openresearch-repository.anu.edu.au · Web viewThis manuscript investigates two important visual...
Transcript of openresearch-repository.anu.edu.au · Web viewThis manuscript investigates two important visual...
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The independence of endogenous attentional orienting and object individuation
Stephanie C. Goodhew
Research School of Psychology, The Australian National University
Word count: (Main text): 6,908
Corresponding Author: Stephanie C. Goodhew
Address: Research School of Psychology (Building 39)
The Australian National University, Canberra, 2601
Email: [email protected]
Running head: Endogenous attention and object individuation
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Abstract
Object individuation is the process whereby the brain infers that dynamic input reflects
multiple discrete objects, rather than a single, continuing object over time. Object substitution
masking is popular method for operationalising object individuation inferences in the
laboratory. While object substitution masking was historically thought to interact with
attentional processes, an emerging body of literature indicates that this form of visual
masking is impervious to some attentional manipulations. However, one form of attention
that has not been systematically studied in relation to object-substitution masking is
endogenous attentional orienting. This is important because in other domains, endogenous
attentional orienting has been found have qualitatively distinct effects from other forms of
attention, including impacting visual perception when other forms of attention do not.
Therefore, if attention does interact with object individuation processes, then endogenous
attentional orienting is the most likely candidate mechanism for such a relationship. Here,
therefore, the impact of endogenous attentional on object-substitution masking was tested.
Across two experiments, while endogenous attentional orienting impacted overall target
perception, it had no impact on object substitution masking. This implies that object
individuation inferences are indeed independent of attention.
Public Significance Statement: This manuscript investigates two important visual processes
and determines whether they interact or are independent. One is voluntary visual attention,
the process of strategically selecting certain aspects of visual scene for privileged perceptual
processing, and the other is object-individuation, the process whereby the human brain
determines that dynamic visual input reflects multiple objects rather than a single object
continuing over time. Here, it was found that these processes, while each having a strong
impact on perception in their own right, operate completely independently of one another.
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Keywords: object individuation; object-substitution masking; object perception; visual
masking; attention; visual attention; endogenous attention; attentional orienting
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Imagine that you are driving and glance in the wing mirror of your car, and see a car driving
directly behind you. In a few moments’ times, you see a car in the lane beside you. Is this the
same car? If your brain decides that this is the same object that has changed relative location
over time, then an inference of object-correspondence is said to have occurred. In contrast, if
your brain determines that it is in fact a distinct object and that the first car is still behind you
(e.g., now in your blindspot), then an inference of object-individuation is said to have been
reached. While such object-individuation inferences can be conceptualised as a judgement,
like much of cognitive processing, they would typically occur pre-consciously, influencing
the contents of conscious perception while the decision-process itself remaining outside of
this sphere. Such inferences can have dramatic consequences for our perception of and
interaction with the world around us (Goodhew, 2017).
Now consider another core cognitive process: attention. In the visual domain, when
looking at a scene there is typically far too much information for our capacity-limited
resources to fully process. Visual attention, therefore, serves as a triaging mechanism,
prioritising the processing of salient and relevant information while filtering out other
information (Broadbent, 1982). For example, when driving, an effective use of attentional
resources would be to focus on other vehicles, road signs, and potential hazards (e.g.
pedestrians approaching the road), while filtering out the roadside trees and advertising signs.
Visual attention can be allocated in different ways, including being involuntarily captured to
a given location, stimulus, or feature due to its raw physical salience, even when it is not
necessarily helpful to the task at hand (e.g., a flashing billboard capturing attention while
driving; exogenous attentional orienting) (Awh, Belopsolsky, & Theeuwes, 2012; Chica,
Bartolomeo, & Lupianez, 2013; Eimer & Kiss, 2007; Jonides & Yantis, 1988; Theeuwes &
Godijn, 2002; Yeshurun & Levy, 2003). Visual attention can also be strategically applied to a
location or stimulus based on useful sources of information in the environment (e.g.,
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voluntarily applying attention to an upcoming intersection to check for cross-traffic;
endogenous attentional orienting) (Abrams, Barbot, & Carrasco, 2010; Addleman, Tao,
Remington, & Jiang, 2018; Awh et al., 2012; Becker, 2010; Chica et al., 2013; Hein, Rolke,
& Ulrich, 2006; Most et al., 2001; Sharp, Melcher, & Hickey, 2018; Vromen, Lipp, &
Remington, 2015), and even on the basis of reward or previous selection goals (e.g., attention
being captured by a red car because you were previously scanning for a red traffic light;
selection history) (Awh et al., 2012; Scalf, Ahn, Beck, & Lleras, 2014). The key question
addressed in this present study is: to what extent do endogenous visual-attentional and object-
individuation mechanisms interact?
A well-established method for operationalising the cognitive process of object
individuation is object-substitution masking (OSM). In OSM, a sparse mask (e.g., four-dots),
that onsets at the same time but temporally-trails after the target interferes with the perception
of the target, via object-individuation mechanisms (Goodhew, 2017; Lleras & Moore, 2003).
Masking magnitude is quantified as the difference in target perception (gauged via
identification or detection accuracy) for these delayed mask-offset trials subtracted from
baseline performance when the target and mask offset simultaneously (simultaneous offset
condition). It is now widely understood that the masking reflects the inference that the
dynamic display reflects a single, continuing object, and therefore the conscious percept is of
the end-state (four-dots alone). Correspondingly, when the original target array and trailing
four-dot mask array are treated as distinct objects (i.e., inference of object-individuation),
then masking is reduced or eliminated (Goodhew, 2017; Goodhew, Boal, & Edwards, 2014;
Goodhew, Edwards, Boal, & Bell, 2015; Goodhew, Gozli, Ferber, & Pratt, 2013; Goodhew,
Greenwood, & Edwards, 2016; Guest, Gellatly, & Pilling, 2012; Lleras & Moore, 2003;
Moore & Lleras, 2005; Pilling & Gellatly, 2010).
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In contrast, early accounts of OSM posited that the preventing focussed attention on
the target was a necessary condition for masking to occur (Di Lollo, Enns, & Rensink, 2000;
Enns & Di Lollo, 1997). Specifically, it was proposed that the target representation is
consolidated and ultimately perceived via a series of iterative re-entrant processing loops that
liaise between broad-brushstroke perceptual representations in frontal regions and localised
high-resolution perceptual details in early visual areas. However, the presentation parameters
of the delayed mask offset in OSM interferes with this process, creating a conflict between an
initial partial or incomplete representation of the target and incoming high-fidelity input of
the mask alone. Masking occurs when the mask ‘wins’ the competition for consciousness,
due to greater perceptual weight than the target, and/or an inability to finalise the rapidly-
decaying target representation (Di Lollo et al., 2000). This object-substitution model is
explicit with respect to the role of attention, stating that non-target items in the display are
involuntarily processed, meaning that the higher the number of non-target stimuli, the greater
the number of iterative loops required to resolve the target (and therefore the greater the
chance that the mask will win the competition and masking will result) (Di Lollo et al.,
2000). If so, then if attention is applied to the location of the target in advance, then masking
should be mitigated or eliminated.
Consistent with this, historically, it was thought that OSM did not occur for a single
item in a display, but instead it only occurred when there were distractors preventing
focussed attention being applied to the target. Moreover, it was thought that attention and
OSM interacted, such that the magnitude of masking increased concomitantly with the
number of distractors or other attentional manipulation (Carlson, Rauschenberger, &
Verstraten, 2007; Di Lollo et al., 2000; Dux, Visser, Goodhew, & Lipp, 2010; Goodhew,
Dux, Lipp, & Visser, 2012; Kotsoni, Csibra, Mareschal, & Johnson, 2007; Tata & Giaschi,
2004; Weidner, Shah, & Fink, 2006; Woodman & Luck, 2003). However, a more recently
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emerging corpus of evidence indicates that this conclusion stemmed from methodological
artefacts in these earlier studies, such as ceiling effects artificially reducing the effect of
attentional manipulations on masking magnitude when attention is more strongly focussed
(e.g., at smaller set-sizes). This work has shown that when these issues are corrected, while
attention has an overall impact on target perception, masking magnitude (i.e., difference in
accuracy between simultaneous and delayed mask offset conditions) appears unaffected, and
OSM can indeed occur for single-item presentations with attention focussed on them
(Argyropoulos, Gellatly, Pilling, & Carter, 2013; Camp, Pilling, Argyropoulos, & Gellatly,
2015; Filmer, Mattingley, & Dux, 2014, 2015; Filmer, Wells-Peris, & Dux, 2017; Goodhew
& Edwards, 2016; Pilling, Gellatly, Argyropoulos, & Skarratt, 2014). More specifically,
OSM magnitude is unchanged irrespective of: the number of distractors presented
concurrently with the target (Argyropoulos et al., 2013; Filmer et al., 2014), exogenous
attentional orienting to the target location (Pilling et al., 2014), the size of the attended region
for a centrally presented target (Goodhew & Edwards, 2016), and even executive rather than
spatial attentional manipulations (Filmer et al., 2017). These findings challenge the object-
substitution account of OSM. However, none of these studies directly tested the impact of
endogenous shifts of attention. This is important because some aspects of perception are only
modulated by endogenous shifts of attention (Prinzmetal, McCool, & Park, 2005; Prinzmetal,
Zvinyatskovskiy, Gutierrez, & Dilem, 2009; Rohenkohl, Coull, & Nobre, 2011). This means
that it may be that attention does modulate OSM and consequently that the object-substitution
account can be rescued – but only by endogenous attentional orienting.
Endogenous attentional orienting, in contrast to its exogenous counterpart, is where a
spatial shift in attention occurs voluntarily or with volition – a strategic response to an
informative rather than a salient cue. In the lab, this is typically operationalised as a centrally-
presented stimulus that has above-chance level predictiveness of the location of the
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subsequent target. This form of cueing also operates on longer timescales than its exogenous
counterpart (Carrasco, 2011; Chica et al., 2013; Jonides, 1981; Posner, 1980). Endogenous
attentional orienting is a crucial aspect to consider, because endogenous attentional orienting
has been found to have qualitatively different effects on perception, with some perceptual
benefits emerging exclusively under endogenous attentional orienting conditions. In
particular, endogenous shifts of attention consistently facilitate perceptual processes such as
temporal acuity and texture segmentation, whereas exogenous shifts do not (Hein et al., 2006;
Yeshurun & Carrasco, 1998; Yeshurun & Hein, 2011; Yeshurun & Levy, 2003; Yeshurun,
Montagna, & Carrasco, 2008). More broadly, it has been suggested that only endogenous
attentional orienting is able to improve perception, rather than just facilitate response
efficiency, which is the outcome of exogenous attentional orienting (Prinzmetal et al., 2005;
Prinzmetal et al., 2009). This highlights the possibility that endogenous attention may
uniquely be able to facilitate the perceptual process that is object-individuation, thereby
reducing masking.
Therefore, in the present study, the effect of endogenous attentional orienting on
object-individuation was examined. A standard OSM array was used, and to operationalise
endogenous attentional orienting, a centrally-presented cue that was 75% predictive of the
location of the target was employed. In Experiment 1, this was an arrow pointing to the left or
right, and in Experiment 2, a colour cue was used instead. Masking magnitude was compared
on for valid trials (where the cue correctly predicted the location of the target) versus invalid
trials (where the cue did not predict the location of the target). If endogenous attention and
object-individuation processes interact, then masking magnitude should be reduced for the
valid compared with the invalid trials. In contrast, if the endogenous attention and object-
individuation processes do not interact, then masking magnitude should be equivalent for the
valid and invalid trials.
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Experiment 1
Method
Participants. Thirty participants were recruited for the experiment. This sample size
was pre-determined on the basis of a power analysis that corrects for publication bias
(Anderson, Kelley, & Maxwell, 2017). This was done using the two-factor repeated-measures
ANOVA Shiny App calculator that accompanies the article by Anderson et al. (2017). This
calculator requires the following information: (a) an observed F-value from a previous study
from (b) a given sample size, for a design with (c) specified number of levels for each factor
in the design, (d) alpha level for the previous study, (e) alpha level for planned study, and (f)
assurance value, and (g) desired level of statistical power for the planned study (see Anderson
et al., 2017, for more information). Here, the F value and N (39) were entered from a
previous study that examined the interaction between attentional breadth and OSM, which
had two factors each with two levels (Goodhew & Edwards, 2016), like the current study.
This previous study showed significant main effects of both the attended-region size and
mask duration factors, and to adopt a conservative approach to ensure adequate power, the
smaller of these two F-values was selected (12.1) for the power calculations here. Alpha level
for both the previous and current study were set at .05. Assurance was set to 0.5 (which
corrects for any publication bias in previously-obtained effect sizes) and power to 0.8.
From this, it was calculated that a sample size of 30 was required to have 80% power to
detect the smaller of the two main effects in Goodhew and Edward’s (2016) Experiment 1.
All participants in this and the following experiment provided written informed consent prior
to participation. The experimental protocol was approved by ANU’s Human Research Ethics
Committee (protocol number 2017/565).
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Demographic data was not available for one participant. For the remaining participants,
the mean age was 21.6 years (SD = 2.3). Eighteen participants reported their gender as
female, 11 as male. Twenty-five reported being right-handed, 3 left-handed, and 1
ambidextrous. Ten participants were born in China, eight in Australia, four in Malaysia, two
in India, and one in each of: New Zealand, Indonesia, Japan, South Korea, and Russia1.
Stimuli & Apparatus. The experiment was run on a 21.5” screen iMac computer with a
refresh rate of 60Hz (and so all stimulus durations are in intervals of 16.67ms). Viewing
distance was fixed at approximately 60cm by means of a chin-rest. The stimuli were
generated and displayed via the Psychtoolbox in Matlab (Brainard, 1997). The cue was a
double-headed arrow presented in the centre of the screen, pointing either to the left or right
(<< or >>). The target was the capital letter ‘E’ or ‘F’, presented approximately 3 of visual
angle to the left or right of the centre of the screen (see Figure 1). Both the cue and target
were presented in size 20 Helvetica font. Each individual dot of the four-dot mask subtended
about 0.3, and they were arranged in a square centered on the target letter, where each side of
the square was about 1. The cues were black [0 0 0], the targets and four-dot mask were dark
grey [55 55 55] while the background of the screen was set to mid-grey [128 128 128].
Procedure. Participants were tested individually and completed two conditions:
Cueing Only Condition, and the Cueing and OSM Condition (order counterbalanced across
participants). The former was included as a check that cueing effects were obtained in a
standard cueing arrangement, whereas the latter directly assessed the interaction between
cueing and OSM.
In the Cueing Only Condition, on each trial, the arrow cue was presented for 300ms.
Next, the target appeared until a response was registered. Participants’ task was to identify
the target letter (as E or F) by pressing the corresponding key on the keyboard. Participants
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were instructed to respond as quickly and accurately as possible. Accuracy was recorded to
ensure compliance with task instructions, but it was expected that response time on correct
trials (RT) would be the primary source of variation.
In the Cueing and OSM condition, on each trial, the arrow cue was presented for 300ms.
Next, the target appeared, surrounded by the four-dots mask, was presented for the target
duration. Then the cue and target disappeared. On simultaneous mask offset trials, the mask
also disappeared at the same time as the cue and target, and the screen was then blank until a
response was registered, whereas on the delayed mask offset trials, the mask alone was
presented for 200ms before this happened. Participants were instructed to identify the target
letter (as E or F) by pressing the corresponding key on the keyboard. Accuracy of response
was emphasised (not speed). Here, therefore, accuracy was the dependent variable.
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Figure 1. An illustration (not to scale) the trial structure in the Cueing and OSM condition in
Experiment 1. This represents a valid trial, since the direction of the arrow correctly predicts
the location of the target. Target duration was determined by participant performance during
practice (see below). This depicts a delayed-mask offset trial, on a simultaneous offset trial,
the screen would be blank after the target disappeared (i.e., 0 ms trailing mask).
For both the Cueing Only and the Cueing and OSM conditions, the validity of the cue
was randomised such that there was a 75% probability of it being valid on a given trial. The
two levels of each of the variables of target identity (E or F), target side (left or right), and for
the Cueing and OSM condition, mask offset condition (simultaneous or delayed mask offset)
occurred on exactly 50% of trials, and were fully crossed and randomly intermixed. Whether
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the cue was pointing left or right was constrained on each trial by the validity and target side
variables. Both conditions had a blank inter-trial interval of 1000ms. The Cueing Only
condition consisted of 200 trials (100 per validity), whereas the Cueing and OSM condition
consisted of 400 trials (100 per combination of validity and mask offset condition).
Participant-paced rest breaks were offered to the participant at 25%, 50%, and 75% of the
way through the number of trials in each condition.
For both conditions, participants first completed a practice block to familiarise them with
the task, where on-screen accuracy of the response was provided on each trial (whereas it was
not in the main experiment). For the Cueing Only condition, the practice block consisted of
four trials, and participants were required to respond correctly on three of the four trials to
progress to the experiment (instructions clarified and practice repeated, if required). For the
Cueing and OSM condition, the purpose of the practice was not only task-familiarity, but also
to gauge an appropriate target presentation time tailored to each individual participant to
mitigate against floor or ceiling effects contaminating the data. The practice block for this
condition therefore contained 50 trials. To facilitate familiarity with the more briefly-
presented stimuli, the target presentation time began at 10-times the final presentation
duration (i.e., 330ms) for trials 1 and 2, 5-times the final presentation duration (i.e., 165ms)
for trials 3 and 4, 2-times the final presentation duration (i.e., 66ms) for trials 5 and 6, and
then 33ms from trial 7 through to trial 50. In a two-alternative forced-choice task as per this
experiment, the level of performance most sensitive to detecting changes (i.e., least affected
by floor/ceiling) is 75%. Hence, if after 50 trials, participants scored greater than or equal to
85% accuracy, they were assigned to a quicker target duration (17ms) for the experiment
proper. If they scored less than 85% but greater than or equal to 65%, they remained at the
33ms target duration. If they scored less than 65%, they were assigned to a 50ms target
duration.
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Results & Discussion
Raw data for both experiments is publicly available (see https://osf.io/gdpxy/). Trials
were excluded as invalid where either: (a) participants pressed a key other than one of the
designated response keys in either condition, or (b) response time in the Cueing Only block
was too rapid to reflect genuine responding (<100ms) or too slow to reflect compliance with
the instruction to respond as quickly and accurately as possible (>2.5 SDs above participant’s
mean RT). This led to an average of less than 3% of trials being excluded in the Cueing Only
block, and less than 1% in the Cueing and OSM condition.
In the Cueing Only condition, participants’ mean accuracy was high, and did not
significantly differ between the Valid (93%) and Invalid (94%) conditions, as revealed by a
repeated measures t-test (t < 1). Participants’ mean RT on correct-response trials was
significantly faster in the Valid (499ms) than the Invalid condition (520ms), t(29) = 3.89, p
= .001. This shows that the cueing procedure was effective in a standard RT-based cueing
paradigm. These results were unchanged (i.e., results stayed significant / non-significant)
irrespective of whether or not a participant who performed below chance-level accuracy in
the Cueing Only condition was included.
Average accuracy in the Cueing and OSM condition was 72%. As can be seen in
Figure 2, there was a clear validity effect, whereby valid trials (left two bars) produced higher
accuracy than invalid trials (right two bars). There were also masking effects, whereby
accuracy was higher in the simultaneous offset condition (yellow bars) than the delayed mask
offset conditions (blue bars). This was true for both valid and invalid conditions, and
crucially, it appears that the masking effect was equivalent for the valid versus invalid
conditions (i.e., no interaction).
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The statistics confirm the pattern apparent in Figure 2. The accuracy data was
submitted to a 2 (Validity: Valid, Invalid) x 2 (Mask Offset Condition: Simultaneous,
Delayed) repeated-measures ANOVA. This revealed a significant main effect of Validity,
F(1, 29) = 16.31, p < .001, p2 = .360, such that accuracy was greater in the Valid (74%)
versus the Invalid condition (69%). This illustrates that participants oriented their attention in
response to the cue, and that this impacted their overall perceptual performance. There was
also a significant main effect of Mask Offset condition, F(1, 29) = 9.84, p = .004, p2 = .253,
such that accuracy was higher in the Simultaneous Offset Condition (73%) compared with
the Delayed Mask Offset Condition (70%). This reveals that OSM was present. The
interaction between Validity and Mask Offset Condition was not significant, F(1, 29) = .024,
p = .877, p2 = .001. This means that despite the fact that endogenous attentional orienting
and masking each impacted accuracy in their own right, these effects were impervious to one
another. That is, the magnitude of masking did not change as a function of whether
endogenous attention was applied to the target or not, in fact, the effect size for the
interaction approached zero.
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Figure 2. An illustration of the results of Experiment 1. Error bars are standard errors
corrected for within-subjects designs (Cousineau, 2005).
For the Cueing and OSM condition, it is important that any potential interaction
between an attentional manipulation and OSM does not reflect an artefact of floor or ceiling
effects. While titrating target exposure duration tailored to each participant was the primary
means of ensuring this, five participants’ datasets were in the range where accuracy was
potentially approaching floor (four with <60% average accuracy) and ceiling (one with >90%
average accuracy). Therefore, the above analysis was repeated with these five datasets
excluded. For the remaining 25 participants, mean accuracy for the group in the Cueing and
OSM condition was 74% - right in the most sensitive range, away from floor (50%) and
ceiling (100%). For this group, the above results replicated (i.e., significant main effects of
Validity and Mask Offset condition, and no interaction (F<1)). This demonstrates that the
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absence of an interaction was not artifactually induced by the constraints of floor or ceiling
effects.
In this experiment, there was a notable lack of interaction – the effect size approached
zero. However, to check that the smallish masking effect (~3%) had not constrained the
power of the interaction, an additional analysis was performed in which participants with
masking effects (difference in accuracy between Simultaneous and Delayed Mask Offset
Conditions) at or below zero were excluded. This left 22 datasets for analysis. This sample
had an average masking effect twice as large (6%). The same repeated-measures ANOVA as
above revealed a significant main effect of Validity, F(1, 21) = 9.56, p = .006, p2 = .313, and
a highly significant main effect of Mask Offset Condition, F(1, 21) = 52.27, p < .001, p2
= .713. However, the interaction was still not significant, F(1, 21) = 2.38, p = .138, p2 = .102.
Since the key result here is an absence of an interaction between two variables, a
Bayesian analysis was also performed to determine whether there was evidence in favour of
the null hypothesis. That is, these 22 datasets were subjected to a Bayesian analysis with the
default priors in JASP (2018). This revealed a BF10 >20 for Validity, a BF10 >670 for Mask
Offset Condition, and BF10 < 1 for the interaction. These factors represent a ratio of the
amount of evidence in favour of the alternative hypothesis versus the null hypothesis.
Therefore, these can be interpreted as strong and very strong evidence for the alternative
hypothesis for the two main effects respectively, and no evidence in favour of the alternate
hypothesis for the interaction. In fact, since the BF10 <1 for the interaction, this analysis
suggests that there is more evidence in favour of the null hypothesis for the interaction
(Jarosz & Wiley, 2014). In other words, the Bayesian analysis also supports the absence of an
interaction between Validity and Mask Offset condition.
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These results suggest that endogenous attentional orienting and OSM are independent
of one another, rather than interactive. However, before this conclusion can be accepted, an
outstanding issue requires addressing. That is, while historically arrow cues have been
employed as prototypical endogenous cues (Jonides, 1981; Muller & Rabbitt, 1989), it has
since been suggested that there may be some reflexive components (Kuhn & Kingstone,
2009). There are several reasons to think that this was not occurring in Experiment 1, since
(1) the cue duration used in Experiment 1 is sufficiently long to likely preclude exogenous
components, and (2) accuracy was impacted by the cueing procedure in the combined Cueing
and OSM block, whereas it has been suggested that exogenous attentional orienting with
valid and invalid cues only affects RT, whereas endogenous cueing can impact accuracy
(Prinzmetal et al., 2005). However, it is already known that exogenous attention and OSM do
not interact (Pilling et al., 2014), and it is therefore possible that in Experiment 1, that any
such a reflexive component may have overwhelmed the endogenous component to arrow
cues and not allowed for a clean test of the interaction between endogenous attentional
orienting and OSM. Therefore, to be sure, in Experiment 2, a “pure” endogenous attentional
cue was used.
Experiment 2
Here in Experiment 2, a colour cue was used instead of an arrow cue. Since a colour cue,
whose relationship to a spatial location is arbitrary and requires interpretation (unlike an
arrow) would likely take longer to process, a longer cue duration was also employed.
Furthermore, in order to increase masking magnitude, the mask dots were changed from
circles to squares, to match the angularness of the E/F letter targets. This is because OSM is
modulated by the similarity between the target and mask stimuli with respect to colour,
luminance, orientation, and spatial frequency content (Goodhew et al., 2015; Luiga &
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Bachmann, 2008; Moore & Lleras, 2005). It was therefore thought that masking might also
be increased by this form similarity.
Method
Participants. Thirty-two participants were recruited for the experiment. As per
Experiment 1, 30 was calculated as the minimum sample size for power, and 32 were
recruited to finish counterbalancing (with the introduction of an additional variable – which
cue colour was valid to the counterbalancing scheme compared with Experiment 1, please see
Procedure section for more information). Participants’ mean age was 23.1 years (SD = 3.8).
Eleven reported their gender as male, 21 as female. Eight participants were born in Australia,
eight in China, four in India, three in Singapore, two in Malaysia, and one in each of:
Myanmar, Greece, Philippines, Pakistan, South Korea, Russia, and Indonesia.
Stimuli & Apparatus. The stimuli and apparatus for Experiment 2 were identical to
Experiment 1, with the following exceptions. The central cue was now a box, coloured either
orange or purple. It subtended about 1.15. The mask dots were squares rather than circles.
Procedure. The procedure for Experiment 2 was identical to Experiment 1, with the
following exceptions. For both conditions, participants were instructed to orient their
attention based on the colour of the cue. For half of participants, orange indicated left and
purple right, whereas for the other half of participants, purple indicated left and orange
indicated right (counterbalanced across participants, and fully crossed counterbalancing with
order of condition completion). Cue exposure duration was increased from 300ms to 600ms.
For the Cueing and OSM condition, target exposure duration during practice was increased to
50ms. This was done because there were more cases affected by potential floor than ceiling
effects in Experiment 1, suggesting that sensitivity could benefit from a slight increase in
performance. To facilitate this, target duration was increased by one monitor refresh. If
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participants scored greater than or equal to 85% accuracy, they were assigned to the quickest
target duration (33ms) for the experiment proper. If they scored less than 85% but greater
than or equal to 65%, they remained at the 50ms target duration. If they scored less than 65%,
they were assigned to a 67ms target duration.
Results & Discussion
Less than 4% of trials were excluded as invalid from the Cueing Only condition and
less than 0.2% from the Cueing and OSM condition.
In the Cueing Only condition, accuracy was high, and did not significantly differ
between the Valid (96%) and Invalid conditions, (96%), (t < 1). RT also did not reliably
differ between the Valid (515ms) and Invalid conditions (519ms), t(31) = 1.20, p = .241. That
is, cueing did not appear to be evident in the Cueing Only condition. These results were
unchanged by the exclusion of one dataset where there were more than 50% invalid
responses. However, endogenous attentional orienting can produce effects where accuracy
rather than speed is the primary dependent variable, and so the effect of the cue was
examined in the Cueing and OSM condition where accuracy was the dependent variable. (Of
course, there is an accuracy measure here in the speeded block, but this is unlikely to be
modulated due to (by design) ceiling effects on accuracy for speeded task. Instead, accuracy
is only likely to be informative in unspeeded tasks, such as the Cueing and OSM condition).
In the Cueing and OSM condition, average accuracy across conditions was 72%.
Figure 3 illustrates the presence of a validity effect, whereby accuracy was higher for valid
than for invalid trials, and a masking effect, such that accuracy was greater for the
simultaneous mask offset compared with the delayed mask offset conditions. Moreover, the
masking effect was present and equivalent for the valid versus invalid conditions. Consistent
with this, a 2 (Validity: Valid, Invalid) x 2 (Mask Offset Condition: Simultaneous, Delayed)
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repeated-measures ANOVA on target identification accuracy revealed a significant main
effect of Validity, F(1, 31) = 25.25, p < .001, p2 = .449, such that accuracy was higher in the
Valid (78%) than the Invalid (66%) condition. Here, therefore, there is clear evidence that
participants did orient their attention in response to the cue, in contrast to the Cueing Only
condition. There was a significant main effect of Mask Offset Condition, F(1, 31) = 19.45, p
< .001, p2 = .385, such that accuracy was greater for the Simultaneous (74%) versus the
Delayed mask Offset condition (70%). There was no significant interaction between Validity
and Mask Offset Condition, F(1, 31) = 0.33, p = .571, p2 = .010. That is, despite clear
evidence that Validity and Mask Offset condition reliably impacted accuracy in their own
right, they were independent rather than interactive in their effects. Furthermore, even when
cases where average accuracy was <60% or >90% were removed, the main effects remained
significant (ps < .001), and the interaction remained non-significant (F<1).
22
Figure 3. An illustration of the results of Experiment 2. Error bars are standard errors
corrected for within-subjects designs (Cousineau, 2005).
Moreover, an additional analysis was performed in which only participants with
masking effects greater than zero were included (N = 26). This revealed a significant main
effect of Validity, F(1, 25) = 16.45, p < .001, p2 = .397, and a significant main effect of
Mask Offset Condition, F(1, 25) = 42.59, p < .001, p2 = .630. The interaction, however, was
still clearly non-significant, F(1, 25) = 1.07, p = .310, p2 = .041. Finally, a Bayesian analysis
indicated that the BF10 > 400,000 for Validity, BF10 >3 for Mask Offset Condition, and BF10
<1 for the interaction. These can be interpreted as very strong, positive, and no evidence for
the alternative hypothesis respectively (Jarosz & Wiley, 2014). Indeed, the Bayesian analysis
implies greater evidence for the null hypothesis for the interaction. In other words, the
Bayesian analysis supports the conclusion that Validity and Mask Offset condition do not
interact.
General Discussion
Across two experiments it was shown that endogenous attentional orienting and
object-individuation processes were independent of one another. That is, despite clear and
demonstrable evidence that an endogenous cue on the one hand and the OSM manipulation
on the other each impacted perceptual performance in their own right, these effects did not
interact. This provides converging evidence with the existing literature that OSM is
independent of exogenous attentional orienting (Pilling et al., 2014), the number of
distractors in the display (Argyropoulos et al., 2013), the distribution of attention across space
(Goodhew & Edwards, 2016), and executive attentional manipulations (Filmer et al., 2017).
Since in other domains endogenous attentional orienting has produced qualitatively different
patterns of effects compared to exogenous attentional orienting, it was entirely possible that
23
this form of attention would interact with OSM despite the other forms being shown not to.
However, here, this was clearly not the case. This was not a conclusion erroneously
stemming from insufficient power – the current experiments were well powered, and the
effect sizes for the interaction were so minuscule that they approximated zero. Moreover, the
Bayesian analysis provided direct evidence in favour of the null hypothesis for the interaction
term. This indicates that the interaction really was not there to be found.
Two previous studies have attempted to understand the role of endogenous attention
in OSM. The first, Luiga and Bachmann (2007), sought to differentiate exogenous and
endogenous attention and their effects of OSM. Their results appeared to suggest that
endogenous attentional orienting did not modulate OSM. However, there are several
methodological issues that cloud a clear interpretation of this data. One issue is that the
endogenous attentional cue was a central arrow, which has since then been shown to
potentially reflect some exogenous components (Kuhn & Kingstone, 2009). Another issue is
that the key comparison was between a present central cue, versus an absent one. The
presence of the central cue may therefore have provided a temporal alerting/vigilance cue,
independent of any spatial-attentional effect. A more appropriate baseline is the comparison
of two conditions where the cue is present, one where it validly predicts the location of the
target, and the other where it does not. Finally, the small sample size (six participants), which
may have underpowered the study’s ability to find reliable results.
Moreover, the conclusion from Luiga and Bachmann (2007) conflicts with that of a
subsequent study, which claimed that endogenous cueing does modulate OSM (Germeys,
Pomianowska, De Graef, Zaenen, & Verfaillie, 2010). However, the evidence to support this
claim was that the impact of the trailing mask on performance was modulated by the interval
of time between the appearance of an arrow cue and the appearance of the target. However,
once again, any benefit here is likely to have reflected a general alerting effect, rather than a
24
spatial attentional effect. In order to support their claim, the appropriate comparison would
have been between valid versus invalid cueing trials. Moreover, the small sample size (six
participants) again may have underpowered the study, undermining its ability to find reliable
results, and finally, the use of an arrow cue may have conflated exogenous and endogenous
attentional orienting components. In contrast, the present appropriately-powered study
directly compared two conditions where the alerting cues were constant because a cue was
always present, but the cue either did or did not predict the location of the target, thereby
actually manipulating spatial attention, unlike the previous studies (Germeys et al., 2010;
Luiga & Bachmann, 2007). Moreover, critically, a pure endogenous attentional orienting
manipulation, completely separated from any exogenous components, was employed. This
manipulation had a strong effect on visual perceptual performance in general, however, the
results clearly demonstrated that this endogenous attentional orienting did not modulate
OSM.
The absence of an attentional cueing effect on OSM demonstrated in the present study
represents the strongest call for, at a minimum, a revision to the object-substitution account of
OSM. According to this theoretical model, preventing focussed attention on the target was
espoused to be key to how masking arises (Di Lollo et al., 2000). Here, however, it was
shown that even the most powerful and perceptually-impactful form of attention –
endogenous attentional orienting – had no influence on OSM. This poses a serious challenge
to the object-substitution theory. Furthermore, one could even argue that since the role of
attention was central to the object-substitution account, that the present evidence altogether
undermines the merit of the account, to the extent that it should be discarded. In contrast, the
object-individuation account of OSM does not propose a critical role for attention. The
object-individuation account also has an undeniably strong evidence base in its own right (for
25
a review, see Goodhew, 2017). The current study could be taken as evidence to suggest that it
should be considered the sole viable account for the mechanisms underlying OSM.
However, from an alternative perspective, while attention was espoused as a key
mechanism to the object-substitution account, perhaps this aspect of the model can be revised
while the other components remain. The other main aspects of the model are the feedback
mechanism in which re-entrant activity disrupts visual representation, and reduced reliance
on local, inhibitory interactions (relative to other forms of masking, such as metacontrast
masking). If we assume that multiple re-entrant processing loops are required in order to
identify a target even when it is attended, then this mechanism could still potentially explain
OSM for attended targets. However, when the evidence is critically reviewed, re-entrant
processing is specific to neither OSM nor the theory of object-substitution. Notably, there
was a zeitgeist of burgeoning appreciation for re-entrant processing and its importance that
coincided with when the object-substitution account was proposed (Lamme & Roelfsema,
2000; Lamme, Super, & Spekreijse, 1998), which means that the emphasis on this new-found
mechanism was understandable. However, since then, a consensus of evidence informs us
that re-entrant processes are integral to visual processing and visual awareness (Ahissar &
Hochstein, 2004; Bar, 2003; Bullier, 2001; Kveraga, Boshyan, & Bar, 2007; Lamme, 2001;
Laycock, Crewther, & Crewther, 2007; Pascual-Leone & Walsh, 2001; Ro, Breitmeyer,
Burton, Singhal, & Lane, 2003; Sabatinelli, Lang, Keil, & Bradley, 2007; Sillito, Cudeiro, &
Jones, 2006; Silvanto, Lavie, & Walsh, 2005; Tapia & Beck, 2014; Wyatte, Curran, &
O'Reilly, 2012; Zeki, 2001). Indeed, it is now uncontroversial to be the point of being
incontrovertible that re-entrant processing is implicated in visual perception of the target in
OSM, because re-entrant processing is implicated in virtually every aspect of visual
perception, including forms of masking that the proponents of object-substitution have been
at pains to differentiate from OSM, such as metacontrast masking (Ro et al., 2003). It is
26
therefore in no way specific to OSM, but rather a general property of conscious visual
perception. The fact that neural re-entrant processing occurs, therefore, does not provide any
evidential weight to any particular theory of OSM.
Of course, it is worth noting that some recent studies have claimed to support the
object-substitution account, but while this evidence is consistent with the model, it is also
consistent with other models – that it, it is not theory-diagnostic. For example, it has been
found that OSM operates on an all-or-none rather than a graded perceptual basis (Pilling,
Guest, & Andrews, 2019). This could be considered consistent with the object-substitution
account, but such a finding is in no way exclusive to the object-substitution account. For
instance, it is equally true that object-individuation could operate on this basis. This evidence,
therefore, while interesting, does not adjudicate between different theoretical accounts.
The final aspect of the original object-substitution model is more a consequence of the
hypothesised attentional and re-entrant processing mechanisms – that OSM is more
impervious to low-level local inhibitory interactions, compared with more traditional forms
of masking such as metacontrast masking. The major issue with this, however, is that even if
it is true, it does not necessarily derive from other aspects of the theory. That is, many,
diverse hypothesised mechanisms other than that proposed in the theory (e.g., object
individuation processes) could also result in relative insensitivity to such low-level effects.
Therefore, altogether we have some evidence that, while consistent with object-substitution,
does do not give reason to favour this over many other theories, since it is equally consistent
with other models. On the other hand, we have some evidence which directly undermines the
object-substitution account, such as the complete independence of attention and OSM, and
some evidence which directly supports other accounts and not object substitution, such as
featural and episodic similarity between the target and mask modulating masking magnitude
27
(for a review, see Goodhew, 2017). In this light, object-substitution theory frankly does not
offer us much.
Finally, visual attention and object-individuation are both such fundamental visual-
cognitive processes, that it may seem surprising that they do not interact with one another,
especially since visual attention impacts such a diverse array of perceptual processes.
However, there may be functional utility in a system keeping these processes separate. That
is, object correspondence versus object inferences would occur so pervasively in real-world
visual perception – indeed it is an inference that needs to made for virtually every object in a
visual scene. Attentional resources are limited and cannot be focussed on all objects
simultaneously. Therefore, it could be problematic to have object individuation inferences
change according to whether attention is applied an object. Moreover, whether attention is
applied to an object at a given location at a particular point in time may not be informative
about whether it reflects a continuing or a new object in the scene. On the one hand, attention
can track objects over time (Flombaum, Scholl, & Pylyshyn, 2008), but equally voluntary
attention can be applied to features such as onsets indicating new objects appearing (Folk,
Remington, & Wright, 1994). The fact that an object is attended therefore does not diagnose
whether an inference of object correspondence versus object individuation should be reached.
In conclusion, here it was shown that endogenous attentional orienting and inferences
of object-individuation do not interact, but are instead independent of one another. More
specifically, neither an arrow nor a colour endogenous cue modulated OSM magnitude. This
represents the final piece of evidence required to conclude that object-individuation truly is
separable from attentional processes. This, in conjunction with a critical review of decades of
research on different forms of masking and the neural processes that support visual
awareness, raises some serious doubts about the ongoing contribution of object-substitution
theory to our understanding of the dynamics of object perception.
28
29
Notes
1. Previous research has indicated that there may be differences in attentional breadth between
individuals born in East Asia versus Western countries (see supplementary material for
Goodhew & Plummer, 2019; McKone et al., 2010). The effectiveness of attentional cueing
could be compromised if both possible target regions fell within a person’s attentional
breadth. Therefore, in both experiments, results were analysed as a function of participants’
country of birth, which was classified into a dichotomous variable of Eastern (e.g., China)
versus Western (e.g., Australia) country of birth. The main results were unchanged when this
between-subjects variable was included in the analysis, and this variable did not interact with
either main effect or the interaction.
30
Acknowledgements
This research was supported by an Australian Research Council (ARC) Future Fellowship
(FT170100021) awarded to S.C.G. I thank Rani Gupta and Nicholas Wyche for assistance with the
data collection. Correspondence regarding this study should be addressed to Stephanie Goodhew
([email protected]), Research School of Psychology, The Australian National
University.
31
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