Profiles Of Working Memory Essay, Research Paper
UPDATED4/may/99
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 * .01) from those to overestimated the passage of time on numerous measures. These differences are summarized in the table below.
Underestimators…
made faster Stroop decisions than
were less affected by Stroop incongruity than
switched attention faster in the Trails-B task than
reported more mental and physical effort than
were less characterized by boredom proneness than
reported more cognitive failures than
…Overestimators
In sum, it appears that individuals who were most extreme in underestimating the passage of time were characterized by increased concentration and effort compared to the people who were most extreme in overestimating the passage of time (despite the fact that this latter group was generally more accurate estimators). However, this effect was only observed when the estimation task was quite difficult and performance was quite poor, as relatively short-duration time estimation did not appear to be a good marker for differences in focused attention.
Washburn, D. A., Rulon, M. J., & Gulledge, J. P. (1999, March). Who Needs A Mouse? Joystick Manipulation by a Rat? Paper at the meeting of the Southeastern Psychological Association. A decade ago, it was reported that rhesus monkeys could learn to respond to computer-generated stimuli by manipulating a joystick, which in turn controlled the movements of a cursor on the computer screen. Since that time, the computerized test system has been used successfully in many experiments, at many laboratories, and with a variety of primate species, resulting in the rejection of some long-held beliefs about the competencies of rhesus monkeys. We were interested in determining whether rodents could simlarly master joystick-manipulation skills required to respond to computerized tasks. It seemed quite possible that rodents would lack the visual acuity, manual strength and dexterity, and cognitive capacity to bridge the stimulus-response spatial discontiguity and to learn the cause-effect relationships necessary to manipulate the a joystick skillfully.
One adult female albino rat was tested in a stainless steel rodent cage, which was modified as shown in Figure 1. Tasks originally developed for training rhesus monkeys to use a joystick were made available on this monitor, so that the rat had continuous access to the joystick and tasks within her home cage.
The rat was initially and automatically trained to manipulate the joystick so as to bring a computer-generated cursor into contact with a blue rectangle located on each border of the screen. As the animal became skilled at achieving contact between the cursor and a target border, the number of targets and their size was decreased, until finally the rat could bring the cursor into contact with a single blue square on the screen. The animal performed about 326 trials per day on this task.
Subsequently, the square moved on the screen whenever the cursor moved. Although she could not capture the moving target very quickly (mean = 14.96 s), the rat was able to manipulate the joystick so as to direct the cursor into contact with the moving target.
To verify that cursor movements were directed at the target (versus random joystick movements that eventually resulted in contact between the cursor and target), a second, nontarget stimulus was presented on the screen. The rat was rewarded for bringing the cursor into contact with the blue (dark) square, but not reinforced for touching the red (light) concentric circles. The rat was able to perform this task at levels significantly better than chance (p * .01), reaching an asymptote of about 71%.
Although this study is limited primarily to one animal, it represents the first report of success by a nonhuman animal species on a task that required control of a computer-generated cursor by manipulation of a joystick. Follow-up studies are underway. Given the wealth of information that has followed the discovery of joystick competencies for rhesus monkeys, we are excited about the prospects for present and future research with these animals and this paradigm.
Washburn, D. A., Putney, R. T., & Tirre, W. (1998, November). Attention Profiles for Speeded and Unspeeded Decision Making. Poster at the meeting of the Society for Judgment and Decision Making. Attention is a multi-dimensional construct, and individuals differ in these component skills or factors. We tested 176 Air Force recruits on a battery of attention tasks and on a flight simulator that required concurrent-task performance. Participants were grouped into the best and worst performers on the flight simulator according to primary-task measures (maintaining pitch, roll, yaw) and speeded secondary-task judgments (detecting oil temperature and pressure warnings). Attention profiles were computed and compared across groups. Attention focusing is important both to flight-orientation and oil-response performance. However, these latter, speeded- decision tasks also benefitted from attention scanning and filtering skills.
Washburn, D. A., Raby, P. R., & Greenidge, J. (1998, November). Playing to Learn: Using Web-Games to Improve Training. Paper at the meeting of the Society for Computers in Psychology. Students and trainees enjoy games but dislike reading long passages of textual information. Notwithstanding, the typical educational resource on the world-wide web consists of pages of text and graphics–essentially a digital library that can be read at a distance. We developed several simple JAVA-games and integrated them into a web-based instructional package to determine the effects on motivation and learning. Our findings suggest several benefits and limitations of this strategy for improving web-based training.
Washburn, D. A. (1998, November). Chronometric and Pupillometric Evidence of Planning. Paper at the meeting of the Psychonomic Society. Adults took longer to initiate a solution to two-dimensional mazes as maze complexity increased. Analysis of eye movements confirm that this interval was associated with planning. With very complex mazes, however, responding was delayed only long enough to plan the first few moves. Nonhuman primates produced a similar pattern, but with reliably less planning. Thus, planning reflects the capacity for executive function, controlled attention, and the capacity of working memory.
Washburn, D. A., & Putney, R. T. (1998, August). Attention Profiles for Boredom Proneness and Cognitive Failure. Poster at the meeting of the American Psychological Association, San Francisco, CA. Attention profiles (summaries of cognitive skills across dimensions or factors of attention) were constructed and compared with performance on two self-report measures: Boredom Proneness and Cognitive Failures. Reliable differences were observed in the attention profiles of individuals who are high versus low in boredom proneness, and of individuals who report frequent versus few cognitive failures. Boredom proneness and cognitive failure were also significantly correlated with one another. These data are discussed with respect to the factor structure of attention, the cognitive processes associated with boredom and cognitive failure, and the distinction between “can do” and “will do” measures of performance.
Washburn, D. A., Rumbaugh, D, M., Richardson, W. K., Gulledge, J. P., Shlyk, G. G., Vasilieva, O. N. (1998, June). PTS Performance by Flight- and Control-Group Macaques. Paper at the XI Conference on Space Biology and Aerospace Medicine, Moscow Russia. Behavior is an important overt manifestation of underlying biology, and alterations in physiological subsystems (e.g., musculoskeletal, regulatory) should be manifest in changes in task performance. Further, spaceflight mission success is primarily assessed using performance variables; that is, it is as important to know whether humans in space are capable of performing their tasks and duties without compromise as it is to understand the physiological aspects of space adaptation syndrome. Finally, overt behavior reveals psychological, as well as physical, well-being. Psychological well-being is an important consideration for ethical reasons as well as for predicting how an organism will respond to crisis situations.
In light of these justifications, we undertook to study the effects of spaceflight on the psychomotor task performance of rhesus monkeys (Macaca mulatta). For this study, a total of 26 young monkeys were trained to use the Psychomotor Test System (PTS), a package of software tasks (together with the computer hardware required to administer them) developed for spaceflight research with nonhuman primates. In the PTS, monkeys respond to computer-generated stimuli by manipulating a standard, analog joystick. Movements of the joystick produced movements of a cursor (a small “+”) on the computer screen in a direction isomorphic to the angle of joystick displacement. Bringing this cursor into contact with another computer-generated stimulus (e.g., a box on the screen) was recorded as a response. Correct responses were reinforced with food pellets.
A training procedure was developed at the Sonny Carter Life Sciences Laboratory at Georgia State University and initiated in Moscow at the Institute for Biomedical Problems. Monkeys were unrestrained in their home cages during training, so that each could reach through the bars of its cage to manipulate the joystick and to retrieve pellets. Performance criteria were used to titrate the difficulty of the training task for each monkey. All of the monkeys obtained the basic joystick-manipulation skills required to use PTS, and 22 of the animals reached the performance criterion established for the task used in this study. This task (CHASE) requires the monkey to move the cursor into contact with a small box that moves predictably across the screen.
Two flight monkeys and two control monkeys were selected from this pool and performed the CHASE task before the flight. One flight monkey died after recovery but before it was tested post-flight with PTS. The other flight monkey was sick after the day of surgery on R+1, but was able to produce PTS data on R+3, R+4, and R+5. The two control monkeys were tested before and after a 14-day control test involving comparable conditions (restraint, isolation, flight protocols) but without spaceflight. All three monkeys performed significantly fewer CHASE trials during the post-test than the pre-test. Response times were reliably increased and response optimality (det
Washburn, D. A., Smith, J. D., & Filion, C. M. (1998, April). What Can We Learn from ” Failures to Learn”? Paper presented at the meeting of the Southern Society for Philosophy and Psychology, New Orleans, LA. New data have challenged many long-held views of qualitative differences between humans and nonhuman primates. We have reported, for instance, that rhesus monkeys can learn relationally, can respond as predictor-operators, are influenced by the perception of choices and control, can extrapolate the motion of hidden targets, and can monitor their own levels of uncertainty–all achievements believed earlier to be the products only of human or, perhaps, great ape cognition. This litany of successes by monkeys and apes (together with the publication bias against negative findings or null effects) may suggest that monkeys can do virtually anything that humans can do–albeit frequently not as well. In the present report, we will discuss several “failures” by monkeys to learn new tasks. These results appear to be meaningful because of the number of reasonable attempts represented in each study, and because the monkeys in each case did learn to respond on the task by a complex set of stimulus-response associations.
For example, we attempted to train monkeys to reproduce lines and simple geometric shapes on a computer screen by “drawing” them using joystick movements. Four monkeys and two orangutans rapidly learned to “connect-the-dots” to draw a horizontal line. Once criterion was attained, a vertical probe was presented, followed by training on horizontal and vertical. When criterion was reached on both trial types, a diagonal probe was presented. This cycle of training and testing continued. In each case, the monkeys learned to reproduce the form on the screen but failed to generalize to any of the novel probes.
Comparable finding will be reviewed from several other paradigms (extrapolation, mental rotation, visuo-spatial memory, mirror-image matching-to-sample). In each case, the monkeys learned a strategy for profitable (but not optimal) responding, and in each case this strategy was revealed in probe testing to be associative rather than relational in nature. These failures contrast directly with other experiments in which the monkeys learned a rule-like strategy for responding. Thus, the data serve to emphasize three issues in learning.
First, these demonstrations highlight the contrast between meanings of “parsimony”–that is, between “Occam’s razor” and “Morgan’s canon.” It is difficult to predict which parsimonious solution to a new problem will characterize learning: (a) a complex matrix of many stimulus-response or stimulus-stimulus associations, each of them simple but together able to map out rather complex behavior; or (b) one (or few) complex, rule-like relations, each relatively higher in psychical domain than the associations of operant and classical conditioning.
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