88,676 research outputs found

    Too Depleted to Try? Testing the Process Model of Ego Depletion in the Context of Unhealthy Snack Consumption

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    Background: The process model proposes that the ego depletion effect is due to (a) an increase in motivation toward indulgence, and (b) a decrease in motivation to control behaviour following an initial act of self-control. In contrast, the reflective-impulsive model predicts that ego depletion results in behaviour that is more consistent with desires, and less consistent with motivations, rather than influencing the strength of desires and motivations. The current study sought to test these alternative accounts of the relationships between ego depletion, motivation, desire, and self-control. Methods: One hundred and fifty-six undergraduate women were randomised to complete a depleting e-crossing task or a non-depleting task, followed by a lab-based measure of snack intake, and self-report measures of motivation and desire strength. Results and Conclusions: In partial support of the process model, ego depletion was related to higher intake, but only indirectly via the influence of lowered motivation. Motivation was more strongly predictive of intake for those in the non-depletion condition, providing partial support for the reflective-impulsive model. Ego depletion did not affect desire, nor did depletion moderate the effect of desire on intake, indicating that desire may be an appropriate target for reducing unhealthy behaviour across situations where self-control resources vary

    Predicting mental imagery based BCI performance from personality, cognitive profile and neurophysiological patterns

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    Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy— EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants’ BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants’ performance with a mean error of less than 3 points. This study determined how users’ profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user

    A prospective study exploring the construct and predictive validity of the COM-B model for physical activity

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    The final, definitive version of this paper has been published in Journal of Health Psychology, November 2017, doi: https://doi.org/10.1177/1359105317739098, published by SAGE Publishing, All rights reserved.This study examined the constructs of Capability, Opportunity, and Motivation from the COM-B model and their influence on moderate-to-vigorous physical activity (MVPA). Using a prospective survey design, 186 healthy adults completed measures representing the Theoretical Domains Framework mapped to the COM-B, and MVPA one week later. The main indicators for the COM constructs were ‘habits’ (Capability), ‘subjective norms’ (Opportunity), and ‘exercise self-identity’ (Motivation). Motivation (77%) and MVPA (50%) were strongly predicted, with Capability and Motivation as key drivers of behaviour. Motivation was a strong mediator for Capability on behaviour. Future research should consider this approach for other populations and behaviours.Peer reviewe

    Implicit attitudes towards smoking predict long-term relapse in abstinent smokers

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    It has previously been argued that implicit attitudes toward substance-related cues drive addictive behavior. Nevertheless, it remains an open question whether behavioral markers of implicit attitude activation can be used to predict long-term relapse. The main objective of this study was to examine the relationship between implicit attitudes toward smoking-related cues and long-term relapse in abstaining smokers. Implicit attitudes toward smoking-related cues were assessed by means of the Implicit Association Test (IAT) and the evaluative priming task (EPT). Both measures were completed by a group of smokers who volunteered to quit smoking (patient group) and a group of nonsmokers (control group). Participants in the patient group completed these measures twice: once prior to smoking cessation and once after smoking cessation. Relapse was assessed by means of short telephone survey, 6 months after completion of the second test session. EPT scores obtained prior to smoking cessation were related to long-term relapse and correlated with self-reported nicotine dependence as well as daily cigarette consumption. In contrast, none of the behavioral outcome measures were found to correlate with the IAT scores. These findings corroborate the idea that implicit attitudes toward substance-related cues are critically involved in long-term relapse. A potential explanation for the divergent findings obtained with the IAT and EPT is provided

    Principles for Consciousness in Integrated Cognitive Control

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    In this article we will argue that given certain conditions for the evolution of bi- \ud ological controllers, these will necessarily evolve in the direction of incorporating \ud consciousness capabilities. We will also see what are the necessary mechanics for \ud the provision of these capabilities and extrapolate this vision to the world of artifi- \ud cial systems postulating seven design principles for conscious systems. This article \ud was published in the journal Neural Networks special issue on brain and conscious- \ud ness

    Antifragility = Elasticity + Resilience + Machine Learning: Models and Algorithms for Open System Fidelity

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    We introduce a model of the fidelity of open systems - fidelity being interpreted here as the compliance between corresponding figures of interest in two separate but communicating domains. A special case of fidelity is given by real-timeliness and synchrony, in which the figure of interest is the physical and the system's notion of time. Our model covers two orthogonal aspects of fidelity, the first one focusing on a system's steady state and the second one capturing that system's dynamic and behavioural characteristics. We discuss how the two aspects correspond respectively to elasticity and resilience and we highlight each aspect's qualities and limitations. Finally we sketch the elements of a new model coupling both of the first model's aspects and complementing them with machine learning. Finally, a conjecture is put forward that the new model may represent a first step towards compositional criteria for antifragile systems.Comment: Preliminary version submitted to the 1st International Workshop "From Dependable to Resilient, from Resilient to Antifragile Ambients and Systems" (ANTIFRAGILE 2014), https://sites.google.com/site/resilience2antifragile

    The gatekeeper: individual differences are key in the chain from perception to behaviour

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    A basic assumption in mainstream social cognition is that the path from perception to behaviour is often automatic and direct, as supported for example by several experimental studies showing that priming can lead directly to a congruent behaviour without any need of conscious awareness of the process. However, we argue that the priming of a goal or an object activates individual differences in automatic evaluations at the associative level that in turn are the key predictors of action (gatekeeper model). A study (n = 90) on the American stereotype is presented to support the model. The results show that individual differences of the American stereotype as assessed with the IAT predicts a relevant action (essay evaluation) but only under condition of priming. Broader implications for predictive validity of implicit measures are also discussed
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