On the research of time past: the hunt for the substrate of memory
Bibliographic record
Abstract
The search for memory is one of the oldest quests in written human history. For at least two millennia, we have tried to understand how we learn and remember. We have gradually converged on the brain and looked inside it to find the basis of knowledge, the trace of memory. The search for memory has been conducted on multiple levels, from the organ to the cell to the synapse, and has been distributed across disciplines with less chronological or intellectual overlap than one might hope. Frequently, the study of the mind and its memories has been severely restricted by technological or philosophical limitations. However, in the last few years, certain technologies have emerged, offering new routes of inquiry into the basis of memory. The 2016 Kavli Futures Symposium was devoted to the past and future of memory studies. At the workshop, participants evaluated the logic and data underlying the existing and emerging theories of memory. In this paper, written in the spirit of the workshop, we briefly review the history of the hunt for memory, summarizing some of the key debates at each level of spatial resolution. We then discuss the exciting new opportunities to unravel the mystery of memory.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.011 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".