Three experiments were conducted to determine whether attention-related changes in luminance detectability reflect a modulation of early sensory processing. Experiments 1 and 2 used peripheral cues to direct attention and found substantial effects of cue validity on target detectability; these effects were consistent with a sensory-level locus of selection but not with certain memory- or decision-level mechanisms. In Experiment 3, event-related brain potentials were recorded in a similar paradigm using central cues, and attention was found to produce changes in sensory-evoked brain activity beginning within the 1st 100 ms of stimulus processing. These changes included both an enhancement of sensory responses to attended stimuli and a suppression of sensory responses to unattended stimuli; the enhancement and suppression effects were isolated to different neural responses, indicating that they may arise from independent attentional mechanisms.

The mechanism by which visual-spatial attention affects the detection of faint signals has been the subject of considerable debate. It is well known that spatial cuing speeds signal detection. This may imply that attentional cuing modulates the processing of sensory information during detection or, alternatively, that cuing acts to create decision bias favoring input at the cued location. These possibilities were evaluated in 3 spatial cuing experiments. Peripheral cues were used in Experiment 1 and central cues were used in Experiments 2 and 3. Cuing similarly enhanced measured sensitivity, P(A) and d', for simple luminance detection in all 3 experiments. Under some conditions it also induced shifts in decision criteria (beta). These findings indicate that visual-spatial attention facilitates the processing of sensory input during detection either by increasing sensory gain for inputs at cued locations or by prioritizing the processing of cued inputs.

Many studies have found that stimuli can be discriminated more accurately at attended locations than at unattended locations, and such results have typically been taken as evidence for the hypothesis that attention operates by allocating limited perceptual processing resources to attended locations. An alternative proposal, however, is that attention acts to reduce uncertainty about target location, thereby increasing accuracy by decreasing the number of noise sources. To distinguish between these alternatives, we conducted 6 spatial cuing experiments in which target location uncertainty was eliminated. Despite the absence of uncertainty, target discriminations were more accurate at the attended location, consistent with resource allocation models. These cue validity effects were observed under a broad range of conditions, including central and peripheral cuing, but were absent at very short cue-target delay intervals.

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.