Electrocorticographic mapping of expressive language function without requiring the patient to speak: A report of three cases

Spontaneous State Detection Using Time-Frequency and Time-Domain Features Extracted From Stereo-Electroencephalography Traces

As a minimally invasive recording technique, stereo-electroencephalography (SEEG) measures intracranial signals directly by inserting depth electrodes shafts into the human brain, and thus can capture neural activities in both cortical layers and subcortical structures. Despite gradually increasing SEEG-based brain-computer interface (BCI) studies, the features utilized were usually confined to the amplitude of the event-related potential (ERP) or band power, and the decoding capabilities of other time-frequency and time-domain features have not been demonstrated for SEEG recordings yet. In this study, we aimed to verify the validity of time-domain and time-frequency features of SEEG, where classification performances served as evaluating indicators. To do this, using SEEG signals under intermittent auditory stimuli, we extracted features including the average amplitude, root mean square, slope of linear regression, and line-length from the ERP trace and three traces of band power activities (high-gamma, beta, and alpha). These features were used to detect the active state (including activations to two types of names) against the idle state. Results suggested that valid time-domain and time-frequency features distributed across multiple regions, including the temporal lobe, parietal lobe, and deeper structures such as the insula. Among all feature types, the average amplitude, root mean square, and line-length extracted from high-gamma (60–140 Hz) power and the line-length extracted from ERP were the most informative. Using a hidden Markov model (HMM), we could precisely detect the onset and the end of the active state with a sensitivity of 95.7 ± 1.3% and a precision of 91.7 ± 1.6%. The valid features derived from high-gamma power and ERP in this work provided new insights into the feature selection procedure for further SEEG-based BCI applications.

Self-Related Stimuli Decoding With Auditory and Visual Modalities Using Stereo-Electroencephalography

Name recognition plays important role in self-related cognitive processes and also contributes to a variety of clinical applications, such as autism spectrum disorder diagnosis and consciousness disorder analysis. However, most previous name-related studies usually adopted noninvasive EEG or fMRI recordings, which were limited by low spatial resolution and temporal resolution, respectively, and thus millisecond-level response latencies in precise brain regions could not be measured using these noninvasive recordings. By invasive stereo-electroencephalography (SEEG) recordings that have high resolution in both the spatial and temporal domain, the current study distinguished the neural response to one's own name or a stranger's name, and explored common active brain regions in both auditory and visual modalities. The neural activities were classified using spatiotemporal features of high-gamma, beta, and alpha band. Results showed that different names could be decoded using multi-region SEEG signals, and the best classification performance was achieved at high gamma (60–145 Hz) band. In this case, auditory and visual modality-based name classification accuracies were 84.5 ± 8.3 and 79.9 ± 4.6%, respectively. Additionally, some single regions such as the supramarginal gyrus, middle temporal gyrus, and insula could also achieve remarkable accuracies for both modalities, supporting their roles in the processing of self-related information. The average latency of the difference between the two responses in these precise regions was 354 ± 63 and 285 ± 59 ms in the auditory and visual modality, respectively. This study suggested that name recognition was attributed to a distributed brain network, and the subsets with decoding capabilities might be potential implanted regions for awareness detection and cognition evaluation.

Passive functional mapping of receptive language areas using electrocorticographic signals

OBJECTIVE

To validate the use of passive functional mapping using electrocorticographic (ECoG) broadband gamma signals for identifying receptive language cortex.

METHODS

We mapped language function in 23 patients using ECoG and using electrical cortical stimulation (ECS) in a subset of 15 subjects.

RESULTS

The qualitative comparison between cortical sites identified by ECoG and ECS show a high concordance. A quantitative comparison indicates a high level of sensitivity (95%) and a lower level of specificity (59%). Detailed analysis reveals that 82% of all cortical sites identified by ECoG were within one contact of a site identified by ECS.

CONCLUSIONS

These results show that passive functional mapping reliably localizes receptive language areas, and that there is a substantial concordance between the ECoG- and ECS-based methods. They also point to a more refined understanding of the differences between ECoG- and ECS-based mappings. This refined understanding helps to clarify the instances in which the two methods disagree and can explain why neurosurgical practice has established the concept of a "safety margin."

SIGNIFICANCE

Passive functional mapping using ECoG signals provides a fast, robust, and reliable method for identifying receptive language areas without many of the risks and limitations associated with ECS.

Electrical Stimulation Mapping of the Brain: Basic Principles and Emerging Alternatives

The application of electrical stimulation mapping (ESM) of the brain for clinical use is approximating a century. Despite this long-standing history, the value of ESM for guiding surgical resections and sparing eloquent cortex is documented largely by small retrospective studies, and ESM protocols are largely inherited and lack standardization. Although models are imperfect and mechanisms are complex, the probabilistic causality of ESM has guaranteed its perpetuation into the 21st century. At present, electrical stimulation of cortical tissue is being revisited for network connectivity. In addition, noninvasive and passive mapping techniques are rapidly evolving to complement and potentially replace ESM in specific clinical situations. Lesional and epilepsy neurosurgery cases now offer different opportunities for multimodal functional assessments.

Electrocorticographic high-gamma modulation with passive listening paradigm for pediatric extraoperative language mapping

OBJECTIVE

This prospective study compared the topography of high-gamma modulation (HGM) during a story-listening task requiring negligible patient cooperation, with the conventional electrical stimulation mapping (ESM) using a picture-naming task, for presurgical language localization in pediatric drug-resistant epilepsy.

METHODS

Patients undergoing extraoperative monitoring with subdural electrodes were included. Electrocorticographic signals were recorded during quiet baseline and a story-listening task. The likelihood of 70- to 150-Hz power modulation during the listening task relative to the baseline was estimated for each electrode and plotted on a cortical surface model. Sensitivity, specificity, accuracy, and diagnostic odds ratio (DOR) were estimated compared to ESM, using a meta-analytic framework.

RESULTS

Nineteen patients (10 with left hemisphere electrodes) aged 4-19 years were analyzed. HGM during story listening was observed in bilateral posterior superior temporal, angular, supramarginal, and inferior frontal gyri, along with anatomically defined language association areas. Compared to either cognitive or both cognitive and orofacial sensorimotor interference with naming during ESM, left hemisphere HGM showed high specificity (0.82-0.84), good accuracy (0.66-0.70), and DOR of 2.23 and 3.24, respectively. HGM was a better classifier of ESM language sites in the left temporoparietal cortex compared to the frontal lobe. Incorporating visual naming with the story-listening task substantially improved the accuracy (0.80) and DOR (13.61) of HGM mapping, while the high specificity (0.85) was retained. In the right hemisphere, no ESM sites for aphasia were seen, and the results of HGM and ESM comparisons were not significant.

SIGNIFICANCE

HGM associated with story listening is a specific determinant of left hemisphere ESM language sites. It can be used for presurgical language mapping in children who cannot cooperate with conventional language tasks requiring active engagement. Incorporation of additional language tasks, if feasible, can further improve the diagnostic accuracy of language localization with HGM.