Ipsilateral representation of oral structures in human anterior parietal somatosensory cortex and integration of inputs across the midline
Bibliographic record
Abstract
Anterior parietal somatosensory areas 3a, 3b, 1, and 2 generally contain cells with receptive fields that are on the contralateral body. However, inputs from midline structures such as the mouth must be uniquely integrated across the midline. This hypothesis is supported by studies of these fields from nonhuman primates that demonstrate ipsilateral representations of oral structures. We used magnetoencephalography (MEG) to examine the cortical representations of the lips and tongue in humans and to examine the time course of interaction of bilateral inputs from these structures. Ipsilateral activation was observed in response to tactile stimulation of the upper lip in 69% of cases, the lower lip in 85% of cases, and the tongue in 88% of cases. In the contralateral hemisphere, the map of oral structures tended to be in agreement with that from nonhuman primates, although variation was large and source locations were not statistically significantly different from each other. There were no differences in latency of activation for ipsi-vs. contralateral responses (about 30 msec), and cortical sources from ipsi-and contralateral stimulation tended to be located together. Differential activation for bilateral vs. unilateral stimulation occurred later than activation in S1, around 110 msec, and was localized to the upper bank of the Sylvian sulcus. Our findings indicate that, unlike nonhuman primates, humans have an ipsilateral representation of the lips in 3b/1, possibly related to the precise manipulation necessary for the articulation of speech. The distinct pattern of differential activation for uni-vs. bilateral stimulation suggests a unique neural mechanism of integration across the midline for inputs from the mouth.
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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".