In modern psychology, vigilance, also termed sustained concentration, is defined as the ability to maintain concentrated attention over prolonged periods of time.[1] During this time, the person attempts to detect the appearance of a particular target stimulus. The individual watches for a signal stimulus that may occur at an unknown time.[2]
The study of vigilance has expanded since the 1940s mainly due to the increased interaction of people with machines for applications involving monitoring and detection of rare events and weak signals. Such applications include air traffic control, inspection and quality control, automated navigation, military and border surveillance, and lifeguarding.[citation needed]
Origins of research
The systematic study of vigilance was initiated by Norman Mackworth during World War II. Mackworth authored "The breakdown of vigilance during prolonged visual search" in 1948 and this paper is the seminal publication on vigilance.[3] Mackworth's 1948 study investigated the tendency of radar and sonar operators to miss rare irregular event detections near the end of their watch. Mackworth simulated rare irregular events on a radar display by having the test participants watch an unmarked clock face over a 2-hour period. A single clock hand moved in small equal increments around the clock face, with the exception of occasional larger jumps. This device became known as the Mackworth Clock. Participants were tasked to report when they detected the larger jumps. Mackworth's results indicated a decline in signal detection over time, known as a vigilance decrement. The participants' event detection declined between 10 and 15 percent in the first 30 minutes and then continued to decline more gradually for the remaining 90 minutes. Mackworth's method became known as the "Clock Test" and this method has been employed in subsequent investigations.
Vigilance decrement
Vigilance decrement is defined as "deterioration in the ability to remain vigilant for critical signals with time, as indicated by a decline in the rate of the correct detection of signals".[4] Vigilance decrement is most commonly associated with monitoring to detect a weak target signal. Detection performance loss is less likely to occur in cases where the target signal exhibits a high saliency. For example, a radar operator would be unlikely to miss a rare target at the end of a watch if it were a large bright flashing signal, but might miss a small dim signal.
Under most conditions, vigilance decrement becomes significant within the first 15 minutes of attention,[5] but a decline in detection performance can occur more quickly if the task demand conditions are high.[6] This occurs in both experienced and novice task performers.[7] Vigilance had traditionally been associated with low cognitive demand and vigilance decrement with a decline in arousal pursuant to the low cognitive demand,[8] but later studies indicated that vigilance is hard work, requiring the allocation of significant cognitive resources, and inducing significant levels of stress.[9]
Vigilance decrement and Signal Detection Theory
Green and Swets[10] formulated the Signal Detection Theory, or SDT, in 1966 to characterize detection task performance sensitivity while accounting for both the observer's perceptual ability and willingness to respond. SDT assumes an active observer making perceptual judgments as conditions of uncertainty vary. A decision maker can vary their response bias, characterized by Beta, to allow more or less correct detections (hits), but at the respective cost of more or less false alarms. This is termed a criterion shift. The degree to which the observer tolerates false alarms to achieve a higher rate of detection is termed the bias. Bias represents a strategy to minimize the consequences of missed targets and false alarms. As an example, the lookout during a bank robbery must set a threshold for how "cop-like" an approaching individual or vehicle may be. Failing to detect the "cop" in a timely fashion may result in jail time, but a false alarm will result in a lost opportunity to steal money. In order to produce a bias-free measure, d' is calculated by measuring the distance between the means of the signal and non-signals (noise) and scaling by the standard deviation of the noise. Mathematically, this can be accomplished by subtracting the z-score of the hit rate from the z-score of the false alarm rate. Application of SDT to the study of vigilance indicates that in most, but not all cases, vigilance decrement is not the result of a reduction in sensitivity over time.[11] In most cases a reduction of detections is accompanied by a commensurate reduction in false alarms, such that d' is relatively unchanged.
Vigilance Taxonomy: discrimination type and event rate
Mental workload, or cognitive load, based on task differences can significantly affect the degree of vigilance decrement. In 1977, Parasuraman and Davies investigated the effect of two task difference variables on d', and proposed the existence of a vigilance taxonomy based on discrimination type and event rate. Parasuraman and Davies employed discrimination tasks which were either successive or simultaneous, and presented both at high and low event rates. Successive discrimination tasks where critical information must be retained in working memory generate a greater mental workload than simultaneous comparison tasks. Their results indicate the type of discrimination and the rate at which discriminable events occur interact to affect sustained attention. Successive discrimination tasks indicate a greater degree of vigilance decrement than simultaneous discriminations, such as comparisons, but only when event rates are relatively high. For detection tasks, empirical evidence suggests that an event rate at or above 24 events per minute significantly reduces sensitivity. Further investigation has indicated that when the discrimination task is difficult, a decrement can occur when the mental workload is low, as with simultaneous comparisons, at both high and low event rates.[12][13]
The effect of event rate on monitoring task performance can be affected by the addition of non-target salient objects at varying frequencies. Clock test research conducted in the late 1950s and 1960s indicates that an increase in event rate for rare irregular low salience signals reduced the vigilance decrement. When non-target "artificial" signals similar to target signals were introduced, the vigilance decrement was also reduced. When the "artificial" signal differed significantly from the target signal, no performance improvement was measured.[14]
Other dimensions beyond event rate and discrimination task difficulty affect the performance of vigilance tasks and are factors in the Vigilance Taxonomy. These include but are not limited to: sensory modality, or combinations of sensory modalities; source complexity; signal duration; signal intensity; multiple signal sources; discrete versus continuous events; intermittent versus continuous attention requirement; observer skill level; and stimulation value.[15]
Measuring mental workload during vigilance tasks
Initial Vigilance Taxonomy studies relied on assumptions regarding the mental workload associated with discrimination tasks, rather than a direct quantification of that workload. Successive discriminations, for example, were assumed to impose a greater workload than simultaneous discriminations. Beginning in the late 1990s, neuroimaging techniques such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and Transcranial Doppler sonography (TCD) have been employed to independently assess brain activation and mental workload during vigilance experiments. These neuroimaging techniques estimate brain activation by measuring the blood flow (fMRI and TCD) or glucose metabolism (PET) associated with specific brain regions. Research employing these techniques has linked increases in mental workload and allocation of attentional resources with increased activity in the prefrontal cortex. Studies employing PET, fMRI and TCD indicate a decline in activity in the prefrontal cortex correlates with vigilance decrement. Neuroimaging studies also indicate that the control of vigilance may reside in the right cerebral hemisphere in a variety of brain regions.[16]
Associated brain regions
Reductions in arousal generally correspond to reductions in vigilance. Arousal is defined as a component of vigilance, though it is not, as one may believe, the sole source of the main effect of the vigilance decrement.[17]
As such, subcortical brain regions associated with arousal play a critical role in the performance of vigilance tasks. Because the amygdala plays an important role in the recognition of emotional stimuli, it appears to be an important brain structure in the regulation of vigilance.[18]
Several cortical brain regions are associated with attention and vigilance. These include the right frontal, inferior parietal, prefrontal, superior temporal cortices and cingulate gyrus. In the frontal lobe, fMRI and TCD data indicate that brain activation increases during vigilance tasks with greater activation in the right hemisphere. Lesion and split brain studies indicate better right-brain performance on vigilance tasks, indicating an important role for the right frontal cortex in vigilance tasks.[21] Activity in the LC noradrenergic system is associated with the alert waking state in animals through the release of noradrenaline. Chemically blocking the release of noradrenaline induces drowsiness and lapses in attention associated with a vigilance decrement. The dorsolateral prefrontal cortex exhibits a higher level of activation than other significantly active areas, indicating a key role in vigilance.
The cingulate gyrus differs from other brain regions associated with vigilance in that it exhibits less activation during vigilance tasks. The role of the cingulate gyrus in vigilance is unclear, but its proximity and connections to the corpus callosum, which regulates interhemispheric activity, may be significant. Reduced activation in the cingulate gyrus may be a by-product of asymmetrical frontal lobe activation initiated in the corpus callosum.[22]
Stress
Stressful activities involve continuous application of extensive cognitive resources. If the vigilance decrement were the result of less brain activity rather than more, vigilance tasks could not be expected to be stressful. High levels of epinephrine and norepinephrine are correlated with continuous extensive mental workloads, making these compounds good chemical indicators of stress levels. Subjects performing vigilance tasks exhibit elevated levels of epinephrine and norepinephrine, consistent with high stress levels and indicative of a significant mental workload.[23] Vigilance tasks may therefore be assumed to be stressful, hard mental work.
Individual differences in performance
Large individual differences in monitoring task performance have been reported in a number of vigilance studies. For a given task, however, the vigilance decrement between subjects is generally consistent over time, such that individuals exhibiting relatively higher levels of performance for a given task maintain that level of performance over time.[24] For different tasks, however, individual performance differences are not consistent[25] for any one individual may not correlate well from one task to another. An individual exhibiting no significant decrement while performing a counting monitoring task may exhibit a significant decrement during a clock test. Relative performance between subjects may also vary based on the nature of the task.[26] For example, subjects whose task performance is well correlated for a successive task may exhibit a poor performance correlation for a simultaneous task. Conversely, subjects performing similar monitoring tasks, such as radar versus sonar target detection, can be expected to exhibit similar patterns of task performance.
Levine et al. propose that individual differences in task performance may be influenced by task demands. For example, some tasks may require rapid comparisons or "perceptual speed", while others may require "flexibility of closure", such as detection of some predefined object within a cluttered scene.[27] Linking task performance differences to task demands is consistent with the Vigilance Taxonomy proposed by Parasuraman and Davies described above, and also supports the hypothesis that vigilance requires mental work, rather than being a passive activity.
Reducing the vigilance decrement with amphetamines
Considerable research has been devoted to the reduction of the vigilance decrement. As noted above, the addition of non-target signals can improve task performance over time if the signals are similar to the target signals. Additionally, practice, performance feedback, amphetamines and rest are believed to moderate temporal performance decline without reducing sensitivity.[28]
Beginning in the mid-1940s research was conducted to determine whether amphetamines could reduce or counteract the vigilance decrement.[29][30] In 1965, Jane Mackworth conducted clock test experiments in which half of 56 participants were given a strong amphetamine and half were given a placebo.[31] Mackworth also provided false feedback and feedback in separate trials. Mackworth analyzed detection and false alarm rates to determine d', the measure of sensitivity. Participants dosed with amphetamine exhibited no increased sensitivity but did exhibit a highly significant reduction in vigilance decrement. In feedback trials, sensitivity increased while the performance decline was significantly reduced. In trials where both amphetamine and feedback were given, sensitivity was increased and there was no significant vigilance decrement.
Practice and sustained attention
Training and practice significantly reduce the vigilance decrement, reduce the false alarm rate, and may improve sensitivity for many sustained attention tasks. Changes in strategy or bias may improve task performance. Improvements based on such a criterion shift would be expected to occur early in the training process.[32] Experiments involving both audio and visual stimuli indicate the expected training performance improvement within the first five to ten hours of practice or less.[33][34][35]
Training improvements may also occur due to the reduced mental workload associated with task automaticity. In pilotage and airport security screening experiments, trained or expert subjects exhibit better detection of low salience targets, a reduction in false alarms, improved sensitivity, and a significantly reduced vigilance decrement. In some cases the vigilance decrement was eliminated or not apparent.[36][37][38]
Aging
Vigilance research conducted with subjects across a range of ages conflict regarding the ability to maintain alertness and sustained attention with age. In 1991, Parasuraman and Giambra reported a trend towards lower detection rates and higher false alarm rates with age when comparing groups between 19 and 27, 40 and 55, and 70 and 80 years old.[39] Deaton and Parasuraman reported in 1993 that beyond the age of 40 years, a trend towards lower detection rates and higher false alarm rates occurs in both cognitive tasks and sensory tasks, with higher and lower mental workloads respectively.[40] Berardi, Parasuraman and Haxby reported no differences in 2001 in the overall levels of vigilance and the ability to sustain attention over time for when comparing middle aged (over 40) and younger subjects.[41] Age dependent differences in cognitive tasks may differ with task type and workload, and some differences in detection and false alarms may be due to the reduction in the sensitivity of sensory organs.
Lack of habituation
Early theories of vigilance explained the reduction of electrophysiological activity over time associated with the vigilance decrement as a result of neural habituation.[42] Habituation is the decrease in neural responsivity due to repeated stimulation. Under passive conditions, when no task is performed, participants exhibit attenuated N100 Event Related Potentials (ERP) that indicate neural habituation, and it was assumed that habituation was also responsible for the vigilance decrement. More recent ERP studies indicate that when performance declines during a vigilance task, N100 amplitude was not diminished. These results indicate that vigilance decrement is not the result of boredom or a reduction in neurological sensitivity.[43][44]
Attention is the concentration of awareness on some phenomenon to the exclusion of other stimuli. It is a process of selectively concentrating on a discrete aspect of information, whether considered subjective or objective. William James (1890) wrote that "Attention is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought. Focalization, concentration, of consciousness are of its essence." Attention has also been described as the allocation of limited cognitive processing resources. Attention is manifested by an attentional bottleneck, in terms of the amount of data the brain can process each second; for example, in human vision, only less than 1% of the visual input data can enter the bottleneck, leading to inattentional blindness.
Arousal is the physiological and psychological state of being awoken or of sense organs stimulated to a point of perception. It involves activation of the ascending reticular activating system (ARAS) in the brain, which mediates wakefulness, the autonomic nervous system, and the endocrine system, leading to increased heart rate and blood pressure and a condition of sensory alertness, desire, mobility, and reactivity.
In cognitive psychology, cognitive load refers to the amount of working memory resources used. However, it is essential to distinguish it from the actual construct of Cognitive Load (CL) or Mental Workload (MWL), which is studied widely in many disciplines. According to work conducted in the field of instructional design and pedagogy, broadly, there are three types of cognitive load: intrinsic cognitive load is the effort associated with a specific topic; extraneous cognitive load refers to the way information or tasks are presented to a learner; and germane cognitive load refers to the work put into creating a permanent store of knowledge. However, over the years, the additivity of these types of cognitive load has been investigated and questioned. Now it is believed that they circularly influence each other.
The term workload can refer to several different yet related entities.
Inattentional blindness or perceptual blindness occurs when an individual fails to perceive an unexpected stimulus in plain sight, purely as a result of a lack of attention rather than any vision defects or deficits. When it becomes impossible to attend to all the stimuli in a given situation, a temporary "blindness" effect can occur, as individuals fail to see unexpected but often salient objects or stimuli.
Age-related memory loss, sometimes described as "normal aging", is qualitatively different from memory loss associated with types of dementia such as Alzheimer's disease, and is believed to have a different brain mechanism.
Neuroergonomics is the application of neuroscience to ergonomics. Traditional ergonomic studies rely predominantly on psychological explanations to address human factors issues such as: work performance, operational safety, and workplace-related risks. Neuroergonomics, in contrast, addresses the biological substrates of ergonomic concerns, with an emphasis on the role of the human nervous system.
Mental chronometry is the scientific study of processing speed or reaction time on cognitive tasks to infer the content, duration, and temporal sequencing of mental operations. Reaction time is measured by the elapsed time between stimulus onset and an individual's response on elementary cognitive tasks (ECTs), which are relatively simple perceptual-motor tasks typically administered in a laboratory setting. Mental chronometry is one of the core methodological paradigms of human experimental, cognitive, and differential psychology, but is also commonly analyzed in psychophysiology, cognitive neuroscience, and behavioral neuroscience to help elucidate the biological mechanisms underlying perception, attention, and decision-making in humans and other species.
The psychological and physiological effects of meditation have been studied. In recent years, studies of meditation have increasingly involved the use of modern instruments, such as fMRI and EEG, which are able to observe brain physiology and neural activity in living subjects, either during the act of meditation itself or before and after meditation. Correlations can thus be established between meditative practices and brain structure or function.
A psychomotor vigilance task (PVT) is a sustained-attention, reaction-timed task that measures the consistency with which subjects respond to a visual stimulus. Research indicates increased sleep debt or sleep deficit correlates with deteriorated alertness, slower problem solving, declined psychomotor skills, and increased rate of false responses.
Norman H. "Mack" Mackworth (1917–2005) was a British psychologist and cognitive scientist known for his pioneering work in the study of boredom, attention, and vigilance; the Mackworth Clock test has been used since the 1940s in the study of vigilance.
The Mackworth Clock is an experimental device used in the field of experimental psychology to study the effects of long term vigilance on the detection of signals. It was originally created by Norman Mackworth as an experimental simulation of long term monitoring by radar operators in the British Air Force during World War II. The device has a large black pointer in a large circular background like a clock. The pointer moves in short jumps like the second hand of an analog clock, approximately every second. At infrequent and irregular intervals, the hand makes a double jump, e.g. 12 times every 30 seconds. The task is to detect when the double jumps occur by pressing a button. Typically, Mackworth's participants would do this task for two hours. The Mackworth Clock was used to establish one of the fundamental findings in the vigilance and sustained attention literature: the vigilance decrement decreases notably after 30 minutes on task. The test continues to be used today in vigilance research in various forms, including computer-displayed versions.
The visual N1 is a visual evoked potential, a type of event-related electrical potential (ERP), that is produced in the brain and recorded on the scalp. The N1 is so named to reflect the polarity and typical timing of the component. The "N" indicates that the polarity of the component is negative with respect to an average mastoid reference. The "1" originally indicated that it was the first negative-going component, but it now better indexes the typical peak of this component, which is around 150 to 200 milliseconds post-stimulus. The N1 deflection may be detected at most recording sites, including the occipital, parietal, central, and frontal electrode sites. Although, the visual N1 is widely distributed over the entire scalp, it peaks earlier over frontal than posterior regions of the scalp, suggestive of distinct neural and/or cognitive correlates. The N1 is elicited by visual stimuli, and is part of the visual evoked potential – a series of voltage deflections observed in response to visual onsets, offsets, and changes. Both the right and left hemispheres generate an N1, but the laterality of the N1 depends on whether a stimulus is presented centrally, laterally, or bilaterally. When a stimulus is presented centrally, the N1 is bilateral. When presented laterally, the N1 is larger, earlier, and contralateral to the visual field of the stimulus. When two visual stimuli are presented, one in each visual field, the N1 is bilateral. In the latter case, the N1's asymmetrical skewedness is modulated by attention. Additionally, its amplitude is influenced by selective attention, and thus it has been used to study a variety of attentional processes.
Emotion perception refers to the capacities and abilities of recognizing and identifying emotions in others, in addition to biological and physiological processes involved. Emotions are typically viewed as having three components: subjective experience, physical changes, and cognitive appraisal; emotion perception is the ability to make accurate decisions about another's subjective experience by interpreting their physical changes through sensory systems responsible for converting these observed changes into mental representations. The ability to perceive emotion is believed to be both innate and subject to environmental influence and is also a critical component in social interactions. How emotion is experienced and interpreted depends on how it is perceived. Likewise, how emotion is perceived is dependent on past experiences and interpretations. Emotion can be accurately perceived in humans. Emotions can be perceived visually, audibly, through smell and also through bodily sensations and this process is believed to be different from the perception of non-emotional material.
Cognitive inhibition refers to the mind's ability to tune out stimuli that are irrelevant to the task/process at hand or to the mind's current state. Additionally, it can be done either in whole or in part, intentionally or otherwise. Cognitive inhibition in particular can be observed in many instances throughout specific areas of cognitive science.
Automation bias is the propensity for humans to favor suggestions from automated decision-making systems and to ignore contradictory information made without automation, even if it is correct. Automation bias stems from the social psychology literature that found a bias in human-human interaction that showed that people assign more positive evaluations to decisions made by humans than to a neutral object. The same type of positivity bias has been found for human-automation interaction, where the automated decisions are rated more positively than neutral. This has become a growing problem for decision making as intensive care units, nuclear power plants, and aircraft cockpits have increasingly integrated computerized system monitors and decision aids to mostly factor out possible human error. Errors of automation bias tend to occur when decision-making is dependent on computers or other automated aids and the human is in an observatory role but able to make decisions. Examples of automation bias range from urgent matters like flying a plane on automatic pilot to such mundane matters as the use of spell-checking programs.
In psychology, the prevalence effect is the phenomenon that one is more likely to miss a target with a low prevalence than a target with a high prevalence or frequency. A real-world application of this phenomenon occurs in airport security screening; since a very small proportion of those going through security checkpoints carry weapons, security staff may fail to detect those attempting to carry weapons onto a plane.
Human performance modeling (HPM) is a method of quantifying human behavior, cognition, and processes. It is a tool used by human factors researchers and practitioners for both the analysis of human function and for the development of systems designed for optimal user experience and interaction. It is a complementary approach to other usability testing methods for evaluating the impact of interface features on operator performance.
Artificial intelligence for video surveillance utilizes computer software programs that analyze the audio and images from video surveillance cameras in order to recognize humans, vehicles, objects, attributes, and events. Security contractors program the software to define restricted areas within the camera's view and program for times of day for the property being protected by the camera surveillance. The artificial intelligence ("A.I.") sends an alert if it detects a trespasser breaking the "rule" set that no person is allowed in that area during that time of day.
Interoception is the collection of senses providing information to the organism about the internal state of the body. This can be both conscious and subconscious. It encompasses the brain's process of integrating signals relayed from the body into specific subregions—like the brainstem, thalamus, insula, somatosensory, and anterior cingulate cortex—allowing for a nuanced representation of the physiological state of the body. This is important for maintaining homeostatic conditions in the body and, potentially, facilitating self-awareness.
References
↑ Warm, J. S., Parasuraman, R., & Matthews, G. (2008). Vigilance requires hard mental work and is stressful. Human factors, 50(3), 433-441.
↑ Mackworth, N.H. (1948). The breakdown of vigilance during prolonged visual search, Quarterly Journal of Experimental Psychology, 1, 6-21.
↑ Parasuraman, R. (1986). Vigilance, Monitoring and Search In J.R. Boff, L. Kaufmann & J.P. Thomas (Eds.) Handbook of Human Perception and Performance, Vol.2, Cognitive Processes and Performance (pp 41–1 - 41-49). New York, Wiley.
↑ Teichner, W.H. (1974). The detection of a simple visual signal as a function of time on watch. Human Factors 16, 339-353.
↑ Helton et al. (2007). The abbreviated vigilance task and cerebral hemodynamics. Journal of Clinical and Experimental Neuropsychology, 29, 549-552.
↑ Mackie, R.R. (1984). Research relevance and the information glut. Human Factors Review, (pp 1–11), Santa Monica, CA: Human Factors Society.
↑ Frankmann, J.P. & Adams, J.A. (1962). Theories of Vigilance. Psychological Bulletin, 59, 257-272.
↑ Parasuraman, R. & Davies, D.R. (1977). A taxonomic analysis of vigilance. In R.R. Mackie, (ed.) Vigilance: Theory, operational performance and physiological correlates, (pp 559–574) New York: Plenum.
↑ Green, D.M. & Swets, J.A. (1966) Signal Detection Theory and Psychophysics. New York: Wiley
↑ Broadbent, D.E. (1971) Decision and Stress. New York: Academic Press.
↑ Williams, P.S. (1986). Processing demands, training and the vigilance decrement. Human Factors, 28. 567-579.
↑ Mackworth, Jane F. (1963) The Effect of Intermittent Signal Probability on Vigilance. Canadian Journal of Psychology, 17(1). 82-89
↑ Parasuraman, R. & Davies, D. (1977) A taxonomic analysis of vigilance performance. In R. Mackie (ed.) Vigilance: Theory, operational performance and physiological correlates. Plenum Press.
↑ Parasuraman, R. & Caggiano, G. (2005). Neural and genetic assays of mental workload. In D. McBride and D. Schmorrow (Ed.) Quantifying Human Information Processing (pp 123–155). Lanham, Maryland: Rowman and Littlefield.
↑ Moruzzi, G. and Magoun, H.W. (1949) Brain stem reticular formation and activation of the EEG. EEG Clinical Neurophysiology I: 455-473
↑ Parasuraman, R., Warm, J. & See, J. (1998) Brain Systems of Vigilance in The Attentive Brain R. Parasuraman (Ed.) pp. 221–256. Cambridge MA: MIT Press
↑ Moore, H., Sarter, M. & Bruno, J.P. (1993) Bidirectional modulation of stimulated cortical acetylcholine release by benzodiazepine receptor ligands. Brain Res. 596: 17-29
↑ Shaw, T.H., Warm, J.S., Finomore, V., Tripp, L., Matthews, G., Weiler, E. & Parasuraman, R. (2009) Effects of sensory modality on cerebral blood flow velocity during vigilance, Neuroscience Letters 461, 207-211
↑ Steriade, M. (1996) Awakening the brain. Nature 383: 24 - 25
↑ Lundberg, U. & Frankenhaeuser, M. (1979) Pituitary-adrenal and sympathetic adrenal correlates of distress and effort (Report 548). Stockholm, Sweden: University of Stockholm, Department of Psychology
↑ Davies, D.R. & Tune, G.S. (1969) Human Vigilance Performance. New York: American Elsevier
↑ Baker, C.H. (1963) Consistency of performance in two human vigilance tasks. Vigilance: A Symposium. New York: McGraw-Hill Performance
↑ Parasuraman, R. (1976) Consistency of Individual Differences of Human Vigilance Performance: An Abilities Classification Analysis. Journal of Applied Psychology Vol. 61 No. 4 486-492
↑ Levine, J.M., Romashko, T., & Fleishman, E.A. (1973) Evaluation of an abilities classification system for integrating and generalizing human performance research findings: An application to vigilance tasks. Journal of Applied Psychology 58, 149-157.
↑ Mackworth, Jane F. (1964) Performance Decrement in Vigilance, Threshold, and High-Speed Perceptual Motor Tasks. Canadian Journal of Psychology, 18(3). 209-223
↑ Solandt, D.Y. & Partridge, D.M. (1946) Research on auditory problems presented by naval operations. Journal of the Canadian Medical Service3. 323-329
↑ Mackworth, N.H. (1950) Researches on the measurement of human performance. Med .Res .Council, Special Report., No. 268
↑ Mackworth, J.F. (1965) The effect of amphetamine on the detectability of signals in a vigilance task. Canadian Journal of Psychology 19 (2). 104-117
↑ Wiliges, R.C. (1976) The vigilance increment: An ideal observer hypothesis. In T.B. Sheridan and G. Johannsen (Eds.) Monitoring Behavior and Supervisory Control. New York: Plenum
↑ Mackworth, J.F. (1963) Effect of Reference Marks on the Detection of Signals on a Clock Face. Journal of Applied Psychology, 47(3). 196-201.
↑ Kerkhoff, G.A., van der Schaaf, T.W. & Korving, H.J. (1980) Auditory Signal Detection: Effects of long-term practice and time on task. Perception and Psychophysics 28, 79-81
↑ Moray N., Fitter, M. Ostry, D., Favreau D., & Nagy, V. (1976) Attention to pure tones. Quarterly Journal of Experimental Psychology 28, 271-283
↑ Uenking, M. (2000) Pilot Biofeedback Training in the Cognitive Awareness Training Study. American Institute of Aeronautics and Astronomics, Proceedings 2000-4074, 1-8
↑ Fisk, A.D. & Schneider, W. (1981) Control and automatic processing during tasks requiring sustained attention: A new approach to vigilance. Human Factors 23, 737-750.
↑ Parasuraman, R. & Giambra, L. (1991) Skill Development in Vigilance: Effects of Event Rate and Age. Psychology and Aging, 6(2), 155-169.
↑ Deaton, J. & Parasuraman, R. (1993) Sensory and Cognitive Vigilance: Effect of Age on Performance and Subjective Workload. Human Performance, 6(1), 71-97.
↑ Berardi, A., Parasuraman, R. & Haxby, J. (2001) Overall vigilance and Sustained Attention Decrements in Healthy Aging. Experimental Aging Research 27, 19-39.
↑ Mackworth, J.F. (1969) Vigilance and Habituation. Baltimore MD: Penguin
↑ Parasuraman, R. (1985) Sustained attention: a multifactorial approach. IN Attention and performance XI. M. Posner and O Marin, (Eds.) 493-511. Hillsdale NJ: Lawrence Erlbaum
↑ Rohrbaugh, J.W., Stapleton, J.M., Parasuraman, R., & Zubovic, E.A. (1987) Dose-related effects of ethanol on sustained attention and Event Related Potentials. Alcohol 4:293-300
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