No abstract

BackgroundProspective memory (PM) denotes the ability to remember to perform actions in the future. It has been argued that standard laboratory paradigms fail to capture core aspects of PM.Methodology/Principal FindingsWe combined functional MRI, virtual reality, eye-tracking and verbal reports to explore the dynamic allocation of neurocognitive processes during a naturalistic PM task where individuals performed errands in a realistic model of their residential town. Based on eye movement data and verbal reports, we modeled PM as an iterative loop of five sustained and transient phases: intention maintenance before target detection (TD), TD, intention maintenance after TD, action, and switching, the latter representing the activation of a new intention in mind. The fMRI analyses revealed continuous engagement of a top-down fronto-parietal network throughout the entire task, likely subserving goal maintenance in mind. In addition, a shift was observed from a perceptual (occipital) system while searching for places to go, to a mnemonic (temporo-parietal, fronto-hippocampal) system for remembering what actions to perform after TD. Updating of the top-down fronto-parietal network occurred at both TD and switching, the latter likely also being characterized by frontopolar activity.Conclusion/SignificanceTaken together, these findings show how brain systems complementary interact during real-world PM, and support a more complete model of PM that can be applied to naturalistic PM tasks and that we named PROspective MEmory DYnamic (PROMEDY) model because of its dynamics on both multi-phase iteration and the interactions of distinct neurocognitive networks.

No abstract

Virtual Reality (VR) is used for a variety of applications ranging from entertainment to psychological medicine. VR has been demonstrated to influence higher order cognitive functions and cortical plasticity, with implications on phobia and stroke treatment. An integral part for successful VR is a high sense of presence – a feeling of ‘being there’ in the virtual scenario. The underlying cognitive and perceptive functions causing presence in VR scenarios are however not completely known. It is evident that the brain function is influenced by drugs, such as ethanol, potentially confounding cortical plasticity, also in VR. As ethanol is ubiquitous and forms part of daily life, understanding the effects of ethanol on presence and user experience, the attitudes and emotions about using VR applications, is important. This exploratory study aims at contributing towards an understanding of how low-dose ethanol intake influences presence, user experience and their relationship in a validated VR context. It was found that low-level ethanol consumption did influence presence and user experience, but on a minimal level. In contrast, correlations between presence and user experience were strongly influenced by low-dose ethanol. Ethanol consumption may consequently alter cognitive and perceptive functions related to the connections between presence and user experience.

Abstract.Recognizing activities based on an actor's interaction with everyday objects is an important research approach within ubiquitous computing. We present a recognition approach which complement objects grabbed or released information with the object's internal state changes (as an effect of intra manipulation) and the object's external state changes with reference to other objects (as an effect of extra manipulation). The concept of Intra manipulation is inspired by the fact that many everyday objects change their internal state when manipulated by the human actor, while extra manipulation is motivated by the fact that humans commonly rearrange the spatial relations between everyday objects as part of their activities. A detailed evaluation of our prototype activity recognition system in virtual reality (VR) environment is presented as a "proof of concept". We have obtained a recognition precision of 92% on the activity-level and 81% on the action-level among 15 everyday home activities. Virtual reality was used as a test-bed in order to speed up the design process of our activity recognition system, allowing us to compensate for the limitations with currently available sensing technologies and to compare the contributions of intra manipulation and extra manipulation for activity recognition.