Exercise-induced Neuroadaptations in Receptor Expression That Predispose to Addiction
Bibliographic record
Abstract
The neuroscience of addiction is complex and involves a variety of responses.Addiction is a chronic, relapsing disorder that involves compulsive seeking of a stimulant to feel euphoria, despite the adverse consequences.It involves functional changes to brain circuits that are involved with reward, stress, and self-control.Anybody can fall into the trap of addiction, even elite athletes.This research addresses certain neuroadaptations in the striatum of the brain that renders elite athletes more vulnerable to addictive behavior, particularly because of an increased tolerance to dopamine and an elongated stress response, leading athletes to seek additional stimulation through risk-taking.The intense exercise of elite athletes can increase D2 receptor expression and binding in the striatum, until tolerance to the elevated levels of dopamine is eventually developed.At the same time, long-term endurance exercise can activate the stress response and stimulate the HPA axis and the SAM pathway, releasing cortisol.Activation of the stress response can push athletes to seek out abusive drugs or behaviors and makes them more vulnerable to the euphoric effects of the stimulant.Rodent studies revealed that reduced function of striatal D2 receptors can lead to diminished sensitivity to negative outcomes, since striatal D2 receptors facilitate avoidance learning.With diminished sensitivity to punishing consequences, athletes are more likely to take part in risky behavior in search of a dopamine rush.Risk-taking behavior can directly lead to a greater vulnerability to addictive behavior.In addition, low striatal D2 receptor expression represents a predisposing factor for risk-taking and subsequent substance abuse.Although athletes' personalities and genetics may predispose them to certain addictive behaviors, their lifestyle can certainly endanger them as well.With the relatively small availability of literature on this topic, this paper will review the literature to test the above hypothesis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".