S1 (FriAM 1-65) - The Psychonomic Society

Saturday Afternoon Papers 204–209
In Session 2, they described these events to a confederate and listened
as the confederate described similar (scripted) events. They then took
turns to describe the major points of each other’s memories. Crucially,
the confederate slipped positive or negative “contagion items” into
their re-telling of participants’ memories (e.g., “you thought your 18th
birthday would be a major turning point”), which were not part of participants’
original recall. On a final individual test, participants often
incorporated, and even elaborated on, the false information from the
confederate. Such “contagion” highlights the ways in which collaboration
shapes individual remembering, even of memories that we assume
that we “own.”
Models of Recognition Processes
Regency DEFH, Saturday Afternoon, 1:30–3:30
Chaired by Scott D. Slotnick, Boston College
1:30–1:45 (204)
No Recollection in Recollection-Based Paradigms: ROC Analysis
Supports a Continuous (Single-Process) Memory Model. SCOTT D.
SLOTNICK, Boston College (sponsored by Scott D. Slotnick)—The
dual-process model assumes memory is based on familiarity or the
threshold process of recollection, whereas the single-process unequal
variance model assumes memory is a continuous signal detection
process. These models can be tested as the dual-process model predicts
positively curved (U-shaped) source memory z-transformed receiver
operating characteristics [zROCs, plots of z(hit rates) vs. z(false
alarm rates)] and the recently modified unequal variance model predicts
linear or negatively curved (inverted U-shaped) source memory
zROCs. At study, in five source memory experiments, short lists of visual
items were presented to the left or right of fixation. At test, responses
to each item included a spatial location memory confidence
rating (these were used to generate source memory ROCs and
zROCs). Critically, source memory zROCs were negatively curved in
all experiments, opposite in curvature to that predicted by the dualprocess
model and in support of the modified unequal variance model.
1:50–2:05 (205)
Testing the Threshold Nature of Recollection Using a Second-Choice
Procedure. COLLEEN M. PARKS & ANDREW P. YONELINAS,
University of California, Davis—We tested the predictions of various
hybrid models of recognition that assume that recognition relies on a
signal detection familiarity process and a threshold recollection
process. In a four-alternative forced-choice recognition test, subjects
were required to make a recognition response, as well as a second response
in case the first one was wrong. When recognition performance
is dominated by recollection, the models predict little to no relationship
between first- and second-choice accuracy, whereas when
familiarity contributes more to performance the models predict a positive
relationship. As predicted, we found a fairly strong first–second
choice relationship in a test of item recognition, but not in a standard
associative recognition test. Moreover, a modest relationship emerged
in associative recognition under conditions designed to allow familiarity
to provide more substantial support of associative recognition.
These results provide further evidence that recollection is subject to
failure and is therefore well-described as a threshold process.
2:10–2:25 (206)
Controlled and Automatic Retrieval Processes: A New Test of the
Independence Assumption. EDGAR ERDFELDER, MONIKA UN-
DORF, TINA-SARAH AUER, & LUTZ CÜPPER, University of
Mannheim—Dual-process models of recognition memory assume that
both controlled recollection and automatic activation contribute to
memory performance. A largely unresolved issue is whether both
processes are uncorrelated (independence model), positively correlated
(redundancy model), or negatively correlated (exclusivity
model). We present and test the correlated-processes signal-detection
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(CPSD) model, a dual-process measurement model that provides measures
for both processes and the sign of their correlation. We report a
series of experiments designed to test the validity of the model’s memory
and response bias parameters. In addition, we assessed process
correlations in each of the experimental conditions. The results support
the psychological validity of the CPSD model and corroborate the
independence model of controlled and automatic retrieval processes.
2:30–2:45 (207)
Criterion or Distribution Shifts? The Within-List, Strength-Based
Mirror Effect. PHILIP A. HIGHAM, University of Southampton,
HELEN TAM, University of Bristol, DAVIDE BRUNO, University of
Southampton, & TIMOTHY J. PERFECT, University of Plymouth—
A common interpretation of the strength-based mirror effect in recognition
memory is that participants adopt a more conservative old/new
criterion following a strongly encoded list compared to a weakly encoded
list. Furthermore, because participants do not vary their criterion
on an item-by-item basis, the mirror effect is not observed if strength
is varied within a single list. We present data that undermine this general
notion, demonstrating strength-based mirror effects within lists
when the list structure and test labels are appropriate. However, rather
than interpret the results in terms of item-by-item criterion shifts, we
suggest that the underlying distributions are located on different places
on the strength-of-evidence scale. The results are discussed in terms of
two classes of recognition memory models that are compatible with this
distributional account: Differentiation models and multiprocess signaldetection
models incorporating a metacognitive component.
2:50–3:05 (208)
The Relationship Between Old/New and Forced-Choice Recognition
Memory Performance. YOONHEE JANG, JOHN T. WIXTED,
& DAVID E. HUBER, University of California, San Diego (read by
John T. Wixted)—Three models have been advanced to explain asymmetrical
ROCs commonly observed on old/new recognition memory
tasks. The unequal-variance signal-detection (UVSD) model assumes
that recognition decisions are based on a continuous memory strength
process that is governed by two Gaussian distributions. The dualprocess
signal-detection (DPSD) model assumes that recognition decisions
are based either on a threshold-recollection process or on a
continuous familiarity process. The mixture signal-detection (MSD)
model holds that recognition memory decisions are based on a continuous
memory strength process, but the old item distribution consists
of a mixture of two equal-variance Gaussian distributions with
different means. We tested the ability of these three models to predict
two-alternative forced-choice recognition performance based on an
ROC analysis of old/new recognition performance. The UVSD model
explained more variance than either the DPSD or the MSD model. The
UVSD model-based parameter estimates were also more sensible than
those of the other two models.
3:10–3:25 (209)
Modeling Confidence Judgments in Recognition Memory.
ROGER RATCLIFF & JEFFREY J. STARNS, Ohio State University—
A model for confidence judgments in recognition memory that assumes
that evidence for each confidence category is accumulated in
a separate leaky diffusion process is presented. The model makes predictions
for both the accuracy and RT distributions for each confidence
judgment. Stimulus information is assumed to be represented
as a normal distribution of values on a familiarity dimension. Confidence
criteria are placed on this dimension and the accumulation rate
for each response category is determined by the area under the distribution
between the confidence criteria. The model incorporates several
different but identifiable sources of variability which results in
the standard interpretation of the zROC function being no longer
valid. Deviations of the slope from unity reflect both decision criterion
settings across confidence criteria as well as differences in familiarity
distribution standard deviations.