Bibliographic record
Abstract
Animal and human research has shown that the brain can reorganize and even remodel itself to restore function in response to central nervous system (CNS) injuries, such as stroke, traumatic brain injury, and spinal cord injury. This chapter will discuss the phenomenon of neuroplasticity after damage to the CNS demonstrated in animal and human experiments. Research on Constraint-Induced Movement therapy or CI therapy, which is a behaviorally based approach to physical rehabilitation, will be a major focus. This body of work, among other contributions, overthrew the reigning clinical wisdom that stroke survivors more than 1-year post-event can not benefit from additional physical rehabilitation. It also provided the first evidence that physical rehabilitation can produce large improvements in real-world arm function and change CNS organization and structure. This evidence provides a neurophysiological basis for continued plasticity in behavior among older adults. Introduction Clinical wisdom, and even the scientific view, until relatively recently was that older adults who suffered damage to their brain had little hope that this vital organ could repair itself or adapt how it functioned to overcome the injury. The scientific view was based on the long-held tenet that the mature central nervous system (CNS) had little capacity to repair or reorganize itself. Though contrary views were expressed (e.g., Flourens, 1842; Fritsch and Hitzig, 1870; Lashley, 1938; Munk, 1881), the mature CNS was generally believed (Kaas, 1995, p. 735) to exhibit little or no plasticity (e.g., Hubel and Wiesel, 1970; Ruch, 1960, p. 274).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.028 |
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".