Hemodynamic and metabolic responses to activation, deactivation and epileptic discharges

www.elsevier.com/locate/ynimg NeuroImage 28 (2005) 205 – 215

Hemodynamic and metabolic responses to activation, deactivation and epileptic discharges Bojana Stefanovic,* Jan M. Warnking, Eliane Kobayashi, Andrew P. Bagshaw, Colin Hawco, Franc¸ois Dubeau, Jean Gotman, and G. Bruce Pike Montreal Neurological Institute, 3801 University Street, Montreal, QC, Canada H3A 2B4 Received 2 February 2005; revised 24 March 2005; accepted 19 May 2005 Available online 5 July 2005 To investigate the coupling between the hemodynamic and metabolic changes following functional brain activation as well as interictal epileptiform discharges (IEDs), blood oxygenation level dependent (BOLD), perfusion and oxygen consumption responses to a unilateral distal motor task and interictal epileptiform discharges (IEDs) were examined via continuous EEG-fMRI. Seven epilepsy patients performed a periodic (1 Hz) right-hand pinch grip using ¨8% of their maximum voluntary contraction, a paradigm previously shown to produce contralateral M1 neuronal excitation and ipsilateral M1 neuronal inhibition. A multi-slice interleaved pulsed arterial spin labeling and T2*-weighted gradient echo sequence was employed to quantify cerebral blood flow (CBF) and BOLD changes. EEG was recorded throughout the imaging session and reviewed to identify the IEDs. During the motor task, BOLD, CBF and cerebral metabolic rate of oxygen consumption (CMRO2) signals increased in the contra- and decreased in the ipsilateral primary motor cortex. The relative changes in CMRO2 and CBF were linearly related, with a slope of 0.46 T 0.05. The ratio of contra- to ipsilateral CBF changes was smaller in the present group of epilepsy patients than in the healthy subjects examined previously. IEDs produced both increases and decreases in BOLD and CBF signals. In the two case studies for which the estimation criteria were met, the coupling ratio between IED-induced CMRO2 and CBF changes was estimated at 0.48 T 0.17. These findings provide evidence for a preserved coupling between hemodynamic and metabolic changes in response to both functional activation and, for the two case studies available, in response to interictal epileptiform activity. D 2005 Elsevier Inc. All rights reserved. Keywords: EEG-fMRI; Epilepsy; Negative BOLD; Perfusion; Oxygen consumption

Introduction Although the relationship between ictal and interictal epileptic activity is not entirely understood (Badier and Chauvel, 1985, 1995; Alarcon et al., 1994; de Curtis and Avanzini, 2001; Avoli, * Corresponding author. Fax: +1 514 398 2975. E-mail address: [email protected] (B. Stefanovic). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter D 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2005.05.038

2001; Janszky et al., 2001), interictal epileptiform discharges (IEDs) represent a very specific marker of epilepsy, the delineation of the irritative zone (Rosenow and Luders, 2001) being of particular interest for presurgical evaluations of epileptic patients (Penfield and Jasper, 1954; Kanner et al., 1995; McKhann et al., 2000). Interictal activity has traditionally been studied with electroencephalography (EEG), IEDs producing pronounced and stereotyped electroencephalographic trace deviations. Although ictal activity is generally associated with increased metabolism and perfusion (Duncan, 1997), no consistent changes in cerebral metabolic rate of glucose consumption (CMRGlc) or cerebral blood flow (CBF) in response to interictal epileptiform activity have been demonstrated (Theodore et al., 1985; Ochs et al., 1987). This has often been ascribed to the poor sensitivity of the methods employed, e.g., low statistical power and poor temporal resolution of positron emission tomography (PET) studies, the latter leading to amalgamation of different states within each measurement (Duncan, 1997; Sperling and Skolnick, 1995). In the last decade, functional magnetic resonance imaging (fMRI) has been deployed in conjunction with EEG (Ives et al., 1993; Huang-Hellinger et al., 1995; Warach et al., 1996) to improve the EEG-based localization of the irritative zone and enable investigation of the hemodynamic and metabolic correlates of IEDs with high spatial and temporal resolution (Seeck et al., 1998; Krakow et al., 1999; Patel et al., 1999; Lazeyras et al., 2000; Jager et al., 2002; Al-Asmi et al., 2003). However, full use of the information afforded from fMRI BOLD data in the combined EEG-fMRI investigations is predicated on the understanding of the physiological changes determining the BOLD response, which are incompletely understood even in normal functional brain activation. Detailed investigation of the BOLD response to IEDs has only recently begun (Lemieux et al., 2001; Benar et al., 2002; Bagshaw et al., 2004; Aghakhani et al., 2004). Regional negative BOLD responses to IEDs have been observed (Salek-Haddadi et al., 2003b; Archer et al., 2003a,b; Bagshaw et al., 2004; Aghakhani et al., 2004), but their origins are presently unknown. In contrast to focal epilepsies where an uncoupling between CBF and CMRGlc has been suggested (Gaillard et al., 1995; Fink et al., 1996; Breier et al., 1997; Bruehl et al., 1998) (and disputed

206

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

(Franck et al., 1989; Kuhl et al., 1980)), the diffuse neurophysiological abnormalities assumed to exist in patients with idiopathic generalized epilepsy (IGE) are commonly believed not to influence the nature of the coupling between metabolic and hemodynamic changes, and hence the interpretation of BOLD fMRI response. While the neurovascular coupling in IGE has largely been unexplored, it may, in principle, still be compromised (as it is in partial epilepsies) even in the interictal state as a result of pharmacological interventions (Theodore et al., 1989; Leiderman et al., 1991), the cumulative effect of seizures, an IED-instigated rise in extracellular potassium (Jensen and Yaari, 1997), pH changes in the course of after-potentials hyperpolarization (de Curtis et al., 1998) and compromised functioning of astrocytes (Grisar et al., 1999), potential mediators of neurovascular coupling (Salek-Haddadi et al., 2003a). In the present study, we set out to investigate the coupling between perfusion and oxygen consumption changes in a group of epilepsy patients, in response to both a motor task and IEDs. Although no direct measurements of this coupling have thus far been made, it is critical for the interpretation of the BOLD fMRI studies in epilepsy. The selected motor task, involving a low-force phasic pinch grip, is known to produce neuronal deactivation (and correspondingly, a negative BOLD response) in the ipsilateral primary motor cortex in addition to neuronal activation (producing a BOLD signal increase) of the contralateral primary motor cortex (Boroojerdi et al., 1996; Netz et al., 1995; Gerloff et al., 1998; Liepert et al., 2001; Ferbert et al., 1992; Hamzei et al., 2002). In a recent study of healthy young adults performing this task, we found the same coupling between changes in oxygen consumption and flow in response to both neuronal activation and deactivation (Stefanovic et al., 2004). In view of the present understanding of IGE, we hypothesized that these patients would exhibit normal coupling between hemodynamic and metabolic responses following neuronal activation or deactivation, with a consistent relationship between CMRO2 and CBF changes underlying both positive and negative steady-state BOLD signal changes. Furthermore, the relatively small perturbations in neuronal state elicited by IEDs were expected to fall within the normal operating range of the neuronal circuitry: the spike-induced flow and oxygen consumption changes were thus anticipated to follow those observed during physiologic stimulation. Here, we report on the relationship between blood flow and oxygen consumption in regions of sustained BOLD and CBF signal increases, in the contralateral primary motor cortex (M1), and their decreases, in the ipsilateral M1, in response to the motor task previously employed in a study of healthy volunteers. Furthermore, the hemodynamic and metabolic responses induced by interictal epileptiform activity were quantified. The present findings elucidate the nature of the metabolic and vascular responses to normal neuronal activation, deactivation and IEDs in the brain of patients with epilepsy.

Methods Overall, the BOLD and CBF responses were simultaneously measured in a group of epilepsy patients exhibiting generalized IEDs who performed a motor task known to produce neuronal activation in the contra- and deactivation in the ipsilateral primary motor cortex. The electroencephalogram was recorded simultaneously with the fMRI to identify the occurrences of the IEDs and

thus allow the quantification of BOLD and CBF responses to IEDs. The concomitant changes in oxygen consumption were estimated via the deoxyhemoglobin dilution model (Davis et al., 1998; Hoge et al., 1999) in conjunction with BOLD and CBF data obtained during the administration of hypercapnia. Motor task The motor task employed was identical to that described in an earlier study of 8 healthy adults (Stefanovic et al., 2004). Briefly, the maximum voluntary contraction of the right-handed pinch grip was measured for each patient. The patients were then trained to perform the pinch grip at a frequency of 1 Hz, on each grip pressing a water-filled ball with the thumb and the index finger of the right hand. The recording and analysis of the exerted pressure was performed in real time and an auditory feedback provided to the patient: a low frequency tone indicated that the force applied was in the desired range, namely within 20% of the target level. A high frequency tone accompanied too strong a force, and no tone was played out when insufficient force was exerted. To minimize habituation, the target level was randomized on each pinch grip and varied between 6 and 10% of the patient’s maximum voluntary contraction. Hypercapnic modulation Mild hypercapnia was induced through administration of mixtures of carbon dioxide and air through a non-rebreathing face mask (Hudson RCI, Model 1069, Temecula, CA). At baseline, the subjects were inhaling medical air (21% O2, balance N2), supplied at 16 L/min. During hyper-capnic perturbations, a premixed preparation of 10% CO2, 21% O2 and balance N2 (BOC Canada Ltd., Montreal, Quebec, Canada) was combined with medical air in a Y-connector. Three levels of hypercapnia were administered, with CO2 concentration of 4, 6, and 8%, respectively. At each level, the gas flow rates were adjusted to maintain a total flow rate of 16 L/ min. End-tidal CO2 was measured via a nasal cannula with monitoring aspirator (Normocap 200, Datex Inc., Plymouth, ME) and increased an average 17 T 4 mm Hg (or 59 T 21%) during inhalation of the highest CO2 concentration mixture. Subjects were asked to breathe at a constant rate, and their respiratory rate was monitored via the capnometer. Patients Seven patients (6 females and 1 male; average age 40 T 6 years) participated in the study. They were selected from a database of 91 epileptic patients (of which 25 had IGE) who had undergone combined EEG-fMRI monitoring at the Montreal Neurological Institute. The patients were selected based on a strong IED-induced negative BOLD response (at least one cluster of
20 voxels with peak t value 5) and overall cooperativity in the prior (no more than 30 months earlier) scanning session, as well as willingness to participate. The exclusion criteria comprised a history of asthma or past neurosurgical interventions. Six of the seven patients were clinically diagnosed with IGE and the remaining one with parietooccipital epilepsy. The top portion of Table 1 summarizes the clinical characteristics of each patient. Informed consent was obtained from each subject prior to the scanning session, the experimental protocol having been approved by the Research Ethics Board of the Montreal Neurological Institute.

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

207

Table 1 Summary of clinical characteristics, electroencephalographic findings, and BOLD/CBF regions of activation/deactivation in each subject Subject Id

1

2

3

4

5

6

7

Age (at onset) [years] Sex Epilepsy syndrome Medications [mg/day]

43 (8) F POE CBZ 800 LMT 400

67 (19) M JME LMT 400 VA 750

24 (7) F JAE LMT 500 VA 375

51 (4) F JAE LMT 200 VA 500

26 (12) F JAE VA 1000

38 (14) F JME CBZ 200

Anatomical MRI

Bilateral PO polymicrogyria polyspikes 404 (N/A) <1 b m PO b P; b Pc b FP b PO

34 (7) F JAE LEV 2000 TPM 50 VA 1750 Normal

Enlarged ventricles

Normal

Normal

Normal

Normal

2–3 82 (5) 4.0 T 1.8 r PO/b m P/b TPO/b TPO none/b PO/b m O/b m PO b P; b PO F; b FP; b P b F; l PO; b m PO; b m PO

4 22 (1) 2T0 bC r m P; r Mc; b P; l PO A A

3–4 39 (8) 2.7 T 0.8 lC r F; l C rF b F; b P

3 33 (14) 2.5 T 0.8 b m PO; b P None A lF

N/A 0 (0) N/A None None None None

4 40 (7) 2.2 T 0.3 b F; b O b Pc; b PO b PO bF

SW frequency [Hz] No. of events (bursts) Burst duration [s] BOLD activations BOLD deactivations CBF activations CBF deactivations

SW: spike and wave; POE: parietooccipital epilepsy; JAE: juvenile absence epilepsy; JME: juvenile myoclonic epilepsy; CBZ: carbamazepine; LMT: lamotrigine; LEV: levetiracetam; TPM: topamax; VA: valproate; b: bilateral; r: right; l: left; m: mesial; P: parietal; O: occipital; F: frontal; T: temporal; C: central; Pc: posterior cingulate; Mc: mid-cingulate; A: scattered throughout the brain. Note that the number of events comprises both isolated events and bursts.

Experiment The scanning protocol consisted of a high-resolution 3 D RFspoiled T1-weighted gradient echo (1  1  2 mm3) sequence for anatomical reference, followed by a multi-slice interleaved pulsed arterial spin labeling (PASL) and T2*-weighted gradient echo sequence for CBF and BOLD signal measurements. The highresolution gradient echo sequence employed a TR of 22 ms, a TE of 10 ms and non-selective 30- RF-spoiled excitation. The CBF and BOLD acquisitions covered 8 slices (inter-slice gap of 1 mm), positioned to include the primary motor cortices as well as the regions showing most prominent BOLD activations and deactivations based on the results of the prior EEG-fMRI experiment. The CBF data were acquired using a QUIPSS II sequence (Wong et al., 1997) with two presaturation BASSI pulses (Warnking and Pike, 2004) in the imaging region followed by an adiabatic BASSI inversion pulse in the labeling region (thickness of 100 mm, gap of 5 mm), with a QUIPSS II delay (TI1) of 700 ms and a post-label delay (TI2) of 1300 ms. An EPI readout (2232 Hz/pixel) was employed, with an echo time of 50 ms for BOLD and 28 ms for CBF (with 4  4  5 mm3 resolution). To increase the signal-tonoise ratio, the resolution was decreased to 5  5  5 mm3 for the latter 5 subjects, resulting in a 22-ms TE for CBF. The repetition time was 2.5 s for the first 2 subjects (subjects 2 and 7), and 1.8 s for the remaining 5 subjects. EEG data were continuously recorded via 21 MR-compatible Ag/AgCl electrodes, placed according to the International 10 – 20 system, with signal sampled at 5 kHz and amplified using a BrainAmp (Brain Products, Munich, Germany) amplifier. The functional paradigm involved 24 repetitions of ¨20 s/60 s/ 40 s off/on/off blocks (only 12 repetitions were done in subjects 2 and 7), rest alternating with the low force, phasic, right-handed pinch grip, the beginning of each block being indicated by auditory cues. Following the functional scan, medical air alternating with graded hypercapnia was administered in three 1 min/3 min/2 min blocks. The total scanning time was approximately 75 min. Patients were immobilized using a vacuum bag (S&S x-ray products, Brooklyn, NY). The RF body coil was used for transmission and a quadrature head coil for signal reception. All

the examinations were performed on a Siemens 1.5 T Magnetom Sonata system. Data analysis EEG data analysis The EEG was filtered offline to remove the artifact generated by the MR scanner (Vision Analyser software, BrainProducts, Munich, Germany). EEG was reviewed by an experienced electroencephalographer (EK), who identified the IEDs according to their spatial distribution, morphology, timing and duration. The durations of the events marked were not different from habitual IEDs. The type of IED was determined based on the spatial distribution and morphology observed on the scalp EEG, resulting in 10 data sets from the seven patients (subject 6 had no IEDs and subject 2 had 4 event types). fMRI data statistical analysis The fMRI data were motion corrected using AFNI’s 3dvolreg software (Cox, 1996). The data were spatially smoothed using a three dimensional Gaussian filter with full width half maximum of 6 mm. Drift was removed by subtracting from each voxel’s time course the low-frequency components of its discrete cosine transform, with a cutoff frequency of one half of the stimulation paradigm frequency. The generalized linear model (Worsley et al., 2002) was used to identify areas of statistically significant task correlation as well as those of statistically significant IEDs correlation at the omnibus significance level of 0.05 in BOLD and CBF data, respectively. The motor task and hypercapnia induced BOLD and CBF response amplitudes from the general linear model were normalized by the baseline signal values and averaged over the voxels of each ROI. To allow for establishment of a physiological steady-state, the hypercapnic data acquired within half a minute following a change in the concentration of the inspired CO2 was excluded from the analysis. The ratios of contra- to ipsilateral BOLD and CBF responses to the motor task were compared to the corresponding values in healthy controls (Stefanovic et al., 2004). Notably, the normalization of contra- by ipsilateral values was performed in each

208

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

subject prior to the comparison in view of the potential confounding effects of the antiepileptic medications on the global resting flow (Gaillard et al., 1996) and the known large inter-subject variability in CBF responses to motor activation in healthy subjects. With respect to the IED events, each data set was analyzed with four impulse response functions, modeled as monophasic, single gamma functions, peaking 3, 5, 7 and 9 s following the event to allow for some variation in the latency of the response while retaining information about its expected shape (Buckner, 1998; Bagshaw et al., 2004). The full width at half maximum of the gamma functions was 5.2 s; the duration of the burst was input when modeling the response. Composite statistical maps were created by taking the maximum value from the four analyses at each voxel, as described by Bagshaw et al. (2005). IED response estimation The regions of interest for IED response estimation were chosen as the clusters in BOLD/CBF t value maps showing statistically significant correlation with the IED events and having at least 5 and no more than 20 voxels (i.e., with a volume, V, 0.625 cc  V  2.5 cc). The IED responses were then estimated by fitting the fMRI signal within each region of interest (ROI) using a Fourier basis set (Josephs et al., 1997; Kang et al., 2003). Only data from those BOLD/CBF ROI pairs whose centers of mass were within 5 mm of each other were considered for CMRO2 estimation, described below. Within each subject, the peak BOLD/CBF changes from all regions of interest satisfying this criterion were averaged before the CMRO2 estimation was done. CMRO2 estimation The hypercapnic data were averaged across all subjects, at each level of hypercapnia and a common maximum achievable BOLD signal change (M) was estimated by linear fitting of the transformed and averaged CBF data vs. averaged BOLD data to the deoxyhemoglobin dilution model (Davis et al., 1998; Hoge et al., 1999):  

DBOLD CBF a  h : ¼M 1 BOLD0 CBF0

ð1Þ

We thus assumed no effect of the mild hypercapnia elicited in this experiment on the rate of oxygen consumption. The a and h

were set to 0.38 and 1.5, respectively (Grubb et al., 1974; Boxerman et al., 1995). The individual motor task-induced CMRO2 changes were next calculated using the M (and its associated standard error) from Eq. (1) in combination with the measured BOLD and CBF data during the functional run, as follows (Davis et al., 1998; Hoge et al., 1999):   1h1 0 
a DBOLD BOLD0 CMRO2 CBF 1  h @ A ¼ 1 : ð2Þ CBF0 M CMRO2 j0 Therefore, the errors in the M estimate from the linear fitting of the transformed and averaged CBF hypercapnia data to averaged BOLD hypercapnia data were propagated into the errors on the calculated activation-induced CMRO2 changes. Finally, a single straight line was fit to the noisy CMRO2, noisy CBF data pairs from both contra- and ipsilateral ROIs of all subjects to obtain an optimal estimate of the CMRO2/CBF coupling ratio for the motor task. The same analysis was performed for the peak BOLD and CBF changes from IED-elicited responses to estimate CMRO2 change as well as the CMRO2/CBF coupling ratio following IEDs. The quality of each fit was assessed by v 2 analysis, with the v 2 probability reported as q (Press et al., 1992).

Results Motor task-induced responses Task-induced increases in BOLD signal were observed, contralaterally, in the primary sensorimotor cortex (SM1), premotor cortex (PMC), supplementary motor area (SMA), as well as a part of the posterior parietal association cortex (PPC) flanking the postcentral sulcus. Ipsilaterally, BOLD signal increased in the secondary areas (namely, PMC, SMA and PPC), but decreased in the primary sensorimotor cortex. Fig. 1 shows a slice of BOLD and CBF ROIs, summed over all subjects after registration (Collins et al., 1994) with the Montreal Neurological Institute template brain (Evans et al., 1993). The (x, y, z) coordinates (in mm) of the center of mass of the t value based primary motor cortex ROIs transformed into the Talairach space and summed over all subjects were (35, 24, 54) for contralateral BOLD, (36, 23, 55) for

Fig. 1. Regions of interest based on t value maps thresholding for BOLD (a) and CBF (b), transformed into the Talairach space and summed over all subjects, are overlaid on the average of all subjects anatomical scans in the Talairach space. The contralateral ROIs are displayed in red and the ipsilateral in green.

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

ipsilateral BOLD, (37, 22, 53) for contralateral CBF, and (35, 24, 54) for ipsilateral CBF. A typical set of BOLD signal and CBF time courses, in both contra- and ipsilateral M1-ROIs of a subject, is shown in Fig. 2. Fig. 3 displays all measured BOLD and CBF data pairs, for hypercapnic perturbation and motor task, as well as the calculated iso-CMRO2 contours. In 5 out of 7 subjects, the magnitude of CBF and BOLD signal changes were larger in the contra- than in the ipsilateral ROI. The maximum achievable BOLD signal increase (M), obtained by linear fitting of the average hypercapnia data across all subjects, was 0.046 T 0.013, corresponding to a DR 2* of 0.9 T 0.2 s1. The v 2 analysis indicated a good fit ( q = 0.39) (Press et al., 1992). The calculated CMRO2 and the corresponding measured CBF changes, for each subject, are displayed in Fig. 4. The slope of the straight line fit to these data yielded a CMRO2/CBF coupling ratio of 0.46 T 0.05 (with q of 0.92 indicating an excellent fit (Press et al., 1992)). Comparison with controls The data of Fig. 3 has been replotted in Fig. 5, in conjunction with the corresponding data from our previous study, which

209

employed the same motor paradigm in a group of healthy subjects (Stefanovic et al., 2004). Notably, the ratio of contra- to ipsilateral CBF responses is significantly ( P ¨ 0.017) smaller in epileptic patients (2.2 T 1.3) than in healthy subjects (4.2 T 2.3). Average contra- and ipsilateral CBF responses across subjects are shown in Fig. 6. A very similar level of deactivation-induced percent CBF decrease is seen in the two groups, in contrast to a smaller excitation-induced percent CBF increase in the epilepsy patients. The same trend of lower contra-to ipsilateral BOLD responses in epileptic patients relative to controls is observed (2.7 T 2.5 vs. 3.7 T 2.1), though it does not reach significance ( P ¨ 0.21). IED-induced responses Six out of seven patients exhibited epileptiform activity in the course of the scanning session (cf. Table 1 for the summary of EEG findings). In each of these subjects, the interictal epileptiform discharges induced both increases and decreases in BOLD and CBF signals, as summarized in Table 1. Only two of the six subjects exhibited sufficiently co-localized (i.e., at most 5 mm separation between their respective ROI centers of mass, as described in Methods) statistically significant changes in both

Fig. 2. Time courses of contralateral (positive) BOLD (a) and CBF (b), as well as ipsilateral (negative) BOLD (c) and CBF (d) percent changes in subject 1. The standard errors are shown as dashed lines. All time course data have been low pass filtered with a Hanning window (FWHM = 20 s) prior to averaging across 24 sessions.

210

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

Fig. 3. The percent changes in BOLD and CBF signals in the ipsilateral ROIs (green circles) and contralateral ROIs (red triangles) for each subject. The average hypercapnia data (black squares) are displayed along with the corresponding fit (indicated by crosses), representing the baseline isoCMRO2 contour. The estimate of the maximum achievable BOLD signal change was substituted into the equation [13] of the deoxyhemoglobin dilution model (Hoge et al., 1999) to generate non-baseline iso-CMRO2 contours (shown as solid black curves), at 10% intervals. The shaded area corresponds to the shaded region of Fig. 4.

Fig. 5. The percent changes in BOLD and CBF signals induced by the motor task in the ipsilateral ROIs (green circles: epilepsy patients; blue circles: healthy subjects) and contralateral ROIs (red triangles: epilepsy patients; magenta triangles: healthy subjects).

ratio of 0.48 T 0.17 (with q of 0.80 indicating a very good fit (Press et al., 1992)).

Discussion BOLD and CBF. These included right parietal and right cuneus regions in subject 1; and bilateral frontal, left occipital, bilateral precentral, left precuneus and right cuneus regions in subject 7. The two BOLD/CBF ROI pairs in subject 1 and 13 BOLD/CBF ROI pairs in subject 7 met the above criteria. Sample t value maps from subject 1 are shown in Fig. 7. As described in Methods, BOLD and CBF data were averaged across the ROIs of each subject prior to the calculation of CMRO2 changes. The optimal linear fit between the resulting CMRO2 estimates and CBF data in the ROIs of these two subjects is displayed in Fig. 8. The slope of the straight line fit to these data yielded a CMRO2/CBF coupling

Fig. 4. The oxygen consumption changes corresponding to each subject’s perfusion changes induced by the motor task in the ipsilateral ROIs (green circles) and contralateral ROIs (red triangles). The optimal straight line fit (q = 0.92) to these data is shown superimposed, yielding a coupling ratio of 0.46 T 0.05. The shaded region represents the standard error in the linear fit.

The present experiments provide, for the first time, a complete set of BOLD, CBF and CMRO2 measurements following functional activation, deactivation and IEDs in epilepsy patients. They demonstrate a preserved coupling between perfusion and oxygen consumption changes in epilepsy patients. As was the case for the healthy volunteers, the CMRO2/CBF relationship was consistent between regions of positive and negative BOLD responses to a motor task (with DCMRO2/DCBF of 0.46 T 0.05). For the regions that showed statistically significant IED-induced changes in both BOLD and CBF (thus allowing for CMRO2 estimation), a similar CMRO2/CBF coupling ratio, of 0.48 T 0.17, was estimated. Overall, these findings are consistent with the general notion of epilepsy as

Fig. 6. The average, motor task induced, percent changes in CBF signal in ipsi- and contralateral ROIs of healthy subjects (C) and epileptic patients (E).

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

211

Fig. 7. Sample BOLD (left) and CBF (right) t value maps in a subject (Subject Id. 1), overlaid on the corresponding anatomical slices. The regions of positive responses are shown in the top row; the regions of negative responses, in the bottom row. The centers of mass for the overlapping regions are shown with a cross hair.

Fig. 8. The oxygen consumption changes corresponding to across ROI average IED-induced perfusion and BOLD changes in subjects 1 and 7. The averages for ROIs showing IED-induced signal decreases are shown as green circles; the averages for ROIs showing IED-induced signal increases, as red triangles. The optimal straight line fit (q = 0.80) to these data is shown superimposed, yielding a coupling ratio of 0.48 T 0.17. The shaded region represents the standard error in the linear fit.

a disorder of neuronal excitability, involving neuronal disinhibition and hyperexcitability. While neuronal hyperexcitability is thought to characterize most epilepsy syndromes, the pathophysiology of these diseases is still incompletely understood. The role of genetics in idiopathic generalized epilepsy has long been suspected (Metrakos and Metrakos, 1961) and a number of different IGE subsyndromes have recently been associated with distinct mutations in GABAA receptor sub-units (Macdonald et al., 2004; Gutierrez-Delicado and Serratosa, 2004). Although IGE patients have normal structural MRI, regional decreases in their N-acetyl aspartate levels have been reported (Savic et al., 2004), suggesting a heterogeneous, diffuse neuronal abnormality. The average resting metabolism and flow in IGE patients are largely unremarkable (Duncan, 1997; Theodore et al., 1985; Ochs et al., 1987; Kapucu et al., 2003; Devous et al., 1990), in sharp contrast to the hypometabolism and hypoperfusion frequently observed in the area of the epileptogenic focus, its immediate surround or elsewhere in the brain of patients with localization-related epilepsies (Kuhl et al., 1980; Engel et al., 1982; Lee et al., 1986; Franck et al., 1986; Kim et al., 2001). While initial seizures in serial seizure animal models were accompanied by the expected increases in cerebral blood volume, arterial blood pressure, cortical oxygen tension and cytochrome oxidase pressure, one or more of these variables failed to rise in response to

212

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

subsequent seizures, testifying to a gradual breakdown of neurovascular coupling in these patients (Kreisman et al., 1981, 1983). Similarly, in a near-infrared spectroscopy study of pediatric epileptic seizures, an early CBV increase gradually changed to a CBV decrease in the course of the seizure in a patient with tonic status epilepticus (Haginoya et al., 2002). In line with the present findings, these data suggest a preserved interictal neurovascular coupling that is progressively compromised in the course of either sustained or highly repetitive ictal events. Each patient in this study was taking one or more antiepileptic drugs (AEDs), which were reported to reduce baseline CMRGlc and CBF (Theodore et al., 1989; Leiderman et al., 1991; Spanaki et al., 1999; Gaillard et al., 1996). A reason for these reductions may lie in the decreased metabolic requirements following the enhancement of cerebral inhibitory neurotransmission (Theodore, 1988). In view of the effect of valproate on brain and CSF GABA levels (Loscher, 1979, 1981), it is important to note that increased CSF GABA (which is linearly related to brain GABA (Palfreyman et al., 1983; Petroff et al., 1996)), following administration of the GABA agonist muscimol, was found to affect both blood flow and glucose consumption as to maintain a normal relationship between the two (Kelly and McCulloch, 1983). While the medications might have shifted the absolute global flow and metabolism in these subjects, there is no evidence in support of their influence on the relationship between metabolic and hemodynamic responses to changes in neuronal activity. Furthermore, we do not expect any spatial variation of their effects across homologous brain regions— namely, primary motor cortices—of interest for our functional paradigm. While fMRI BOLD studies of physiological brain activation are often done in surgical epileptic candidates to map the eloquent cortex (Deblieck et al., 2003; Diehl et al., 2003; Huettel et al., 2004; Szaflarski et al., 2004), there are no studies making simultaneous measurements of activation-induced BOLD, CBF and CMRO2 changes in epilepsy patients, likely due to the complexity and limited SNR of such measurements. The slope of 0.46 T 0.05 of the best line fit to both contra- and ipsilateral M1 CMRO2 vs. CBF percent signal changes found here is in excellent agreement with the value of 0.44 T 0.04 we reported in an earlier study of healthy volunteers performing the same motor task. It is also in reasonable agreement (given the paradigm differences and the expected intersubject variability) with the ratios reported by our and other groups for the contralateral primary motor cortex activation in studies of BOLD signal increases, with the average of 0.35 T 0.03 found in this lab (Atkinson et al., 2000) and 0.33 T 0.06 reported by Kastrup (Kastrup et al., 2002). The ratio of the changes in perfusion—between the contralateral region of neuronal activation and homologous ipsilateral region of neuronal deactivation—was decreased in the epileptic patients compared to the corresponding value in healthy subjects studied previously. This significant difference in the CBF ratios resulted from a decrease in the activation-induced CBF increases, with a preserved range of deactivation-induced CBF decreases. In view of the diffuse cortical hyperexcitability presumed to exist in these patients and the suggested dominant contribution of presynaptic potentials to the total metabolic demands of neuronal activity (Logothetis et al., 2001), it is tempting to speculate that the relative metabolic cost of neuronal activation with respect to neuronal deactivation may be diminished in these patients when compared to healthy volunteers, though the neuronal excitability (and hence the energetic cost of the activation) may well be

influenced by AEDs (Tassinari et al., 2003). The dissociation of the effects of the underlying pathology from those of the medications is, however, presently unavailable. In contrast to the sustained after-depolarizations and multiple spike discharges characteristic of the ictal state (Matsumoto and Ajmone Marsan, 1964a), IEDs are associated with a paroxysmal depolarization shift of the resting neuronal membrane potential, bursts of action potentials and ensuing hyperpolarization and hence inhibition (Matsumoto and Ajmone Marsan, 1964b). In view of this pronounced difference in the electrophysiological signature of the two states, the CBF and CMRO2 changes induced by interictal discharges are expected to be far less conspicuous than their ictal counterparts (Prevett et al., 1995; Engel et al., 1985; Theodore et al., 1985). Likely due to the limited sensitivity of the methods in combination with the sparcity of the interictal discharges in most patients, there are few reports of metabolic and hemodynamic changes induced by IEDs in epilepsy patients. No effect of the spike and wave activity on the CMRGlc was observed in a PET study of a group of generalized epilepsy patients, though there was a slight trend toward CMRGlc increases in IGE patients (Ochs et al., 1987). In a PET study of a reflex epilepsy patient, a 34.6% increase in CBF and 13% increase in CMRGlc were measured in a region concordant with the site of maximal ictal EEG abnormality, as determined by implanted electrodes (Bittar et al., 1999). In a group of patients with photosensitive epilepsy, a significant blood flow increase was measured in the hypothalamus during a photoparoxysmal response (da Silva et al., 1999). In the caudate nucleus, the CBF increase instigated by the intermittent photic stimulation was abolished during the photoparoxysmal response (da Silva et al., 1999). Both widespread positive and negative BOLD responses to IEDs have been reported in a number of EEG-fMRI studies (SalekHaddadi et al., 2003b; Archer et al., 2003a,b; Bagshaw et al., 2004; Aghakhani et al., 2004). In the present study, we also observed regions of both BOLD and CBF increases and decreases. Since BOLD signal has a complex dependence on a number of physiological parameters (Davis et al., 1998; Hoge et al., 1999), we also estimated the corresponding oxygen consumption changes, to obtain a more direct marker of the underlying metabolic costs. Due to a combination of factors—the limited PASL contrast-tonoise ratio at 1.5 T; few, transient IED events (compared to e.g., numerous repetitions of the block motor paradigm employed when estimating the DCMRO2 following neuronal activation/deactivation); and the stringent requirement for the overlap of BOLD/CBF ROIs (to ensure robust, colocalized BOLD and CBF measurements), the set of data available for quantification of oxygen consumption changes in response to IEDs was severely curtailed. A total of only 15 ROIs (showing statistically significant signal changes)—from 2 patients—were sufficiently overlapped to allow the estimation of the corresponding oxygen consumption. In these 2 case studies, BOLD changes were invariably accompanied by CBF changes of the same sign, with the estimated DCMRO2/DCBF coupling ratio of 0.48 T 0.17, thus very close to the one observed for the functional activation in these patients as well as the one obtained in healthy volunteers (Stefanovic et al., 2004). Nonetheless, the paucity of data available for this estimation, in combination with the large variability of both epileptic syndromes and the nature and dosage of medications customarily prescribed in its treatment preclude any general conclusions about the hemodynamic and metabolic responses to IEDs to be made from the present results.

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

While these data suggest that IED-induced negative BOLD responses may arise from the larger flow relative to oxygen consumption decreases, as observed for motor task-induced negative BOLD responses in healthy volunteers (Stefanovic et al., 2004), other explanations of negative BOLD phenomena are still possible. This is particularly true of epileptogenic zones in focal epilepsies and responses to ictal activity, where neurovascular coupling may well be compromised, as suggested earlier. Nevertheless, it is tempting to apply Gloor’s account of the spike and wave phenomenon (Gloor, 1978), thus hypothesizing that the presently measured negative CBF and BOLD responses result from the net deactivation of the region due to a locally predominant cortical inhibition relative to excitation. This also allows for the existence of regions showing no BOLD response, due to a balance between changes in local excitation and inhibition, integrated over the interval determined by the effective BOLD temporal resolution, as proposed earlier (Archer et al., 2003a). Finally, the metabolic costs of IEDs and hence the ensuing CMRO2 response and, indirectly, BOLD response are likely affected by the relative contributions of changes in synchronicity vs. synaptic activity to the generation of IEDs (Salek-Haddadi et al., 2003b).

Conclusion We observed normal hemodynamic responses to hypercapnic perturbation in a group of epilepsy patients with generalized IEDs. A consistent linear relationship between oxygen consumption and perfusion changes during motor task performance in regions of sustained positive as well as negative BOLD response was found. The slope of the linear fit to CMRO2 vs. CBF changes from both ipsi- and contralateral ROIs was 0.46 T 0.05, in close agreement with the coupling ratio found in an earlier study of healthy volunteers. On the other hand, a decreased ratio of the magnitude of contra- to ipsilateral flow changes was observed in the patient group. Interictal epileptiform discharges produced a similar coupling, with DCMRO2/DCBF of 0.48 T 0.17. The current findings suggest a preserved coupling between metabolic and hemodynamic processes underlying BOLD increases and decreases in epileptic patients, in response to both normal functional activation and IEDs and provide no evidence for a disturbance in the interictal cerebral vascular responses in this disorder.

Acknowledgments This work was supported by the Natural Sciences and Engineering Research Council of Canada and the Canadian Institutes of Health Research.

References Aghakhani, Y., Bagshaw, A.P., Benar, C.G., Hawco, C., Andermann, F., Dubeau, F., Gotman, J., 2004. fMRI activation during spike and wave discharges in idiopathic generalized epilepsy. Brain 127, 1127 – 1144. Alarcon, G., Guy, C.N., Binnie, C.D., Walker, S.R., Elwes, R.D., Polkey, C.E., 1994. Intracerebral propagation of interictal activity in partial epilepsy: implications for source localisation. J. Neurol., Neurosurg. Psychiatry 57 (4), 435 – 449. Al-Asmi, A., Benar, C.G., Gross, D.W., Khani, Y.A., Andermann, F., Pike,

213

G.B., Dubeau, F., Gotman, J., 2003. fMRI activation in continuous and spike-triggered EEG-fMRI studies of epileptic spikes. Epilepsia 44 (10), 1328 – 1339. Archer, J.S., Abbott, D.F., Waites, A.B., Jackson, G.D., 2003a. fMRI ‘‘deactivation’’ of the posterior cingulate during generalized spike and wave. NeuroImage 20 (4), 1915 – 1922. Archer, J.S., Briellman, R.S., Abbott, D.F., Syngeniotis, A., Wellard, R.M., Jackson, G.D., 2003b. Benign epilepsy with centro-temporal spikes: spike triggered fMRI shows somato-sensory cortex activity. Epilepsia 44 (2), 200 – 204. Atkinson, J.D., Hoge, R.D., Gill, B., Sadikot, A.F., Pike, G.B., 2000. BOLD, CBF, and CMRO2 in the human primary motor cortex. Proceedings of the Sixth International Conference on Functional Mapping of the Human Brain, San Antonio, Elsevier, p. S803. Avoli, M., 2001. Do interictal discharges promote or control seizures? Experimental evidence from an in vitro model of epileptiform discharge. Epilepsia 42S3, 2 – 4. Badier, J., Chauvel, P., 1985. Electroencephalographic spiking activity, drug levels, and seizure occurrence in epileptic patients. Ann. Neurol. 17 (6), 597 – 603. Badier, J., Chauvel, P., 1995. Spatio-temporal characteristics of paroxysmal interictal events in human temporal lobe epilepsy. J. Physiol. (Paris) 89 (4 – 6), 255 – 264. Bagshaw, A.P., Aghakhani, Y., Benar, C.G., Kobayashi, E., Hawco, C., Dubeau, F., Pike, G.B., Gotman, J., 2004. EEG-fMRI of focal epileptic spikes: analysis with multiple haemodynamic functions and comparison with Gadolinium-enhanced MR angiograms. Hum. Brain Mapp. 22 (3), 179 – 192. Bagshaw, A.P., Hawco, C., Benar, C.G., Kobayashi, E., Aghakhani, Y., Dubeau, F., Pike, G.B., Gotman, J., 2005. Analysis of the EEG-fMRI response to prolonged bursts of interictal epileptiform activity. NeuroImage 24 (4), 1099 – 1112. Benar, C.G., Gross, D.W., Wang, Y., Petre, V., Pike, G.B., Dubeau, F., Gotman, J., 2002. The BOLD response to interictal epileptiform discharges. NeuroImage 17 (3), 1182 – 1192. Bittar, R.G., Andermann, F., Olivier, A., Dubeau, F., Dumoulin, S.O., Pike, G.B., Reutens, D.C., 1999. Interictal spikes increase cerebral glucose metabolism and blood flow: a PET study. Epilepsia 40 (2), 170 – 178. Boroojerdi, B., Diefenbach, K., Ferbert, A., 1996. Transcallosal inhibition in cortical and subcortical cerebral vascular lesions. J. Neurol. Sci. 144, 160 – 170. Boxerman, J.L., Bandettini, P.A., Kwong, K.K., Baker, J.R., Davis, T.L., Rosen, B.R., Weisskoff, R.M., 1995. The intravascular contribution to fMRI signal change: Monte Carlo modeling and diffusion-weighted studies in vivo. Magn. Reson. Med. 34 (1), 4 – 10 Jul.). Breier, J.I., Mullani, N.A., Thomas, A.B., Wheless, J.W., Plenger, P.M., Gould, K.L., Papanicolaou, A., Willmore, L.J., 1997. Effects of duration of epilepsy on the uncoupling of metabolism and blood flow in complex partial seizures. Neurology 48 (4), 1047 – 1053. Bruehl, C., Hagemann, G., Witte, O.W., 1998. Uncoupling of blood flow and metabolism in focal epilepsy. Epilepsia 39 (12), 1235 – 1242. Buckner, R.L., 1998. Event-related fMRI and the hemodynamic response. Hum. Brain Mapp. 6 (5 – 6), 373 – 377. Collins, D.L., Neelin, P., Peters, T.M., Evans, A.C., 1994. Automatic 3 D intersubject registration of MR volumetric data in standardized Talairach space. J. Comput. Assist. Tomogr. 18 (2), 192 – 205. Cox, R.J., 1996. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29, 162 – 173. da Silva, E.A., Muller, R.A., Chugani, D.C., Shah, J., Shah, A., Watson, C., Chugani, H.T., 1999. Brain activation during intermittent photic stimulation: a [15O]-water PET study on photosensitive epilepsy. Epilepsia 40 (S4), 17 – 22. Davis, T., Kwong, K., Weisskoff, R., Rosen, B., 1998. Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proc. Natl. Acad. Sci. U. S. A. 95, 1834 – 1839. de Curtis, M., Avanzini, G., 2001. Interictal spikes in focal epileptogenesis. Prog. Neurobiol. 63 (5), 541 – 567.

214

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215

de Curtis, M., Manfridi, A., Biella, G., 1998. Activity-dependent pH shifts and periodic recurrence of spontaneous interictal spikes in a model of focal epileptogenesis. J. Neurosci. 18 (18), 7543 – 7551. Deblieck, C., Pesenti, G., Scifo, P., Fazio, F., Bricolo, E., Russo, G.L., Scialfa, G., Cossu, M., Bottini, G., Paulesu, E., 2003. Preserved functional competence of perilesional areas in drug-resistant epilepsy with lesion in supplementary motor cortex: fMRI and neuropsychological observations. NeuroImage 20 (4), 2225 – 2234. Devous, M.D., Leroy, R.F., Homan, R.W., 1990. Single photon emission computed tomography in epilepsy. Semin. Nucl. Med. 20 (4), 325 – 341. Diehl, B., Salek-Haddadi, A., Fish, D.R., Lemieux, L., 2003. Mapping of spikes, slow waves, and motor tasks in a patient with malformation of cortical development using simultaneous EEG and fMRI. Magn. Reson. Imaging 21 (10), 1167 – 1173. Duncan, J.S., 1997. Imaging and epilepsy. Brain 120 (Pt. 2), 339 – 377 Feb.). Engel, J., Kuhl, D.E., Phelps, M.E., Mazziotta, J.C., 1982. Interictal cerebral glucose metabolism in partial epilepsy and its relation to EEG changes. Ann. Neurol. 12 (6), 510 – 517. Engel, J., Lubens, P., Kuhl, D.E., Phelps, M.E., 1985. Local cerebral metabolic rate for glucose during petit mal absences. Ann. Neurol. 17 (2), 121 – 128. Evans, A.C., Collins, D.L., Mills, S.R., Brown, E.D., Kelly, R.L., Peters, T.M., 1993. 3D statistical neuroanatomical models from 305 MRI volumes. Proceedings of IEEE-Nuclear Science Symposium and Medical Imaging Conference, pp. 1813 – 1817. Ferbert, A., Rothwell, J.C., Day, B.L., Colebatch, J.G., Marsden, C.D., 1992. Interhemispheric inhibition of the human motor cortex. J. Physiol. 453 (1), 525 – 546. Fink, G.R., Pawlik, G., Stefan, H., Pietrzyk, U., Wienhard, K., Heiss, W.D., 1996. Temporal lobe epilepsy: evidence for interictal uncoupling of blood flow and glucose metabolism in temporomesial structures. J. Neurol. Sci. 137 (1), 28 – 34. Franck, G., Sadzot, B., Salmon, E., Depresseux, J.C., Grisar, T., Peters, J.M., Guillaume, M., Quaglia, L., Delfiore, G., Lamotte, D., 1986. Regional cerebral blood flow and metabolic rates in human focal epilepsy and status epilepticus. Adv. Neurol. 44, 935 – 948. Franck, G., Salmon, E., Sadzot, B., Maquet, P., 1989. Epilepsy: the use of oxygen-15-labeled gases. Semin. Neurol. 9 (4), 307 – 316. Gaillard, W.D., Fazilat, S., White, S., Malow, B., Sato, S., Reeves, P., Herscovitch, P., Theodore, W.H., 1995. Interictal metabolism and blood flow are uncoupled in temporal lobe cortex of patients with complex partial epilepsy. Neurology 45 (10), 1841 – 1847. Gaillard, W.D., Zeffiro, T., Fazilat, S., DeCarli, C., Theodore, W.H., 1996. Effect of valproate on cerebral metabolism and blood flow: an 18F-2deoxyglucose and 15O water positron emission tomography study. Epilepsia 37 (6), 515 – 521. Gerloff, C., Cohen, L.G., Floeter, M.K., Chen, R., Corwell, B., Hallett, M., 1998. Inhibitory influence of the ipsilateral motor cortex on responses to stimulation of the human cortex and pyramidal tract. J. Physiol. 510 (1), 249 – 259. Gloor, P., 1978. Generalized epilepsy with bilateral synchronous spike and wave discharge. New findings concerning its physiological mechanisms. Electroencephalogr. Clin. Neurophysiol., Suppl. 34, 245 – 249. Grisar, T., Lakaye, B., Thomas, E., Bettendorf, L., Minet, A., 1999. The molecular neuron – glia couple and epileptogenesis. Adv. Neurol. 79, 591 – 602. Grubb, R., Phelps, M., Eichling, J., 1974. The effects of vascular changes in PaCO 2 on cerebral blood volume, blood flow and vascular mean transit time. Stroke 5, 630 – 639. Gutierrez-Delicado, E., Serratosa, J.M., 2004. Genetics of the epilepsies. Curr. Opin. Neurol. 17 (2), 147 – 153 Apr.). Haginoya, K., Munakata, M., Kato, R., Yokoyama, H., Ishizuka, M., Iinuma, K., 2002. Ictal cerebral haemodynamics of childhood epilepsy measured with near-infrared spectrophotometry. Brain 125, 1960 – 1971. Hamzei, F., Dettmers, C., Rzanny, R., Liepert, J., Buechel, C., Weiller, C., 2002. Reduction of excitability (‘‘inhibition’’) in the ipsilateral primary

motor cortex is mirrored by fMRI signal decreases. NeuroImage 17, 490 – 496. Hoge, R.D., Atkinson, J., Gill, B., Crelier, G., Marrett, S., Pike, G., 1999. Investigation of BOLD signal dependence on CBF and CMRO2: the deoxyhemoglobin dilution model. Magn. Reson. Med. 42 (5), 849 – 863. Huang-Hellinger, F.R., Breiter, H.C., McCormack, G., Cohen, M.S., Kwong, K.K., Sutton, J.P., Savoy, R.L., Weiskoff, R.M., Davis, T.L., Baker, J.R., Belliveau, J.W., Rosen, B.R., 1995. Simultaneous functional magnetic resonance imaging and electrophysiological recording. Hum. Brain Mapp. 3, 13 – 23. Huettel, S.A., McKeown, M.J., Song, A.W., Hart, S., Spencer, D.D., Allison, T., McCarthy, G., 2004. Linking hemodynamic and electrophysiological measures of brain activity: evidence from functional MRI and intracranial field potentials. Cereb. Cortex 14 (2), 165 – 173. Ives, J.R., Warach, S., Schmitt, F., Edelman, R.R., Schomer, D.L., 1993. Monitoring the patient’s EEG during echo planar MRI. Electroencephalogr. Clin. Neurophysiol. 87 (6), 417 – 420. Jager, L., Werhahn, K.J., Hoffmann, A., Berthold, S., Scholz, V., Weber, J., Noachtar, S., Reiser, M., 2002. Focal epileptiform activity in the brain: detection with spike-related functional MR imaging—Preliminary results. Radiology 223 (3), 860 – 869. Janszky, J., Fogarasi, A., Jokeit, H., Schulz, R., Hoppe, M., Ebner, A., 2001. Spatiotemporal relationship between seizure activity and interictal spikes in temporal lobe epilepsy. Epilepsy Res. 47 (3), 179 – 188. Jensen, M.S., Yaari, Y., 1997. Role of intrinsic burst firing, potassium accumulation, and electrical coupling in the elevated potassium model of hippocampal epilepsy. J. Neurophysiol. 77 (3), 1224 – 1233. Josephs, O., Turner, R., Friston, K., 1997. Event-related fMRI. Hum. Brain Mapp. 5, 1 – 7. Kang, J.K., Benar, C.G., Al-Asmi, A., Khani, Y.A., Pike, G.B., Dubeau, F., Gotman, J., 2003. Using patient-specific hemodynamic response functions in combined EEG-fMRI studies in epilepsy. NeuroImage 20 (2), 1162 – 1170. Kanner, A.M., Kaydanova, Y., de Toledo-Morrell, L., Morrell, F., Smith, M.C., Bergen, D., Pierre-Louis, S.J., Ristanovic, R., 1995. Tailored anterior temporal lobectomy. Relation between extent of resection of mesial structures and postsurgical seizure outcome. Arch. Neurol. 52 (2), 173 – 178. Kapucu, L.O., Serdaroglu, A., Okuyaz, C., Kose, G., Gucuyener, K., 2003. Brain single photon emission computed tomographic evaluation of patients with childhood absence epilepsy. J. Child. Neurol. 18 (8), 542 – 548. Kastrup, A., Krueger, G., Neumann-Haefelin, T., Glover, G., Moseley, M.E., 2002. Changes of cerebral blood flow, oxygenation and oxidative metabolism during graded motor activation. NeuroImage 15, 74 – 82. Kelly, P.A., McCulloch, J., 1983. The effects of the GABAergic agonist muscimol upon the relationship between local cerebral blood flow and glucose utilization. Brain Res. 258 (2), 338 – 342. Kim, S.-K., Lee, D.S., Lee, S.K., Kim, Y.K., Kang, K.W., Chung, C.K., Chung, J.-K., Myung, C.L., 2001. Diagnostic performance of [18F]FDG-PET and ictal [99mTc]-HMPAO SPECT in occipital lobe epilepsy. Epilepsia 42 (12), 1531 – 1540. Krakow, K., Woermann, F.G., Symms, M.R., Allen, P.J., Lemieux, L., Barker, G.J., Duncan, J.S., Fish, D.R., 1999. EEG-triggered functional MRI of interictal epileptiform activity in patients with partial seizures. Brain 122, 1679 – 1688. Kreisman, N.R., LaManna, J.C., Rosenthal, M., Sick, T.J., 1981. Oxidative metabolic responses with recurrent seizures in rat cerebral cortex: role of systemic factors. Brain Res. 218 (1 – 2), 175 – 188. Kreisman, N.R., Rosenthal, M., Sick, T.J., LaManna, J.C., 1983. Oxidative metabolic responses during recurrent seizures are independent of convulsant, anesthetic, or species. Neurology 33 (7), 861 – 867. Kuhl, D.E., Engel, J., Phelps, M.E., Selin, C., 1980. Epileptic patterns of local cerebral metabolism and perfusion in humans determined by emission computed tomography of 18 FDG and 13N-H3. Ann. Neurol. 8 (4), 348 – 360.

B. Stefanovic et al. / NeuroImage 28 (2005) 205 – 215 Lazeyras, F., Blanke, O., Perrig, S., Zimine, I., Golay, X., Delavelle, J., Michel, C.M., de Tribolet, N., Villemure, J.G., Seeck, M., 2000. EEGtriggered functional MRI in patients with pharmacoresistant epilepsy. J. Magn. Reson. Imaging 12 (1), 177 – 185. Lee, B.I., Markand, O.N., Siddiqui, A.R., Park, H.M., Mock, B., Wellman, H.H., Worth, R.M., Edwards, M.K., 1986. Single photon emission computed tomography (SPECT) brain imaging using N,N,NV-trimethylNV-(2 hydroxy-3-methyl-5-123I-iodobenzyl)-1,3-propanediamine 2 HCl (HIPDM): intractable complex partial seizures. Neurology 36 (11), 1471 – 1477. Leiderman, D.B., Balish, M., Bromfield, E.B., Theodore, W.H., 1991. Effect of valproate on human cerebral glucose metabolism. Epilepsia 32 (3), 417 – 422. Lemieux, L., Salek-Haddadi, A., Josephs, O., Allen, P., Toms, N., Scott, C., Krakow, K., Turner, R., Fish, D.R., 2001. Event-related fMRI with simultaneous and continuous EEG: description of the method and initial case report. NeuroImage 14 (3), 780 – 787. Liepert, J., Dettmers, C., Terborg, C., Weiller, C., 2001. Inhibition of ipsilateral motor cortex during phasic generation of low force. Clin. Neurophysiol. 112, 114 – 121. Logothetis, N., Pauls, J., Augath, M., Trinath, T., Oeltermann, A., 2001. Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150 – 157. Loscher, W., 1979. GABA in plasma and cerebrospinal fluid of different species. Effects of gamma-acetylenic GABA, gamma-vinyl GABA and sodium valproate. J. Neurochem. 32 (5), 1587 – 1591. Loscher, W., 1981. Valproate induced changes in GABA metabolism at the subcellular level. Biochem. Pharmacol. 30 (11), 1364 – 1366. Macdonald, R.L., Gallagher, M.J., Feng, H.J., Kang, J., 2004. GABA(A) receptor epilepsy mutations. Biochem. Pharmacol. 68 (8), 1497 – 1506. Matsumoto, H., Ajmone Marsan, C., 1964a. Cortical cellular phenomena in experimental epilepsy: ictal manifestations. Exp. Neurol. 25, 305 – 326. Matsumoto, H., Ajmone Marsan, C., 1964b. Cortical cellular phenomena in experimental epilepsy: interictal manifestations. Exp. Neurol. 80, 286 – 304. McKhann, G.M., Schoenfeld-McNeill, J., Born, D.E., Haglund, M.M., Ojemann, G.A., 2000. Intraoperative hippocampal electrocorticography to predict the extent of hippocampal resection in temporal lobe epilepsy surgery. J. Neurosurg. 93 (1), 44 – 52. Metrakos, K., Metrakos, J.D., 1961. Genetics of convulsive disorders: II. Genetic and electroencephalographic studies in centrencephalic epilepsy. Neurology 11, 474 – 483. Netz, J., Ziemann, U., Hoemberg, V., 1995. Hemispheric asymmetry of transcallosal inhibition in man. Exp. Brain Res. 104, 527 – 533. Ochs, R.F., Gloor, P., Tyler, J.L., Wolfson, T., Worsley, K., Andermann, F., Diksic, M., Meyer, E., Evans, A., 1987. Effect of generalized spike-andwave discharge on glucose metabolism measured by positron emission tomography. Ann. Neurol. 21 (5), 458 – 464. Palfreyman, M.G., Huot, S., Grove, J., 1983. Total GABA and homocarnosine in CSF as indices of brain GABA concentrations. Neurosci. Lett. 35 (2), 161 – 166. Patel, M.R., Blum, A., Pearlman, J.D., Yousuf, N., Ives, J.R., Saeteng, S., Schomer, D.L., Edelman, R.R., 1999. Echo-planar functional MR imaging of epilepsy with concurrent EEG monitoring. Am. J. Neuroradiol. 20 (10), 1916 – 1919. Penfield, W., Jasper, H., 1954. Epilepsy and the Functional Anatomy of the Human Brain. Little, Brown and Company, Boston, MA. Petroff, O.A., Rothman, D.L., Behar, K.L., Collins, T.L., Mattson, R.H.,

215

1996. Human brain GABA levels rise rapidly after initiation of vigabatrin therapy. Neurology 47 (6), 1567 – 1571. Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P., 1992. Numerical Recipes in C: The Art of Scientific Computing, 2nd edition. Cambridge University Press, New York, pp. 666 – 670 (Chapt. 15). Prevett, M.C., Duncan, J.S., Jones, T., Fish, D.R., Brooks, D.J., 1995. Demonstration of thalamic activation during typical absence seizures using H2(15)O and PET. Neurology 45 (7), 1396 – 1402. Rosenow, F., Luders, H., 2001. Presurgical evaluation of epilepsy. Epilepsia 42 (12), 1515 – 1522. Salek-Haddadi, A., Friston, K.J., Lemieux, L., Fish, D.R., 2003a. Studying spontaneous EEG activity with fMRI. Brain Res. Rev. 43 (1), 110 – 133. Salek-Haddadi, A., Lemieux, L., Merschhemke, M., Friston, K.J., Duncan, J.S., Fish, D.R., 2003b. Functional magnetic resonance imaging of human absence seizures. Ann. Neurol. 53 (5), 663 – 667. Savic, I., Osterman, Y., Helms, G., 2004. MRS shows syndrome differentiated metabolite changes in human-generalized epilepsies. NeuroImage 21 (1), 163 – 172. Seeck, M., Lazeyras, F., Michel, C.M., Blanke, O., Gericke, C.A., Ives, J., Delavelle, J., Golay, X., Haenggeli, C.A., de Tribolet, N., Landis, T., 1998. Non-invasive epileptic focus localization using EEG-triggered functional MRI and electromagnetic tomography. Electroencephalogr. Clin. Neurophysiol. 106, 508 – 512. Spanaki, M.V., Siegel, H., Kopylev, L., Fazilat, S., Dean, A., Liow, K., BenMenachem, E., Gaillard, W.D., Theodore, W.H., 1999. The effect of vigabatrin (gamma-vinyl GABA) on cerebral blood flow and metabolism. Neurology 53 (7), 1518 – 1522. Sperling, M.R., Skolnick, B.E., 1995. Cerebral blood flow during spikewave discharges. Epilepsia 36 (2), 156 – 163. Stefanovic, B., Warnking, J.M., Pike, G.B., 2004. Hemodynamic and metabolic responses to neuronal inhibition. NeuroImage 22 (2), 771 – 778. Szaflarski, J.P., Holland, S.K., Schmithorst, V.J., Dunn, R.S., Privitera, M.D., 2004. High-resolution functional MRI at 3 T in healthy and epilepsy subjects: hippocampal activation with picture encoding task. Epilepsy Behav. 5 (2), 244 – 252. Tassinari, C.A., Cincotta, M., Zaccara, G., Michelucci, R., 2003. Transcranial magnetic stimulation and epilepsy. Clin. Neurophysiol. 114 (5), 777 – 798. Theodore, W.H., 1988. Antiepileptic drugs and cerebral glucose metabolism. Epilepsia 29S2, S48 – S55. Theodore, W.H., Brooks, R., Margolin, R., Patronas, N., Sato, S., Porter, R.J., Mansi, L., Bairamian, D., DiChiro, G., 1985. Positron emission tomography in generalized seizures. Neurology 35 (5), 684 – 690. Theodore, W.H., Bromfield, E., Onorati, L., 1989. The effect of carbamazepine on cerebral glucose metabolism. Ann. Neurol. 25 (5), 516 – 520. Warach, S., Ives, J.R., Schlaug, G., Patel, M.R., Darby, D.G., Thangaraj, V., Edelman, R.R., Schomer, D.L., 1996. EEG-triggered echo-planar functional MRI in epilepsy. Neurology 47 (1), 89 – 93. Warnking, J.M., Pike, G.B., 2004. Bandwidth-modulated adiabatic RF pulses for uniform selective saturation and inversion. Magn. Reson. Med. 52 (5), 1190 – 1199. Wong, E., Buxton, R., Frank, L., 1997. Implementation of quantitative perfusion imaging techniques for functional brain mapping using pulsed arterial spin labeling. NMR Biomed. 10, 237 – 249. Worsley, K., Liao, C., Aston, J., Petre, V., Duncan, G., Morales, F., Evans, A., 2002. A general statistical analysis for fMRI data. NeuroImage 15, 1 – 15.