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While numerous studies have explored the mechanisms of reward-based decisions (the choice of action based on expected gain), few have asked how reward influences attention (the selection of information relevant for a decision). Here we show that a powerful determinant of attentional priority is the association between a stimulus and an appetitive reward. A(More)
We describe a closed-loop brain-computer interface that re-ranks an image database by iterating between user generated 'interest' scores and computer vision generated visual similarity measures. The interest scores are based on decoding the electroencephalographic (EEG) correlates of target detection, attentional shifts and self-monitoring processes, which(More)
Novelty modulates sensory and reward processes, but it remains unknown how these effects interact, i.e., how the visual effects of novelty are related to its motivational effects. A widespread hypothesis, based on findings that novelty activates reward-related structures, is that all the effects of novelty are explained in terms of reward. According to this(More)
OBJECTIVE As we move through an environment, we are constantly making assessments, judgments and decisions about the things we encounter. Some are acted upon immediately, but many more become mental notes or fleeting impressions-our implicit 'labeling' of the world. In this paper, we use physiological correlates of this labeling to construct a hybrid(More)
Our group has been investigating the development of BCI systems for improving information delivery to a user, specifically systems for triaging image content based on what captures a user's attention. One of the systems we have developed uses single-trial EEG scores as noisy labels for a computer vision image retrieval system. In this paper we investigate(More)
As we navigate our environment, we are constantly assessing the objects we encounter and deciding on their subjective interest to us. In this study, we investigate the neural and ocular correlates of this assessment as a step towards their potential use in a mobile human-computer interface (HCI). Past research has shown that multiple physiological signals(More)
Objective. We investigated the neural correlates of workload buildup in a fine visuomotor task called the boundary avoidance task (BAT). The BAT has been known to induce naturally occurring failures of human-machine coupling in high performance aircraft that can potentially lead to a crash – these failures are termed pilot induced oscillations (PIOs).(More)
Multi-echo fMRI, particularly the multi-echo independent component analysis (ME-ICA) algorithm, has previously proven useful for increasing the sensitivity and reducing false positives for functional MRI (fMRI) based resting state connectivity studies. Less is known about its efficacy for task-based fMRI, especially at the single subject level. This work,(More)
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