A High-Resolution Anisotropic Finite-Volume Head Model for EEG Source Analysis
Bibliographic record
Abstract
Solution of the electroencephalogram (EEG) forward problem in a realistic head model is necessary for accurate source analysis. Realistic head models are usually derived from volumetric magnetic resonance images that provide a voxel resolution of about 1 mm3. The availability of an electrical head model with this resolution would therefore be extremely advantageous. Head models with resolution in the millimeter range that incorporate the anisotropic properties of their elements have been formulated with the finite element method (FEM). However, these FEM models are fraught with complications related to irregular grids and meshes, along with the incumbent segmentation problems. Presented here is a finite volume method (FVM) formulation of the realistic head model in cubic elements that can ameliorate some of these problems, can incorporate tissue anisotropy, and is both physically intuitive and simple to implement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".