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Dynamic Allocation of Attention in Aging and Alzheimer Disease
Uncoupling of the Eye and Mind
Mark Mapstone, PhD;
Alexander Rösler, MD;
Alissa Hays;
Darren R. Gitelman, MD;
Sandra Weintraub, PhD
Arch Neurol. 2001;58:1443-1447.
ABSTRACT
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Context Visual attention can be distributed focally, in the direction of gaze,
or globally, throughout the extrapersonal space. Aging, and especially Alzheimer
disease (AD), may influence global attention, resulting in shifts of gaze
to attend to the global workspace.
Objective To determine if subjects who have AD and cognitively intact older subjects
shift their gaze more often than young subjects while viewing a dynamic stimulus
that emphasizes global attention.
Design Experimental study of eye fixation patterns in response to a simulated
driving scene with stationary and moving distractors.
Setting Urban, medical school, National Institute on Aging–funded Alzheimer's
Disease Center.
Participants Thirteen subjects with mild probable AD, 13 age-comparable cognitively
intact older control subjects, and 11 young control subjects.
Main Outcome Measure Proportion of eye fixations within and outside of a central region of
interest encompassing the "road" surface.
Results Young controls made significantly more eye fixations (mean number of
eye fixations, 47.5) than either of the other 2 groups (older controls mean,
33.2; patients with AD mean, 32.2). However, 76% of their fixations remained
within the central region of interest. Older controls and subjects with AD
made proportionately fewer fixations within this region (48% and 49%, respectively)
than young controls and moved their eyes more often to the periphery but did
not differ from one another.
Conclusions Young controls maintain central eye position regardless of peripheral
distraction. Older controls move their eyes to the periphery, presumably to
widen the window of attention. Subjects with mild AD did not experience an
additional disadvantage beyond that associated with aging.
INTRODUCTION
THE LIMITED information processing capacity of the brain creates a situation
where only parts of the environment can become the focus of attention at any
given time. In the visual modality, global attention encompasses the entire
extrapersonal space and is used for the rapid detection of novel events. Such
events can then attract a more focused sort of attention for detailed assessment.
These shifts of visual attention can occur overtly, through shifts in gaze,
or covertly, without eye movements.
Shifts between global and local allocation of attention have been studied
experimentally in patients with Alzheimer disease (AD).1, 2
In these and other studies, the stimuli have been static or appear suddenly
in one of several cued or uncued locations. One common daily circumstance
in which there is a premium on rapid and dynamic covert shifts of attention
between local and global levels occurs while driving an automobile. In this
situation, it is necessary to maintain eye position within a relatively circumscribed
area, "on the road," while global attention and covert shifts of attention
move flexibly within the extrapersonal space to detect events related to traffic
and road conditions. Alterations of attention in part account for a higher
frequency of motor vehicle collisions in older drivers in situations where
there is great demand on attentional resources, such as at intersections and
traffic circles.3, 4 Aging and,
to a greater extent, AD may influence the ability to inhibit shifts of gaze5, 6 causing gaze to be diverted to extraneous
locations and objects.
The goal of this study was to characterize visual attention strategies
in subjects with mild probable AD in response to a dynamic scene that places
a premium on sustained global allocation of attention. We used virtual reality
methods to create a dynamic scene of the view from the driver's perspective
in a moving automobile. We selected this task because it represents a highly
familiar situation that perhaps has more ecological face validity than other
paradigms that have been used to study visuospatial attention in elderly patients
with AD. Eye movements were recorded while subjects viewed this dynamic visual
scene and eye fixation patterns were analyzed to determine where subjects
focused their gaze and whether shifts in gaze were more common in patients
with AD and cognitively intact older control subjects (ONCs) without dementia.
This study was not conducted to evaluate driving ability per se, but the results
may have implications for assessing driving safety in older individuals.
SUBJECTS AND METHODS
SUBJECTS
The subjects consisted of 13 patients with mild probable AD, 13 age-
and education-matched cognitively intact ONCs, and 11 young control subjects
(YNCs). The patients and ONCs were recruited from the Clinical Core subject
registry of the Northwestern Alzheimer's Disease Center, Chicago, Ill. They
had all undergone neurologic and neuropsychological examinations to verify
the absence of neurologic disease, cognitive deficits, and alterations in
daily living activities in the ONC group and to establish the diagnosis of
"probable AD" in the patient group.7 The absence
of dementia and preservation of daily living activities in the ONC group was
also verified in an interview with a designated informant, as part of the
Northwestern Alzheimer's Disease Center registry procedures for enrolling
subjects. Young controls were recruited from advertisements placed around
the university and were screened using a telephone interview for exclusion
criteria prior to participation. Exclusion criteria for the present study
were (1) use of psychoactive medications, (2) unusual corrective lenses that
might interfere with the collection of eye movement data, (3) corrected visual
acuity worse than 20/40 in either eye, and (4) visual field deficits on neurologic
examination.
The following neuropsychological tests had been administered to the
patients with AD and ONCs as part of the Northwestern Alzheimer's Disease
Center Clinical Core methods for establishing a diagnosis: Mini-Mental State
Examination, Digit Span, Logical Memory and Visual Reproduction subtests from
the Wechsler Memory Scale–Revised, the Boston Naming Test, Verbal Fluency
(animal list generation), and the word list and constructions subtests from
the battery of the Consortium to Establish a Registry for Alzheimer's Disease,
and Judgment of Line Orientation.8, 9, 10, 11, 12
The YNCs were graduate students and did not undergo additional testing. The
study was approved by the institutional review board of Northwestern University,
Chicago, Ill. All subjects gave informed consent.
PROCEDURE
An infrared-based eye tracking system (model RK-426PC; ISCAN, Burlington,
Mass) recorded eye position, sampling at a rate of 60 Hz, while subjects looked
at an animation simulating the view from the perspective of the driver in
a moving automobile. The animation was displayed on a 21-in monitor subtending
a visual angle of 23°. Eye position was recorded in 2-dimensional space
and saved to a personal computer (Macintosh; Apple Computers, Cupertino, Calif)
for analysis using custom-designed software (ILAB, Chicago, Ill)13
running in the MATLAB environment (Mathworks, Natick, Mass). A standardized
calibration procedure preceded the experimental task to ensure accuracy of
eye position within the display.
Movement of a car down a 2-way street was simulated by displaying 300
still frames of digitized images at the rate of 15 frames per second, approximating
a speed of 30 mph. Subjects viewed three 20-second simulations that differed
with respect to the density of stationary distractors flanking the street
(eg, buildings, pedestrians, trees, etc). In addition, moving vehicles approached
from the periphery at each of 2 intersections, but the traffic lights in the
direction of simulated travel remained green so that automatic motoricity
responses related to slowing or braking would not be provoked. Although the
simulations were not representative of real driving conditions, they could
be compared with light traffic situations that might be encountered in rural
or suburban areas during daytime hours.
Based on reports by Cole and Hughes,14
a region of interest (ROI) for a primary location of attentional focus for
safe driving was operationally defined as the area occupied by the street
in the direction of the heading on the display monitor (Figure 1). In the experimental task this ROI occupied the same relative
visual position on the screen throughout the 20-second duration of each simulation.
Subjects were instructed to view the simulations as if they were safely driving
to emphasize reliance on a more global attentional strategy.
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Eye fixation patterns superimposed on the experimental scene. A,
Eye fixation locations (circles) and scan paths (lines) from a young control
subject averaged over the three 20-second experimental trials and displayed
on 1 frame from the simulation. The relative position of the road remained
fixed throughout the trials. Circle size is proportional to fixation duration.
Most fixations remain within a constricted region on the road in front of
the subject. B, Similar data from an older control subject. Fixations frequently
leave the region of interest of the road surface. C, Eye fixations from a
subject with Alzheimer disease, shows a pattern similar to that of the older
control subject. The scan path tracings that fall beyond the main scene in
parts B and C indicate that some eye fixations went to areas in the black
frame surrounding the simulation on the computer screen.
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DATA ANALYSIS
Eye fixations are accepted as a valid measure of attentional allocation15, 16, 17, 18, 19
and constituted the dependent variable in this study. A fixation was defined
as eye position remaining within a 6-pixel horizontal by 4-pixel vertical
area on the display for at least 100 milliseconds.20, 21
The mean total number of fixations and mean fixation duration within the ROI
were calculated for each of the three 20-second animations and a grand mean
was derived for each measure for each subject. Three separate 1-way analyses
of variance (ANOVAs) with planned contrasts of group means (YNCs vs ONCs,
ONCs vs subjects with AD) were used to compare the groups for the average
total number of fixations, average duration of fixations, and average percentage
of fixations that fell within the defined ROI while viewing the animations.
RESULTS
SUBJECT DEMOGRAPHICS AND NEUROPSYCHOLOGICAL TEST SCORES
Table 1 lists demographic
information, Mini-Mental State Examination scores, and scores from the delayed
recall condition of the Logical Memory subtest from the Wechsler Memory Scale–Revised
for the 2 older subject groups. Subjects with AD and ONCs did not differ significantly
from one another for age. Mean years of education differed among the 3 groups
(F2,34 = 6.5, P = .004), but post hoc
comparisons showed that the only statistically significant difference was
between the YNCs and the subjects with AD (P = .005).
Scores on the Mini-Mental State Examination were normal for ONCs (mean [SD],
28.2 [1.5]) and in the mildly impaired range for subjects with AD (24.3 [3.1], P = .003). Subjects with AD also had abnormal scores on
the delayed recall condition of the Logical Memory subtest from the Wechsler
Memory Scale–Revised, consistent with their prominent amnestic disorder.
All ONCs scored within the normal range on the neuropsychological battery
and were performing normally in all activities of daily living, as corroborated
by their designated informants.
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Table 1. Subject Characteristics*
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Although this study was not aimed at predicting actual driving skill,
subjects were asked about their driving experience because this could potentially
influence performance. All subjects had driving experience, and 10 of the
13 subjects with AD were continuing to drive at the time of the study. Three
subjects with AD had not driven for the previous 2 to 3 years, 1 because of
physical limitations, and 2 who were relying on others for transportation
over the same interval. All ONCs and YNCs were current drivers, but many stated
that they often relied on public transportation.
EXPERIMENTAL TASK
Group mean scores for each dependent variable are given in Table 2. The omnibus ANOVAs for average
total number of fixations and average percentage of fixations within the ROI
were statistically significant (F2,34 = 5.01, P = .01; and F2,34 = 3.85, P =
.03, respectively). Although mean fixation duration was briefer in the YNCs
than in the other 2 groups, the difference was not statistically significant.
This is perhaps because of the large variability in this measure in the 2
older groups.
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Table 2. Results of Analysis of Fixation Variables*
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The planned comparisons revealed that the YNCs made significantly more
eye fixations overall while viewing the simulations than the ONCs (P = .01). In addition, significantly more of the eye fixations of the
YNCs fell within the ROI when compared with those of the ONCs (P = .02). That is, a greater proportion of eye fixations of ONCs fell
outside the ROI, directed at the periphery of the scene. There was no statistically
significant difference between the ONCs and the subjects with AD on any of
the 3 dependent measures.
COMMENT
Patients with mild probable AD and cognitively intact ONCs make frequent
eye movements to the periphery of a dynamic scene that simulates the driver's
view in a moving automobile. Younger controls, in contrast, make more frequent
eye movements but the excursions are small and the eyes remain within a circumscribed
area analogous to the surface of the road directly ahead of them.
The infrequency of eye movements made by YNCs outside the ROI, even
in the presence of peripheral distractors, leads us to suspect that they were
able to attend to the periphery without also shifting gaze, although we did
not specifically test their awareness of events in the periphery. In contrast,
subjects with mild AD and ONCs moved their eyes, presumably along with their
attention, to locations in the periphery, suggesting diminished capacity for
the flexible interplay between covert and overt shifts of attention. This
interpretation may be challenged by many reports of the absence of a significant
impairment of covert shifts of attention in cognitively intact ONCs.22, 23 However, these studies used static
stimulus displays with targets that occurred in predictable locations. The
dynamic scene used in our study places rapidly changing demands on the attentional
system and may, therefore, reduce the efficiency of covert shifts of attention
in nondemented older subjects.
One measure of the visuospatial allocation of attention that has been
applied to driving is the useful field of view (UFOV).24, 25
The UFOV is defined as the area of the visual field in which information can
be most readily processed without eye or head movements. It is tested by having
subjects maintain central fixation and monitor central events while responding
to targets that suddenly appear in a stationary display at various eccentricities
from fixation. This window of visual attention reflects 3 different factors—visual
processing speed, the ability to divide attention, and freedom from distractibility.
Although deficits in each of these domains can occur with aging, these components
can operate independently of each other and additively to alter the UFOV.25 Several studies have shown that the percentage of
reduction in the UFOV, combined with overall mental status scores, has a high
predictive value for motor vehicle collisions in elderly persons.4, 26, 27, 28 Recently,
patients with AD were found to be impaired relative to age-matched controls
on all components of the UFOV.29
One consequence of a reduction in the UFOV during an activity such as
driving or other similar attention-demanding activities might be an increase
in the number of overt changes in eye position needed to attend to peripheral
events.30 Although YNCs made more fixations
than the 2 older subject groups while viewing the dynamic experimental scene,
these fixations remained within a limited area. Thus, small deviations in
eye position within the ROI could have been sufficient for the YNCs to covertly
monitor the full extent of the scene in the periphery. In contrast, although
the ONCs and the subjects with AD made fewer fixations, more fixations left
the ROI in a way that may have diverted focal attention away from the direction
in which the road was heading. These results are, in part, consistent with
the UFOV model and demonstrate the effects of aging on visual attention to
a dynamic stimulus.
There are several limitations of our study. The sample size is small
because of a need to use subjects with mild dementia and also to fulfill inclusion-exclusion
criteria for recording accurate eye data. Thus, the results may not generalize
to a larger sample. In addition, the driving scene was used as a metaphor
for a condition in which both global and local modes of attention were required
in quick succession. Therefore, this was not a study of driving—actual
driving skill was not measured—and so findings cannot be directly translated
to predictions for driving safety. We also did not inquire about differential
experiences in driver training. Older subjects may have learned to drive before
standardized driver education courses were instituted and the instruction
to drive safely during this task may have evoked different strategies in each
subject group based on prior training. Finally, the experimental task excluded
many features of driving that further increase the attentional load in the
naturalistic setting, including street sounds, the sound of a car radio or
a cellular phone, the presence of a passenger, information in rearview and
side view mirrors, and unexpected events. Despite these limitations, however,
the similarity in visual attention strategies between nondemented ONCs and
older subjects with mild dementia in our study may provide information that
helps to explain why some patients with AD may retain the ability to drive
safely, at least in the early stages.31, 32, 33, 34
The age-related changes in visual attention demonstrated in this study
may have several roots. First, this may reflect an alteration of the neurologic
mechanisms of attention in aging. Second, it may represent increased caution
in older subjects, who may need to compensate for generally reduced reaction
time by more extensive scanning with the eyes. Furthermore, while attention
strategies may differ in younger and older individuals, the changes may not
necessarily be adverse for activities such as driving. One way to explore
the relationship between these findings and driving safety would be to compare
fixation patterns in individuals with good and poor driving records. The findings
of our study may have some implications for how elderly individuals can correct
for reduced flexibility in shifting among different forms of attentional allocation.
For example, training older individuals to detect targets in the periphery,
while maintaining central fixation, could possibly improve global attention.
This study emphasizes the need to distinguish age-associated from dementia-related
changes in visuospatial attention. The debate over driving and the elderly
population has evolved into a highly charged issue in this country, in part
because our society places such a premium on personal independence and the
freedom conferred by having an automobile. It is clear that a visual acuity
test is insufficient to assure safe driving and that cognitive deficits impair
the strategic deployment of attention that is necessary for successful driving.14 The many components of visuospatial attention, each
of which may show differential vulnerability to aging and to different stages
of AD, may provide a sensitive probe for deficits that could impair driving
safety.
AUTHOR INFORMATION
Accepted for publication May 4, 2001.
This work was supported in part by grants RO1-AG14068 (Dr Weintraub)
and AG13854 from the National Institute on Aging, Bethesda, Md, to the Northwestern
Alzheimer's Disease Center, and by a Buehler Summer Gerontology Fellowship
to the Northwestern University Medical School (Dr Mapstone).
We thank Marsel Mesulam, MD, for his helpful comments on the manuscript
and Kathy Schelble for technical assistance in recruiting and testing the
subjects.
From the Cognitive Neurology and Alzheimer's Disease Center (Drs Mapstone,
Rösler, Gitelman, and Weintraub, and Ms Hays), Division of Psychology,
Departments of Psychiatry and Behavioral Sciences (Drs Mapstone and Weintraub
and Ms Hays) and Neurology (Drs Gitelman and Weintraub), Northwestern University
Medical School, Chicago, Ill; and the Department of Neurology, Johann-Wolfgang
Goethe University, Frankfurt-Main, Germany (Dr Rösler). Dr Mapstone is
now with the Department of Neurology, University of Rochester Medical Center,
Rochester, NY.
Corresponding author: Sandra Weintraub, PhD, Cognitive Neurology
and Alzheimer's Disease Center, Northwestern University Medical School, 320
E Superior St, Searle 11-467, Chicago, IL 60611 (e-mail:
sweintraub{at}northwestern.edu).
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