Abstracts 2005 - The Psychonomic Society

Saturday Afternoon Papers 207–213
(IPS), and frontal (FEF) visual cortex exhibited sustained responses
during epochs of voluntary attention to the contralateral visual field.
Furthermore, contralateral target-colored distractors that captured attention
evoked heightened responses within these same cortical areas.
Thus, these regions constitute an array of attentional priority maps
that combine stimulus-driven and goal-directed influences. The degree
to which a given region is influenced by salient image features
or by top-down goals varies continuously from early to late regions of
the visual system.
1:50–2:05 (207)
Native and Supported Mode Processing in Attentional Control Network.
WALTER SCHNEIDER, NICOLE HILL, & MICHAEL COLE,
University of Pittsburgh—In fMRI experiments, we examined attentional
control between frontal cortex (DLPFC) and posterior parietal
cortex (PPC) to establish what functions are native mode (can be done
directly by PPC) and supported mode (requires frontal cortex input).
In a visual line search paradigm, attention was allocated to a single or
multiple locations either exogenously controlled (single pop up) or endogenously
controlled (scan in circular pattern, along diagonal, or single
position). Activity in PPC indicated selective attentional processing.
Exogenous search produced little DLPFC involvement, whereas
endogenous search, diagonal search, and even maintaining attention
on a single position required substantial DLPFC involvement. This
suggests that PPC attentional processing is quite limited and that most
of what we view as voluntary attention is due to external (DLPFC) driving
of attentional control in PPC. This is consistent with the CAP2
model (Schneider & Chein, 2003) and suggests that PPC attention
control requires extensive frontal input.
2:10–2:25 (208)
Anisotropy of Attention Orienting Across the Visual Field. ALEXA
ROGGEVEEN & LAWRENCE M. WARD, University of British Columbia
(read by Lawrence M. Ward)—Voluntary, covert attention enhances
processing of stimuli at attended locations (see Carrasco et al.,
2002). Previous behavioral data have revealed that attentional enhancement
is anisotropic, with more accuracy and speed improvement
in the lower visual field and on the horizontal meridian, and more enhancement
as stimulus eccentricity increases (Carrasco et al., 2001).
Our cue–target experiment expanded these results by mapping attentional
enhancement across the visual field using a different paradigm,
measuring both behavior and event-related potentials (ERPs), and
specifically examining attentional modulations of early sensory ERPs
(Mangun & Hillyard, 1991). Surprisingly, our behavioral results
showed a different anisotropic pattern of attentional enhancement than
has been previously found. Furthermore, we found a problematic lack
of correlation between behavioral and ERP measures of attentional
enhancement at various locations in the visual field. These results will
be discussed in terms of top-down influences on attention allocation
strategies.
2:30–2:45 (209)
Top-Down Control of Visual Attention: A Rational Account.
MICHAEL C. MOZER & MICHAEL SHETTEL, University of Colorado,
Boulder, & SHAUN P. VECERA, University of Iowa—Some theories
of visual attention are premised on the notion of a saliency map
that encodes conspicuous locations in the visual field. Features such
as local color contrast and motion drive the saliency map, and topdown
attentional control modulates the relative contribution of each
feature type. Insight into attentional control comes from studies that
explore repetition priming effects in a sequence of visual search trials.
We interpret priming in these studies as a manifestation of attentional
control adapting to the statistical structure of the environment.
We propose a probabilistic model of the environment that is updated
after each trial. Under the assumption that attentional control operates
so as to make performance more efficient for more likely environmental
states, we obtain parsimonious explanations for data from a
wide range of experiments. Furthermore, our model provides a ratio-
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nal explanation for why the influence of past experience on attentional
control is short lived.
2:50–3:05 (210)
Empirical Tests of a Resource Allocation Model of Hick’s Law. MAR-
IAN E. BERRYHILL & HOWARD C. HUGHES, Dartmouth College
(read by Howard C. Hughes)—Hick’s law (Hick, 1955) states that reaction
times are proportional to the logarithm of the number of response
alternatives. Initial accounts of this relationship in terms of information
theory were quickly recognized as inadequate, and there is
still no comprehensive account of the effects of response uncertainty
on response latency. The present paper presents a resource allocation
model that attempts to account both for Hick’s law and for some previously
reported violations. This account is tested using a dual-task
procedure. The results do not provide direct support for the resource
allocation model, but can be reconciled with a modified version of the
basic ideas behind the model.
False Memory
Grand Ballroom West, Saturday Afternoon, 1:30–3:50
Chaired by Giuliana Mazzoni, University of Plymouth
1:30–1:45 (211)
Intentional Suppression of True and False Memories. GIULIANA
MAZZONI, University of Plymouth—In a cued-recall task of pairs of
unrelated words, target words can be intentionally suppressed by simply
not thinking about them (Anderson & Green, 2000). In other conditions,
asking not to think about an item produces the paradoxical effect of
enhancing its memory (the “white bear effect”). The suppression (think–
no think) procedure was used in a DRM task by asking participants
not to think about words presented in the center of the lists (true memories),
and about critical nonpresented words (false memories). The
procedure was repeated zero, four, or eight times. Results showed that
in the no-think condition, recall and recognition of presented words
increased, but they decreased for critical nonpresented words. The results
reveal one condition in which the same instructions have opposite
effects on true and false memories and are discussed in terms of
the paradoxical ‘white bear’ effect.
1:50–2:05 (212)
Does the d′ Difference for Critical Items and Associates From DRM
Lists Depend on Study Intentionality and Within-List Relatedness?
CHI-SHING TSE & JAMES H. NEELY, SUNY, Albany (read by James
H. Neely)—A person’s ability to discriminate (as indexed by d′) whether
an item was or was not studied in a Deese/Roediger–McDermott (DRM)
study list containing all related items has been shown to be lower for
critical items (CIs; e.g., sleep) than for associates (e.g., blanket). We
find that this “CI memory inferiority effect” occurs to the same degree
whether the CI or associate is studied in a related DRM list or in
a list of totally unrelated words, and whether the CI or associate is
studied under intentional learning conditions or in a shallow, incidental
letter search task. We discuss the implications these results have
for DRM CI versus associate memory differences and for the general
issue of how semantic relatedness of study items affects recognition
memory.
2:10–2:25 (213)
DRM Lists in Experiments About the “Violent Black Man Stereotype.”
BEM P. ALLEN, Western Illinois University—Previous research
on the Web and in the lab has shown that subjects primed with a “violent
man” DRM list (“murderer”) subsequently were more likely to
falsely report “African American” in recollection of entries on an ethnic
names DRM target list (sans “African American”) in comparison
with control–prime conditions (a royalty list and a positive/neutral list
referring to black men). In the present Web experiment, subjects performed
interpolated activities between exposure to prime lists and the
presentation of the target lists. Comparisons were made with the po-