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Accurate matching of unfamiliar faces is vital in security and forensic applications, yet previous research has suggested that humans often perform poorly when matching unfamiliar faces. Hairstyle and facial hair can strongly influence unfamiliar face matching but are potentially unreliable cues. This study investigated whether increased attention to the more stable internal face features of eyes, nose, and mouth was associated with more accurate face-matching performance. Forty-three first-year psychology students decided whether two simultaneously presented faces were of the same person or not. The faces were displayed for either 2 or 6 seconds, and had either similar or dissimilar hairstyles. The level of attention to internal features was measured by the proportion of fixation time spent on the internal face features and the sensitivity of discrimination to changes in external feature similarity. Increased attention to internal features was associated with increased discrimination in the 2-second display-time condition, but no significant relationship was found in the 6-second condition. Individual differences in eye-movements were highly stable across the experimental conditions. Unfamiliar face matching is unreliableThe ability to match two face images accurately is critical in security and forensic applications. Yet despite our daily interaction with faces, unfamiliar face-matching performance appears to be far from perfect. Previous studies have examined facematching performance in retail (Kemp, Towell, & Pike, 1997), forensic (Bruce et al., 1999) and security (Lee, Vast, & Butavicius, 2006) applications. In each of these cases, participants were asked to decide if two simultaneously presented face images were of the same person or different. The studies reported miss rates (where faces of two different people were identified as being of the same person) that ranged from 13% to 49%, and false-alarm rates (where two face images

This study tested whether the display of rings indicating the probability of target detection would improve human performance on a simulated active sonar detection task. Participants viewed a series of simulated sonar returns and decided whether a target was present or not. Participants performed the task both with and without uncertainty range rings that indicated 90% and 10% detectability ranges. The probability of detection rings did not improve the overall ability of participants to distinguish targets from noise, but did appear to influence response bias and spatial attention. These results suggest that displaying probability of detection may not be an effective way of improving the performance of sonar system operators.

Changes in task demands can trigger a complex and dynamic self-regulatory process which influences a range of metacognitive and physiological states. Individuals continuously monitor task cues, the level of task performance and other internal states in order to form an assessment of current task demands. Cognitive-energetic theories propose that individuals possess a finite amount of available resources which can be allocated to meet task demands.Increased task demands will generate an increase in the level of resources allocated in order to maintain task performance, but only up to a point of maximum effort which is determined by the level of available resources. However, while the level of available resources is finite, it is not necessarily fixed. It is generally held that the sustained allocation of resources depletes the level of available resources, so that prior high task demands will reduce the level of available resources and therefore the maximum level of resources allocated to meet current high task demands. Reduced levels of available resources may also cause a compensatory increase in the level of allocated resources at low demand levels in order to protect against possible performance lapses caused by low resource availability.The current thesis proposes that, instead of a general process by which all resource allocation depletes the level of available resources, the allocation of attentional control resources depletes the level of available resources but the allocation of information processing resources provides an opposing short-term increase in the level of available resources. This proposal provides a way of accounting for potentially contradictory empirical data and integrating ego depletion theory and malleable resources theory. The thesis develops a resource-based self-regulatory dynamic control model of the human response to task demands in which the level of available and allocated information processing and attentional control resources both influence and are influenced by current and prior task demands. The model also identifies how the level of available and allocated resources contribute to the metacognitive states of perceived difficulty, effort, activation and valence and the physiological state of pupil diameter. Three experiments were conducted to test predictions arising from the model. Experiments 1 and 2 manipulated the level of task demands within a range of relatively simple, short-term, intermittent cognitive and motor control tasks and Experiment 3 manipulated demand level within a sustained, continuous, and complex control task in order to identify the validity of the proposed model under a range of task conditions. The experiments provided mixed support for the model. The proposal that attentional control demands and information processing demands had opposing effects on the level of available resources was broadly supported by the empirical data which suggests that resource theories need to distinguish the effects of these two types of task demands. However, the ...