A neural index of inefficient evidence accumulation in dyslexia underlying slow perceptual decision making
Bibliographic record
Abstract
Visual processing deficits have been widely reported in developmental dyslexia however the locus of cognitive dysfunction remains unclear. Here, we examined the neural correlates of perceptual decision-making using a dot-motion task and electroencephalography (EEG) and investigated whether presenting deficits were unique to children with dyslexia or if they were also evident in other, typically developing children with equally immature reading systems. Sixty-eight children participated: 32 with dyslexia (DD; 16 females); 21 age-matched controls (AM; 11 females) and 15 reading-matched controls (RM; 9 females). All participants completed a bilaterally presented random-dot-motion task while EEG was recorded. Neural signatures of low level sensory processing (steady state visual evoked potentials; SSVEPs), pre-target attentional bias (posterior α power), attentional orienting (N2), evidence accumulation (centro-parietal positive decision signal; CPP) and execution of a motor response (β) were obtained to dissect the temporal sequence of perceptual decision-making. Reading profile provided a score of relative lexical and sublexical skills for each participant. Although all groups performed comparably in terms of task accuracy and false alarm rate, the DD group were slower and demonstrated an earlier peak latency, reduced slope and lower amplitude of the CPP compared with both AM and RM controls. Reading profile was found to moderate the relationship between word reading ability, reaction time as well as CPP indices showing that lexical dyslexics responded more slowly and had a shallower slope, reduced amplitude and earlier latency of CPP waveforms than sublexical dyslexics. These findings suggest that children with dyslexia, particularly those with relatively poorer lexical abilities, have a reduced rate and peak of evidence accumulation as denoted by CPP markers yet remain slow in their overt response. This is in keeping with hypotheses that children with dyslexia have impairment in effectively sampling and processing evidence about visual motion stimuli.
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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".