119 research outputs found

    Autonomic emotional responses to food: private label brands versus national brands

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    Private label brands (PLB) have been increasing both perceived quality and consumer acceptance in the last decades, which has compelled national brands (NBs) to invest in maintaining consumer confidence and preference. Recent economic crisis led consumers to become more price sensitive and more worried about cutting on daily needs, such as food consumption. However, taste is still one of the most important factor of decision for consumers regarding food products. Despite such importance of taste in decision-making, most research on consumer senses still relies on traditional methods of surveying consumers, which are unable to measure the consumers' autonomic emotional reactions. The current paper uses a psychophysiological method to measure emotional arousal–electrodermal activity (EDA) and a self-assessment manikin to measure pleasure. Emotions are then tested to assess their influence on perceived quality and willingness to buy (WTB). Findings show that NB are still perceived by consumers as superior, but consumers' WTB is not higher for NB. These results show that consumers' decisions are not always in favor of the product which is perceived to have a better quality which suggests that the “quality gap” is fading and the “branding gap” is gaining momentum.info:eu-repo/semantics/acceptedVersio

    Investigating Perceptual-Cognitive Expertise, Visual Gaze, and Neural Activity in Golf Putting

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    Background/Aims: Perceptual-cognitive expertise, measured through quiet eye (QE) duration has been linked to superior golf putting performance. There are however some unanswered questions in relation to how QE duration improves performance and inconsistencies when trying to apply optimal QE duration in practice. Consequently, the overarching aim of this thesis was to identify factors of perceptual-cognitive expertise related to golf putting performance. Methods: To explore the impact of QE duration on performance, Study 1, Study 2 (a, b, c) assessed gaze behaviour, performance, stroke kinematics and neural activity. The final studies explored perceptual-cognitive expertise in golf putting through exploring the whole putting routine capturing gaze behaviour, performance and stroke kinematics alongside golfers and coach ratings. A mixed method triangulation design was used to interpret the data and to develop further understanding of perceptual-cognitive expertise in golf putting. Results: Shorter QE durations were most effective for performance, influencing our decision to explore perceptual-cognitive expertise beyond QE. Exploring the interaction between the golfer, task and environment formed the basis of the development of an intervention designed to improve performance. Observable neural signatures differentiating successful and unsuccessful putts were also found. Furthermore, we found even within a highly skilled cohort a high level of within and between variation in performance, gaze and kinematic measures. Conclusions: Findings reveal perceptual-cognitive expertise in golf putting is multi-faceted and goes beyond QE duration. We discuss the benefits of future research adopting an Ecological Dynamics approach to explore the complex interactions between the task, individual and environment. The challenge lies in collecting combined synchronised EEG and eye tracking data and we suggest future studies employ longitudinal designs to examine changes in expertise over time. It is proposed any applied recommendations are devised on an individual level

    Editorial: Executive function(s): Conductor, Orchestra or Symphony? Towards a Trans-Disciplinary Unification of Theory and Practice Across Development, in Normal and Atypical Groups

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    There are several theories of executive function(s) that tend to share some theoretical overlap yet are also conceptually distinct, each bolstered by empirical data (Norman and Shallice, 1986; Shallice & Burgess, 1991; Stuss and Alexander, 2007; Burgess, Gilbert, & Dumentheil, 2007; Burgess & Shallice, 1996; Miyake et al., 2000). The notion that executive processes are supervisory, and most in demand in novel situations was an early conceptualization of executive function that has been adapted and refined over time (Norman & Shallice, 1986; Shallice, 2001; Burgess, Gilbert & Dumentheil, 2007). Presently there is general consensus that executive functions are multi-componential (Shallice, 2001), and are supervisory only in the sense that attention in one form or another is key to the co-ordination of other hierarchically organized ‘lower’ cognitive processes. Attention in this sense is defined as (i) independent but interrelated attentional control processes (Stuss & Alexander, 2007); (ii) automatic orientation towards stimuli in the environment or internally–driven thought (Burgess, Gilbert & Dumontheil, 2007); (iii) the automatically generated interface between tacit processes and strategic conscious thought (Barker, Andrade, Romanowski, Morton and Wasti, 2006; Morton and Barker, 2010); and (iv) distinct but interrelated executive processes that maintain, update and switch across different sources of information (Miyake et al., 2000). One problem is that executive dysfunction or dysexecutive syndrome (Baddeley & Wilson, 1988) after brain injury typically produces a constellation of deficits across social, cognate, emotional and motivational domains that rarely map neatly onto theoretical frameworks (Barker, Andrade & Romanowski, 2004). As a consequence there is debate that conceptual theories of executive function do not always correspond well to the clinical picture (Manchester, Priestley & Jackson, 2004). Several studies have reported cases of individuals with frontal lobe pathology and impaired daily functioning despite having little detectable impairment on traditional tests of executive function (Shallice & Burgess, 1991; Eslinger & Damasio, 1985; Barker, Andrade & Romanowski, 2004; AndrĂ©s & Van der Linden, 2002; Chevignard et al., 2000; Cripe, 1998; Fortin, Godbout & Braun, 2003). There is also some suggestion that weak ecological validity limits predictive and clinical utility of many traditional measures of executive function (Burgess et al, 2006; Lamberts, Evans & Spikman, 2010; Barker, Morton, Morrison, McGuire, 2011). Complete elimination of environmental confounds runs the risk of generating results that cannot be generalized beyond constrained circumstances of the test environment (Barker, Andrade & Romanowski, 2004). Several researchers have concluded that a new approach is needed that is mindful of the needs of the clinician yet also informed by the academic debate and progress within the discipline (McFarquhar & Barker, 2012; Burgess et al., 2006). Finally, translational issues also confound executive function research across different disciplines (psychiatry, cognitive science, and developmental psychology) and across typically developing and clinical populations (including Autism Spectrum Disorders, Head Injury and Schizophrenia – Blakemore & Choudhury, 2006; Taylor, Barker, Heavey & McHale, 2013). Consequently, there is a need for unification of executive function approaches across disciplines and populations and narrowing of the conceptual gap between theoretical positions, clinical symptoms and measurement

    Topological Changes in the Functional Brain Networks Induced by Isometric Force Exertions Using a Graph Theoretical Approach: An EEG-based Neuroergonomics Study

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    Neuroergonomics, the application of neuroscience to human factors and ergonomics, is an emerging science focusing on the human brain concerning performance at work and in everyday settings. The advent of portable neurophysiological methods, including electroencephalography (EEG), has enabled measurements of real-time brain activity during physical tasks without restricting body movements. However, the EEG signatures of different physical exertion activity levels that involve the musculoskeletal system in everyday settings remain poorly understood. Furthermore, the assessment of functional connectivity among different brain regions during different force exertion levels remains unclear. One approach to investigating the brain connectome is to model the underlying mechanism of the brain as a complex network. This study applied employed a graph-theoretical approach to characterize the topological properties of the functional brain network induced by predefined force exertion levels, namely extremely light (EL), light (L), somewhat hard (SWH), hard (H), and extremely hard (EH) in two frequency bands, i.e., alpha and beta. Twelve female participants performed an isometric force exertion task and rated their perception of physical comfort at different physical exertion levels. A CGX-Mobile-64 EEG was used for recording spontaneous brain electrical activity. After preprocessing the EEG data, a source localization method was applied to study the functional brain connectivity at the source level. Subsequently, the alpha and beta networks were constructed by calculating the coherence between all pairs of 84 brain regions of interests that were selected using Brodmann Areas. Graph -theoretical measures were then employed to quantify the topological properties of the functional brain networks at different levels of force exertions at each frequency band. During an \u27extremely hard\u27 exertion level, a small-world network was observed for the alpha coherence network, whereas an ordered network was observed for the beta coherence network. The results suggest that high-level force exertions are associated with brain networks characterized by a more significant clustering coefficient, more global and local efficiency, and shorter characteristic path length under alpha coherence. The above suggests that brain regions are communicating and cooperating to a more considerable degree when the muscle force exertions increase to meet physically challenging tasks. The exploration of the present study extends the current understanding of the neurophysiological basis of physical efforts with different force levels of human physical exertion to reduce work-related musculoskeletal disorders

    The neuropsychological measure (EEG) of flow under conditions of peak performance

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    Flow is a mental state characterised by a feeling of energised focus, complete involvement and success when fully immersed in an activity. The dimensions of and the conditions required for flow to occur have been explored in a broad spectrum of situational contexts. The close relationship between flow and peak performance sparked an interest in ways to induce flow. However, any process of flow induction requires a measure to trace the degree to which flow is in fact occurring. Self-reports of the flow experience are subjective and provide ad hoc information. Psycho-physiological measures, such as EEG, can provide objective and continuous indications of the degree to which flow is occurring. Unfortunately few studies have explored the relationships between psycho-physiological measures and flow. The present study was an attempt to determine the EEG correlates of flow under conditions of peak performance. Twenty participants were asked to perform a continuous visuomotor task 10 times. Time taken per task was used as an indicator of task performance. EEG recordings were done concurrently. Participants completed an Abbreviated Flow Questionnaire (AFQ) after each task and a Game Flow Inventory (GFI) after having finished all 10 tasks. On completion, performance times and associated flow scores were standardised where after the sample was segmented into a high flow - peak performance and a low flow - low performance level. Multi-variate analysis of variance (MANOVA) was conducted on the performance, flow and EEG data to establish that a significant difference existed between the two levels. In addition, a one-way analysis of variance between high and low flow data was conducted for all variables and main effects were established. Inter-correlations of all EEG data at both levels were then conducted across four brain sites (F3, C3, P3, O1). In high flow only, results indicated increased lobeta power in the sensorimotor cortex together with a unique EEG pattern showing beta band synchronisation between the prefrontal and sensori-motor areas and de-synchronisation between all other areas, while all other frequencies (delta, theta, alpha, lobeta, hibeta, and gamma) remained synchronised across all scalp locations. These findings supported a theoretical neuropsychological model of flow.PsychologyD. Com. (Consulting Psychology

    DYNAMICS OF FUNCTIONAL CONNECTIVITY WITHIN CORTICAL MOTOR NETWORK DURING MOTOR LEARNING IN STROKE - CORRELATIONS WITH "TRUE" MOTOR RECOVERY

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    Arm motor recovery after stroke is usually incomplete; six months after onset about two-thirds of patients suffer from arm motor impairment that significantly impacts the individual's activities of daily living. Thus, novel concepts beyond current strategies for arm motor rehabilitation after stroke are needed. An essential approach for this is to better understand whether motor learning-related neural changes in stroke are similar with those in healthy controls and how these neural changes relate to recovery of the pre-morbid movement pattern or "true" recovery. Abnormal task-related activation in primary and non-primary motor cortices has been a consistent finding in functional MRI studies of stroke. Disturbed functional network architecture, e.g., the influence that one motor area exerts over another, also impacts stroke recovery. The outcome measures chosen to evaluate recovery are also important for the interpretation of these brain changes. Thus, the long-range goal of this work was to longitudinally investigate the changes in cortical motor function at two levels, regional (micro-circuitry, regional activation) and network (macro-circuitry, functional connectivity), following an arm-focused motor training in chronic stroke survivors and how these brain changes relate to recovery of the pre-morbid movement pattern or "true" recovery. In the Chapter I, we reviewed the literature concerning the pathophysiology of stroke, neural substrates of motor control, and motor learning principles and neural substrates in healthy and pathological (stroke) brain. In the Chapter II, we examined the relationships between task-related motor activation and clinical and kinematic metrics of arm motor impairment in survivors of subcortical stroke. We found evidence that primary motor activation was significantly correlated to kinematic metrics of arm motor impairment, but not with clinical metrics. In the Chapter III, we longitudinally investigated the regional changes in motor-related activation (functional MRI) in primary and non-primary motor areas following an arm-focused motor training in stroke survivors and age-sex matched healthy controls. We demonstrated that similar changes in the motor areas contralateral to the trained arm were found with training in both stroke and healthy participants. We also demonstrated a significant increase in motor performance in both groups as well as a normalization of the correlations between bilateral motor activation and movement kinematics in participants with stroke. In the Chapter IV, we also investigated the changes in functional connectivity between primary and non-primary motor areas following an arm-focused motor training and how these changes correlate with "true" motor recovery. We demonstrated significant enhanced functional connectivity in motor areas contralateral to the trained hand (or ipsilesional), although no "normalization" of the inter-hemispheric inhibition following training in our survivors. We also showed a "normalization" of the relationships between cortical motor functional connectivity and movement kinematics. In the Chapter V, we concluded that the present dissertation work support the hypotheses that motor system is plastic at different levels, regional and network, even in the chronic stage of stroke and some of these changes are similar with those reported in healthy controls. Further, these changes provide a substrate for "true" recovery. These findings promote the use of neuroimaging and kinematic metrics to improve our understanding of the neural substrates underlying reorganization in remaining intact brain structures after stroke. Such an approach may further enable monitoring recovery or compensation based on this reorganization and evaluating new treatment regimes that assist motor recovery

    Modern Developments in Transcranial Magnetic Stimulation (TMS) – Applications and Perspectives in Clinical Neuroscience

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    Transcranial magnetic stimulation (TMS) is being increasingly used in neuroscience and clinics. Modern advances include but are not limited to the combination of TMS with precise neuronavigation as well as the integration of TMS into a multimodal environment, e.g., by guiding the TMS application using complementary techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), diffusion tensor imaging (DTI), or magnetoencephalography (MEG). Furthermore, the impact of stimulation can be identified and characterized by such multimodal approaches, helping to shed light on the basic neurophysiology and TMS effects in the human brain. Against this background, the aim of this Special Issue was to explore advancements in the field of TMS considering both investigations in healthy subjects as well as patients

    Exploiting physiological changes during the flow experience for assessing virtual-reality game design.

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    Immersive experiences are considered the principal attraction of video games. Achieving a healthy balance between the game's demands and the user's skills is a particularly challenging goal. However, it is a coveted outcome, as it gives rise to the flow experience – a mental state of deep concentration and game engagement. When this balance fractures, the player may experience considerable disinclination to continue playing, which may be a product of anxiety or boredom. Thus, being able to predict manifestations of these psychological states in video game players is essential for understanding player motivation and designing better games. To this end, we build on earlier work to evaluate flow dynamics from a physiological perspective using a custom video game. Although advancements in this area are growing, there has been little consideration given to the interpersonal characteristics that may influence the expression of the flow experience. In this thesis, two angles are introduced that remain poorly understood. First, the investigation is contextualized in the virtual reality domain, a technology that putatively amplifies affective experiences, yet is still insufficiently addressed in the flow literature. Second, a novel analysis setup is proposed, whereby the recorded physiological responses and psychometric self-ratings are combined to assess the effectiveness of our game's design in a series of experiments. The analysis workflow employed heart rate and eye blink variability, and electroencephalography (EEG) as objective assessment measures of the game's impact, and self-reports as subjective assessment measures. These inputs were submitted to a clustering method, cross-referencing the membership of the observations with self-report ratings of the players they originated from. Next, this information was used to effectively inform specialized decoders of the flow state from the physiological responses. This approach successfully enabled classifiers to operate at high accuracy rates in all our studies. Furthermore, we addressed the compression of medium-resolution EEG sensors to a minimal set required to decode flow. Overall, our findings suggest that the approaches employed in this thesis have wide applicability and potential for improving game designing practices

    The relationship between cortical beta oscillations and motor learning

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    The ability to learn and retain new motor skills is pivotal for everyday life activities and motor rehabilitation after stroke. However, people show considerable individual differences in motor learning. Understanding the neurophysiological processes underlying these individual differences is of significant scientific and clinical importance. At a mechanistic level, oscillations in the beta frequency range (15–30 Hz), fundamental for motor control, reflect underlying cortical inhibitory and excitatory mechanisms. As such, they may provide appropriate biomarkers with which to bridge the gap between cellular and behavioural accounts of cortical plasticity in both healthy and diseased states. This thesis explores the interplay between cortical beta oscillations and individual differences in short-term motor learning within the context of healthy ageing and after stroke. First, I assess the test-retest reliability of resting and movement-related beta estimates in a group of healthy subjects across several weeks. By demonstrating that EEG-derived power measures of beta activity are highly reliable, I validate the notion that these measures reflect meaningful individual differences that can be utilized in basic research and in the clinic. Second, I probe the neurophysiological mechanisms underlying natural inter-individual differences in short-term motor learning. I demonstrate comparable motor learning ability between young and elderly individuals, despite age-related alterations in beta activity. Implementing a multivariate approach, I show that beta dynamics explain some of the individual differences in post-training tracking performance. Third, I extend this line of research by focusing on stroke-related inter-individual variations in motor learning. Employing the same tasks and analyses, I demonstrate preserved, albeit reduced motor learning ability and no aberrant beta activity after stroke. Beta dynamics explained some of the individual differences in stroke patients’ performance 24 hours after training, and may thus offer novel targets for therapeutic interventions
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