Method Matters: An Empirical Study of Impact in Cognitive Neuroscience
Bibliographic record
Abstract
A major thrust of cognitive neuroscience is the elucidation of structure-function relationships in the human brain. Over the last several years, functional neuroimaging has risen in prominence relative to the lesion studies that formed the historical core of work in this field. These two methods have different strengths and weaknesses. Among these is a crucial difference in the nature of evidence each can provide. Lesion studies can provide evidence for necessity claims, whereas functional neuroimaging studies do not. We hypothesized that lesion studies will continue to have greater scientific impact even as the relative proportion of such studies in the cognitive neuroscience literature declines. Using methods drawn from systematic literature review, we identified a set of original cognitive neuroscience articles that employed either functional imaging or lesion techniques, published at one of two time points in the 1990s, and assessed the effect of the method used on each article's impact across the decade. Functional neuroimaging studies were cited three times more often than lesion studies throughout the time span we examined. This effect was in large part due to differences in the influence of the journals publishing the two methods; functional neuroimaging studies appeared disproportionately more often in higher impact journals. There were also differences in the degree to which articles using one method cited articles using the other method. Functional neuroimaging articles were less likely to include such cross-method citations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".