Bibliographic record
Abstract
Amnesia in its various forms is characterized by defects in one or more components of a complex system. Implantation of short-term memory occurs in the hippocampus, while long-term memory is essentially located in the neocortex; these regions are interconnected through complex synaptic structures. In the hippocampus, physiological data show that, as predicted by Hebb, excitatory synapses between nearby excitatory cells become strengthened by simultaneous activation. In contrast with this local process, the preponderance of clinical and experimental evidence indicates that cortical recall of a "memory" is the reconstruction of fragments stored in different synaptically distant brain regions. A mathematical model of memory must reconcile this apparent contradiction as well as explain how many different memories and "ideas" can be assembled within a given anatomical area. Continuum theory, which treats an ensemble of "cell assemblies" or neural networks, offers a step in this direction. Linear analysis using this approach shows that it is the nature of the neural continuum to generate activity waves of wavelength greater than synaptic connection ranges. These waves grow under certain circumstances, and their wavelength is controlled by the synaptic parameters. Both hippocampal and cortical tissue are subject to such wave growth. In the hippocampus, the local Hebbian strengthening controls the global wave growth, making the difference between wave decay and growth. The cortical wave structure can become very complex, so that reproducible memory recall as well as "creative thought" can be accommodated in the theory. Deficits in the functioning of the system may also be evaluated potentially by means of "goodness-of-fit" of the clinical and spatially resolved data with the model.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".