From acute neglect to chronic constructional deficits: parietotemporal contributions to long-term post-stroke impairments
Bibliographic record
Abstract
Patients with acute hemispheric stroke exhibit various visuospatial impairments. While many recover rapidly, others remain impaired. Better defining which symptoms characterize the acute and chronic phases and which brain areas and connections are implicated could help to improve diagnostic and rehabilitation tools and inform effective rehabilitation strategies. Here, we report a systematic anatomo-functional study of two populations of acute and chronic hemispheric stroke patients (cross-sectional design). Patients were examined by a series of neuropsychological tests assessing different post-stroke clinical manifestations in the visuospatial domain. We first performed a statistical factorial analysis of patients' behavioural performance across tests to break down symptoms into coherent profiles of co-varying deficits and determine whether any factors may be specific to each post-stroke phase. We then conducted voxel- and atlas-based lesion-symptom mapping, as well as disconnection-symptom mapping in the two populations. We found different patterns of behavioural impairment across groups, with acute symptoms mostly characterized by lateralized attentional deficits and chronic symptoms manifesting as constructional spatial impairments. Lesions to and/or disconnections of frontal and precentral gyri correlated with lateralized visuospatial symptoms in the acute but not chronic phase, whereas lesions to and/or disconnections of temporoparietal areas correlated with constructional deficits in the chronic phase. Our results indicate that constructional spatial deficits and damage/disconnection of dorsoventral higher-order visual areas most pervasively impair stroke patients in the long term. Such deficits might be overlooked or disregarded by rehabilitation strategies focusing on the (mainly acute) lateralized component of their visuospatial deficits and ignoring concomitant, more object-based deficits. This work may help design more specific diagnostic tests and guide future rehabilitation strategies, ultimately promoting better and more extensive recovery beyond lateralized deficits in attention and spatial awareness.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".