(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. 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.
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 |
|
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.
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. 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. Washburn, D. A. (1998, November). Chronometric and Pupillometric Evidence of
Planning. Paper at the meeting of the Psychonomic Society. 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. 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.
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 (determined by the topography or path of
responding) were also significantly compromised during the post-test versus the pre-test for
all three animals. In each case, however, performance by the flight monkey was
significantly worse than the control monkeys. Thus, all three monkeys showed some
disruption in performance after the test (14-day flight conditions plus one anesthetized day
of biopsies and other tests), but the effect of spaceflight on the one flight monkey was large
and reliable. Unfortunately it is impossible from the present data to determine the degree
to which this effect on psychomotor performance reflects spaceflight directly versus the
illness that resulted from the interaction of spaceflight and R+1 research activities.
[Supported by NASA grant NAG2-438.]
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.
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. 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. 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. 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.
DAVID A. WASHBURN, PhD | |
| Sonny Carter Life Sciences Lab
Department of Psychology Georgia State University Atlanta, Georgia 30303 |
CERT
Morris Brown College 643 Martin Luther King Jr. Dr. Atlanta, Georgia 30314 |
Army Research Office (DAAL03-92-G-0382)
Army Research Office (DASW01-97-K-0002)
Army Research Institute
National Aeronautics and Space Administration (NAG2-438)
National Aeronautics and Space Administration (NAG2-1271)
National Institutes of Health (HD-06016)
Office of Naval Research (N00014-95-1-1100)
U.S. Air Force Research Office (F41624-95-C-5000)
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