Event-Related Potentials Study of Cognitive Functions in Patients with Post-Stroke Cognitive Impairment
Bibliographic record
Abstract
ObjectivePost-stroke cognitive impairment （PSCI） is a common syndrome associated with cerebral stroke，and there is a significant lack of objective cognitive assessment methods clinically for PSCI. This study aims to investigate the correlation between different electrode P300 latencies and cognitive functions in patients with PSCI，to provide experimental support for using P300 as an objective index in cognitive function assessment.MethodsThis study included 46 patients diagnosed with post-stroke cognitive impairment from May to August 2023 at the Rehabilitation Hospital affiliated with Fujian University of Traditional Chinese Medicine，along with 20 control subjects. The control group underwent the MoCA assessment. Participants in the PSCI group underwent neuropsychological tests：MoCA，Trail Making Test A （TMT-A），Trail Making Test B （TMT-B），Rivermead Behavioral Memory Test （RBMT-II），and Rey-Osterrieth Complex Figure Test （ROCFT）. All patients and control subjects completed the event-related potential P300 assessment.ResultsCompared with the control group，participants in the PSCI group had significantly longer P300 latencies at nine electrodes （Fz，Cz，Pz，F3，C3，P3，F4，C4，and P4） （P < 0. 001）. ROC analysis showed that the latencies of P300-Cz and P300-Pz were strongly correlated with predicting overall cognitive function in PSCI （AUC > 0. 7）. In the analysis of specific cognitive domains，we found that P300-Pz and P300-P4 latencies were highly correlated with visuospatial/executive functions，P300-Pz latency with orientation，P300-Fz latency with attention，and latencies at Cz，Pz，and P4 with memory function （P < 0. 01）.ConclusionThe prolongation of the P300 latency in PSCI patients is correlated with cognitive dysfunction. The P300 latencies at electrodes Fz，Cz，Pz，and P4 may serve as predictive indicators for overall cognitive function，visuospatial/executive abilities，orientation，attention，and memory. These results further expand the assessment tools for cognitive functions in patients with PSCI.
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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 | 0.001 |
| 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".