Electrostimulation as a Prosthesis for Repair of Information Flow in a Computer Model of Neocortex
Bibliographic record
Abstract
Damage to a cortical area reduces not only information transmitted to other cortical areas, but also activation of these areas. This phenomenon, whereby the dynamics of a follower area are dramatically altered, is typically manifested as a marked reduction in activity. Ideally, neuroprosthetic stimulation would replace both information and activation. However, replacement of activation alone may be valuable as a means of restoring dynamics and information processing of other signals in this multiplexing system. We used neuroprosthetic stimulation in a computer model of the cortex to repair activation dynamics, using a simple repetitive stimulation to replace the more complex, naturalistic stimulation that had been removed. We found that we were able to restore activity in terms of neuronal firing rates. Additionally, we were able to restore information processing, measured as a restoration of causality between an experimentally recorded signal fed into the in silico brain and a cortical output. These results indicate that even simple neuroprosthetics that do not restore lost information may nonetheless be effective in improving the functionality of surrounding areas of cortex.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".