Parcellating the vertical associative fiber network of the temporoparietal area: Evidence from focused anatomic fiber dissections
Bibliographic record
Abstract
Introduction: The connectivity of the temporoparietal (TP) region has been the subject of multiple anatomical and functional studies. Its role in high cognitive functions has been primarily correlated with long association fiber connections. As a major sensory integration hub, coactivation of areas within the TP requires a stream of short association fibers running between its subregions. The latter have been the subject of a small number of recent in vivo and cadaveric studies. This has resulted in limited understanding of this network and, in certain occasions, terminology ambiguity. Research question: To systematically study the vertical parietal and temporoparietal short association fibers. Material and methods: Thirteen normal, adult cadaveric hemispheres, were treated with the Klinger's freeze-thaw process and their subcortical anatomy was studied using the microdissection technique. Results: Two separate fiber layers were identified. Superficially, directly beneath the cortical u-fibers, the Stratum proprium intraparietalis (SP) was seen connecting Superior Parietal lobule and Precuneal cortical areas to inferior cortical regions of the Parietal lobe, running deep to the Intraparietal sulcus. At the same dissection level, the IPL-TP fibers were identified as a bundle connecting the Inferior Parietal lobule with posterior Temporal cortical areas. At a deeper level, parallel to the Arcuate fasciculus fibers, the SPL-TP fibers were seen connecting the Superior Parietal lobule to posterior Temporal cortical areas. Discussion and conclusion: To our knowledge this is the first cadaveric dissection study to comprehensively study and describe of the vertical association fibers of the temporoparietal region while proposing a universal terminology.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".