Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-2683; and Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
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ABSTRACT |
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Olson, Carl R. and Sonya N. Gettner. Macaque SEF neurons encode object-centered directions of eye movements regardless of the visual attributes of instructional cues. Neurons in the supplementary eye field (SEF) of the macaque monkey exhibit object-centered direction selectivity in the context of a task in which a spot flashed on the right or left end of a sample bar instructs a monkey to make an eye movement to the right or left end of a target bar. To determine whether SEF neurons are selective for the location of the cue, as defined relative to the sample bar, or, alternatively, for the location of the target, as defined relative to the target bar, we carried out recording while monkeys performed a new task. In this task, the color of a cue-spot instructed the monkey to which end of the target bar an eye movement should be made (blue for the left end and yellow for the right end). Object-centered direction selectivity persisted under this condition, indicating that neurons are selective for the location of the target relative to the target bar. However, object-centered signals developed at a longer latency (by ~200 ms) when the instruction was conveyed by color than when it was conveyed by the location of a spot on a sample bar.
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INTRODUCTION |
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Object-centered spatial awarenessawareness of
the locations of parts relative to an object
is central to many human
abilities, including the performance of construction, reading, and
drawing tasks, but has been little studied in nonhuman primates. To
carry out studies of object-centered spatial awareness in monkeys, we recently devised a task requiring them to make judgements of locations as defined relative to a reference object (Olson and Gettner
1995
). In this task, an object-centered cue (a spot flashed on
the right or the left end of a horizontal sample bar) instructed the
monkey to make an object-centered behavioral response (an eye movement to the corresponding end of a horizontal target bar). Recording from
the supplementary eye field (SEF) (Schall 1991
;
Schlag and Schlag-Rey 1987
) of trained monkeys, we found
that neurons fired differentially, during the interval between the cue
and the response, some exhibiting a preference for bar-right and some
for bar-left trials (Olson and Gettner 1995
). This
finding is subject to at least two interpretations. Neurons firing most
strongly on bar-right trials might be selective for the presentation of
the cue on the right end of the sample bar (thus exhibiting
object-centered visual responses or carrying object-centered visual
memory signals). Alternatively, they might be selective for the
programming of eye movements to the right ends of reference objects
(thus carrying object-centered oculomotor signals).
To choose between visual and motor interpretations, we have
characterized the activity of SEF neurons in a task in which the cues
are either configurational (presentation of a spot on the left or right
end of the sample bar) or chromatic (blue and yellow conveying bar-left
and bar-right instructions, respectively). Using this paradigm, we have
enlarged on preliminary findings from a single monkey (Olson and
Gettner 1995) to demonstrate for a substantial population of
neurons in two monkeys that object-centered direction selectivity is
manifested in the SEF under both configurational and chromatic cue
conditions. We have shown that individual SEF neurons, in addition to
exhibiting object-centered direction selectivity under both cue
conditions, show it to an equal degree, evincing little or no
modulation in the strength of the directional signal dependent on the
type of cue. Further we have discovered one clear difference in SEF
neuronal activity across cue conditions. Whereas object-centered
directional signals appear at ~200 ms after configurational cues,
they develop markedly later, at ~400 ms, after color cues. We
interpret this effect as reflecting a difference in the amount of time
required by visual areas outside the SEF to process the cues, form a
decision, and activate SEF neurons encoding the object-centered motor
program. Either extra-SEF visual processing and decision making are
faster for configurational cues or the areas responsible for
interpreting configurational cues are linked to the SEF by faster
communication lines.
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METHODS |
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Subjects
Two adult male rhesus monkeys were used (Macaca mulatta; laboratory designations Qu and Pk). Experimental procedures were approved by the Carnegie Mellon University Animal Care and Use Committee and were in compliance with the guidelines set forth in the United States Public Health Service Guide for the Care and Use of Laboratory Animals.
Preparatory surgery
At the outset of the training period, each monkey underwent
sterile surgery under general anesthesia maintained with isofluorane inhalation. The top of the skull was exposed, bone screws were inserted
around the perimeter of the exposed area, a continuous cap of rapidly
hardening acrylic was laid down so as to cover the skull and embed the
heads of the screws, a head-restraint bar was embedded in the cap, and
scleral search coils were implanted on the eyes with the leads directed
subcutaneously to plugs on the acrylic cap (Remmel 1984;
Robinson 1963
). After initial training, a 2-cm-diam disk
of acrylic and skull, centered on the midline of the brain at anterior
21 mm (Horsley-Clarke coordinates), was removed, and a cylindrical
recording chamber was cemented into the hole with its base just above
the exposed dural membrane.
Single-neuron recording
At the beginning of each day's session, a varnish-coated
tungsten microelectrode with an initial impedance of several megohms at
1 kHz (Frederick Haer and Company, Bowdoinham, ME) was advanced vertically through the dura into the immediately underlying cortex. The
electrode could be placed reproducibly at points forming a square grid
with 1-mm spacing (Crist et al. 1988). The action potentials of a single neuron were isolated from the multineuronal trace by means of an on-line spike-sorting system using a template matching algorithm (Signal Processing Systems, Prospect, Australia). The spike-sorting system, on detection of an action potential, generated a pulse that was stored with 1-ms resolution.
Behavioral apparatus
All aspects of the behavioral experiment, including presentation of stimuli, monitoring of eye movements, monitoring of neuronal activity, and delivery of reward, were under the control of a 486- or Pentium-based computer running Cortex software provided by R. Desimone, Laboratory of Neuropsychology, National Institute of Mental Health. Eye position was monitored by means of a scleral search coil system (Remmel Labs, Ashland, MA, or Riverbend Instruments, Birmingham, AL) and the x and y coordinates of eye position were stored with 4-ms resolution. Stimuli generated by an active matrix LCD projector (Sharp, XG H4OU) were rear-projected on a frontoparallel screen 18 cm from the monkey's eyes. Reward in the form of ~0.1 ml of water or juice was delivered through a spigot under control of a solenoid valve on successful completion of each trial.
Statistical analysis
Details of statistical analysis are provided in the text. The general approach was to analyze results obtained with a given behavioral paradigm by applying a set of identical procedures to data collected from each neuron. In each procedure, the trial epoch under consideration was defined either as the period between two identifiable events (for instance, onset of the cue and onset of the signal to move) or as a period of fixed length beginning or ending at a fixed time relative to a single identifiable event. The mean firing rate during the epoch was computed for each trial completed successfully during recording from the neuron. Then an ANOVA was carried out to determine whether firing rate varied significantly across the trials as a function of the conditions by which trials differed from each other.
Localization of recording sites
On the last day of the experiment, marking pins were lowered into the brain through selected grid holes. With the pins in place, the monkey was anesthetized with an overdose of pentobarbital sodium and perfused through the heart with 10% formalin. The pins then were removed from the brain, and the brain was removed from the skull. The surface of the brain was photographed to show the visible holes left by the marking pins and gross morphological landmarks including the hemispheric midline and the arcuate and principal sulci. By interpolation based on the grid coordinates at which the electrode had been placed, recording sites then were projected onto the image of the cortical surface. The resulting map formed the basis for subsequent measurements of the locations of recording sites.
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RESULTS |
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Training
Two monkeys were trained to perform a task in which a cue presented early in each trial instructed them whether to make an eye movement to the right or left end of a horizontal target bar appearing at an unpredictable location at the end of the trial. The cue could be either configurational (a spot flashed on the right or left end of a sample bar) or chromatic (a blue spot instructing a bar-left response or a yellow spot instructing a bar-right response). At the beginning of each configuration-cue trial, while the monkey was fixating a central spot, a sample was presented in the form of a solid horizontal bar (Fig. 1A2). Then one end of the sample was cued (Fig. 1A3). After a delay, a horizontal target-bar appeared at an unpredictable location (Fig. 1A5). After a second delay, extinction of the central fixation spot (Fig. 1A6) signaled the monkey to make an eye movement (Fig. 1A7). Reward was delivered only if the monkey made a saccade directly to the end of the target corresponding to the cued end of the sample. Because the location of the target-bar varied unpredictably across trials (Fig. 1B, f-h), it was impossible for the monkey to perform the task by simply programming an eye movement. Instead during the delay period before target onset, he had to remember an object-centered spatial instruction (select the right or left end of the target bar regardless of its absolute location). Color-cue trials differed from configuration-cue trials in that a small precue marker replaced the sample-bar (Fig. 1A2') and in that the cue appearing subsequently at the marked location was colored blue or yellow (Fig. 1A3').
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Conditions varied from trial to trial in such a way that bar-centered direction was counterbalanced against other factors that might influence SEF neurons. In trials with configurational cues, the same cue (Fig. 1B, d) could signal either a bar-right trial (if superimposed on the right end of sample bar a) or a bar-left trial (if superimposed on the left end of sample bar b). Thus the retinal location of the cue was dissociated from the object-centered direction of the eye movement. Likewise, the orbital direction of the eye movement was dissociated from the eye movement's object-centered direction. For example, on some bar-left trials, the monkey executed eye movement 2 (up and to the left) to the left end of target g, whereas, on other bar-left trials, he executed the same eye movement to the right end of target f (Fig. 1B). Systematic variation of these factors across trials gave rise to 18 conditions (Fig. 1C).
During the early phase of data collection, trials were blocked according to cue type (20 neurons from monkey Pk and 3 neurons from monkey Qu were characterized in the context of blocked trials). Later configuration- and color-cue trials were intermingled in a single block (3 neurons from monkey Pk and 21 neurons from monkey Qu were characterized in the context of interleaved trials). Conditions within each block were imposed in pseudorandom sequence according to the principle that one trial conforming to each condition should be completed successfully before the beginning of the next round of trials. During collection of neuronal data, this procedure continued until 10-20 successful trials (routinely 16) had been completed under each condition.
Performance
Both monkeys mastered the task and performed at a consistently high level. Both experienced moderately more difficulty on color-cue than on configuration-cue trials. Monkey Pk scored 92.2% on configuration-cue trials as compared with 81.6% on color-cue trials (averages computed across all neuronal data collection sessions; consideration restricted to trials in which the monkey made an eye movement to one end or the other of the target). The difference between the percent-correct scores was significant (2-tailed paired t-test, P = 0.0001). Monkey Qu scored 97.9 and 93.9% on configuration- and color-cue trials, respectively; these values were significantly different (P = 0.0009).
The behavioral reaction time was not expected to vary across conditions because of the long delay period imposed between the cue and the go signal. Nevertheless we computed, for trials completed successfully by each monkey, the average interval between the signal to move (offset of the fixation spot) and initiation of the saccadic eye movement. In monkey Pk, there was a significant (2-tailed paired t-test, P = 0.0064) trend toward longer reaction times on color-cue trials (215 vs. 189 ms). In contrast, in monkey Qu, there was a significant (P = 0.0232) trend toward shorter reaction times on color-cue trials (160 vs. 168 ms). We can propose no simple explanation for these effects.
Recording sites
Recording was carried out in the superficial cortex of the
dorsomedial frontal lobe bilaterally in each of the monkeys. The sites
were within a restricted zone in which many neurons showed task-related
activity and exhibited direction selectivity in standard oculomotor
tests requiring eye movements to small spots. We carried out full tests
on 23 neurons in monkey Pk and 24 neurons in monkey Qu. The distribution of recording sites is shown in Fig.
2, where each dot represents one site,
and the size of the dot indicates how many neurons within that site
contributed data to the present paper. The lateromedial distribution of
these sites, as defined relative to the brain's midline, and the
anteroposterior distribution, as defined relative to the genu of the
arcuate sulcus, are consonant with previous reports on the location of
the SEF, as summarized by Tehovnik (1995). Although the
number of recorded neurons may seem small, it should be noted that the
aim of this experiment was to answer a specific, well-defined question
and that the results providing the answer to this question were
statistically significant in each monkey and were consistent between
monkeys.
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Object-centered direction selectivity
We use the term "object-centered direction selectivity" to describe the pattern of task-related activity exhibited by neurons that fire at different rates on trials requiring an eye movement to the left end of one bar versus the right end of another bar, the bars being positioned so that the retinal location of the target is the same in both conditions. Figure 3, A and B, illustrates a pair of such conditions next to histograms representing the firing rate of a neuron that was more active before eye movements to the bar's left end (Fig. 3A). We refer to this neuron as having a "preferred direction" (bar-left) and an "antipreferred direction" (bar-right) as defined with respect to an object-centered, not a retina-centered, reference frame. Because we tested only two object-centered locations (the bar's right and left ends), the possibility remains that eye movements to another object-centered location might have elicited even stronger activity.
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It was evident on casual observation that neurons exhibiting object-centered direction selectivity in trials involving one type of cue exhibited a consonant pattern of selectivity in trials involving the other type of cue. This finding is exemplified by data from the neuron that fired more strongly during bar-left than bar-right trials under both configuration- and color-cue conditions (Fig. 3).
To assess this effect quantitatively, we considered separately the first delay period (between cue onset and target-bar onset), the second delay period (between target-bar onset and fixation-light offset) and the response period (extending from initiation of the saccade to 100 ms after its completion). We took this approach because it is common for a neuron to express object-centered direction selectivity during some but not all phases of a trial.
In the analysis of data from each epoch, we considered only neurons for which object-centered direction selectivity during that epoch met a minimal statistical criterion. To select these neurons, we carried out independent analyses of variance on data from configuration- and color-cue trials with firing rate as the dependent variable, with object-centered direction as the single factor, and with consideration restricted to a subset of trials in which object-centered direction varied independently of the retinal location of the cue and the orbital direction of the eye movement (configuration-cue conditions 2, 4, 9, and 11 and color-cue conditions 14, 15, 16, and 17: Fig. 1C). Cases meeting a probability criterion of P < 0.05 during a given epoch were included in subsequent stages of analysis for that epoch. This cutoff, although arbitrary, was applied equally to color- and configuration-cue trials and so could not have biased the results.
Across all epochs subjected to analysis (47 neurons × 3 epochs), there were 44 epochs in which object-centered direction
selectivity met criterion under both cue-conditions, 21 epochs in which
it met criterion only under the configurational condition, 20 epochs in
which it met criterion only under the chromatic condition, and 56 epochs in which it met criterion under neither condition (Table
1). On the basis of these results, we can
reject the hypothesis that object-centered direction selectivity was
systematically more frequent under one cue condition than under the
other (2 test, P = 0.87). However, we
cannot conclude that the expression of object-centered direction
selectivity was dependent on the type of cue. Those cases in which a
neuron met criterion under one cue condition but not the other could
have arisen simply from random variability in the firing rate. This
issue will be resolved by means of an appropriate method of analysis in
the last paragraph in this section.
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The main aim of the procedure described above was to identify
neurons exhibiting object-centered direction selectivity under both cue
conditions during a given trial epoch. In each such case, we proceeded
to ask whether the directions preferred on color- and configuration-cue
trials were the same or different. We found without exception, in 24 cases from monkey Pk and 20 cases from monkey Qu,
that the preferred directions were in agreement. In monkey
Pk, 12 neurons (3 bar-left and 9 bar-right) exhibited matching preferred directions during one or more trial epochs. The tendency for
the preferred directions to match was significant (2
test, P = 0.007). In monkey Qu, 14 neurons
(12 bar-left and 2 bar-right) exhibited matching preferred directions
during one or more trial epochs. This result also was significant
(P = 0.03). The number of "instances" of matching
preferred direction (44) was greater than the number of "neurons"
in which preferred directions matched (26) because, in several neurons,
object-centered direction selectivity was present in more than one
trial epoch.
The fact that object-centered direction selectivity, in some
neurons during some trial epochs, met criterion under only a single cue
condition might be interpreted as reflecting either random variability
or a genuine influence of cue type on the directional signal. To
distinguish between these possibilities, we carried out an analysis
restricted to data from sessions in which chromatic and configurational
trials were interleaved rather than blocked (3 neurons in monkey
Pk and 21 neurons in monkey Qu). We adopted this
constraint to prevent interpreting any slow drift in neuronal properties between the two blocks of trials as due to the effect of cue
type. Analyses of variance were carried out on 72 data sets (24 neurons × 3 trial epochs) with cue type and object-centered direction as factors. These revealed only five apparent cases of
significant interaction between cue type and object-centered direction
selectivity, a number not significantly different from that expected by
chance given the probability criterion of P < 0.05 (2 test, P = 0.449). This essential
result remained the same when we adopted a more rigorous criterion for
significance (P < 0.01). We conclude that the type of
cue (configurational or chromatic) does not significantly affect the
strength or sign of the object-centered directional signal.
Timing of the object-centered directional signal
We observed an apparent tendency for neuronal activity reflecting the object-centered instruction to develop later after chromatic cues than after configurational cues (as seen in data from one neuron in Fig. 3). To quantify this tendency, we computed the average firing rate as a function of time relative to onset of the cue, for trials in the preferred object-centered direction and also for trials in the antipreferred object-centered direction, for all neurons exhibiting significant object-centered direction selectivity during the first delay period. Population activity on preferred- and antipreferred-direction trials diverged at ~200 ms after cue onset in configuration-cue trials (monkey Pk: Fig. 4A; monkey Qu: Fig. 4B). The divergence of firing rates appeared to occur later on trials when the cue was chromatic (monkey Pk: Fig. 4B; monkey Qu: Fig. 4D). To obtain an objective estimate of the delay in the onset of the color-cued as compared with the configuration-cued directional signal, we computed a difference curve for each cue condition (the mean population firing rate on preferred trials minus the mean population firing rate on antipreferred-direction trials as a function of time relative to onset of the cue). To facilitate comparison, we smoothed and normalized the difference curves. The results are shown in Fig. 5, A (monkey Pk) and C (monkey Qu). We then displaced the configurational difference curve in 10-ms steps along the time axis until we found the displacement that gave maximal overlap with the chromatic difference curve as judged by minimization of a sum-of-squared-differences measure. The displacements minimizing the differences between the configurational and chromatic curves were 240 ms in monkey Pk (Fig. 5B) and 190 ms in monkey Qu (Fig. 5D). We conclude that population activity reflecting the object-centered direction of the impending eye movement developed ~200 ms later after chromatic than after configurational cues.
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DISCUSSION |
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The essential conclusion of this study is that object-centered
direction selectivity, as observed in the macaque supplementary eye
field, is not a property only of visual responses or of memory traces
elicited by visual stimuli. Rather, robust object-centered direction
selectivity is present even when nonspatial cues elicit, by arbitrary
association, behavioral responses in particular object-centered directions. In this regard, object-centered direction selectivity is
like orbit-centered direction selectivity, which persists in the SEF
even when eye movements in different directions are elicited by foveal
cues arbitrarily associated with those directions (Chen and Wise
1995; Olson and Gettner 1996
). These findings
indicate that SEF neurons participate in a spatially selective process subsequent to the processing of visual stimuli. Whether that process is
best understood in terms of imagery (as in picturing one end of the
anticipated target bar), movement programming (as in preparing an eye
movement to one end of anticipated target bar), or attention (as in
preparing to attend to one end of the anticipated target bar) cannot be
resolved by the current results. However, the hypothesis of movement
programming is most compatible with the widespread idea that the SEF is
a premotor area for eye movements (Schall 1991
;
Schlag and Schlag-Rey 1987
). The fact that
object-centered signals elicited by chromatic cues appear in the SEF at
a latency considerably longer than the standard latency for visually
elicited saccades (~400 ms as compared with ~200 ms) might be taken
as casting doubt on the idea that the signals are related to saccadic programming. However, in a reaction-time paradigm (unlike the delay
paradigm used here), object-centered eye movements elicited by
chromatic cues almost certainly would occur at a latency much in excess
of 200 ms because of the complexity of the decision process.
The fact that SEF neurons encode the object-centered directions
of behavioral responses even when those responses are elicited by
chromatic cues does not in itself rule out the possibility that they
also give object-centered visual responses. It would be reasonable to
characterize them as giving object-centered visual responses if they
responded at standard visual latency to noninstructional stimuli
presented at preferred object-centered locations. In the current study,
all object-centered stimuli possessed instructional significance.
However, we still can ask whether the responses elicited by the
instructional stimuli occurred at standard visual latency. The answer
is that they did not. Object-centered signals, when elicited by an
instructional cue flashed on one end of a reference bar, appeared at a
latency of ~200 ms (Fig. 4, A and C). This is
much longer than the latency of ~100 ms at which the same neurons, in
control experiments not described in this paper, distinguished visual
stimuli at preferred and antipreferred retinal locations (see also
Schall 1991). It is comparable, instead, with the
latency at which SEF neurons signal the direction of an impending response instructed by a foveal stimulus in a pattern-conditional eye
movement task (Olson and Gettner 1996
). This observation
rules out any simple mechanism, such as a shifter circuit
(Olshausen et al. 1993
), in which neurons register the
object-centered location of a stimulus as early as they do its
retina-centered location.
Although rejecting the notion that SEF neurons possess
object-centered visual receptive fields, we believe, nevertheless, that
the SEF neurons observed in this study were linked by especially strong
or direct functional pathways to visual neurons responsible for
detecting the object-relative locations of cues. Support for this view
arises from the fact that configurational cues elicited object-centered
activity much sooner (by ~200 ms) than chromatic cues (Fig. 5). There
are at least three possible causes for this effect. First, the SEF is
connected by relatively strong pathways to areas in the intraparietal
and superior temporal sulci that are thought to serve visuospatial
functions but is not directly connected to inferotemporal cortex and
other ventral stream areas in which color is processed (Bullier
et al. 1996; Huerta and Kaas 1990
). Thus the
neural substrate mediating the association of visual configurations
with movement directions may be stronger than the substrate mediating
the association of colors with movement directions. Second, because of
genetic factors or postnatal experience, anatomic connections between
visual cortex and the SEF may have been patterned in advance of any
training so as to favor the driving of SEF neurons with object-right
(or object-left) selectivity by visual neurons with matching
preferences. This would constitute an instance of stimulus-response
compatibility as characterized in human studies, which have shown that
visual stimuli located to the right (or left) of the current focus of
attention are particularly potent at eliciting responses from effectors
at rightward (or leftward) anatomic locations as reflected by a
reaction time measure (Nicoletti and Umiltá 1989
;
Stoffer 1991
; Umiltá and Nicoletti 1987
). Whether object-right (or object-left) visual stimuli are especially effective at driving movements to object-right (or object-left) target locations in humans is an interesting question that
has not yet been addressed experimentally. Third, longer and more
intense training on the use of configurational cues may have led to
greater automaticity in processing them. Both monkeys in our study were
trained first on tasks using configurational cues. Moreover throughout
the experimental period, both monkeys spent more time performing such
tasks. To decide among these possible mechanisms will require further study.
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ACKNOWLEDGMENTS |
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We thank D. Moorman and K. Rearick for excellent technical assistance.
C. R. Olson received support from the National Science Foundation Grant IBN 9312763 and National Institutes of Health Grants RO1 NS-27287 and RO1 EY-11831. S. N. Gettner received support from NIH Grant 1 F32 NS-09452 and the McDonnell-Pew Program in Cognitive Neuroscience. Technical support was provided by NIH Core Grant EY-08098.
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FOOTNOTES |
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Address for reprint requests: C. R. Olson, Center for the Neural Basis of Cognition, Mellon Institute, Room 115, 4400 Fifth Ave., Pittsburgh, PA 15213-2683.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 8 October 1998; accepted in final form 28 January 1999.
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REFERENCES |
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