Pathways to depression: Dynamic associations between neural responses to appetitive cues in the environment, stress, and the development of illness
Bibliographic record
Abstract
This review focuses on research my colleagues and I have conducted on etiological pathways to depression. Much of this work has focused on the measurement of neural responses to appetitive cues, using two event-related brain potential (ERP) components, the Late Positive Potential (LPP) and the Reward Positivity (RewP). Reductions in each of these components have been associated with current symptoms of depression, and in some cases have been shown to differentiate anxious from depressive phenotypes. In this review, I will describe three broad and related approaches we have taken in our research to address a series of interdependent issuess. The first attempts to understand different sources of variation in the LPP and RewP, and how these sources interact with one another. The second tries to identify whether variation in the processes measured by these ERP components might reflect a latent vulnerability to depression and its symptoms, that is evident prior to illness onset. And the third examines the possibility that the processes reflected in the LPP and RewP might play a mechanistic role in the development of depression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".