EEG spectral changes underlying BOLD responses contralateral to spikes in patients with focal epilepsy.
ABSTRACT Simultaneous electroencephalogram and functional magnetic resonance imaging (EEG-fMRI) in patients with focal epilepsy and unilateral spikes often shows positive blood oxygenation level-dependent (BOLD) responses (activations), not only ipsilateral but also contralateral to the spikes. We aimed to investigate whether minimal EEG changes could underlie these contralateral BOLD responses by using EEG spectral analysis.
We studied 19 patients with focal epilepsy and unilateral spikes. According to the pattern of BOLD activation, patients were divided into Group 1 (ipsi- and contralateral to the spikes) or Group 2 (only ipsilateral). EEG from outside the scanner was used to mark spikes similar to those recorded in the scanner. Epochs of 640 ms before and after the peak of the spikes were chosen as baseline and spike epochs. Spectral analysis was performed in referential montage (FCz reference), and differences between baselines and spikes were analyzed by paired t-test.
Significant EEG changes in electrodes contralateral to the spikes were seen in 9 of 10 patients in Group 1 and in only 2 of 10 patients in Group 2 (one patient had two types of spikes that were analyzed separately). Spectral changes were seen in delta and/or theta bands in all patients except one (in Group 1) who had changes in all bands.
Significant contralateral EEG changes occurred in 90% of contralateral BOLD activations and in only 20% of patients without contralateral BOLD responses. The reason why these changes predominate in lower frequencies rather than in higher frequencies is unclear. These spectral changes in areas corresponding to contralateral activations might reflect poorly synchronized but possibly intense neuronal activity.
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ABSTRACT: The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.Frontiers in Neurology 01/2014; 5:31.
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ABSTRACT: Activation detection in functional Magnetic Resonance Imaging (fMRI) typically assumes the hemodynamic response to neuronal activity to be invariant across brain regions and subjects. Reports of substantial variability of the morphology of Blood-Oxygenation-Level-Dependent (BOLD) responses are accumulating, suggesting that the use of a single generic model of the expected response in general linear model (GLM) analyses does not provide optimal sensitivity due to model misspecification. Relaxing assumptions of the model can limit the impact of hemodynamic response function (HRF) variability, but at a cost on model parsimony. Alternatively, better specification of the model could be obtain from a priori knowledge of the HRF of a given subject, but the effectiveness of this approach has only been tested on simulation data. Using fast BOLD fMRI, we characterized the variability of hemodynamic responses to a simple event-related auditory-motor task, as well as its effect on activation detection with GLM analyses. We show variability to be higher between subjects than between regions and variation in different regions to correlate from one subject to the other. Accounting for subject-related variability by deriving subject-specific models from responses to the task in some regions lead to more sensitive detection of responses in other regions. We applied the approach to epilepsy patients, where task-derived patient-specific models provided additional information compared to the use of a generic model for the detection of BOLD responses to epileptiform activity identified on scalp electro-encephalogram (EEG). This work highlights the importance of improving the accuracy of the model for detecting neuronal activation with fMRI, and the fact that it can be done at no cost to model parsimony through the acquisition of independent a priori information about the hemodynamic response.NeuroImage 02/2014; · 6.25 Impact Factor
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ABSTRACT: Introduction: Blood oxygenation level-dependent (BOLD) signal changes at the time of interictal epileptic discharges (IEDs) identify their associated vascular/hemodynamic responses. BOLD activations and deactivations can be found within the epileptogenic zone but also at a distance. Source imaging identifies electric (ESI) and magnetic (MSI) sources of IEDs, with the advantage of a higher temporal resolution. Therefore, the objective of our study was to evaluate the spatial concordance between ESI/MSI and BOLD responses for similar IEDs. Methods: Twenty-one patients with similar IEDs in simultaneous electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) and in simultaneous EEG/magnetoencephalogram (MEG) recordings were studied. IEDs in EEG/fMRI acquisition were analyzed in an event-related paradigm within a general linear model (GLM). ESI/MSI of averaged IEDs was performed using the Maximum Entropy on the Mean. We assessed the spatial concordance between ESI/MSI and clusters of BOLD activations/deactivations with surface-based metrics. Results: ESI/MSI were concordant with one BOLD cluster for 20/21patients (concordance with activation: 14/21 patients, deactivation: 6/21 patients, no concordance: 1/21 patients; concordance with MSI only: 3/21, ESI only: 2/21). These BOLD clusters exhibited in 19/20 cases the most significant voxel. BOLD clusters that were spatially concordant with ESI/MSI were concordant with IEDs from invasive recordings in 8/11 patients (activations: 5/8, deactivations: 3/8). Conclusion: As the results of BOLD, ESI and MSI are often concordant, they reinforce our confidence in all of them. ESI and MSI confirm the most significant BOLD cluster within BOLD maps, emphasizing the importance of these clusters for the definition of the epileptic focus.Human Brain Mapping 02/2014; · 6.88 Impact Factor
EEG spectral changes underlying BOLD responses
contralateral tospikes inpatients with focal epilepsy
1Juming M. Yu, Louise Tyvaert, Pierre LeVan, Rina Zelmann, Franc ¸ois Dubeau,
Jean Gotman, andEliane Kobayashi
Montreal Neurological Institute andDepartment ofNeurology and Neurosurgery, McGillUniversity,
and functional magnetic resonance imaging (EEG–
fMRI) in patients with focal epilepsy and unilateral
spikes often shows positive blood oxygenation
level–dependent (BOLD) responses (activations),
not only ipsilateral but also contralateral to the
spikes. We aimed to investigate whether mini-
mal EEG changes could underlie these contra-
lateral BOLD responses by using EEG spectral
Methods: We studied 19 patients with focal epi-
lepsy and unilateral spikes. According to the pat-
tern of BOLD activation, patients were divided
into Group 1 (ipsi- and contralateral to the spikes)
or Group 2 (only ipsilateral). EEG from outside the
scanner was used to mark spikes similar to those
recorded in the scanner. Epochs of 640 ms before
and after the peak of the spikes were chosen as
baseline and spike epochs. Spectral analysis was
performed in referential montage (FCz refer-
ence), and differences between baselines and
spikes were analyzed by paired t-test.
Results: Significant EEG changes in electrodes
contralateral to the spikes were seen in 9 of 10
patients in Group 1 and in only 2 of 10 patients in
Group 2 (one patient had two types of spikes that
were analyzed separately). Spectral changes were
seen in delta and/or theta bands in all patients
except one (in Group 1) who had changes in all
Discussion: Significant contralateral EEG changes
occurred in 90% of contralateral BOLD activations
and in only 20% of patients without contralateral
BOLD responses. The reason why these changes
predominate in lower frequencies rather than in
higher frequencies is unclear. These spectral
changes in areas corresponding to contralateral
activations might reflect poorly synchronized but
possibly intense neuronal activity.
KEY WORDS: EEG–fMRI,Focalepilepsy,Unilateral
spikes, BOLD response, Bilateral BOLD response,
Focal epilepsy is the most frequent type of epilepsy in
adults (Hauser et al., 1993). Although focal epileptiform
discharges on the electroencephalogram (EEG) are char-
acteristic of focal epilepsy, many functional imaging stud-
ies used on a clinical basis, such as positron emission
tomography (PET) (Hammers et al., 2002; Chassoux
et al., 2004) and magnetic resonance spectroscopy (MRS)
(Li et al., 2000; Mueller et al., 2004), frequently disclose
Most imaging techniques do not have sufficient tempo-
ral resolution to assess changes directly related to the
spikes, which occur within a window of milliseconds
duration. Combined recording of EEG and functional
magnetic resonance imaging (EEG–fMRI) is a unique
method that allows us to image the whole brain at the time
of epileptic spikes (Gotman et al., 2006; Gotman, 2008).
It has been demonstrated that EEG–fMRI can identify
positive and negative changes in the blood oxygenation
level–dependent(BOLD) signal related tointerictalspikes
(Bagshaw et al., 2004; Kobayashi et al., 2006; Salek-
Haddadi et al., 2006; Zijlmans et al., 2007).
AcceptedJanuary22, 2009;EarlyViewpublication April6,2009.
Address correspondence to Eliane Kobayashi, M.D., Ph.D., Montreal
Neurological Institute, McGill University, 3801 University Street,
Montreal, Quebec, Canada, H3A 2B4. E-mail: eliane.kobayashi@
1Current address: Department of Neurology, Affiliated Hospital,
Previous EEG–fMRI studies in patients with focal
epilepsies demonstrated that BOLD activations are fre-
quently seen in regions that are spatially concordant
with the localization of the EEG spikes (Bagshaw et al.,
2004; Kobayashi et al., 2006; Salek-Haddadi et al.,
2006; Zijlmans et al., 2007). This is in agreement with
the premise that increased neuronal activity in the focus
leads to an increase in the BOLD signal. However,
BOLD activations often involved additionally
regions contralateral and homologous to the spike topo-
graphy (Kobayashi et al., 2006), where no EEG changes
could be identified. Moreover, we have found in a few
patients responses only contralateral and homologous to
the spike topography, with no ipsilateral involvement
(Kobayashi et al., 2006). This phenomenon has not yet
been investigated, and the possibility of subtle EEG
changes that occur simultaneously or by propagation
cannot be ruled out.
Because fMRI assesses the epileptic network atthe time
of spike occurrence, further characterization of the neuro-
nal correlates of BOLD response may help to interpret this
phenomenon. Finding associated EEG abnormalities may
help confirm that the BOLD responses are not artifactual.
Moreover, these findings may relate to neuropsychologi-
cal deficits or other clinical aspects of epilepsy in an indi-
Objectives and Rationale
Our objective was to investigate whether subtle EEG
changes identified by spectral analysis were associated
with BOLD responses contralateral and homologous to
the EEG focus in patients with focal epilepsy. We aimed
to compare patients with unilateral spikes and bilateral
activations with patients who had only an ipsilateral
responseto the spikes.
We retrospectively investigated patients from the
EEG–fMRI database at the Montreal Neurological Insti-
tute, who had been evaluated between November 2003
and February 2008.
Patients were selected based on the following criteria:
history of focal seizures and unilateral spikes (including
those with bilateral independent spikes, which were ana-
lyzed separately as different spike types), with no general-
A total of 19 patients and 20 EEG–fMRI studies were
included (one patient had two types of spikes that were
analyzed separately). They were eight males and 11
females, whose mean age at EEG–fMRI studies was
33.2 years (range 11–55 years). Mean age at seizure onset
was 15.8 years (range 9 months to 50 years), and mean
duration of epilepsy was 16.5 years (range 5–47 years).
Two patients experienced febrile seizures in childhood.
Seizure frequency ranged from 1 per year to 30 per month.
Based on electroclinical localization and neuroimaging
findings, there were 11 cases of temporal lobe epilepsy, 4
cases of frontal lobe epilepsy (including one frontocen-
tral), 2 cases of frontotemporal epilepsy, and 2 cases of
MRI investigation showed that six patients had unilat-
eral hippocampal atrophy (HA), four had malformations
of cortical development, two had cavernomas, one had a
posttraumatic lesion, one had left frontal and parietal
white matter abnormality (subcortical), and one had
right amygdala atrophy. The remaining four showed no
clear MRI abnormalities. Clinical details are shown in
Based on the spatial distribution of BOLD activations,
patients were divided intotwo groups (Fig. 1):
• Group 1 (bilateral activation): activation was seen
within or very close to the area anatomically related to
the spike (ipsilateral) and involved at the same time the
contralateral homologous region.
• Group 2 (ipsilateral activation): activation occurred
only ipsilateral tothe spikes.
Patients were selected regardless of the presence of
additional areas of activation at a distance from these two
EEG–fMRI acquisition and data processing have been
described in detail in previously published papers
(Bagshaw et al., 2004; Kobayashi et al., 2006). In sum-
mary, EEGs recorded inside the scanner were filtered
offline, for visual identification of spikes, which were
marked according to spatial distribution and morphology.
Each type of spike from each subject constituted one
EEG–fMRI study, generating t-maps of the BOLD
response. In the present study, only activations (positive
BOLD responses) have been evaluated.
EEG spectral analysis
Although it is possible to successfully remove the
gradient artifact from the EEG recorded inside the
MRI scanner to identify the spikes, residuals might
be still present in the signal and might affect spectral
decided to use EEGs from video-EEG monitoring (not
recorded during fMRI scanning). Only one patient did
not have such an investigation, and we used a pro-
longed EEG recording acquired immediately after the
EEG–fMRI session. Telemetry EEG was recorded by
21 electrodes using the 10–20 system, in addition to
zygomatic electrodes and inferior temporal electrodes
placed according to the 10–10 system. The interval
between telemetry EEGs and EEG–fMRI investigations
Spectral Changes in EEG–fMRIResponses
ranged from 1 to 9 days. The EEG of the patient
who had a prolonged recording immediately after the
EEG–fMRI study included 44 electrodes placed on
the scalp according to the 10–10 system.
Spikes with spatial distribution and morphology similar
to those in the EEG–fMRI session were marked in the
telemetry EEG. For each patient, a minimum of 20 spikes
An EEG segment of 640 ms before and after the peak
of the marked spikes was used as baseline and spike
epoch, respectively. The order of magnitude of the
length (0.5–1 s) was selected because we hypothesized
that this is a reasonable duration for which one could
expect the effect of a spike, itself lasting around
100 ms, to last. The specific value of 640 ms comes
from the convenience of using a number of samples that
is a power of 2 for the calculation of the fast Fourier
transform. Given the 200 Hz sampling rate, 128 samples
correspond to 640 ms. Fluctuations in the level of alert-
ness of the subject result in important fluctuations of
EEG baseline. To compare the post-spike segment to a
baseline segment that is most likely to be in the same
state, we selected the baseline segment just before the
spike. In some patients we had to select a baseline epoch
that was farther from the spike due to the presence of
repeated spikes or bursts of slow waves occurring with
the spike under consideration. The referential montage
(FCz) was used for spectral analysis, which included
five frequency bands: delta (0.1–4 Hz), theta (4–8 Hz),
alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–
70 Hz). For each study, we selected for spectral analysis
one electrode contralateral and homologous to the
region of the ipsilateral BOLD response (Fig. 2). The
differences between baselines and spikes for each study
were analyzed by paired t-test (spike minus baseline)
at a p £ 0.05. Analysis was performed using Matlab
(Mathworks, Natick, MA, U.S.A.).
Table1. Clinical data of thepatientsa
L F andT
L,left; R, right;B, bilateral; T, temporal;F, frontal;P, parietal; C,central; O,occipital; I, insular.
WMA, white matter abnormality; MCD, malformation of cortical development; HA, hippocampal atrophy; AA, amygdala atrophy;
PHN, periventricular nodular heterotopia; CPS, complex partial seizure; GTCS, secondary generalized tonic–clonic seizure; SPS,
aDiagnosis is based on neuroimaging findings and electroclinical localization according to the International League Against
Epilepsy (ILAE) criteria.
Patients were grouped by activation patterns (in
orange). Group 1, activations ipsilateral and contra-
lateral tothespikes.Group2,only ipsilateralactivation.
J. M. Yu et al.
One patient had two types of spikes, which corre-
sponded, respectively, to Group 1 and Group 2. Therefore,
a total of 20 spectral studies in 19 patients were per-
formed: 10 in Group 1 and 10 in Group 2. The mean num-
ber of spikes in the spectral analysis per study was 30.4
(range 21–48)in Group 1and 23.9 (range 20–32) inGroup
2. We averaged all spikes from each patient: the average
spike voltage in Group 1 was 74 lV and in Group 2 was
73 lV (t = 0.071; p = 0.94;d.f. = 18).
Group 1(bilateral activation)
Nine of the 10 studies showed spectral changes in both
delta and theta bands (n = 3), in delta band only (n = 3),
in theta band only (n = 2), or in delta, theta, alpha, and
beta bands (n = 1). See Table 2for details.
The only patient (no. 10, in Table 2) in this group who
did not show spectral changes had T4–T6 spikes but
strongbilateralhomologousBOLDactivation inthe parie-
tal lobes. We, therefore, selected P3 as the electrode on
which to perform spectral analysis in the contralateral
Group 2(ipsilateral activation only)
Only 2 of the 10 studies (from patients 11 and 12 in
Table 3) showed spectral changes, in delta band (n = 1) or
in theta band (n = 1). See Table 3 fordetails.
Example of electrode selection for spectral analysis.
(A) Activations in bilateral homologous regions, in a
patient with left temporal spikes (Patient 9, Table 2).
Activations are close to electrodes T3 and T4, and the
T4 electrode was chosen for spectral analysis. (B) Ipsi-
lateral activation only, in a patient with right temporal
spikes (Patient 18, Table 3). Activation is adjacent to
electrode F8, and the F7 electrode was, therefore,
selected for spectral analysis. To note: maximum
BOLD response in these two patients appears maxi-
mum in the suprasylvian rather than in the temporal
regions. This same pattern has been demonstrated in a
series of patients with temporal lobe epilepsy patients
who have studied (Kobayashi et al., 2006; Epilepsia),
and this has been confirmed in an interindividual analy-
sis as the common pattern of activation found in
patients with temporal lobe epilepsy (Kobayashi E,
Grova C, DuveauF, Gotman J., unpubl. ms.).
Table 2. Summary of spectral analysis results
in Group 1
L, left; R, right; B, bilateral; T, temporal; F, frontal; P, parietal;
C,central;O, occipital; I,insular.
Table 3. Summary of spectral analysis results
in Group 2
L, left; R, right; B, bilateral; T, temporal; F, frontal; P, parietal;
C,central;O, occipital; I,insular.
Spectral Changes in EEG–fMRIResponses
To exclude the possibility that, in these two patients
who had spectral changes, there were activations just
below the statistical threshold of the t maps, we looked
back at the maps with a lower threshold. No activations
could be seen in the contralateral region, even when using
a lower threshold.
To evaluate whether this lack of spectral change in
Group 2 was due to suboptimal selection of the contralat-
eral electrode, we further investigated whether in these
studies with no spectral changes, the four electrodes
located around the originally chosen one showed any
spectral change. No changes could be seen in this addi-
In this study we aimed to assess the origin of the con-
tralateral BOLD changes that has been observed in
spikes that appear unilateral on EEG. We could demon-
strate that this corresponds to a subtle EEG change and,
therefore, confirm that genuine contralateral changes
can occur in spikes that appear unilateral. Although
BOLD responses at a distance from the focus seem to
occur frequently (Bagshaw et al., 2004; Kobayashi
et al., 2006; Salek-Haddadi et al., 2006; Zijlmans et al.,
2007), contralateral homologous responses to unilateral
spikes seem to be observed in a larger proportion than
other brain regions (Kobayashi et al., 2006). The possi-
bility of propagation of epileptic activity, effect at a
distance from the spike, or simultaneous changes in
neuronal activity could underlie this phenomenon. In
our patient group, spikes were strictly unilateral and no
contralateral spike could be seen by visual inspection of
the EEG. We found that 90% of contralateral homolo-
gous activations were associated with minimal but sig-
nificant EEG changes, mostly in delta or theta bands.
Such abnormalities occurred in only 20% of studies with
activation only ipsilateral to the spikes.
In summary, in the majority of our studies we found (1)
contralateral homologous BOLD activation with concom-
itant spectral EEG changes; and (2) no contralateral spec-
tral changes in most cases where there was no
contralateral BOLD response. These two scenarios cor-
roborate our working hypothesis. However, we also found
in a much smaller proportion of studies: (3) contralateral
homologous activation without concomitant spectral
changes, seen in one study; and (4) spectral changes con-
tralateral to the spikes, despite only ipsilateral activation,
seen in two studies.
Observations (1) and (2) suggest that although we do
not identify any clear EEG transients the electrodes con-
tralateral to the spikes, subtle EEG changes do exist in
underlying regions of BOLD activation. One explanation
for these changes in delta and theta bands could be that
some spikes are followed by a slow wave, which could
have a wider distribution than the spike itself, including
the contralateral region. However, slow waves following
the averaged spikes for each patient were equally identi-
fied in both groups (seven studies in each group), thus not
supporting such a hypothesis to explain spectral changes
observed inGroup 1.
One could consider whether the frequency of secondary
generalized tonic–clonic seizures (GTCS) could influence
the presence of contralateral spread and BOLD response
in Group 1. However, there were more patients in Group 2
(n = 6) than in Group 1 (n = 4) with history of GTCS, and
only one patient in Group 1 was still having frequent
GTCS at the time of scanning (3–4 per month). Therefore,
frequency of GTCS does not explain the difference
The fact that we have not identified any spectral
changes when further exploring the electrodes surround-
ing the contralateral region in Group 2, suggests that the
presence or absence of such changes is not diffuse in
the contralateral hemisphere. This supports the idea that if
contralateral homologous activation, this finding is not
related toa widespread nonspecific effect of the spikes.
The effect at a distance of the spikes could, therefore,
occur as propagation of the epileptic activity, following
the underlying structure of the epileptic network and
involving the mirror region of the main activated area.
Although the underlying path forthis possible propagation
could be transcallosal in at least some of these patients, we
have no means of proving it. Propagation speed cannot be
assessed by such a low temporal resolution method as the
hemodynamic response measured by the BOLD signal. If
propagation indeed occurs, it does not result in activity
that is sufficiently synchronous to be seen in the scalp
EEG, since no clear discharge can be seen in these contra-
A possible explanation for observation (3) is related to
the fact that, in this patient, the spikes from which the
BOLD maps originated and which were used to trigger the
spectral analysis, had right temporal topography, whereas
the bilateral activation and, therefore, the EEG electrode
analyzed were in parietal regions. This could suggest that
both ipsilateral and contralateral parietal responses corre-
spond to an effect at a distance from the original spike.
However, this left parietal activation had a high t value,
and we cannot explain why such robust hemodynamic
response does not appear associated with any underlying
In situation (4), we have excluded the presence of con-
tralateral homologous activation just below threshold in
these areas showing EEG spectral changes, by looking at
the BOLD maps with a lower threshold. One possible
explanation is that in these two studies, the spectral
changes that were seen were not sufficient to cause any
detectable BOLD changes. This could be compared with
J. M. Yu et al.
patients who have a good number of spikes during an
EEG–fMRI acquisition, but for whom no BOLD
responses can be detected in the t maps. The possibility of
a variation of the neurovascular coupling in these specific
regions cannot be ruled out.
In this study, we have not looked at deactivations. This
was due to the fact that the number of EEG–fMRI studies
that had ipsilateral onlyor bilateral deactivations to unilat-
eral spikes, was much lower and not sufficient to provide
statistical power to the analysis. In addition, the signifi-
cance of deactivations is much less understood, and these
uncertainties could make any analysis much more specu-
lative than activations, which are known to be related to
increased neuronal activity. We do acknowledge, how-
ever, that the evaluation of these negative BOLD
responseswould also be interesting.
We have demonstrated that epileptic spikes that appear
unilateral are often accompanied by a contralateral change
in the form of a BOLD activation associated with an EEG
change; other spikes that appear similarly unilateral are
not accompanied by either BOLD change or EEG change.
The EEG–fMRI method was thus able to identify the
spikes that have a contralateral effect, and this change
could be confirmed with EEG analysis. Spikes that have a
contralateral effect may have a more deleterious effect on
cognition or long-term epileptogenesis than spikes that
remain totally unilateral.
Study supported by operating grant MOP-38079 from the Canadian
Institutes of Health Research. JMY is supported by China scholarship
Council. LT is supported by a postdoctoral fellowship from the Savoy
Foundation for Epilepsy. EK is supported by the Milken Family Founda-
tion through the Early Career Physician Scientist Award from the Ameri-
We confirmthatwe haveread the Journal’s positionon issuesinvolvedin
ethical publication and affirm that this report is consistent with those
Disclosure:Noneofthe authorshasanyconflictofinterestto disclose.
Bagshaw AP, Aghakhani Y, B?nar CG, Kobayashi E, Hawco C, Dubeau
F, Pike GB, Gotman J. (2004) EEG–fMRI of focal epileptic spikes:
analysiswith multiplehaemodynamic functionsandcomparisonwith
gadolinium-enhanced MR angiograms. Hum Brain Mapp 22(3):179–
Chassoux F, Semah F, Bouilleret V, Landre E, Devaux B, Turak B,
Nataf F, Roux FX. (2004) Metabolic changes and electro-clinical
patterns in mesio-temporal lobe epilepsy: a correlative study. Brain
Gotman J, Kobayashi E, Bagshaw AP, B?nar CG, Dubeau F. (2006)
Combining EEG and fMRI: a multimodal tool for epilepsy research.
Gotman J. (2008) Epileptic networks studied with EEG–fMRI. Epilepsia
DJ, Duncan JS. (2002) Abnormalities of grey and white matter
[11C]flumazenil binding in temporal lobe epilepsy with normal MRI.
Hauser WA, Annegers JF, Kurland LT. (1993) Incidence of epilepsy and
unprovoked seizures in Rochester, Minnesota: 1935–1984. Epilepsia
Kobayashi E, Bagshaw AP, Benar CG, Aghakhani Y, Andermann F,
Dubeau F, Gotman J. (2006) Temporal and extratemporal BOLD
responses to temporal lobe interictal spikes. Epilepsia 47(2):343–
Li LM, Cendes F, Andermann F, Dubeau F, Arnold DL. (2000) Spatial
extent of neuronal metabolic dysfunction measured by proton MR
spectroscopic imaging in patients with localization-related epilepsy.
Mueller SG, Laxer KD, Cashdollar N, Flenniken DL, Matson GB, Wei-
ner MW. (2004) Identification of abnormal neuronalmetabolism out-
sidethe seizurefocusin temporallobeepilepsy.Epilepsia45(4):355–
Salek-Haddadi A, Diehl B, Hamandi K, Merschhemke M, Liston A, Fris-
ton K, Duncan JS, Fish DR, Lemieux L. (2006) Hemodynamic corre-
lates of epileptiform discharges: an EEG–fMRI study of 63 patients
Zijlmans M, Huiskamp G, Hersevoort M, Seppenwoolde JH, van Huffe-
len AC, Leijten FS. (2007) EEG–fMRI in the preoperative work-up
Spectral Changes in EEG–fMRIResponses