Replication of The advantage of combining MEG and EEG: comparison to fMRI in focally-stimulated visual cortex by Sharon et al. (2007, Neuroimage)

Author

Qiyuan Feng (qyfeng@stanford.edu)

Published

October 27, 2025

Repository link: GitHub repo Original paper (PDF in repo): sharon2007.pdf

Introduction

Justification

I study visual perception using different neuroimaging techniques, including EEG/MEG and fMRI. I’m particularly interested in finding out how well we can localize signals across modalities. This original paper reports that combining EEG and MEG can approach the spatial resolution of fMRI when localizing signals in primary visual cortex (V1). This is significant for vision research: if we can get fMRI-like localization without scanning every time, we can run more flexible studies while keeping spatial accuracy in check. I will replicate the core idea on the EEG side, using the same two visual stimuli at 5° eccentricity in the left visual field that the original paper used. Using each subject’s pRF maps and structural MRI-based head models as “ground truth”, I will quantify localization error of EEG source estimates and compare it to the paper’s reported error profiles.

Stimuli and Procedures

Stimuli will be two small patches presented at 5° eccentricity in the left visual field (same positions as two of the original paper’s four stimuli), designed to drive a circumscribed patch of right-hemisphere early visual cortex (V1). Each patch will be a high-contrast checkerboard (size ~1–2°; exact size matched to our lab’s display geometry), contrast-reversing at a steady rate to boost SSVEP SNR. Subjects fixate centrally with a fixation marker; brief attention checks (e.g., infrequent color change at fixation) help maintain fixation. Each stimulus position will be run in multiple short blocks to collect adequate trials for frequency-domain averaging.

For “ground truth,” I will use each subject’s pRF maps and cortical surfaces from T1 MRI to define the expected cortical locus (and extent) representing each 5° stimulus. For EEG, I will use each subject’s MRI to build a BEM head model, co-register electrodes to the scalp, and compute forward models. I will estimate sources with a standard inverse (e.g., depth-weighted MNE/dSPM or an LCMV beamformer with appropriate regularization). Localization error will be computed as the cortical (geodesic) distance between the EEG peak (or center-of-mass above a fixed threshold) and the pRF-defined target vertex/ROI. I will summarize error per stimulus and per subject, plus uncertainty via bootstrap over epochs.

Potential Challenges

  • Retinotopic variability: the same 5° polar-angle location can fall on gyral vs. sulcal cortex across people; sources buried in a sulcus have weaker EEG fields, inflating error.
  • Ground-truth alignment: pRF maps have their own uncertainty (fit noise, attention/fixation drift). I will propagate pRF ROI uncertainty when scoring error (e.g., distance to the nearest vertex within the pRF ROI).
  • Head model/inverse sensitivity: localization is sensitive to BEM accuracy, conductivity assumptions, coregistration error, inverse depth weighting, and regularization. I will fix parameters a priori and report sensitivity analyses (e.g., ±10% regularization, with/without depth weighting).
  • SNR and sample size: with few subjects, variance will be high. I will maximize SNR (SSVEP averaging, artifact rejection/ICA, notch and band-pass) and report per-subject results plus group medians rather than rely only on NHST.

Methods

Power Analysis

The original study by Sharon et al. (2007) included six participants, each completing four scanning sessions (MEG/EEG, fMRI, retinotopy, and structural MRI). They reported statistically reliable localization differences across modalities (EEG vs MEG vs combined), with effect sizes corresponding to localization-error differences of ~8 mm ± 1 mm between conditions. Based on this magnitude, a power analysis (Cohen’s d ≈ 1.0) indicates that n = 7 yields ~80 % power, n = 9 ~90 %, and n = 11 ~95 % power for within-subject paired comparisons (α = .05, two-tailed).

Planned Sample

We plan to include 6 adult participants (ages 25–35) recruited from the Stanford University community (students, faculty, and staff).

  • Inclusion criteria: normal or corrected-to-normal vision; no neurological or psychiatric disorders; availability of a high-quality T1-weighted MRI scan.
  • Exclusion criteria: none beyond standard EEG contraindications (e.g., skin irritation, implanted metal).Only individuals with an existing MRI are included for budget and modeling reasons. No pre-selection based on handedness or eye dominance is used.

Materials

“A single 100 % contrast Gabor patch was presented in one of four locations (upper or lower visual quadrant, at 5 or 10 degrees eccentricity) for 500 ms while the subject fixated a central fixation cross. A blank condition (gray except for the fixation cross) was additionally presented… Each arm of the fixation cross was 0.17° long… The gray level of the background was equivalent to the mean of the Gabor patches. The carrier spatial frequency of the Gabor patch was 2 cycles/degree, and the Gaussian full-width at half-maximum was 1.2° and 1.7° for the 5° and 10° eccentricity stimuli, respectively.”

All stimuli in our replication will closely follow these parameters except for two planned modifications:

  1. We will use three flickering stimuli instead of four static ones, employing frequency tagging (steady-state visual evoked potentials, SSVEP) to increase SNR.

  2. Each stimulus will be a contrast-reversing checkerboard at distinct temporal frequencies (5, 6, 7.5 Hz).

The stimuli will be positioned as follows: - Two patches at 5° eccentricity in the upper-left and lower-left quadrants (polar angles ≈ 45° and 135°). - One patch at 2° eccentricity on the left horizontal meridian (near central vision). This arrangement allows simultaneous frequency-specific tagging of multiple visual field locations within hardware refresh constraints (60 Hz monitor; each frequency synchronized to integer frame durations).

Procedure

“In both fMRI and MEG/EEG sessions, a single 100 % contrast Gabor patch was presented in one of four locations for 500 ms while the subject fixated a central fixation cross… One arm of the fixation cross disappeared for 33 ms as soon as the stimulus epoch ended, and the subject indicated by button-press whether it was the upper or lower arm. Incorrect or missed trials were discarded. The inter-stimulus interval was randomized between 1–6.5 s… Each session included 20 scans of 4:16 minutes, for a total of 500 repetitions per condition.”

In our EEG-only replication, each stimulus frequency will be presented continuously in 10 s blocks, alternating between the three stimulus locations. Participants will maintain fixation on the central cross and perform a simple letter-change detection task at fixation to ensure stable gaze. Each frequency condition will include 40 blocks per subject, giving ~10-12 minutes total per frequency. EEG will be recorded at 128 channels using the same montage across participants, with EOG monitoring for eye artifacts.

Analysis Plan

“MEG/EEG data were analyzed using the MNE software… low-pass filtered at 200 Hz… noisy channels identified by inspection and ignored… forward solution constructed using a three-layer BEM (conductivities = 0.3, 0.006, 0.3 S/m). The data and forward matrix were whitened using the noise covariance matrix… Anatomically constrained inverse solutions (dSPM and depth-weighted MNE) were computed with a loose orientation constraint of 0.6… Localization error was defined as the 3D distance between the EEG/MEG V1 peak and the fMRI V1 peak.”

Our analysis follows the same procedure:

  1. Preprocessing: band-pass (1–40 Hz), notch filter at 60 Hz, ICA for eye/blink artifacts.
  2. Frequency-domain extraction: Fourier transform of each block; extract complex coefficients at 5, 6, 7.5 Hz.
  3. Source estimation: use subject-specific BEM head model and structural MRI for forward modeling. Apply dSPM and depth-weighted MNE to obtain complex-valued source estimates per frequency.
  4. Ground truth: use pRF-based retinotopic maps from each subject’s fMRI to define the expected cortical ROI (analogous to Sharon’s V1 ROI).
  5. Localization error: compute geodesic distance between the maximum (or center of mass) of EEG power at each frequency and the expected V1 ROI center.
  6. Statistical comparison: bootstrap within-subject error distribution; report median error per frequency.

Clarify key analysis of interest here

Differences from Original Study

Compared with Sharon et al. (2007):

  • Modalities: we use EEG only, not MEG/EEG simultaneous recording. This will correspond to only the first part of Sharon et al.(2007)’s study, where they compare EEG to the ground-truth fMRI.

  • Stimuli: instead of transient 500 ms flashes, we use continuous frequency-tagged stimuli (5, 6, and 7.5 Hz) to improve SNR and allow simultaneous multi-location stimulation for budget consideration.

  • Timing: Sharon used ~500 ms trials with randomized ISI; we use 10s SSVEP blocks with continuous presentation.

  • Session duration: shorter overall session (originally 1 hour total recording per subject; now ~12min per subject).

  • Ground truth: instead of fMRI recorded in the same session, we use pRF maps from prior scans as a reference.

  • Expected impact: frequency tagging yields higher SNR and more stable phase estimates but sacrifices precise transient timing. The change from transient to steady-state stimulation should not alter the spatial pattern of V1 activation but may slightly broaden cortical response spread due to temporal integration.

Methods Addendum (Post Data Collection)

You can comment this section out prior to final report with data collection.

Actual Sample

Sample size, demographics, data exclusions based on rules spelled out in analysis plan

Differences from pre-data collection methods plan

Any differences from what was described as the original plan, or “none”.

Results

Data preparation

Data preparation following the analysis plan.

Confirmatory analysis

The analyses as specified in the analysis plan.

Side-by-side graph with original graph is ideal here

Exploratory analyses

Any follow-up analyses desired (not required).

Discussion

Summary of Replication Attempt

Open the discussion section with a paragraph summarizing the primary result from the confirmatory analysis and the assessment of whether it replicated, partially replicated, or failed to replicate the original result.

Commentary

Add open-ended commentary (if any) reflecting (a) insights from follow-up exploratory analysis, (b) assessment of the meaning of the replication (or not) - e.g., for a failure to replicate, are the differences between original and present study ones that definitely, plausibly, or are unlikely to have been moderators of the result, and (c) discussion of any objections or challenges raised by the current and original authors about the replication attempt. None of these need to be long.