UC San Diego

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