GABA-ergic inhibition in human MT predicts visuo-spatial intelligence mediated by reverberation with frontal cortex
Bibliographic record
Abstract
Abstract The canonical theory emphasizes fronto-parietal network (FPN) is key in mediating general fluid intelligence (gF). Meanwhile, recent studies show that multiple sensory regions in occipito-temporal border also play a key role in gF. However, the underlying mechanism is not yet clear. To investigate this issue, this study selects human MT complex (MT+), a region locates at the occipito-temporal border representing multiple sensory flows as a target brain area. Using ultra-high field magnetic resonance spectroscopy (MRS) to measure GABA/glutamate concentrations in MT+ combining resting-state fMRI functional connectivity (FC), behavioral examinations including MT+ perception suppression test and gF subtest in visuo-spatial component, we reveal that MT+ GABA and frontal-MT+ FC significantly correlate with the performance of visuo-spatial intelligence. Further, serial mediation model demonstrates that MT+ GABA predicting visuo-spatial gF fully mediated by reverberation effect between frontal and MT+ network. Our finding highlights that sensory cortex could integrate into complex cognition system as an intellectual hub.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".