Article

Local Functional Connectivity as a Pre-Surgical Tool for Seizure Focus Identification in Non-Lesion, Focal Epilepsy

Department of Radiology, University of Washington Seattle, WA, USA
Frontiers in Neurology 05/2013; 4:43. DOI: 10.3389/fneur.2013.00043
Source: PubMed

ABSTRACT

Successful resection of cortical tissue engendering seizure activity is efficacious for the treatment of refractory, focal epilepsy. The pre-operative localization of the seizure focus is therefore critical to yielding positive, post-operative outcomes. In a small proportion of focal epilepsy patients presenting with normal MRI, identification of the seizure focus is significantly more challenging. We examined the capacity of resting state functional MRI (rsfMRI) to identify the seizure focus in a group of 4 non-lesion, focal (NLF) epilepsy individuals. We predicted that computing patterns of local functional connectivity (fc) in and around the epileptogenic zone combined with a specific reference to the corresponding region within the contralateral hemisphere would reliably predict the location of the seizure focus. We first averaged voxel-wise regional homogeneity (ReHo) across regions of interest (ROIs) from a standardized, probabilistic atlas for each NLF subject as well as 16 age and gender matched controls. To examine contralateral effects, we computed a ratio of the mean pair-wise correlations of all voxels within a ROI with the corresponding contralateral region (InterRegional Connectivity - IRC). For each subject, ROIs were ranked (from lowest to highest) on ReHo, IRC and the mean of the two values. At the group level, we observed a significant decrease in the rank for ROI harboring the seizure focus for the ReHo rankings as well as for the mean rank. At the individual level, the seizure focus ReHo rank was within bottom 10% lowest ranked ROIs for all 4 NLF epilepsy patients and 3 out of the 4 for the IRC rankings. However, when the two ranks were combined (averaging across ReHo and IRC ranks and scalars), the seizure focus ROI was either the lowest or second lowest ranked ROI for 3 out of the 4 epilepsy subjects. This suggests that rsfMRI may serve as an adjunct pre-surgical tool, facilitating the identification of the seizure focus in focal epilepsy.

Full-text

Available from: Wanpracha Chaovalitwongse, May 07, 2014
ORIGINAL RESEARCH ARTICLE
published: 01 May 2013
doi: 10.3389/fneur.2013.00043
Local functional connectivity as a pre-surgical tool for
seizure focus identification in non-lesion, focal epilepsy
K. E. Weaver
1,2
*,W. A. Chaovalitwongse
1,2,3
, E. J. Novotny
2,4
, A. Poliakov
5
,T. G. Grabowski
1,2,6
and
J. G. Ojemann
2,7,8
1
Department of Radiology, University of Washington, Seattle, WA, USA
2
Integrated Brain Imaging Center, University of Washington, Seattle, WA, USA
3
Industrial and Systems Engineering, University of Washington, Seattle, WA, USA
4
Neurology, Seattle Childrens Hospital, Seattle, WA, USA
5
Radiology, Seattle Childrens Hospital, Seattle, WA, USA
6
Department of Neurology, University of Washington, Seattle, WA, USA
7
Department of Neurological Surgery, University of Washington, Seattle, WA, USA
8
Neurosurgery, Seattle Childrens Hospital, Seattle, WA, USA
Edited by:
Mark Holmes, University of
Washington, USA
Reviewed by:
Sandrine DeRibaupierre, University of
Western Ontario, Canada
Mario A. Vanegas, Instituto Nacional
de Neurologia y Neurocirugia, Mexico
*Correspondence:
K. E. Weaver, Department of
Radiology, University of Washington,
1959 NE Pacific Street, Box 357115,
Seattle, WA 98195, USA.
e-mail: weaverk@uw.edu
Successful resection of cortical tissue engendering seizure activity is efficacious for the
treatment of refractory, focal epilepsy. The pre-operative localization of the seizure focus
is therefore critical to yielding positive, post-operative outcomes. In a small proportion of
focal epilepsy patients presenting with normal MRI, identification of the seizure focus is
significantly more challenging. We examined the capacity of resting state functional MRI
(rsfMRI) to identify the seizure focus in a group of four non-lesion, focal (NLF) epilepsy
individuals. We predicted that computing patterns of local functional connectivity in and
around the epileptogenic zone combined with a specific reference to the corresponding
region within the contralateral hemisphere would reliably predict the location of the seizure
focus. We first averaged voxel-wise regional homogeneity (ReHo) across regions of inter-
est (ROIs) from a standardized, probabilistic atlas for each NLF subject as well as 16 age-
and gender-matched controls. To examine contralateral effects, we computed a ratio of the
mean pair-wise correlations of all voxels within a ROI with the corresponding contralateral
region (IntraRegional Connectivity IRC). For each subject, ROIs were ranked (from lowest
to highest) on ReHo, IRC, and the mean of the two values. At the group level, we observed
a significant decrease in the rank for ROI harboring the seizure focus for the ReHo rankings
as well as for the mean rank. At the individual level, the seizure focus ReHo rank was
within bottom 10% lowest ranked ROIs for all four NLF epilepsy patients and three out of
the four for the IRC rankings. However, when the two ranks were combined (averaging
across ReHo and IRC ranks and scalars), the seizure focus ROI was either the lowest or
second lowest ranked ROI for three out of the four epilepsy subjects. This suggests that
rsfMRI may serve as an adjunct pre-surgical tool, facilitating the identification of the seizure
focus in focal epilepsy.
Keywords: resting state fMRI, functional connectivity, non-lesion, focal epilepsy, ReHo, contralateral, pre-operative
evaluation, epilepsy surgery
INTRODUCTION
Current standards of care for the treatment of pharmacoresis-
tant, focal epilepsy includes the surgical resection of epileptogenic
cortex. Typically, the tissue targeted for resection encompasses an
extended area around the seizure focus believed to be involved
in the propagation of epileptiform discharges, generally referred
to as the epileptogenic zone (Rosenow and Lüders, 2001; Laufs,
2012). The benefits of epilepsy surgery have clearly been estab-
lished. Numerous prospective as well as longitudinal studies have
shown that higher rates of seizure freedom, improved quality of
life, and decreased long-term remission rates are associated with
successful surgical intervention (Wiebe et al., 2001; Spencer and
Huh, 2008; de Tisi et al., 2011).
The precise localization of the seizure focus and the extended
epileptogenic zone is therefore critical to yielding positive, post-
operative outcomes. Pre-surgical evaluations aimed at identifying
the seizure focus are comprised of any number of interdisci-
plinary approaches, including electrophysiological investigations
[e.g., electroencephalography and less frequently sub-dural elec-
trophysiology such as electrocorticography (ECoG) or stereoelec-
troencephalography], traditional neuropsychological evaluation,
modern structural [e.g., structural magnetic resonance imag-
ing (MRI)], metabolic [e.g., [
18
F]fluoro-2-deoxy-glucose positron
emission tomography (FDG-PET)], and functional imaging based
approaches (e.g., functional MRI). The typical clinical evaluation
identifies sites of pathology from structural-based MR scans and
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Weaver et al. Local fcfMRI in epilepsy
probes surrounding tissue for epileptogenic potential using a com-
bination of the aforementioned modalities. However, in a few
patients (i.e., approximately 25% of all qualifying surgical candi-
dates), structural imaging is normal (i.e., an absence of qualitative,
gross pathology Duncan, 2010). In these non-lesional cases,
seizure localization presents an additional challenge and clinicians
must rely more heavily on alternative approaches (Siegel et al.,
2001; Jayakar et al., 2008).
[18F]fluoro-2-deoxy-glucose positron emission tomography,
which has traditionally been a widely used pre-surgical evalua-
tive tool, plays a particularly important role in the absence of
identified structural abnormalities (Mauguière and Ryvlin, 2004).
In cases of refractory, non-lesional epilepsy, identification of a
focal area of hypometabolism may reflect candidate seizure focus
sites. It is not uncommon however to find hypometabolic regions
outside the suspected region of interest (ROI). Thus, FDG-PET
hypometabolic regions are frequently used to guide ECoG record-
ings. During these studies it is often noted that the extent of
abnormal hypometabolic regions overlaps with the ictal onset
zones and in many cases these areas are substantially larger than
and overlap with electrodes displaying interictal epileptic dis-
charges (IEDs) (Duncan, 2010). Moreover, overlapping sites of
hypometabolism are commonly lateralized to one hemisphere. For
example, when classified by seizure-freedom rates at a 12-month
follow-up, quantitative comparisons of FDG uptake rates of the
hypometabolic regions relative to the contralateral side showed
high accuracy (80%) in identifying the hemisphere harboring
the epileptogenic focus (Won et al., 1999).
In recent clinical research studies, fMRI has been shown to be a
reliable complementary study to FDG-PET. For example, resected
cortex displaying pre-operative evoked BOLD signal activations
highly concordant with simultaneously EEG recorded IEDs was
associated with a greater probability of post-operative seizure free-
dom (Thornton et al., 2010). It was noted that the greater the
degree of overlap between resected tissue and the spread of IED
correlated BOLD signal across a region, the greater the probability
of long-term seizure freedom. Based on this good concordance,
the authors suggested that use of simultaneously acquired EEG-
fMRI maybea useful adjunct”during the pre-operative evaluation
of epileptogenic cortex, particularly in the absence of identified
pathology (Zijlmans et al., 2007; Thornton et al., 2010). Despite
the major advantages of simultaneous EEG-fMRI during pre-
operative evaluation, it is not readily available in the clinical
setting.
One promising application of BOLD fMRI that may aid seizure
focus localization and is now commonly available in the clin-
ical setting is resting state functional MRI (rsfMRI) functional
connectivity (fc) (Fox and Raichle, 2007; Biswal et al., 2010).
This method calculates whole-brain voxel-wise correlations of
infra-slow (<0.1 Hz) BOLD signal fluctuations extracted during
a resting period and depicts them as maps of brain connectivity.
rsfMRI has been used extensively to reveal patterns of fc across and
between large-scale neural networks (Damoiseaux et al., 2006).
These patterns of correlations are believed to reflect an under-
lying dynamic but intrinsic neural architecture (Honey et al.,
2009; Keller et al., 2011) driven by direct (e.g., mono-synaptic)
and/or indirect (poly-synaptic) anatomical connectivity (Biswal
et al., 2010). Many proposed applications have capitalized on the
inherent advantages of rsfMRI. For instance, rsfMRI has been to
shown to identify intact language networks in the absence of ver-
bal responses (Shimony et al., 2009). In MTLE patients, rsfMRI
has revealed disrupted fc across regions commonly involved in
the greater epilepsy network, primarily on the ipsilateral side to
the seizure focus. Interestingly, increased fc within contralateral
regions was also observed suggestive a possible cross-hemisphere
compensatory mechanism (Bettus et al., 2009). As a follow-up
investigation, the same group of investigators reported that fc
increases observed contralateral to MTL pathology lead to high
degree of specificity (>91%) for identification of the hemisphere
that houses the seizure focus (Bettus et al., 2010).
More recent developments in rsfMRI methodology have begun
to focus on patterns of connectivity specific to the local cortical
environment (Zang et al., 2004). That is, measures of local connec-
tivity mapping correlations restricted to a finite set of voxels within
a ROI. One such method that has recently gained some popular-
ity is Regional Homogeneity (ReHo), a technique that calculates
a non-parametric cross-correlation coefficient between the time-
series of a center voxel with a local cluster of voxels of pre-defined
sized (Zang et al., 2004; Zhong et al., 2011). To date, reports apply-
ing ReHo for seizure focus localization have not been published.
A few studies have contrasted ReHo in epilepsy patients relative
to control volunteers, observing for example significantly higher
thalamic ReHo in a group of generalized tonic-clonic epilepsy
patients, values that were negatively correlated with epilepsy dura-
tion (Zhong et al., 2011). The anatomical assumptions underlying
local fc are built upon patterns of cortico-cortical connectivity.
Variability across local cortical neighborhoods or “small-world
networks” are therefore assumed to reflect weighted differences
of connectivity across neighboring neuronal units (He et al., 2007;
Bullmore and Sporns, 2009) leading to the concept of scale-free
network properties inherent to the brains innate architecture
(Barabási and Albert, 1999).
While epileptogenic mechanisms and the underlying etiolo-
gies are widely variable in patients with focal, treatment-resistant
epilepsy, it is well established that the aberrant nature of prolonged
epileptic discharges lead to significant neuroanatomical alterations
particularly within the epileptogenic zone (Thom, 2004). Animal
models and neuropathological reports of resected human epilep-
togenic tissue have revealed that prolonged seizure activity results
in (among many other well-established biochemical and patho-
logical effects) significant neuronal injury and necrosis within the
seizure network, particularly within neocortical pyramidal cells
(Sankar et al., 1998; Chen and Wasterlain, 2006). Further, a wealth
of animal studies has concluded that persistent seizures activity can
lead to significant dendritic damage including alterations in spin
morphology and an overall down regulation of dendritic spines
(Multani et al., 1994; Wong and Guo, in press).
Our overall aim is to examine the capacity of rsfMRI local
connectivity to serve as a useful adjunct in the pre-operative eval-
uation process of seizure focus localization. Based on the extent
literature, we hypothesized that local fc in and around the seizure
focus in patients with non-lesion, focal (NLF) epilepsy would be
significantly lower relative to (1) controls, (2) the correspond-
ing region within the contralateral hemisphere, and (3) ipsilateral
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Weaver et al. Local fcfMRI in epilepsy
ROIs outside of the epileptogenic zone. We choose a two-step
analysis approach. First we examined fc in and around the seizure
focus. To accomplish this we calculated whole-brain ReHo and
averaged across different ROIs. We then tailored a more traditional
fc approach to specifically contrast local fc at the seizure focus to
the corresponding region within the contralateral hemisphere, an
analysis we referred to as IntraRegional Connectivity (IRC).
MATERIALS AND METHODS
SUBJECTS
Four NLF epilepsy individuals (two female, mean age: 37.75
Table 1) with unknown pathology (MRI negative) were scanned
prior to epilepsy surgery at the University of Washington (UW).
Scans from NLF patients were acquired on two different scanners
(three on a clinical and one on a research magnet; both Philips 3T
Achieva) using identical eight-channel SENSE head coils. Table 1
details the biographical information for each NLF subject. Note:
color-coding within Table 1 is kept consistent throughout to
denote results specific to each individual NLF subject. In order
to minimize variance within the NLF data sets due to use of differ-
ent scanners, we downloaded functional and anatomical data sets
from 16 age- and gender-matched controls (Table A1 inAppendix)
from a multisite rsfMRI repository, the 1000 connectomes data-
base
1
. Of the 16 controls, one quarter were specifically matched to
one NLF subject. That is, four gender-matched controls with an
age range of ±1 year were selected with specific reference to each
NLF subject.
IMAGING
MRI acquisition
At each UW scan session (NLF subjects), the scanning
protocol included a Magnetization prepared rapid gradient
echo (MPRAGE) high-resolution T1 sequence (repetition time
(TR)/echo time (TE)/flip angle: 6.5 ms/3 ms/8˚; matrix size of
256 × 256 and with 170 sagittally collected slices and a slice
thickness of 1 mm) and a 6-min resting state, echo planar fMRI
sequence (rsfMRI, TR/TE/FA: 2000/21/90˚). The clinical scan
sequence consisted of 38 axially oriented slices and a matrix size
64 × 64, while the research scan sequence consisted of 41 axially
oriented slices and a matrix size 80 × 80. For all subjects, five
dummy” volumes which were collected to stabilize T1 equilibra-
tion effects were excluded from analyses. Scan parameters for the
1000 connectomes control subjects varied according to acquisition
site (see Table A1 in Appendix for details).
1
http://fcon_1000.projects.nitrc.org
Seizure focus identification
After scanning, each NLF epilepsy subject underwent a craniotomy
and long-term ECoG monitoring for epileptiform discharges. Ictal
onset was defined clinically from video-ECoG and identification
of concordant fast spiking, low voltage activity extending from
the sub-dural montage. Figure 1 (left column) shows the ECoG
montage for the four NLF subjects. Electrodes highlighted in red
denote the electrodes in the ictal onset zone. After ECoG monitor-
ing, subjects underwent surgical resection of epileptic tissue. The
red transparent areas (Figure 1, left column) reveal the approxi-
mate location of the resected tissue as outlined by post-op surgical
notes. The location of the seizure focus was defined as the region
containing an overlap between ECoG recorded ictal onset activity
contained within the resection zone.
ANALYSIS
Pre-processing
At the individual level, standard rsfMRI pre-processing was
conducted using FEAT (FMRI Expert Analysis Tool) Version
5.98, part of FSL (FMRIB’s Software Library)
2
to remove non-
neuronal sources of variance. These included skull stripping
using BET, motion correction (realignment to the center vol-
ume) with FSL MCFLIRT, spatial smoothing using a 6 mm full-
width half-maximum (FWHM) Gaussian kernel, grand-mean
intensity normalization, and linear drift removal. Identified vol-
umes exceeding 0.5 mm of motion in any direction or plane
were eliminated (scrubbed) from further processing. Addition-
ally, ventricular CSF signal was extracted, averaged, and removed
from the overall whole-brain time-series. Each 4D data set
was entered into a regression analysis, treating the movement
parameters and CSF signal as nuisance variables. Finally, to
limit the effect of physiological noise on fc, the overall time-
series was temporally low-passed filtered removing frequencies
above 0.1 Hz.
Regions of interests
Our aim was to compare across cortical regions containing the
seizure focus and control regions at the individual level. Thus,
we parcellated each individual subject’s brain into established,
known ROIs using the MNI Harvard–Oxford (HO) probability
atlas (included as part of the FSL anatomical toolkit; Figure 2A).
Each of the 48 HO cortical ROIs (employing the 25% threshold
criteria) were selected, degraded by an additional 25% to pre-
vent overlap after warping into native space and then co-registered
2
www.fmrib.ox.ac.uk/fsl
Table 1 | Epilepsy subject demographic information and scanning parameters.
Subject Age Gender Focus location TR/TE Resolution No. of
volumes
Matrix No. of
slices
Scanner
Epilepsy 1 fpei 34 F Right inferior sub-temporal 2, 21 3.5 × 3.5 180 64 × 64 38 Philips 3T (clinical)
Epilepsy 2 FPE2 36 F Right posterior sub-temporal 2, 21 3.5 × 3.5 180 64 × 64 38 Philips 3T (clinical)
Epilepsy 3 FPE3 37 M Left medial to inferior temporal 2, 21 3 × 3 180 80 × 80 41 Philips 3T (research)
Epilepsy 4 FPE4 44 M Left middle temporal 2, 21 3.5 × 3.5 180 64 × 64 38 Philips 3T (clinical)
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Weaver et al. Local fcfMRI in epilepsy
FIGURE 1 | Identification of the seizure focus and ROI. For each NLF
subject, the seizure focus was retrospectively defined and identified as
tissue showing onset of ictal discharges based on electrocorticographic
findings as well as contained with the resection zone (epileptogenic
zone). For consistency throughout, each NLF subject is color-coded as
seen in Table 1. First column shows a 3D surface rendering of the
subjects high-res T1 MPRAGE scan (generated with FREESURFER
automated tools for surface reconstruction) with the overlaid ECoG grid
and strip electrodes. Electrodes colored in red reveal the locales of the
ECoG recorded ictal onset activity. The overlaid red transparencies
show the approximate resected, epileptogenic zone. The second
column (black boxes) plots the HO ROI (on the MNI 152 brain) that
overlaps with the electrode falling within the seizure focus for each NLF
subject.
into native fMRI space through a three-step registration process
using FSL FLIRT. First, the native high-resolution MPRAGE was
registered into native fMRI space using a rigid-body transform.
Second, the MNI 2-mm standard brain was registered onto the
warped MRPRAGE using an affine transformation. The gener-
ated transformation matrices from standard-to-warped MPRAGE
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Weaver et al. Local fcfMRI in epilepsy
FIGURE 2 | Regions of interest and local connectivity. (A) Shows the 48
thresholded HO ROIs overlaid in the MNI 152 brain. Using the structural
detail inherent to the high-res T1 scans, all ROIs were warped into native
fMRI space for each subject. Whole brain, normalized ReHo, and IRC values
were then extracted and averaged from each ROI. (B) Reveals an example
ReHo map form one epilepsy subject. Note the cross-hairs pinpoint a
qualitative decrease in ReHo in and around the seizure focus within the right
hemisphere, an effect that is absent from the left. (C) Plots raw normalized
ReHo values across the 48 HO ROIs for the same NLF subject (green bars)
and the mean of the four age- and gender-matched control subjects (white
bars). Epilepsy and control values are sorted from lowest to highest for the
NLF subject. In this NLF subject, the ROI that contains the epileptogenic
zone (ROI 38) has one of the five lowest mean normalized ReHo values of all
ROIs.
were then applied to all HO ROIs. Finally, for each patient the
HO co-registered ROI that contained the electrode overlaying the
seizure focus was identified and selected for statistical analysis
(Figure 2, right-most column, cross-hairs, the ROI corresponding
to the seizure focus is listed in the bottom right hand corner of the
black box).
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Weaver et al. Local fcfMRI in epilepsy
FC ANALYSES
Regional homogeneity
Each 4D pre-processed data set was then passed through ReHo
analysis using the REST toolbox in MATLAB
3
. For each voxel, a
mean correlation coefficient was computed using Kendal’s coef-
ficient of concordance (KCC-ReHo), relative to the time-series
from the surrounding 27 voxel neighbors. Voxel-wise ReHo values
were normalized by dividing by the global mean KCC-ReHo value
(Mankinen et al., 2011). Greater ReHo values denote increased
local connectivity (Figure 2B).
IRC
To specifically contrast fc between the HO ROI contralateral to
the seizure focus, we adapted traditional fc methods by comput-
ing pair-wise correlation coefficients between all possible voxel
pairs within each HO ROI. Coefficients within an ROI were then
transformed into z-scores and a mean value of absolute z-scores
was estimated. This score was then transformed back into an aver-
age correlation coefficient yielding a mean value of intra-nodal or
local fc. Finally, a ratio of local fc in the left hemisphere ROI to
the connectivity in the right hemisphere ROI was calculated. If
the ratio is close to 1, the brains fc is more symmetric, vice versa.
The ratios were subsequently converted into log scale resulting in
degrees of asymmetry (i.e., the larger the value, the more left ROI
is locally connected in comparison to the right ROI).
Statistics
We are specifically interested in whether local fc within the HO
ROI containing the seizure focus is lower relative to the same ROI
in controls and non-seizure focus ROIs within each epilepsy sub-
ject (thus serving as his/her own control). Because of the small
patient population presenting with refractory, non-lesion epilepsy
combined with interest in comparing across different fc analyses,
we used a non-parametric ranking metric to evaluate differences
at the group level. For each subject, HO ROIs were ranked from
lowest to highest with respect to the normalized ReHo values ipsi-
lateral to the hemisphere housing the seizure focus (for an example
ranking see Figure 2C). IRC ROIs were sorted according to the
degree of left-to-right (or right-to-left depending on which hemi-
sphere housed the focus) asymmetry. The two rankings were then
averaged. Thus, stemming from our local connectivity analysis
approaches, we generated three sets of rankings of 48 values of
local connectivity for each subject. The rank value of each focus
ROI for each of the three rankings were entered into an indepen-
dent sample Wilcoxon Rank Sum test (two-sided, alpha level of
0.05), contrasting the rank value of that ROI for the four NLF
against the 16 matched controls.
Additionally, we reasoned the translational value of rsfMRI fc as
a pre-operative evaluation tool would come at the individual level,
contrasting local fc values across brain regions for a given surgical
candidate. To characterize the ranking values for each NLF epilepsy
subject, we took a parametric approach calculating the mean and
standard deviation of the ranks from across all controls for each of
the four seizure focus ROIs. For each of these four distributions, a
3
http://www.restfmri.net/forum/index.php
corresponding z-score and p value was estimated testing the null
hypothesis that the local fc rank for a given NLF epilepsy subject
was no different than the controls rank values.
Finally, the mean ReHo values from each ROI was standardized
to a 1 to 1 distribution in order to average across the quantitative
estimate of ReHo with the left-right IRC ratios (Table 2). For each
HO ROI, a mean standardized ReHo and IRC ratios were averaged,
ranked, and compared to the mean rank values.
RESULTS
The HO ROI containing the seizure focus for each epilepsy subject
ordered in the bottom 10% for all within-subject rankings except
for the IRC ranking for NLF4 (red text in Table 2). For example,
the ReHo ranking for participant NLF1 was 2 indicating the HO
ROI housing the seizure focus had the second lowest mean, nor-
malized ReHo with respect to all ipsilateral ROIs. Further, the IRC
ranking for this subject was 3, indicating that this ROI showed
the third lowest local fc ranking when mean local fc was directly
contrasted with its contralateral counterpart. The one exception
was the IRC ranking for subject NLF4, indicated that the local fc
showed a greater degree of contralateral connectivity relative to the
seizure focus. Figure 3 plots the rank value for the three ranking
distributions revealing the raw values for each non-lesional, focal
epilepsy patient as the colored bar.
GROUP-LEVEL CONTRASTS
To determine whether local fc in the seizure focus ROI was
lower in the epilepsy group, we compared the rank value of
the seizure focus ROI between NLF and controls across our
three sets of rankings (ReHo, IRC, and mean rank). Both the
ReHo (p = 0.0156, Wilcoxon Rank Sum test) and the mean rank
(p = 0.0421, Wilcoxon Rank Sum test) were significantly lower
averaged across the NLF subjects (Figure 3, color bars) relative to
controls (Figure 3, mean value shown in gray bars) but not the
IRC fc method (p = 0.0184). It should be noted that the unusual
contralateral connectivity effect seen with in NLF4 subject likely
contributed to the null statistical effect for the IRC method at the
group level.
INDIVIDUAL-LEVEL CONTRASTS
To piece out ranking effects at the individual level, we calculated
z-score statistics from the mean and SD across ranks values from
the controls. For each seizure focus ROI across each of the three
local fc rankings, we were able to reject the null hypothesis for only
NLF1 subject (p = 0.0424) under the IRC rankings. Further, when
the ReHo and IRC rankings were averaged together, both subjects
NLF1 (p = 0.0409) and NLF3 (p = 0.0427) showed significantly
lower rankings relative to controls.
We also directly contrasted the mean rankings (i.e., the average
between ReHo and IRC) for each individual NLF subject with a
mean value of the raw local fc estimations. For each ROI, quan-
titative local fc values were an average metric calculated from the
normalized ReHo and the IRC ratio scores. The mean local fc value
paralleled the average ranking for all four NLF epilepsy subjects.
The red text items in Table 2 reveal the ranking and raw local fc
values for each of the seizure focus ROIs. As can be seen, across
both the mean rankings and combined local fc estimates, the ROI
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Weaver et al. Local fcfMRI in epilepsy
Table 2 | ReHo, IRC and mean ranking values for all HO ROIs.
ReHo IRC
1 2 3 4 1 2 3 4
ROI Raw
value
Normal-
ized
ROI Raw
value
Normal-
ized
ROI Raw
value
Normal-
ized
ROI Raw
value
Normal-
ized
ROI IRC ROI IRC ROI IRC ROI IRC
NLF SUBJECT
34 0.658 1.000 45 0.716 1.000 37 0.794 1.000 14 0.735 1.000 34 1.000 2 1.000 25 1.000 6 1.000
37 0.668 0.974 44 0.742 0.929 34 0.819 0.905 11 0.761 0.932 7 0.856 46 0.924 6 0.925 41 0.937
14 0.710 0.851 41 0.806 0.759 27 0.854 0.770 5 0.821 0.772 37 0.615 38 0.823 37 0.714 42 0.911
41 0.732 0.789 2 0.807 0.755 8 0.913 0.541 9 0.848 0.700 14 0.300 48 0.507 48 0.624 27 0.838
38 0.738 0.771 38 0.814 0.736 14 0.926 0.491 12 0.896 0.575 6 0.239 1 0.462 28 0.508 4 0.802
27 0.771 0.676 14 0.827 0.701 38 0.939 0.441 33 0.896 0.575 42 0.236 41 0.424 5 0.500 25 0.774
42 0.800 0.593 7 0.863 0.605 25 0.943 0.425 15 0.909 0.541 1 0.155 21 0.390 26 0.455 40 0.772
2 0.808 0.570 46 0.867 0.596 3 0.952 0.391 38 0.910 0.539 27 0.134 19 0.386 36 0.447 9 0.764
35 0.854 0.439 19 0.875 0.574 1 0.954 0.384 34 0.923 0.503 38 0.097 43 0.363 40 0.408 19 0.756
46 0.854 0.438 33 0.880 0.560 33 0.975 0.303 8 0.931 0.481 18 0.036 8 0.335 7 0.391 22 0.731
8 0.865 0.406 37 0.886 0.544 29 0.979 0.289 37 0.950 0.432 19 0.055 42 0.308 27 0.384 2 0.727
33 0.874 0.379 26 0.902 0.503 28 1.002 0.198 44 0.971 0.377 20 0.075 33 0.285 19 0.355 24 0.716
43 0.887 0.343 42 0.916 0.463 26 1.006 0.183 26 0.972 0.373 29 0.099 4 0.270 39 0.355 47 0.700
7 0.890 0.335 43 0.920 0.454 35 1.011 0.162 27 0.973 0.370 17 0.125 34 0.179 13 0.348 32 0.695
15 0.898 0.310 15 0.924 0443 4 1.025 0.108 35 0.988 0.332 16 0.129 7 0.135 24 0.338 28 0.678
29 0.906 0.287 48 0.932 0.422 15 1.048 0.021 45 0.994 0.315 10 0.149 14 0.131 30 0.325 31 0.676
44 0.919 0.252 4 0.959 0.350 11 1.050 0.012 1 1.002 0.295 2 0.155 40 0.123 23 0.323 39 0.632
45 0.923 0.239 1 0.968 0.326 6 1.064 0.039 10 1.020 0.248 21 0.175 44 0.095 32 0.309 29 0.624
6 0.928 0.224 17 0.989 0.269 7 1.067 0.052 4 1.026 0.232 46 0.193 26 0.089 46 0.298 45 0.622
5 0.938 0.195 8 0.989 0.269 5 1.070 0.064 3 1.037 0.203 23 0.205 10 0.066 34 0.297 20 0.615
1 0.970 0.103 6 1.004 0.227 41 1.079 0.098 20 1.044 0.184 39 0.222 16 0.037 10 0.281 17 0.581
10 0.979 0.079 27 1.023 0.176 32 1.086 0.126 46 1.047 0.176 8 0.247 31 0.000 43 0.249 3 0.574
18 0.990 0.047 3 1.029 0.163 36 1.097 0.169 19 1.047 0.176 44 0.288 20 0.002 31 0.244 44 0.564
17 0.999 0.020 18 1.032 0.154 10 1.105 0.200 6 1.050 0.167 3 0.294 39 0.025 17 0.238 23 0.536
28 1.005 0.002 5 1.051 0.103 30 1.106 0.202 41 1.059 0.146 33 0.320 30 0.056 20 0.227 33 0.515
4 1.025 0.055 20 1.058 0.085 18 1.109 0.216 2 1.067 0.125 31 0.372 47 0.059 3 0.221 18 0.508
32 1.034 0.079 29 1.088 0.004 31 1.117 0.246 18 1.084 0.078 5 0.402 12 0.060 21 0.217 36 0.506
19 1.048 0.122 16 1.090 0.002 47 1.120 0.257 42 1.085 0.076 35 0.409 23 0.082 29 0.185 35 0.477
11 1.060 0.156 34 1.114 0.065 9 1.122 0.265 36 1.087 0.072 15 0.413 36 0.104 15 0.113 30 0.477
3 1.063 0.163 11 1.120 0.083 16 1.128 0.287 30 1.089 0.066 48 0.452 32 0.115 47 0.110 46 0.415
26 1.069 0.180 23 1.136 0.126 17 1.143 0.345 7 1.093 0.055 32 0.460 3 0.126 44 0.048 43 0.400
21 1.073 0.192 10 1.139 0.133 46 1.150 0.372 48 1.099 0.038 36 0.478 25 0.129 1 0.045 15 0.376
20 1.083 0.222 30 1.159 0.186 39 1.162 0.419 43 1.100 0.035 12 0.519 45 0.158 35 0.034 37 0.375
48 1.084 0.224 21 1.182 0.248 24 1.165 0.431 29 1.107 0.018 24 0.522 37 0.158 45 0.013 26 0.367
47 1.100 0.271 12 1.186 0.259 42 1.170 0.448 28 1.111 0.007 45 0.535 11 0.160 4 0.010 21 0.358
16 1.101 0.273 13 1.193 0.277 40 1.171 0.454 17 1.116 0.006 28 0.544 24 0.210 9 0.018 34 0.345
12 1.113 0.308 28 1.204 0.305 2 1.172 0.457 32 1.146 0.085 43 0.575 18 0.249 41 0.043 16 0.328
30 1.130 0.357 40 1.220 0.349 48 1.179 0.484 23 1.148 0.091 30 0.625 17 0.249 42 0.058 48 0.312
9 1.132 0.361 39 1.220 0.351 12 1.184 0.502 40 1.151 0.098 22 0.626 29 0.269 14 0.070 10 0.305
39 1.139 0.382 22 1.236 0.393 13 1.192 0.535 13 1.154 0.107 26 0.655 15 0.279 I8 0.133 1 0.235
23 1.139 0.383 31 1.245 0.415 44 1.202 0.574 16 1.183 0.182 4 0.669 27 0.306 33 0.209 12 0.233
24 1.152 0.420 9 1.255 0.444 19 1.208 0.597 39 1.183 0.183 13 0.678 13 0.389 38 0.211 14 0.125
31 1.187 0.519 35 1.260 0.457 45 1.212 0.612 21 1.229 0.303 40 0.698 22 0.401 12 0.218 5 0.035
13 1.196 0.545 24 1.302 0.570 22 1.228 0.673 24 1.235 0.319 47 0.709 5 0.536 2 0.225 38 0.017
36 1.219 0.612 25 1.307 0.582 23 1.229 0.676 22 1.281 0442 25 0.717 35 0.613 16 0.282 11 0.036
22 1.255 0.715 36 1.367 0.744 43 1.262 0.804 31 1.336 0.586 9 0.864 6 0.635 22 0.328 7 0.076
25 1.288 0.811 32 1.401 0.834 20 1.292 0.921 47 1.388 0.724 41 0.879 28 0.640 8 0.989 13 0.088
40 1.354 1.000 47 1.463 1.000 21 1.313 1.000 25 1.493 1.000 11 1.000 9 1.000 11 1.000 8 1.000
(Continued)
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Weaver et al. Local fcfMRI in epilepsy
Table 2 | Continued
Mean
1 2 3 4
ROI Mean rank Mean value ROI Mean rank Mean value ROI Mean rank Mean value ROI Mean rank Mean value
NLF SUBJECT
34 1 1.000 2 2.5 0.877 37 2 0.857 9 6 0.732
37 2.5 0.794 38 4 0.780 25 4 0.712 27 9 0.604
7 3.5 0.595 46 4.5 0.760 34 7 0.601 6 12 0.584
14 6.5 0.575 41 5 0.592 77 8.5 0.577 14 12.5 0.562
38 7 0.434 44 8.5 0.512 6 10 0.443 33 13.5 0.545
42 7 0.415 19 10 0.480 78 10 0.353 41 15.5 0.542
27 8 0.405 48 10 0.464 26 11 0.319 4 15.5 0.517
6 12 0.232 33 11 0.422 3 13 0.306 42 16 0.493
2 12.5 0.207 45 11 0.421 29 14.5 0.237 44 17.5 0.471
1 14 0.129 14 11 0.416 5 15.5 0.218 45 17.5 0.469
46 14.5 0.122 43 11.5 0.408 1 17 0.215 19 18.5 0.466
29 14.5 0.094 1 11.5 0.394 14 19.5 0.210 15 19.5 0.459
8 16.5 0.080 42 12 0.386 7 20 0.170 11 20.5 0.448
33 16.5 0.029 7 15 0.370 36 20.5 0.139 2 21 0.426
35 18.5 0.015 4 15 0.310 38 20.5 0.115 34 21.5 0.424
18 18.5 0.005 8 15.5 0.302 35 21 0.098 35 21.5 0.405
44 19 0.018 26 17 0.296 32 22 0.092 12 22 0.404
10 19 0.035 37 20.5 0.193 48 22.5 0.070 37 22.5 0.404
41 19.5 0.045 15 21.5 0.082 15 22.5 0.067 5 23 0.403
15 20 0.052 21 22.5 0.071 30 22.5 0.062 70 23 0.399
17 22 0.052 34 24.5 0.057 4 23 0.059 3 23 0.388
19 22.5 0.088 20 24.5 0.042 33 23.5 0.047 26 23.5 0.370
5 23.5 0.103 3 26 0.019 10 24 0.041 28 23.5 0.342
43 25 0.116 16 27 0.017 31 24.5 0.001 40 25 0.337
45 25 0.148 17 27.5 0.010 40 25 0.023 29 25.5 0.321
20 25.5 0.148 10 27.5 0.033 39 25 0.032 32 26 0.305
21 25.5 0.184 18 28.5 0.048 46 25.5 0.037 46 26 0.296
16 26.5 0.201 27 29 0.065 74 25.5 0.047 18 26 0.293
3 27 0.229 23 29.5 0.104 17 25.5 0.053 36 26.5 0.289
32 29 0.270 40 30.5 0.113 41 27 0.071 17 27 0.287
28 30.5 0.271 11 31 0.121 47 27 0.073 10 27.5 0.276
23 30.5 0.294 30 31.5 0.121 13 27.5 0.093 30 28 0.271
39 30.5 0.302 29 31.5 0.132 19 29 0.121 1 28 0.265
48 32 0.338 12 31.5 0.160 9 29 0.142 38 28.5 0.261
4 33.5 0.362 39 32.5 0.188 18 31 0.174 39 28.5 0.224
12 34.5 0.414 6 33 0.204 23 32.5 0.177 23 28.5 0.223
26 35 43.417 31 33.5 0.208 8 32.5 0.224 43 29 0.218
31 35.5 0.446 5 34.5 0.217 42 33 0.253 24 29.5 0.199
24 38 0.471 13 37 0.333 44 34 0.263 48 29.5 0.175
47 38 0.490 25 37.5 0.356 43 36 0.277 22 30 0.144
30 38.5 0.491 24 38.5 0.390 16 36 0.284 16 31 0.073
36 38.5 0.545 77 38.5 0.397 45 36.5 0.300 31 31 0.045
11 39.5 0.578 36 39 0.424 2 37.5 0.341 21 32 0.027
13 42.5 0.612 28 40 0.473 20 37.5 0.347 7 35 0.011
9 42.5 0.613 32 41.5 0.475 12 38.5 0.360 47 38.5 0.012
22 43 0.671 47 42 0.530 21 40.5 0.392 13 39 0.097
25 45.5 0.764 35 44 0.535 11 41 0.494 25 39 0.113
40 46 0.849 9 45 0.722 22 45 0.501 8 43.5 0.259
Raw values for local fc measurements with the corresponding rankings are shown across all ROIs. Red, bold text represents the seizure focus ROI for each subject.
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Weaver et al. Local fcfMRI in epilepsy
FIGURE 3 | Ranking the local fc estimates from the HO ROI around the
seizure focus. For each NLF subject and the 16 age- and gender-matched
controls, ReHo, IRC, and mean scalars were calculated from the ROI that
contained the seizure focus. For each of the 20 subjects, values from all
ROIs were sorted from lowest to highest and assigned a rank relative to the
48 ROIs within the HO atlas. The first column plots ReHo ranks, the second
column plots the IRC ranks (ranking either R > L or L > R) and the third the
average rank across the two methods for all subjects. The color bar
represents the ranking for the respective NLF subject as noted in Table 1.
The gray bar represents the mean (with standard error of the mean) of the
16 controls subjects, and each black bar represents the ranking for each
control subject.
housing the seizure focus was lower in value relative to either of
the constituent values alone for three out of the four NLF patients.
For example, in the patient NLF 2, the seizure focus ROI was the
second lowest ranked and second lowest combined computed local
fc value, but ranked third and fifth when individually sorting IRC
and ReHo values, respectively.
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Weaver et al. Local fcfMRI in epilepsy
DISCUSSION
Here we observe that rsfMRI local fc shows some potential as
a pre-operative mapping tool for seizure focus identification in
individuals with NLF epilepsy. We examined two different meth-
ods of fc estimation, averaged across both methods and contrasted
local fc at the site of the seizure focus between epilepsy individu-
als, normal controls, and within-subject ROIs. At a group level, we
observed a decrease in both the ReHo ranking and the combined
rank for the ROI harboring the focus compared to a matched group
of control subjects. This suggests that in our cohort of local epilep-
tics there was a marked decrease in one measure of local fc (ReHo)
in the area around the seizure focus. Thus, at the group level, the
disease process associated with epilepsy appears to alter local fc
around the focus, a hypothesis that is consistent with the patho-
logical effects typically seen in the epileptogenic zone (Thom,2004;
Wong and Guo, in press). The real clinical value however of local fc
to epilepsy surgery is an accurate estimation of the location of the
epileptogenic zone at the individual level that is concordant with
other modalities of investigation. This is particularly important
for patients with focal epilepsy with a normal MRI where macro-
scopic structural abnormalities are not available as an initial guide
for surgical planning.
A WITHIN-SUBJECT METHOD FOR IDENTIFYING THE SEIZURE FOCUS
We therefore examined whether rsfMRI could clarify the location
of the seizure focus in NLF epilepsy at an individual level. Based
on neuropathological reports and animal studies of focal epilepsy
reporting significant neuronal necrosis at the seizure focus, we
hypothesized that values of local connectivity would be abnormal
in and around the seizure focus (Thom, 2004; Wong and Guo, in
press). Based upon an extensive imaging literature showing com-
pensatory effects within the contralateral hemisphere, we extended
this hypothesis to a specific decrease in local fc within the ipsilat-
eral relative to the contralateral cortical region (Won et al., 1999;
Morgan et al., 2012). The approach providing the greatest poten-
tial for revealing our predicted effects was averaging across both
ReHo and IRC and contrasting across all ROIs from a single subject
(Table 2). This procedure revealed that for three out of the four
NLF subjects the seizure focus ROI was either the lowest (NLF3)
or second lowest (NLF1 and NLF2) ranked ROI (see Figure 3,
colored bars, Table 2; for a specific discussion on the IRC ranking
of NLF4, see below). That is, the predictive capacity of local fc
rsfMRI in focal, non-lesion epilepsy is improved when combin-
ing a method that specifically computes local fc within the region
around the seizure focus (ReHo) with an analysis that contrasts
local fc with specific reference to the corresponding contralateral
hemisphere (IRC).
We argue using the epilepsy patient as his or her own con-
trol while combining these two local fc approaches provides the
most promise as a translational tool. rsfMRI provides whole-
brain coverage. Thus, contrasting ReHo and IRC values across the
brain is readily available when employing standard clinical rsfMRI
sequences. Normative, population values for patterns of local fc
have not been established, more importantly are not readily avail-
able in the clinical setting and will likely need to be developed for
specific MR systems and imaging sequences. When combined with
established physiological and anatomical and functional imaging
abnormalities commonly associated with the seizure focus as well
as including the possible compensatory effects observed in the
contralateral hemisphere (Bettus et al., 2009), it is not surprising
that factoring in both of these methodologies would improve the
overall ability to identify the epileptogenic focus ROI.
This combined approach may also have an important role in
patients early in the course of the epileptogenic process where
potentially surgically remediable lesions can be identified at an
incipient stage before neuroanatomical changes are observed on
conventional MRI. Several studies have shown that surgical inter-
ventions early in the course of pharmacoresistant epilepsy leads to
better quality of life and outcomes (Engel et al., 2012).
THE LARGER SEIZURE NETWORK
For NLF1, the HO ROI 34 (corresponding to anterior division
of the parahippocampal gyrus) ranked lower after combining
both ReHo and the IRC methods than the seizure focus ROI
(corresponding to the anterior extent of the temporal fusiform
Figure 1). Portions of HO ROI 34 were resected in this patient.
Thus under established criteria, the parahippocampal gyrus would
be included as part of the epileptogenic zone (c.f. Laufs, 2012). This
region shares significant inter-connectivity with cortex through-
out the medial temporal lobe, including the perirhinal and
entorhinal cortices as well as with the hippocampus proper (Bur-
well, 2000). Accordingly, the parahippocampal cortex is heavily
involved in recall and/or numerous memory-related processes
(Eichenbaum et al., 2007). Intrinsic connectivity studies using
rsfMRI have revealed significant fc with numerous neocortical
association cortices including the posterior regions of the default
mode network as well as inter-connectivity spread throughout the
lateral temporal lobe (Ranganath and Ritchey, 2012) and exten-
sively with the anterior extent of the inferior temporal lobe (Kahn
et al., 2008). Not surprisingly, the parahippocampal gyrus is a key
fixture in the larger network underlying MTL epilepsy and seizure
propagation (McIntyre and Gilby, 2008). The widespread pat-
tern of connectivity extending from the parahippocampal region
throughout the temporal lobe provides an architecture that would
easily promote temporal lobe seizure propagation. With specific
reference to NLF1, the seizure focus is located in a densely con-
nected adjacent portion of the anterior, inferior temporal lobe
(the temporal lobe fusiform). Thus, the observation that these
two regions show the lowest local fc estimates likely signifies
that rsfMRI is revealing a broader epileptogenic zone or epilepsy
network in this subject.
For NLF epilepsy subject 2, only the insular cortex ROI ranked
lower in local fc relative to the seizure focus ROI (located within the
posterior temporal fusiform). The insula is generally considered a
multimodal integration site that shares a high level of connectiv-
ity with frontal and temporal cortex. A recent seed-based rsfMRI
report noted significant fc between two different points along the
anterior-posterior insular plane and the posterior fusiform (Tay-
lor et al., 2009). Both ictal and IEDs originating from the insula
have been reported in MTL epilepsy (Isnard et al., 2000). In this
same report, it was observed that two patients with significant
insular discharges continued to have seizures after temporal lobec-
tomy. Moreover, lesions in the insula have been shown to develop
into intractable epilepsy where resection of the lesion and the
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Weaver et al. Local fcfMRI in epilepsy
surrounding insular tissue yields seizure freedom (Roper et al.,
1993). Based on these and similar reports, insula-based epilepsy
has become more routinely recognized over the past few decades
(Nguyen et al., 2009).
The converging notion from the current NLF epilepsy patients
one through three is that alterations in local fc may identify the
epileptogenic zone as well as the larger epilepsy network (Stuffle-
beam et al., 2011). The concept of widespread epilepsy networks
has been identified using both imaging with MRS (Pan et al., 2012),
SPECT (Sequeira et al., 2013), FDG-PET (Mauguière and Ryvlin,
2004), and electrophysiological studies (Muldoon et al., 2013).
The observation that ROIs ranking lower in local fc relative to
the seizure focus likely share rich patterns of connectivity with
the seizure focus may be exposing a more widespread patholog-
ical consequence of the seizure propagation. Building upon the
hypothesis that discrepancies in local fc are linked to local neuronal
insults such as necrosis (or apoptosis), alterations in dendritic
morphology, and potential compensation within the contralateral
hemisphere, the currently applied techniques may be revealing the
downstream consequences of seizure propagation across the entire
epilepsy network.
METHODOLOGICAL CONSIDERATIONS AND LIMITATIONS
We choose to focus specifically on refractory, non-lesion epilepsy
patients because of the added importance that functional-based
modalities (i.e., electrophysiological and imaging based proce-
dures) provide in the pre-surgical localization of the seizure focus.
The number of patients presenting with NLF epilepsy that are can-
didates for surgery are however relatively small (<10% of all new
cases per year; Duncan, 2010). Despite this limitation, the current
results should be taken with a degree of caution due the small sam-
ple size. As a follow-up, future studies will clearly need to conduct
similar analyses with larger samples. It is however likely that esti-
mates of local fc may aid in the identification of the epileptogenic
focus among patients presenting with various focal pathologies
(i.e., cortical dysplasia, AVM, brain tumors etc.). Taken together
with the lateralized fc differences throughout the medial temporal
lobe previously reported in MTLE patients (Bettus et al., 2009),
local fc would likely contribute to the pre-surgical evaluation even
in the presence of an identified insult.
The current results would benefit from a more precise delin-
eation of the epileptogenic zone. Other groups have identified the
epileptogenic zone using a variety of additional techniques (c.f.
Jayakar et al., 2008; Duncan, 2010). We were not able to use a more
sophisticated means of defining the epileptogenic zone other than
a description from post-op surgical notes of the extent and bound-
aries of the resected region. By choosing to parcellate the brain into
ROIs using a well-established, probabilistic atlas combined with a
sorting method based on mean local fc values, we ensured a com-
pletely unbiased process of identifying patterns of reduced local fc
across subjects while maintaining relatively high anatomical speci-
ficity. One unfortunate and likely consequence of this procedure
is a smearing of voxel types within an ROI. More specifically, it
is unlikely that the ROI corresponding to the seizure focus in any
given NLF patient contains voxels that would be exclusively labeled
as falling in or exclusively out of the epileptogenic zone. Thus, it
is likely that the mean values for each ROI in and around the
epileptogenic zone are underestimated, and the true local fc value
associated with the epileptogenic zone is likely lower. One possi-
ble solution for consideration in future studies is to contrast pre
and post-resection MRI scans. This would generate a voxel mask
of the resected tissue and by extension the extended epileptogenic
zone. Furthermore, the current results would indeed benefit from
the addition of simultaneously acquired EEG. Confirmation of the
IED-related activity during rsfMRI acquisition would provide the
ability to confirm the boundaries of epileptogenic zone. Provided
the presence of IEDs during functional scanning, it may be feasi-
ble to select out specific periods of “IED-free” rsfMRI activity in
order to determine whether the presence of IEDs are negatively
(or positively) impacting local lc correlation coefficients. How-
ever, we reason that rsfMRI provides a simple yet powerful means
of examining the underlying physiology of the epileptogenic zone
that is also feasible in the clinical context (c.f. Fox and Greicius,
2010). Future studies will clearly need to address the influence of
IEDs (as well as ictal discharges) on the rsfMRI BOLD activity
and local fc estimates. Furthermore, future studies will need to
address the concordance between rsfMRI local fc estimates in NLF
epilepsy and more commonly used modalities such as FDG-PET.
However, if local fc does indeed reflect the accurate location of the
seizure focus and thereby supplementing more traditional evalu-
ative modalities, then the need of simultaneous EEG would prove
relatively superfluous.
NLF 4 did this not show the same pattern of IRC within the
seizure focus ROI (located within the left middle temporal gyrus)
as was observed in other NLF 3 patients. Although the raw and
ranked ReHo values were within the bottom 10% of all sorted
ROIs, the pattern of local fc under the IRC calculation was signif-
icantly greater within the ipsilateral hemisphere. The mechanism
contributing to this effect is unknown. Results from the WADA
test as well as clinical fMRI scans using various language screens
concluded that language dominance was localized to the left hemi-
sphere for this patient. It is possible that patterns of contralateral
connectivity are not as vast within the middle, temporal lobe rel-
ative to noted contralateral compensatory effects stemming from
medial temporal lobe (Bettus et al., 2009). It is also conceivable that
scalars of local fc are greater in regions throughout the language
dominant hemisphere relative to the contralateral counterparts. It
is clear that future work will need to address baseline differences
in local fc across both the temporal lobe as well as whole brain.
CONCLUSION
We present evidence suggesting local fc measurements from
rsfMRI provide an accurate estimate of the location of the epilepto-
genic region in non-lesional, focal epilepsy. Structurally identified
lesions are typically considered a reliable guide as a first pass for
identifying the approximate location of the epileptogenic zone.
Because the long-term benefits of epilepsy surgery are significant
for individuals presenting with normal anatomical MRIs (Jayakar
et al., 2008), accurate localization is a critical pre-operative func-
tion. In the absence of identified lesions, clinicians must rely
more heavily on alterative methods to identify epileptogenic zones.
Here we provide the first evidence that rsfMRI local fc may pro-
vide additional, confirmatory information about the location of
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Weaver et al. Local fcfMRI in epilepsy
the epileptogenic focus in refractory NLF epilepsy. These tech-
niques may also identify the broader epilepsy network and identify
comorbid neuropsychological dysfunction due to involvement of
other functional networks.
ACKNOWLEDGMENTS
This research was supported by NIH/NIMH grant 5K01
MH086118-03 (K. E. Weaver) and NIH/NINDS 5ROI NS065186-
03 & The Dreuding foundation (J. G. Ojemann).
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Conflict of Interest Statement: The
authors declare that the research was
conducted in the absence of any
commercial or financial relationships
that could be construed as a potential
conflict of interest.
Received: 20 February 2013; paper pend-
ing published: 14 March 2013; accepted:
17 April 2013; published online: 01 May
2013.
Citation: Weaver KE, Chaovalitwongse
WA, Novotny EJ, Poliakov A, Grabowski
TG and Ojemann JG (2013) Local
functional connectivity as a pre-surgical
tool for seizure focus identification in non-
lesion, focal epilepsy. Front. Neurol. 4:43.
doi: 10.3389/fneur.2013.00043
This article was submitted to Frontiers
in Epilepsy, a specialty of Frontiers in
Neurology.
Copyright © 2013 Weaver, Chaovalit-
wongse, Novotny, Poliakov, Grabowski
and Ojemann. This is an open-access
article distributed under the terms of the
Creative Commons Attribution License,
which permits use, distribution and
reproduction in other forums, provided
the original authors and source are cred-
ited and subject to any copyright notices
concerning any third-party graphics
etc.
www.frontiersin.org May 2013 | Volume 4 | Article 43 | 13
Page 13
Weaver et al. Local fcfMRI in epilepsy
APPENDIX
Table A1 | Control subject demographic information and scanning parameters.
1000C ID Age Gender Control ID TR Resolution No. of volumes Matrix No. of slices
NY sub33062 34 F ctrl002 2 3 × 3 180 64 × 64 39
Leipzig sub41241 34 F ctrl003 2.3 3 × 3 180 64 × 64 34
Palo Alto sub29935 33 F ctrl004 2 3.4 × 3.4 180 64 × 64 29
NY sub53710 34 F ctrl015 2 3 × 3 180 64 × 64 39
NY sub30860 35 F ctrl016 2 3 × 3 180 64 × 64 39
NY sub47633 37 F ctrl017 2 3 × 3 180 64 × 64 39
Oxford subl3304 35 F ctrl018 2 3 × 3 175 64 × 64 34
Oxford sub85152 35 F ctrl019 2 3 × 3 175 64 × 64 34
Bangor sub04097 36 M ctrl006 2 3 × 3 180 80 × 80 34
Bangor sub81464 38 M ctrl007 2 3 × 3 180 80 × 80 34
ICBM sub51677 37 M ctrl008 2 4 × 4 128 64 × 64 23
Leipzig sub36858 38 M ctrl009 2.3 3 × 3 180 64 × 64 34
ICBM sub94169 43 M ctrlOll 2 4 × 4 128 64 × 64 23
Milwaukie sub91468 44 M ctrl014 2 3.75 × 3.75 175 64 × 64 20
Milwaukie sub49975 45 M ctrl020 2 3.75 × 3.75 175 64 × 64 20
UW sub56994 43 M ctrl021 2 3 × 3 180 80 × 80 41
Frontiers in Neurology | Epilepsy May 2013 | Volume 4 | Article 43 | 14
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    • "The reported characteristics of seizure-specific connectivity have varied. Some have found an increase in local connectivity ipsilateral to the seizure onset zone (Bartolomei et al 2013, Haneef et al 2014, Luo et al 2014, Maneshi et al 2014), while others have reported decreased local connectivity (Bettus et al 2009, Morgan et al 2012, Pittau et al 2012, Maccotta et al 2013, Weaver et al 2013). There seems to be more consistency in the question of longdistance connectivity, where the epileptogenic zone has been found to be less connected to the contralateral hemisphere, the default mode network, and sensorimotor networks (Voets et al 2012, Bartolomei et al 2013, Maccotta et al 2013, Luo et al 2014 ). "
    [Show abstract] [Hide abstract] ABSTRACT: Objective: Quantifying the relationship between microelectrode-recorded multi-unit activity (MUA) and local field potentials (LFPs) in distinct brain regions can provide detailed information on the extent of functional connectivity in spatially widespread networks. These methods are common in studies of cognition using non-human animal models, but are rare in humans. Here we applied a neuronal spike-triggered impulse response to electrophysiological recordings from the human epileptic brain for the first time, and we evaluate functional connectivity in relation to brain areas supporting the generation of seizures. Approach: Broadband interictal electrophysiological data were recorded from microwires adapted to clinical depth electrodes that were implanted bilaterally using stereotactic techniques in six presurgical patients with medically refractory epilepsy. MUA and LFPs were isolated in each microwire, and we calculated the impulse response between the MUA on one microwire and the LFPs on a second microwire for all possible MUA/LFP pairs. Results were compared to clinical seizure localization, including sites of seizure onset and interictal epileptiform discharges. Main results: We detected significant interictal long-range functional connections in each subject, in some cases across hemispheres. Results were consistent between two independent datasets, and the timing and location of significant impulse responses reflected anatomical connectivity. However, within individual subjects, the spatial distribution of impulse responses was unique. In two subjects with clear seizure localization and successful surgery, the epileptogenic zone was associated with significant impulse responses. Significance: The results suggest that the spike-triggered impulse response can provide valuable information about the neuronal networks that contribute to seizures using only interictal data. This technique will enable testing of specific hypotheses regarding functional connectivity in epilepsy and the relationship between functional properties and imaging findings. Beyond epilepsy, we expect that the impulse response could be more broadly applied as a measure of long-range functional connectivity in studies of cognition.
    No preview · Article · Mar 2016 · Journal of Neural Engineering
  • Source
    • "Thus, this method has been suggested to investigate the functional modulations and to characterize the neuropsychological changes in the resting state in patients with various clinical populations [36] [37] [38] [39] [40] [41] [42]. In particular, abnormal ReHo has mostly been used to depict aberrant spontaneous brain temporal synchrony in epilepsy [43] [44] [45] [46] [47]. Little is known, however, about the changes of local synchronization of spontaneous BOLD fluctuations in RE. "
    Full-text · Dataset · May 2015
  • Source
    • "Thus, this method has been suggested to investigate the functional modulations and to characterize the neuropsychological changes in the resting state in patients with various clinical populations [36] [37] [38] [39] [40] [41] [42]. In particular, abnormal ReHo has mostly been used to depict aberrant spontaneous brain temporal synchrony in epilepsy [43] [44] [45] [46] [47]. Little is known, however, about the changes of local synchronization of spontaneous BOLD fluctuations in RE. "
    Full-text · Dataset · May 2015
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