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Mismatch Between Electrocortical Stimulation and Electrocorticography Frequency Mapping of Language
Brain Stimulation 6 (2013) 524e531
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Mismatch Between Electrocortical Stimulation and Electrocorticography Frequency Mapping of Language Prisca R. Bauer, Mariska J. Vansteensel, Martin G. Bleichner, Dora Hermes, Cyrille H. Ferrier, Erik J. Aarnoutse, Nick F. Ramsey* Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Department of Neurology and Neurosurgery, Section Brainfunction and Plasticity, HP G.03.124, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
a r t i c l e i n f o
a b s t r a c t
Article history: Received 14 August 2012 Received in revised form 6 December 2012 Accepted 2 January 2013 Available online 8 Feburary 2013
Background: Electrocortical Stimulation Mapping (ESM) is the gold standard for mapping eloquent cortex in neurosurgery. This technique, however, can cause seizures and requires good patient cooperation. Electrocorticography (ECoG) could replace ESM. Several studies have directly compared ESM and ECoG frequency mapping of language cortex, with mixed results. This may be due to ECoG mapping typically being limited to one or a few language tasks, potentially leading to underestimation of language representation. Objective: To evaluate the influence of the language task on the match between ECoG and ESM, we mapped language function based on episodes of spontaneous conversation with ECoG, and compared this with ESM data in eight epilepsy patients. A verb generation and picture naming task were used as reference standard. Methods: From the continuous ECoG and video registrations, periods of conversation were identified, distinguishing three conditions: speaking, listening and rest. A power-frequency analysis was done for each condition and the two language tasks. The match between ESM and ECoG frequency mapping was evaluated on the basis of sensitivity and specificity measures. Results: ECoG activation during spontaneous conversation and language tasks was seen in and around classic language areas. Comparing the electrodes activated in each condition with those indicated as language positive by ESM revealed that there was high specificity but relatively low sensitivity. Conclusion: The relatively poor match between ESM and ECoG mapping is not improved by using spontaneous language. Ó 2013 Elsevier Inc. All rights reserved.
Keywords: Electrocortical stimulation ESM Electrocorticography ECoG Language Conversation Mapping
Introduction In neurosurgery it is of paramount importance to resect a maximum of pathological brain tissue, while at the same time sparing essential brain functions. The gold standard for functional brain mapping to date is electrocortical stimulation mapping ESM [1e3]. ESM, although considered a clinical gold standard, has several disadvantages, the most important one being that it causes after-discharges in about 70% of the patients [4]. After-discharges
Financial disclosures: This research was funded by the BrainGain Smart Mix Programme, the Dutch Technology Foundation STW, the Applied Science Division of Netherlands Organisation for Scientific Research, the Technology Program of the Ministry of Economic Affairs, and the University of Utrecht (grant UGT7685). Conflict of interest: The authors have no conflicts of interest to disclose. * Corresponding author. Tel.: þ31 (0)88 755 6863; fax: þ31 (0)30 254 2100. E-mail address: [email protected] (N.F. Ramsey). 1935-861X/$ e see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.brs.2013.01.001
can lead to epileptic seizures, putting the patient at risk and making further testing unreliable or even impossible [5]. The technique is not standardized and has never been tested in a randomized controlled manner [1]. Much is unknown about the exact extent of the effect of ESM. The spreading of the applied current in brain tissue depends highly on individual anatomical and physiological properties and is therefore probably quite variable [1,6]. Furthermore, the experience of the neurologist or neuropsychologist carrying out ESM is crucial to its success. ESM is time consuming and subtle deficits, which may be important in daily life, may not be detected [7]. It requires good patient cooperation, which makes mapping in children or mentally challenged patients even more demanding. The electrical signal from the brain comprises oscillations of different frequencies, the amplitude of which is known to vary during behavior. This electrical neural activity can be registered from the brain with high spatial and temporal resolution using
P.R. Bauer et al. / Brain Stimulation 6 (2013) 524e531 Table 1 Inclusion criteria. Written consent signed for participation in scientific research Older than twelve years of age No language or other major cognitive impairments prior to electrode implantation Native Dutch speakers Left-sided language lateralization according to Wada test Left-sided grid coverage encompassing anatomical Broca’s and Wernicke’s areas Language was found during ESM
electrocorticography (ECoG) [8]. ECoG signals and their spatially localized, task-related power changes are being considered as an alternative method for clinical functional brain mapping [5,6,11e16]. This technique would be more patient friendly and time-efficient than ESM as it does not cause after-discharges and as it gives information about all electrodes simultaneously. Several studies have compared ECoG frequency mapping with ESM for mapping of the language cortex, with mixed results [12,13,15,16]. In all these studies so far, either sensitivity or specificity is too low to consider ECoG frequency mapping for language as a viable alternative for ESM. The suboptimal match between ECoG frequency mapping and ESM of language regions may be caused by the use of language tasks for ECoG mapping. Tasks address specific elements of language and may thus be too specific for mapping language function as a whole. Spontaneous conversation captures many elements of language function as opposed to specific language tasks, and may therefore provide a better representation. ECoG is typically acquired for many hours, allowing for extraction of data during conversation. In addition, since patients do not have to perform a task, this method could be potentially useful for patients who find it difficult to cooperate. Brain activation during conversations has been studied previously and showed clear changes in gamma power over classical language regions, as well as over more frontal and central regions [15]. The current study aims to explore the clinical usefulness of spontaneous language ECoG mapping and compare it with mapping based on language tasks. To our knowledge, this study is the first to examine ECoG frequency changes related to spontaneous speech as well as spontaneous listening, and the first to investigate whether ECoG frequency changes during non-task language match ESM results.
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A statistical comparison of ESM and ECoG mapping of spontaneous language was made. ECoG data of picture naming and verb generation tasks were used as a reference standard. Comparing these language tasks with spontaneous language also offers the opportunity to extend current knowledge about language function and language tasks. Methods Of the database of patients who underwent pre-operative grid implantation between 2006 and 2011 at the University Medical Center Utrecht, patients were selected who had left-sided electrode coverage over anatomical language areas and confirmed left-sided language function by ESM. Eight patients met the inclusion criteria (Tables 1 and 2). All patients gave their written consent for participation in this study. Grid-electrodes were implanted (between 88 and 110 contact points per patient, 2.3 mm exposed diameter, inter electrode distance 1 cm center to center; Ad-Tech, Racine, USA) for approximately one week. Signals were recorded continuously using a 128channel Micromed (Treviso, Italy) system (22 bits, band pass filter 0.15e134.4 Hz) at a sampling frequency of 512 Hz. The electrodes were placed at the surface of the lateral frontal, temporal and parietal cortical areas of the left hemisphere (Fig. 1A, [17]). Electrodes were localized based on a CT scan. To correct for the brain shift after electrode implantation, electrodes were projected to the brain surface of a preoperative anatomical MRI [17]. For visualization, electrode coordinates were normalized to MNI space using unified segmentation of the anatomical MRI [18]. Electrocortical stimulation mapping ESM mapping was performed according to standard clinical practice of the UMC Utrecht [19e21]. To map essential regions involved in language, patients had to name objects that were presented to them physically or as pictures on a computer screen, while brief currents were applied to neighboring electrode pairs using an IRES 600 CH electrical stimulator (Micromed, Italy; 50 Hz, 4e7 s, 1.5e10 mA). Intensity of the stimulations was individually tailored, maximizing effect size and minimizing the occurrence of after-discharges. Responses could range from no language problems at all to overt speech arrest. In our analysis, arrest means that the patient was unable to speak, whereas speech disruption
Table 2 Demographics of included patients. Patient Age Sex Handedness Wada Seizure focus
Grid location
1
24
F
R
L
L-posteriotemporal
L-temporal, temporo-occipital
94
2
43
M
R
L
L-temporal
L-temporal lobe, inferior frontal gyrus
88
L-temporal
L-temporal, frontal, parietal
110
L-centroparietal operculum in supramarginal gyrus L-posteriotemporal, focus anterior of Wernicke’s area L-temporo-parietal, 1) gyrus temp. sup., 2) in language areas L-frontotemporal, supramarginal gyrus. Complex seizure when hippocampus is involved L-frontal
L-parietal, L-central
104
L-frontal, temporal, parietal
107
L-temporal, frontal, parietal
104
Around L-superior temporal gyrus
104
L-frontal, Sylvian region, parietal
104
a
3
40
M
R
L
4
35
F
R
L
5
34
F
R
La
6
30
F
R
L a
7
49
M
R
L
8
34
F
R
L
IQ is performance IQ. a Wada test was done bilaterally. b IQ not tested. Patient performed on normal level.
No of IQ electrodes
Resection
111 L-sided basoanterior temporal and complete amygdalohippocampectomy b L-neocorticoamygdalohippocampectomy 107 L-temporal lobectomy hippocampectomy 90 L-inferior part of postcentral gyrus until parietal operculum 100 L-superior temporal gyrus 74 L-superior temporal gyrus 108 L-temporal and amygdalohippocampectomy 75 L-middle and inferior frontal gyrus
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P.R. Bauer et al. / Brain Stimulation 6 (2013) 524e531
Figure 1. (A) Electrodes stimulated for language (ESM (þ) and ESM ()). (B) ESM (þ) language electrodes. Electrodes plotted on normalized brain renderings for patients 1e8. See for method Hermes et al., 2010 [17].
encompassed everything between naming mistakes and hesitations. The records of the clinical language ESM sessions were analyzed systematically. For each stimulated electrode, the combinations in which it was stimulated, the number of times this combination was stimulated, and the effect of the stimulation were noted. In addition, the stimulations that were accompanied by an after-discharge were visually screened for the occurrence of a spread of the after-discharge over other electrodes than the stimulated ones. When this occurred, the respective stimulation was excluded from further analysis. Note that ESM was performed for pairs of electrodes, but that each electrode site needs to be considered separately in further analysis to obtain a meaningful comparison with ECoG frequency mapping. To identify individual ESM-positive electrodes for language, the following criteria were used: Each electrode had been stimulated at least twice and stimulation led to: e A speech arrest in at least two out of three stimulation trials (per electrode pair) in two or more pairs or e A speech arrest in at least two out of three stimulation trials (per pair) in one (or more) pairs þ speech disruption in at least two out of three stimulation trials (per pair) in one or more pairs or e A speech disruption in at least one out of three stimulation trials (per pair) in three or more pairs. Electrodes that were stimulated only once, and in one combination, were excluded from analysis.
Electrocorticography frequency mapping-spontaneous language All patients had simultaneous ECoG and video registration for 24 h a day. For each patient, a continuous period of 2 h of recording was selected, during which he or she had a conversation. Based on the video material, segments of data were extracted out of those periods, distinguishing three conditions: 1) Speaking, in which the patient was speaking directly to someone in the room or on the telephone. Monosyllabic
reactions from conversation partners were excluded as much as possible. 2) Listening, in which the patient listened to someone directly talking to him or her. Phone conversations and watching television were excluded. Monosyllabic reactions from the patients were excluded as much as possible, as were longer reactions. Humming, however, was accepted. 3) Rest, during which the patient was aware and awake, eyes open, but silent and in a silent environment. Watching television, reading and eating were excluded from this condition. Data within an hour after a clinical seizure, and trials with excessive movements, were excluded. In the speaking and listening condition, pauses longer than 1 s were excluded. For each patient, 90 s of material per condition was used for analysis, after exclusion of artefactual trials and electrodes. Analysis was done using in-house Matlab (version 7.9.0, R2009b) code and the open source Matlab toolbox Fieldtrip (http://www.ru.nl/ fcdonders/fieldtrip/). For each condition, data were re-referenced to the common average of all intracranial electrodes, and epoched into 1 s segments. For each epoch, spectral power was computed using a fast Fourier transform (1 Hz bins). Power was averaged over five different frequency bands: theta (4e7 Hz), alpha (8e14 Hz), beta (15e25 Hz), low gamma (26e45 Hz) and high gamma (65e95 Hz). Significance of the differences in power were determined using two-sided t-tests (P < 0.05, Bonferroni-corrected for the number of simultaneously recorded electrodes) for the contrasts speaking versus rest, listening versus rest and listening versus speaking/speaking versus listening for each frequency band. For the low frequencies (theta, alpha and beta), only electrodes showing a significant decrease in power were considered for further analysis. Averaged across tasks, less than 7% of electrodes displayed an increase in these frequency bands. For the 26e45 and 65e95 Hz frequency bands, only electrodes with a significant increase in power were studied further. Previous studies demonstrated that decreases in low frequencies and increases in high frequencies are most relevant for ECoG function mapping [9,10]. Table 3 Computation of sensitivity and specificity. ECoG (Reference test)
ESM (Gold standard) ESM (þ)
ESM ()
ECoG (þ) ECoG ()
A C
B D
Sensitivity and specificity were computed as follows: Sensitivity ¼ A/(A þ C). Specificity ¼ D/(B þ D). ESM (þ) ¼ electrodes stimulated for language, which were involved in language function. ESM () ¼ electrodes stimulated for language, which were not involved in language function.
P.R. Bauer et al. / Brain Stimulation 6 (2013) 524e531 Table 4 ESM data per patient. Patient
Number of stimulated electrodes
Number of language significant electrodes
1 2 3 4 5 6 7 8 Mean
50 63 57 45 86 56 34 68 57.375
2 6 9 5 3 20 7 6 7.3
(4) (9.5) (15.8) (11.1) (3.5) (35.7) (20.6) (8.7) (13.6)
In brackets percentages of total number of stimulated electrodes.
Electrocorticography frequency mapping-tasks Seven of the eight patients performed a verb generation task, overtly (n ¼ 6) or covertly (n ¼ 1). The task consisted of a visually presented noun, to which patients had to respond with a matching verb (e.g., “chair / to sit”). During the rest condition a cross hair was presented during which patients had to relax. Four of the eight patients performed a picture-naming task. Patients were presented with line drawings of familiar objects, which they had to name. The rest condition consisted of pictures of the same picture-set made unrecognizable by scrambling, during which they had to relax. For each task and each patient, 2 s per active and rest trial were used for analysis, and the total amount of data per condition was
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reduced to 90 s to equal the amount of data to that of spontaneous language. Video recordings confirmed that the majority of responses were indeed given during the 2 s of active trial selected. Signal processing was performed in the same way as described for the spontaneous language data. Comparison ESM e ECoG mapping To quantify the match between ECoG and ESM, sensitivity and specificity were computed for ECoG spontaneous language and task data using ESM as the gold standard (Table 3). Each electrode that was included for analysis (i.e., was stimulated at least in two combinations) was labeled as ECoG positive (þ) or negative (), and ESM (þ) or (). Sensitivity was computed as the total number of sites (of all patients) that were both ESM (þ) and ECoG (þ), divided by the total number of ESM (þ) electrodes (A/A þ C in Table 3). Specificity was the number of electrodes that were ESM () and ECoG (), divided by the total number of ESM () electrodes (D/ D þ B in Table 3). Only electrodes that were stimulated for language were included in this analysis. Results ESM (þ) electrodes were found in classical language areas, such as Broca and Wernicke and around the Sylvian fissure in the superior temporal gyrus (Table 4 and Fig. 1). During spontaneous speech, significant (t-test, P < 0.05) power changes were seen in all frequency bands (Fig. 2), but the number of activated channels
Figure 2. Renderings of all significantly responding ECoG electrodes (ECoG (þ)) in each frequency band that was studied, on a normalized brain, for patients 1e8 for spontaneous language and task-related language data. (A) Speaking versus rest, (N ¼ 8). (B) Listening versus rest, (N ¼ 8). (C) Verb generation versus rest, (N ¼ 7). (D) Picture naming versus rest, (N ¼ 4).
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Table 5 Numbers of significantly activated electrodes in the five frequency ranges that were studied for (A) speaking versus rest, (B) listening versus rest, (C) verb generation versus rest and (D) picture naming versus rest. A) Patient
Speaking
Speaking
Speaking
Speaking
Speaking
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
1 2 3 4 5 6 7 8 Mean
28 41 58 20 42 34 7 36 33.3
31 55 49 15 56 42 50 26 40.5
23 6 3 4 58 16 25 14 18.6
1 6 1 5 0 5 7 33 7.3
22 10 39 12 3 10 62 25 22.9
B) Patient
Listening
Listening
Listening
Listening
Listening
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
1 2 3 4 5 6 7 8 Mean
33 45 62 31 56 9 2 11 31.1
47 59 46 24 71 25 8 15 36.9
20 13 5 7 56 14 10 14 17.4
0 3 8 6 0 0 0 0 2.1
26 7 38 26 1 7 27 6 17.3
C) Patient
Verb gen
Verb gen
Verb gen
Verb gen
Verb gen
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
1 2 3 4 5 6 7 8 Mean
26 46 8 37 13 5 n.a. 65 28.6
38 53 2 37 12 7 n.a. 49 28.3
32 9 8 45 14 2 n.a. 15 17.9
0 4 0 0 0 0 n.a. 15 2.7
9 9 10 20 11 6 n.a. 15 11.4
D) Patient
Picnam
Picnam
Picnam
Picnam
Picnam
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
24 46 n.a. 14 n.a. n.a. n.a. 9 23.3
24 17 n.a. 13 n.a. n.a. n.a. 3 14.3
13 4 n.a. 14 n.a. n.a. n.a. 0 7.8
0 1 n.a. 0 n.a. n.a. n.a. 0 0.3
20 11 n.a. 4 n.a. n.a. n.a. 3 9.5
1 2 3 4 5 6 7 8 Mean
n.a. ¼ data not available for this patient.
differed between patients, and between frequency bands. Generally, more electrodes showed significant changes in low frequencies than in higher frequencies (Table 5A and B). In most patients, there were more ECoG (þ) electrodes than ESM (þ) electrodes. ECoG (þ)electrodes were located consistently in classical language areas in all patients. For both speaking versus rest and listening versus rest, active electrodes were seen on the precentral gyrus, postcentral gyrus, inferior and superior parietal lobule, inferior frontal gyrus, middle frontal gyrus, superior frontal gyrus, and across the temporal lobe, including the temporal pole (Fig. 2A and B). Interestingly, when subtracting listening activation from speaking, activation was generally localized superior of the Sylvian fissure, whereas the focus of the activation was located inferior of the Sylvian fissure when speaking was subtracted from listening (Fig. 3). This was clearest in the alpha (8e14 Hz) and high gamma (65e95 Hz) bands. For the verb generation task, ECoG (þ) channels were found most consistently on the posterior part of the superior, middle and
inferior temporal gyrus, the angular and supramarginal gyri, the precentral gyrus and postcentral gyrus, and the inferior frontal gyrus (Fig. 2C). For the picture naming task, positive ECoG channels clustered around the Sylvian fissure (Fig. 2D). Consistent with our findings in spontaneous language, more ECoG (þ) electrodes were found in the lower frequency bands (Table 5C and D). ECoG data of spontaneous language and language tasks were compared with ESM data using sensitivity and specificity (Table 6). The alpha band was the most sensitive in speaking and listening versus rest (0.57 and 0.45 respectively). For the language tasks, the theta band was the most sensitive (0.37 and 0.53 for verb generation and picture naming, respectively). The specificity of the theta and alpha frequency bands, however, were the lowest (0.55e0.82) in all conditions. Formal post-operative testing of language function was available for 5 of 8 patients (Table 7). Of these, 2 patients (1 and 3) did not have any language deficits. Areas under ESM (þ) electrodes were resected in 2 patients (6 and 7). Patient 6 did not report any language deficits, although she was not formally tested. Patient 7 had the same verbal IQ as pre-operatively, but reported mild dysphasia when tired. In six patients, areas under ECoG (þ) electrodes were resected. Of these, four patients had no language deficits (2 not formally tested). Two patients reported mild dysphasia (1 formally tested). Interestingly, patient 4 had mild dysphasia post-operatively, but no ESM (þ) or ECoG (þ) sites were resected. Discussion This study investigated whether ECoG frequency mapping of spontaneous language is of clinical use for pre-operative language mapping and how it compares to ECoG mapping based on tasks in the context of complementing or replacing ESM. Limited agreement was observed between ECoG and ESM mapping regardless of the paradigm. The findings imply that ECoG mapping of critical language function for determination of regions to be spared in surgery, may yet not be feasible. We here provide additional support for the notion that functional mapping and ESM may yield fundamentally different results, as has been reported previously [13,20]. ECoG and ESM activation were found in classical language areas. ECoG also showed activation outside classical language areas, which could be related to the spatial extensiveness of the electrode coverage, allowing detection of power changes outside classical language areas. In addition, self-directed conversations are more complex, and may therefore involve a more elaborate neuronal network than simple language tasks [15,22]. Indeed, areas such as the prefrontal cortex (Brodmann’s area 10, and 9/46) and the temporal pole (Brodmann’s area 38), were more often activated during spontaneous language than during tasks (compare e.g. Fig. 2A and C). The former is thought to play a role in working memory, episodic retrieval, multi-tasking, attention and language [23,24]. Its role in language is probably on building a link between language content and memory [25]. The latter has been linked to discourse-level processing [26e29], and specific word retrieval such as names [30], but also seems to have a role in social and emotional processes, such as face recognition and theory of mind [31]. Activation over the sensorimotor cortex was seen for spontaneous as well as task-related language, although to a lesser extent in the latter. Gamma power increase in this area occurred more often during speaking than during listening. The involvement of motor areas, including limb areas, during language processing has been demonstrated before [32e37], but its function is not completely elucidated. It is likely that activation of these motor areas has a specific function and is not merely a by-product of other activity in
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Figure 3. Renderings of all electrodes showing a significant difference in the contrasts. (A) Speaking versus listening and (B) listening versus speaking.
the brain. Proposed roles are linguistic processing at the phoneme, syntax or semantic level, sound category processing, and conversational turn [38]. The number of ECoG (þ) electrodes differed largely between patients (Table 5), which could not be explained by differences in electrode coverage (Table 2). A possible cause is inter-individual anatomical variation, with language areas being located more on the surface in some people than in others. In addition, there is some evidence toward a relation between task complexity and spread of activation [22]. Indeed, the complexity of conversation varied between patients. Third, the number of activated ECoG electrodes may be related to the general level of arousal or to anti-epileptic medication effects [39,40]. Comparing the speaking and listening conditions of the spontaneous language with each other revealed that more electrodes showed changes in gamma power than in the other frequency bands. It is possible that power changes in the high gamma band are more function-specific than changes in lower frequency bands. Gamma power during speaking was greater than during listening over the precentral gyrus and the inferior frontal gyrus around Broca’s area. This indicates that the above-mentioned involvement of the motor cortex is stronger during speaking than during listening. Greater power during listening compared to speaking was seen around the Sylvian fissure, especially in and around the superior temporal gyrus. Numminen et al. [41] already showed that the activity of the auditory cortex was modulated during active speech. This could reflect the suppression of the sound of one’s own voice while speaking, and could be part of auditory feedback [42]. In the comparison between ESM and ECoG, the sensitivity and specificity values varied for the different frequencies and conditions. Values for task-related and spontaneous language were, however, all in the same range, and matched a low sensitivity with a higher specificity. The low frequency bands (theta/alpha) were consistently the most sensitive for ESM, but showed the lowest specificity. The higher frequency bands, on the other hand, were least sensitive but very specific. Previous studies comparing ESM and ECoG mapping for language have mainly focused on the gamma frequency band
[13,15,16]. In general, our sensitivity values for high gamma power are lower than the values found in those studies, whereas our specificity values are relatively high. One other study has focused on both low and high frequency bands [12], and found lower sensitivity values for low frequencies than for high frequencies, whereas specificity was higher in the lower frequency bands. This is in contrast to the consistently higher sensitivity we obtained in the theta and alpha bands, for both spontaneous and task-related language. Discrepancies in the sensitivity and specificity values between the different studies (including ours) may partially be explained by methodological differences in ECoG frequency mapping. Not only are the nature and the number of tasks or approaches dissimilar, but also the exact frequency bands differ, as well as the spectral power computations and the use (or not) of a correction for multiple comparisons in the statistical analysis. The diversity in ESM methods and analysis is even more important. We chose not to exclude electrodes from the sensitivity/ specificity analysis, which were shown by ESM to be involved in e.g., motor function, thereby replicating the clinical situation if ECoG were to be used to guide or even replace ESM. Moreover, a critical issue is the comparison between ECoG data, which gives information about single electrodes, and the results of ESM, which is performed over pairs of electrodes. In our study, we have taken a rigorous approach and used all available pair-wise ESM information to label individual electrodes as ESM (þ) or ESM (), allowing a direct comparison between ESM and ECoG frequency mapping on a single electrode basis. The only other study describing a similar approach is the one by Sinai et al. [13], whose sensitivity data were, notably, the most comparable to the values we obtained. It has been demonstrated that the computation of sensitivity and specificity values is highly affected by the choice of using single electrode ESM data or pair-based ESM data [14], with much higher sensitivity and specificity values obtained when pairwise ESM data are used. Although ESM and ECoG frequency mapping are fundamentally different methods and are therefore difficult to compare accurately, we believe that, in order to validate ECoG frequency mapping for its ability to replace ESM, it is crucial to confirm that electrodes that are indicated to be relevant for
Table 6 Sensitivity and specificity values for speaking, listening, verb generation and picture naming, with ESM as the gold standard.
4e7 Hz 8e14 Hz 15e25 Hz 26e45 Hz 65e95 Hz
Speaking versus rest
Listening versus rest
Verb generation versus rest
Picture naming versus rest
Sensitivity
Specificity
Sensitivity
Specificity
Sensitivity
Specificity
Sensitivity
Specificity
0.45 0.57 0.12 0.03 0.22
0.62 0.56 0.76 0.95 0.82
0.24 0.45 0.22 0.02 0.17
0.60 0.55 0.78 0.98 0.83
0.37 0.35 0.14 0.04 0.16
0.69 0.68 0.79 0.97 0.88
0.53 0.32 0.16 0.00 0.21
0.72 0.82 0.89 1.00 0.90
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Table 7 Outcome. Patient number
Post-operative outcome
Resection ESM (þ)
Resection ECoG (þ)
1 2 3 4 5 6 7
No language deficits Mild decline in word-finding abilities, paraphasia No language deficits Mild dysphasia, slight decrease in verbal IQ Very mild word-finding problems when tired (not formally tested) No language deficits (not formally tested) Mild dysphasia when tired. Otherwise no language deficits. Verbal IQ as pre-operatively No language deficits (not formally tested)
0 0 0 0 0 2 1
1 (alpha) 14 (theta & alpha) 10 (theta & alpha, 2 also in high gamma) 0 6 (theta, alpha, beta) 2 (alpha) 0
0
1 (theta, low gamma)
8
For each patient, the outcome of language function is given, together with the number electrodes that were assigned as ESM (þ) and/or that showed a significant change in one or more frequency bands during speaking versus rest and/or listening versus rest.
a function by ECoG frequency mapping, match exactly with ESM (þ) electrodes. Based on the sensitivity and specificity values we obtained for spontaneous and task-based language, we conclude that ECoG frequency mapping is not yet robust enough to be of clinical utility. This is in line with other studies demonstrating an incomplete match between ESM and ECoG frequency mapping [13,15,16]. The underlying cause for the incomplete match remains unclear, but may be related to the comparison between a lesioning technique (ESM) and an activation technique (ECoG frequency mapping). Using micro-electrode recordings, it was shown that besides “essential” language areas, which can be functionally disrupted by ESM, language function is supported by non-essential “participatory” areas (See for review [43]). A mapping technique such as ECoG probably shows activity in both essential and non-essential language areas [15]. Rutten et al. [20] demonstrated improvement of the match between another mapping technique (fMRI) and ESM, using several language tasks rather than one. This may also hold true for ECoG. It should be noted that spontaneous language is likely to engage a variety of language functions, and as such to some extent represents multiple tasks. It is, however, not clear whether such representation is adequate to map multiple language functions, a topic that deserves further examination. A second possible cause of the mismatch is the fact that different ESM tasks may result in different stimulation maps. For example, electrodes that are found to be stimulation positive when using a naming task, are not necessarily stimulation positive when verb generation is used as a paradigm during ESM [43]. In our patient population, ESM was performed with a picture naming task. It will be interesting to investigate whether a combination of tasks for ESM and/or ECoG frequency mapping will lead to a better prediction by the latter. A third possible cause is the selection of control tasks or conditions. More sophisticated control tasks conceptually produce more specific activation patterns (since nonlanguage regions then no longer confound the activity maps). However, the results of the present study reveal that even without careful control for non-language functions, the ECoG maps do not identify ESM foci well (low sensitivity). If more elegant control tasks were used, one would expect to find less ECoG activity, which is likely to further reduce the already low positive predictive value. Other methodological issues, such as the comparison of threshold dependent ECoG with all-or-none ESM should not be overlooked [13]. Another hypothesis is that ESM can disrupt the function of an area that is too small to generate enough gamma power for ECoG electrodes to pick up, or that ECoG may be more sensitive and ESM less specific than assumed [13]. This last hypothesis is supported by our results that demonstrate that lower frequencies, which are thought to be less area-specific, seem to be more sensitive for ESM than high frequencies, which are thought to be spatially focal [9,10].
Limitations of this study include the small sample size and heterogeneity of the patients in terms of e.g. seizure focus, which makes it difficult to draw robust conclusions. Lack of a standardized ESM procedures was discussed before [1]. Investigation of postoperative naming decline in patients who underwent temporal lobectomy showed no difference between patients who underwent pre-operative language mapping with ESM and patients who did not [44]. Recently, Cervenka et al. [7], showed that in bilingual individuals, ECoG predicted language deficits that ESM did not predict. It is thus not clear what an ESM (þ) electrode represents [1]. Future studies should aim to increase the understanding of the mechanisms underlying ESM and ECoG. To investigate the predictive value of ECoG and its potential to replace or complement ESM, post-operative effects when ESM () but ECoG (þ) sites are resected should be investigated. In the current study, no relationship between the occurrence of language deficits and the resection of ECoG (þ) electrodes was seen, but the number of included patients is too small to draw any conclusions. This issue should be studied in large groups [7]. Careful post-operative examination of language ability and self-reported subtle deficits in spontaneous language could help ascertain the value of both pre-operative mapping techniques. In conclusion, this study has shown that ECoG frequency mapping of spontaneous language and task-related language did not match ESM language mapping on single-electrode level. This emphasizes the importance of ESM for language function mapping. The results indicate that the relatively poor match between ESM and ECoG mapping is not improved by using spontaneous language. Instead, these, and other findings, encourage further investigation into the underlying phenomena of ESM and ECoG power changes. Acknowledgments The authors thank Frans Leijten, Geertjan Huiskamp, Herke Jan Noordmans and Tineke Gebbink for their help in collecting the data, Peter Gosselaar and Peter van Rijen for implanting the electrodes and staff of the clinical neurophysiology department for their time and effort. References [1] Hamberger MJ. Cortical language mapping in epilepsy: a critical review. Neuropsychol Rev 2007;17:477e89. [2] Penfield W, Roberts L. Speech and brain-mechanisms. Princeton University Press; 1959. Ch. 7: p. 103e111. [3] Ojemann G, Ojemann J, Lettich E, Berger M. Cortical language localisation in left, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients. J Neurosurg 1989;71:316e26. [4] Pouratian N, Cannestra AF, Bookheimer SY, Martin NA, Toga AW. Variability of intraoperative electrocortical stimulation mapping parameters across and within individuals. J Neurosurg 2004;101(3):458e66.
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Mismatch Between Electrocortical Stimulation and Electrocorticography Frequency Mapping of Language Prisca R. Bauer, Mariska J. Vansteensel, Martin G. Bleichner, Dora Hermes, Cyrille H. Ferrier, Erik J. Aarnoutse, Nick F. Ramsey* Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Department of Neurology and Neurosurgery, Section Brainfunction and Plasticity, HP G.03.124, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
a r t i c l e i n f o
a b s t r a c t
Article history: Received 14 August 2012 Received in revised form 6 December 2012 Accepted 2 January 2013 Available online 8 Feburary 2013
Background: Electrocortical Stimulation Mapping (ESM) is the gold standard for mapping eloquent cortex in neurosurgery. This technique, however, can cause seizures and requires good patient cooperation. Electrocorticography (ECoG) could replace ESM. Several studies have directly compared ESM and ECoG frequency mapping of language cortex, with mixed results. This may be due to ECoG mapping typically being limited to one or a few language tasks, potentially leading to underestimation of language representation. Objective: To evaluate the influence of the language task on the match between ECoG and ESM, we mapped language function based on episodes of spontaneous conversation with ECoG, and compared this with ESM data in eight epilepsy patients. A verb generation and picture naming task were used as reference standard. Methods: From the continuous ECoG and video registrations, periods of conversation were identified, distinguishing three conditions: speaking, listening and rest. A power-frequency analysis was done for each condition and the two language tasks. The match between ESM and ECoG frequency mapping was evaluated on the basis of sensitivity and specificity measures. Results: ECoG activation during spontaneous conversation and language tasks was seen in and around classic language areas. Comparing the electrodes activated in each condition with those indicated as language positive by ESM revealed that there was high specificity but relatively low sensitivity. Conclusion: The relatively poor match between ESM and ECoG mapping is not improved by using spontaneous language. Ó 2013 Elsevier Inc. All rights reserved.
Keywords: Electrocortical stimulation ESM Electrocorticography ECoG Language Conversation Mapping
Introduction In neurosurgery it is of paramount importance to resect a maximum of pathological brain tissue, while at the same time sparing essential brain functions. The gold standard for functional brain mapping to date is electrocortical stimulation mapping ESM [1e3]. ESM, although considered a clinical gold standard, has several disadvantages, the most important one being that it causes after-discharges in about 70% of the patients [4]. After-discharges
Financial disclosures: This research was funded by the BrainGain Smart Mix Programme, the Dutch Technology Foundation STW, the Applied Science Division of Netherlands Organisation for Scientific Research, the Technology Program of the Ministry of Economic Affairs, and the University of Utrecht (grant UGT7685). Conflict of interest: The authors have no conflicts of interest to disclose. * Corresponding author. Tel.: þ31 (0)88 755 6863; fax: þ31 (0)30 254 2100. E-mail address: [email protected] (N.F. Ramsey). 1935-861X/$ e see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.brs.2013.01.001
can lead to epileptic seizures, putting the patient at risk and making further testing unreliable or even impossible [5]. The technique is not standardized and has never been tested in a randomized controlled manner [1]. Much is unknown about the exact extent of the effect of ESM. The spreading of the applied current in brain tissue depends highly on individual anatomical and physiological properties and is therefore probably quite variable [1,6]. Furthermore, the experience of the neurologist or neuropsychologist carrying out ESM is crucial to its success. ESM is time consuming and subtle deficits, which may be important in daily life, may not be detected [7]. It requires good patient cooperation, which makes mapping in children or mentally challenged patients even more demanding. The electrical signal from the brain comprises oscillations of different frequencies, the amplitude of which is known to vary during behavior. This electrical neural activity can be registered from the brain with high spatial and temporal resolution using
P.R. Bauer et al. / Brain Stimulation 6 (2013) 524e531 Table 1 Inclusion criteria. Written consent signed for participation in scientific research Older than twelve years of age No language or other major cognitive impairments prior to electrode implantation Native Dutch speakers Left-sided language lateralization according to Wada test Left-sided grid coverage encompassing anatomical Broca’s and Wernicke’s areas Language was found during ESM
electrocorticography (ECoG) [8]. ECoG signals and their spatially localized, task-related power changes are being considered as an alternative method for clinical functional brain mapping [5,6,11e16]. This technique would be more patient friendly and time-efficient than ESM as it does not cause after-discharges and as it gives information about all electrodes simultaneously. Several studies have compared ECoG frequency mapping with ESM for mapping of the language cortex, with mixed results [12,13,15,16]. In all these studies so far, either sensitivity or specificity is too low to consider ECoG frequency mapping for language as a viable alternative for ESM. The suboptimal match between ECoG frequency mapping and ESM of language regions may be caused by the use of language tasks for ECoG mapping. Tasks address specific elements of language and may thus be too specific for mapping language function as a whole. Spontaneous conversation captures many elements of language function as opposed to specific language tasks, and may therefore provide a better representation. ECoG is typically acquired for many hours, allowing for extraction of data during conversation. In addition, since patients do not have to perform a task, this method could be potentially useful for patients who find it difficult to cooperate. Brain activation during conversations has been studied previously and showed clear changes in gamma power over classical language regions, as well as over more frontal and central regions [15]. The current study aims to explore the clinical usefulness of spontaneous language ECoG mapping and compare it with mapping based on language tasks. To our knowledge, this study is the first to examine ECoG frequency changes related to spontaneous speech as well as spontaneous listening, and the first to investigate whether ECoG frequency changes during non-task language match ESM results.
525
A statistical comparison of ESM and ECoG mapping of spontaneous language was made. ECoG data of picture naming and verb generation tasks were used as a reference standard. Comparing these language tasks with spontaneous language also offers the opportunity to extend current knowledge about language function and language tasks. Methods Of the database of patients who underwent pre-operative grid implantation between 2006 and 2011 at the University Medical Center Utrecht, patients were selected who had left-sided electrode coverage over anatomical language areas and confirmed left-sided language function by ESM. Eight patients met the inclusion criteria (Tables 1 and 2). All patients gave their written consent for participation in this study. Grid-electrodes were implanted (between 88 and 110 contact points per patient, 2.3 mm exposed diameter, inter electrode distance 1 cm center to center; Ad-Tech, Racine, USA) for approximately one week. Signals were recorded continuously using a 128channel Micromed (Treviso, Italy) system (22 bits, band pass filter 0.15e134.4 Hz) at a sampling frequency of 512 Hz. The electrodes were placed at the surface of the lateral frontal, temporal and parietal cortical areas of the left hemisphere (Fig. 1A, [17]). Electrodes were localized based on a CT scan. To correct for the brain shift after electrode implantation, electrodes were projected to the brain surface of a preoperative anatomical MRI [17]. For visualization, electrode coordinates were normalized to MNI space using unified segmentation of the anatomical MRI [18]. Electrocortical stimulation mapping ESM mapping was performed according to standard clinical practice of the UMC Utrecht [19e21]. To map essential regions involved in language, patients had to name objects that were presented to them physically or as pictures on a computer screen, while brief currents were applied to neighboring electrode pairs using an IRES 600 CH electrical stimulator (Micromed, Italy; 50 Hz, 4e7 s, 1.5e10 mA). Intensity of the stimulations was individually tailored, maximizing effect size and minimizing the occurrence of after-discharges. Responses could range from no language problems at all to overt speech arrest. In our analysis, arrest means that the patient was unable to speak, whereas speech disruption
Table 2 Demographics of included patients. Patient Age Sex Handedness Wada Seizure focus
Grid location
1
24
F
R
L
L-posteriotemporal
L-temporal, temporo-occipital
94
2
43
M
R
L
L-temporal
L-temporal lobe, inferior frontal gyrus
88
L-temporal
L-temporal, frontal, parietal
110
L-centroparietal operculum in supramarginal gyrus L-posteriotemporal, focus anterior of Wernicke’s area L-temporo-parietal, 1) gyrus temp. sup., 2) in language areas L-frontotemporal, supramarginal gyrus. Complex seizure when hippocampus is involved L-frontal
L-parietal, L-central
104
L-frontal, temporal, parietal
107
L-temporal, frontal, parietal
104
Around L-superior temporal gyrus
104
L-frontal, Sylvian region, parietal
104
a
3
40
M
R
L
4
35
F
R
L
5
34
F
R
La
6
30
F
R
L a
7
49
M
R
L
8
34
F
R
L
IQ is performance IQ. a Wada test was done bilaterally. b IQ not tested. Patient performed on normal level.
No of IQ electrodes
Resection
111 L-sided basoanterior temporal and complete amygdalohippocampectomy b L-neocorticoamygdalohippocampectomy 107 L-temporal lobectomy hippocampectomy 90 L-inferior part of postcentral gyrus until parietal operculum 100 L-superior temporal gyrus 74 L-superior temporal gyrus 108 L-temporal and amygdalohippocampectomy 75 L-middle and inferior frontal gyrus
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P.R. Bauer et al. / Brain Stimulation 6 (2013) 524e531
Figure 1. (A) Electrodes stimulated for language (ESM (þ) and ESM ()). (B) ESM (þ) language electrodes. Electrodes plotted on normalized brain renderings for patients 1e8. See for method Hermes et al., 2010 [17].
encompassed everything between naming mistakes and hesitations. The records of the clinical language ESM sessions were analyzed systematically. For each stimulated electrode, the combinations in which it was stimulated, the number of times this combination was stimulated, and the effect of the stimulation were noted. In addition, the stimulations that were accompanied by an after-discharge were visually screened for the occurrence of a spread of the after-discharge over other electrodes than the stimulated ones. When this occurred, the respective stimulation was excluded from further analysis. Note that ESM was performed for pairs of electrodes, but that each electrode site needs to be considered separately in further analysis to obtain a meaningful comparison with ECoG frequency mapping. To identify individual ESM-positive electrodes for language, the following criteria were used: Each electrode had been stimulated at least twice and stimulation led to: e A speech arrest in at least two out of three stimulation trials (per electrode pair) in two or more pairs or e A speech arrest in at least two out of three stimulation trials (per pair) in one (or more) pairs þ speech disruption in at least two out of three stimulation trials (per pair) in one or more pairs or e A speech disruption in at least one out of three stimulation trials (per pair) in three or more pairs. Electrodes that were stimulated only once, and in one combination, were excluded from analysis.
Electrocorticography frequency mapping-spontaneous language All patients had simultaneous ECoG and video registration for 24 h a day. For each patient, a continuous period of 2 h of recording was selected, during which he or she had a conversation. Based on the video material, segments of data were extracted out of those periods, distinguishing three conditions: 1) Speaking, in which the patient was speaking directly to someone in the room or on the telephone. Monosyllabic
reactions from conversation partners were excluded as much as possible. 2) Listening, in which the patient listened to someone directly talking to him or her. Phone conversations and watching television were excluded. Monosyllabic reactions from the patients were excluded as much as possible, as were longer reactions. Humming, however, was accepted. 3) Rest, during which the patient was aware and awake, eyes open, but silent and in a silent environment. Watching television, reading and eating were excluded from this condition. Data within an hour after a clinical seizure, and trials with excessive movements, were excluded. In the speaking and listening condition, pauses longer than 1 s were excluded. For each patient, 90 s of material per condition was used for analysis, after exclusion of artefactual trials and electrodes. Analysis was done using in-house Matlab (version 7.9.0, R2009b) code and the open source Matlab toolbox Fieldtrip (http://www.ru.nl/ fcdonders/fieldtrip/). For each condition, data were re-referenced to the common average of all intracranial electrodes, and epoched into 1 s segments. For each epoch, spectral power was computed using a fast Fourier transform (1 Hz bins). Power was averaged over five different frequency bands: theta (4e7 Hz), alpha (8e14 Hz), beta (15e25 Hz), low gamma (26e45 Hz) and high gamma (65e95 Hz). Significance of the differences in power were determined using two-sided t-tests (P < 0.05, Bonferroni-corrected for the number of simultaneously recorded electrodes) for the contrasts speaking versus rest, listening versus rest and listening versus speaking/speaking versus listening for each frequency band. For the low frequencies (theta, alpha and beta), only electrodes showing a significant decrease in power were considered for further analysis. Averaged across tasks, less than 7% of electrodes displayed an increase in these frequency bands. For the 26e45 and 65e95 Hz frequency bands, only electrodes with a significant increase in power were studied further. Previous studies demonstrated that decreases in low frequencies and increases in high frequencies are most relevant for ECoG function mapping [9,10]. Table 3 Computation of sensitivity and specificity. ECoG (Reference test)
ESM (Gold standard) ESM (þ)
ESM ()
ECoG (þ) ECoG ()
A C
B D
Sensitivity and specificity were computed as follows: Sensitivity ¼ A/(A þ C). Specificity ¼ D/(B þ D). ESM (þ) ¼ electrodes stimulated for language, which were involved in language function. ESM () ¼ electrodes stimulated for language, which were not involved in language function.
P.R. Bauer et al. / Brain Stimulation 6 (2013) 524e531 Table 4 ESM data per patient. Patient
Number of stimulated electrodes
Number of language significant electrodes
1 2 3 4 5 6 7 8 Mean
50 63 57 45 86 56 34 68 57.375
2 6 9 5 3 20 7 6 7.3
(4) (9.5) (15.8) (11.1) (3.5) (35.7) (20.6) (8.7) (13.6)
In brackets percentages of total number of stimulated electrodes.
Electrocorticography frequency mapping-tasks Seven of the eight patients performed a verb generation task, overtly (n ¼ 6) or covertly (n ¼ 1). The task consisted of a visually presented noun, to which patients had to respond with a matching verb (e.g., “chair / to sit”). During the rest condition a cross hair was presented during which patients had to relax. Four of the eight patients performed a picture-naming task. Patients were presented with line drawings of familiar objects, which they had to name. The rest condition consisted of pictures of the same picture-set made unrecognizable by scrambling, during which they had to relax. For each task and each patient, 2 s per active and rest trial were used for analysis, and the total amount of data per condition was
527
reduced to 90 s to equal the amount of data to that of spontaneous language. Video recordings confirmed that the majority of responses were indeed given during the 2 s of active trial selected. Signal processing was performed in the same way as described for the spontaneous language data. Comparison ESM e ECoG mapping To quantify the match between ECoG and ESM, sensitivity and specificity were computed for ECoG spontaneous language and task data using ESM as the gold standard (Table 3). Each electrode that was included for analysis (i.e., was stimulated at least in two combinations) was labeled as ECoG positive (þ) or negative (), and ESM (þ) or (). Sensitivity was computed as the total number of sites (of all patients) that were both ESM (þ) and ECoG (þ), divided by the total number of ESM (þ) electrodes (A/A þ C in Table 3). Specificity was the number of electrodes that were ESM () and ECoG (), divided by the total number of ESM () electrodes (D/ D þ B in Table 3). Only electrodes that were stimulated for language were included in this analysis. Results ESM (þ) electrodes were found in classical language areas, such as Broca and Wernicke and around the Sylvian fissure in the superior temporal gyrus (Table 4 and Fig. 1). During spontaneous speech, significant (t-test, P < 0.05) power changes were seen in all frequency bands (Fig. 2), but the number of activated channels
Figure 2. Renderings of all significantly responding ECoG electrodes (ECoG (þ)) in each frequency band that was studied, on a normalized brain, for patients 1e8 for spontaneous language and task-related language data. (A) Speaking versus rest, (N ¼ 8). (B) Listening versus rest, (N ¼ 8). (C) Verb generation versus rest, (N ¼ 7). (D) Picture naming versus rest, (N ¼ 4).
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Table 5 Numbers of significantly activated electrodes in the five frequency ranges that were studied for (A) speaking versus rest, (B) listening versus rest, (C) verb generation versus rest and (D) picture naming versus rest. A) Patient
Speaking
Speaking
Speaking
Speaking
Speaking
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
1 2 3 4 5 6 7 8 Mean
28 41 58 20 42 34 7 36 33.3
31 55 49 15 56 42 50 26 40.5
23 6 3 4 58 16 25 14 18.6
1 6 1 5 0 5 7 33 7.3
22 10 39 12 3 10 62 25 22.9
B) Patient
Listening
Listening
Listening
Listening
Listening
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
1 2 3 4 5 6 7 8 Mean
33 45 62 31 56 9 2 11 31.1
47 59 46 24 71 25 8 15 36.9
20 13 5 7 56 14 10 14 17.4
0 3 8 6 0 0 0 0 2.1
26 7 38 26 1 7 27 6 17.3
C) Patient
Verb gen
Verb gen
Verb gen
Verb gen
Verb gen
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
1 2 3 4 5 6 7 8 Mean
26 46 8 37 13 5 n.a. 65 28.6
38 53 2 37 12 7 n.a. 49 28.3
32 9 8 45 14 2 n.a. 15 17.9
0 4 0 0 0 0 n.a. 15 2.7
9 9 10 20 11 6 n.a. 15 11.4
D) Patient
Picnam
Picnam
Picnam
Picnam
Picnam
4e7 Hz
8e14 Hz
15e25 Hz
26e45 Hz
65e95 Hz
24 46 n.a. 14 n.a. n.a. n.a. 9 23.3
24 17 n.a. 13 n.a. n.a. n.a. 3 14.3
13 4 n.a. 14 n.a. n.a. n.a. 0 7.8
0 1 n.a. 0 n.a. n.a. n.a. 0 0.3
20 11 n.a. 4 n.a. n.a. n.a. 3 9.5
1 2 3 4 5 6 7 8 Mean
n.a. ¼ data not available for this patient.
differed between patients, and between frequency bands. Generally, more electrodes showed significant changes in low frequencies than in higher frequencies (Table 5A and B). In most patients, there were more ECoG (þ) electrodes than ESM (þ) electrodes. ECoG (þ)electrodes were located consistently in classical language areas in all patients. For both speaking versus rest and listening versus rest, active electrodes were seen on the precentral gyrus, postcentral gyrus, inferior and superior parietal lobule, inferior frontal gyrus, middle frontal gyrus, superior frontal gyrus, and across the temporal lobe, including the temporal pole (Fig. 2A and B). Interestingly, when subtracting listening activation from speaking, activation was generally localized superior of the Sylvian fissure, whereas the focus of the activation was located inferior of the Sylvian fissure when speaking was subtracted from listening (Fig. 3). This was clearest in the alpha (8e14 Hz) and high gamma (65e95 Hz) bands. For the verb generation task, ECoG (þ) channels were found most consistently on the posterior part of the superior, middle and
inferior temporal gyrus, the angular and supramarginal gyri, the precentral gyrus and postcentral gyrus, and the inferior frontal gyrus (Fig. 2C). For the picture naming task, positive ECoG channels clustered around the Sylvian fissure (Fig. 2D). Consistent with our findings in spontaneous language, more ECoG (þ) electrodes were found in the lower frequency bands (Table 5C and D). ECoG data of spontaneous language and language tasks were compared with ESM data using sensitivity and specificity (Table 6). The alpha band was the most sensitive in speaking and listening versus rest (0.57 and 0.45 respectively). For the language tasks, the theta band was the most sensitive (0.37 and 0.53 for verb generation and picture naming, respectively). The specificity of the theta and alpha frequency bands, however, were the lowest (0.55e0.82) in all conditions. Formal post-operative testing of language function was available for 5 of 8 patients (Table 7). Of these, 2 patients (1 and 3) did not have any language deficits. Areas under ESM (þ) electrodes were resected in 2 patients (6 and 7). Patient 6 did not report any language deficits, although she was not formally tested. Patient 7 had the same verbal IQ as pre-operatively, but reported mild dysphasia when tired. In six patients, areas under ECoG (þ) electrodes were resected. Of these, four patients had no language deficits (2 not formally tested). Two patients reported mild dysphasia (1 formally tested). Interestingly, patient 4 had mild dysphasia post-operatively, but no ESM (þ) or ECoG (þ) sites were resected. Discussion This study investigated whether ECoG frequency mapping of spontaneous language is of clinical use for pre-operative language mapping and how it compares to ECoG mapping based on tasks in the context of complementing or replacing ESM. Limited agreement was observed between ECoG and ESM mapping regardless of the paradigm. The findings imply that ECoG mapping of critical language function for determination of regions to be spared in surgery, may yet not be feasible. We here provide additional support for the notion that functional mapping and ESM may yield fundamentally different results, as has been reported previously [13,20]. ECoG and ESM activation were found in classical language areas. ECoG also showed activation outside classical language areas, which could be related to the spatial extensiveness of the electrode coverage, allowing detection of power changes outside classical language areas. In addition, self-directed conversations are more complex, and may therefore involve a more elaborate neuronal network than simple language tasks [15,22]. Indeed, areas such as the prefrontal cortex (Brodmann’s area 10, and 9/46) and the temporal pole (Brodmann’s area 38), were more often activated during spontaneous language than during tasks (compare e.g. Fig. 2A and C). The former is thought to play a role in working memory, episodic retrieval, multi-tasking, attention and language [23,24]. Its role in language is probably on building a link between language content and memory [25]. The latter has been linked to discourse-level processing [26e29], and specific word retrieval such as names [30], but also seems to have a role in social and emotional processes, such as face recognition and theory of mind [31]. Activation over the sensorimotor cortex was seen for spontaneous as well as task-related language, although to a lesser extent in the latter. Gamma power increase in this area occurred more often during speaking than during listening. The involvement of motor areas, including limb areas, during language processing has been demonstrated before [32e37], but its function is not completely elucidated. It is likely that activation of these motor areas has a specific function and is not merely a by-product of other activity in
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Figure 3. Renderings of all electrodes showing a significant difference in the contrasts. (A) Speaking versus listening and (B) listening versus speaking.
the brain. Proposed roles are linguistic processing at the phoneme, syntax or semantic level, sound category processing, and conversational turn [38]. The number of ECoG (þ) electrodes differed largely between patients (Table 5), which could not be explained by differences in electrode coverage (Table 2). A possible cause is inter-individual anatomical variation, with language areas being located more on the surface in some people than in others. In addition, there is some evidence toward a relation between task complexity and spread of activation [22]. Indeed, the complexity of conversation varied between patients. Third, the number of activated ECoG electrodes may be related to the general level of arousal or to anti-epileptic medication effects [39,40]. Comparing the speaking and listening conditions of the spontaneous language with each other revealed that more electrodes showed changes in gamma power than in the other frequency bands. It is possible that power changes in the high gamma band are more function-specific than changes in lower frequency bands. Gamma power during speaking was greater than during listening over the precentral gyrus and the inferior frontal gyrus around Broca’s area. This indicates that the above-mentioned involvement of the motor cortex is stronger during speaking than during listening. Greater power during listening compared to speaking was seen around the Sylvian fissure, especially in and around the superior temporal gyrus. Numminen et al. [41] already showed that the activity of the auditory cortex was modulated during active speech. This could reflect the suppression of the sound of one’s own voice while speaking, and could be part of auditory feedback [42]. In the comparison between ESM and ECoG, the sensitivity and specificity values varied for the different frequencies and conditions. Values for task-related and spontaneous language were, however, all in the same range, and matched a low sensitivity with a higher specificity. The low frequency bands (theta/alpha) were consistently the most sensitive for ESM, but showed the lowest specificity. The higher frequency bands, on the other hand, were least sensitive but very specific. Previous studies comparing ESM and ECoG mapping for language have mainly focused on the gamma frequency band
[13,15,16]. In general, our sensitivity values for high gamma power are lower than the values found in those studies, whereas our specificity values are relatively high. One other study has focused on both low and high frequency bands [12], and found lower sensitivity values for low frequencies than for high frequencies, whereas specificity was higher in the lower frequency bands. This is in contrast to the consistently higher sensitivity we obtained in the theta and alpha bands, for both spontaneous and task-related language. Discrepancies in the sensitivity and specificity values between the different studies (including ours) may partially be explained by methodological differences in ECoG frequency mapping. Not only are the nature and the number of tasks or approaches dissimilar, but also the exact frequency bands differ, as well as the spectral power computations and the use (or not) of a correction for multiple comparisons in the statistical analysis. The diversity in ESM methods and analysis is even more important. We chose not to exclude electrodes from the sensitivity/ specificity analysis, which were shown by ESM to be involved in e.g., motor function, thereby replicating the clinical situation if ECoG were to be used to guide or even replace ESM. Moreover, a critical issue is the comparison between ECoG data, which gives information about single electrodes, and the results of ESM, which is performed over pairs of electrodes. In our study, we have taken a rigorous approach and used all available pair-wise ESM information to label individual electrodes as ESM (þ) or ESM (), allowing a direct comparison between ESM and ECoG frequency mapping on a single electrode basis. The only other study describing a similar approach is the one by Sinai et al. [13], whose sensitivity data were, notably, the most comparable to the values we obtained. It has been demonstrated that the computation of sensitivity and specificity values is highly affected by the choice of using single electrode ESM data or pair-based ESM data [14], with much higher sensitivity and specificity values obtained when pairwise ESM data are used. Although ESM and ECoG frequency mapping are fundamentally different methods and are therefore difficult to compare accurately, we believe that, in order to validate ECoG frequency mapping for its ability to replace ESM, it is crucial to confirm that electrodes that are indicated to be relevant for
Table 6 Sensitivity and specificity values for speaking, listening, verb generation and picture naming, with ESM as the gold standard.
4e7 Hz 8e14 Hz 15e25 Hz 26e45 Hz 65e95 Hz
Speaking versus rest
Listening versus rest
Verb generation versus rest
Picture naming versus rest
Sensitivity
Specificity
Sensitivity
Specificity
Sensitivity
Specificity
Sensitivity
Specificity
0.45 0.57 0.12 0.03 0.22
0.62 0.56 0.76 0.95 0.82
0.24 0.45 0.22 0.02 0.17
0.60 0.55 0.78 0.98 0.83
0.37 0.35 0.14 0.04 0.16
0.69 0.68 0.79 0.97 0.88
0.53 0.32 0.16 0.00 0.21
0.72 0.82 0.89 1.00 0.90
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Table 7 Outcome. Patient number
Post-operative outcome
Resection ESM (þ)
Resection ECoG (þ)
1 2 3 4 5 6 7
No language deficits Mild decline in word-finding abilities, paraphasia No language deficits Mild dysphasia, slight decrease in verbal IQ Very mild word-finding problems when tired (not formally tested) No language deficits (not formally tested) Mild dysphasia when tired. Otherwise no language deficits. Verbal IQ as pre-operatively No language deficits (not formally tested)
0 0 0 0 0 2 1
1 (alpha) 14 (theta & alpha) 10 (theta & alpha, 2 also in high gamma) 0 6 (theta, alpha, beta) 2 (alpha) 0
0
1 (theta, low gamma)
8
For each patient, the outcome of language function is given, together with the number electrodes that were assigned as ESM (þ) and/or that showed a significant change in one or more frequency bands during speaking versus rest and/or listening versus rest.
a function by ECoG frequency mapping, match exactly with ESM (þ) electrodes. Based on the sensitivity and specificity values we obtained for spontaneous and task-based language, we conclude that ECoG frequency mapping is not yet robust enough to be of clinical utility. This is in line with other studies demonstrating an incomplete match between ESM and ECoG frequency mapping [13,15,16]. The underlying cause for the incomplete match remains unclear, but may be related to the comparison between a lesioning technique (ESM) and an activation technique (ECoG frequency mapping). Using micro-electrode recordings, it was shown that besides “essential” language areas, which can be functionally disrupted by ESM, language function is supported by non-essential “participatory” areas (See for review [43]). A mapping technique such as ECoG probably shows activity in both essential and non-essential language areas [15]. Rutten et al. [20] demonstrated improvement of the match between another mapping technique (fMRI) and ESM, using several language tasks rather than one. This may also hold true for ECoG. It should be noted that spontaneous language is likely to engage a variety of language functions, and as such to some extent represents multiple tasks. It is, however, not clear whether such representation is adequate to map multiple language functions, a topic that deserves further examination. A second possible cause of the mismatch is the fact that different ESM tasks may result in different stimulation maps. For example, electrodes that are found to be stimulation positive when using a naming task, are not necessarily stimulation positive when verb generation is used as a paradigm during ESM [43]. In our patient population, ESM was performed with a picture naming task. It will be interesting to investigate whether a combination of tasks for ESM and/or ECoG frequency mapping will lead to a better prediction by the latter. A third possible cause is the selection of control tasks or conditions. More sophisticated control tasks conceptually produce more specific activation patterns (since nonlanguage regions then no longer confound the activity maps). However, the results of the present study reveal that even without careful control for non-language functions, the ECoG maps do not identify ESM foci well (low sensitivity). If more elegant control tasks were used, one would expect to find less ECoG activity, which is likely to further reduce the already low positive predictive value. Other methodological issues, such as the comparison of threshold dependent ECoG with all-or-none ESM should not be overlooked [13]. Another hypothesis is that ESM can disrupt the function of an area that is too small to generate enough gamma power for ECoG electrodes to pick up, or that ECoG may be more sensitive and ESM less specific than assumed [13]. This last hypothesis is supported by our results that demonstrate that lower frequencies, which are thought to be less area-specific, seem to be more sensitive for ESM than high frequencies, which are thought to be spatially focal [9,10].
Limitations of this study include the small sample size and heterogeneity of the patients in terms of e.g. seizure focus, which makes it difficult to draw robust conclusions. Lack of a standardized ESM procedures was discussed before [1]. Investigation of postoperative naming decline in patients who underwent temporal lobectomy showed no difference between patients who underwent pre-operative language mapping with ESM and patients who did not [44]. Recently, Cervenka et al. [7], showed that in bilingual individuals, ECoG predicted language deficits that ESM did not predict. It is thus not clear what an ESM (þ) electrode represents [1]. Future studies should aim to increase the understanding of the mechanisms underlying ESM and ECoG. To investigate the predictive value of ECoG and its potential to replace or complement ESM, post-operative effects when ESM () but ECoG (þ) sites are resected should be investigated. In the current study, no relationship between the occurrence of language deficits and the resection of ECoG (þ) electrodes was seen, but the number of included patients is too small to draw any conclusions. This issue should be studied in large groups [7]. Careful post-operative examination of language ability and self-reported subtle deficits in spontaneous language could help ascertain the value of both pre-operative mapping techniques. In conclusion, this study has shown that ECoG frequency mapping of spontaneous language and task-related language did not match ESM language mapping on single-electrode level. This emphasizes the importance of ESM for language function mapping. The results indicate that the relatively poor match between ESM and ECoG mapping is not improved by using spontaneous language. Instead, these, and other findings, encourage further investigation into the underlying phenomena of ESM and ECoG power changes. Acknowledgments The authors thank Frans Leijten, Geertjan Huiskamp, Herke Jan Noordmans and Tineke Gebbink for their help in collecting the data, Peter Gosselaar and Peter van Rijen for implanting the electrodes and staff of the clinical neurophysiology department for their time and effort. References [1] Hamberger MJ. Cortical language mapping in epilepsy: a critical review. Neuropsychol Rev 2007;17:477e89. [2] Penfield W, Roberts L. Speech and brain-mechanisms. Princeton University Press; 1959. Ch. 7: p. 103e111. [3] Ojemann G, Ojemann J, Lettich E, Berger M. Cortical language localisation in left, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients. J Neurosurg 1989;71:316e26. [4] Pouratian N, Cannestra AF, Bookheimer SY, Martin NA, Toga AW. Variability of intraoperative electrocortical stimulation mapping parameters across and within individuals. J Neurosurg 2004;101(3):458e66.
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