Distinct connectivity patterns in human medial parietal cortices: Evidence from standardized connectivity map using cortico-cortical evoked potential
Bibliographic record
Abstract
The medial parietal cortices are components of the default mode network (DMN), which are active in the resting state. The medial parietal cortices include the precuneus and the dorsal posterior cingulate cortex (dPCC). Few studies have mentioned differences in the connectivity in the medial parietal cortices, and these differences have not yet been precisely elucidated. Electrophysiological connectivity is essential for understanding cortical function or functional differences. Since little is known about electrophysiological connections from the medial parietal cortices in humans, we evaluated distinct connectivity patterns in the medial parietal cortices by constructing a standardized connectivity map using cortico-cortical evoked potential (CCEP). This study included nine patients with partial epilepsy or a brain tumor who underwent chronic intracranial electrode placement covering the medial parietal cortices. Single-pulse electrical stimuli were delivered to the medial parietal cortices (38 pairs of electrodes). Responses were standardized using the z-score of the baseline activity, and a response density map was constructed in the Montreal Neurological Institutes (MNI) space. The precuneus tended to connect with the inferior parietal lobule (IPL), the occipital cortex, superior parietal lobule (SPL), and the dorsal premotor area (PMd) (the four most active regions, in descending order), while the dPCC tended to connect to the middle cingulate cortex, SPL, precuneus, and IPL. The connectivity pattern differs significantly between the precuneus and dPCC stimulation (p<0.05). Regarding each part of the medial parietal cortices, the distributions of parts of CCEP responses resembled those of the functional connectivity database. Based on how the dPCC was connected to the medial frontal area, SPL, and IPL, its connectivity pattern could not be explained by DMN alone, but suggested a mixture of DMN and the frontoparietal cognitive network. These findings improve our understanding of the connectivity profile within the medial parietal cortices. The electrophysiological connectivity is the basis of propagation of electrical activities in patients with epilepsy. In addition, it helps us to better understand the epileptic network arising from the medial parietal cortices.
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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 | 0.001 | 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) | 0.001 | 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".