Somatosensory deficits and neural correlates in cerebral palsy: a scoping review
Bibliographic record
Abstract
AIM: To synthetize studies assessing somatosensory deficits and alterations in cerebral responses evoked by somatosensory stimulation in individuals with cerebral palsy (CP) compared to typically developing individuals. METHOD: A scoping review of the literature was performed in the MEDLINE, Embase, PsycInfo, CINAHL, Evidence-Based Medicine Reviews, and Web of Science databases (last search carried out on 6th and 7th August 2020) with a combination of keywords related to CP and somatosensory functions. Somatosensory deficits were measured with clinical tests and alterations in cerebral responses were measured with functional magnetic resonance imaging, electroencephalography, and magnetoencephalography. RESULTS: Forty-eight articles were included. Overall, 1463 participants with CP (mean [SD] age 13y 1mo [4y 11mo], range 1-55y; 416 males, 319 females, sex not identified for the remaining participants) and 1478 controls (mean [SD] age 13y 1mo [5y 8mo], range 1-42y; 362 males, 334 females, sex not identified for the remaining participants) were included in the scoping review. For tactile function, most studies reported registration (8 out of 13) or perception (21 out of 21) deficits in participants with CP. For proprioception, most studies also reported registration (6 out of 8) or perception (10 out of 15) deficits. Pain function has not been studied as much, but most studies reported registration (2 out of 3) or perception (3 out of 3) alterations. Neuroimaging findings (18 studies) showed alterations in the somatotopy, morphology, latency, or amplitude of cortical responses evoked by somatosensory stimuli. INTERPRETATION: Despite the heterogeneity in the methods employed, most studies reported somatosensory deficits. The focus has been mainly on tactile and proprioceptive function, whereas pain has received little attention. Future research should rigorously define the methods employed and include a sample that is more representative of the population with CP. What this paper adds Most of the papers reviewed found tactile registration and perception deficits in the upper limbs. Proprioceptive deficits were generally observed in cerebral palsy but results were heterogeneous. Pain has received little attention compared to tactile and proprioceptive functions. Neuroimaging studies supported behavioral observations. Alterations were observed for both the most and least affected limb.
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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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.024 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".