S1 (FriAM 1-65) - The Psychonomic Society

Friday Afternoon Papers 72–78
Visual Search
Regency DEFH, Friday Afternoon, 1:30–3:30
Chaired by Jeremy M. Wolfe
Brigham & Women’s Hospital and Harvard Medical School
1:30–1:45 (72)
Is Pink Special? The Evidence From Visual Search. JEREMY M.
WOLFE, Brigham & Women’s Hospital and Harvard Medical School,
ANINA N. RICH, Macquarie University, ANGELA BROWN &
DELWIN LINDSEY, Ohio State University, & ESTER REIJNEN,
University of Basel—Desaturated red is named “pink.” Other desaturated
colors lack such color terms in English. They are named for objects
(lavender) or, more often, are named using compound words, relative
to the saturated hue (pale green). Does pink have a special
“categorical” status making it easier to find in visual search tasks?
Observers searched for desaturated targets midway (in xyY space) between
saturated and desaturated distractors. Search was faster and
more efficient when saturated distractors and desaturated targets were
in the red range than when they were any other hues. This result was
obtained (1) with items as bright and saturated as possible, (2) when
all items were isoluminant, or (3) when the separation in CIExy from
target to distractors was equated across hues. But is pink really special?
Maybe not. Search remained fast and efficient with a range of
targets that were not categorically “pink” but might be characterized
as skin tones.
1:50–2:05 (73)
Efficient Segregation of Moving and Stationary Objects in Visual
Search. TODD S. HOROWITZ, Harvard Medical School, & ANINA N.
RICH, Macquarie University—How efficiently can the visual system
guide attention to moving or stationary objects? We constructed displays
of two spatially interleaved search sets, composed of randomly
moving and stationary disks. Each set consisted of 4, 8, or 12 gray
disks marked with white lines. Observers were instructed to search for
a vertical line target among distractors tilted ±30º, in either the moving
or the stationary set (blocked). The target could be present or absent
in each set independently. Segregation by motion was highly efficient.
Target-present RTs for both conditions were unaffected by the
number of items in the irrelevant set. However, the irrelevant set was
not completely suppressed; a target in the irrelevant set slowed targetabsent
RTs. Finally, search through randomly moving disks
(21 msec/item) was just as efficient as search through stationary disks
(23 msec/item). The visual system makes optimal use of motion information
in visual search.
2:10–2:25 (74)
The Effect of Task-Irrelevant Objects on Learning the Spatial
Context in Visual Search. ADRIAN VON MÜHLENEN, University
of Warwick, & MARKUS CONCI, LMU Munich—During visual
search, the spatial configuration of the stimuli can be learned when
the same displays are presented repeatedly. This in turn can facilitate
finding the target (contextual cuing effect). This study investigated
how this effect is influenced by the presence of a task-irrelevant object.
Experiment 1 used a standard T/L search task with “old” display
configurations presented repeatedly among “new” displays. A green
filled square appeared at unoccupied locations within the search display.
The results showed that the typical contextual cuing effect was
completely eliminated when a square was added to the display. In Experiment
2 the contextual cuing effect was reinstated by simply including
trials where the square could appear at an occupied location
(i.e., below a stimulus). These findings are discussed in terms of an
account that depends on whether the square is perceived as part of the
search display or as part of the display background.
2:30–2:45 (75)
Different Causes for Attention Interference in Focused and Divided
Attention Tasks. ASHER COHEN & GERSHON BEN SHAKHAR,
12
Hebrew University—Distractors carrying task-relevant information
often affect performance in both focused and divided attention (e.g.,
visual search) tasks. In divided attention tasks it is generally assumed
that task-relevant distractors “capture” attention. There is less agreement
on the cause of interference in focused attention tasks. Typically,
the nature of task-relevant distractors is different in the two paradigms,
rendering a direct comparison difficult. In the present study,
we created a paradigm in which we can compare directly focused and
divided attention tasks, and we use the same type of response-related
distractors for both tasks. Several experiments show that these distractors
interfere with performance in both tasks, but there is a fundamental
difference between the two types of interference. Whereas
response-related task-relevant distractors indeed capture attention in
visual search, attention gradient rather than attention capture causes
interference in focused attention tasks.
2:50–3:05 (76)
Experience-Guided Search: A Theory of Attentional Control.
MICHAEL C. MOZER, University of Colorado, & DAVID BALDWIN,
Indiana University—Visual search data are often explained by the
Guided Search model (Wolfe, 1994, 2007), which assumes visualfield
locations are prioritized by a saliency map whose activity is effectively
a weighted sum of primitive-feature activities. The weights
are determined based on the task to yield high saliency for locations
containing targets. Many models based on this key idea have appeared,
and to explain human data, all must be “dumbed down” by restricting
the weights and/or corrupting the saliency map with noise.
We present a formulation of Guided Search in which the weights are
determined by statistical inference based on experience with the task
over a series of trials. The weights can be cast as optimal under certain
assumptions about the statistical structure of the environment. We
show that this mathematically elegant and parsimonious formulation
obtains accounts of human performance in a range of visual search
tasks.
3:10–3:25 (77)
Not All Visual Memories Are Created Equal. CARRICK C.
WILLIAMS, Mississippi State University—Two experiments investigated
differences in the impact of number of presentations and viewing
time on visual memory for search objects. In Experiment 1, participants
searched for real-world targets (e.g., a green door) 2, 4, 6, or
8 times in a field of real-world conjunction distractors, followed by a
memory test for the presented objects. Visual memory improved
across presentations, but the rate of improvement was unequal for different
object types: Target memory improved more with each presentation
than did distractors. In Experiment 2, eye movements were
monitored while participants searched arrays either 2 or 4 times, followed
by a memory test. The overall memory results replicated Experiment
1. Importantly, regression analyses indicated that number of
search presentations had a large effect on target memory with little additional
impact of total viewing time, whereas the opposite was true
of distractors. Both experiments demonstrate differences in processing
of target and distractor memories.
Judgment and Decision Making
Beacon A, Friday Afternoon, 1:30–3:30
Chaired by John S. Shaw, Lafayette College
1:30–1:45 (78)
Public Predictions of Future Performance. JOHN S. SHAW &
SARAH A. FILONE, Lafayette College—Two experiments tested
whether public predictions about one’s performance on an anagram
task would have an impact on the number of anagrams actually solved.
Before working on two sets of anagrams, 243 participants made predictions
about how many anagrams they would solve in each set. Manipulated
variables included Prediction Privacy (public vs. private)
and Performance Privacy (public vs. private). Consistent with self-