Feature-based attention (FBA) is a selection mechanism implemented in the visual system that facilitates perceptual representations of behaviorally-relevant stimulus features at the expense of behaviorally- irrelevant features in order to aid decision-making. Traditional accounts of FBA indicate that this facilitation occurs via the modulation of feature- selective neurons in visual cortex: the responses of neurons that are maximally driven by (or "tuned to") the relevant feature are enhanced (termed sensory gain or attentional gain), while the responses of other neurons are suppressed. However, recent theoretical and psychophysical evidence suggests potential modifications to this longstanding model, wherein the locus of attentional gain depends not only on the shape of the neuronal tuning functions, but also on the nature of the perceptual task. For example, during a coarse discrimination task, in which an observer must discriminate a target feature (e.g., 90° oriented line) from a set of highly dissimilar distractors (e.g., 180° oriented line), neurons tuned to the target (termed on- channel or on-target neurons) are highly informative given a large change in firing rates between stimulus alternatives (i.e., greater signal-to-noise ratio or SNR). During a fine discrimination task, however, in which the target and distractors are highly similar (e.g., 90° oriented line among 85° oriented lines), on-channel neurons provide little sensory evidence since they respond nearly as well to both the target and distractors. In this case, attentional gain should be applied to neurons tuned away from the target feature (interchangeably termed off- channel or off-target neurons) that produce a greater SNR. Here, I present a set of psychophysical (Chapter 1) and neuroimaging (Chapters 2 and 3) studies in support of an optimal gain model of FBA that flexibly targets sensory inputs based on informativeness. Together, the studies suggest that human observers are able to optimally deploy attentional gain according to task demands to feature- selective populations in visual cortex. Furthermore, the level of off-channel modulation is predictive of subjects' behavioral performance on a range of difficult fine discrimination tasks, indicating that these inputs are ultimately utilized in perceptual decision-making

Space-based and object-based attention studies suggest these selective mechanisms can be involuntarily or voluntarily deployed. We performed two experiments exploring automatic deployment of object-mediated space-based attention. Subjects performed a modified flanker task with targets and distractors presented within the same or different object frames. If object selection occurs automatically, the flanker effect should be larger in the same condition. However, both object frame conditions produced equally large flanker effects within accuracy. Next, we manipulated the observer’s sustained attentional spotlight via an inducer task to determine whether object-mediated space-based selection depends on initial spotlight size. This time, object-based effects emerged only during narrow spotlight conditions. The results from both experiments suggest the deployment of object-based attention may occur when spatial attention is initially focused narrowly, even when such selection is suboptimal. These results add to the existing literature while reconciling previous inconsistent findings of object-based selection.

The study aimed to examine the relationship between mindfulness and affective thought dynamics. We hypothesized two principle components that are associated with trait mindfulness. Twenty-three participants wrote ten successive words from six seed words, rated affective dimensions on these words, and completed the five-facet mindfulness questionnaire (FFMQ; act-aware, describing, non-judgment, non-reactivity, and observing). Principle Components Analysis (PCA) was used reduce the affective dimensions and Markov-Chain to analyze state changes. Linear regressions were then used to examine the relationships between the PCs and FFMQ. Our results revealed one PC (valence, arousal, and importance). Linear regressions revealed that observing, act-aware, and describing predicted the probability of transitioning from negative to positive [P(N->P)] (B = 1.77, p = 0.040), P(PP) (B = 1.77, p = 0.040), and P(PP) (B = 1.77, p = 0.040), respectively. These state shifts may explain improvements in emotion regulation through mindfulness, which directs these affective shifts.

After committing an error, people slow down to avoid subsequent errors. This post-error slowing (PES) is sometimes considered a functional adaption that leads to improved post-error accuracy (PIA). However, the co-occurrence of these two phenomena is inconsistent, bringing into question the functional role of PES. We first reanalyzed previous flanker data to investigate the functionality of these adjustments by comparing RT and accuracy between post-correct and post-error trials. Using a flanker task with absent, congruent, or incongruent distractors, we can explore whether cognitive demand differences yield different effects on PES and PIA. Instead, a significant PIA effect was uniformly observed across conditions, while a not significant post-error speeding effect suggests they are distinct phenomena. A second experiment with a shortened cue period and intertrial interval produced only a marginally significant post-error speeding effect. In sum, these data suggest these phenomena are distinct and their occurrence is reliant on task demands.