Is the Link between Anatomical Structure and Function Equally Strong at All Cognitive Levels of Processing?
Bibliographic record
Abstract
Whereas low-level sensory processes can be linked to macroanatomy with great confidence, the degree to which high-level cognitive processes map onto anatomy is less clear. If function respects anatomy, more accurate intersubject anatomical registration should result in better functional alignment. Here, we use auditory functional magnetic resonance imaging and compare the effectiveness of affine and nonlinear registration methods for aligning anatomy and functional activation across subjects. Anatomical alignment was measured using normalized cross-correlation within functionally defined regions of interest. Functional overlap was assessed using t-statistics from the group analyses and the degree to which group statistics predict high and consistent signal change in individual data sets. In regions related to early stages of auditory processing, nonlinear registration resulted in more accurate anatomical registration and stronger functional overlap among subjects compared with affine. In frontal and temporal areas reflecting high-level processing of linguistic meaning, nonlinear registration also improved the accuracy of anatomical registration. However, functional overlap across subjects was not enhanced in these regions. Therefore, functional organization, relative to anatomy, is more variable in the frontal and temporal areas supporting meaning-based processes than in areas devoted to sensory/perceptual auditory processing. This demonstrates for the first time that functional variability increases systematically between regions supporting lower and higher cognitive processes.
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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".