Center for the Neural Basis of Cognition, Mellon Institute, Pittsburgh, Pennsylvania 15213-2683
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ABSTRACT |
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Olson, Carl R. and Léon Tremblay. Macaque Supplementary Eye Field Neurons Encode Object-Centered Locations Relative to Both Continuous and Discontinuous Objects. J. Neurophysiol. 83: 2392-2411, 2000. Many neurons in the supplementary eye field (SEF) of the macaque monkey fire at different rates before eye movements to the right or the left end of a horizontal bar regardless of the bar's location in the visual field. We refer to such neurons as carrying object-centered directional signals. The aim of the present study was to throw light on the nature of object-centered direction selectivity by determining whether it depends on the reference image's physical continuity. To address this issue, we recorded from 143 neurons in two monkeys. All of these neurons were located in a region coincident with the SEF as mapped out in previous electrical stimulation studies and many exhibited task-related activity in a standard saccade task. In each neuron, we compared neuronal activity across trials in which the monkey made eye movements to the right or left end of a reference image. On interleaved trials, the reference image might be either a horizontal bar or a pair of discrete dots in a horizontal array. The dominant effect revealed by this experiment was that neurons selectively active before eye movements to the right (or left) end of a bar were also selectively active before eye movements to the right (or left) dot in a horizontal array. An additional minor effect, present in around a quarter of the sample, took the form of a difference in firing rate between bar and dot trials, with the greater level of activity most commonly associated with dot trials. These phenomena could not be accounted for by minor intertrial differences in the physical directions of eye movements. In summary, SEF neurons carry object-centered signals and carry these signals regardless of whether the reference image is physically continuous or disjunct.
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INTRODUCTION |
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The supplementary eye field (SEF), an area located
on the dorsomedial shoulder of the frontal lobe in macaque monkeys, has been thought since its discovery 10 years ago to serve oculomotor functions (Schlag and Schlag-Rey 1985, 1987
). This view
has been supported by studies demonstrating that electrical stimulation of the SEF at reasonably low currents (<50 µA) evokes saccadic eye
movements (Chen and Wise 1995b
; Fujii et al.
1995
; Lee and Tehovnik 1995
; Mann et al.
1988
; Mitz and Goldschalk 1989
; Russo and
Bruce 1993
; Tehovnik and Lee 1993
;
Tehovnik and Sommer 1997
; Tehovnik et al.
1994
; Tian and Lynch 1995
) and that neurons in the SEF fire during the preparation and execution of saccades, exhibiting selectivity for particular saccade directions (Bon and Lucchetti 1992
; Chen and Wise 1995a
,b
, 1996
,
1997
; Hanes et al. 1995
; Mann et al.
1988
; Mushiake et al. 1996
; Russo and
Bruce 1996
; Schall 1991a
,b
; Schlag and
Schlag-Rey 1985
, 1987
; Schlag-Rey et al. 1997
).
However, the contributions of the SEF to oculomotor control probably
are not as straightforward as those of the other major frontal
oculomotor area, the frontal eye field (FEF). In the SEF, more
frequently than in the FEF, neuronal activity varies across the course
of learning as monkeys acquire arbitrary associations between visual
patterns and eye-movement directions (Chen and Wise
1995b
). Further, around half of SEF neurons, unlike neurons in
the FEF, fire differentially during combined movements of the arm and
eye as compared with eye movements alone (Mushiake et al.
1996
). Finally, higher levels of electrical current must be delivered to the SEF than to the FEF to elicit saccades (Russo and Bruce 1993
; Tehovnik and Sommer 1997
). These
observations suggest that the SEF is removed farther than the FEF from
processes occurring at the oculomotor periphery and that its functions, while encompassing oculomotor control, may not be restricted to it.
A potentially valuable approach to understanding the functions of the
SEF is to characterize the spatial reference frames with respect to
which it operates. This requires answering the question: insofar as
specific sites or neurons in the SEF represent particular eye-movement
directions, with respect to what reference frame are these directions
specified? Studies carried out to date have yielded evidence for three
forms of spatial sensitivity in the SEF: eye-centered, head-centered,
and object-centered. 1) Evidence that the SEF encodes
directions relative to an oculocentric reference frame arose
from studies based on both electrical-stimulation and single-neuron
recording. Electrical-stimulation studies demonstrated that fixed
vector saccades (saccades having a particular size and direction
regardless of the eyes' starting point in the orbit) could be elicited
from certain sites in the SEF (Bon and Lucchetti 1992;
Mitz and Godschalk 1989
; Russo and Bruce
1993
; Schlag and Schlag-Rey 1987
). Likewise,
some SEF neurons were shown to fire in conjunction with saccades in
preferred directions regardless of the eyes' starting point
(Mitz and Godschalk 1989
; Russo and Bruce
1996
; Schlag and Schlag-Rey 1987
). 2)
There are also signs that the SEF encodes directions relative to a
craniocentric frame. The fact that electrical stimulation at
some sites in the SEF seems to elicit goal-directed saccades, driving
the eyes to a certain angle in the orbit regardless of initial
direction, has been taken by some as evidence for craniocentric
encoding (Tehovnik 1995
; Tehovnik and Lee
1993
; Tehovnik et al. 1994
), although others have interpreted this phenomenon as arising from failure of SEF stimulation to engage cerebellar mechanisms that correct for variations in ocular mechanics across orbital position (Russo and Bruce
1993
). At the level of single-neuron recording, some SEF
neurons have been shown to possess craniocentric gaze fields, firing as
a function of the angle of the eyes in the head during motivated
fixation of external targets (Bon and Lucchetti 1990
,
1992
; Lee and Tehovnik 1995
; Schlag et
al. 1992
). 3) Finally, studies carried out in our
laboratory during the last several years have indicated that some SEF
neurons are sensitive to the allocentric directions of eye
movements
directions as defined with respect to objects in the
external world. In monkeys planning and executing eye movements to the
left or right end of a horizontal bar, around half of SEF neurons fire
differentially on bar-left and bar-right trials even when the location
of the bar on the screen is manipulated so as to keep the location of
the target on the screen the same (Olson and Gettner 1995
,
1999
). The object-centered spatial selectivity of these neurons
suggests that they are involved in eye-movement control at the level of
target specification rather than of motor programming.
The aim of the experiment described here was to extend our
understanding of object-centered direction selectivity in the SEF by
answering the question does this phenomenon depend on the nature of the
reference image and, in particular, on its physical continuity? In
previous studies, monkeys were required to make eye movements to the
left or right end of only a single image, a physically continuous
horizontal bar. Here we trained monkeys to perform a task in which, on
interleaved trials, they had to make eye movements to the right or left
end of a bar, as in the previous experiments, or, alternatively, to the
right or left element in an array consisting of two horizontally
separated dots. We recorded from SEF neurons during performance of this
task to determine whether firing was different under bar and dot
conditions. We found only subtle differences in neuronal activity
across the two conditions. This result suggests that SEF neurons carry
comparatively pure object-centered spatial signalssignals that
reflect the location of the target with respect to the selected
reference image but are not influenced to a major degree by the
reference image's intrinsic properties.
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METHODS |
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Subjects
Two adult male rhesus monkeys were used (Macaca mulatta; laboratory designations Ju and Po). 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
approximately at anterior 23 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 the time of which 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 10-ms resolution. Stimuli generated by an active matrix LCD projector (Sharp, XG H4OU) were rear-projected on a frontoparallel screen 25 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.
ANOVA and t-test analysis of data from individual neurons
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. The trial epoch under consideration was defined as the period between two identifiable events. The mean firing rate during the epoch was computed for each trial completed successfully during recording from the neuron. Then an ANOVA or t-test 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.
2 analysis of population data
A population of neurons might exhibit trait a or
b in one context and trait x or y in
another context. For example, among neurons significantly selective for
horizontal direction in two tasks, each neuron might prefer right
(a) or left (b) in the first task and right
(x) or left (y) in the second task. In such
cases, to test whether the distribution of neurons with respect to
a and b was correlated with the distribution with
respect to x and y, we employed the following
procedure. We took as observed values the four counts
Oax, Oay, Obx, and Oby, where Oax was
the number of neurons observed to express trait a in the
first context and trait x in the second context, and so on
for Oay, Obx, and Oby. We then computed the sum
of the counts, S = Oax + Oay + Obx + Oby, and the four frequencies,
Fa = (Oax + Oay)/S,
Fb = (Obx + Oby)/S, Fx = (Oax + Obx)/S, and
Fy = (Oay + Oby)/S.
Then on the assumption that the distribution of neurons with respect to
a and b was uncorrelated with the distribution
with respect to x and y, we computed the four
expected counts: Eax = Fa*Fx*S, Eay = Fa*Fy*S, Ebx = Fb*Fx*S, and Eby = Fb*Fy*S. Finally, we used a
2 test with 1 df to determine the level of
significance of the deviation of the observed values (Oax, Oay,
Obx, and Oby) from the expected values (Eax, Eay,
Ebx, and Eby).
Localization of recording sites
In each monkey, recording was carried out in a pair of regions, each a few mm in extent, disposed approximately symmetrically across the interhemispheric midline. One of the monkeys (Po) is still under study in behavioral experiments. In the other monkey (Ju) the brain was photographed after it was killed with an overdose of pentobarbital sodium and transcardiac perfusion with 10% formalin. Marks indicating the location of the recording chamber were compared with gross anatomic landmarks including the hemispheric midline and the arcuate and principal sulci. On the basis of the grid coordinates at which the electrode had been placed, recording sites then were projected onto the image of the cortical surface.
Bar-dot task
Both monkeys were trained to perform a task requiring them to make eye movements to one end or the other of a reference image which could be physically continuous or discontinuous. Essential features of the task are summarized in Fig. 1, A and B. At the beginning of each trial, while the monkey was fixating a central spot, a sample was presented, either in the form of a solid horizontal bar (Fig. 1A2) or in the form of a pair of dots corresponding to the ends of a virtual horizontal bar (Fig. 1B2). Then one end of the sample was cued (3). After a delay, a target appeared, identical to the sample in form but not necessarily in location (5). After a second delay, extinction of the central fixation spot (7) signaled the monkey to make an eye movement (8). If the monkey made a saccade directly to the end of the target corresponding to the cued end of the sample, then 100 ms after target-attainment, a white spot came on at the now-fixated target location, thus providing positive feedback. However, the monkey was required to maintain fixation on the target for an additional variable period (300-450 ms). Only at the end of this period was the display extinguished and reward delivered. These postattainment steps were introduced to prevent the monkey from following up the first saccade with a second one to some other part of the display. Any such behavior would have led to interpretational difficulties inasmuch as activity around the time of the first saccade might have been related to programming of the second one. To perform this task successfully, monkeys had to perceive and remember the location of the cue relative to a reference frame centered on the sample and had to do so regardless of whether the sample was a continuous horizontal bar or a pair of dots forming a horizontal array.
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Individual trials differed not only with respect to the nature of the reference image (bar or dots), but also with respect to the location of the sample (Fig. 1C: a or b; each bar indicates the location at which a bar or array could appear), the cued end of the sample (right or left), and the location of the target (Fig. 1C: f, g, or h; each bar indicates the location at which a bar or array could appear). Systematic variation in these factors gave rise to 24 conditions summarized in Fig. 1D. Trials corresponding to these 24 conditions were interleaved pseudorandomly according to the rule that one trial of each type had to be completed successfully before initiation of the next block. An essential feature of this design was the dissociation of relative location (the right or left end of the bar or array) from certain other factors that might influence neuronal activity in the SEF, notably the location of the cue on the screen (and thus the location of its image on the retina) and the screen location of the target. A cue at one screen location (Fig. 1C: d) could mark either the right end of a left-displaced sample (Fig. 1C: b) or the left end of a right-displaced sample (Fig. 1C: a). Similarly a target at one screen location (Fig. 1C: 3) might be either the right side of a left-displaced target (Fig. 1C: h) or the left side of a right-displaced target (Fig. 1C: g).
It may be noted that the location of the sample image was different in
this task than in the task employed in previous studies (Olson
and Gettner 1995, 1999
). In those studies, it was placed to one
side of fixation. Here, in contrast, it was presented in the upper
visual field where it appeared to the left or right of the midline on
interleaved trials. This change was instituted so as to eliminate the
asymmetry with respect to the visual field midline inherent in the
earlier design. Results obtained with the design used here can be
interpreted identically regardless of the recording hemisphere because
the task is perfectly symmetric with respect to the visual field and
thus with respect to hemispheric representation of visual space.
Memory-guided saccade task
We also recorded neuronal activity during performance of a standard oculomotor test requiring the monkey to make eye movements to targets in the form of small dots located at 9.6° eccentricity above, below, to the right of, and to the left of the fixation point. The main stages of a single representative trial lasting ~1.5 s are summarized in Fig. 13, A-F. The staggered panels in this figure represent the display on the screen in front of the monkey during successive stages of the trial. In each panel, a circle indicates the monkey's direction of gaze. While the monkey maintained fixation on a central spot (A), four potential targets were presented (B) and one of the targets was cued (C). The monkey then was required to maintain central fixation during a delay period (D) at the end of which the fixation spot was extinguished (E), whereupon the monkey had to make an eye movement rapidly and directly to the previously cued target (F). If the monkey made a saccade directly to the target, then 100 ms after target-attainment, the now fixated target increased in size, thus providing positive feedback. However, the monkey was required to maintain fixation on the target for an additional variable period (300-450 ms) before reward was delivered. Trials were imposed in pseudorandom sequence according to the rule that the monkey had to complete successfully one trial in each direction before moving on to the next block. Data collection continued until ~16 successful trials conforming to each of the four conditions had been completed.
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RESULTS |
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Task performance
Both monkeys learned to perform the bar-dot task at a level well above chance, and each experienced moderately more difficulty on dot than on bar trials. Monkey Ju scored 99.9% on bar trials as compared with 99.6% on dot 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 two percent-correct scores, although only a fraction of a percent, was significant (2-tailed paired t-test, P = 0.03). Monkey Po scored 95.9 and 89.4% on bar and dot trials, respectively; these values differed at a high level of significance (P < .0001).
The behavioral reaction time (the interval between offset of the fixation spot and initiation of the saccadic eye movement) also was measured as a function of cue condition in each monkey. In monkey Ju, there was a minor but significant (2-tailed paired t-test, P = 0.004) tendency for reaction times to be longer on bar than on dot trials (150 vs. 148 ms). The same tendency was present and significant in monkey Po (164 vs. 160 ms; P = 0.008). Decision time was not a factor in this effect because a long delay intervened between the instructional cue and the imperative signal. Perhaps it was related to subtle differences in the eye movements executed on bar and dot trials, as described in the following text.
Recording sites
Our approach in selecting recording sites was to record from neurons at the rough location of the SEF, as estimated on the basis of stereotaxic coordinates and, having identified sites at which there was robust eye-movement-related activity, to record from these sites and then move out from them to adjacent sites over successive recording sessions. At each site, we recorded from neurons located in the superficial cortex, remaining within the initially encountered gray matter and never passing through white matter into buried cortex. The mean recording depth (as measured relative to the level at which neural activity first was detected) was 875 ± 448 µm (mean ± SD; minimum = 178 µm, maximum = 1,988 µm) in monkey Ju and 781 ± 681 µm (minimum = 0 µm; maximum = 2,724 µm) in monkey Po. In the context of the bar-dot task, we characterized a total of 77 neurons from monkey Ju (17 and 60 in the left and right hemispheres, respectively) and 66 neurons from monkey Po (29 and 37 in the left and right hemispheres, respectively). The tangential distribution of bar-dot recording sites in monkey Ju is shown in Fig. 2A, where each dot represents one site and the size of the dot indicates how many neurons at that site contributed data to the present paper. Monkey Po is still under behavioral study, therefore it is not possible to describe precisely the relation of the recording sites to gross morphological landmarks.
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Because we almost immediately located sites of oculomotor activity in
each hemisphere of each monkey, we had no occasion to carry out
extensive mapping, defining the borders of the SEF or identifying
adjacent regions such as the supplementary motor area. Accordingly, it
is reasonable to ask whether the sites from which we recorded were
indeed in the SEF. To answer this question, we compared our recording
sites to maps of the SEF generated in previous studies as summarized by
Tehovnik (1995). Table 1 of Tehovnik's review
summarizes the results of 10 studies in which electrical stimulation
was used to map out the SEF, indicating, for each study, the area's
mediolateral extent (ML, defined relative to the interhemispheric
midline) and anterior-posterior extent (AP, defined relative to the
genu of the arcuate sulcus). These results are translated, in Fig.
2B, into a graph in which the area of each dot corresponds
to the fraction of the 10 studies in which electrical stimulation at
the dot's location elicited eye movements (the dots in Fig.
2B range in area from 1
only one study reported elicitation
of eye movements by stimulation at that location
to 10
all 10 studies reported a positive result). Loci at which electrical
stimulation elicited eye movements in a large number of studies are
marked by a cluster of large dots extending 3-7 mm anterior to the
level of the genu of the arcuate sulcus. We may now compare the
recording sites in monkey Ju to sites of electrical stimulation in these studies. Recording sites in monkey Ju
extended 4-9 mm anterior to the genu of the arcuate sulcus (Fig.
2A: as, genu), with an average of ~6 mm. We conclude that
recording sites in monkey Ju were toward the front of the
cortical territory in which electrical stimulation has been reported to
elicit eye movements and that they overlapped the part of this
territory in which electrically induced eye movements have been
obtained with greatest frequency. Recording sites in monkey
Ju also overlapped the SEF as identified by electrical stimulation
in later studies not considered by Tehovnik. Chen and Wise
(1995b
, Fig. 8A) show sites positive for elicitation of eye
movements as extending 2-6 mm anterior to the genu, whereas Fujii et al. (1995
, Fig. 1) show such sites at levels
1-8 mm anterior to the genu. Finally, it should be noted that
recording sites in monkey Ju do not overlap the zone rostral
to the SEF in which Bon and Lucchetti (1994)
have
described electrical stimulation as eliciting ear movements. This zone
extends ~10-14 mm anterior to the genu (Bon and Lucchetti
1994
, Fig. 2A). This set of comparisons, although not as
conclusive as electrical stimulation mapping carried out in the same
monkey and although limited by the accuracy with which gross
morphological landmarks can be identified in published figures,
nevertheless suggests strongly that recording sites in this study were
confined to the SEF.
Object-centered direction selectivity
We will refer to a neuron as exhibiting object-centered direction selectivity if it fired at different rates on trials requiring an eye movement to the left versus the right end of a reference image even when the retinal location of the cue and the location of the target on the screen were held constant across trials. An example of a neuron exhibiting strong object-centered direction selectivity under both bar and dot conditions is shown in Fig. 3. During delay 1, the period between presentation of the cue and onset of the target bar, this neuron's rate of firing was markedly higher on trials in which the right side of the image had been cued (Fig. 3, C and D) than on those in which the left side had been cued (Fig. 3, A and B) regardless of whether the image was a bar (Fig. 3, B and D) or a pair of dots (Fig. 3, A and C). This difference in level of activity cannot have resulted from any difference in the retinal location of the cue because, under all four illustrated conditions, the cue was at the same location, directly above fixation.
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To obtain an objective estimate of the frequency with which neurons exhibited object-centered direction selectivity, we carried out analyses of variance on data collected from each neuron during three trial epochs: delay 1 (from cue onset until target onset), delay 2 (from target-onset until fix-spot-offset) and the movement period (from the initiation of the saccade until 100 ms after its completion). There was a solid rationale for using these epochs, insofar as object-centered signals, if they waxed and waned during a trial, generally did so in the vicinity of the epoch boundaries. Nevertheless the divisions should be viewed as essentially heuristic with full appreciation of the fact that continuous activity might be parsed into multiple epochs (e.g., in the case shown in Fig. 3, where object-centered signals carried over from delay 1 to delay 2). In each analysis, there was one dependent variable (firing rate) and there were two factors: object-centered direction (right or left) and image type (bar or dot). Consideration during delay 1 was restricted to a subset of conditions in which the screen location of the cue was balanced across the two factors (conditions 2, 4, 6, 7, 9, 11, 14, 16, 18, 19, 21, and 23 in Fig. 1D). Consideration during delay 2 and the movement period was restricted to a subset of conditions in which the screen location of the target was balanced across the two factors (conditions 2, 3, 4, 5, 8, 9, 10, 11, 14, 15, 16, 17, 20, 21, 22, and 23 in Fig. 1D). A significance criterion of P < 0.05 was employed. The results, summarized in Table 1, indicate that around half of the tested neurons showed a main effect of object-centered direction during each epoch (65/143 during delay 1, 89/143 during delay 2, and 57/143 during the movement period).
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To determine whether neurons exhibiting object-centered direction selectivity were arranged within the recording zone according to any clear global pattern, we computed for each recording site the frequency with which neurons at that site yielded a significant main effect for object-centered direction. Three tests had been carried out on each neuron, assessing activity during delay 1, delay 2, and the movement period. Thus at a cortical site where n neurons had been studied, 3*n tests were carried out. The results of these tests are summarized for each recording site in Fig. 4, A and B. In this figure, the size of each circle indicates the percentage of tests revealing significant selectivity for object-centered direction. Although there was some variation from site to site in the proportion of tests yielding a significant result, there was no clear mediolateral or anterior-posterior trend in the arrangement of sites with a high yield.
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It was obvious on casual inspection of the data that neurons exhibiting object-centered direction selectivity under bar conditions also did so under dot conditions (Fig. 3). To assess this effect systematically, we carried out an additional step of analysis. For each recorded neuron during each trial epoch, we computed the directional signal (firing rate under left-side-cued trials minus firing rate on right-side-cued trials) independently for bar and dot conditions, restricting consideration to conditions in which the retinal location of the cue and the screen-location of the target were balanced across object-centered direction. The results are summarized in the graphs of Fig. 5, which plot the directional signal for dot trials, on the vertical axis, against the directional signal for bar trials, on the horizontal axis, with each neuron represented as a single point. The clear positive correlation between directional signals recorded during dot and bar trials (significant at P < .0001 for each monkey during each epoch) indicates that neurons firing more strongly during left-side-cued (or right-side-cued) trials under dot conditions tended to display the same pattern under bar conditions. In monkey Ju, the R2 values for delay 1, delay 2, and the movement period were 0.574, 0.584, and 0.405, respectively. In monkey Po, the corresponding values were 0.810, 0.449, and 0.324.
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A few neurons, although exhibiting object-centered direction
selectivity under both bar and dot conditions, nevertheless appeared to
fire at different rates under the two conditions or appeared to carry
object-centered signals of different strength. In the neuron of Fig.
6, firing during delay 1 was stronger on
trials in which the right end of the image had been cued (Fig. 6:
C and D vs. A and B). In
addition, activity was stronger under bar conditions than under
corresponding dot conditions (Fig. 6: B and D vs.
A and C). The converse was true of the neuron
shown in Fig. 7. During delay 2, after
onset of the target and before the signal to respond, this neuron fired
more strongly on trials when the right end of the reference image was
the target (Fig. 7: E-H vs. A-D). However, its
activity differed across dot and bar trials. On dot trials, it fired
more strongly and showed an enhancement of the object-centered directional signal (the difference in firing rate between conditions in
which the left or right end of the reference image had been cued). The
strength of the directional signal can be estimated in Fig. 7 by
comparing horizontally juxtaposed histograms (A vs. E;
B vs. F; C vs. G; D vs. H). In
each pair, the left histogram represents activity on trials in which
the left end of the reference image had been cued and the right
histogram represents activity on trials in which the right end had been
cued, with other factorsthe retinal location of the cue and the
location of the target on the screen
held constant.
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The frequency with which neurons differentiated between bar and dot
conditions is indicated by results summarized in Table 1. On the basis
of the frequency with which main effects and interaction effects
involving image type occurred, we draw the following conclusions.
1) Around a quarter of tested neurons showed a main effect
of image type (bar vs. dot) during each epoch (31/143 during delay 1, 44/143 during delay 2, and 36/143 during the movement period). Each of
these proportions is greater than expected by chance (P < .0001, 2 test). 2) Among neurons
in which there was a main effect of image type, those firing more
strongly under dot conditions were markedly preponderant during later
epochs (34/44 during delay 2 and 30/36 during the movement period).
Each of these proportions is greater than expected by chance
(P < 0.001,
2 test).
3) In a few neurons, there was an interaction between object-centered direction and image type (17/143 during delay 1, 39/143
during delay 2, and 22/143 during the movement period). Each of these
proportions is greater than expected by chance (P < 0.001,
2 test). 4) Among neurons
exhibiting a significant interaction between object-centered direction
and image type, the preponderant pattern during later epochs was for
the directional signal (the difference in firing rate between
left-side-cued and right-side-cued conditions) to be stronger under the
dot condition (26/39 during delay 2 and 16/22 during the movement
period). Each of these proportions is greater than expected by chance
(P < 0.05,
2 test). The
general conclusion arising from these observations is that neuronal
activity (both net activity and differential activity dependent on
object-centered direction) tended to be stronger under the dot
condition but that the effect was weak.
Finally, we assessed whether the tendency of neurons to fire
differently on bar and dot trials was related to their cortical location. For each neuron during each of three trial epochsdelay 1, delay 2, and the movement period
an ANOVA had been carried out
indicating whether or not firing rate was significantly
(P < 0.05) dependent on two factors (object-centered
direction and image type) or their interaction. Thus at a location in
the cortex where n neurons had been recorded, there were
3*n tests that might reveal a main effect of image type and
3*n tests that might reveal an interaction effect involving
image type. For each cortical location, we counted the number of
significant outcomes in each of four categories: main effect (firing
greater under dot conditions), main effect (firing greater under bar
conditions), interaction effect (difference in firing rate between
left-on-image and right-on-image trials greater under dot conditions),
and interaction effect (difference in firing rate between left-on-image
and right-on-image trials greater under bar conditions). The results
are shown in Fig. 8, A-H,
where the size of each circle indicates the number of tests on data
from that site yielding the indicated outcome. The figure reveals no
clear trend toward segregation of sites exhibiting different patterns
of dependence on image type.
|
In summary, our main finding is that most SEF neurons exhibiting object-centered direction selectivity under the standard condition used in our previous experiments (horizontal bar as reference image) also did so under a new condition (a pair of dots in a horizontal array as reference image). During each trial epoch, the firing of around a quarter of the neuronal sample was significantly affected by the type of image (bar or dot) either in the form of a main effect or in the form of an interaction with object-centered direction. Even in these cases, however, the preferred object-centered direction was the same under both conditions.
Possible influence of variations in ocular landing position
It is important to ask whether the signals interpreted in the preceding section as being object-centered possibly could have arisen from minor variations in the physical trajectory of the eyes. Accordingly, we analyzed saccades executed on bar and dot trials. We found that the trajectory of the eyes did vary slightly as a function of whether the target was the left or right end of a reference image. Especially in the case of a bar, the eyes did not land precisely on the end of the image but rather deviated inward toward its center. This is illustrated in Fig. 9, which shows eye-movement data from a single data-collection session. The symbols represent eye position over a period extending from 100 ms before to 100 ms after the instant of peak eye velocity for ~12 eye movements under each of 12 conditions. The reference image could be at any of three locations (left = L, middle = M, and right = R), and the target could be either the right end (r) or the left end (l) of the image. Thus there were six conditions in which the reference image was a bar and six in which it was a pair of dots. Among the six bar conditions (Fig. 9A), there were two pairs in which the targets were at the same location on the screen but at opposite ends of a bar (Lr vs. Ml and Mr vs. Rl). It is clear that the terminal direction of gaze was offset to the left by around half a degree on trials when the target was the right end of a bar (Lr and Mr) as compared with corresponding trials when target was the left end of a bar (Ml and Rl, respectively). In contrast, under conditions in which the target was an array of dots (Fig. 9B), this tendency was vanishingly small.
|
To determine how consistent this pattern was, we computed the mean
landing point of the eyes (the location to which gaze was directed
70-100 ms after the instant of peak velocity) under each of four
spatial conditions (Lr, Ml, Mr, and Rl) for both bar and dot reference
images. The results are summarized in Fig.
10, which shows the mean, across all
data collection sessions, of the ocular landing position associated
with each condition (all SDs were between 0.05 and 0.25°). In each of
eight comparisons (2 screen locations × 2 image types × 2 monkeys), the eyes landed at significantly different loci when the
targets were at the same location on the screen but at opposite ends of
their respective reference images (paired t-test,
P < 0.05). In seven of eight comparisons, the eyes
deviated toward the center of the reference image so as to land farther
to the left when the target was the right end of a reference image and
farther the right when it was the left end. The sole exception arose in
monkey Ju on comparison of eye movements to the right end of
the middle dot array (Mr) and the left end of the right dot array (Rl).
Across both monkeys and all four target locations, the mean horizontal
displacement of the landing position on image-right as compared with
image-left trials was 0.85° under the bar condition and 0.10° under
the dot condition. This pattern of deviation is similar to the one
observed by Edelman and Keller (1998) in monkeys trained
to make eye movements to single target spots and exposed to occasional
trials in which two spots came on simultaneously at radial directions
45° apart. On those trials, the eyes tended to land between the two
targets; indeed when the saccades were of express latency (<90 ms),
they landed close to the middle of the array. The effect was mild in our study because, unlike Edelman and Keller, we trained monkeys to
select one end or the other of the distributed pattern, withholding reward if they landed outside a target window centered on the correct
end.
|
Given that the orbital directions of the eye movements varied
subtly but systematically between image-right and image-left trials, we
considered the possibility that neurons exhibiting apparent
object-centered direction selectivity were simply selective for the
orbital directions of eye movements. To assess this possibility, we
carried out a test summarized in Fig.
11. The test was applied to each neuron
for which the ANOVA had revealed a significant main effect of
object-centered direction. For each such neuron, the test was applied
independently to each epoch in which a significant effect had been
present. For each such epoch, it was applied to each image type. Each
test focused on those four trial conditions in which the target was the
right end of an image at the left location (Lr), the left end of an
image at the middle location (Ml), the right end of an image at the
middle location (Mr), or the left end of an image at the right location
(Rl). For each of these conditions, we computed the mean horizontal
coordinate of the eyes' landing position: X(Lr),
X(Ml), X(Mr), and X(Rl). We also
computed the mean observed firing rate: O(Lr),
O(Ml), O(Mr), and O(Rl). We next
fitted a line to the four points representing O as a
function of X. Then for each condition, we computed the firing rates predicted on the assumption that firing rate was a linear
function of X: P(Lr), P(Ml),
P(Mr), and P(Rl). Finally, we computed two
object-centered directional signals: the one actually observed0.5 *
[O(Mr)
O(Rl) + O(Lr)
O(Ml)]
and the one predicted from the linear function
0.5
* [P(Mr)
P(Rl) + P(Lr)
P(Ml)]. Figure 11 shows the results of applying this
procedure to a single case
neuron ju152a41, delay 2, dot
conditions
for which eye-position data are shown in Fig. 9B
and firing rate data in Fig. 7, A, C, E, and G. The observed object-centered directional signal was 9.6 spikes/s, in
marked contrast to the object-centered directional signal predicted on
the basis of linear dependence on horizontal landing position (
0.23
spikes/s). Given the fact that the predicted signal was 42 times
smaller in amplitude than the observed signal, not to mention opposite
in sign, we conclude that orbital direction selectivity cannot explain
this neuron's object-centered direction selectivity.
|
The results for all neurons and epochs are summarized in Fig. 12, where, in each panel, the observed object-centered signal is plotted on the horizontal axis and the object-centered signal predicted on the basis of the landing-position hypothesis is plotted on the vertical axis. The range of predicted object-centered signals is obviously miniscule as compared with the range of observed object-centered signals. In monkey Ju, the standard deviation of the observed values was greater than the standard deviation of the predicted values by factors of 9.7 and 38.1 under bar and dot conditions, respectively. In monkey Po, the corresponding values were 5.3 and 56.1. In summary, if we assume that neuronal activity is related only to the eyes' landing position, form the best estimate of the linear function relating firing rate to landing position, take into account the differences in landing position across different conditions, and compute the spurious "object-centered" directional signal predicted on the basis of the differences in landing position, then we find that the predicted spurious signals are extremely small as compared with the signals actually observed in the experiment. We conclude that object-centered direction selectivity is not an artifact arising from subtle variations of the eyes' landing position across conditions.
|
Relation to selectivity for saccade direction in the memory-guided saccade task
Even if our recording sites were within the SEF as defined on
morphological grounds, which we believe to have been the case, nevertheless neurons exhibiting object-centered direction selectivity in the bar-dot task might constitute a population distinct from intermingled neurons exhibiting selectivity for saccade direction in
standard oculomotor tasks as described by previous authors. To cast
light on this issue, we compared results obtained in the bar-dot task
(Fig. 1) with those obtained in a memory-guided saccade task (Fig.
13). The latter task required monkeys
to make eye movements to four targets at rightward, upward, leftward,
and downward locations relative to fixation. The use of four targets at
directions 90° apart, common in studies of the SEF (Chen and
Wise 1995a,b
, 1996
, 1997
; Schall 1991a
,b
), is
warranted because SEF neurons are very broadly tuned for saccade
direction and amplitude (Russo and Bruce 1996
). In the
context of the memory-guided saccade task, we studied a total of 125 neurons from monkey Ju (56 and 69 in the left and right
hemispheres, respectively) and 156 neurons from monkey Po (79 and 77 in the left and right hemispheres, respectively). Many but
not all of these neurons also were studied in the bar-dot task (62 in
monkey Ju and 52 in monkey Po).
|
First we asked whether there was any systematic pattern to the topographic distribution of neurons exhibiting saccade-direction selectivity. We based this analysis on all neurons studied in the memory-guided saccade test regardless of whether they were studied in the bar-dot task. The significance (P < 0.05) of each neuron's selectivity for eye-movement direction was assessed by means of an ANOVA with direction (right, up, left, or down) as the single factor and with firing rate as the dependent variable. This was done independently for the delay period (from onset of the cue to offset of the fixation spot) and the movement period (from offset of the fixation spot to 100 ms after completion of the saccade). Thus at a location in the cortex where n neurons had been recorded, 2*n tests of significance were carried out. For each cortical location, we computed the percentage of tests that yielded a significant outcome. The results are shown in Fig. 14, A and, B, where the size of each circle indicates the percentage of tests, on data from that site, indicating significant selectivity for eye-movement direction. Inspection of this figure reveals that orbital direction selectivity was comparatively widespread across the recording sites sampled in each monkey. Further, the patterns of regional arrangement showed no clear trends of a form consistent across hemispheres or monkeys. Finally, comparison of sites yielding significant selectivity for eye-movement direction (Fig. 14, A and B) to sites yielding significant selectivity for object-centered direction (Fig. 4, A and B) reveals that the two were largely overlapping.
|
Next we carried out a set of comparisons intended to reveal whether the presence or sign of direction selectivity in the memory-guided saccade task was correlated with the presence or sign of object-centered direction selectivity in the bar-dot task. This analysis was restricted to 114 neurons studied in both tasks. Data collected from each neuron during the memory-guided saccade task were assessed to determine whether the firing rate was significantly affected by vertical direction (upward vs. downward trials) or horizontal direction (rightward vs. leftward trials). Each comparison was carried out on data from the delay period (cue onset to fix-spot offset) and the movement period (fix-spot offset to 100 ms after completion of the saccade). Four t-tests indicated whether the neuron was significantly (P < 0.05) selective for direction as defined with respect to the horizontal and vertical axes during the delay and movement epochs. Neurons were tested for object-centered direction selectivity by means of an ANOVA as described in an earlier section.
We first asked whether selectivity for vertical direction,
as observed in the memory-guided saccade task, was related to
object-centered direction selectivity, as observed in the bar-dot task.
It was reasonable to pose this question because all eye movements
required in the bar-dot task were in an upward direction. We calculated the numbers of neurons exhibiting various combinations of selectivity during three pairs of epochs: delay 1 in the bar-dot task versus delay
in the memory-guided saccade task; delay 2 in the bar-dot task versus
delay in the memory-guided saccade task; and movement period in the
bar-dot task versus movement period in the memory-guided saccade task.
The results are presented in Fig. 15,
A and B. In each panel, the rows contain counts
of cells exhibiting (S) or not exhibiting (N) significant
image-centered direction selectivity in the bar-dot task. Likewise, the
columns contain counts of cells not exhibiting vertical direction
selectivity (N) or significantly favoring downward (D) or upward (U)
movements in the memory-guided saccade task. We carried out two
2 tests on these counts. The first test,
applied to all neurons, assessed whether the presence of
selectivity for eye-movement direction as defined with respect to
the vertical axis (in the memory-guided saccade task) was correlated
with the presence of selectivity for object-centered
direction (in the bar-dot task). Overall, across all pairs of
epochs in both monkeys, there was a slight trend for object-centered
direction selectivity to be more common among neurons selective for
vertical direction than among those not so selective (56 vs. 46%).
However, this tendency did not achieve significance (P < 0.05) for any pair of epochs in either monkey. The second test,
applied only to neurons exhibiting selectivity for direction as defined
with respect to the vertical axis, assessed whether the preferred
vertical eye-movement direction (upward or downward) was
correlated with the presence of selectivity for object-centered
direction. Overall, across all pairs of epochs in both monkeys,
there was a slight trend for object-centered direction selectivity to
be more common in neurons selective for upward than in those selective
for downward movement (58 vs. 41%). However, this tendency did not
achieve significance (P < 0.05) for any pair of epochs
in either monkey.
|
We next asked whether selectivity for horizontal direction,
as observed in the memory-guided saccade task, was related to object-centered direction selectivity, as observed in the bar-dot task.
We wished to determine whether object-centered direction selectivity
was especially common among neurons exhibiting selectivity for
horizontal eye-movement direction. Further, in cases where selectivity
was present in both tasks, we wished to determine whether the preferred
directions matched. We compared results between three pairs of epochs
as described in the preceding paragraph. Counts of neurons exhibiting
various combinations of significant selectivity during these epochs are
presented in Fig. 15, C and D. In each panel, the
rows contain counts of neurons not exhibiting object-centered direction
selectivity (N) or significantly favoring the image's ipsilateral (I)
or contralateral (C) end in the bar-dot task. Likewise, the columns
contain counts of neurons not exhibiting horizontal direction
selectivity (N) or significantly favoring ipsiversive (I) or
contraversive (C) eye movements in the memory-guided saccade task. We
carried out two 2 tests on these counts. The
first test, applied to all neurons, assessed whether the presence
of selectivity for eye-movement direction as defined with respect
to the horizontal axis (in the memory-guided saccade task) was
correlated with the presence of selectivity for object-centered
direction (in the bar-dot task). Overall, across all pairs of
epochs in both monkeys, there was a slight trend for object-centered
direction selectivity to occur more frequently in cases where
horizontal eye-movement direction selectivity was present than in cases
where it was absent (56 vs. 44%). However, this tendency did not
achieve significance (P < 0.05) for any task epoch in
either monkey. The second test, applied only to neurons exhibiting
direction selectivity in both tasks, assessed whether the
preferred horizontal eye-movement direction (contraversive
or ipsiversive) was correlated with the preferred object-centered
direction (contralateral-on-image or ipsilateral-on-image).
Overall, across all pairs of epochs in both monkeys, neurons with
matching preferences for object-centered direction (in the bar-dot
task) and eye-movement direction (in the memory-guided saccade task)
outnumbered those with nonmatching preferences (70 vs. 21%). When
delay 1 in the bar-dot task was compared with the delay period in the
memory-guided saccade task, the trend toward matching directional
preferences was significant in monkey Po (P = 0.007) and approached significance in monkey Ju
(P = 0.099). When delay 2 in the bar-dot task was
compared with the delay period in the memory-guided saccade task, the
trend toward matching directional preferences achieved significance in
monkey Po (P = 0.020) but not in
monkey Ju (P = 0.35). When the movement
period in the bar-dot task was compared with the movement period in the
memory-guided saccade task, the trend toward matching directional
preferences achieved significance in monkey Ju
(P = 0.038) and approached significance in monkey
Po (P = 0.098). We conclude that the strongest
correlation between results obtained in the bar-dot task and the
memory-guided saccade task concerns preferred direction. Neurons
preferring contraversive (or ipsiversive) eye movements in the
memory-guided saccade task tend to prefer the contralateral (or
ipsilateral) end of the image in the bar-dot task.
In summary, comparison between neuronal activity in the memory-guided saccade task and the bar-dot task has revealed a significant trend for neurons preferring leftward (or rightward) saccades in the memory-guided saccade task to favor the left (or right) end of the bar or dot display. Two other trends were present but did not achieve significance. First, neurons selective for saccade direction with respect either to the vertical or the horizontal axis tended also to be selective for object-centered direction. Second, among neurons selective for vertical saccade direction, those selective for upward saccades (the direction required in the bar-dot task) tended to exhibit object-centered direction selectivity. The first, significant, finding is compatible with the notion that there is a principled relation between neuronal activity displayed in the two task contexts. The other trends, if genuine, would provide additional support for this view.
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DISCUSSION |
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SEF neurons encode locations relative to bars and arrays
The most general finding of this study is that the SEF contains a
population of neurons that encode the object-centered location of the
target of an eye movement, doing so regardless of whether that location
is defined with respect to a continuous image (a horizontal bar) or a
discontinuous image (a pair of dots marking the ends of a virtual
horizontal bar). Neurons firing preferentially when the monkey has
selected the left (or right) end of a bar as a target also fire
preferentially when he has selected the leftmost (or rightmost) of two
dots in a horizontal array. The primary significance of this finding
lies in its showing that the object-centered direction selectivity of
SEF neurons (Olson and Gettner 1995, 1999
) is robust
across large changes in the visual properties of the reference object
including ones that affect its physical continuity. The only precedent
for such an effect is the finding of Niki (1974)
that
prefrontal neurons in monkeys performing a delayed alternation task
fired at a level determined by the relative location of the previously
selected lever (right or left) regardless of the absolute location of
the two-lever array.
In light of this finding, one can imagine two general possibilities. 1) If the monkey can discriminate an image from the background and if, doing so, he makes eye movements to particular locations defined relative to the image, then SEF neurons will encode the object-centered directions of those eye movements. In other words, object-centered directional signals in the SEF can be referred to any discriminable object. 2) Some visual attributes of the image other than sheer discriminability do matter, but physical continuity is not one of those attributes. There are manipulations by which one could still further degrade the perceptual coherence of the dot array used in this experiment while leaving it discriminable. For example, the salience of the dot array could be reduced by presenting it against a field of multiple dots from which it is only minimally discriminable. Alternatively, its perceptual unity could be reduced by making the two dots different in color, shape, and motion. It is conceivable that the monkey still would be able to perform the task after these manipulations and yet that object-centered signals in the SEF would be reduced.
There is an apparent discrepancy between our finding of bar-dot
equivalence and studies of brain-damaged humans demonstrating that
neural pathways for "within-object" and "between-object" spatial vision are at least partially separate (Humphreys and Riddoch 1994, 1995
). Humphreys and Riddoch have described
bilateral parietal-lobe patients who neglect the left side of an array
if treating it as an object (as in reading a printed word) but neglect the right side if treating it as an array (as in spelling out a written
word one letter at a time). This result implies that separate
populations of neurons in the intact parietal lobe must represent the
right or left end of an object as opposed to the right or left element
in an array. In contrast, we have found that the same population of SEF
neurons encodes the right or left end of a bar and the right or left
element in a dot-pair. This apparent discrepancy is potentially
resolvable in at least two ways. Perhaps within-object and
between-object signals are carried by separate populations of neurons
at the level of parietal cortex but converge at the level of the SEF.
Or perhaps our monkeys adopted a within-object set toward both the bars
and the dot arrays with the result that the same within-object neuronal
population was active during both kinds of trials. Observations on
parietal neglect patients have suggested that the mode of processing is
dependent on both the physical properties of the stimulus and the
subject's instructional set. The influence of the stimulus is manifest
in the fact that Humphreys and Riddoch's patient JR exhibited
within-object and between-object patterns of neglect when carrying out
an identical task on groups of elements that respectively suggested or
did not suggest a single object. Further, a pair of neglect patients studied by Bisiach et al. (1994)
made subtly different
bisection errors according to whether the image being bisected was a
horizontal line or a pair of dots. The influence of instructional set
is manifest in the fact that two instructions ("read" or
"spell") induced different modes of processing of the same material
(a word) in Humphreys and Riddoch's patients. The implication of this
dual set of observations is that presenting a pair of dots as a
reference image probably favored but did not necessarily enforce the
monkeys' processing it as two objects rather than one.
Some SEF neurons are sensitive to image type
The central finding of this study is that SEF neurons encode
object-centered locations regardless of the physical continuity or
discontinuity of the reference image; however, a secondary finding is
that some neurons do fire more or less strongly according to whether
the reference image is a bar or a pair of dots. During each task epoch,
beginning with the onset of the reference image and ending with
execution of the eye movement, around a quarter of SEF neurons fired at
significantly different levels under dot and bar conditions with a
majority firing more strongly under the dot condition. Likewise,
neurons tended to carry stronger object-centered directional signals
under the dot condition. These effects cannot be interpreted
unequivocally on the basis of the present data alone. They could
reflect neuronal sensitivity to the purely visual properties of the
image, the requirement to make within-object versus between-object
spatial judgements, or task difficulty. Certain manipulations rendering
an oculomotor task more difficult already are known to elicit enhanced
activity in the SEF. These include requiring the monkey to select a
target by a learned arbitrary association (Olson and Gettner
1996) and requiring him to make an eye movement away from a cue
(Gettner and Olson 1996
; Schlag et al.
1997
). Although there is little face validity to the notion
that the dot condition should have been harder than the bar condition,
the fact is that both monkeys made more errors under this condition.
Regardless of which explanation turns out to be the correct one, this
phenomenon does not detract from the main conclusion of this study,
namely, that SEF neurons do encode object-centered locations regardless
of whether the reference images are physically continuous or discontinuous.
Selectivity for object-centered direction versus saccade direction
A full analysis of the relation between object-centered direction
selectivity and selectivity for saccade direction is outside the scope
of this paper. However, we will comment briefly on the issue of how
these two properties relate to each other. On comparing neuronal
activity in the bar-dot task to neuronal activity in the memory-guided
saccade task, we discovered one significant trend. Neurons preferring
leftward (or rightward) saccades in the memory-guided saccade task
tended to favor the left (or right) end of the bar or dot display. This
finding seems to imply that the same neuron can carry object-centered
signals in one context and eye-centered signals in another; however, it
is conceivable that this is not so. For example, in the memory-guided
saccade task, the signals that we have regarded as reflecting saccade direction might in fact encode the location of the target relative to a
default reference object such as the screen or the array of possible
targets. In this case, neuronal activity in both tasks would reflect
object-centered direction. Alternatively, in the bar-dot task, on
image-right (or -left) trials, the monkey might covertly program
saccades to the right (or left) on the false premise that the end of
the bar predicts the direction of the saccade. In this case, neuronal
activity in both tasks would reflect the direction of the intended
saccade. Arguments that there is only one kind of signal falter,
however, when confronted with the observation that the same neuron can
be influenced simultaneously by both eye- and object-centered direction
during the second delay period in the bar-dot task, a period during
which the monkey knows both the eye- and the object-centered direction
of the impending saccade (Olson and Gettner 1995) (also
Fig. 7 of this paper). For this reason, we believe that SEF neurons
genuinely carry both eye- and object-centered signals. The confluence
of eye- and object-centered signals in the SEF, far from being
problematic, would make good sense if the area were at a level in the
functional circuitry of the brain transitional between stages at which
spatial representations are object and eye centered (Deneve and
Pouget 1998
) or if SEF neurons embodied a basis set from which
representations relative to multiple reference frames including
eye-centered and object-centered ones could be extracted (Pouget
and Sejnowski 1999
). The fact that any given neuron's activity
is ambiguous (because it could reflect either eye-centered or
object-centered direction) is no more a problem than in area V1 (where
a given level of activity in a given neuron may arise from numerous
combinations of orientation and contrast). In each case, ambiguity
vanishes at the level of activity across a population.
Implications with respect to general functions of the SEF
The long-standing view that the SEF is a premotor area for eye
movements (Schall 1997) is supported by two main
observations: SEF neurons fire before and during saccades (Bon
and Lucchetti 1992
; Chen and Wise 1995a
,b
, 1996
,
1997
; Hanes et al. 1995
; Mann et al.
1988
; Mushiake et al. 1996
; Russo and
Bruce 1996
; Schall 1991a
,b
; Schlag and
Schlag-Rey 1985
, 1987
; Schlag-Rey et al. 1997
) and electrical stimulation of the SEF elicits saccades (Chen and Wise 1995b
; Fujii et al. 1995
; Lee and
Tehovnik 1995
; Mann et al. 1988
; Mitz and
Goldschalk 1989
; Russo and Bruce 1993
;
Tehovnik and Lee 1993
; Tehovnik and Sommer
1997
; Tehovnik et al. 1994
; Tian and
Lynch 1995
). Further, in both recording and stimulation studies, it has been shown that particular sites in the SEF represent directions with respect to motorically relevant frames of reference: frames centered on the eye (Bon and Lucchetti 1992
;
Mitz and Godschalk 1989
; Russo and Bruce 1993
,
1996
; Schlag and Schlag-Rey 1987
) and head
(Bon and Lucchetti 1990
, 1992
; Lee and Tehovnik
1995
; Schlag et al. 1992
; Tehovnik
1995
; Tehovnik and Lee 1993
; Tehovnik et
al. 1994
). These observations, with their strong implication that the SEF is an oculomotor area, seem difficult to reconcile with
the finding, reported both here and in our previous publications (Olson and Gettner 1995
, 1999
), that around half of SEF
neurons signal the directions of eye movements as defined relative to an object-centered reference frame. Neurons that carry object-centered signals fire at different levels during physically similar eye movements if those eye movements are to different parts of a reference image. Thus their signals are unyoked from the dynamics and kinetics of
the eye movements and, in that sense, are not motor signals. How are we
to resolve the apparent contradiction between this finding and the
classic view of the SEF as an oculomotor area?
There would be no contradiction between our findings and the classic
view of the SEF as a motor area if it was the case that our recording
sites were outside the SEF. Then we simply could conclude that neurons
in an area adjacent to the SEF encode the object-centered locations of
targets while SEF neurons participate in the programming of eye
movements. The view that our recording sites were outside the SEF seems
implausible, however, in light of the anatomic location of recording
sites and the functional properties of neurons. We have measured the
location of the recording sites relative to a standard set of
morphological landmarks (Tehovnik 1995) and have shown
that they lie within the zone demarcated in previous mapping studies
based on electrical stimulation (Fig. 2). Within this zone, they are
located relatively anteriorly, but they are not outside it. Further,
they overlap the subregion of the zone in which eye movements have been
elicited most frequently
i.e., in virtually all electrical stimulation
studies to date (largest dots in Fig. 2B). Further, we have
compared results obtained in the object-centered localization task to
results obtained in a standard oculomotor test, the memory-guided
saccade task. We have shown that cortical sites where neurons exhibit
object-centered direction selectivity (Fig. 4) substantially overlap
those sites where neurons exhibit selectivity for saccade direction
(Fig. 14). Further, we have shown that a substantial number of neurons exhibits spatial selectivity in the context of both tasks and that,
among these neurons, there is a significant tendency for those
preferring rightward (or leftward) eye movements in the memory-guided
saccade task to prefer right-on-image (or left-on-image) conditions in
the object-centered localization task. On these grounds, we consider it
very probable that our recording sites are within the confines of the
SEF as delimited by other authors.
There would be no contradiction between our findings and the classic
view of the SEF as a motor area if the apparently object-centered signals of the neurons in our study were correlated with the physical properties of the monkey's eye movementsproperties that happened to
covary with object-centered direction. To assess this possibility, we
analyzed the directions of eye movements executed under different trial
conditions. We found that the landing position of the eyes did deviate
slightly away from the target location toward the center of the
reference object on bar trials and, to a lesser degree, on dot trials
(Figs. 9 and 10). However, it is unlikely that this alone could account
for object-centered direction selectivity. Against this interpretation,
we have shown that the measured orbital sensitivity of each neuron
could account for only a small fraction of its measured object-centered
directional sensitivity (Figs. 11 and 12). Further, we have shown that
object-centered direction selectivity is at least as strong under dot
conditions as under bar conditions (Fig. 5), whereas the deviation of
the eyes from the target is smaller under dot than under bar conditions
by almost an order of magnitude (Fig. 10). Thus we feel confident that
object-centered directional signals in the SEF are not simply an
artifact of variations in eye-movement direction. It might be suggested
that even though the initial saccades were similar on image-right and
image-left trials, they were followed up by second saccades that were
in different directions. In particular, having fixated the right end of
the reference image, monkeys might execute a saccade to its left end,
and vice versa. Human and monkey studies have implicated the SEF in the
execution of sequences of saccades; so it would not be surprising if
neurons fired differentially at the outset of different sequences
(Gaymard et al. 1990
, 1993
; Sommer and Tehovnik
1999
). However, this interpretation is ruled out by the fact
that the monkeys in our study were required to maintain fixation on the
target for a period of 450-550 ms after foveating it, at which point
the display was extinguished and reward delivered, so that there was no
opportunity to execute a saccade to the other end of the target object.
At the moment of reward delivery, both monkeys generally made large
downward saccades; however, because data collection stopped at that
point, we are not able to comment on the metrics of these movements.
Given that the neurons in our study are in the SEF and do carry
object-centered signals, we are left with an apparent contradiction between the classic view that the SEF is an oculomotor area and the
current finding that the activity of some of its neurons is unyoked
from the physical parameters of eye movements. The simplest resolution
to this contradiction is to suppose that the SEF contributes to
oculomotor control at a comparatively early or abstract stage before
the final programming of the movements. This view is actually consonant
with an already existent body of evidence indicating that the functions
of the SEF are comparatively far removed from the oculomotor periphery.
In particular, the SEF, as compared with the FEF, exhibits a higher
incidence of learning-related activity (Chen and Wise
1995b), a greater frequency of hand-movement-related activity
(Mushiake et al. 1996
), a higher current-threshold for elicitation of eye movements by electrical stimulation (Russo and Bruce 1993
; Tehovnik and Sommer 1997
), and a
weaker impact of local inactivation on oculomotor performance
(Sommer and Tehovnik 1999
).
There are several general functions, antecedent to programming the
physical parameters of eye movements, to which the SEF might contribute
and in terms of which one might try to understand the phenomenon of
object-centered direction selectivity. In this section, we will
consider and provisionally reject three possible interpretations before
presenting a fourth interpretation that seems, on the basis of current
evidence, to be the most plausible. We recognize, however, that this
issue is a complex one and that final resolution will not be possible
without further study. 1) Representing cues for eye
movements. One potential explanation for object-centered direction
selectivity is that SEF neurons mediate arbitrary learned associations
between cues and eye movements. According to this argument, SEF neurons
with object-centered direction selectivity are simply recording the
occurrence of a visual event (appearance of the cue on the right or
left end of the sample bar) possessing a learned association with a
particular eye movement. This argument is fallacious because, in fact,
the sample-cue display is not associated with a particular eye movement
but rather with a particular rule for selecting the eye movement, given
the location of the target bar. Further, this argument ignores the
report of Chen and Wise (1995a,b
), that SEF neurons,
recorded in monkeys performing a pattern-conditional eye movement task,
encode eye-movement direction and not cue identity. 2)
Representing rules for eye movements. Another potential
explanation for object-centered direction selectivity is that SEF
neurons represent any arbitrary rule by which the monkey is prepared to
select an eye-movement target. This would imply that select populations
of SEF neurons should become active when the monkey is prepared to
select not only the leftmost but also the reddest or the largest of a
group of impending stimuli. We question this interpretation on two
grounds. First, some SEF neurons fire differentially before visually
guided eye movements to a spot incidentally superimposed on the left or
right end of a task-irrelevant bar, thus carrying object-centered
signals even when the monkey is not following an object-centered rule (Olson and Gettner 1995
). Second, when the monkey is
using a color rule (select as target either the red or green dot of a
two-dot array) SEF neurons exhibit virtually no difference in activity on trials when the rule is "red" or "green" but differentiate strongly between trials on which the target dot happens to be the right
or left end of its array (Olson et al. 1999
).
3) Representing corrections of eye movements. A
third potential explanation for object-centered signals is that they
represent corrections imposed by the SEF on reflexively programmed eye
movements. Suppose, as suggested by the results of Edelman and
Keller (1998)
, that the onset of a target configuration
automatically induces the programming of a reflexive eye movement that
would bring the eye to the configuration's visual center of gravity.
Correct performance in the bar-dot task then could be achieved by
adding to this reflexive signal (directing the eyes to the center of
the bar or array) a corrective signal (corresponding to the offset of
the selected target from the center). This corrective signal would
appear to be object-centered. This explanation is appealing because it
links object-centered direction selectivity to a quite peripheral
aspect of oculomotor control. It falters, however, in the face of the
observation that object-centered signals are virtually unaffected by a
doubling of the size of the target bar (unpublished results). One would
expect neuronal activity encoding the corrective signal to change
dramatically under these circumstances. 4)
Representing locations of targets relative to landmarks. A
final potential explanation for object-centered direction selectivity
is that the SEF mediates the performance of eye movements under
conditions such as those pertaining in this study
conditions in which
the location of the target is computed by triangulation from other
elements visible in the scene. The ability to make eye movements under
the guidance of visible stimuli to locations not at the center of
gravity of those stimuli may seem like a skill with little use outside
the laboratory. However, it is easy to imagine cases in which it would
be worthwhile to look at a location where something is expected to
appear, even when that point is not currently marked by any local
detail, and that getting to that point might be aided by taking into
account elements visible elsewhere in the scene. Humans are able to use indirect spatial cues in this way as evidenced by the fact that their
saccades to a remembered location are more accurate if a visible
landmark is present in some part of the scene (Karn et al.
1997
). How often, under natural circumstances, monkeys execute a saccade, under guidance of a set of scene elements, to a location other than the center of gravity of those elements is an empiric issue
that remains to be resolved. On any occasion when they do so, the brain
can be thought of as carrying out a process in which it combines the
perceived eye-centered coordinates of a landmark and the stored
landmark-centered coordinates of the target so as to compute the
intended eye-centered coordinates of the saccade. We suggest that the
SEF is part of a network responsible for this process and that, within
that network, it occupies a level before the output level at which
representations are purely motoric. This general account leaves many
specific questions unanswered. For example, why do different neurons
carry object-centered signals during different phases of task
performance and why do some neurons carry object-centered signals even
during the movement epoch
after selection of the target has been
finalized? Despite these limitations, the idea that the SEF
participates in the guidance of eye movements by landmarks seems to
provide the most plausible explanation for our results.
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ACKNOWLEDGMENTS |
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We thank K. Rearick for excellent technical assistance.
C. R. Olson received support from the National Eye Institute (Grant RO1 EY-11831), which also provided technical support through Core Grant EY-08098.
Present address of L. Tremblay: INSERM U289, Pavillon Claude Bernard, Hôpital de la Salpêtri re, 47 Bld. de l'Hôpital, 75651 Paris Cedex 13, France.
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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 9 August 1999; accepted in final form 2 November 1999.
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