Quantifying Cortical Resilience in Experimental, Clinical, and Epidemiological Studies: A Conceptually Grounded Method Using Noninvasive Brain Stimulation
Bibliographic record
Abstract
OBJECTIVE: Cortical resilience can be defined as the ability of the cortex of the human brain to rebound efficiently from perturbation. This concept is important in both research and clinical practice contexts. However, no direct measure of cortical resilience exists. Inhibitory variants of repetitive transcranial magnetic stimulation, such as continuous theta burst stimulation, provide a standardized method for inducing a perturbation; when coupled with the assessment of recovery rate from the perturbation, such a paradigm might provide a standardized measure of cortical resilience. This article describes a standardized method for quantifying cortical resilience using theta burst stimulation protocols. METHODS: A descriptive overview of a method for assessing cortical resilience is presented. Links are drawn between critical facets of the resilience construct and the protocol described. RESULTS: The Cortical Challenge and Recovery Test (CCaRT) method makes use of existing stimulation parameters and cognitive testing paradigms to provide a flexible and conceptually meaningful measure of cortical resilience. CONCLUSIONS: The CCaRT paradigm is potentially useful in research and contexts where cortical resilience is to be measured. The CCaRT paradigm has applicability to epidemiological studies and laboratory experimentation as well as diagnostic practice and clinical trial outcome measures.
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 | 0.001 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".