Second, these experiments raise the question: Given that rhesus monkeys (or other advanced primates) can learn relationally, what factors determine when they will learn relationally? Although we have no clear empirical answer at present, several possibilities (including visual imagery, memory requirements, and the control of attention) are suggested by the present data and their contrast with prior findings. Manipulations for distinguishing these possibilities will be discussed.
Finally, it is suggested that the probability of relational learning may vary systematically across primate species. That is, the qualitative differences once posited between nonhuman primates and humans (or between monkeys and apes) may instead be instantiated as systematic quantitative differences in the probability of relational versus associative learning (with relational learning highly probable in humans, less so in apes, even less in monkeys with relatively complex brains, at or near zero in simple-brained primates). Similar variations in the probability of relational learning may reflect developmental trends in humans.
Clearly, empirical exploration of these issues will not only require continued experimental successes, but also will necessitate consideration of more “meaningful failures.” [Supported by NASA grant NAG2-438 and NIH grant HD-06016.]
Washburn, D. A., Greene, H. H., & Putney, R. T. (1997, November). Individual differences in attention and shoot/don’t-shoot skill. Poster presented to the Society for Judgment and Decision Making, Philadelphia, PA. Students were tested with a battery of 16 tasks to determine individual differences across basic dimensions of attention, and on a series of shoot/don’t-shoot scenarios in a firearms training simulator. The attention tasks reveal six basic factors of attention and executive function, along with factors that reflect non-attentional cognitive constructs. The sensitivity of threat detection (d’) in shoot/don’t-shoot judgment was reliably predicted by measures of attention-task accuracy and by the difference in effectiveness of peripheral cues versus central cues. Boredom proneness was also associated with the accuracy and sensitivity of shoot/don’t-shoot judgment. Detection bias was significantly predicted by variables that reflect individual differences in attention filtering (cuing and search) and sustaining (comparison and sorting). Each regression model accounted for over half of the respective signal detection variance. Generally however, shoot/don’t-shoot judgment was not associated with profiles of attention skills across latent factors–at least with respect to accuracy measures of decisions.
Washburn, D. A. & Putney, R. T. (1997, October). Individual differences in attention profiles. Poster presentation at The Future of Learning and Individual Differences Research: Processes, Traits, and Content. Minneapolis, MN. Attention research has burgeoned during the past 50 years resulting in a variety of meanings for this seemingly unitary term. The experimental literature and the factor analysis literature alike suggest that there are numerous component dimensions or factors of attention. We review 13 of the published factor analyses and report the factor structure of our battery of tasks (ASAP). Four factors of attention (FOCUS, SCAN, FILTER, SUSTAIN) and two executive factors (SORT, SEARCH) emerge from our data (N = 525 Air Force recruits tested on all 16 task), and are repeatedly observed in the prior studies of the factor structure of attention. Further, we find that individual differences in attention profiles across these ASAP dimensions reliably predict performance on a variety of criterion tasks (e.g., situation awareness in driving).
Washburn, D. A., Wu, Charles L, Ludwig, T., Brown, W. S., Richardson, J., & Rulon, M. J. (March, 1997). Under his microscope: Donald M. MacKay. Symposium presented at the meeting of the Southern Society for Philosophy and Psychology, Atlanta, GA. Donald MacCrimmon MacKay (1922-1987) was a world-renowned brain scientist and philosopher. Trained as a physicist, MacKay’s research interests ranged from visual psychophysics and neurophysiology to the functional cerebral asymmetries evident when the hemispheres are surgically separated. His attempts to develop an information-flow model of human behavior led to a view of the brain as a communication system. This view is evident in his founding of the Department of Communication in Neuroscience at the University of Keele–an institute in which physiology, psychology, computer science, and physics are brought together to elucidate the information-processing mechanisms of vision, hearing, and touch. MacKay’s productive legacy of research is revealed in the dozens of journal and chapter publications that span four decades of prestigious and influential volumes. His contributions to psychology and other disciplines also include the numerous scientists with whom he collaborated and mentored (including several of the presenters in this symposium). MacKay’s philosophical ideas reflect a natural complement to these research interests, and were articulated in numerous books as well as in MacKay’s 1971 televised debate with B. F. Skinner. His books include Information, Mechanism, and Meaning, Human Science and Human Dignity, Brains, Machines and Persons, Science and the Quest for Meaning, and Behind the Eye. One theme throughout Donald M. MacKay’s research and career was captured in his 1986 Gifford Lectures: “Examining humans under our own microscope.” Ten years after his death, this symposium has been organized to permit the psychologists and philosophers of the SSPP to meet Professor Mackay “under his own microscope.” The papers from this symposium are now in press in Philosophical Psychology.
Washburn, D. A. & Greene, H. H. (November, 1997). Attentional factors in shoot/don’t-shoot decision making. Poster presented at the annual meeting of the Society for Judgment and Decision Making, Chicago, IL. Variables like visual search set-size, target eccentricity, and distractor similarity are frequently examined in laboratory studies of attention and decision making. It is more difficult to study the effects of these psychological variables in shoot/don’t shoot scenarios which are typically filmed for training, not research, purposes. We filmed a series of simple “shoot” scenarios for use with a firearms training simulator. Overt responses and eye movements (monitored with a head-mounted eye tracker) to the live-action stimuli were analyzed as a function of set-size, expectation, and target eccentricity. Preliminary analyses suggest the utility of the research paradigm described here, although several problems were also identified.
Bibliography
RECENT PUBLICATION / PRESENTATION ABSTRACTS
UPDATED4/may/99
(Contact David Washburn for reprints and related publications)
Supported by grants from NASA, NICHD, ARI, ARO, ONR, USAF
Washburn, D. A., & Putney, R. T. (1999, June). Attention Profiles of Working Memory. Paper at the meeting of the American Psychological Society. Although each construct has its own literature, phenomena, and theories, it is widely recognized that attention and working memory are integrally related. Individual differences in serial probe recognition performance were profiled across basic dimensions of attention. Good working memory tended to be associated with good concentration, scanning, and attention-control skills.
Washburn, D. A., & Putney, R. T. (1999, April). Individual Differences in Time Estimation and Concentration. Paper at the meeting of the Southern Society for Philosophy and Psychology. There are numerous reasons to believe that the ability to estimate the passage of time may provide a useful and interesting cognitive measure. In the present study, we examined individual differences in time estimation and their relation to measures of attention, learning, memory, and executive function.
Air Force recruits (n = 141) were tested on a battery of 20 tasks designed to assess skills and weaknesses across dimensions of attention and executive function. This battery included tests of simple and choice response time, working memory with and without concurrent tracking, set-switching and task-switching, visual search, comparison, and cue utilization. Additionally, the battery contained computerized versions of several popular assessment tools such as the Stroop task, Trails-A and Trails-B, the Cancellation Test, and a continuous performance task. Finally, several standardized questionnaires were administered as part of the battery (the Boredom Proneness Scale, the Cognitive Failures Questionnaire, and the NASA Task Load Index). Each task was administered on a computer screen, and participants responded my moving and clicking a mouse.
On two occasions during administration of this battery of automated tasks, the recruits were asked to estimate the amount of time that had elapsed since the beginning of the test session. They were instructed not to refer to timekeeping devices, but rather to indicate (to the nearest minute) the amount of time that had passed. The first such probe came about 12 minutes into the session, after the participants had completed the Boredom Proneness Questionnaire, the simple and choice response-time tests, and the five-minute continuous performance task. The second time estimation probe occurred near the end of the test session (after approximately 100 minutes), and was preceded by every task except the Cancellation Test, the comparison task, the sorting task, selective tracking, and the Task Load Index. We hypothesized that errors in time estimation would be related to performance on other tasks, and specifically that individuals who underestimated the interval of elapsed time would show evidence of increased mental effort in performance on other cognitive tasks.
On average, participants slightly underestimated the passage of time on the first probe (mean deviation = -0.65 minutes, standard error = 0.489). However, variations in time estimation were generally uncorrelated with other measures. Individuals were assigned to groups based on quartile splits, representing the extreme under- and over-estimators. No reliable differences were found between these groups in performance on the other cognitive tasks.
For the second probe session, however, mean deviation was -15.36 minutes (standard error = 1.75). Individuals who were most extreme in underestimating the passage of time differed reliably (p