A bilateral frontoparietal network underlies visuospatial analogical reasoning.

Abstract

Our ability to reason by analogy facilitates problem solving and allows us to communicate ideas efficiently. In this study, we examined the neural correlates of analogical reasoning and, more specifically, the contribution of rostrolateral prefrontal cortex (RLPFC) to reasoning. This area of the brain has been hypothesized to integrate relational information, as in analogy, or the outcomes of subgoals, as in multi-tasking and complex problem solving. Using fMRI, we compared visuospatial analogical reasoning to a control task that was as complex and difficult as the analogies and required the coordination of subgoals but not the integration of relations. We found that analogical reasoning more strongly activated bilateral RLPFC, suggesting that anterior prefrontal cortex is preferentially recruited by the integration of relational knowledge. Consistent with the need for inhibition during analogy, bilateral, and particularly right, inferior frontal gyri were also more active during analogy. Finally, greater activity in bilateral inferior parietal cortex during the analogy task is consistent with recent evidence for the neural basis of spatial relation knowledge. Together, these findings indicate that a network of frontoparietal areas underlies analogical reasoning; we also suggest that hemispheric differences may emerge depending on the visuospatial or verbal/semantic nature of the analogies.

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A bilateral frontoparietal network underlies visuospatial analogical reasoning
Christine E. Watson⁎, Anjan Chatterjee
Department of Neurology and Center for Cognitive Neuroscience, 3 West Gates Building, 3400 Spruce St., University of Pennsylvania, Philadelphia, PA, 19104, USA
a b s t r a c ta r t i c l ei n f o
Article history:
Received 25 May 2011
Revised 15 August 2011
Accepted 15 September 2011
Available online xxxx
Keywords:
Analogical reasoning
Relational integration
Rostrolateral prefrontal cortex
Inferior frontal gyrus
Spatial relations
Our ability to reason by analogy facilitates problem solving and allows us to communicate ideas efficiently. In
this study, we examined the neural correlates of analogical reasoning and, more specifically, the contribution
of rostrolateral prefrontal cortex (RLPFC) to reasoning. This area of the brain has been hypothesized to inte-
grate relational information, as in analogy, or the outcomes of subgoals, as in multi-tasking and complex
problem solving. Using fMRI, we compared visuospatial analogical reasoning to a control task that was as
complex and difficult as the analogies and required the coordination of subgoals but not the integration of
relations. We found that analogical reasoning more strongly activated bilateral RLPFC, suggesting that ante-
rior prefrontal cortex is preferentially recruited by the integration of relational knowledge. Consistent with
the need for inhibition during analogy, bilateral, and particularly right, inferior frontal gyri were also more
active during analogy. Finally, greater activity in bilateral inferior parietal cortex during the analogy task is
consistent with recent evidence for the neural basis of spatial relation knowledge. Together, these findings
indicate that a network of frontoparietal areas underlies analogical reasoning; we also suggest that hemi-
spheric differences may emerge depending on the visuospatial or verbal/semantic nature of the analogies.
© 2011 Elsevier Inc. All rights reserved.
Introduction
The ability to reason by analogy has been claimed to be at the
“core of cognition” (Hofstadter, 2000). Two objects, concepts, or
even real-world situations are analogous if they are dissimilar on
the surface but share some higher-order, structural similarities. For
instance, consider this analogy often attributed to Einstein: “You
see, wire telegraph is a kind of a very, very long cat. You pull his tail
in New York, and his head is meowing in Los Angeles.” Superficially,
a telegraph and a cat have little in common, and yet this analogy con-
veys an important point about the way in which a local action can
have long-distance consequences. Similarly, analogies are used fre-
quently and naturally to communicate ideas in a wide-variety of do-
mains (Holyoak and Thagard, 1995), including science (Dunbar, 1995)
and politics (Blanchette and Dunbar, 2001), and their use promotes
learning in education (Loewenstein et al., 1999) and rehabilitation
(Wai-Kwong Man et al., 2006).
Perhaps because of analogy's critical role in human cognition (and
some primates, Flemming et al., 2008; Gillan et al., 1981), analogical
reasoning has been the focus of many behavioral and computational
investigations in the past three decades. However, not much is
known about analogy's neural basis or the way in which cognitive ac-
counts of analogy map onto neural dynamics. Of the functional mag-
netic resonance imaging (fMRI) studies that have examined
analogical reasoning, most point to the rostrolateral prefrontal cortex
(RLPFC) as playing a pivotal role in mediating analogy. For instance,
activity in RLPFC is sensitive to the number of relations, or the rela-
tionships between components of an analogy, that need to be consid-
ered (Cho et al., 2010; Christoff et al., 2001; Krawczyk et al., 2011;
Kroger et al., 2002). The degree to which an analogy's components
are dissimilar on the surface also modulates RLPFC activation
(Green et al., 2010; Hampshire et al., 2011). For instance, cross-do-
main analogies (e.g., nose:scent::antenna:signal) elicit greater fronto-
polar activity than within-domain analogies (e.g., nose:scent::
tongue:taste) (Green et al., 2010). The development of analogical rea-
soning ability in children is also accompanied by changes in the way
in which RLPFC is engaged (Crone et al., 2009; Wright et al., 2008;
see also Dumontheil et al., 2008), and damage to prefrontal cortex
(PFC) is associated with impaired performance on analogies (Krawczyk
et al., 2008; Morrison et al., 2004).
The recruitment of RLPFC during analogical (and other types of re-
lational) reasoning has been hypothesized to reflect the need to si-
multaneously compare and integrate multiple relations between
things — “relational integration” (Bunge et al., 2005, 2009; Christoff
et al., 2001; Kroger et al., 2002; Wendelken et al., 2008). For example,
determining whether or not two pairs of words are analogous to each
other (e.g., bouquet:flower::chain:link?), a task that requires rela-
tional integration, more strongly recruits left RLPFC than determining
whether or not the words in each pair are semantically related, a task
that does not require relational integration (Bunge et al., 2009). Suc-
cessful analogy-making requires comparing and evaluating relational
similarities between concepts (Gentner, 1983, 2003; Holyoak, 2005;
NeuroImage xxx (2011) xxx–xxx
⁎ Corresponding author. Fax: +1 11 215 349 8260.
E-mail addresses: watsonc@mail.med.upenn.edu (C.E. Watson),
anjan@mail.med.upenn.edu (A. Chatterjee).
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1053-8119/$ – see front matter © 2011 Elsevier Inc. All rights reserved.
doi:10.1016/j.neuroimage.2011.09.030
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Holyoak and Thagard, 1997), and the need for relational integration
distinguishes analogical reasoning from other complex cognitive
skills.
However, anterior PFC activity is also observed during a wide range
of non-analogical cognitive tasks, including episodic memory retrieval
(Ranganath et al., 2000, 2003), prospective memory (Burgess et al.,
2001; Simons et al., 2006), and multi-tasking (Braver and Bongiolatti,
2002;Dreheretal.,2008;Koechlinetal.,1999).Thisdomain-generalin-
volvementofanteriorPFChasledtocomprehensivetheoriesofitsfunc-
tion. On several accounts, this area of the brain coordinates the
outcomes of subgoals in the service of fulfilling a main goal (Braver
and Bongiolatti, 2002; De Pisapia and Braver, 2008; Koechlin et al.,
1999; Ramnani and Owen, 2004; Reynolds et al., 2006). For instance,
greater frontopolar activity was observed when participants detected
that any concrete word followed any abstract word in a stream of
words relative to detecting that a specific concrete word (“lime”) fol-
lowed a specific abstract word (“fate”) (Braver and Bongiolatti, 2002).
In this way, the task that elicited greater frontopolar activity required
participants to semantically classify the probe words (subgoal tasks)
and integrate their outcomes with the context (concrete follows ab-
stract) to make a response. On this view, integrating the relations be-
tween entities is just a special case of coordinating subgoals, and even
non-analogical reasoning tasks may require “the integration of the re-
sults of two or more separate cognitive operations” (Ramnani and
Owen,2004, p.190). Thus, a comparison ofanalogy toanother complex
taskthatrequiresthecoordinationofsubgoalsbutnottheintegrationof
relations would test the specificity of RLPFC for relational integration.
A challenge for any neuroimaging study of analogy is the difficulty
of analogical reasoning relative to most other tasks — and the obser-
vation that the tasks that engage RLPFC are frequently the most diffi-
cult to solve (Braver et al., 2003; Velanova et al., 2003). Among
neuroimaging studies of analogical reasoning, analogies are often
solved less accurately and more slowly than the non-analogical task
to which they are compared (Bunge et al., 2005, 2009; Luo et al.,
2003; Prabhakaran et al., 1997; Volle et al., 2010; Wharton et al.,
2000; but see Krawczyk et al., 2010, 2011). A non-analogical task as
difficult as analogy natively is needed to more precisely investigate
the neural basis of analogical reasoning.
In the current study, we investigated the neural correlates of ana-
logical reasoning relative to a task that, while necessitating the coor-
dination of subgoals, did not require integration of relations. This
comparison task was both similarly difficult and perceptually-
matched to the analogy task. To create our stimuli, we drew inspira-
tion from developmental studies of analogical reasoning (e.g.,
Kotovsky and Gentner, 1996) and used sets of colored shapes as the
basis for our reasoning tasks (Fig. 1). In the “analogy” condition, the
correct answer is arrived at by considering the spatial relations be-
tween the colored shapes in the source set and selecting the response
with the same set of relations. In the “item” condition, however, the
relationships between the colored shapes are not relevant: the cor-
rect answer is arrived at by selecting the choice that contains the
same three colored shapes as the source, in any order. In this way,
both reasoning tasks required evaluation of multiple subgoals to se-
lect an answer. Only the analogy condition, however, requires an in-
tegration of relations, in particular (here, relations in space).
If RLPFC is more strongly driven by relational integration, we ex-
pect greater activity in this region during the analogy condition. How-
ever, if this area responds to the coordination of subgoals, more
generally, we expect no differences in this area between conditions.
In fact, because the item condition was slightly more difficult than
the analogy condition for participants in the scanner (see Results), a
degree of difficulty account would predict greater activity in RLPFC
during the item condition.
Of course, relational integration is only one part of the analogical
reasoning process; many accounts of analogy also include inhibition
as a crucial component (Krawczyk et al., 2008; Morrison et al.,
2004; Robin and Holyoak, 1995; Viskontas et al., 2004). Inhibitory
control is necessary to minimize interference from responses that
are based on superficial (e.g., semantic or perceptual) similarity rath-
er than deeper, relational similarity. As a result, patients with im-
paired inhibitory processes as a result of frontotemporal lobar
degeneration show deficits on relational reasoning tasks (Krawczyk
et al., 2008; Morrison et al., 2004). Similarly, several fMRI studies
have found greater activity within inferior frontal gyrus (IFG) during
analogy (Cho et al., 2010; Christoff et al., 2001; Green et al., 2006,
2010; Krawczyk et al., 2011; Luo et al., 2003; Volle et al., 2010), an
area of the brain that, in the right hemisphere, also participates in re-
sponse inhibition (e.g., Aron et al., 2003; for a review, see Aron et al.,
2004) and, in the left hemisphere, in selecting among competing se-
mantic representations in memory (e.g., Moss et al., 2005; Novick et
al., 2005; Thompson-Schill et al., 1997). In the current task, responses
in the analogy condition were based on relational rather than percep-
tual similarities. On the assumption that participants' dominant, pre-
potent responses are driven by perceptual cues, we predicted greater
activity in IFG, particularly in the right hemisphere, during the analo-
gy task compared to the “item” task.
In addition to this network of frontal regions, posterior areas of the
brain that mediate the visuospatial (or semantic) information upon
which analogies are based are also recruited during analogical rea-
soning (Krawczyk, 2010). In the present task, analogies are solved
based on the spatial relationships between colored shapes. A recent
fMRI study from our lab of the neural basis of categorical spatial rela-
tions like “in” and “above” found that attending to spatial relations
produced greater activity in bilateral superior and inferior parietal
cortices and middle frontal gyrus relative to attending to the identity
of objects (Amorapanth et al., 2010). Several neuroimaging studies of
visuospatial analogies have also implicated parietal cortex (Cho et al.,
2010; Crone et al., 2009; Geake and Hansen, 2005; Preusse et al.,
2010; Volle et al., 2010; Wartenburger et al., 2009; Wharton et al.,
2000). Therefore, we predicted greater activation in this area during
the analogy task relative to the item task, in which spatial relations
were uninformative. By contrast, we predicted greater activation by
the item task in areas involved in processing shape and color — sur-
face, not relational, aspects of the stimuli. Amorapanth et al. (2010)
found greater activity in left fusiform gyrus when participants
attended to object identity relative to spatial relations, and fusiform
gyri have also been implicated in visual semantic processing (Martin
and Chao, 2001; Martin et al., 1995; Simons et al., 2003). Although
Fig. 1. Stimuli from the analogy and item tasks. A) An analogy trial on which the critical
relations between source and correct answer are between shapes. B) An analogy trial
on which the critical relations between source and correct answer are between colors.
C) An item trial on which the correct answer and foil differ only in shape. D) An item
trial on which the correct answer and foil differ only in color.
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visual information like color and shape is relevant to both tasks at
some point in the reasoning process, we speculated that heightened
attention to structural features in the analogy condition might lessen
sustained activity in areas responsible for processing visual informa-
tion relative to the item condition.
Materials and methods
Stimuli
Stimulus materials consisted of a visuospatial analogical reasoning
task (“analogy” task), a visuospatial, non-analogical reasoning task
(“item” task), and an identity matching task used as a baseline
(“matching” task). In all three conditions, each trial was made up of
a display of three sets of colored shapes. The source set, presented
at the top of the screen, was designed to match one of the response
sets at the bottom. The nature of this match was determined by the
task at hand (Fig. 1).
As described above, a correct response in the analogy condition
was the set of colored shapes that contained the same pattern of spa-
tial relations as the source. On any given trial, only one type of infor-
mation, color (blue, green, red, yellow) or shape (circle, diamond,
square, triangle), was relevant for selecting a response. When the
basis of an analogy was the system of relations between shapes, all
three sets contained the identical pattern of colors (Fig. 1A). Con-
versely, when the basis of an analogy was relations between colors,
all sets contained the identical pattern of shapes (Fig. 1B). In the
item condition, relations between colored shapes were not relevant
for selecting a response. Instead, a correct response was the set of col-
ored shapes that contained the same items as the source, in any order.
Distinguishing correct and incorrect responses could be a difference
in shape (Fig. 1C) or a difference in color (Fig. 1D). Finally, a correct
response in the matching condition (not pictured) was the single col-
ored shape that was perceptually identical to the single colored shape
presented as the source. In all three tasks, the location of the correct
answer (left or right) was randomly determined on each trial.
The item task was matched in difficulty and complexity to the
analogy task, requiring subgoal coordination without the need to in-
tegrate spatial relations between items. We verified that this manip-
ulation produced tasks of similar difficulty by collecting pilot
reaction time and accuracy data from 22 participants at the University
of Pennsylvania. Participants performed 100 analogy trials and 100
item trials, with no time limit required for a response. Trials of each
type were presented in alternating blocks of 10 trials each. One sub-
ject was excluded from our analyses for having an average reaction
time on all trials greater than 2.5 standard deviations from the
group mean. On the basis of this pilot data, we determined the aver-
age accuracy and reaction time for each stimulus item. We then used
the SOS stimulus matching software (B Armstrong, CE Watson, DC
Plaut, in preparation) to select 72 analogy trials and 72 item trials
thatdifferednon-significantly
SD=3.19, Mitem=97.55%, SD 3.57, t(142)=.59, p=.56] and reaction
time [Manalogy=2517.64, SD=454.80, Mitem=2509.98, SD=499.00,
t(142)=.10, p=.92].
onaccuracy[Manalogy=97.88%,
Participants
We recruited 23 participants from the University of Pennsylvania
(Mage=22.80 years, range: 18–27). Fourteen participants were fe-
male, and all were right-handed, native speakers of English with
corrected-to-normal vision. All participants gave informed consent
in accordance with the procedures of the University of Pennsylvania
and were paid $20/hour for their participation. Prior to entering the
scanner, each participant completed approximately 5 min of practice
trials of each type (analogy, item, and matching).
Behavioral task
In the scanner, participants completed 216 individual trials: 72
analogy trials, 72 item trials, and 72 matching trials. Responses and
reaction times were recorded via a button box held with both
hands. On each trial, the correct answer was selected by pressing a
button on the left or right side with the left or right thumb, respec-
tively. All stimuli were presented on a black background.
Trials were presented in four separate scanning runs. During a
given run, trials were blocked by task type. Each block consisted of
6 trials, and participants had 5 s to respond to each trial. If no re-
sponse was recorded after 5 s, the experiment advanced to the next
trial. Trials were separated by a 500 ms fixation cross. Additionally,
each block began with a 5 s instruction screen alerting participants
to the nature of the upcoming trials; trials in the analogy condition,
for instance, were preceded by a screen with the words “Analogy Tri-
als”. Prior to entering the scanner, participants were familiarized with
the names of each condition.
In total, each block of trials lasted 38 s. Each of four scanning runs
contained 3 blocks of each condition (9 blocks total). The order in
which blocks were presented cycled between conditions so that all
three conditions were seen every within every 3 blocks (e.g.,
analogy-item-matching-analogy-item-matching…). This constraint
allowed for 6 possible block sequences. We counterbalanced the oc-
currence of each sequence across participants, but the location of an
individual trial was randomly determined for every participant. In-
cluding time spent collecting both structural and functional MRI
data (and resting state activity not reported here), the entire scanning
session lasted approximately 40 min.
MRI data acquisition
Structural and functional data were collected on a 3.0 T Siemens
Trio scanner with an eight-channel head coil. High-resolution T1-
weighted structural images were collected for each participant
using a 3-D MPRAGE pulse sequence (TR=1620 ms, TE=3.87 ms,
TI=950 ms, flip angle=15°). Each volume consisted of 160 axial
slices and nearisotropicvoxels
1.0000 mm). Functional volumes were acquired using a BOLD EPI se-
quence (TR=3000 ms, TE=30 ms, flip angle=90°). Each volume
consisted of 50 interleaved axial slices approximately 3 mm thick.
During each of four scanning runs, 118 functional volumes were ac-
quired, for a total of 472 volumes. The first three volumes of each
run consisted of fixation screens and were discarded to allow for
steady state magnetization.
(0.9766 mm×0.9766 mmx
Image processing
Data analysis was performed using VoxBo (www.voxbo.org) and
SPM2 (www.fil.ion.ucl.ac.uk/spm). Data preprocessing procedures in-
cluded slice timing correction by sinc interpolation, and standard
alignment, smoothing, and normalization procedures. Each partici-
pant's structural data were normalized to the standard MNI template
using the SPM2 normalization routine. Functional BOLD data were
then realigned with the participant's first functional volume using
rigid body alignment. Normalization of the functional data was ac-
complished by using the parameters generated by SPM2 during nor-
malization of the participant's structural data. Functional data were
smoothed with a 3 voxel full width at half maximum (FWHM) Gauss-
ian smoothing kernel.
Data analysis
First-level analyses
We used the modified general linear model (Worsley and Friston,
1995) to analyze BOLD data from each subject as a function of
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condition. Task covariates were boxcar waveforms convolved with an
estimate of the BOLD hemodynamic response function empirically
derived from motor cortex in a large group of subjects (Aguirre et
al., 1998). Nuisance covariates for effects of scan and six types of
rigid-body motion were also included. Because reaction time differ-
ences between analogy and item conditions emerged in the scanner
(see Results), reaction time was included as a covariate of non-interest
and convolved with an estimate of the BOLD hemodynamic response
function (Aguirre et al., 1998). Time series data were subjected to a
high-pass filter.
Second-level analyses
We evaluated the effect of condition on BOLD signal differences
with second-level, random effects analyses performed on beta values
obtained from the first-level analyses. To do so, we used a multiple re-
gression analysis with subject as a random effect. To derive group ac-
tivation maps for whole-brain analyses, the false positive rate was
controlled by performing 2000 Monte-Carlo permutation tests on
the data (Nichols and Holmes, 2002). The result was a t-statistic
threshold and minimum cluster size of 20 voxels that corrected for
multiple comparisons at pb.05. For region-of-interest (ROI) analyses,
we calculated beta values for each ROI from a single, spatially aver-
aged time series separately for each participant. Paired or one-sample
t-tests were then used to determine if a given contrast was consis-
tently different between hemispheres or consistently greater than
zero, respectively, across all participants.
Regions-of-interest
We defined ROIs in two different ways. First, left and right RLPFC
ROIs were determined by averaging the peak voxels that had been
reported in these regions in previous fMRI studies of analogical rea-
soning. For the average in each hemisphere, we only considered
peaks that emerged from corrected, whole-brain analyses. Two
peaks were determined to be located within medial anterior PFC
(Green et al., 2006; Green et al., 2010) and were excluded from the
average given recent evidence that lateral and medial rostral PFC
are cytoarchitectonically and functionally distinct (Burgess et al.,
2003; Gilbert et al., 2006; Koechlin et al., 2000). Average coordinates
were calculated separately for each hemisphere, with six studies
reporting peaks in left RLPFC (Bunge et al., 2005, 2009; Christoff et al.,
2001; Hampshire et al., 2011; Volle et al., 2010; Wendelken et al.,
2008) and two in right RLPFC (Bunge et al., 2009; Wendelken et al.,
2008). In the left, the average was determined to be x=42, y=50,
z=6 (MNI coordinates). In the right, the average was determined to
be x=−42, y=44, z=0 (MNI coordinates). ROIs were created by
placing 10 mm spheres around each point.
All other ROIs were defined anatomically using the Automated An-
atomical Labeling (AAL) atlas of the MNI single-subject brain
(Tzourio-Mazoyer et al., 2002). For each structure, separate ROIs
were created for left and right hemispheres. ROIs consisted of: left
and right inferior frontal gyri, inferior parietal cortex, superior parie-
tal cortex, and fusiform gyri.
Results
Behavioral results
By design, the matching task was much easier than the analogy and
item task. Therefore, statistics were computed only on data from analogy
and item tasks. Analogy (M=95.69%, SD=.03) and item conditions
(M=94.79%, SD=.03) did not differ in accuracy [t(19)=1.14, p=.27]
(Fig.2).However,despitehavingbeenmatchedforaccuracyandreaction
timeusingpilotdata, analogytrials(M=2043.01 ms,SD=356.62) were
completed more quickly than item trials (M=2183.61, SD=287.42) in
the scanner [t(19)=2.96, pb.01] (Fig. 2). Because reaction time differ-
ences can produce activation differences between conditions, we includ-
ed in our statistical model of BOLD data regressors to covary out the
effects of reaction time (Kable et al., 2004).
Imaging results
Whole-brain analyses (Table 1, Fig. 3)
First, we determined brain areas that were more active during the
analogy condition than the item condition. This analysis resulted in a
single cluster of 26 voxels within right inferior frontal gyrus (Fig. 3)
(BA 6/45, x=52, y=40, z=10, MNI coordinates). For descriptive
purposes, we also report all peaks of activation that exceeded
pb.001, uncorrected, with a minimum cluster size of 20 (Table 1).
No brain areas were more active during the item condition relative
to the analogy condition. Because participants responded significantly
more slowly in the item condition than the analogy condition, we in-
cluded reaction time as a covariate in our analyses to ensure that ac-
tivation differences were not due to longer processing times. To
determine if including reaction time as a covariate had, however,
eliminated regions that responded more strongly to the item condi-
tion, we performed a subsequent analysis in which reaction time
was not included as a covariate. Even so, the same pattern of results
emerged for both analogyNitem and itemNanalogy contrasts.
Anatomical regions-of-interest (Table 2, Fig. 3)
Within each ROI, we determined if a contrast was significantly
greater than zero across participants using a one-sample t-test. In
some cases, we also determined if a contrast was significantly greater
in one hemisphere or the other using a paired-samples t-test. ROIs
predicted to exhibit greater activation during the analogy condition
relative to the item condition included left and right RLPFC, inferior
frontal gyri, and inferior and superior parietal cortex. Within our em-
pirically-defined RLPFC ROIs, both left [t(19)=2.31, pb.05, one-
tailed] and right [t(19)=1.97, pb.05, one-tailed] ROIs exhibited
greater activity during the analogy condition relative to the item
Fig. 2. Mean reaction time (correct trials only) and accuracy by condition. Analogy trials are significantly faster than item trials [t(19)=2.96, pb.01], but analogy and item trials do
not differ on accuracy [t(19)=1.14, p=.27].
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Page 5

condition (Fig. 3B). The strength of RLPFC recruitment during analogy
did not differ by hemisphere [t(19)=.30, p=.77].
Analogical reasoning also produced greater activation in right
[t(19)=2.66, pb.01, one-tailed] and left [t(19)=2.03, pb.05,
one-tailed] IFG (Fig. 3C) and right [t(19)=1.81, pb.05, one-tailed]
and left [t(19)=1.81, pb.05, one-tailed] inferior parietal cortex
(Fig. 3D). Greater activity in the analogy relative to the item con-
dition was not observed in left [t(19)=.65, p=.26, one-tailed] or
right [t(19)=.46, p=.33, one-tailed] superior parietal cortex. Addi-
tionally, none of the significant ROIs showed hemispheric differences:
rightversusleftIFG[t(19)=.39,p=.70,one-tailed],rightversusleftin-
ferior parietal cortex [t(19)=.18, p=.86, one-tailed].
Activity in fusiform gyrus, predicted to be greater during the item
condition relative to the analogy condition, did not exhibit a stronger
response to the item condition in either the left [t(19)=1.34, p=.90,
one-tailed] or right [t(19)=2.13, p=.97, one-tailed] hemispheres.
Discussion
In the present study, we investigated the neural basis of analogical
reasoning. To determine whether or not the integration of relations or
the coordination of multiple subgoals more strongly engages RLPFC,
we compared an analogy task to another reasoning task that did not
require extracting relational information. We also predicted greater
activity in inferior frontal gyrus during the analogy task given the
need for inhibition during analogical reasoning (Morrison et al.,
2004; Robin and Holyoak, 1995). Additionally, the relevance of spatial
relations in the analogy task led to a proposed role for parietal cortex
in analogical relative to non-analogical reasoning; conversely, the
need to attend to object identity led to a prediction for greater activity
in fusiform gyrus in the non-analogical, item condition. The major
strengths of our design were the difficulty of the non-analogical
item task and the fact that both analogy and item tasks required the
use of subgoals operating on similar visual stimuli.
To test our primary hypothesis of interest – the contribution of
RLPFC to reasoning – we examined activity within ROIs based on
peak voxels reported in previous fMRI studies of analogy. Both left
and right RLPFC were more active during the analogy condition rela-
tive to the item condition. Because the analogy task alone required in-
tegration of relations, these results suggest that RLPFC activity is more
strongly driven by the need to integrate relational information rather
than coordinate subgoal outcomes, more generally. The task to which
analogical reasoning was compared was, in fact, more difficult than
the analogy condition. Contrasting analogy with a task that is at
least as difficult is rare. We know of only two other studies to have
done so (Krawczyk et al., 2010, 2011), and, in both of these studies,
the greater speed with which participants solved analogies relative
to control problems may have been artificially affected by the smaller
number of possible correct responses in the analogy condition. In the
current study, stimuli in both conditions were nearly perceptually
identical with an equal number of possible responses (2) to each
item. Additionally, both tasks required the coordination of multiple
subgoals. Thus, increased reaction times during the item task could
have been interpreted as reflecting increased demands on subgoal co-
ordination. If RLPFC participates in the coordination of multiple cogni-
tive operations, then we should have observed greater activity within
this region for the item condition. However, ROI analyses revealed the
opposite result: despite being solved more quickly, analogies elicited
greater average activity within left and right RLPFC. This pattern of
Table 1
Results for the whole-brain analysis for analogyNitem contrast.
Brain region HemispherePeak voxel
t-value
Cluster size
(voxels)
XYZ
Inferior frontal gyrus
(pars triangularis)
Middle temporal gyrus
Inferior frontal gyrus
(pars opercularis)
R5.6758 5240 10
R
R
4.33
4.38
34
20
64
52
−47
−5
197
Peaks of activation exceeded pb.001 (uncorrected) threshold, with at least 20
contiguous voxels. Coordinates are reported in standardized MNI space. Peaks that
survived correction for multiple comparisons (pb.05) are in boldface.
Fig. 3. A) Whole-brain activation map for regions that responded more strongly in the
analogy task compared to the item task. Map has been thresholded at α=.05 (t=4.22)
corrected for multiple comparisons with at least 20 contiguous voxels. B) Right and left
empirically-defined RLPFC ROIs for analogyNitem contrast, both psb.05. Although ROI
statistics were computed on average activity, voxel-wise activation is depicted here at
a level of pb.05 (uncorrected). The extent of the ROI is shown in green. C) Right and left
IFG ROIs for analogyNitem contrast, both psb.05. D) Right and left inferior parietal ROIs
for analogyNitem contrast, both psb.05.
Table 2
Results for the region-of-interest analyses.
Region of interest Hemisphere
t-values
p-values (one-tailed)
AnalogyNItem contrast
RLPFC
L
R
L
R
L
R
L
R
2.32
1.97
2.03
2.66
1.81
1.81
.65
.46
.016
.032
.029
.008
.043
.043
.261
.325
Inferior frontal gyrus
Inferior parietal cortex
Superior parietal cortex
ItemNAnalogy contrast
Fusiform gyrusL
R
−1.35
−2.13
.904
.977
Contrasts that are significantly different from zero (pb.05) are in boldface.
5
C.E. Watson, A. Chatterjee / NeuroImage xxx (2011) xxx–xxx
Please cite this article as: Watson, C.E., Chatterjee, A., A bilateral frontoparietal network underlies visuospatial analogical reasoning, Neuro-
Image (2011), doi:10.1016/j.neuroimage.2011.09.030