Understanding the neurobiological basis of mixed-strategy decision-making in health and disease
Bibliographic record
Abstract
During competitive interactions involving multiple agents, such as sporting competitions, the outcome of each individual’s actions is dependent not only on a historical sequence of their own choices, but on those of their opponents as well. Success in such rivalries often requires that individuals adopt a mixed-strategy wherein available actions are chosen dynamically and unpredictably. Action selection in mixed-strategy environments involves the coordination of widespread neural processes, spanning the cognitive, emotional, and limbic domains. More specifically, choice selection involves working memory, valuation and reward processes, reinforcement learning, and execution of motor responses. The three studies in this thesis investigated the neurobiological mechanisms involved in choosing in mixed-strategy environments, and how these processes change throughout the course of neurodegenerative and neuropsychiatric disease. In the first study, we examined the human brain network underlying mixedstrategy decision-making using functional magnetic resonance imaging (fMRI). Using a carefully controlled paradigm, we compared the network underlying strategic decisions to that involved in choosing in nonstrategic environments. This study allowed us to gain insight into the specialized cognitive circuitry involved in choosing dynamically within a strategic context. In the second study, we asked how dopaminergic transmission affected mixed-strategy decisionmaking by investigating how degeneration of the dopamine system in Parkinson’s disease (PD) affected strategic choice patterns. Further, we investigated the hypothesis that cognitive function is deleteriously affected by dopaminergic medication (levodopa and dopamine agonists) in patients with PD, and whether genetic mechanisms controlling dopaminergic transmission could explain susceptibility to medicationinduced cognitive deficits. ii In the final study, we examined mixed-strategy decisions in patients with borderline personality disorder (BPD), a heterogeneous disorder prevalent in adolescent populations. We explored how the core clinical features of BPD, namely impulsivity and emotional dysregulation, affected mixed-strategy decisions in adolescents showing the first signs of BPD. Together, these studies provide a detailed account of how mixed-strategy decision-making is implemented in the brain, and how the cognitive functions required for choosing in such environments become affected throughout the course of neurological illness. This work, as a whole, represents a significant contribution to our understanding of how the brain integrates diverse sources of information to execute mixed-strategy decisions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".