Fast presurgical functional mapping using task-related intracranial high gamma activity

Abstract

Object: Electrocorticography (ECoG) is a powerful tool for presurgical functional mapping. Power increase in the high gamma band has been observed from ECoG electrodes on the surface of the sensory motor cortex during the execution of body movements. In this study the authors aim to validate the clinical usage of high gamma activity in presurgical mapping by comparing ECoG mapping with traditional direct electrical cortical stimulation (ECS) and functional MRI (fMRI) mapping.

Methods: Seventeen patients with epilepsy participated in an ECoG motor mapping experiment. The patients executed a 5-minute hand/tongue movement task while the ECoG signal was recorded. All 17 patients also underwent extraoperative ECS mapping to localize the motor cortex. Eight patients also participated in a presurgical fMRI study. The high gamma activity on ECoG was modeled using the general linear model (GLM), and the regions showing significant gamma power increase during the task condition compared with the rest condition were localized. The maps derived from GLM-based ECoG mapping, ECS, and fMRI were then compared.

Results: High gamma activity in the motor cortex can be reliably modulated by motor tasks. Localization of the motor regions achieved with GLM-based ECoG mapping was consistent with the localization determined by ECS. The maps also appeared to be highly localized compared with the fMRI activations. Using the ECS findings as the reference, GLM-based ECoG mapping showed a significantly higher sensitivity than fMRI (66.7% for ECoG, 52.6% for fMRI, p<0.05), while the specificity was high for both techniques (>97%). If the current-spreading effect in ECS is accounted for, ECoG mapping may produce maps almost identical to those produced by ECS mapping (100% sensitivity and 99.5% specificity).

Conclusions: General linear model-based ECoG mapping showed a superior performance compared to traditional ECS and fMRI mapping in terms of efficiency and accuracy. Using this method, motor functions can be reliably mapped in less than 5 minutes.

Fig. 1

Left: Schematic diagram of the experimental setup. Surgical patients with implanted subdural electrodes performed hand or tongue movement tasks in 20-second blocks interleaved with 8-second rest blocks. The type of movement (hand or tongue) was indicated by a visual cue displayed on the screen throughout the block. In each task block, the patient grasped the hand contralateral to the side of electrode implantation, or stuck out his tongue immediately following an auditory cue (duration 0.2 seconds, average interstimulus interval 4 seconds). Each block involved only one type of movement. Right: The GLM design matrix. The upper 2 plots show the contrast vectors of the hand and tongue movement tasks. The lower graph depicts the design matrix, with each row corresponding to one sample point of the ECoG. The full design matrix contains 4 columns. The first 2 columns represent the hand and tongue movement; the third column represents the rest condition, and the fourth is the constant. The 2 task columns were obtained by replacing the first 3 seconds of each trial with a high gamma response template. s = seconds.

Fig. 2

Left: The relative power (task/rest) of the ECoG signal recorded from the representative electrode during movement (from 0.3 to 1.3 seconds after the auditory cue onset). The representative electrode was chosen if the patient showed or reported symptoms related to the sensory motor cortex when stimulated with the minimum current intensity during the ECS test. The blue curve represents the relative power spectra averaged across all 17 patients. The movement task induced a significant power increase in the high gamma band but a decrease in the alpha (8–13 Hz) and beta (15–30 Hz) bands. The power in the low gamma band did not show any significant change. Right: The time-frequency plane was divided into small time-frequency bins (each bin is 15 msec ×1 Hz). The power spectra in the time-frequency bins showing significant task versus rest difference were averaged across all subjects. The modulation effect of the movement tasks was clearly demonstrated in the high gamma band and some of the low-frequency bands.

Fig. 3

Hand and tongue motor areas localized by ECS, ECoG, and fMRI. The mapping results were projected to each individual’s brain surface reconstructed from the T1-weighted MR images. Each row represents the results obtained in 1 patient. The number on the left is the case number as shown in Table 1. The left 3 columns illustrate the hand motor regions mapped by ECS, ECoG, and fMRI, respectively. The right 3 columns are the maps of the tongue motor regions. The blue dots in the ECS maps indicate negative electrodes (no symptoms related to sensory motor cortex reported when stimulated) and the yellow dots indicate positive electrodes. The ECoG results were the t-values of all electrodes determined by the GLM rendered on the cortical surface. The fMRI activation maps were also the t-values determined by the GLM. The ECoG maps were highly consistent with the ECS findings and were more localized than fMRI results.

Fig. 4

Overall sensitivity and specificity of ECoG and fMRI mapping. To determine the sensitivity and specificity, ECS results were used as the reference. The sensitivity and specificity in each patient are listed in Table 2. The overall percentage is computed as the total number of electrodes belonging to A, B, C, or D conditions (defined in Table 2) over all tasks and patients (17 patients for ECoG, 8 patients for fMRI). Compared with fMRI, ECoG mapping results are significantly more consistent with the ECS findings. *p < 0.05, paired t-test.

Fig. 5

A: A high gamma response template was obtained by averaging the single-trial gamma-band activity. The blue curves are the fitted gamma functions of single trials recorded from the representative electrodes. The black curve is the high gamma response template derived from averaging the blue curves. B: The gamma band was separated into multiple subbands, and the mean power in these subbands was averaged across all trials/tasks/subjects. For each trial, the mean power during the time window of 0–2 seconds was calculated. Compared with other subbands, the 60-to 90-Hz band has the highest power during movement tasks. C: The broadband (30-Hz bin) high gamma envelope has a greater signal-to-noise ratio than the narrow band (10-Hz bin). The broadband high gamma activity, especially between 60 and 90 Hz, has a greater t-statistic value than the other subbands within the same ECoG data set. D: Using the gamma template, fewer trials are needed to achieve the same performance than when the square template or the peak template are used. On average, the gamma template needs 20 trials, the square template needs 50 trials, and the peak template needs 29 trials for the same performance. SNR = signal-to-noise ratio. Patient ID = case number (Table 1).