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Electrocorticographic high gamma activity versus electrical cortical stimulation mapping of naming

Alon Sinai, Christopher W. Bowers, Ciprian M. Crainiceanu, Dana Boatman, Barry Gordon, Ronald P. Lesser, Frederick A. Lenz, Nathan E. Crone
DOI: http://dx.doi.org/10.1093/brain/awh491 1556-1570 First published online: 7 April 2005

Summary

Subdural electrocorticographic (ECoG) recordings in patients undergoing epilepsy surgery have shown that functional activation is associated with event-related broadband gamma activity in a higher frequency range (>70 Hz) than previously studied in human scalp EEG. To investigate the utility of this high gamma activity (HGA) for mapping language cortex, we compared its neuroanatomical distribution with functional maps derived from electrical cortical stimulation (ECS), which remains the gold standard for predicting functional impairment after surgery for epilepsy, tumours or vascular malformations. Thirteen patients had undergone subdural electrode implantation for the surgical management of intractable epilepsy. Subdural ECoG signals were recorded while each patient verbally named sequentially presented line drawings of objects, and estimates of event-related HGA (80–100 Hz) were made at each recording site. Routine clinical ECS mapping used a subset of the same naming stimuli at each cortical site. If ECS disrupted mouth-related motor function, i.e. if it affected the mouth, lips or tongue, naming could not be tested with ECS at the same cortical site. Because naming during ECoG involved these muscles of articulation, the sensitivity and specificity of ECoG HGA were estimated relative to both ECS-induced impairments of naming and ECS disruption of mouth-related motor function. When these estimates were made separately for 12 electrode sites per patient (the average number with significant HGA), the specificity of ECoG HGA with respect to ECS was 78% for naming and 81% for mouth-related motor function, and equivalent sensitivities were 38% and 46%, respectively. When ECS maps of naming and mouth-related motor function were combined, the specificity and sensitivity of ECoG HGA with respect to ECS were 84% and 43%, respectively. This study indicates that event-related ECoG HGA during confrontation naming predicts ECS interference with naming and mouth-related motor function with good specificity but relatively low sensitivity. Its favourable specificity suggests that ECoG HGA can be used to construct a preliminary functional map that may help identify cortical sites of lower priority for ECS mapping. Passive recordings of ECoG gamma activity may be done simultaneously at all electrode sites without the risk of after-discharges associated with ECS mapping, which must be done sequentially at pairs of electrodes. We discuss the relative merits of these two functional mapping techniques.

  • electrical cortical stimulation
  • electrocorticography
  • functional mapping
  • gamma band
  • language
  • ECoG = electrocorticography
  • ECS = electrical cortical stimulation
  • fMRI = functional MRI
  • HGA = high gamma activity
  • MEG = magnetoencephalography

Introduction

When assessing the risk of neurological impairment following surgery for intractable epilepsy, cerebral neoplasms or vascular malformations, interindividual variability in the details of functional anatomy, particularly with respect to language (Ojemann et al., 1989, 2003; Branco et al., 2003; Miglioretti and Boatman, 2003) often make it necessary to map cortical function in each patient. Despite continuing advances in functional neuroimaging, electrical cortical stimulation (ECS) mapping is still the only method in widespread clinical use for reversibly inducing a functional lesion. Its utility for mapping essential language cortex has been demonstrated in a large number of patients (Ojemann et al., 1989) and it is widely considered the gold standard for predicting postoperative functional impairment. ECS mapping can be done intraoperatively or extraoperatively through surgically implanted subdural electrodes. Implanted electrodes also allow ictal recordings of the epileptogenic zone in patients with intractable epilepsy and provide more time for language mapping with a comprehensive battery of tests (Lesser et al., 1987, 1994).

When subdural electrodes are implanted for the surgical management of intractable epilepsy, continuous electrocorticography (ECoG) is performed through them to detect the area of seizure onset. These passive recordings may also detect cortical activity associated with functional brain activation and could therefore be used to map cortical function. ECoG functional mapping, whether intra- or extraoperative, would have several potential advantages over ECS mapping. While ECS mapping must be done at one cortical site at a time, ECoG mapping could be done at all cortical sites at once, reducing the time needed for mapping and allowing more widespread and comprehensive mapping of cortical function. In addition, ECoG mapping would carry no risk of the after-discharges that are often associated with ECS mapping and that occasionally lead to seizures (Lesser et al., 1984; Blume et al., 2004), sometimes preventing further mapping of at-risk cortical sites. However, the success of ECoG mapping would depend on the ability of electrophysiological indices of cortical activation to identify cortical tissue that is necessary for normal function.

EEG activity in the gamma band (>30 Hz) has been a particularly promising index of cortical activation for both theoretical and empirical reasons. Its theoretical significance stems from animal studies that have implicated gamma oscillations in the dynamic representation of information in distributed cortical neuronal networks (Singer and Gray, 1995; Gray, 1999; Engel and Singer, 2001). Event-related gamma activity has also been observed in human scalp EEG during auditory (Pantev, 1995), visual (Tallon-Baudry and Bertrand, 1999) and motor (Pfurtscheller et al., 1993) tasks. Most of these responses have been observed in relatively low gamma frequencies near 40 Hz. However, subdural ECoG recordings in patients with epilepsy have also revealed activity in a higher gamma frequency range beginning at ∼70–80 Hz (Crone et al., 1998b) and including a broad range of higher frequencies that may extend up to ∼150 Hz (Crone et al., 2001b; Ray et al., 2003). This broadband ‘high gamma’ activity (HGA) has been observed during a variety of functional activation tasks, including self-paced and visually cued limb movements (Crone et al., 1998b; Ohara et al., 2000; Pfurtscheller et al., 2003; Leuthardt et al., 2004), auditory discrimination (Crone et al., 2001b) and word production tasks (Crone et al., 2001a).

ECoG studies have also shown that, compared with event-related activity in other frequency bands, event-related HGA typically occurs in spatial and temporal patterns that are more consistent with functional anatomy and the results of ECS (Crone et al., 1998a, b, 2001b; Crone and Hao, 2002a; Pfurtscheller et al., 2003). For example, whereas alpha desynchronization is observed in a broad distribution over bilateral sensorimotor cortex during unilateral limb movements, HGA occurs in a more discrete distribution over the limb's contralateral motor representation (Pfurtscheller et al., 2003), and HGA has a temporal profile that more closely corresponds with the timing of stimuli and responses (Crone et al., 1998b, 2001a, b). In ECoG recordings of auditory association cortex in dominant superior temporal gyrus, HGA was greater and more widespread during speech discrimination than during tone discrimination, whereas auditory evoked responses were not appreciably different, suggesting that HGA provided a better index of the cortical processing demands of the tasks (Crone et al., 2001b). In addition, although ECoG power in high gamma frequencies was consistently augmented during cortical activation, the power in lower gamma frequencies around the traditional 40 Hz band was sometimes increased and at other times decreased, varying not only across patients, but also across recording sites within patients.

Because of its spatial, temporal and functional response characteristics, HGA appears to be a promising index of task-related cortical activation with potential applications in functional mapping, particularly in patients undergoing surgery for intractable epilepsy. However, like the BOLD response of functional MRI (fMRI), ECoG gamma activity is a measure of cortical activation and could theoretically overestimate cortical tissue that is necessary for function. It is therefore important to compare HGA with ECS, and ultimately with the results of surgical resection. Similar comparisons have been made between fMRI and ECS maps of language cortex in comparably sized groups of patients (FitzGerald et al., 1997; Pouratian et al., 2002; Rutten et al., 2002; Roux et al., 2003). In this paper we compared maps of language according to event-related ECoG HGA with those according to ECS.

Since naming is the task most often used for mapping language with both intraoperative and extraoperative ECS, we studied ECoG HGA during naming and compared its spatial distribution with ECS maps of naming. In addition, because naming is routinely performed aloud during ECS mapping to measure the effect of stimulation, and therefore involves muscles of articulation, we compared ECoG gamma maps of naming with ECS maps of mouth-related motor function.

Methods

Patients and clinical setting

Thirteen patients (see Table 1) were enrolled after surgical implantation of subdural electrode grids. Two patient had arteriovenous malformations, and 12 patients had intractable epilepsy. Patients were recruited for this study if subdural electrode arrays were surgically implanted for clinical purposes over the language-dominant hemisphere (left in all patients). Patients with full-scale IQ below 80 or significant preoperative impairment of naming function were excluded. The electrode grids were implanted for better localization of the seizure focus and/or for functional mapping of language and motor cortex to prevent postoperative neurological impairments. Patients were admitted to the Johns Hopkins Epilepsy Monitoring Unit one day following electrode implantation and remained under continuous video and EEG surveillance for 6–14 days before a second surgery to remove the electrodes and perform a resection of the seizure focus, if possible. The protocol used for this study was approved by the Johns Hopkins Hospital Institutional Review Board in compliance with the Declaration of Helsinki. Patients volunteered to participate and gave consent for research ECoG recordings in accordance with this protocol.

View this table:
Table 1

Patient characteristics

Patient no.Age (years)HandednessGenderAge at seizure onsetHemispheric dominance for language (IAP)Full scale IQ
126RightMale9 monthsLeft92
247RightFemale39 yearsLeft116
316RightFemale3 yearsLeft91
447RightMale8 yearsLeft*
535RightFemale6 monthsBilateral106
618RightMale1 year109
730RightMale15 yearsLeft110
832RightMale16 yearsLeft97
946RightMale39 yearsLeft113
1020LeftFemale15 yearsLeft114
1138RightFemaleNA§87
1245RightMaleNeonatalLeft81
1340RightMale35 yearsLeft114
  • * IQ was not tested; patient completed 12 years of education and owned his business.

  • IAP test was not administered.

  • Patient had an arteriovenous malformation with no history of seizures.

  • § IAP was not administered; ECS results indicated left hemisphere dominance. IAP = intracarotid amobarbital procedure.

Subdural electrode placement and localization

The subdural electrode arrays consisted of 1.5-mm-thick, soft Silastic sheets embedded with platinum-iridium electrodes (4-mm diameter, 2.3-mm diameter exposed surface) that were equally spaced with 1 cm centre-to-centre distances (Adtech, Racine, WI, USA). The location of these electrodes with respect to underlying cortical gyral anatomy was determined by coregistration of pre-implantation volumetric brain MRI (1- to 1.8-mm coronal slice thickness) with post-implantation volumetric brain CT (1-mm axial slice thickness) according to anatomic fiducials (Curry, Compumedics Neuroscan, El Paso, TX, USA). Electrode positions derived from post-implantation CT were then displayed with a brain surface rendering derived from the pre-implantation MRI.

Electrical cortical stimulation

All patients underwent functional ECS mapping of motor and language cortex according to routine clinical procedures (Lesser et al., 1987). ECS testing was done in 2-h blocks, twice a day, for 2–4 days. ECS mapping utilized constant current electrical stimulation between pairs of adjacent electrodes using a Grass S-88 or S-12 cortical stimulator (Grass-Telefactor/Astro-Med, Inc., West Warwick, RI, USA) with 1- to 5-s trains of 50 Hz, 0.3 ms, alternating polarity square-wave pulses, starting with a stimulus intensity of 1 mA and increasing in 0.5- to 1.0-mA increments up to a maximum of 15 mA. Stimulus intensity at each electrode pair was individualized according to the highest amperage below 15 mA that did not produce after-discharges (Lesser et al., 1984). While stimulus intensity was adjusted, each patient reported any unusual or involuntary sensations or movements, and once a maximum stimulus intensity was reached, disruption of motor function was detected by observing the patient during voluntary movements in turn of the tongue, bilateral fingers and bilateral toes.

If ECS interfered with voluntary movement or produced involuntary movement or unpleasant sensations in one or more body parts, ECS mapping of language function was usually not performed for that electrode pair. At some electrode pairs these sensory or motor effects were not sufficiently uncomfortable or distracting to interfere with ECS mapping of language, but this was the exception rather than the rule. ECS interference with speech-related motor function, i.e. involving mouth, lips or tongue, was usually too distracting to proceed with ECS testing of language function. Even if ECS was tolerable to the patient, ECS mapping of language at that electrode pair was usually skipped because the cortical region was already considered unresectable due to the risk of motor impairment.

ECS mapping of language was performed with a battery of tasks probing expressive and receptive language function, including picture naming, sentence comprehension (modified Token Test), paragraph reading and spontaneous speech. Picture naming was performed with 84 pictures of objects derived from the Boston Naming Test (Goodglass et al., 1983). Each object was depicted by a black and white line drawing on paper or on a computer monitor. ECS current was begun immediately before stimulus onset and lasted no longer than 5 s. Naming errors could consist of absent or delayed responses, incorrect responses, or paraphasias. ECS-induced functional impairment was confirmed only if there was an error induced by ECS current during at least two stimulus trains and if the errors during ECS stimulation could be clearly differentiated from the patient's baseline performance on the same task without ECS stimulation.

Subdural ECoG recordings

ECoG signals were amplified (5 × 1000) and filtered (1–300 Hz, 6 dB/octave) using Grass amplifiers (Model 12A5; Grass-Telefactor/Astro-Med, Inc.). All ECoG recordings were made with a referential montage using a single subdural reference electrode chosen for its relative inactivity and greatest distance from electrodes recording from the areas of interest. ECoG recordings in two patients were limited to a maximum of 128 channels; otherwise, recordings were limited to a maximum of 64 ECoG channels. All ECoG signals were remontaged to an average reference to obtain reference-independent topographic maps of spectral measures (Crone et al., 1998a). The amplified ECoG signals were digitally recorded (sampling rate = 1 kHz) in parallel with experimental markers of stimulus onset and offset. All ECoG recordings were made after the patients had recovered from surgical implantation of subdural electrodes and only if the patients had not had a seizure in the previous 2 h.

During ECoG recordings, picture naming stimuli were sequentially presented to the patients one at a time on a video monitor. These stimuli consisted of 84 objects (black and white drawings) from which stimuli for ECS mapping were derived. The order of stimulus presentation was randomized for each ECoG recording. Patients were asked to fixate on a black dot on a white background between stimulus presentations, and the onset of each visual stimulus began 400 ms after disappearance of the fixation point, at least 3 s following the patient's response to the previous stimulus. Vocal responses were monitored with a voice trigger. Picture stimuli were replaced with the fixation point once a vocal response was detected. Trials were excluded from analysis if the patient's responses were absent, delayed or incorrect, or if the patient was interrupted or distracted during the stimulus-response trial or in the 1-s timeframe preceding it. Trials that were contaminated with epileptiform activity were also excluded from further analysis.

ECoG signal analysis

ECoG recordings during the picture naming task were analysed for event-related changes in the ECoG power spectrum, focusing particularly on event-related HGA. A detailed description of the ECoG signal analyses used in this study has been published elsewhere (Crone et al., 2001b). In brief, after subtracting the average evoked potential, ECoG signals were filtered in the high gamma (80–100 Hz) band, then squared and averaged across trials. The resulting time series were segmented into a series of 100-ms epochs with 50% overlap, spanning 1 s before and 3 s after stimulus onset. Statistical analyses of ECoG gamma power have also been described in detail elsewhere (Crone et al., 1998a). In brief, estimates of ECoG gamma power were compared between post-stimulus epochs and a pool of pre-stimulus (baseline) epochs. A separate mixed effects regression model was fitted for each channel using the change in power from baseline to each post-stimulus epoch as the dependent variable and post-stimulus epoch latency as the independent variable. The mean values and confidence limits were then back-transformed to give the geometric mean percentage change from baseline and 95% confidence limits. An event-related change in gamma power from baseline was considered statistically significant if the confidence intervals did not include zero for at least four consecutive epochs. In bootstrap simulations using samples of detrended energy estimates this criterion was met in no more than three out of 1000 samples.

Comparison of ECS and ECoG functional maps

All electrode sites at which ECS affected cortical function were counted separately for (i) sites where ECS interfered with picture naming, and (ii) sites where ECS interfered with or produced involuntary movements of the mouth, lips or tongue, i.e. movements involving muscles of articulation. Although ECS was performed at pairs of adjacent electrodes, each electrode site was counted separately in order to compare ECS results with maps of HGA, which were derived from referential ECoG recordings of individual electrodes. Therefore, we reported and discussed all results in terms of individual electrode sites. We referred to electrode sites at which there was statistically significant HGA as HGA(+) and those at which there was not as HGA(−), and we referred to electrode sites at which ECS affected task performance as ECS(+) and those at which it did not as ECS(−). In accordance with routine clinical interpretation of ECS, if an individual electrode was common to two pairs of electrodes where ECS was performed, that electrode was deemed ECS(−) if any of these pairs did not affect task performance. Otherwise, the electrode was ECS(+) for all tasks whose performance was affected by ECS at pairs that included the electrode. This interpretation is based on the understanding that ECS may impair the function of cortex underlying each of the electrodes in a pair, as well as cortex between the electrode pair (Nathan et al., 1993).

All comparisons of HGA and ECS functional maps were based on the assumption that ECS was the ‘gold standard’ for localization of cortical function. We calculated descriptive statistics of the sensitivity and specificity of HGA in relation to ECS in a manner analogous to the way a diagnostic marker for disease (e.g. prostate-specific antigen) is tested against a definitive disease diagnosis (e.g. biopsy-proven prostate cancer). The sensitivity and specificity of HGA were calculated only for sites where both HGA and ECS were tested. HGA sensitivity was calculated as the percentage of sites that were both HGA(+) and ECS(+) among all ECS(+) sites, and HGA specificity was calculated as the percentage of sites that were both HGA(−) and ECS(−) among all ECS(−) sites. These measures were calculated separately for electrode sites where ECS interfered with picture naming and mouth-related motor function. Because ECS interference with mouth-related motor function often precluded ECS testing of naming, HGA specificity and sensitivity were also calculated for the subset of ECS-tested electrode sites that were tested for naming, excluding electrode sites where naming was not tested because of interference with mouth-related motor function. Confidence intervals (P < 0.05) were calculated for the sensitivity and specificity estimates under the assumption that, conditional on ECS, the findings of HGA were independent, identically distributed, Bernoulli random variables.

We noticed a considerable interindividual variability amongst patients in (i) the number of ‘active’ sites, i.e. HGA(+) with event-related gamma activity according to our criteria, (ii) the magnitude of statistically significant event-related gamma activity, and (iii) the spatial distribution of HGA(+) sites. In order to explore the selection criteria for HGA(+) sites that would yield the optimal sensitivity and specificity in relation to ECS functional maps, we systematically changed our criteria for determining HGA(+) sites in two different ways (Table 2). The first was the threshold magnitude of event-related HGA at which we selected electrodes as HGA(+). We studied the effect of varying this threshold in three categories of HGA(+) sites defined by (i) all significant sites (no threshold magnitude), (ii) only sites at which the magnitude of significant event-related HGA was ≥30% above baseline, and (iii) only sites with significant event-related HGA ≥50% above baseline (Table 2). The second way by which we varied our criteria for HGA(+) sites was to limit the total number of HGA(+) sites to be allowed for each patient in our calculations of HGA sensitivity and specificity. This was done to reduce the influence of individual differences in the magnitude (and therefore the statistical significance) of HGA and the number of HGA(+) electrode sites, without arbitrarily selecting a threshold of HGA magnitude. In each patient the HGA(+) electrode sites were ordered according to the magnitude of statistically significant event-related HGA, and the additive specificity and sensitivity of HGA were calculated for one to 18 of the sites with the greatest event-related gamma magnitude (Table 2). Note that some patients had <18 HGA(+) sites and therefore did not contribute to the calculations beyond their total number of HGA(+) sites.

View this table:
Table 2

Sensitivity/specificity of ECoG HGA in relation to ECS maps: effects of different selection criteria for HGA(+) sites

Sensitivity (%)Specificity (%)
Mouth*NamingMouth + namingMouth*NamingMouth + naming
HGA magnitude threshold
≥50%28.925.027.383.682.285.2
≥30%45.838.342.773.671.375.9
No threshold49.443.346.970.468.373.0
HGA(+) sites
18.43.36.398.497.298.7
213.36.710.596.094.496.5
318.110.014.793.891.994.5
421.715.018.991.689.892.9
525.316.721.789.587.390.7
630.118.325.288.185.389.4
734.921.729.486.883.588.4
841.026.735.085.782.088.1
944.630.038.584.680.787.5
1045.836.742.083.079.986.8
1145.838.342.781.778.985.5
1245.838.342.780.677.984.2
1347.038.343.479.876.983.3
1447.038.343.479.076.182.3
1548.240.044.878.475.682.0
1648.241.745.577.675.181.4
1749.441.746.277.174.480.7
1849.441.746.276.573.980.1
  • * ECS interference with mouth-related motor function.

  • Threshold for designating HGA(+) sites according to percentage increase of HGA (power in 80–100 Hz band) over baseline.

  • The maximum number of HGA(+) electrode sites allowed for calculations of sensitivity/specificity.

A lateral view of electrode positions over the left hemisphere was taken from each patient and normalized to a single schematic lateral brain image. All ECS(+) sites for naming and mouth-related motor function, and HGA(+) sites up to a limit of 12 sites per patient, were displayed in separate groups in the common coordinates of the schematic brain (Fig. 1), and the coordinates of the electrode sites were measured to evaluate the spatial distributions for each group of sites.

Fig. 1

Spatial distribution of ECoG and ECS maps from all 13 patients in common coordinates. (A) Electrode sites where both ECoG and ECS mapping was performed. (B) Electrode sites with event-related ECoG HGA during naming, limited to the 12 sites per patient with greatest HGA magnitude. (C) Electrode sites where ECS interfered with or produced involuntary movements of mouth, lips or tongue. (D) Electrode sites where ECS interfered with naming.

To further investigate the association between HGA and ECS functional maps, a χ2-test was performed to test the null hypothesis that HGA results were independent of ECS results. For each electrode site studied we obtained one of four possible outcomes for the two mapping methods (ECS, HGA): (+,+), (+,−), (−,+) or (−,−). In this coding, for example, (+,−) corresponded to a site that was ECS(+) and HGA(−), i.e. ECS induced impairment without event-related gamma activity. Given the paired nature of ECS and HGA testing at each electrode site, a 2 × 2 table was constructed in which each cell contained the number of observed pairs of (ECS,HGA) results. The corresponding 2 × 2 table was then used in a chi-square test of the independence of ECS versus HGA maps. The contribution of each of the individual cells was also calculated separately to show the largest cell contributions to the overall test statistic.

ECS and ECoG functional maps and postoperative outcome

In the 10 patients who underwent surgical resection, the extent of the resection and its relationship with the results of ECS and ECoG mapping were determined from (i) preoperative and operative notes and/or (ii) postoperative neuroimaging (available in four patients). Postoperative outcome was assessed with formal cognitive testing in seven patients who underwent surgical resection. Naming performance was assessed with the Boston Naming Test (Goodglass et al., 1983). Verbal fluency was assessed with the FAS test (Tombaugh et al., 1999). Verbal memory was assessed with the Rey Auditory Verbal Learning Test (Western Psychological Services, Los Angeles, CA, USA). Outcome information in the remainder was drawn from informal clinical assessments found in patients' postoperative medical records.

Results

Maps of ECS and ECoG HGA

The electrode sites tested with both ECS and ECoG HGA are illustrated in Fig. 1A for all patients in common coordinates. The number of electrode sites (average ± SD) tested for ECoG HGA (60.6 ± 18.5) was greater than the number tested with ECS (44.2 ± 18.7) in 11 of the 13 patients, resulting in many HGA(+) results at sites that were not tested by ECS. On the other hand, most sites tested with ECS were also tested for HGA. This may reflect the fact that ECoG recording could be performed in parallel on all subdural electrodes at once. In contrast, ECS testing was carried out sequentially on pairs of electrodes and was therefore more time consuming, requiring prioritization of electrode sites for ECS testing.

Results from both ECS and ECoG HGA were obtained in an average of 34.9 ± 13.1 electrode sites per patient. Of these sites, ECS interfered with naming in an average of 7.6 ± 5.7 sites. ECS interfered with mouth-related motor function in an average of 8.6 ± 7.2 sites. The average number of all HGA(+) sites in each patient was 11.6 ± 10.1. Figures 24 illustrate the neuroanatomical relationships between the results of ECS and ECoG HGA in three different patients. Note the differences between these patients in the cortical regions covered by subdural electrodes, determined solely by clinical considerations. The plots of event-related ECoG HGA in these patients illustrate the variability of this activity across patients and across electrode sites within patients. This variability led us to investigate the effect of different thresholds of HGA on our sensitivity/specificity estimates (see below). These patients also illustrate that there were electrodes where ECoG was recorded, but ECS mapping was not performed, in some cases because of stimulation-induced pain (yellow bars in Figs 3 and 4).

Fig. 2

Comparison of event-related ECoG HGA with ECS maps in patient 3. White circles denote electrode sites where ECoG was recorded. Yellow plots show the magnitude of HGA as a percentage change (y-axis) with respect to baseline. The onset of the pictured object to be named occurred 400 ms after disappearance of a fixation point at 0 s (x-axis). Coloured bars join electrode pairs where ECS mapping was performed, colour-coded for the occurrence and types of functional effects. Note that ECS was not performed at some electrode sites where ECoG was recorded.

Fig. 3

Comparison of event-related ECoG HGA with ECS maps in patient 11, as in Fig. 2. Yellow bars indicate stimulation-induced pain, precluding functional mapping with ECS.

Fig. 4

Comparison of event-related ECoG HGA with ECS maps in patient 4, as in Figs 2 and 3. The extent of the temporal lobectomy is indicated by the shaded area.

The neuroanatomical distribution of HGA(+) and ECS(+) sites exhibited a good deal of interindividual variability. This is evident in the grouped data illustrated in common topographical coordinates (Fig. 1B–D). However, the anatomical variability of sites that were ECS(+) for mouth-related motor function appeared to be less than that of sites that were ECS(+) for naming. The SDs of the distances from the mean location of HGA(+) and ECS(+) sites were computed, and the SD for ECS(+) mouth-related motor sites was about 51% of the SD for ECS(+) naming sites.

The distribution of sites that were ECS(+) for mouth-related motor function was concentrated near posterior inferior frontal gyrus and inferior paracentral cortex in the frontal-parietal operculum (Fig. 1C). Sites that were ECS(+) for naming were most concentrated near the superior temporal gyrus and tended to exclude the aforementioned regions where ECS commonly disrupted mouth-related motor function. This was likely due in large part to the fact that naming was not routinely tested at sites that were ECS(+) for mouth-related motor function. The distribution of sites that were HGA(+) during naming appeared to encompass both regions with mouth-related ECS(+) sites and regions with sites ECS(+) for naming. Estimates of the sensitivity and specificity of ECoG HGA were therefore also made by combining sites that were ECS(+) for mouth-related motor function with those that were ECS(+) for naming (see below).

Sensitivity and specificity of ECoG HGA

The sensitivity and specificity of ECoG HGA were calculated only for sites where both ECS and ECoG mapping were performed (Fig. 1A and Table 2). Calculations for all 454 of these sites across the entire group of patients yielded a decreasing HGA specificity as the maximum number of allowed HGA(+) sites per patient increased and as the threshold gamma magnitude for HGA(+) sites was reduced; an opposite trend was observed for estimates of HGA sensitivity. When the average number of HGA(+) sites across patients, i.e. 12 sites, was used as the maximum number of allowed HGA(+) sites for each patient, the specificity of HGA was 77.9 ± 3.5% (95% confidence interval) relative to ECS(−) sites for naming and 80.6 ± 3.1% relative to ECS(−) sites for mouth-related motor function. The same number of allowed HGA(+) sites yielded a sensitivity of 38.3 ± 3.5% relative to ECS(+) naming sites and 45.8 ± 4.0% relative to ECS(+) sites for mouth-related motor function.

When the criterion for HGA(+) sites was set at different thresholds for the magnitude of event-related gamma activity during naming, the estimates of HGA sensitivity and specificity varied in a manner similar to the effects of varying the maximum number of allowed HGA(+) sites (Table 2). When the HGA(+) criterion required the magnitude of significant event-related HGA to exceed a threshold of 50% above baseline, the estimated specificity of HGA was 82.2 ± 3.1% relative to ECS(−) naming sites and 83.6 ± 3.1% relative to ECS(−) sites for mouth-related motor function sites. The equivalent HGA sensitivities were 25 ± 3.2% for ECS(+) naming sites and 28.9 ± 3.3% for mouth-related ECS(+) sites.

The sensitivity and specificity of HGA were also calculated after combining ECS sites for naming and mouth-related motor function. This was done because the distribution of sites that were HGA(+) during naming appeared to encompass both regions with mouth-related ECS(+) sites and regions with sites that were ECS(+) for naming or language function. Also, because naming was usually not tested if a site was ECS(+) for mouth-related motor function, sites that were ECS(+) for naming were almost mutually exclusive of sites that were ECS(+) for mouth-related motor function. Since the naming task used for ECoG recordings (and for ECS mapping) required verbal responses, presumably activating cortical sites responsible for mouth-related motor function, we estimated the sensitivity and specificity of ECoG HGA based on the assumption that if sites that were ECS(+) for mouth-related motor function could have been tested for naming, naming would have been impaired as well. This change in our calculations resulted in HGA sensitivity estimates that were intermediate between those calculated separately for ECS maps of mouth-related motor function and naming, but the combined specificity was higher than the separate calculations (Table 2). The sensitivity and specificity of HGA were also calculated only at sites where ECS naming was tested, excluding the sites where naming was not tested with ECS because of interference with mouth-related motor function. The sensitivities, e.g. 42.7 ± 3.7 for 12 HGA(+) sites, were similar to those calculated from all ECS-tested sites, whereas the specificities, e.g. 84.2 ± 3.4 for 12 HGA(+) sites, were higher than those calculated for ECS(+) naming sites among all ECS-tested sites (Table 2).

The null hypothesis of independence between ECS and ECoG gamma maps was rejected for mouth-related motor function (P < 0.001) and for naming (P < 0.01) after limiting the allowable numbers of HGA(+) electrodes per patient. The null hypothesis was rejected for naming when the number of allowed HGA(+) sites was 10 or more, whereas it was rejected for mouth-related motor function and for the combined mouth and naming sites regardless of the number of HGA(+) sites allowed. Evaluating the contribution to the χ2 statistic of each individual cell revealed that the cell contributing the most was that of electrode sites that were both HGA(+) and ECS(+), regardless of the function that was tested with ECS.

ECS and ECoG functional maps and postoperative outcome

To compare how well ECS and ECoG functional maps predicted postoperative functional outcome, it would be necessary to know precisely which ECS(+) and HGA(+) sites were resected. However, this information was not available for many of the patients that were studied with both mapping techniques (Table 3). Three patients did not undergo a resection because their seizure focus appeared to be located within functionally critical cortex. Postoperative neuroimaging was either not done, or the films were not available, in all but four patients. Although medical records describing the extent of resection sometimes contained sufficient information to determine whether ECS(+) or HGA(+) sites were resected, there were several patients in whom this information was indeterminate (‘+/−’ in Table 3).

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Table 3

Functional mapping and functional outcome of surgery

PatientSurgical procedure (extent of resection, if known) [complications, if any]Postoperative MRIECS(+) sites resectedHGA(+) sites resectedPost-operative cognitive outcome
1LTL + AH (5 cm)↓ verbal memory*
2No resectionNANANANA
3No resectionNANANANA
4LTL + AH (Fig. 4)++Impaired naming and verbal memory
5LTL + AH+/−No clinical change (no formal testing)
6LTL + AH (4.5 cm)++/−Transient mild expressive dysphasia (no formal testing)
7Left frontal lobectomy+/−↓ verbal memory, naming unchanged
8No resectionNANANANA
9LTL + H (5–5.5 cm)++/−↓ naming, ↓ verbal memory
10LTL only (3.5–4 cm)+No change
11Left temporal AVM resection [perioperative infarct of left temporal-parietal junction]− (CT)++Aphasia, right hemiparesis and hemianopia (no formal testing)
12LTL + AH+/−Initial word-finding difficulties resolved within 4 months, naming unchanged, ↓ verbal memory
13Left frontal AVM resection [venous thrombosis and infarct]+/−+/−Impaired verbal fluency, naming unchanged
  • * Decrement without impairment, post-op cognitive testing done only two days post-op, no further testing done.

  • HGA + site not included in calculations of sensitivity/specificity.

  • Multiple sites involved in perioperative infarct. ↓ = Decrement in performance on formal testing, without impairment; + /− = Insufficient information to verify whether (+) electrodes resected; LTL = left temporal lobectomy; AH = amygdalohippocampectomy, H = hippocampectomy without amygdalectomy; AVM = arteriovenous malformation.

In two patients, attempts to resect an arteriovenous malformation (AVM) were complicated by perioperative infarcts extending beyond the planned margins of resection. In Patient 11 (Table 3) the perioperative infarct involved a large portion of the left temporal-parietal junction and included several cortical sites that were ECS(+) and/or HGA(+). This patient had a severe postoperative aphasia, as well as a right hemiparesis and a right homonymous hemianopsia. However, the large extent of this patient's lesion makes it difficult to draw conclusions about the predictive validity of ECS or ECoG event-related HGA.

Patient 6 suffered a mild transient expressive dysphasia following a left temporal resection that definitely included ECS(+) sites; however, HGA(+) sites may have also been resected. In contrast, Patient 4 suffered severe and persistent naming and verbal memory impairments following resective surgery that included at least one HGA(+) site, but no ECS(+) sites. This was confirmed by coregistration of the subdural electrode coordinates from a post-implantation/pre-resection CT scan with a postoperative volumetric MRI demonstrating the extent of resection (Fig. 4). However, a large portion of the resected temporal lobe was not mapped, either because it was not covered with electrodes (no ECoG or ECS) or because of stimulation-induced pain (no ECS).

Of the two patients in whom it could be definitively said that no ECS(+) or HGA(+) sites were resected, one had a decrement (but no impairment) of verbal memory and no change in naming performance. Cognitive testing in the other patient revealed no change in naming or memory.

In the remaining four patients with resections (patients 5, 7, 9 and 12), there was insufficient information about the extent of resection (e.g. no postoperative neuroimaging) and its relationship to the subdural electrodes that were mapped, to determine definitively whether ECS(+) or HGA(+) sites were resected. Postoperative outcome in these patients was mixed, ranging from no clinical impairment (without formal testing) in patient 5, to decrements in naming and/or verbal memory (without impairment) on formal testing in patients 7, 9 and 12.

Discussion

General considerations

An ideal evaluation of the utility of ECoG HGA for functional mapping would consist of its comparison with postoperative neuropsychological outcome following the surgical resection of ECoG-mapped cortical tissue. Although ECoG mapping would be validated in part by the absence of impairment following resection of HGA(−) cortical tissue, an equally important validation would consist of impairment following resection of HGA(+) cortex. However, assuming the surgical plan cannot yet take ECoG maps into account because their clinical utility is still being investigated, such a finding is likely to occur only if (i) ECS is discordant with ECoG, i.e. ECS(−)/HGA(+), (ii) ECS mapping cannot be done because of stimulation-induced pain (Lesser et al., 1985) or excessive afterdischarges (Lesser et al., 1984, 1999; Blume et al., 2004), or (iii) ECS-induced impairments are disregarded because of an overriding concern for postoperative seizure control or tumor resection. Given our findings that HGA(+) tissue is often ECS(+), we expect that HGA(+) tissue will only rarely be resected and that a large number of patients will be required to make this critical test possible.

The data available from this study are too limited to draw definitive conclusions about the relationship between postoperative cognitive outcome and whether HGA(+) tissue was resected. Nevertheless, HGA(+) tissue was either resected (patient 4) or destroyed by perioperative infarction (patient 11, during resection of an AVM) in two patients, and both had postoperative language impairment. In patient 11, many ECS(+) sites were also involved in the perioperative infarct. In patient 4, ECS was negative in all tested electrode sites that were resected; however, there were several electrode sites that were not tested with ECS because of pain, and a good portion of the resected basal temporal neocortex was not covered by electrodes and thus was not mapped with either ECoG or ECS. In four patients (patients 7, 9, 10 and 12), all the cortical sites that were resected were HGA(−). Patients 7 and 10 had no postoperative change in naming performance, patient 9 demonstrated a decrease (without impairment) in naming and patient 12 experienced transient word-finding difficulties, but was unchanged in naming performance on subsequent formal testing. It could not be determined with certainty whether ECS(+) sites were included in the resection in the latter two patients. These results, though provocative, are still insufficient to demonstrate the predictive ability of ECoG HGA, and also underline the methodological difficulties of comparing either ECoG or ECS with postoperative outcome. Even when the extent of resection is well-defined (patient 4), cortical regions that are not covered with electrodes or cannot be mapped are nevertheless often included in the resection. Since a comprehensive evaluation of ECoG mapping against postoperative cognitive outcome is still forthcoming, we used the best available alternative, i.e. ECS mapping, to evaluate the utility of ECoG mapping using event-related HGA as an index of functional activation.

The widespread clinical use of ECS is based on numerous studies (for a recent review see Ojemann, 2003) that have supported its utility in preventing postoperative deficits. ECS is currently considered the gold standard for functional mapping in humans, against which newer mapping procedures, notably fMRI, have been measured (FitzGerald et al., 1997; Simos et al., 1999; Pouratian et al., 2002; Rutten et al., 2002; Roux et al., 2003). However, ECS is not an absolute gold standard, but is rather the best method that is currently available. Concerns about the accuracy of ECS have arisen from several sources. For example, ECS maps of sensorimotor cortex have demonstrated motor responses in cortex up to 4.7 cm anterior and 3.4 cm posterior to the central sulcus (Nii et al., 1996), yet postoperative motor deficits usually do not occur without lesions of relatively circumscribed and somatotopically specific regions in and around the banks of the central sulcus. Likewise, ECS of basal temporal cortex, including anterior fusiform gyrus and inferior temporal gyrus, often interferes with a variety of language tasks, but these same language tasks are usually unimpaired following its resection (Luders et al., 1991; Krauss et al., 1996). These observations and others (see below) have suggested that ECS may sometimes overestimate the cortical territory that is critical to function and thus may underestimate the territory that is safe for resection. For this reason it seems prudent for the time being to compare all functional mapping techniques, including ECS, with one another in order to understand the different perspectives that each method provides on cortical function, and to improve the utility of each for predicting postoperative deficits.

With the aforementioned caveats in mind, we compared maps of naming according to event-related ECoG HGA (80–100 Hz) with ECS maps of the same or related functions. The results of this study suggest that ECoG HGA is a reasonably specific but relatively insensitive screening test for predicting ECS-associated interference with naming. Our findings are not consistent with the widespread assumption that mapping methods based on cortical activation, e.g. fMRI, PET, EEG and MEG, will detect a larger area of activation than the area in which ECS and other lesions impair function. Maps based upon the effects of lesions, as with ECS, are assumed to include only those cortical regions without which function would not be possible. Activation-based mapping methods are assumed to also identify regions that are participating but are not necessarily critical for function (Sergent, 1994). These assumptions have been supported by three studies comparing fMRI with ECS (FitzGerald et al., 1997; Pouratian et al., 2002; Rutten et al., 2002). In these studies, fMRI activations predicted ECS-induced impairment with relatively high sensitivity but low specificity. However, these studies used batteries of four to five fMRI language tasks in comparisons with intraoperative ECS maps. fMRI maps of multiple language tasks were compared with intraoperative ECS maps of naming alone in two of these studies (Pouratian et al., 2002; Rutten et al., 2002), and in the remaining study (FitzGerald et al., 1997) intraoperative ECS mapping was guided by preoperative fMRI maps. A recent study comparing fMRI with ECS in 14 patients undergoing surgery for brain tumours (Roux et al., 2003) found that fMRI performed with naming alone had relatively low sensitivity but high specificity for detecting intraoperative ECS(+) cortical sites, similar to our findings.

Potential explanations for the discrepancies between ECoG and ECS maps, particularly the low apparent sensitivity of HGA, can be divided into (i) the methodological limitations of our comparison of ECoG with ECS, (ii) the limitations of HGA as a functional mapping tool, and (iii) the limitations of ECS as a gold standard for comparison.

Methodological limitations of comparing ECoG and ECS

Fundamental differences between ECoG and ECS complicate any comparison of their functional maps. ECoG yields an estimate of cortical activation, the magnitude of which varies over time and correlates temporally with stimuli and responses, and by inference with cortical processing (Crone et al., 1998b, 2001a, b). There is no a priori knowledge of what magnitude of HGA is indicative of cortical processing, or more fundamentally, of how much cortical processing is necessary and sufficient for function. Like fMRI and other activation-based methods, ECoG mapping requires the setting of a threshold that must be arbitrarily or empirically derived. In contrast, ECS typically yields a result that is essentially all-or-none and does not provide information about the amount or timing of cortical processing that was disrupted, except under experimental conditions (Hart et al., 1998). Because of the all-or-none, time-invariant nature of ECS, a significant amount of data reduction was required of our ECoG data to compare it with ECS, and this may have affected our results in ways that are yet to be discovered.

Another difference between the two methods arose from the fact that ECS mapping of language was not usually performed in electrodes where it interfered with mouth-related motor function. This required us to use ECS interference with mouth-related motor function as a surrogate for ECS interference with motor activity specific to speech production. However, among the electrode sites that were ECS(+) for mouth-related motor function there may have been some sites that were not critical for speech production. Although silent naming could have been used for ECoG mapping, it is not routinely used for ECS because of the need to verify the presence or absence of a response and therefore would have presented other problems for comparisons of the two methods.

Our comparison of ECoG and ECS was facilitated by the fact that both methods used the same subdural electrodes, and therefore the same coordinate space, making coregistration of their maps more straightforward than comparisons of other methods. However, the stimulating current of ECS was passed between pairs of electrodes and may have affected cortical tissue that was not within the field of view of ECoG recordings. Likewise, even if ECS exerted its effect through cortical tissue underlying only one of the pair of electrodes, both electrodes could have been considered ECS(+). Both of these sources of inaccuracy could have had the effect of artifactually reducing the apparent sensitivity of ECoG HGA. In addition, ECoG was recorded from many electrodes that were not tested with ECS. These electrode sites could not be included in our calculations of HGA sensitivity/specificity or of the overall association of the two methods, and might have changed our estimates if they could have been. There were also many regions that were simply not covered by electrodes and for which neither method could be used, and because clinical circumstances necessarily dictated the placement of subdural electrodes, there was a good deal of variability across patients in the number and location of electrodes.

Potential limitations of ECoG HGA

In spite of the necessary limitations of our methodology for comparison, our estimates of HGA sensitivity with respect to ECS were lower than expected and suggested that HGA might not have detected activation of some cortical regions critical to function. One potential explanation for this would be that our subdural ECoG recording apparatus did not record all the HGA associated with cortical activation. Given the low amplitude of gamma activity in macroelectrode recordings such as subdural ECoG, this is an important consideration. Based upon the common observation that the amplitudes of field potential oscillations logarithmically decline with increasing frequency, it is generally accepted that higher frequency oscillations are generated by coherent neuronal assemblies with smaller or more dispersed neuronal aggregates (Menon et al., 1996). ECS could potentially interfere with processing in cortical regions that are too small to generate enough gamma activity to be recorded by our apparatus. In addition, it is possible that the 1-cm centre-to-centre spacing of the implanted electrode array provided insufficient spatial sampling to capture all the gamma activity that was present. ECS may have interfered with function in a larger region of cortex, particularly between electrodes, than the field of view of ECoG, and it is possible that the gamma activity generated by these regions simply ‘fell between the cracks’. Future studies with more densely spaced electrode arrays may help determine whether this was a likely explanation for our findings, and in turn may improve the sensitivity of HGA.

It is also possible that the high gamma band we used was not optimal for comparison with ECS maps. Our choice of this band was based upon previous studies of event-related ECoG gamma activity in both low (∼40 Hz) and high (>70 Hz) gamma bands (Crone et al., 1998b, 2001b; Ohara et al., 2000; Pfurtscheller et al., 2003). These studies found that HGA was more consistently present in cortical regions where functional activation was expected. Based upon these studies HGA appeared to be a good candidate for a simple, general index of cortical activation. However, the functional significance of HGA, as well as its relationship to event-related changes in other frequency bands, including the traditional 40 Hz band, is still a topic of active investigation (Pfurtscheller and Lopes da Silva, 1999b; Crone and Hao, 2002b; Kaiser and Lutzenberger, 2003; Herrmann et al., 2004). These considerations underline the fact that ECoG spectral mapping is yet a new method and that like fMRI, many of its parameters will require adjustment for optimal performance.

Potential limitations of ECS

It is also important to consider the potential limitations of the ECS gold standard against which we compared ECoG HGA. It is possible that ECS is less specific than assumed, and conversely, that ECoG HGA is more sensitive than it appears upon comparison with ECS. Previous studies of ECS functional mapping of motor cortex (Nii et al., 1996) and language cortex (Luders et al., 1991; Krauss et al., 1996) have suggested that it may sometimes overestimate functionally critical cortex and underestimate cortex that is safe for resection. In the present study, the grouped data (Fig. 1B–D) showed that ECoG gamma had a more restricted distribution over perisylvian cortical regions known from lesion studies to be most critical for naming and other language functions (Gordon, 1997).

The specificity of ECS with respect to surgical outcome could potentially be reduced if cortex that is essential for function were deactivated by ECS in cortex that is itself not essential but has strong functional connectivity with essential cortex. This effect could take place by transynaptic interference with normal network activity in essential cortex and/or by diaschisis from deactivation of functionally interconnected cortex. In a recent case report (Ishitobi et al., 2000), ECS of basal temporal language cortex produced aphasic symptoms in association with intra-stimulus remote discharges in posterior superior temporal gyrus. Resection of ECS(+) sites in basal temporal cortex did not produce language deficits. Although the ECS current itself is likely concentrated within several millimeters of the pair of stimulating electrodes (Nathan et al., 1993), studies of ECS-induced afterdischarges have shown that they often spread to electrodes outside the immediate site of stimulation current (Lesser et al., 1984; Motamedi et al., 2002; Blume et al., 2004). Not only does this cast doubt on the reliability of ECS when it is associated with afterdischarges, but it also suggests a more general potential for ECS effects outside the stimulating current field. By simultaneously stimulating and recording through subdural electrodes, Matsumoto et al. (2004) recently found that single pulses at intensities typical for ECS produced cortico-cortical-evoked potentials. These potentials were observed in basal temporal cortex after stimulating anterior and posterior language areas, suggesting strong functional connectivity between these areas. Likewise, evoked potentials were elicited in anterior language areas by stimulation of posterior language areas and vice versa. All these findings suggest that ECS could have effects outside the immediate area of stimulation. Such a possibility must be considered in the clinical utilization of ECS and in its use as a gold standard for comparison with other functional mapping techniques.

Potential clinical uses for ECoG HGA in preoperative language mapping

The ideal methodology for functional mapping would have sufficient sensitivity to find all essential language regions and enough specificity to maximize the resection of diseased tissue. Assuming that ECS meets these criteria, the methodology of ECoG mapping with HGA used in this study appears to have good specificity but insufficient sensitivity to be considered a potential replacement for ECS. However, the favourable specificity of ECoG HGA suggests that in the clinical setting of patients undergoing epilepsy surgery, HGA could be useful for choosing cortical sites of lower priority for ECS mapping. That is, if a cortical site were HGA(+) according to the criteria we used in this study, it could reasonably be expected to be ECS(+) as well. However, if a site were HGA(−), it could still be ECS(+) and should therefore be given priority for ECS mapping, particularly if it lies in the path of the planned resection. ECoG could therefore provide a preliminary functional map from all implanted subdural electrodes before ECS is carried out sequentially at each cortical site. Similar ECoG methodology could also be used in the operating room in conjunction with ECS mapping. A functional map derived from ECoG gamma activity as defined in this paper would necessarily be understood to complement, but not replace the ECS map.

ECoG mapping could also be useful when ECS is not feasible. ECS sometimes produces excessive afterdischarges or even clinical seizures, which can interfere with localization of the focus responsible for spontaneous seizures (Lesser et al., 1984, 1999; Blume et al., 2004). ECS may also be halted by stimulus-induced pain, presumably through stimulation of trigeminal afferents in dura mater and larger blood vessels (Lesser et al., 1985). Under these circumstances, however, it would be especially important to remember the potential limitations of ECoG, i.e. HGA(−) sites might still be ECS(+).

ECoG mapping could also be used in conjunction with preoperative fMRI. Like ECoG, fMRI has not yet been accepted as a replacement for ECS. Direct comparisons of fMRI with intraoperative ECS have yielded contradicting conclusions (Pouratian et al., 2002; Roux et al., 2003). Although comparisons of ECoG or ECS with fMRI are complicated by the coregistration of functional maps that are topographic versus those that are tomographic, respectively, it seems prudent to obtain as much complementary information as possible given the varying strengths and limitations of these different methodologies. Greater experience with all available techniques may also yield additional insights into their respective roles in human functional brain mapping.

Future studies

There are a number of ways in which the utility of ECoG spectral mapping might be improved in the future. As already mentioned, the sensitivity of HGA could be improved by increasing the spatial sampling rate of the ECoG sensors, i.e. by reducing interelectrode distances. This would greatly increase the number of recording electrodes and amplifiers to record them, a technical challenge that should be easily met by emerging technology. In addition, the threshold for determining if sites are HGA(+) could be varied according to the individual considerations of each patient and perhaps each cortical region, including such factors as the distance of a site from the proposed resection and other data such as the results of the preoperative neuropsychological testing or the presence of a lesion on MRI. The use of additional or different language tasks might also help in identifying essential language cortex.

To simplify our comparison of ECoG with ECS we did not use the temporal information that is available from ECoG. However, the timing of cortical activation is a dimension of ECoG mapping that should not be underestimated. Previous studies have shown that the latency of ECoG HGA varies according to response latency (Crone et al., 1998b, 2001a), suggesting that HGA can be used to estimate the timing of cortical activation. The timing of cortical activation may in turn be used to infer the stage of associated information processing at the site where HGA is observed, analogous to the interpretation of the latency of event-related potentials and fields (Nobre and McCarthy, 1995; Levelt et al., 1998). Inferences about the stage of processing that takes place at a cortical site may provide more detailed information about its function, and thus about the risks associated with its resection.

Although prior studies have suggested that HGA is a good candidate for a general index of cortical activation, it is possible that the performance of ECoG spectral mapping might also be improved with the use of other ECoG frequency bands, or perhaps a combination of different frequency bands with complementary response properties. For example, both scalp EEG and subdural ECoG studies have suggested that event-related desynchronization in the alpha band may be a more sensitive but less specific index of functional cortical activation than the gamma band (Crone et al., 1998a, b; Pfurtscheller and Lopes da Silva, 1999a; Crone and Hao, 2002a; Pfurtscheller et al., 2003). Nevertheless, its apparent high sensitivity could improve the sensitivity of ECoG mapping, assuming the contribution of this index can be weighted appropriately in relation to that of the gamma band. Likewise, a different, perhaps broader, definition of the gamma band might yield different results. Previous ECoG recordings suggested that, across patients and recording sites, the 80–100 Hz band is most consistently reactive during functional cortical activation (Crone et al., 2001b). However, these studies also observed ECoG high gamma responses extending upward to frequencies ∼150 Hz (Ray et al., 2003). Systematic exploration of the effects of different frequency bands on the sensitivity/specificity of ECoG spectral maps were beyond the scope of this study but may eventually yield better diagnostic results. More importantly, a better understanding of the functional significance of event-related changes in the energy of different frequency bands may allow these electrophysiological phenomena to be used more effectively for both clinical and research purposes.

Because all currently available methods for functional mapping appear to have their unique strengths and limitations, further studies will be necessary to determine how they should be used to guide clinical decision-making. The utility of ECoG mapping, using event-related gamma activity and/or other indices of cortical activation, will ultimately depend on its ability to predict postoperative functional impairments, but further studies involving many more patients will be required to assess the predictive power of ECoG maps from this standpoint. Until then ECoG mapping may provide functional maps that complement those of other available methods, namely ECS and fMRI, in patients undergoing cortical resection for epilepsy and other brain diseases.

Acknowledgments

The authors would like to thank Robert Webber, PhD, Lei Hao, PhD, Jason Hamner, Muralikrishna Indukuri and Darryl Jackson for technical assistance. This study was supported by NINDS R01 NS040596 (N.E.C.). The work of D.B. was supported by NIDCD R01 DC005645. The work of B.G. was supported by R01 NS26553 and R01 NS29973. The work of F.A.L. was supported by R01 NS38493 and R01 NS40059.

References

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