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Dissociating Source Memory Decisions in the
Prefrontal Cortex: fMRI of Diagnostic
and Disqualifying Monitoring
David A. Gallo
1
, Ian M. McDonough
1
, and Jason Scimeca
2
Abstract
■We used event-related fMRI to study two types of retrieval
monitoring that regulate episodic memory accuracy: diagnostic
and disqualifying monitoring. Diagnostic monitoring relies on
expectations, whereby the failure to retrieve expected recollec-
tions prevents source memory misattributions (sometimes
called the distinctiveness heuristic). Disqualifying monitoring
relies on corroborative evidence, whereby the successful recollec-
tion of accurate source information prevents misattribution to
an alternative source (sometimes called recall to reject). Using
criterial recollection tests, we found that orienting retrieval
toward distinctive recollections (colored pictures) reduced
source memory misattributions compared with a control test in
which retrieval was oriented toward less distinctive recollections
(colored font). However, the corresponding neural activity de-
pended on the type of monitoring engaged on these tests.
Rejecting items based on the absence of picture recollections
(i.e., the distinctiveness heuristic) decreased activity in dorsolat-
eral prefrontal cortex relative to the control test, whereas rejecting
items based on successful picture recollections (i.e., a recall-to-
reject strategy) increased activity in dorsolateral prefrontal cortex.
There alsowas some evidence thatthese effects were differentially
lateralized. This study provides the first neuroimaging compari-
son of these two recollection-based monitoring processes and ad-
vances theories of prefrontal involvement in memory retrieval. ■
INTRODUCTION
Episodic memory accuracy is determined by the quality
of the originally encoded information as well as the effec-
tiveness of the monitoring processes engaged during
retrieval. Retrieval monitoring is a general concept, refer-
ring to the various search and decision processes people
use when reconstructing events from memory. According
to the influential source-monitoring framework, numerous
factors influence retrieval monitoring ( Johnson, 2006).
These factors include the types and amounts of retrieved
information, retrieval expectations, and relationships
between past events. Retrieval monitoring is a high-level
cognitive process, and evidence from patient and neuro-
imaging studies indicates that prefrontal brain regions are
critically involved (for reviews, see Pannu & Kaszniak, 2005;
Fletcher & Henson, 2001).
Dozens of fMRI studies have found that regions within
dorsolateral prefrontal cortex (DLPFC), including bilateral
regions along the midfrontal gyrus such as Brodmannʼs
areas (BA) 9, 46, and sometimes 8, are more active for
complex or effortful memory decisions that likely require
retrieval monitoring (Achim & Lepage, 2005; Velanova et al.,
2003; Wheeler & Buckner, 2003; Cansino, Maquet, Dolan, &
Rugg, 2002; Cabeza, Rao, Wagner, Mayer, & Schacter, 2001;
McDermott, Jones, Petersen, Lageman, & Roediger, 2000;
Henson, Shallice, & Dolan, 1999). Moreover, activity within
these DLPFC regions is not specific to memory or to the
materials used, suggesting that these regions support
domain-general monitoring or decisions (e.g., Dobbins &
Han, 2006; Fleck, Daselaar, Dobbins, & Cabeza, 2005).
Some theories maintain that different types of retrieval
monitoring are subserved by different prefrontal regions.
For example, it has been argued that left prefrontal regions
subserve the use of systematic source monitoring pro-
cesses or strategically using specific recollections or contex-
tual information to make a decision. In contrast, it has been
argued that right prefrontal regions subserve heuristic
source monitoring processes or the use of less differen-
tiated information or more vague feelings of familiarity
to make a decision (Nolde, Johnson, & Raye, 1989; see also
Mitchell et al., 2008; Dudukovic & Wagner, 2007; Dobbins,
Simons, & Schacter, 2004; Mitchell, Johnson, Raye, &
Greene, 2004; Ranganath, 2004). A different account
emphasizes right DLPFC in postretrieval monitoring or
the engagement of search and decision processes after
an initial retrieval attempt yields insufficient information
(Lepage, 2004; Henson et al., 1999; for a review, see Rugg,
2004). To the extent that systematic processes involve post-
retrieval monitoring, this emphasis on right DLPFC con-
flicts with the idea that systematic processes depend on
left DLPFC.
An important aspect in many of these earlier neuro-
imaging studies is that they compared conditions that likely
1
University of Chicago,
2
Northwestern University
© 2009 Massachusetts Institute of Technology Journal of Cognitive Neuroscience 22:5, pp. 955–969
relied on recollection and familiarity to different degrees.
Whereas recollection refers to the conscious recall of in-
formation that was previously associated with a test item,
familiarity refers to a decontextualized feeling that the test
item was earlier encountered (see Yonelinas, 2002). The
main evidence for prefrontal lateralization within the
systematic/heuristic distinction comes from comparisons of
source memory tests, which engage recollection, and item
recognition or recency tests, which can rely more heavily
on familiarity (Mitchell et al., 2004, 2008; Rugg, Fletcher,
Chua, & Dolan, 1999; Nolde, Johnson, & DʼEsposito,
1998). As a result of these comparisons, these lateraliza-
tion effects may have been caused by the differential re-
trieval of recollection and familiarity across tests (Wheeler
& Buckner, 2004; Kensinger, Clarke, & Corkin, 2003), the
different decision processes that might correspond to rec-
ollection and familiarity (Yonelinas, 2002), or other moni-
toring processes that may contribute to source memory
tests.
An fMRI study by Dobbins and Han (2006) attempted
to disentangle some of these factors, holding test items
constant but varying the decision to be made on these
items. They found that bilateral DLPFC and frontopolar
activity increased with the number of subprocesses re-
quired to make the test decision, but not with the level
of supporting evidence in memory (also see Hayama,
Johnson, & Rugg, 2008; Rajah, Ames, & DʼEsposito, 2008).
The exact nature of the decision rules used in these tasks
as well as the degree that they may have relied on recol-
lection and familiarity is unclear. Nevertheless, these stud-
ies raise the intriguing possibility that DLPFC regions are
mostly sensitive to the nature and complexity of the deci-
sion rules used during memory tests, as opposed to the
actual information retrieved. Building on this idea, the
current experiment investigated two well-characterized
recollection-based monitoring processes.
Diagnostic and Disqualifying Monitoring
Diagnostic and disqualifying monitoring refer to two
types of recollection-based retrieval monitoring that re-
duce false recognition and source misattributions across
a variety of memory tasks (Gallo, 2004; for a review see
Gallo, 2006). This dichotomy is intended to highlight
qualitative differences in the logic of the underlying deci-
sion process. Diagnostic monitoring involves searching
memory for recollections that are expected to be charac-
teristic of a particular type of event, context, or target
source (e.g., studying items as words or as pictures). If
the test item passes these recollective criteria, then it is
attributed to the target source; otherwise, it is rejected as
having occurred in that source. This process underlies
many source monitoring biases, such as the “it-had-to-
be-you”effect (e.g., Marsh & Hicks, 1998; Johnson, Raye,
Foley, & Foley, 1981) as well as the distinctiveness heu-
ristic that has been demonstrated in false recognition
tasks (e.g., Ghetti, 2003; Dodson, Koutstaal, & Schacter,
2000; Schacter, Israel, & Racine, 1999). A subject reject-
ing a test item based on the distinctiveness heuristic
might reason, “This item is familiar, but I donʼt have a
distinctive recollection. Because the target source elicits
distinctive recollections, it probably wasnʼt studied in
that source.”Note that diagnostic monitoring does not
always rely on distinctive features, but expecting distinc-
tive features can make the monitoring process more
accurate, thereby reducing memory distortion.
Disqualifying monitoring involves searching memory
for recollections that are not diagnostic of the target
source but nevertheless can strategically inform or corrob-
orate whether the item had occurred in that target source.
This process often occurs when the participant believes
that the different types of studied items or sources are
mutually exclusive. In these situations, if the test item is
recollected as having occurred in the nontarget source,
then it is rejected as having occurred in the target source.
This process underlies many source-based exclusion pro-
cesses (e.g., Jacoby, Jones, & Dolan, 1998) as well as many
recall-to-reject processes that have been found in false re-
ognition tasks (e.g., Lampinen, Odegard, & Neuschatz,
2004; Brainerd, Reyna, Wright, & Mojardin, 2003; Rotello
& Heit, 2000; Hintzman & Curran, 1994). A subject using
a recall-to-reject strategy might reason, “This item is famil-
iar, but I recollect that it was studied in the nontarget
source. Because the sources were mutually exclusive, it
couldnʼt have been studied in the target source.”Disquali-
fying monitoring can occur for multiple types of informa-
tion, including the source of an item as well as other
features associated with an item, as long as the studied
events are structured in such a way that the retrieval of
one type of information logically excludes another from
having occurred.
Gallo, Cotel, Moore, and Schacter (2007) demon-
strated both diagnostic and disqualifying monitoring
using the criterial recollection task. Subjects studied a list
of common object labels in black font. Each label was
paired with the same word in red font or with a colored
picture of the corresponding object. Memory then was
tested using black labels as retrieval cues. On the red
word test, subjects responded “yes”if they recollected
a red word, whereas on the picture test, they responded
“yes”if they recollected a picture. Importantly, some test
items had been paired with both a red word and a picture
at study. Because these study formats were not mutually
exclusive, noncriterial recollections were relatively un-
informative (e.g., picture items on the red word test).
Subjects instead had to selectively search their memory
for the to-be-recollected (or criterial) information (e.g.,
red word items on the red word test) using diagnostic
monitoring processes. Under these conditions, source
memory confusions were lower on the picture test than
on the red word test. Subjects expected more distinctive
recollections on the picture test, and these retrieval ex-
pectations enhanced diagnostic monitoring accuracy
(the distinctiveness heuristic). Gallo et al. also included
956 Journal of Cognitive Neuroscience Volume 22, Number 5
a condition where the study formats were mutually exclu-
sive, thereby allowing the use of a disqualifying monitor-
ing process (e.g., rejecting items on the red word test by
recollecting a picture). As predicted, source memory con-
fusions were further reduced in this exclusion condition.
A handful of fMRI studies are relevant to these specific
monitoring processes. Gallo, Kensinger, and Schacter
(2006) used the nonexclusive conditions of the criterial
recollection task to investigate the neural correlates of
diagnostic monitoring in the absence of a recall-to-reject
strategy. They found that studied items on the red word
test were more likely to activate regions in bilateral
DLPFC relative to these same items on the picture test.
Because red word recollections were relatively less dis-
tinctive than picture recollections, it was argued that
subjects needed to engage more effortful retrieval moni-
toring on the red word test, thereby increasing activity in
DLPFC (for related ERP results, see Budson et al., 2005;
for related patient results, see Hwang et al., 2007). Said
differently, the DLPFC was less likely to be recruited when
subjects monitored memory for distinctive picture recol-
lections (i.e., the distinctiveness heuristic). Woodruff,
Uncapher, and Rugg (2006) also found greater activity in
bilateral DLPFC when subjects were tested for words com-
pared with pictures. These effects were sustained across
the retrieval blocks, potentially reflecting the adoption of
different retrieval orientations (analogous to a distinctive-
ness heuristic). However, the study formats were mutually
exclusive in this study, potentially implicating a recall-to-
reject strategy as well.
A few fMRI studies are more directly relevant to disqual-
ifying monitoring. Rugg, Henson, and Robb (2003) and
Henson et al. (1999) both found elevated bilateral DLPFC
activity when the test required a source-based exclusion
strategy compared with item recognition tests in which
all studied items were to be accepted (for relevant ERP
findings, see Fraser, Brisdon, & Wilding, 2007; Herron &
Rugg, 2003). These results suggest that DLPFC is recruited
when subjects use a recall-to-reject process, potentially
reflecting the application of a rule-based rejection strategy.
However, these differences may have reflected a differ-
ential reliance on recollection and familiarity across the
tests, as opposed to the monitoring process itself. Using
a conjunction-word task, McDermott et al. (2000) found
greater activity in bilateral DLPFC when subjects rejected
lures that could have benefited from a recall-to-reject strat-
egy, relative to control lures or studied targets (for analo-
gous results in an associative-recognition task, see Achim
& Lepage, 2005). Unlike the targets, though, each lure cor-
responded to the rearrangement of two different studied
items in these tasks, so these activity differences may have
been due to differences in retrieval success as opposed to
monitoring processes.
To summarize, only a handful of neuroimaging stud-
ies have investigated different types of retrieval monitor-
ing. With respect to disqualifying monitoring, fMRI
studies have shown elevated DLPFC activity (as well as
other PFC regions) when subjects reject items based on
a recall-to-reject strategy. These findings are consistent
with the idea that recollection-based retrieval monitoring
is a type of cognitive control that relies on DLPFC. In con-
trast, only one fMRI study has attempted to isolate diag-
nostic monitoring (Gallo et al., 2006), and this study
found decreased DLPFC activity associated with the use
of a distinctiveness heuristic. To the extent that the dis-
tinctiveness heuristic is considered a recollection-based
monitoring process or even a metacognitive strategy that
can be turned “on”or “off”(cf. Schacter & Wiseman,
2006; Dodson et al., 2000), the finding that this process
reduced DLPFC activity may seem at odds with the idea
that recollection-based monitoring depends on DLPFC.
However, if the distinctiveness heuristic is instead con-
ceptualized as one instance of a more general diagnostic
monitoring process, a process that occurs whenever one
searches memory for recollections, these findings can
be reconciled with prior research. From this perspective,
diagnostic monitoring is critically dependent on the
DLPFC, but the degree to which diagnostic monitoring
is recruited on any test depends on the relative distinc-
tiveness of the to-be-retrieved information. By defini-
tion, distinctive representations are more vivid and more
easily discriminated in memory, requiring less effortful
diagnostic monitoring and leading to less recruitment of
DLPFC.
Current Experiment
For the current experiment, we modified the task used by
Gallo et al. (2007) to directly compare diagnostic and dis-
qualifying monitoring. No prior fMRI study has compared
these two monitoring processes, but doing so provides a
more direct test of the theoretical framework described
above. Prior work investigating these processes has relied
on different types of tasks and different types of to-be-
remembered materials. Thus, the degree that the different
patterns of neural activity observed reflects the use of
two different retrieval monitoring processes, as opposed
to other differences between the experiments, cannot
be ascertained. The current task avoids these issues by
using the same type of to-be-remembered materials (i.e.,
pictures) for each of the recollection-based monitor-
ing processes (i.e., the distinctiveness heuristic and the
recall-to-reject processes) and also by controlling for possi-
ble familiarity confounds. By comparing these processes
in a single task, the current experiment also afforded a test
of the functional lateralization ideas that have been pro-
posed within the source monitoring framework and the
postretrieval monitoring theory, as described below.
To investigate diagnostic monitoring, we compared
the red word test and picture test under nonexclusive
conditions. These conditions required subjects to selec-
tively recollect a single source of information, differing
only in the relative distinctiveness of the to-be-recollected
Gallo, McDonough, and Scimeca 957
information (pictures > red words). Based on Gallo et al.
(2006), we expected that DLPFC would be more active on
the red word test relative to the picture test, indicating
more effortful diagnostic monitoring. This earlier study
found activity in bilateral DLPFC, but unlike that study,
we more precisely equated familiarity across the stimuli
in the current study. Thus, any observed laterality effects
would be more interpretable in terms of the underlying
recollection-based monitoring process. According to the
postretrieval monitoring theory, effortful diagnostic moni-
toring situations should recruit right DLPFC more than
left DLPFC (consistent with the earlier finding). Predictions
based on the systematic/heuristic distinction are less clear
in this case because this dichotomy is more general
and descriptive. The simplest prediction is that the pic-
ture test should recruit right DLPFC more than the red
word test because the picture test relies more heavily on
heuristic-based responding (the distinctiveness heuristic),
although other interpretations are possible (discussed
later).
To investigate disqualifying monitoring, we compared
the red word test to an exclusion test. Like the red word
test, subjects responded “yes”to red words on the exclu-
sion test. Unlike the red word test, we did not include
test items that were studied in both formats so that sub-
jects could use an exclusion-based rejection rule (i.e., re-
jecting test items that elicit picture recollections). We
expected that DLPFC would be more active when sub-
jects engaged in such a recall-to-reject process, but later-
alization theories result in contrasting predictions. The
systematic/heuristic distinction predicts that the exclu-
sion strategy would elicit more activity in left DLPFC than
in right DLPFC because this is a more systematic rule-
based process. In contrast, the postretrieval monitoring
perspective predicts greater activity in right DLPFC. Only
the exclusion test required subjects to monitor memory
for multiple types of recollections, thereby requiring the
most postretrieval monitoring.
METHODS
Subjects
For the imaging experiment, 27 students at the University
of Chicago participated for $40 (18–36 years, 16 women,
all right-handed and fluent in English). Behavioral and
imaging data from six subjects were excluded, owing to
excessive head movement or other technicalities or an
insufficient number of behavioral responses. Before the
imaging study, 18 subjects participated in a behavioral
pilot (not reported). For the manipulation check experi-
ment, 13 students participated for course credit or $10,
with data from one student replaced for failure to pay
attention at encoding. MRI subjects were prescreened
using standard safety procedures, and all subjects gave in-
formed consent.
Materials
Stimuli were drawn from Gallo et al. (2006) and included
360 colored pictures of common objects (e.g., lemon,
toaster) on a white background and corresponding ver-
bal labels in red font. Each study trial began with a black
word (500 msec), immediately followed (100 msec) by
the same word in larger red letters (1200 msec) or the
corresponding picture (1200 msec), with a 150-msec
ISI. At test, a 6-sec prompt cued the retrieval demands
of the upcoming test block (Red Word, Picture, or Exclu-
sion). Verbal labels (black font on white background)
were used as retrieval cues, along with a test prompt to
keep subjects on task (“red word?”for the Red Word test,
“picture?”for the Picture test, and “red word only?”for
the Exclusion test). Twelve scripts were created to coun-
terbalance the stimuli, across subjects, through the item
conditions (studied as red word, picture, both, or non-
studied) and test conditions (Red Word, Picture, Exclusion).
After the initial counterbalancing was met, the remaining
subjects were arbitrarily assigned.For ease of viewing, stim-
uli were projected onto a mirror above the head coil.
Criterial Recollection Procedure
Subjects first completed a practice version of the task,
using separate stimuli, to ensure that they understood
the instructions (approximately 6 min). For the main ex-
periment, the study phase occurred outside the scanner
(approximately 25 min). Subjects studied 240 red words
and pictures for the upcoming tests (90 red words, 90 pic-
tures, and 60 both items, presented as both red words and
pictures, nonconsecutively). Each red word and picture
was presented twice, nonconsecutively (including those
corresponding to both items). Subjects were instructed
to make a semantic judgment for each red word (“Is this
item made in a factory?”) and focus on the perceptual fea-
tures of each picture. To avoid carryover effects of these
orienting tasks, subjects studied alternating blocks of red
words and pictures, with stimuli randomized within each
block and order counterbalanced across subjects. Pilot
work indicated that these study presentation procedures
would equate the familiarity of the test words across
the red word and picture conditions while maintaining
differences in recollective distinctiveness (pictures > red
words).
The test phase occurred in the scanner, following ap-
proximately 20 min of preparation. The tests were divided
into three runs of functional scans (approximately 10 min
per run). Each run was subdivided into three test blocks,
corresponding to each of the three types of test, separating
each block by 21sec of fixation. Test block order was varied
across runs and counterbalanced across subjects. During
each test block, subjects saw 10 test words correspond-
ing to each type of studied item (red word, picture, both,
or new), except that the both items were replaced with 10
additional new items on the exclusion test blocks. Test
958 Journal of Cognitive Neuroscience Volume 22, Number 5
words were presented for 3 sec and separated by a central
fixation cross of jittered duration (3, 6, or 9 sec, mean
SOA = 3.83 sec). The order of items and fixations was arbi-
trarily mixed using a program to maximize the MR signal
(e.g., Dale, 1999). In total, there were 30 items of each criti-
cal type (red words, pictures, new) on each of the three
tests, with 30 filler items also included to manipulate the ex-
clusion demands (30 both items on the Red Word and Pic-
ture tests, 30 additional new items on the Exclusion test).
Test responses were made with the index (“yes”) and
middle (“no”) fingers of the right hand, whereas the test
word was on the screen. On the Red Word test, subjects
pressed “yes”if they remembered studying a correspond-
ing red word (i.e., red word and both items) and “no”if
not, regardless of whether they remembered a corre-
sponding picture (i.e., picture and new items). On the
Picture test, subjects pressed “yes”if they remembered
studying a corresponding picture (i.e., picture and both
items) and “no”if not, regardless of whether they re-
membered a corresponding red word (i.e., red word
and new items). For these nonexclusion tests, it was
emphasized that some items were studied in both for-
mats so that the recollection of one format (e.g., a pic-
ture) did not preclude presentation in the other format
(e.g., a red word). Instead, subjects were instructed to fo-
cus only on whether they could recollect the to-be-
remembered format (a diagnostic monitoring process).
On the Exclusion test, they were to press “yes”if they re-
membered studying a corresponding red word and “no”
if not. It was emphasized that both items would not be
included on this test so that red word and picture items
were mutually exclusive. Thus, if they recollected a pic-
ture on the exclusion test, they could be sure that the
item was not associated with a red word at study (a dis-
qualifying process).
Manipulation Check Procedure
The manipulation check experiment was conducted inde-
pendently from the fMRI study and used several proce-
dures to measure recollection and familiarity. The study
phase for the manipulation check experiment was identical
to the fMRI experiments except there was no practice
phase. The test phase immediately followed and was di-
vided into three test blocks. Each block contained a subset
of the red words, pictures, and new items. Both items were
not relevant to the purpose of this study, but because we
used the same materials as in the fMRI study, we arbitrarily
included them on the first and last test blocks.
The first block contained a speeded recognition test,
on which subjects responded “yes”to studied items
and “no”to nonstudied items, independent of whether
they recollected a red word or a picture. Responses were
speeded using prompts to establish a tempo (Balota,
Burgess, Cortese, & Adams, 2002), yielding an average
response latency of 688 msec (SD = 24.6 msec) that
should primarily reflect familiarity-based recognition (cf.
Yonelinas, 2002). The second block was a self-paced sub-
jective test, on which subjects responded “actually recol-
lect”if they remembered a red word or picture from
study, “very familiar”if they thought the item was studied
but could not recollect the format, and “new”if they
thought the item was nonstudied. The third block also
was a self-paced subjective test, on which subjects rated
the level of strength and details that they could recollect
for each test item (using a 0–7 scale). The recollection
strength index was designed to capture overall differ-
ences in memory strength (ranging from “no recollec-
tion”to “strong or vivid recollection”). The recollection
details index was designed to capture the amount of
unique or distinctive details that could be recollected
(ranging from “no details”to “many details”). We were
primarily interested in recollective distinctiveness, but
we had subjects make a separate “strength”and “details”
judgment to help clarify the difference (see McDonough
& Gallo, 2008).
Neuroimaging Procedure
Images were acquired using a 3-T GE Signa scanner at the
University of Chicago Brain Research Imaging Center.
Functional images were acquired using a T2*-weighted
gradient-echo spiral in/out pulse sequence (repetition
time = 3 sec, echo time = 28 msec, field of view =
240 mm; flip angle = 80 degrees, matrix size = 64 ×
64, in-plane resolution = 3.75 mm). For whole-brain cover-
age, 30 interleaved sagittal slices (4.8-mm thickness,
0.5-mm skip) were acquired. Three event-related func-
tional runs were used for the memory tests, followed by
two functional localizer runs (not reported here), and an
anatomical scan using a T1-weighted multiplanar rapidly
acquired gradient-echo sequence. All preprocessing and
data analysis were carried out using SPM5 (Wellcome
Department of Cognitive Imaging Neuroscience, London),
as implemented in MATLAB 7.4.0 (The MathWorks Inc.,
Natick, MA). Standard preprocessing was performed on
the functional data, including slice-timing correction rela-
tive to the second (middle) slice, realignment using rigid
body motion correction, anatomical coregistration, nor-
malization to the MNI template (resampling at 3-mm cubic
voxels), and spatial smoothing (using an 8-mm FWHM
isotropic Gaussian kernel).
For each participant, an event-related analysis was first
conducted on a voxel-by-voxel basis, in which all instances
of each event type were modeled through convolution
with a canonical hemodynamic response function locked
to event onset times. Event types reflected a combination
of the test condition (Red Word, Picture, Exclusion), the
item type (both, red word, picture, new), and the partici-
pantʼs response (yes, no). All participants had at least 10
instances of each event type included in the analyses.
Modeling proceeded in two levels, an individual subject
Gallo, McDonough, and Scimeca 959
analysis using the general linear model (including the canon-
ical HRF and the temporal derivatives, a 128-sec high-pass
filter, and session effects) followed by a pooled analysis with
subjects as the random effect. The most significant voxel
within a cluster is reported in Talairach coordinates, along
with the approximate BA from the Talairach atlas (Talairach
& Tournoux, 1998) and the Talairach Daemon (Lancaster
et al., 2000).
BEHAVIORAL RESULTS
We first report the results from the manipulation check
experiment, followed by the criterial recollection task used
during the fMRI sessions. All behavioral comparisons were
based on prior work, and unless otherwise specified, all
results were considered significant at p< .05, two-tailed.
Effect sizes for significant comparisons were calculated
with Cohenʼsd.
Manipulation Check
The critical results from the manipulation check are pre-
sented in Table 1. Consistent with our efforts to equate
familiarity across test items, hits to red word items (0.73)
and picture items (0.71) were equated on the speeded
test, t(11) < 1, whereas these items were recognized
more often than new items (0.36), both pʼs < .001. On the
recollect/familiar test, we estimated familiarity using the
independent-remember-know adjustment (see Yonelinas,
2002). Like the speeded test, the difference between red
word items (0.55) and picture items (0.47) was not signifi-
cant with this estimate of familiarity, t(11) = 1.25, SEM =
0.063, p= .24, but each was greater than new items (0.19),
both pʼs < .01. In contrast, the proportion of “actually recol-
lect”judgments was significantly greater for picture items
(0.65) than red word items (0.55), t(11) = 2.98, SEM =
0.033, d= .58, and so too were ratings of unique or distinc-
tive recollective details, 3.19 versus 2.10, t(11) = 2.45, SEM =
0.446, d= .34. Overall, these results confirm that test words
that were associated with pictures at study led to more dis-
tinctive recollections than those associated with red words,
with no differences in familiarity.
Criterial Recollection
The results from the criterial recollection task are pre-
sented in Table 2 and replicate prior work using this task
(e.g., Gallo et al., 2007). Consider the results from the non-
exclusive conditions first. On the red word test, subjects
were more likely to endorse red word items than picture
items (0.62 vs. 0.41), t(20) = 4.07, SEM = 0.052, d=
1.49, whereas on the picture test, subjects were more likely
to endorse picture items than red word items (0.61 vs.
0.19), t(20) = 8.25, SEM = 0.051, d= 2.71. This crossover
pattern indicates that subjects had relied on red word rec-
ollections on the red word test and picture recollections
on the picture test. Recollection was not perfect, though,
and subjects also made source memory confusions to
items that were studied in the noncriterial format. Picture
items were more likely to be falsely recognized than
new items on the red word test (0.41 and 0.27), t(20) =
4.94, SEM = 0.028, d= .81, and red word items were more
likely to be falsely recognized than new items on the pic-
ture test (0.19 and 0.11), t(20) = 3.85, SEM = 0.020, d= .52.
Such familiarity influences also can explain why items stud-
ied in both formats were more likely to be recognized than
items studied in only one format on the red word test (0.70
vs. 0.62), t(20) = 3.02, SEM = 0.026, d= .61, and the picture
test (0.75 vs. 0.61), t(20) = 5.49, SEM = 0.025, d= .90.
Evidence that subjects had engaged in diagnostic moni-
toring comes from a planned comparison of false recog-
nition across the red word and picture tests. Because
pictures elicited more distinctive recollections than red
words, diagnostic monitoring should have been more
effective on the picture test, reducing false recognition
for items that failed to elicit picture recollections (i.e., a
distinctiveness heuristic). Consistent with this prediction,
false recognition of noncriterial items was greater on the
red word test than on the picture test (0.41 and 0.19),
t(20) = 8.03, SEM = 0.028, d= 1.49, and so too was false
recognition of new items (0.27 and 0.11), t(20) = 6.13,
SEM = 0.027, d= .93. Because familiarity was equated
across stimuli, these differences indicate that recollection-
based monitoring was more effective on the picture test
than on the red word test. The fact that these effects were
found for false recognition of red words and new items
on the picture test is consistent with this interpretation
Table 1. Speeded Recognition and Subjective Responses in the Manipulation Check Experiment
Item Type
Speeded Test Recollect/Familiar Test Recollection Quality Test
p, “Yes”p, “AR”p, “VF”IRK Strength Details
Red words .73 (0.04) .55 (0.05) .24 (0.03) .55 (0.08) 4.05 (0.37) 2.10 (0.32)
Pictures .71 (0.02) .65 (0.04) .16 (0.02) .47 (0.08) 4.55 (0.31) 3.19 (0.30)
New .36 (0.06) .08 (0.02) .16 (0.03) .19 (0.04) 1.33 (0.28) 0.67 (0.22)
Standard errors of each mean are in parenthesis. Ratings for the recollection quality judgments were on a 0–7 scale. AR = actually recollect, VF = very
familiar, IRK = familiarity estimate from independent-recollection-familiarity adjustment.
960 Journal of Cognitive Neuroscience Volume 22, Number 5
because neither of these items should have elicited distinc-
tive picture recollections.
Evidence that subjects had engaged a disqualifying
monitoring strategy comes from a planned comparison
between the red word test and the exclusion test. The
exclusion test required subjects to endorse items that
elicited red word recollections, but unlike the red word
test, we did not include test items that were studied in
both formats on the exclusion test. As a result, if subjects
could recollect pictures then they could be sure that the
item had not been studied as a red word, thereby reduc-
ing false recognition. Unlike the distinctiveness heuristic
described above, such a recall-to-reject strategy should
selectively reduce false recognition to picture items be-
cause only these items could elicit picture recollections.
Consistent with this prediction, false recognition of pic-
ture items was significantly reduced on the exclusion test
(0.30) compared with the red word test (0.41), t(20) =
4.05, SEM = 0.028, d= .83, with no corresponding differ-
ences in hits to red word items (0.65 and 0.62, t< 1)
or false recognition of new items (0.29 vs. 0.27, t< 1).
Additional evidence that subjects had used a recall-to-
reject strategy is that false recognition of picture items
and new items was equated on the exclusion test (0.30
vs. 0.29, t< 1), although a significant difference was ob-
served on the red word test. On the exclusion test, sub-
jects overcame this false recognition effect by using a
recall-to-reject strategy.
Response Latencies
On the basis of prior work, we expected latencies to be
slower on the red word test than on the picture test
because diagnostic monitoring should have been more
effortful on the red word test. These differences were sig-
nificant for hits to both items, t(20) = 4.85, SEM = 44.01,
d= .92, and hits to criterial items, t(20) = 5.84, SEM =
31.11, d= 1.21, but failed to reach significance for cor-
rect rejections of noncriterial items, t(20) = 1.79, SEM =
41.73, p= .09, d= .32. We also compared latencies
across the red word test and the exclusion test. Pre-
dictions for this comparison were less clear because the
recall-to-reject strategy facilitated rejections (potentially
making responses faster) but also should have required
the search for multiple recollections (potentially making
responses slower). Consistent with the latter, responses
to red words were slower on the exclusion test than on
the red word test, t(20) = 3.85, SEM = 400, d= .76, and
similarly for new items, t(20) = 3.05, SEM = 32.41, d=
.49. Subjects may have attempted an unsuccessful recall-
to-reject process for these items, thereby slowing the de-
cision. In contrast, there was no difference in response
latencies for pictures on the red word test and exclusion
tests, t< 1, illustrating that response latencies were a
poor indicator of underlying retrieval monitoring pro-
cesses. Although correct rejections were somewhat faster
on the picture test (cf. Gallo et al., 2006), they did not
differ between the exclusion test and the red word test.
NEUROIMAGING RESULTS
We report two primary sets of neuroimaging analyses.
First, we used simple contrasts to compare activity be-
tween the memory tests, using unbiased whole-brain
analyses ( p< .001, uncorrected, five contiguous voxel
threshold). These contrasts compared the red word test
to the picture test, as in our behavioral analysis of diag-
nostic monitoring, and the red word test to the exclusion
test, as in our behavioral analysis of disqualifying moni-
toring. Second, we conducted conjunction analyses that
were designed to more precisely isolate the two types of
recollection-based retrieval monitoring while controlling
for the potentially confounding influence of retrieval
success.
Cross-test Comparisons
For the first set of analyses, we pooled correct responses
to red word items and picture items on each test (yield-
ing an average of 40 observations per test, per subject).
Pooling these items increased our statistical power
for cross-test comparisons and was theoretically justified
Table 2. Mean Recognition of Each Item Type on the Criterial
Recollection Tests and Response Latencies for Correct
Responses
p, “Yes”Latency “Yes”Latency “No”
Red Word Test
Both .70 (0.02) 1422 –
Red words .62 (0.03) 1399 –
Pictures .41 (0.03) –1481
New .27 (0.04) –1343
Picture Test
Both .75 (0.03) 1209 –
Red words .19 (0.03) –1406
Pictures .61 (0.03) 1218 –
New .11 (0.03) –1335
Exclusion Test
Red words .65 (0.03) 1552 –
Pictures .30 (0.03) –1482
New .29 (0.04) –1442
Standard errors of each mean are in parenthesis. Red words were targets
on the red word test and exclusion test, and lures on the picture test.
Pictures were targets on the picture test, but lures on the red word test
and exclusion test.
Gallo, McDonough, and Scimeca 961
because retrieval monitoring processes should have
occurred for all studied items (cf. Gallo et al., 2006). This
analysis equated item history and response types across
the tests (correct hits and correct rejections), so that any
resulting differences would be due to the different types
of information that were recollected and/or correspond-
ing monitoring processes. Analyses of items studied in
both formats are not reported because they were more
familiar than the other items (and only occurred on two
of the tests). We also compared correct rejections of new
items across the tests.
As can be seen from Table 3, two right frontal regions
were more active for studied items on the red word test
than the picture test, including a region in right DLPFC
(near BA 8/9). In contrast, no regions were more active
for studied items on the picture test compared with
the red word test. This pattern is consistent with the idea
that diagnostic retrieval monitoring was more effortful on
the red word test than the picture test, thereby recruit-
ing DLPFC more heavily. On the picture test, subjects
were able to use the distinctiveness heuristic to suppress
false recognition, and basing their decisions on relatively
more distinctive recollections placed fewer demands on
DLPFC. No DLPFC regions were active for the correspond-
ing new item contrasts, although a more anterior and me-
dial frontal region was more active on the red word test
relative to the picture test (see Table 4). New items were
less familiar than studied items and so should not have
engaged recollection-based retrieval monitoring to the
same extent, although false recognition to new items was
greater on the red word test than on the picture test, sug-
gesting at least some degree of retrieval monitoring.
Comparing the exclusion test and the red word test re-
vealed that studied items were more likely to activate
frontal regions on the exclusion test, including a cluster
in left anterior DLPFC (near BA 10/46). In contrast, no
frontal regions were more active on the red word test
than on the exclusion test. This pattern suggests that the
picture-based recall-to-reject strategy increased DLPFC
activity relative to the red word test, in contrast to the
picture-based distinctiveness heuristic, which decreased
DLPFC activity relative to the red word test. The compari-
son with new items yielded no activity in the left hemi-
sphere, although several right frontal regions were more
active on the exclusion test than on the red word test (in-
cluding a DLPFC region near BA 8). This activity may reflect
additional monitoring demands on the exclusion test, a
possibility we discuss more in the General Discussion.
Monitoring Conjunctions
The aforementioned analyses of studied items revealed
that frontal regions were less active on the picture test
compared with the red word test but more active on the
exclusion test compared with the red word test. Moreover,
these effects appeared to be lateralized, with the former
emerging in right DLPFC and the latter in the left. As dis-
cussed, these effects may reflect contributions of diagnos-
tic and disqualifying monitoring, respectively, but different
types of information may have been recollected across the
tests. To further isolate retrieval monitoring, we conducted
two conjunction analyses, controlling for retrieval success.
Conjunction analyses identify regions of overlap between
two simple contrasts, making them more conservative
than the contributing contrasts. Although the simple con-
trasts in these analyses were not independent, we used a
more liberal threshold for each contributing contrast to
Table 3. All Active Clusters from Comparing Studied Items across the Recollection Tests
Talairach No. Voxels Approximate Region BA
Red Word Test > Picture Test
33, 2, 44 16 R frontal/middle gyrus 6
27, 37, 40 12 R frontal/middle gyrus 8/9
30, −74, 29 14 R occipital/superior gyrus 19
−65, −22, 20 7 L parietal/postcentral gyrus 40
Picture Test > Red Word Test No suprathreshold regions
Exclusion Test > Red Word Test
3, 32, 48 5 R frontal/medial gyrus 8
−33, 45, 23 12 L frontal/middle gyrus 10/46
Red Word Test > Exclusion Test
−62, −16, 20 10 L parietal/postcentral gyrus 43/40
Talairach coordinates (x,y,z) are the peak activation within a cluster, arranged anterior to posterior and laterally (R = right, L = left). BA = approxi-
mate Brodmannʼs areas.
962 Journal of Cognitive Neuroscience Volume 22, Number 5
characterize the regions of overlap and avoid Type II error
(p< .01, uncorrected, five contiguous voxel threshold).
To isolate diagnostic monitoring, we performed a con-
junction analysis to find regions that were more active
when subjects rejected picture items on the red word
test compared with rejecting red word items on the pic-
ture test, as well as rejecting picture items on the red
word test compared with accepting picture items on
the picture test. The first contrast controls for the type of
response across tests (correct rejection of equally familiar
studied items) but varies item history and potential re-
trieval success (pictures and red words). The second con-
trast controls for item history and potential retrieval
success effects (i.e., the recollection of pictures) while vary-
ing the type of response across tests (correct rejection and
correct acceptance). The resulting overlap should reflect
the diagnostic monitoring process that was more effortful
on the red word test than on the picture test.
Figure 1 (top panel) illustrates prefrontal activity ob-
served for this diagnostic monitoring conjunction. There
were two prominent clusters in right DLPFC ( Talairach
coordinates for the centers = 27, 37, 41, near BA 8/9 on
the middle frontal gyrus, and 31, 48, 30, near BA 9 on
the superior frontal gyrus) as well as a more posterior right
PFC region (34, 3, 47, near BA 6). There was no prominent
activity in analogous left DLPFC regions, although there
was overlapping activity near cingulate gyrus (−20, 8, 40,
near BA 32) and relatively smaller clusters near BA 8
(−27, 23, 38) and BA 44 (−50, 14, 16). To show the extent
of these and other regions of activity, Figure 2 presents
whole brain activity for this conjunction. Of additional
interest were clusters in bilateral inferior parietal cortex
(near BA 40) as well as more posterior regions in right
occipital cortex, that is, fusiform (BA 19), lingual gyrus
(BA 18), and a more superior region near BA 39/19. These
latter regions have been associated with retrieval success in
several memory studies, a point that we discuss more in
the General Discussion section.
We next conducted an ROI analysis as a direct test of the
lateralization observed in DLPFC activity. Using MarsBar
software (Brett, Anton, Valabregue, & Poline, 2002), we
created two ROIs based on a 5-mm sphere centered
around the peak voxel of the two DLPFC clusters found
in the conjunction analysis. We then created two ROIs that
were based on the same coordinates but in the opposite
hemisphere. For each ROI, we extracted the percent signal
change (relative to the ROI mean signal) for red word items
and picture items and then conducted a 2 (Hemisphere:
left, right) ×2 (Response Types: hits, correct rejections)
×2 (Test: red word test, picture test) ANOVA on the ex-
tracted signal.
1
Analysis of the cluster near BA 9 (31, 48,
30 on the right) confirmed an interaction between test
type and hemisphere, F(1,20) = 4.29, MSE = 0.698, p=
.05, η
p2
= .177, with no other main effects or interactions.
Follow-up ttests revealed that this interaction was driven
by greater right DLPFC activity for the rejection of lures
on the red word test compared with the picture test,
t(20) = 2.38, SEM = 0.201, d= .49, with no other signifi-
cant effects. A similar analysis of the cluster near BA 8/9 (27,
37, 41) revealed only a marginal effect of test (red word
test > picture test, p= .10) with no significant interactions.
Thus, although we observed two right DLPFC clusters in
the whole-brain conjunction, only one of these regions
survived the direct test of laterality.
Table 4. All Active Clusters from Comparing New Items across the Recollection Tests
Talairach No. Voxels Approximate Region BA
Red Word Test > Picture Test
12, 47, 0 5 R frontal/medial gyrus 10
−21, −81, 21 19 L occipital/cuneus 18
Picture Test > Red Word Test
24, −40, 13 10 R sublobular/caudate nucleus NA
Exclusion Test > Red Word Test
21, 46, −10 5 R frontal/orbital gyrus 11
45, 22, 40 11 R frontal/middle gyrus 8
30, 20, 52 9 R frontal/middle gyrus 6/8
42, −10, 31 6 R frontal/precentral gyrus 6
48, −45, 30 20 R parietal/supramarginal gyrus 40
6, −57, 30 14 R parietal/precuneus 7
Red Word Test > Exclusion Test No suprathreshold regions
Talairach coordinates (x,y,z) are the peak activation within a cluster, arranged anterior to posterior and laterally (R = right, L = left). BA = approx-
imate Brodmannʼs areas.
Gallo, McDonough, and Scimeca 963
Figure 1. Axial slices
illustrating prefrontal activity
observed in the diagnostic
monitoring conjunction
(top) and in the disqualifying
monitoring conjunction
(bottom).
Figure 2. All active clusters in
the diagnostic monitoring
conjunction projected onto
transparent brain templates.
964 Journal of Cognitive Neuroscience Volume 22, Number 5
To isolate disqualifying monitoring, we performed a
conjunction analysis to find regions that were more active
when subjects rejected picture items on the exclusion
test compared with rejecting picture items on the red
word test as well as rejecting picture items on the exclusion
test compared with accepting picture items on the picture
test. The first contrast controls for the type of response
across tests (correct rejection of picture items) but po-
tentially varies retrieval success (i.e., being greater when
subjects were explicitly attempting to recollect pictures in
the rejection strategy). The second contrast controls for
retrieval success while varying the type of response across
tests (correct rejection and correct acceptance). The re-
sulting overlap should represent the disqualifying moni-
toring process that we assume was used only on the
exclusion test.
Figure 1 (bottom panel) illustrates prefrontal activity ob-
served for this disqualifying monitoring conjunction. There
were two clusters in left DLPFC, one near BA 10/46 on the
middle frontal gyrus (−34, 42, 20) and one near BA 8 on
the middle frontal gyrus (−38, 28, 44), with no correspond-
ing activity on the right. Figure 3 presents whole brain ac-
tivity for this conjunction. The two posterior clusters were
in left inferior parietal cortex (−36, −49, 35, near BA 40,
supramarginal gyrus) and precuneus (10, −64, 39, near
BA 7). To explore the lateralization of the observed DLPFC
effects, we again conducted an ANOVA on the signal
extracted from ROIs centered on the obtained clusters.
Analysis of the cluster near BA 10/46 (−34, 42, 20 on the
left) revealed a main effect of test (exclusion test > red
word test), F(1,20) = 9.86, MSE = 0.468, η
p2
= .330, with
no other effects or interactions. Analysis of the cluster
near BA 8 (−38, 28, 44 on the left) also revealed a main
effect of test (exclusion test > red word test), F(1,20) =
6.94, MSE = 1.23, η
p2
= .258, and further there was an ef-
fect of response (correct rejections > hits), F(1,20) = 5.20,
MSE = 0.408, η
p2
= .206, with no other effects or inter-
actions. Thus, although the exclusion test elicited greater
activity in these DLPFC regions than the red word test,
these effects were not significantly greater in the left hemi-
sphere than in the right.
GENERAL DISCUSSION
We measured the neural correlates of two fundamental
types of retrieval monitoring. Subjects studied red words
and pictures under conditions where (a) these stimuli
were equated on familiarity and (b) pictures afforded
more distinctive recollections than red words. We found
that source memory confusions were reduced on the
picture test relative to the red word test, indicating that
expecting more detailed recollections for pictures en-
hanced diagnostic monitoring accuracy (i.e., a distinctive-
ness heuristic; Dodson et al., 2000; Schacter et al., 1999).
The use of this diagnostic monitoring process on the pic-
ture test was associated with less DLPFC activity compared
with the red word test. We also found that source memory
confusions were reduced in a mutually exclusive condi-
tion compared with a nonexclusive condition, indicating
that the exclusivity relationship facilitated disqualifying
monitoring accuracy (i.e., a recall-to-reject strategy; Jacoby
et al., 1998; Hintzman & Curran, 1994). The use of this
Figure 3. All active clusters in
the disqualifying monitoring
conjunction projected onto
transparent brain templates.
Gallo, McDonough, and Scimeca 965
disqualifying monitoring strategy on the exclusion test was
associated with increased DLPFC activity compared with
the red word test.
Our results indicate that different types of recollection-
based retrieval monitoring correspond to different patterns
of prefrontal activity. This activity cannot be mapped easily
onto single-process notions such as retrieval effort. For
example, one might argue that the red word test required
the most retrieval effort (hence prefrontal resources) rela-
tive to the other two tests because it elicited the greatest
number of source memory confusions. This idea can
explain why the red word test elicited more prefrontal ac-
tivity than the picture test (which benefitted from distinc-
tive picture recollections), but it cannot explain why there
was less activity compared with the exclusion test (which
also benefitted from picture recollections). The argument
that all recollection-based rejection processes recruit pre-
frontal regions also falters because the picture test clearly
benefitted from the use of a recollection-based monitoring
process but was less likely to activate DLPFC than the red
word test. More generally, all three of our tests required the
recollection and the monitoring of specific details.
Our results are best understood by considering the
two different types of retrieval monitoring processes iso-
lated by our task. When subjects used the absence of
picture recollections to reject familiar items (the distinc-
tiveness heuristic), the memory decision was associated
with less effortful diagnostic monitoring and led to reduced
DLPFC activity. Subjects engaged in diagnostic monitoring
on both the red word test and the picture test, but such
monitoring was more heavily recruited on the red word
test (i.e., they had to spend more effort recollecting the
studied context). In contrast, when subjects used the pre-
sence of picture recollections to reject familiar lures (recall-
to-reject), the memory decision was associated with an
additional disqualifying monitoring strategy and led to
increased DLPFC activity. Unlike diagnostic monitoring,
which theoretically occurred to some degree on all of
our tests, subjects were only justified in using disqualifying
monitoring on the exclusion test (i.e., recollecting pictures
to avoid source confusions). Considered as a whole, these
results implicate DLPFC in both types of retrieval moni-
toring, with the relative level of activity tracking those
memory decisions that more heavily relied on a given type
of monitoring.
Retrieval Monitoring Theories
The current results help to constrain the more general
theories of retrieval monitoring that were described in
the Introduction. Consider the systematic/ heuristic dis-
tinction of the source monitoring framework (Johnson,
2006). Heuristic processes involve relatively fast or simple
decisions, such as when a memory decision is based on a
single type ofinformation like familiarity. Similar to a signal-
detection process, subjects expect to retrieve a certain
degree of information along the relevant memory dimen-
sion, and a test item is compared with this criterion to
make a decision (cf. Johnson & Raye, 1981). In contrast,
systematic processes take advantage of additional informa-
tion to help make a memory decision. Systematic process-
ing may also involve criterion setting, but it goes a step
further in terms of the strategic use of contextual informa-
tion that also can inform the decision. Heuristic processes
have been attributed more to the right PFC and systematic
processes have been attributed more to the left PFC (e.g.,
Nolde et al., 1998).
The disqualifying monitoring process that occurred on
our exclusion test can be considered a type of systematic
process. On this test, in addition to searching memory
for the to-be-recollected information, subjects also bene-
fited from strategically recollecting noncriterial recollec-
tions (i.e., a recall-to-reject strategy). Consistent with
the idea that left DLPFC supports systematic processes,
we found that left DLPFC was more active on the exclu-
sion test than on the red word test in several analyses,
although a direct test of the laterality of this effect was
not significant.
2
A similar effect in right DLPFC was not
observed in any of our analyses, providing little support
for the idea that right DLPFC is critical for postretrieval
monitoring (Rugg et al., 2003; Henson et al., 1999).
It is less clear what the source monitoring framework
would predict for the retrieval monitoring process that
occurred on our nonexclusion test. If one considers the
distinctiveness heuristic to be a special type of metacog-
nitive monitoring process, one that is engaged only when
distinctive recollections are expected (cf. Schacter &
Wiseman,2006; Dodson et al., 2000), then the picture test
involved a heuristic process that did not occur on the red
word test. This conceptualization also would be keeping
with the idea that heuristic processes are relatively fast
acting, as response latencies were fastest on the picture
test. In this case, the systematic/ heuristic distinction of
the source monitoring framework would incorrectly pre-
dict greater right DLPFC for the picture test compared
with the red word test because the right DLPFC has been
associated with heuristic-based responding.
In contrast, the current approach conceptualizes the
distinctiveness heuristic as just one instance of a more
general diagnostic monitoring process, one that occurs
whenever subjects must base a memory decision on spe-
cific source recollections. On each of our criterial recol-
lection tests, subjects set a response criterion along the
relevant recollection dimension to make a memory deci-
sion. Such diagnostic monitoring was more effortful on
the red word test than the picture test, making it more
likely to recruit right DLPFC. From this perspective, pre-
vious neuroimaging findings that were attributed to heu-
ristic processes (e.g., fast and effortless decisions) may
instead have been caused by diagnostic monitoring (e.g.,
setting response criterion along a single dimension). Either
way, the current study indicates the importance of study-
ing specific types of decision processes to understand
966 Journal of Cognitive Neuroscience Volume 22, Number 5
retrieval monitoring, as opposed to more general notions
of retrieval speed or difficulty.
Outstanding Questions
One remaining question is the role of the more posterior
activity observed in our conjunction analyses, including
left parietal and right occipital regions (e.g., fusiform
and precuneus). Activity in these regions has been attrib-
uted to retrieval success in many memory studies (for a re-
view, see Skinner & Fernandes, 2007), with parietal activity
potentially reflecting attention to information that is
thought to be “old”and occipital activity potentially reflect-
ing the perceptual reactivation of picture recollections
(e.g., Woodruff, Johnson, Uncapher, & Rugg, 2005; Wheeler
& Buckner, 2004). Although pictures also were involved
in each of our conjunctions, we controlled for retrieval
success effects by including picture hits on the picture test.
This activity observed here instead may reflect the top–
down modulation of these regions during the retrieval
monitoring process (see Hornberger, Rugg, & Henson,
2006). Although speculative, our subjects may have allo-
cated more attention to picture representations when
attempting to use a recall-to-reject strategy.
A related question regards the activity in right DLPFC
and posterior regions that we observed for new items on
the exclusion test. Activity is not always obtained for new
items across conditions that differ in retrieval monitor-
ing demands (Gallo et al., 2006; Rugg et al., 2003), but
Woodruff et al. (2006) also observed activity for new
items in DLPFC regions and similar posterior regions
during an exclusion task. They attributed this activity to
retrieval monitoring processes, such as orienting toward
a specific type of information during a memory search. The
current data are consistent with this account. As discussed,
response latencies were slower for new items on the exclu-
sion test than on the red word test, potentially because
subjects had attempted a recall-to-reject strategy. However,
new items could not benefit from this strategy and instead
needed to be rejected via diagnostic monitoring processes.
The observed activity might reflect the use of these addi-
tional monitoring processes.
One final question is the degree that the current findings
will generalize to the monitoring of other types of events in
memory. As discussed by Mitchell et al. (2008) and others,
retrieval-monitoring processes operate across different
types of materials, but they also can be influenced by the
quality of retrieved information. We attempted to overcome
any material-specific effects in the current study with our
specific contrasts and conjunction analyses. It remains to
be seen, though, whether the current pattern of effects
can be found with other types of materials. As discussed,
evidence for a recall-to-reject strategy and the distinctive-
ness heuristic has been found across a variety of cognitive
tasks and materials. To the degree that the same types of
decision processes underlie these various effects, studies
with these other materials should find similar patterns of
DLPFC activity as were found here. Such findings would
bolster the idea that an understanding of the types of
decision processes involved is critical for understanding
prefrontal contributions to retrieval monitoring.
Acknowledgments
This project was funded by grants from the University of Chicagoʼs
Office of the Vice President, Social Sciences Division, and Brain
Research Imaging Center. Thanks to Jean Decety, Robert Lyons,
and Steve Small for technical assistance.
Reprint requests should be sent to David A. Gallo, Department
of Psychology, University of Chicago, 5848 South University
Avenue, Chicago, IL 60637, or via e-mail: dgallo@uchicago.edu.
Notes
1. It is important to acknowledge that this is a biased selection
of ROIs because it is based on observed activation patterns from
the whole-brain analysis. Nevertheless, this analysis allows for
a direct test of whether the right-lateralized effects observed in
the unbiased whole-brain conjunction were significantly different
from any subthreshold effects that also may have been present in
the left hemisphere.
2. We do not believe that this laterality effect is due to the
materials that we used. First, we used verbal labels on all of our
memory tests, so that the critical difference between these two
tests was in the distinctiveness of the to-be-recollected stimulus
(a red word or a picture). Second, the conjunction analysis at-
tempted to control for any material-specific retrieval success
effects. Finally, we found that searching memory for the verbal
information (red words) was more likely to activate right DLPFC
compared with picture information, a finding that is opposite to
what one might expect based on material-specific lateralization of
DLPFC activity (e.g., Kelley et al., 1998).
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