Electrocorticographic high gamma language mapping: Mind the pitfalls of comparison with electrocortical stimulation

Combining Gamma With Alpha and Beta Power Modulation for Enhanced Cortical Mapping in Patients With Focal Epilepsy

About one third of patients with epilepsy have seizures refractory to the medical treatment. Electrical stimulation mapping (ESM) is the gold standard for the identification of “eloquent” areas prior to resection of epileptogenic tissue. However, it is time-consuming and may cause undesired side effects. Broadband gamma activity (55–200 Hz) recorded with extraoperative electrocorticography (ECoG) during cognitive tasks may be an alternative to ESM but until now has not proven of definitive clinical value. Considering their role in cognition, the alpha (8–12 Hz) and beta (15–25 Hz) bands could further improve the identification of eloquent cortex. We compared gamma, alpha and beta activity, and their combinations for the identification of eloquent cortical areas defined by ESM. Ten patients with intractable focal epilepsy (age: 35.9 ± 9.1 years, range: 22–48, 8 females, 9 right handed) participated in a delayed-match-to-sample task, where syllable sounds were compared to visually presented letters. We used a generalized linear model (GLM) approach to find the optimal weighting of each band for predicting ESM-defined categories and estimated the diagnostic ability by calculating the area under the receiver operating characteristic (ROC) curve. Gamma activity increased more in eloquent than in non-eloquent areas, whereas alpha and beta power decreased more in eloquent areas. Diagnostic ability of each band was close to 0.7 for all bands but depended on multiple factors including the time period of the cognitive task, the location of the electrodes and the patient’s degree of attention to the stimulus. We show that diagnostic ability can be increased by 3–5% by combining gamma and alpha and by 7.5–11% when gamma and beta were combined. We then show how ECoG power modulation from cognitive testing can be used to map the probability of eloquence in individual patients and how this probability map can be used in clinical settings to optimize ESM planning. We conclude that the combination of gamma and beta power modulation during cognitive testing can contribute to the identification of eloquent areas prior to ESM in patients with refractory focal epilepsy.

Dynamic tractography: Integrating cortico-cortical evoked potentials and diffusion imaging

INTRODUCTION

Cortico-cortical evoked potentials (CCEPs) are utilized to identify effective networks in the human brain. Following single-pulse electrical stimulation of cortical electrodes, evoked responses are recorded from distant cortical areas. A negative deflection (N1) which occurs 10-50 ​ms post-stimulus is considered to be a marker for direct cortico-cortical connectivity. However, with CCEPs alone it is not possible to observe the white matter pathways that conduct the signal or accurately predict N1 amplitude and latency at downstream recoding sites. Here, we develop a new approach, termed "dynamic tractography," which integrates CCEP data with diffusion-weighted imaging (DWI) data collected from the same patients. This innovative method allows greater insights into cortico-cortical networks than provided by each method alone and may improve the understanding of large-scale networks that support cognitive functions. The dynamic tractography model produces several fundamental hypotheses which we investigate: 1) DWI-based pathlength predicts N1 latency; 2) DWI-based pathlength negatively predicts N1 voltage; and 3) fractional anisotropy (FA) along the white matter path predicts N1 propagation velocity.

METHODS

Twenty-three neurosurgical patients with drug-resistant epilepsy underwent both extraoperative CCEP recordings and preoperative DWI scans. Subdural grids of 3 ​mm diameter electrodes were used for stimulation and recording, with 98-128 eligible electrodes per patient. CCEPs were elicited by trains of 1 ​Hz stimuli with an intensity of 5 ​mA and recorded at a sample rate of 1 ​kHz. N1 peak and latency were defined as the maximum of a negative deflection within 10-50 ​ms post-stimulus with a z-score > 5 relative to baseline. Electrodes and DWI were coregistered to construct electrode connectomes for white matter quantification.

RESULTS

Clinical variables (age, sex, number of anti-epileptic drugs, handedness, and stimulated hemisphere) did not correlate with the key outcome measures (N1 peak amplitude, latency, velocity, or DWI pathlength). All subjects and electrodes were therefore pooled into a group-level analysis to determine overall patterns. As hypothesized, DWI path length positively predicted N1 latency (R² ​= ​0.81, β ​= ​1.51, p ​= ​4.76e-16) and negatively predicted N1 voltage (R² ​= ​0.79, β ​= ​-0.094, p ​= ​9.30e-15), while FA predicted N1 propagation velocity (R² ​= ​0.35, β ​= ​48.0, p ​= ​0.001).

CONCLUSION

We have demonstrated that the strength and timing of the CCEP N1 is dependent on the properties of the underlying white matter network. Integrated CCEP and DWI visualization allows robust localization of intact axonal pathways which effectively interconnect eloquent cortex.