3.4 years), with no previous dental training, were randomly allocated to one of three groups (n = 21 each). Group 1 received device‐only feedback during the training phase, that is the visual display of the simulator (DFB); Group 2 received verbal feedback from a qualified dental instructor (IFB); and Group 3 received a combination of instructor and device feedback (IDFB). Participants completed four tasks during which feedback was given according to group allocation as well as two skills transfer tests. Skill retention was examined immediately after training, at 1 week and at 1 month post‐test. Results Statistically significant differences were found between the groups in overall performance (P < 0.001) and error (P = 0.006). Post hoc comparisons revealed the IDFB group produced substantially better performance and fewer errors in comparison with DFB and IFB training. This difference translated to improved performance in skill retention and generalisation of knowledge to novel tasks. Conclusion These data indicate that the acquisition and retention of basic dental motor skills in novice trainees is best optimised through a combination of instructor and visual display (VR)‐driven feedback. The results have implications for the utility and implementation of VR haptic technology in dental education.

We investigated whether well-known neural markers of selective attention to motivationally-relevant stimuli were modulated by variations in subjective preference towards consumer goods in a virtual shopping task. Specifically, participants viewed and rated pictures of various goods on the extent to which they wanted each item, which they could potentially purchase afterwards. Using the event-related potentials (ERP) method, we found that variations in subjective preferences for consumer goods strongly modulated positive slow waves (PSW) from 800 to 3000 milliseconds after stimulus onset. We also found that subjective preferences modulated the N200 and the late positive potential (LPP). In addition, we found that both PSW and LPP were modulated by subsequent buying decisions. Overall, these findings show that well-known brain event-related potentials reflecting selective attention processes can reliably index preferences to consumer goods in a shopping environment. Based on a large body of previous research, we suggest that early ERPs (e.g. the N200) to consumer goods could be indicative of preferences driven by unconditional and automatic processes, whereas later ERPs such as the LPP and the PSW could reflect preferences built upon more elaborative and conscious cognitive processes.

A growing trend of neuroimaging, behavioral, and computational research has investigated the topic of outcome uncertainty in decision-making. Although evidence to date indicates that humans are very effective in learning to adapt to uncertain situations, the nature of the specific cognitive processes involved in the adaptation to uncertainty are still a matter of debate. In this article, we reviewed evidence suggesting that cognitive control processes are at the heart of uncertainty in decision-making contexts. Available evidence suggests that: (1) There is a strong conceptual overlap between the constructs of uncertainty and cognitive control; (2) There is a remarkable overlap between the neural networks associated with uncertainty and the brain networks subserving cognitive control; (3) The perception and estimation of uncertainty might play a key role in monitoring processes and the evaluation of the “need for control”; (4) Potential interactions between uncertainty and cognitive control might play a significant role in several affective disorders.