Passive functional mapping of receptive language areas using electrocorticographic signals

Swift, James; Coon, William G.; Guger, Christoph; Brunner, Peter; Bunch, Marjorie E.; Lynch, Timothy M.; Frawley, Bridget K.; Ritaccio, Anthony L.; Schalk, Gerwin

doi:10.1016/j.clinph.2018.09.007

Cited by 24 publications

(12 citation statements)

References 47 publications

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“…Post-operative T1-weighted MRI was obtained from each patient to extract the resected volumes. The electrode locations within 10 mm distance to the resected volume were defined as resected locations to comply with the 10 mm safety margin published in previous mapping studies (Haglund et al, 1994;Sanai et al, 2008;Swift et al, 2018). Figure 4 shows the ECS results of patients P1 to P5.…”

Section: Surgical Outcome Evaluationmentioning

confidence: 99%

Multi-modal Mapping of the Face Selective Ventral Temporal Cortex–A Group Study With Clinical Implications for ECS, ECoG, and fMRI

Sanada

Kapeller

Jordán

et al. 2021

Front. Hum. Neurosci.

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Face recognition is impaired in patients with prosopagnosia, which may occur as a side effect of neurosurgical procedures. Face selective regions on the ventral temporal cortex have been localized with electrical cortical stimulation (ECS), electrocorticography (ECoG), and functional magnetic resonance imagining (fMRI). This is the first group study using within-patient comparisons to validate face selective regions mapping, utilizing the aforementioned modalities. Five patients underwent surgical treatment of intractable epilepsy and joined the study. Subdural grid electrodes were implanted on their ventral temporal cortices to localize seizure foci and face selective regions as part of the functional mapping protocol. Face selective regions were identified in all patients with fMRI, four patients with ECoG, and two patients with ECS. From 177 tested electrode locations in the region of interest (ROI), which is defined by the fusiform gyrus and the inferior temporal gyrus, 54 face locations were identified by at least one modality in all patients. fMRI mapping showed the highest detection rate, revealing 70.4% for face selective locations, whereas ECoG and ECS identified 64.8 and 31.5%, respectively. Thus, 28 face locations were co-localized by at least two modalities, with detection rates of 89.3% for fMRI, 85.7% for ECoG and 53.6 % for ECS. All five patients had no face recognition deficits after surgery, even though five of the face selective locations, one obtained by ECoG and the other four by fMRI, were within 10 mm to the resected volumes. Moreover, fMRI included a quite large volume artifact on the ventral temporal cortex in the ROI from the anatomical structures of the temporal base. In conclusion, ECS was not sensitive in several patients, whereas ECoG and fMRI even showed activation within 10 mm to the resected volumes. Considering the potential signal drop-out in fMRI makes ECoG the most reliable tool to identify face selective locations in this study. A multimodal approach can improve the specificity of ECoG and fMRI, while simultaneously minimizing the number of required ECS sessions. Hence, all modalities should be considered in a clinical mapping protocol entailing combined results of co-localized face selective locations.

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Section: Surgical Outcome Evaluationmentioning

confidence: 99%

Multi-modal Mapping of the Face Selective Ventral Temporal Cortex–A Group Study With Clinical Implications for ECS, ECoG, and fMRI

Sanada

Kapeller

Jordán

et al. 2021

Front. Hum. Neurosci.

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“…ECS has been the gold standard for functional mapping for decades ( 4 ). It is widely accepted that the application of conventional ECS methods produces specific and reliable outcomes at defined sites and that neurosurgical resective strategies guided by this method can eliminate or minimize sensorimotor and linguistic postoperative deficits ( 6 , 7 ).…”

Section: Discussionmentioning

confidence: 99%

“…Awake craniotomy is the only established method to intraoperatively verify the preservation of language function ( 2 ); however, precise functional mapping is still difficult in patients with language deficits ( 3 ). ECS has shortcomings, as it is time-consuming and may evoke after-discharges or seizures ( 4 ).…”

Section: Introductionmentioning

confidence: 99%

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The Efficacy of Intraoperative Passive Language Mapping for Glioma Surgery: A Case Report

et al. 2021

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Background: Recently, electrocorticographic (ECoG) studies have emphasized the importance of gamma band-based functional mapping in the presurgical localization of the eloquent cortex. Passive functional mapping using ECoG signals provides a reliable method for identifying receptive language areas without many of the risks and limitations associated with electrical cortical stimulation. We report a surgical case of left temporal malignant glioma with intraoperative passive language mapping.Case Description: A 78-year-old woman was diagnosed with left temporal glioma with inspection of her language difficulty. MRI showed a left temporal tumor measuring 74.6 × 50.0 × 51.5 mm in size. Real-time CortiQ-based mapping using high-gamma activity by word-listening and story-listening tasks was performed. Significant listening task-evoked high gamma activities were detected in 5 channels in the superior temporal gyrus and one channel in the middle temporal gyrus. The tumor was grossly removed except for the region corresponding to listening task-evoked high gamma activities. Postoperatively, the patient's symptoms of language comprehension difficulty improved, and no new neurological deficits were observed.Conclusion: Intraoperative passive language mapping was successfully performed, and the patient's language function was well-preserved. Intraoperative passive language mapping, which is applicable in a short time and under general anesthesia, can be an important tool for detecting language areas.

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“…Investigators have successfully recorded task-free high gamma augmentation associated with spontaneous cooing and babbling 76 and during passive listening. 7,77 Measurement of spectral responses to single-pulse electrical stimulation also has the potential to localize the network supporting speech and language [78][79][80] Additional measures are expected to improve the accuracy of machine learning-based prediction models.…”

Section: Methodological Considerationsmentioning

confidence: 99%

Naming-related spectral responses predict neuropsychological outcome after epilepsy surgery

Sonoda

Robert²,

Carlson³

et al. 2021

Preprint

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This prospective study determined the utility of intracranially-recorded spectral responses during naming tasks in predicting neuropsychological performance following epilepsy surgery. We recruited 65 patients with drug-resistant focal epilepsy who underwent preoperative neuropsychological assessment and intracranial EEG (iEEG) recording. The Clinical Evaluation of Language Fundamentals (CELF) evaluated the baseline and postoperative language function. During extraoperative iEEG recording, we assigned patients to undergo auditory and picture naming tasks. Time-frequency analysis determined the spatiotemporal characteristics of naming-related amplitude modulations, including high gamma augmentation (HGA) at 70-110 Hz. We surgically removed the presumed epileptogenic zone based on the extent of iEEG and MRI abnormalities while maximally preserving the eloquent areas defined by electrical stimulation mapping (ESM). The multivariate regression model incorporating auditory naming-related HGA predicted the postoperative changes in Core Language Score (CLS) on CELF with r2 of 0.37 (p = 0.015) and in Expressive Language Index (ELI) with r2 of 0.32 (p = 0.047). Independently of the effects of epilepsy and neuroimaging profiles, higher HGA at the resected language-dominant hemispheric area predicted a more severe postoperative decline in CLS (p = 0.004) and ELI (p = 0.012). Conversely, the model incorporating picture naming-related HGA predicted the change in Receptive Language Index (RLI) with r2 of 0.50 (p < 0.001). Higher HGA independently predicted a more severe postoperative decline in RLI (p = 0.03). Ancillary regression analysis indicated that naming-related low gamma augmentation as well as alpha/beta attenuation likewise independently predicted a more severe CLS decline. The machine learning-based prediction model, referred to as the boosted tree ensemble model, suggested that naming-related HGA, among all spectral responses utilized as predictors, most strongly contributed to the improved prediction of patients showing a >5-point CLS decline (reflecting the lower 25 percentile among patients). We generated the model-based atlas visualizing sites, which, if resected, would lead to such a CLS decline. The auditory naming-based model predicted patients who developed the CLS decline with an accuracy of 0.80. The model indicated that virtual resection of an ESM-defined language site would have increased the relative risk of the CLS decline by 5.28 (95%CI: 3.47 to 8.02). Especially, that of an ESM-defined receptive language site would have maximized it to 15.90 (95%CI: 9.59-26.33). In summary, naming-related spectral responses predict objectively-measured neuropsychological outcome after epilepsy surgery. We have provided our prediction model as an open-source material, which will indicate the postoperative language function of future patients and facilitate external validation at tertiary epilepsy centers.

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Passive functional mapping of receptive language areas using electrocorticographic signals

Cited by 24 publications

References 47 publications

Multi-modal Mapping of the Face Selective Ventral Temporal Cortex–A Group Study With Clinical Implications for ECS, ECoG, and fMRI

Multi-modal Mapping of the Face Selective Ventral Temporal Cortex–A Group Study With Clinical Implications for ECS, ECoG, and fMRI

The Efficacy of Intraoperative Passive Language Mapping for Glioma Surgery: A Case Report

Naming-related spectral responses predict neuropsychological outcome after epilepsy surgery

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