Visual and Auditory fMRI Paradigms for Presurgical Language Mapping: Convergent Validity and Relationship to Individual Variables
Bibliographic record
Abstract
Functional MRI (fMRI) has emerged as a safe alternative to invasive procedures for determining hemispheric language dominance prior to neurosurgery. Despite this, there are currently no standardized fMRI protocols that have been explored in healthy controls to determine the influence of individual patient variables on the results, which poses challenges in clinical interpretation of ambiguous findings in patient populations. In addition, most fMRI protocols are not suitable for individuals with visual or intellectual disabilities (IQ<70). In the current study, 61 healthy adults (ages: 18-74 years) completed two fMRI paradigms for language mapping. One paradigm used visually based stimuli and has shown good face validity to date in our center. The second paradigm used auditory stimuli presented at slowed speed and was designed for individuals with visual or cognitive dysfunction but has not yet been used clinically. The paradigms demonstrated 97% agreement in classifying individuals as left-hemisphere, right-hemisphere, and bilaterally dominant. Cases that were classified differently showed bilateral dominance in response to either paradigm. Dominance classification rates for right- and left-handed individuals were largely in keeping with published data. Within the left-handed group, IQ and education were positively correlated with laterality indices generated by both paradigms (r values range: 0.44-0.95, p<0.01), suggesting that individuals with higher IQ and formal education were more likely to be classified as left-hemisphere dominant in the current sample. This study will help improve clinical interpretation of language fMRI maps by identifying factors that might impact results (like IQ). It also offers an alternative paradigm to make this procedure more accessible to a broader range of patients. Future studies will replicate results with a sample of patients with epilepsy across a broad range of intellectual abilities.
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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 | 0.001 | 0.007 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".