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Neural correlates of object-based attention
Abstract
Much research has been directed toward disentangling the "units" of attention: Is attention directed to locations in space, visual objects, or to individual features of an object? Moreover, there is considerable interest in whether attention increases the gain of neural mechanisms (signal enhancement) or acts by other means, such as reducing noise or narrowing channel tuning. To address these questions, we used a direct measure of signal strength: the amplitude of visual evoked potentials and a task in which selection could be based on a depth order cue but not on location. Attended and nonattended stimuli were presented at different temporal frequencies, and, thus, responses to the two stimuli could be analyzed separately even though they were presented simultaneously. Attention increased the amplitude of the second harmonic component of the response, but not the fourth harmonic. In addition, responses measured at the second harmonic, but not at the fourth harmonic, were larger for stimuli seen as behind. The results are consistent with the fourth harmonic being generated at a stage of processing that is not accessible to attention and where depth order has not been extracted. The second harmonic, on the other hand, is modifiable by attention and shows evidence for differential encoding of depth order.
History
Received March 7, 2002; published December 6, 2002
Citation
Pei, F., Pettet, M. W., & Norcia, A. M. (2002). Neural correlates of object-based attention.
Journal of Vision, 2(9):1, 588-596,
Keywords
attention, Visual Evoked Potentials, visual cortex, electrophysiology, VEP, ERP
Several theories of attention postulate that attention
is organized around space and works like a “spotlight” that moves
across the visual field (Eriksen &
Eriksen, 1974; Posner, 1980; LaBerge & Brown, 1986; Eriksen & St James, 1986; Treisman, 1988; for reviews, see Cave & Bichot, 1999; Kanwisher & Wojciulik, 2000). Several
lines of evidence support this view. Performance measured through accuracy and
reaction time is better for a stimulus presented at an attended region of space
(Posner, 1980; Posner, Snyder, & Davidson, 1980;
Bashinski & Bacharach, 1980; Muller & Findlay, 1987; Downing, 1988), and event-related potential
(ERP) studies have shown enhanced processing for stimuli presented to attended
locations in the form of increased evoked response amplitudes (Posner et al., 1980; Hillyard & Munte, 1984; Mangun & Hillyard, 1987).
Other authors have argued that visual attention
operates on object features, such as motion, shape, color, and orientation,
suggesting that features rather than spatial locations are the primary cues that
engage the attentional process (Hillyard
& Munte, 1984; Corbetta, Miezin,
Dobmeyer, Shulman, & Petersen, 1990; Roelfsema et al., 1998; Baldassi & Burr, 2000). Duncan (1984) suggested that attention is
directed to segmented objects. Evidence from both human and animal studies has
supported this theory (Roelfsema, Lamme
& Spekreijse, 1998;
Valdes-Sosa, Bobes, Rodriguez, & Pinilla, 1998; for reviews, see Posner and
Driver, 1992; Scholl, 2001). It has
also been argued that location- and object-based attention mechanisms are not
mutually exclusive, but they are alternatively evoked by different task demands
(Vecera & Farah, 1994), and more
recent theories have incorporated both location- and object-based types of
selection (Treisman, 1993; Desimone & Duncan, 1995).
Within the object/feature selection model, it is
difficult to distinguish experimentally between the effects related to features
of objects as opposed to the object per se. Moreover, the use of subjective
recall to measure processing of unattended stimuli can confound attentional effects with memory effects (cf., Driver,
2001). More direct, neurally based measures, such as fMRI and the ERP,
present alternative methodologies for assessing processing within attended and
nonattended streams. O’Craven, Downing,
and Kanwisher (1999) showed that attention to objects (houses
and faces) produced higher neural activity in brain areas specialized for
processing that kind of information (parahippocampal “place area”
and fusiform “face area”). This experiment excluded the spatial
attentional cue by superimposing the attended and nonattended stimuli. A second
strength of their paradigm lay in the fact that they could measure, at the same
time, the response to a feature of the objects (motion) that was not relevant
for the primary task, as well as responses related to the objects per se.
ERPs have been used extensively to study neural
activity generated by attended and nonattended stimuli. Early studies used transient ERPs and manipulated spatial attention (Hillyard & Munte, 1984; Mangun & Hillyard, 1987). In those
studies, a flash of light or grating was presented to one hemifield and the
subjects were cued to the side where the stimuli would subsequently appear.
Spatially directed attention to a cued stimulus produced an enhancement of
particular components of the signal (P1/N1), suggesting an active gain control
mechanism (for a review, see Mangun,
1995).
Attentional effects have also been demonstrated using
the steady-state response evoked by flickering, spatially cued stimuli (Morgan, Hansen, & Hillyard, 1996;
Muller et al., 1998; Di Russo & Spinelli, 1999; Muller & Hillyard, 2000; Di Russo, Spinelli, & Morrone, 2001). In
Morgan et al. (1996) and Muller et al. (1998),
task-relevant and task-irrelevant stimuli were temporally modulated at different
temporal frequencies, and responses were separately measured at the
corresponding response frequencies. Enhancement of the steady-state signal was
found for stimuli presented at the cued spatial location. In DiRusso and Spinelli (1999) and DiRusso et al. (2001), flickering chromatic
or achromatic gratings were presented in one hemifield. In one condition,
attention was directed to that hemifield through a contrast discrimination task
while visual evoked potentials (VEPs) were measured. In another condition,
attention was directed to the opposite hemifield by having the observers perform
a letter discrimination task. Attention directed to the hemifield with the test
stimuli resulted in larger signal amplitudes for both chromatic and achromatic
gratings and marginally faster response latencies for the achromatic
gratings.
More recently, Valdes-Sosa, et al.
(1998) found evidence for object-based ERP effects using
superimposed stimuli that could not be selected on the basis of location. In
that study, two transparent, rotating dot fields were presented, one comprised
of red dots and the other of green dots. After a period of oppositely directed
rotations, one of the fields translated linearly and the motion onset VEP to
that motion was recorded. The observers were cued as to which color stimulus was
task relevant (direction discrimination), and VEPs were measured to
displacements that occurred for either task-relevant or task-irrelevant stimuli.
Valdes-Sosa, et al. (1988) found
a strong suppression of P1/N1 components related to the unattended motions.
Attentional modulation was weak or absent in control conditions that did not
elicit the percept of separate transparent surfaces. Torriente, Valdes-Sosa, Ramirez, and Bobes
(1999) presented random element patterns that split into moving and static
subsets that were spatially interspersed. The observers were given a task that
required attention either to the static or moving elements. The amplitude of the
N170 component to motion was reduced when attention was directed to the static
elements.
Here we combined the temporal tagging method used by Morgan et al. (1996) and Muller et al. (1998) with a
motion display that used occlusion cues to segregate overlapping stimuli into
different apparent depth planes. The advantage of the tagging method is that one
can directly monitor processing in the attended and unattended streams
simultaneously and with high precision for response dynamics. Rather than
allowing spatial selection, as in by Morgan et
al. (1996) and Muller et
al. (1998), we provided features that supported the
perceptual segregation of the attended and nonattended targets into separated
depth planes. This combination of features will constitute our operational
definition of an “object” in this study.
Thirteen adults (6 males and 7 females, aged 21 to 50
years) participated. Two participants were excluded from the analysis because
their signal-to-noise ratio was too low. The exclusion was blind to the effects
of attention or any of the other dependent measures. Each observer had 6/6 or
better acuity in each eye, normal stereopsis on the Frisby free-space
stereo-test, and was fully refracted for the viewing distance. The research
followed the tenets of the World Medical Association Declaration of Helsinki,
and informed consent was obtained from the subjects after explanation of the
nature and possible consequences of the study. The local institutional human
experimentation committee approved the research.
The display was generated using conventional raster
graphics (800 × 600 pixels at 72 Hz refresh) on a monochrome computer
monitor. The stimulus consisted of a series of 16 crosses spread across an 18.5
× 24-deg display with a background luminance of 50 cd/m2. Each
bar was 3 deg high and 0.3 deg wide. The center-to-center spacing of the crosses
was 6.03 deg. The bars were oscillating sinusoidally at two different but very
close temporal frequencies (TF) (Movie 1). This
allowed us to analyze the data separately for the two different components even
though the responses were being generated simultaneously in the attended and
nonattended streams. The vertical bars moved together right and left at TF1 =
2.4 Hz, and the horizontal bars moved up and down at TF2 = 3.0 Hz. The relative
amplitude of the motion was 40% of the bar length (1.2/deg peak-to-peak motion
centered the 3 deg
bars).
Movie 1. This
movie is an example of one of the eight conditions that we used in our
experiment showing how the two components were moving.
We counterbalanced luminance (5, 95 cd/m2)
and depth order (in front, behind) of the vertical and horizontal bars in order
to obtain four different stimulus configurations (Figure 1). Because the luminance of the bars
differed, we could assign one of the colors to occlude the other, creating an
unambiguous monocular cue for depth order.
Figure 1. The figure shows the four different configurations of the stimuli used in our experiment. The vertical and horizontal bars were matched for luminance and depth order. The vertical bars (TF1) oscillated rightward and leftward at 2.4 Hz while the horizontal bars oscillated upward and downward at 3.0 Hz (TF2). We collected data for each of these four stimuli in two different conditions, paying attention to the vertical bars paying attention to the horizontal bars.
For each configuration described above, we collected
data in two different attentional conditions (attend vertical bars or attend
horizontal bars) for a total of eight conditions. Each trial presentation lasted
8.3 s, and we recorded 10 trials for each condition. Trials were run in blocks
of 5, and each block was repeated twice with the order of presentation of each
block being randomized.
Before starting each trial, the observer was instructed
to attend to either the vertical or the horizontal bars while maintaining
fixation in the center of the display, without making any eye movements. The
observers were also instructed to withhold eye blinks during the trial. The
observers initiated trials with a button and could interrupt the trials or abort
them as needed to retain blink-free fixation. Each observer was previously
trained with about 4 to 6 trails before starting the session to be sure they
understood the task and could perform it correctly.
The brain electrical activity was recorded with Grass gold-cup surface electrodes. Electrode impedance was between 3 and 10 kilo-ohms. We recorded from a chain of 5 electrodes placed over the posterior occipital lobe, each referenced to linked ears. The central electrode was placed at the midline 3 cm above the Inion. Two electrodes were placed 3 and 6 cm laterally on each side of the midline electrode from left to right; these derivations will be referred to as O3, O1, Oz, O2, and O4. The inter-electrode distance was 3 cm (see Figure 2).
Figure 2. The image shows schematically the electrode positions on a head seen from above. The posterior part of the head is on the bottom of the figure. Oz was placed 3 cm above the Inion. O3, O1, O2, and O4 are the occipital sites (channels), and the distance between each site was 3 cm starting from Oz. A1 and A2 are the two reference electrodes placed on the ear lobes.
The electroencephalogram (EEG) was amplified by 50,000
times with Grass Model 12 amplifiers and was digitized to 16 bits accuracy at a
sampling rate of 432 Hz. Analog filter settings were 0.3 to 100 Hz, measured at
–6 dB points. We averaged the data for each subject for all the trials
related to the eight separate conditions. Responses were isolated from the EEG
by analyzing the distinct temporal harmonic components generated by the vertical
(1F1, 2F1, 4F1...) and the horizontal bars (1F2, 2F2, 4F2...). Spectrum analysis
at these harmonics was performed with an adaptive matched filter technique using
a recursive least squares adaptive filter (Tang
& Norcia, 1995). Complete spectra (e.g., Figure 3) were computed with a mixed-radix
discrete Fourier Transform (dft routine; MATLAB, Mathworks, Inc.).
Because each of the two stimulus components was tagged
by a different temporal frequency, we could measure the responses generated by
both the attended and the nonattended stimulus components in the same condition
at the same time. Figure 3 shows the spectrum
of the response for a single
observer. Figure 3. Example of spectral analysis of data from a single observer. The data are from the Oz derivation recorded under two different conditions: attending to vertical (the upper, orange spectrum) and attending to horizontal bars (the bottom, blue spectrum). The vertical bar oscillated at TF1 = 2.4 Hz and the horizontal bars oscillated at TF2 = 3.0 Hz. Attention increased the amplitude of the second harmonic of the attended stimulus relative to the unattended stimulus.
We concentrated our data analysis on the second and the
fourth harmonics because these even harmonics dominate the response to symmetric
oscillatory motion. As can be seen in Figure
4 (top panel), evoked response amplitude at the second harmonic component
was maximal at Oz for both TF1 and TF2 stimuli (error bars are ±1 SEM).
However, the effect of attention was present on all channels. We did not find an
effect of attention at the fourth harmonic.
Figure 4. Plots of the amplitude of the
VEP signal for the second harmonics (top panel) and fourth harmonic (bottom
panel) as a function of different channels. Data averaged across subjects. On
the left side are plotted the signal related to the vertical bars (2F1 and 4F1)
when they were attended (blue symbols) and when they were nonattended (red
symbols). On the right is plotted the signal related to the horizontal bars (2F2
and 4F2) when they were attended (green symbols), and when they were nonattended
(orange symbols). The experimental noise levels are shown as dotted lines. The
noise estimates were calculated as the mean amplitudes at a pair of adjacent
nonharmonic frequencies. These frequencies were located ± 0.6 Hz from the
response frequency of interest (see Norcia, Sato, Shinn,
& Mertus, 1985; Norcia, Hamer,
Jampolsky, & Orel-Bixel, 1995).
The effects of attentional instruction, depth order,
luminance, and orientation of the bars were analyzed using a multi-variate
approach to repeated measures analysis (multi-variate analysis of variance
[MANOVA]).
For each main effect and interaction, we computed
Hotelling’s T2statistic:
which, in our design, is
F(1,n-1)-distributed, where
n = number of subjects;
and,
is the mean response vector, where
yi
is the 32-element vector of scalp potentials recorded for the full set of
permutations of our five design factors, for each subject, j;
and,
is the pooled covariance matrix; and
c is a contrast vector corresponding to
the particular effect being tested. Details and
derivations can be found in Rencher
(1995, p. 158).
Data reported below are from the Oz derivation, which
was chosen because it had the largest and most reliable response across
observers.
We analyzed the data separately for the two harmonics
of interest (second, fourth). Earlier pilot studies indicated that temporal
frequency and bar orientation variables do not interact with attention. The
error bars represented in the graphs are always ±1 SEM.
First, we analyzed the data related to the four
different stimulus configurations, collapsing across the attention variable. Figure 5 plots mean amplitude data for the
second and fourth harmonics as a function of frequency (TF1, TF2) and relative
luminance. There was no main effect of luminance, nor were there any significant
interactions involving the luminance variable (see Figure 5). However, the same analysis for the
variable depth order showed an increment of the second harmonic signal amplitude
related to the tagged component that is behind (see Figure 6). This effect was not present for the
fourth harmonic. Overall, there was a significant main effect of depth order
(F(1,10) = 22.4; p = .0008)
with amplitudes larger for responses generated by occluded stimuli. We found a
significant interaction involving depth and harmonic (F(1,10) =
19.36; p = .001) reflecting depth order
effects present only at the second harmonic. Additionally, there was a
significant depth-by-frequency interaction (F(1,10) = 14.1;
p = .004). At the second harmonic, the
F2 stimulus generated a relatively large response when it was behind (see Figure
6).
Figure 5. Second and fourth harmonic data
from Oz averaged across subjects. The two graphs show the amplitude of the
signal at the second harmonic and at the fourth pooled across the variable
attention when the bars were
5-cd/m2 luminance (green
bars) or 95-cd/m2
luminance (gray bars). There are no effects of luminance.
Knowing the influence of depth order and luminance on
the signal baseline, we looked at the effect of the variable attention. The
average of the signal amplitude across subjects for each of the 5 occipital
channels was significantly larger for the attended component of the stimuli
compared to the nonattended one in all of the conditions. The effect of
attention as a function of frequency is shown in Figure 7 for the Oz derivation for both second
and fourth harmonic components. Overall, there is a main effect of attention
(F(1,10) = 35.07; p = .0001)
with the attended condition having larger amplitudes. There is an
attention-by-harmonic interaction (F(1,10) = 22.8;
p = .0007) consistent with the presence
of an attentional modulation of about 30% at the second harmonic that is absent
at the fourth harmonic. There were no other effects involving the attention
variable. Importantly, we found that both depth order and luminance have no
effect in relation to the signal enhancement due to attention at the second
harmonic (F(1,10) = 0.002; p
= .97 and F(1,10) = 0.113; p
= .74). Also at the fourth harmonic, none of the variables interact with
attention. Figure 6. Data from Oz averaged across
subjects. The two graphs show the amplitude of the signal at the second harmonic
and at the fourth pooled across the variable attention when the bars were behind
(green bars) or in front (gray bars). The response to each temporal frequency
oscillation at the second harmonic is larger when the bars are behind.
There is a possibility, related to the spatial
attention hypothesis, that the observers were paying attention just to the tips
of the bars (the segments that were not overlapping at any time), say in the
immediate area around fixation. It is possible, but unlikely, that attentional
modulation of responses generated by this small fraction of the display would be
able to swing the total VEP voltage by the amount we
measured. Figure 7. Data from Oz averaged across
subjects. On the left panel, we represent the signal amplitude at the second
harmonics for the vertical (2F1) and the horizontal (2F2) bars. For both 2F1 and
2F2, the attended condition (orange bars) shows significantly larger amplitude
than the nonattended one (blue bars). This graph shows the enhancement of the
signal with attention in our experiment. On the right side, we plotted the
amplitude of the signal for both the vertical (4F1) and the horizontal (4F2)
bars at the fourth harmonic. In this case, there was no difference between the
attended (orange bars) and the nonattended (blue bars) conditions. Spatial
Attention Control Experiment
In order to eliminate this possibility, we ran a
control experiment in five subjects where we used the same temporal frequency of
the bars and motion amplitude as in the original experiment. The difference was
that in this experiment the bars themselves were shortened so that they
completely overlapped over the stimulus cycle (1.2 deg motion of 1.2 deg bars).
The observers were instructed to attend to either the vertical bars (F1) or the
horizontal bars (F2) in separate conditions. We used only one of the
configurations illustrated in Figure 1.
Responses were measured at the second and fourth harmonics of the two component
frequencies, and we pooled that data across temporal frequency (F1/F2) for
attended and nonattended conditions. We found that observers were still able to
modulate the magnitude of their responses: responses averaged 60% larger at the
second harmonic for attended versus nonattended stimuli
(p < .001; paired comparison
t test). There was no significant
effect of attention at the fourth harmonic
(p = .5029), replicating the results of
the first experiment. For spatial attention to act on these stimuli, the
spotlight would have to be movable both with high precision (to avoid the region
of the nonattended bar) and with great speed (because the faster of the bars was
moving at 3 Hz).
Sustained attention to a component of a complex moving
pattern produced an enhancement of evoked activity at the second harmonic but
not the fourth harmonic. In our study, the two components were spatially
overlapped, and it is difficult to imagine that a spatial location mechanism
such as an attentional “spotlight” could separate them. On the other
hand, the components had a well-segregated perceptual depth ordering, and
attentional selection along the depth
axis might underlie the effect. In this regard, it is important to note that
depth order itself produced reliable differences in response amplitude that were
independent of attentional instruction for the second harmonic.
The use of the tagging VEP technique allowed us to
monitor the response from the two stimulus components at the same time. Although
we did not use an auxiliary behavioral task to monitor attentional performance,
the fact that we measured an enhancement of the signal related to the specific
temporal frequency corresponding to the attended bars means that the subjects
were successful in doing the task. An auxiliary task could possibly have
increased the effect, so our data may represent a lower bound on the magnitude
of modulation that is possible under optimal conditions.
Our interpretation of this pattern of results is that
the fourth harmonic is generated early in the chain of visual processing at a
site that is both prior to attentional access and the extraction of depth order.
We can make this inference based on a general principle of neural systems: the
higher harmonics are preferentially generated during the earliest part of the
time-evolution of the evoked response. Those harmonics dominate the leading edge
of the evoked response, which is invariably steeper than the trailing edge (cf.,
the time-frequency analysis of Norcia et al., 1985).
We thus suggest that the second harmonic component is dominated by later
processing stages where depth order has been extracted and attention can act. It
is possible that attention can only act on segmented “objects,” and
our attentional effect thus lies either at or after the depth-order extraction
stage. Previous psychophysical studies have also suggested that attention is
deployed at the level of segmented objects (Duncan, 1984; for reviews, see Driver, 2001 and Scholl, 2001).
One could also propose that attention is needed to
perform the depth segmentation. Regardless of the direction of causality, it is
apparent that we have tapped two very distinct levels of processing: a
preliminary stage representing itself in the fourth harmonic and a later stage
that contributes to the second harmonic.
As noted in the “Introduction,” most
previous ERP studies have been conducted within the spatial attention framework,
with the observers being cued as to the location of the task-relevant target.
Attention to location results in enhancement of early components in the P1
(approximately 80-120 msec) to N1 (approximately 150-200 msec) latency ranges,
without a corresponding change in scalp topography (for reviews, see Mangun, 1995, and Anllo-Vento & Hillyard,1996). Other
ERP studies have presented relevant and irrelevant stimuli sequentially to the
same location with selection being based on a feature such as color (Hillyard & Munte, 1984; Anllo-Vento & Hillyard, 1996), motion
(Anllo-Vento & Hillyard, 1996), or
spatial frequency (Harter and Previc,
1978; Martinez, Di Russo, Anllo-Vento,
& Hillyard, 2001). These studies have found an increased negativity in
the 150-300 msec time-range (selection negativity [SN]) for attended stimuli,
with the scalp topography of the SN being substantially different than that of
N1/P1.
In our study, using steady-state potentials, we showed
that attention increased the signal strength at a neural level similar to
previous studies, but that spatial attention is not required for amplitude
enhancement. Within the limits of our sampling, the attentional effect does not
involve substantial changes in response topography (see Figure 4).
Of more direct relevance to this work are the
experiments of Valdes-Sosa, Cobo, and Pinilla
(1998), Torriente et al.
(1999), and Pinilla, Cobo, Torres, and
Valdes-Sosa (2001). In each of these studies, motion cues were used to
elicit the percept of two overlapping objects lying in different depth planes.
As noted by the authors of these studies, location-based spotlight mechanisms
could not be used to select stimuli. Torriente et al. (1999) suggested that
their results and, by implication, those of Valdes-Sosa, Cobo, et al. (1998) and
Pinilla et al. (2001) could be
interpreted within the framework of a “motion-filter” (e.g., McLeod, Driver, & Crisp, 1988; McLeod, Driver, Dienes, & Crisp, 1991; Driver, McLeod, & Dienes, 1992). In this
view, stimuli of different motion characteristics activate separate
motion-selective channels that can be selected via attentional mechanisms.
As a general speculation and to stimulate further
research (other than positing a filter-based model for selection of moving
stimuli), it is possible to reformulate the spotlight metaphor to include the
third dimension, in which case selection on the basis of perceptual depth order
could comprise a variant of spatial attention. Valdes-Sosa, Cobo, et al.
(1998) and Pinilla et al.
(2001) have proposed an internal surface-based representation (e.g., He & Nakayama, 1995) as an alternative basis
for selection, which is tantamount to an explicitly 3-D version of the spotlight
model. Objects, by their very nature, exist in three dimensions and there are
many monocular cues, such as the occlusion cue used in this study, that could
signal a separation in depth that would be useful for attentional
selection.
This work was supported by grant EY06579 (A.M.N. and
M.W.P.) from the National Eye Institute of the National Institutes of Health and
by a Rachel C. Atkinson Fellowship (F.P.). A preliminary version of this work
was presented at the 2001 Annual Meeting of the Optical Society of America,
October 13-14, 2001, Irvine, CA. Thanks to Stefano Baldassi for helpful comments
and advice. Commercial Relationships: None.
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