Size of the spatial correlation between ECoG and fMRI activity

Area of Science:

• Neuroscience
• Biomedical Engineering
• Cognitive Science

Background:

• Electrocorticography (ECoG) precisely localizes brain activity and functions for epilepsy surgery.
• Functional MRI (fMRI) measures blood-oxygen-level-dependent (BOLD) signals to map cognitive functions.
• Integrating ECoG and fMRI offers insights into the spatiotemporal dynamics of cognition.

Purpose of the Study:

• To determine the optimal spatial smoothing kernel width for integrating ECoG and 3T fMRI data.
• To investigate the spatial characteristics of the BOLD signal in relation to ECoG recordings.
• To guide future multimodal neuroimaging studies by providing data-driven kernel width recommendations.

Main Methods:

• ECoG high-frequency broadband (HFB) activity was recorded during a motor task, serving as ground truth.
• 3T fMRI data for the same task was acquired from the same participants prior to surgery.
• A 3D Gaussian kernel of varying widths (1-20 mm) was applied to fMRI maps to correlate with ECoG HFB power.

Main Results:

• Maximal spatial specificity between ECoG and fMRI BOLD signals was achieved with a 4 mm kernel width.
• Highest explained variance was observed at a 9 mm kernel width, indicating a trade-off between specificity and variance explained.
• Lower frequency bands (alpha, beta) showed maximal specificity at 4 mm but greater spatial extent for explained variance compared to HFB.

Conclusions:

• Spatial specificity in multimodal ECoG-fMRI integration is limited to approximately 4 mm.
• Maximizing explained variance requires larger kernel widths (e.g., 9 mm), sacrificing spatial precision.
• Researchers should select kernel width based on specific research objectives: 4 mm for maximal specificity, larger widths for optimal correlation.