Neglect is a Spatial Failure of Alerting Mechanisms Required for Awareness: An ERP Study
Bibliographic record
Abstract
In the present study, we describe a group of right brain-damaged (RBD) patients with neglect or extinction, most of them affected in all three (visual, auditory, somatosensory) modalities studied. We applied event-related potential (ERP) analysis to reveal the neural mechanisms underlying hemispatial neglect. ERPs to stimuli of all three modalities were determined for the patients with neglect/extinction at (sub)acute phase, and 3 and 12 months post-stroke. Our results demonstrated that N1 deflections in ERPs, reflecting fronto-parietal alerting mechanisms, wereabsent or diminished/delayed in neglect, and the waves became normalized with recovery from neglect. In somatosensory ERPs, similar changes were evident also in P1 deflections preceding the N1, reflecting activation of the secondary somatosensory cortex (SII).We also demonstrated somatosensory ERPs of some of our patients who showed different responses elicited by low intensity electrical stimulation of the median nerve at the wrist depending on the location of the hands either in uncrossed anatomical position or crossed over the body midline to the other hemispace. Our results indicate that there are cases among patients with hemispatial neglect who do indeed show emergence or increment of responses to left-hand stimulation when the arm is crossed to the right hemispace.Therefore, we propose that the mechanism underlying hemispatial neglect is the disruption of the flow of (location related) sensory information to awareness at the level of multimodal alerting mechanisms.
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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".