Context, emotion, and the strategic pursuit of goals: interactions among multiple brain systems controlling motivated behavior
Why this work is in the frame
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Bibliographic record
Abstract
Motivated behavior exhibits properties that change with experience and partially dissociate among a number of brain structures. Here, we review evidence from rodent experiments demonstrating that multiple brain systems acquire information in parallel and either cooperate or compete for behavioral control. We propose a conceptual model of systems interaction wherein a ventral emotional memory network involving ventral striatum (VS), amygdala, ventral hippocampus, and ventromedial prefrontal cortex triages behavioral responding to stimuli according to their associated affective outcomes. This system engages autonomic and postural responding (avoiding, ignoring, approaching) in accordance with associated stimulus valence (negative, neutral, positive), but does not engage particular operant responses. Rather, this emotional system suppresses or invigorates actions that are selected through competition between goal-directed control involving dorsomedial striatum (DMS) and habitual control involving dorsolateral striatum (DLS). The hippocampus provides contextual specificity to the emotional system, and provides an information rich input to the goal-directed system for navigation and discriminations involving ambiguous contexts, complex sensory configurations, or temporal ordering. The rapid acquisition and high capacity for episodic associations in the emotional system may unburden the more complex goal-directed system and reduce interference in the habit system from processing contingencies of neutral stimuli. Interactions among these systems likely involve inhibitory mechanisms and neuromodulation in the striatum to form a dominant response strategy. Innate traits, training methods, and task demands contribute to the nature of these interactions, which can include incidental learning in non-dominant systems. Addition of these features to reinforcement learning models of decision-making may better align theoretical predictions with behavioral and neural correlates in animals.
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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 | 0.000 |
| 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 | 0.001 |
| 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 it