r Human Brain Mapping 35:1061–1073 (2014) r
The Parahippocampal Gyrus Links the
Default-Mode Cortical Network With the
Medial Temporal Lobe Memory System
Andrew M. Ward,1,2,3Aaron P. Schultz,2,3Willem Huijbers,1,2,3
Koene R.A. Van Dijk,3,4,5Trey Hedden,3,4and Reisa A. Sperling1,2,3,6*
1Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School,
2Department of Neurology, Massachusetts General Hospital, Harvard Medical School,
3Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts
4Department of Radiology, Massachusetts General Hospital, Harvard Medical School,
5Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts
6Center for Alzheimer Research and Treatment, Boston, Massachusetts
Abstract: The default-mode network (DMN) is a distributed functional-anatomic network implicated
in supporting memory. Current resting-state functional connectivity studies in humans remain divided
on the exact involvement of medial temporal lobe (MTL) in this network at rest. Notably, it is unclear
to what extent the MTL regions involved in successful memory encoding are connected to the cortical
nodes of the DMN during resting state. Our findings using functional connectivity MRI analyses of
resting-state data indicate that the parahippocampal gyrus (PHG) is the primary hub of the DMN in
the MTL during resting state. Also, connectivity of the PHG is distinct from connectivity of hippocam-
pal regions identified by an associative memory-encoding task. We confirmed that several hippocam-
pal encoding regions lack significant functional connectivity with cortical DMN nodes during resting
state. Additionally, a mediation analysis showed that resting-state connectivity between the hippocam-
pus and posterior cingulate cortex—a major hub of the DMN—is indirect and mediated by the PHG.
Our findings support the hypothesis that the MTL memory system represents a functional subnetwork
that relates to the cortical nodes of the DMN through parahippocampal functional connections. Hum
Brain Mapp 35:1061–1073, 2014.
C 2013 Wiley Periodicals, Inc.
Keywords: brain mapping; physiology; human; resting state; functional connectivity; brain networks;
Magnetic Resonance Imaging; MTL; Mediation; young adult
Contract grant sponsor: NIA; Contract grant numbers: AG027435,
P01AG036694, P50 AG005134, K24 AG035007, NS002189,
AG040197; Contract grant sponsor: the European Molecular
Biology Organization; Contract grant number: ALTF 318-2011
(W.H.); Contract grant sponsor: the Fidelity Medical Foundation;
the Harvard NeuroDiscovery Center; and the American Health
*Correspondence to: Reisa A. Sperling, Sperling, 221 Longwood
Avenue, Boston, MA 02115. E-mail: firstname.lastname@example.org
Received for publication 4 June 2012; Revised 14 September 2012;
Accepted 12 November 2012
Published online 13 February 2013 in Wiley Online Library
C 2013 Wiley Periodicals, Inc.
The default-mode network(DMN)(Gusnard and
Raichle, 2001; Raichle et al., 2001) is a set of cortical
regions identified by reduced activity during many exter-
nally oriented tasks (Buckner et al., 2008; Shulman et al.,
1997). DMN regions also exhibit coherent fluctuations dur-
ing resting state (Greicius et al., 2003). The DMN has been
implicated in episodic memory function and appears to be
particularly vulnerable to the detrimental effects of aging
and Alzheimer’s disease (AD; e.g., Andrews-Hanna et al.,
2007; Buckner et al., 2005, 2008; Hedden et al., 2009;
Sheline et al., 2010a,b; Sperling et al., 2009). Current rest-
ing-state functional connectivity MRI (fcMRI) studies
remain divided on the exact involvement of the medial
temporal lobe (MTL) in this network at rest. Specifically, it
remains unclear if the hippocampus is directly connected
to the DMN, or if it forms part of a functional subnetwork
that interfaces with the DMN through the parahippocam-
pal gyrus (PHG; Kahn et al., 2008; Vincent et al., 2006).
Interestingly, task-based fMRI studies indicate that MTL
subregions can be dynamically coupled and uncoupled
with the DMN during memory encoding and retrieval
(McCormick et al., 2010; Huijbers et al., 2011; Vannini
et al., 2010), implying context dependent, rather than
static, interactions between the hippocampus and the
DMN. Using resting-state fcMRI in combination with task-
based fMRI, we test the hypothesis that the PHG is the
primary DMN node in the MTL and that the PHG medi-
ates the connectivity between the DMN and MTL struc-
tures engagedin memory
approach allows us to compare MTL activations and DMN
connectivity within modality using functional acquisitions
collected with identical slice prescriptions and parameters
in the same session.
Previous fcMRI studies have reported DMN connectivity
with various MTL subregions, including some combina-
tion of the hippocampus and PHG (e.g., Greicius et al.,
2004; Kahn et al., 2008; Shannon and Buckner, 2004;
Vincent et al., 2006; 2008). However, not all studies have
found evidence of robust DMN-MTL connectivity during
rest (e.g., Greicius, 2008; Sorg et al., 2007). One potential
reason for this discrepancy is that the nodes of the DMN
do not display identical intrinsic activity and the strength
of the connections between these nodes is not homogenous
(Andrews-Hanna et al., 2010; Uddin et al., 2009). Addition-
ally, prior work indicates that anterior and posterior parts
of the hippocampus have different degrees and patterns of
connectivity to the DMN (Kahn et al., 2008; Libby et al.,
2012), possibly contributing to inconsistencies.
Episodic memory is critically dependent on the MTL
and its functional connections to cortex (Milner et al.,
1968; Song et al., 2011; Valenstein et al., 1987). Disconnec-
tion of the MTL is thought to underlie early memory
deficits in AD (Go ´mez-Isla et al., 1996; Hyman et al., 1986).
Task-based fMRI has been used to identify the focal subre-
gions within the MTL that are functionally active during
episodic memory (Chua et al., 2006; Ranganath et al., 2005;
Yassa and Stark, 2008; Zeineh et al., 2003) and altered in
the presence of AD pathology (Small et al., 1999; Sperling
et al., 2009).
Finally, anatomical studies find few direct connections
between hippocampus and cortical DMN regions (Burwell
and Amaral, 1998; Suzuki and Amaral, 1994), but many
between PHG and the DMN (Burwell, 2000; Furtak et al.,
2007; Lavenex and Amaral, 2000; Witter et al., 2000a).
Anatomical data also indicate that the entorhinal cortex,
part of the PHG, mediates the input and output streams to
the hippocampus (Witter et al., 2000b).
Based on these previous functional and anatomic find-
ings, we predict that the hippocampus is not the locus of
functional connectivity between the MTL and the cortical
nodes of the DMN during resting state. Instead, we expect
to find stronger functional connectivity during resting state
between the PHG and cortical nodes of the DMN. Second,
given that the PHG has direct connections to both the
hippocampus and cortical nodes of the DMN and that the
hippocampus can be dynamically coupled and uncoupled
with the DMN (Huijbers et al., 2011; Vannini et al., 2010;
Young and Mcnaughton, 2009), we predict that functional
connectivity between the hippocampus and cortical DMN
nodes during resting state is mediated through the PHG.
MATERIAL AND METHODS
Thirty-one healthy young adults (11 males, 20 females;
age range: 18–28 years; mean age: 23.5 ? 2.3 years) partici-
pated in the study. All subjects were right-handed, native
English speakers with normal or corrected-to-normal
vision. The subjects had no history of psychiatric or neuro-
logical disorders, head trauma, and were not using any
psychoactive medications. Informed consent was obtained
in accordance with guidelines and procedures governed
by the institutional review boards of the Massachusetts
General Hospital and Brigham and Women’s Hospital
(Boston, MA). Data from these subjects have not been pre-
Participants underwent functional MRI on a Siemens
Trio Tim 3.0 Tesla scanner (Siemens Medical Systems,
Erlangen, Germany) equipped with a 12-channel phased-
array head coil. Visual stimuli for the task were generated
using an iBook G4 laptop (Apple Computer, Cupertino,
California) running MacStim 2.5 (WhiteAnt Occasional
Publishing, Melbourne, Australia) and projected to a
screen positioned at the head of the magnet bore and
reflected onto a mirror attached to the head coil. Head
motion was restrained with extendable foam-padded
clamps. Earplugs and noise-reduction headphones were
rWard et al. r
r 1062 r
used to attenuate scanner noise. Functional data were
acquired using a gradient-echo echo-planar pulse sequence
sensitive to BOLD contrast (Kwong et al., 1992; Ogawa
et al., 1992) using the following parameters: TR ¼ 2,000
ms, TE ¼ 30 ms, FA ¼ 90?, 64 ? 64 matrix, FOV ¼ 200
mm, 3.125 ? 3.125 ? 5 skip 1 mm voxels. Thirty inter-
leaved coronal oblique slices aligned perpendicular to the
anterior-posterior commissural plane covered the whole
brain. Functional images were acquired in one run of 196
time points for the resting state, and six runs of 127 time
points for the encoding task.
The data were processed using SPM8 (http://www.fil.
ion.ucl.ac.uk/spm/; version r4290). Each run was slice-
time corrected, realigned to the first volume of each
run with INRIAlign (http://www-sop.inria.fr/epidaure/
software/INRIAlign/; Freire and Mangin, 2001; Freire
et al., 2002), normalized to the MNI 152 EPI template
(Montreal Neurological Institute, Montreal, Canada), and
smoothed with an 6 mm FWHM Gaussian kernel. Finally,
the data for each subject were manually checked to iden-
tify registration errors and signal dropout. No subjects had
An additional set of preprocessing steps was carried out
to enable analysis of functional correlations between
regions (see Fox et al., 2005; Vincent et al., 2006). A series
of regressors from the resting-state data were entered into
a multiple regression analysis. These were: motion param-
eters as estimated by the six realignment parameters, aver-
age signal from a deep white matter mask, average signal
from a ventricle mask, average signal from the whole
brain mask, and the first derivative of each of these nui-
sance regressors. The residuals from this model were then
linearly detrended and low-pass filtered with a second-
order Butterworth filter with a frequency cutoff of 0.08 Hz.
These processed data were used as the basis for all seed-
based correlation maps.
As part of hypothesis-driven analysis to explore DMN
connectivity with the MTL, we created seed-based correla-
tion maps using 10-mm diameter spherical seeds located
in the PCC at MNI coordinates [0 ?53 26], and inferior in
retrosplenial cortex (RSC) at MNI coordinates [0 ?51 15].
The PCC is known to be a key region within the DMN
(Fransson and Marrelec, 2008), and has been used as a
seed region in multiple publications (e.g., Andrews-Hanna
et al., 2007; Hedden et al., 2009; van Dijk et al., 2010). RSC
is known to have strong connectivity with the hippocam-
pal formation (Kobayashi and Amaral, 2003; Yeo et al.,
2011), and has been functionally dissociated from the PCC
(Huijbers et al., 2010). Seed-based correlation maps were
created by first averaging the BOLD signal across all the
voxels within the seed region. Next, this averaged signal
was correlated with the preprocessed signal for every
voxel in the brain. Finally, the maps were Fisher-Z trans-
formed with a hyperbolic arc tangent geometric transform
to increase normality of the distribution of values for sec-
ond-level analyses. We found highly similar patterns of
connectivity with similar peaks in the MTL for the PCC
and RSP seed maps (Table I).
To further test whether the results were a product of the
choice of PCC seed location or could be generalized to the
DMN as a whole, we used an independent component
analysis (ICA) to isolate the DMN. We computed a spatio-
temporal ICA using the GIFT (http://mialab.mrn.org/soft-
(MathWorks, Natick, MA) package. Data that were prepro-
cessed up to and including spatial smoothing were passed
into GIFT where they were first intensity normalized.
Next, data were reduced in a first-pass principal compo-
nent analysis step with 40 principal components. The
et al., 2004) MATLAB
TABLE I. Labels, locations, and t values of peaks in the
MTL of resting-state connectivity and task activity
MNI labelH Coordinates
ParahippocampusL[?25 ?22 ?22]
[?15 ?28 ?16]
[27 ?19 ?25]
[18 ?7 ?37]
ParahippocampusL[?24 ?22 ?27]
[?18 ?10 ?34]
[24 ?19 ?28]
[30 ?34 ?13]
[?23 ?19 ?27]
[27 ?19 ?22]
[27 ?34 ?13]
HCH > R
HippocampusL[?19 ?7 ?16]
[?18 ?34 ?4]
[32 ?20 ?17]
[?24 2 ?25]
[18 ?4 ?19]
[?42 ?50 ?19]
[38 ?53 ?21]
MNI labelHALE (?10?3)
[?22 ?10 ?16]
[18 ?8 ?16]
[?42 ?46 ?22]
[44 ?52 ?14]
H ¼ hemisphere, L ¼ left, R ¼ right, ALE ¼ activation likelihood
rDMN-MTL Connectivity r
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Infomax ICA algorithm was used to generate 20 independ-
ent components, and the GICA3 reconstruction algorithm
was used to back-reconstruct spatial component maps and
time courses for each subject. Individual subject compo-
nent loadings were not normalized post hoc.
The component matching the DMN was identified first
through visual inspection by five independent raters. All
raters indicated that the ICA produced a single DMN com-
ponent and selected the same component as the DMN.
This component’s relationship to the PCC and RSC seed-
derived DMNs was confirmed using a goodness of fit
analysis. The goodness of fit metric was computed by first
creating a binary mask from the positive values of the
group PCC and RSC seed t-maps, respectively. Goodness
of fit for each ICA component was calculated by taking
the mean of the value of voxels within the DMN template
mask minus the mean of the value of voxels outside the
DMN template mask (Greicius et al., 2004). The selected
DMN component was an eightfold better match than the
next best fitting component for both PCC and RSC seed-
maps, confirming that the DMN did not split into multiple
components (see Damoiseaux et al., 2006 for discussion of
one versus multiple ICA DMN components).
The ICA produced back-projected time-courses for each
component for each subject. The individual subject time-
courses for the selected DMN component were used as seed
time-courses to create a new set of connectivity maps. That
is, for this analysis, rather than choose a small spherical
seed region, we used the signal decomposition of the ICA to
isolate the spatiotemporally defined DMN time course for
each subject. These time courses were used to generate
Fisher-Z transformed correlation maps for each subject,
which allowed for a direct comparison between the ICA
results and the seed-based connectivity maps (see Fig. 1).
To more specifically determine the functional connectivity
relationship, if any, between regions of the hippocampus
involved in successful memory encoding and the cortical
nodes of the DMN, we defined a bilateral ‘‘entire’’ hippo-
campal seed (all-hip) based on the High Confidence Hits >
Repeated contrast (HCH>R; see ‘‘Task-Based Analysis’’ sec-
tion for details). Specifically, the seed was defined as a bi-
nary conjunction of the contrast map using an uncorrected
threshold of P < 0.001 and the anatomical boundaries of the
hippocampus defined by the AAL MNI atlas (Tzourio-
Mazoyer et al., 2002). To compare hippocampus connectiv-
ity to PHG connectivity, we created a similar bilateral PHG
seed region (para-hip) from the conjunction of the seed-
derived DMN using an uncorrected threshold of P < 0.001
and the anatomical boundaries of the PHG. These masks
allow us to directly compare MTL subregions involved in
successful memory formation with MTL subregions that ex-
hibit connectivity with cortical DMN nodes at a liberal
threshold while still loosely restricting between the ana-
tomic location of the hippocampus and PHG.
Kahn et al. (2008) defined two distinct cortical networks
that converge on the hippocampal formation. The first
network converges on the anterior hippocampus, and
includes the anterior temporal lobe, regions of the middle
temporal gyrus, and the perirhinal/entorhinal cortices. The
second network converges on the posterior hippocampus,
and includes the lateral parietal cortex, RSC, PCC, and
medial prefrontal cortex—all of which are cortical DMN
regions. To test this anterior–posterior split, we constructed
two additional seeds. These seeds are subsets of the all-hip
mask. They were created as a binary conjunction mask of a
10-mm sphere drawn around the most anterior and most
posterior HCH>R peaks in the left hippocampus (MNI
[?19, ?7, ?16] and [?18, ?34, ?4]) and the all-hip mask.
Only the left hippocampus contained both an anterior and
posterior peak. These conjunction masks limit our explora-
tion to regions activated during successful memory encod-
ing, while focusing on any difference between anterior and
posterior hippocampus. We also used these masks to
extract data from task and rest for the purpose of statistical
comparisons. These extracted data were normalized using
Fisher’s r-to-z transformation (Zar, 1996). Para-hip/PCC
connectivity was tested against hippocampus/PCC connec-
tivity using a within-subjects model. We also tested para-
hip task activations against hippocampus task activations
using an identical within-subjects model.
The top panel shows comparison of the PCC (teal) and ICA
(yellow) seed maps in a sagittal (left: MNI x ¼ 0) and coronal
(right: z ¼ 26) plane. Overlap is shown in purple. The bottom
panel shows comparison (at MNI [x ¼ ?18, y ¼ ?18]) of
HCH>R activations (red) and activation likelihood estimation
meta-analytic (Kim, 2011) activations (blue). Overlap is shown in
green. All maps are thresholded at a < 0.01 FDR corrected.
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All four of these seeds—entire hippocampus (all-hip),
anterior hippocampus (ant-hip), posterior hippocampus
(post-hip), and PHG (para-hip)—were used to create
whole-brain correlation maps to examine patterns of func-
tional connectivity between these regions and the entire
cerebral cortex. Each of the hippocampus seed-based maps
was then tested against the PHG seed-based map with a
within-subjects design to identify regions of significant dif-
fering connectivity. To correct for multiple comparisons,
we first Bonferroni corrected our initial a < 0.05 to control
for multiple tests (Abdi, 2007). The whole-brain images
were then corrected using false discovery rate (FDR; Geno-
vese et al., 2002) correction using the corrected a < 0.01.
Finally, to determine if the interface between the regions
of the hippocampus involved in successful memory forma-
tion and the DMN are modulated by the PHG, we per-
formed a series of simple and partial correlations. These
correlations were based on resting-state time series data
extracted from the previously defined all-hip, ant-hip,
post-hip, para-hip seeds, and the spherical PCC ROI
centered at MNI [0 ?53 26]. We examined the direct
relationship between hippocampus, PHG, and PCC. Addi-
tionally, we examined the partial correlations between one
MTL structure and the PCC while controlling for the
other. This allows us to conduct a mediation analysis. In
this analysis, the conditions for mediation are met if: (1)
all of the pairwise correlations are significantly greater
than zero, (2) the correlation of the hypothesized mediator
(B) and dependent variable (C) while controlling for the
independent variable (A) is significant, and (3) the correla-
tion of A and C while controlling for B is not significant
(Mackinnon et al., 2007). The fulfillment of these conditions
indicates a system whereby the connectivity observed
between A and C primarily reflects a transitive pathway
A-B-C, rather than a direct pathway A-C (see Fig. 5).
The fMRI memory paradigm was a previously pub-
lished face-name associative encoding mixed block- and
event-related design (Sperling et al., 2009). Briefly, the task
consisted of six runs of four 40 s alternating blocks of
novel and repeated face-name pairs with 25 s fixation
between the blocks. Each novel block consisted of seven
face-name pairs with jittered fixation ISI, resulting in 84
total gender- and age-balanced novel face-name pairs.
Repeated blocks consisted of alternating presentation of
the same two gender-balanced face-name pairs. The two
repeated face-name pairs are never presented in novel
blocks, nor are novel face-name pairs ever repeated.
Encoding success of novel face-name pairs was tested post
hoc with a two-alternative forced-choice test, followed by
a high/low confidence ranking for each pair. The mean
correct responses across the subjects were 84.3 ? 8.7%.
The mean high confidence correct responses were 62.1 ?
The task analysis removed frequencies with a period of
less than 260 s. In addition, bad volume regressors were
included to negate volumes that had a global signal value
beyond 2.5 standard deviations for the run, translational
movement exceeding 0.75 mm per TR, and/or rotational
movement exceeding 1.5?per TR. Outlier volume regres-
sors consisted of an additional column in the design
matrix for each identified outlier volume that consisted of
a value of 1 for the outlier volume and zeros everywhere
else. After data screening, no subjects were excluded, and
all participants had four good runs that were included in
the first-level analysis.
(HCH>R) were created for each subject across all runs
included in the analysis. A whole brain one-sample t-test
on the set of 31 participants was used to create a group-
level map. All second-level analyses were performed with
custom in-house GLM scripts (http://nmr.mgh.harvar-
GLM_Flex.html). These scripts were designed to function
identically to SPM8 with the exception that not all data
points needed to be present to analyze a particular voxel.
If any voxel contained 15 or more values (maximum was
31), it was analyzed. No data were missing in the MTL,
PCC, or lateral parietal cortex. Some data were missing in
frontal regions, likely due to signal dropout.
The PCC seed maps show resting-state connectivity
with multiple regions of the DMN, including connectivity
to medial prefrontal cortex, left and right lateral parietal
cortex (LPC), left and right lateral temporal cortex, and
MTL. Within the MTL, the connectivity was most signifi-
cant within the PHG, exhibiting bilateral peaks (Table I).
We did not observe significant (a < 0.01, FDR corrected)
map-level functional connectivity between the PCC seed
and hippocampus during resting state. As the lack of sig-
nificant connectivity at rest between major cortical nodes
of the DMN and hippocampus may have been due to the
choice of an a priori cortical seed region as hub of the
DMN, we also took a data-driven approach in which we
used group ICA to define a DMN time course for each
subject. The ICA generated a group-level map that was
virtually identical to the group PCC seed-based map (Fig.
1, Table I) suggesting that the findings using the PCC seed
were not attributable to idiosyncrasies of the seed location.
The results from the HCH>R task contrast demon-
strated significant bilateral activity peaks in hippocampus
(Table I). Peaks were also found bilaterally in the amyg-
dala and fusiform gyrus. No peaks were found in the
rDMN-MTL Connectivity r
r 1065 r
PHG (see Table I). Previous work has indicated that struc-
tures recruited in support of memory tasks will shift
depending on the nature of the task (Davachi, 2006; Ran-
ganath, 2010). To test if our task results differ significantly
from frequent activations across many fMRI encoding
tasks, we compared our task activations with activation
likelihood estimation (ALE; Laird et al., 2005) maps from
74 fMRI studies using a subsequent-memory approach
(Kim, 2011). Activations in the MTL from our task (see red
area in Fig. 1) are very similar to the ALE-maps (blue in
Fig. 1, overlap in green), but include a large area of poste-
rior hippocampus that is not significantly activated using
the meta-analytic approach (Fig. 1, Table I).
Task-and Resting-State Locations
A comparison between the group map of HCH>R and
the PCC z-maps (Fig. 2A–C) revealed a distinct difference
in the location of task activation in the MTL versus PCC
resting-state connectivity within the MTL. The MTL peaks
for memory task-related activity (MNI [?19, ?7, ?16]) and
PCC connectivity during rest (MNI [?25, ?22, ?22]) corre-
sponded to the expected atlas coordinates of the hippo-
campus and PHG, respectively. The overlap of these two
maps contained neither peaks of task activation nor peaks
of resting-state functional connectivity, suggesting minimal
functional overlap of the two distinct foci.
To examine the functional/anatomic boundary between
the hippocampus and PHG, we first illustrated the spatial
overlap between task and rest in the MTL at three differ-
ent thresholds for display purposes (P < 0.01, P < 0.001,
and P < 0.0001 uncorrected Fig. 2A–C). Then, we
evaluated the relative contribution of task-evoked activity
and resting-state connectivity in the MTL. We took 20
evenly spaced samples from 6 mm ROIs from each
subject between the task-derived left hippocampus peak
(MNI [?19, ?7, ?16]) and the resting state left PHG peak
(MNI [?25, ?22, ?22]). This vector ran linearly from
peak to peak. We normalized the extracted values from
each dataset by median positive value to allow for visual
comparisons of task activity and resting-state connectiv-
ity. The resulting plot (Fig. 2D) displays an anatomic
dissociation between task activity and resting-state con-
nectivity. Most importantly, as we travel along this vector
across the hippocampus/PHG anatomic boundary, we
observe a shift from task activity-dominant to resting-
state connectivity dominant. To explicitly test this distinc-
tion, we examined the connectivity of the para-hip,
all-hip, ant-hip, and post-hip seeds defined previously. In
resting state, Para-hip/PCC connectivity was significantly
greater than any hippocampus seed/PCC connectivity
(P < 0.001; Table II). In task, para-hip activation was
significantly less than any hippocampus seed activation
(P < 0.05; Table II).
Spatial comparison of task activity and DMN connectivity. Panels
A, B, and C display the task and PCC seed maps at varying
thresholds in the sagittal plane (MNI x ¼ ?25). Panel A is
thresholded at P < 0.01, panel B at P < 0.001, and panel C at P
< 0.0001 uncorrected. Red areas show significant task activation
and blue areas show significant connectivity with the PCC seed.
Green areas show overlap between task activation and PCC
connectivity. The overlap region is small, runs the border
between the hippocampus and parahippocampus, and does not
contain any peaks. Panel D displays the median-normalized val-
ues extracted from these maps along a vector running between
the hippocampal peak from task activations and the parahippo-
campal peak from PCC connectivity.
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Next, we computed whole-brain seed-based correlation
maps using the all-hip, para-hip, ant-hip, and post-hip
seeds defined previously. As shown in Figure 3A, the
para-hip seed generated a canonical DMN map, whereas
none of the task-derived hippocampal seeds exhibited
significant functional connectivity with the standard corti-
cal DMN nodes (Fig. 3B–D; Table III). Paired samples t-
tests between each hippocampus seed map and the para-
hip seed map (Fig. 4) show these maps to be significantly
different (a < 0.01, FDR corrected) in the major regions of
cortical DMN connectivity. Notably, neither the ant-hip
nor post-hip seed exhibited connectivity with the cortical
nodes of the DMN with similar magnitude or spatial
extent as the para-hip seed. This suggests that there is no
difference in connectivity to cortical DMN nodes within
the hippocampus. However, there is a significant differ-
ence in connectivity to cortical DMN nodes between the
hippocampus and the PHG.
Finally, to explore whether the pattern of connectivity
relationships support a model in which PHG mediates the
relationship between the hippocampus and the DMN, we
computed a series of partial correlations for each subject
and tested whether these correlation values were signifi-
cant (i.e., >0 connectivity). First, we correlated the all-hip
with the PCC, the para-hip with the PCC, and the all-hip
TABLE II. Seed-based analysis of within-modality
differences in connectivity and activity between regions
in the MTL
connectivity Task activations
0.20 ? 0.12
0.07 ? 0.12
0.09 ? 0.14
0.05 ? 0.12
0.65 ? 1.13
1.51 ? 1.27
2.57 ? 1.93
1.26 ? 1.14
#denotes P < 0.05
**denotes P < 0.001, *denotes P < 0.01, and
MTL seeds and resulting functional connectivity maps. The panels display connectivity maps
seeded from para-hip (A, blue), all-hip (B, green), ant-hip (C, purple), and post-hip (D, yellow)
seeds. Seeds are displayed in the sagittal plane (MNI x ¼ ?23). Connectivity maps are displayed
below each seed in the axial (MNI z ¼ ?26) and sagittal (MNI x ¼ 0) planes and are thresh-
olded at a < 0.01 FDR corrected.
rDMN-MTL Connectivity r
r 1067 r
with the para-hip (Fig. 5A). All of these correlations were
models significantly greater than zero [t(30) > 3]. How-
ever, all-hip was not significantly correlated with the PCC
when controlling for para-hip (Fig. 5B), whereas the para-
hip was highly significantly correlated with the PCC while
controlling for the all-hip seed (Fig. 5C). This mediation
analysis indicates that the majority of the variance shared
between the hippocampus and PCC is contained within
the PHG–PCC relationship, consistent with a model where
the connection between hippocampus and PCC is indirect
and mediated by the PHG. To determine whether the
same pattern was present in other hippocampal seeds, we
repeated this analysis using ant-hip and post-hip seeds,
and the results statistically equivalent. Overall, these pat-
terns are consistent with the hypothesis of the PHG as a
major node of the DMN.
We found evidence for functional connectivity between
major cortical nodes of DMN and specific subregions in the
MTL, consistentwith previous
Andrews-Hanna et al., 2007; Buckner et al., 2008; Hedden
et al., 2009; Vincent et al., 2006). We extended these findings
by using a functional localizer that activated the hippocam-
pus, and showed a clear dissociation within the MTL
between the locations of hippocampal activity during mem-
ory encoding and PHG connectivity with the DMN during
rest. This dissociation of activation and connectivity was
robust across multiple seeds and analysis methods. Finally,
we extend findings that PHG and hippocampus have differ-
ent patterns of cortical connectivity (Kahn et al., 2008, Libby
et al., 2012) by demonstrating that the PHG mediates the
connectivity between the hippocampus and the posterior
cingulate cortex (PCC), the posterior cortical hub of the
Agreement With Previous Anatomic
Our functional connectivity findings in humans parallel
anatomic studies of connectivity conducted in macaque
and rat. Anatomical studies have established that PHG has
many reciprocal connections with cortex (Burwell, 2000;
Furtak et al., 2007; Lavenex and Amaral, 2000; Witter
et al., 2000a). However, the hippocampus itself has few
direct cortical connections (Burwell and Amaral, 1998;
Suzuki and Amaral, 1994; van Strien et al., 2009). It is im-
portant to note that these studies of monosynaptic connec-
tivitymay not entirely
polysynaptic connections that underlie human functional
connectivity. However, the relevance of those structural
TABLE III. Clusters and peaks from MTL seed-derived resting-state correlation maps
SeedLobeRegionH Coordinates (MNI)t(30)mm3
Middle, inferior, temporal pole, insula,
fusiform, olfactory, thalamus, vermis,
Orbital middle, superior medial
Superior, middle, temporal pole, fusiform,
caudate, lingual, putamen, amygdala,
vermis, hippocampus, PHC
Fusiform, thalamus, calcarine,
L[?3 59 ?6]
[9 ?31 ?18]
[?3 ?58 26]
[2 58 20]
[21 ?7 ?19]
L[?6 ?50 8]
[?8 ?50 4]
Parietal L/R[?3 ?34 35]5.97 801
Paired sample t-tests between the para-hip seed maps versus all-
hip (A), ant-hip (B), and post-hip (C) seed maps. Maps are dis-
played in the axial (top: z ¼ 26), sagittal (middle: x ¼ 0), and
coronal (bottom: y ¼ ?63) planes and are thresholded at a <
0.01 FDR corrected.
rWard et al. r
r 1068 r
findings are supported by fcMRI analyses showing that
macaques and rats have fcMRI-derived homologs to major
posterior DMN nodes (Lu et al., 2012; Margulies et al.,
2009; Rilling et al., 2007; Vincent et al., 2007). Additionally,
Catani et al. (2003) have also shown similarities between
human and macaque MTL anatomy using diffusion tensor
imaging. These anatomical findings implicate the PHG as
a DMN node, which we have confirmed in humans with
functional connectivity fMRI.
The MTL Memory System is Distinct from, but
Interfaces with the DMN
When using the task-defined hippocampal seed regions
(Fig. 3C–E), we see very little functional connectivity with
cortex, but a high degree of bilateral local coherence. Nota-
bly, this is true for both the anterior- and posterior-specific
hippocampus seeds. This parallels previous findings that
indicate that the hippocampus is highly correlated across
hemispheres (Buckner et al., 2008; Kahn et al., 2008; Vin-
cent et al., 2006; Wang et al., 2010). Given the weak cortical
functional connectivity found when seeding the hippocam-
pus, our findings imply that the regions of the hippocam-
pus engaged in encoding are not functionally connected to
major cortical DMN nodes during rest, but rather are part
of a functional subnetwork whose interface with the DMN
is mediated through the PHG. Additionally, connectivity
measures have been shown to be dynamic during resting-
state scans (Chang and Glover, 2010; Jones et al., 2012),
possibly due to spontaneous memory processes, which in
turn might also reflect coupling and decoupling of the
DMN and MTL memory system.
The MTL memory system is likely composed of several
subnetworks that support distinct memory processes
(Eichenbaum et al., 2007; Ranganath and Richey 2012;
Yassa and Stark 2008). Multiple task-based fMRI studies
have confirmed the role of the hippocampus during mem-
ory encoding, particularly in associative or relational
encoding (e.g., Hannula and Ranganath, 2008; Zeineh
et al., 2003). Other memory tasks, including spatial mem-
ory or recollected retrieval also activate MTL regions,
although the foci differ (e.g., Poppenk and Moscovitch,
2011; Spaniol et al., 2009). Previous work using resting-
state fcMRI has described the MTL regions involved in
memory as a subnetwork of the DMN (Vincent et al.,
2008), but did not address this hypothesis within a mem-
ory task paradigm. In our view, the DMN exhibits condi-
tion-dependent dynamic functional connectivity with the
MTL memory systems. Specifically, in the context of mem-
ory encoding and retrieval, a change in the relationship
between activity in the MTL and cortical nodes of the
DMN has been observed. This is typically characterized by
inversely correlated activity patterns during encoding
(MTL will activate and DMN will deactivate) and posi-
tively correlated activity patterns during retrieval (both
MTL and DMN will activate) (Daselaar et al., 2009; Huijb-
ers et al., 2011; Vannini et al., 2010).
Further support for the distinction between MTL-based
memory systems and the DMN can be found in the multi-
ple pathologies that show DMN disruption but not mem-
ory impairment. Changes in DMN connectivity have been
widely reported in a range of neurological disorders,
including depression (Greicius et al., 2007; Sheline et al.,
2010b), autism spectrum disorders (Assaf et al., 2010;
Cherkassky et al., 2006; Kennedy and Courchesne, 2008),
schizophrenia (Bluhm et al., 2007; Rotarska-Jagiela et al.,
2010; Zhou et al., 2007), and obsessive-compulsive disorder
(Jang et al., 2010). However, many of these disorders do
not manifest episodic memory impairment as the most sa-
lient clinical feature. Additionally, these results focus on
differences in functional connectivity among cortical nodes
of the DMN. The majority of functional connectivity stud-
ies in AD and mild cognitive impairment have reported
specific evidence of altered connectivity between the DMN
and the MTL (Celone et al., 2006; Greicius et al., 2004; Pet-
rella et al., 2011; Rombouts et al., 2005; Sorg et al., 2007),
suggesting that disconnection between these two systems
may be more specific for amnestic disorders. Because corti-
cal DMN dysfunction does not appear to be specific to
Models of MTL-DMN mediation.
rDMN-MTL Connectivity r
r 1069 r
amnestic disorders, it may be a more general indicator of
synaptic pathology (Buckner et al., 2008).
Previous studies have indicated that lesions to the PHG
that spare the hippocampus can also cause major memory
deficits (Suzuki et al., 1993; Zola-Morgan et al., 1989). A
study of anatomic connectivity indicated that the input
and output streams of the hippocampus are mediated
through the superficial and deep layers, respectively, of
the entorhinal cortex (Witter et al., 2000b). Recent work in
rats indicates that chemical inhibition of neural activity in
the PHG disrupts memory retrieval of previously condi-
tioned behavior (Morrissey et al., 2012). Additionally,
fcMRI studies of patients with damage to the hippocam-
pus find reduced connectivity in the ipsilesional regions of
the MTL, but not with the cortical nodes of the DMN
(Frings et al., 2009). Further, patients with specific hippo-
campal damage showed no difference in cortical thickness
in DMN regions when compared with controls (Bernhardt
et al., 2008), consistent with intact connections between the
PHG and DMN. These findings indicate that previous
observations of hippocampus/DMN connectivity (e.g.,
Andrews-Hanna et al., 2010; Poppenk and Moscovitch,
2011) may reflect connectivity mediated through the PHG.
This, collectively, supports our finding that the PHG
serves as the interface between the MTL memory system
and cortical nodes of the DMN and suggests that memory
deficits caused by direct insult to PHG may be related to
disruption of critical connections between the MTL mem-
ory system and the DMN.
The fMRI data were relatively low resolution (3.125 ?
3.125 ? 6) to achieve whole-brain coverage in the oblique
coronal plane, and the analyses were conducted in com-
mon MNI atlas space. Low-resolution images may make
precise anatomic localization difficult, and nonlinear nor-
malization to group space may result in localization errors.
However, no localization errors were observed. Addition-
ally, our functional slices sample perpendicular to the
anterior-posterior commissural plane and we are able to
use the task analysis as a within-modality functional local-
izer. Our slice prescription is optimized to observe MTL
activity during either task or rest. This allows excellent
separation in the coronal plane as well as a direct compari-
son with resting-state connectivity using known hippo-
campal engagement during task.
Our finding that PHG serves as mediator between the
cortical DMN nodes and the hippocampus proper sup-
ports the hypothesis that early pathological changes within
the PHG may isolate the hippocampus from the DMN via
changes in PHG-DMN connectivity, rather than direct
changes in hippocampus-DMN connections (Go ´mez-Isla
et al., 1997; Hyman et al., 1986). It is possible that dis-
rupted connectivity between these subnetworks leads to
hippocampal hyperactivation and associated failure to
deactivate posteromedial cortices during memory encod-
ing (Miller et al., 2008; Sperling et al., 2009). A recent find-
ingof CA3/dentate hyperactivity
hypoactivity in patients with amnestic mild cognitive
impairment suggests that this interface is critically impor-
tant for memory tasks (Yassa et al., 2010b). We have also
recently found evidence that hippocampal hyperactivity is
associated with thinning in the entorhinal cortex and
DMN regions and with the degree of memory impairment
in patients with early mild cognitive impairment (Putcha
et al., 2011). Finally, recent work indicating that tau pa-
thology can propagate from one neuron to another along
network connections (de Calignon et al., 2012; Liu et al.,
2012), as well as evidence that neurodegeneration proceeds
along functionally connected networks (de Calignon et al.,
2012; Liu et al., 2012; Pievani et al., 2011; Seeley, 2011; See-
ley et al., 2009), may link early focal MTL pathology, such
as neurofibrillary tangle formation and neuronal loss, to
dysfunction of large-scale networks distributed throughout
Our finding that the PHG, rather than the hippocampus
proper, is functionally coupled to the DMN at rest has sev-
eral implications. First, it suggests that the hippocampus is
part of a distinct MTL memory system that interfaces
with, but is not directly part of, the DMN. Second, the
PHG appears to modulate functional connectivity between
cortical DMN nodes and the hippocampus, which is con-
sistent with previously published patterns of anatomical
connectivity. Finally, our findings may have implications
for the role of early PHG pathology in the disconnection
of the DMN from the hippocampus proper in AD. If the
PHG is in fact the nexus linking the MTL and cortical
nodes of the DMN, then sensitive measures of PHG
connectivity may prove to be a particularly promising
biomarker of early AD-related network dysfunction.
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