Early life stress, literacy and dyslexia: an evolutionary perspective
Bibliographic record
Abstract
Stress and learning co-evolved in parallel, with their interdependence critical to the survival of the species. Even today, the regulation of moderate levels of stress by the central autonomic network (CAN), especially during pre- and post-natal periods, facilitates biological adaptability and is an essential precursor for the cognitive requisites of learning to read. Reading is a remarkable evolutionary achievement of the human brain, mysteriously unusual, because it is not pre-wired with a genetic address to facilitate its acquisition. There is no gene for reading. The review suggests that reading co-opts a brain circuit centered in the left hemisphere ventral occipital cortex that evolved as a domain-general visual processor. Its adoption by reading depends on the CAN's coordination of the learning and emotional requirements of learning to read at the metabolic, cellular, synaptic, and network levels. By stabilizing a child's self-control and modulating the attention network's inhibitory controls over the reading circuit, the CAN plays a key role in school readiness and learning to read. In addition, the review revealed two beneficial CAN evolutionary adjustments to early-life stress "overloads" that come with incidental costs of school under-performance and dyslexia. A short-term adaptation involving methylation of the FKBP5 and NR3C1 genes is a liability for academic achievement in primary school. The adaptation leading to dyslexia induces alterations in BDNF trafficking, promoting long-term adaptive fitness by protecting against excessive glucocorticoid toxicity but risks reading difficulties by disruptive signaling from the CAN to the attention networks and the reading circuit.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".