For decades, the amygdala has been simplistically branded as the brain’s fear center—a rudimentary structure that triggers instinctive responses to threats witnessed in our environments, from spiders to crowded spaces. However, groundbreaking research from Dartmouth College reveals this dual-lobed brain region as a far more intricate and dynamic player in our cognitive repertoire, particularly in how the brain navigates uncertainty by arbitrating between competing learning strategies. This paradigm-shifting study, published in Nature Communications, redefines the amygdala’s role, showcasing it as a sophisticated mediator that dynamically balances action- and stimulus-based learning mechanisms involved in decision-making.
Traditional interpretations framed the amygdala largely within the confines of emotional processing, anchored in fear responses and associated with reward learning in a reflexive, almost reactionary capacity. Jae Hyung Woo, lead author and doctoral candidate in psychological and brain sciences at Dartmouth, contends that considering the amygdala merely a repository for fear oversimplifies its functionality given its dense, widespread neural connections. These connections enable it to interact with key brain regions implicated in memory, sensory perception, and executive functions, suggesting a higher-order integrative role essential to adaptive behavior.
The research team delved deeply into how the amygdala contributes to learning under conditions of uncertainty, employing computational reinforcement learning models to simulate the brain’s internal arbitration processes. These models provided a nuanced perspective: when confronted with unfamiliar scenarios, the brain must choose between two learning strategies—action-based, which relies on replicating successful motor behaviors from past experiences, and stimulus-based, which hinges on identifying salient cues or features in the environment predictive of desired outcomes. Using the analogy of mastering an unfamiliar coffee machine, the dichotomy becomes clear—should one press a previously successful button (action-based), or focus on environmental signals like blinking lights indicative of readiness (stimulus-based)?
Alireza Soltani, senior author and associate professor of psychological and brain sciences, highlights the subtle but critical distinction between these modes. Action-based learning is tightly coupled with executing precise motor sequences, making it relatively rigid but effective when the sequence is well-known. In contrast, stimulus-based learning offers greater flexibility, allowing the individual to generalize across varying contexts by focusing on stimulus properties detached from specific motor actions. This flexibility is critical in novel or unpredictable environments, enabling exploration of alternative paths toward reward.
In their experiments, the researchers observed that a functioning amygdala dynamically arbitrates between these strategies, effectively ‘weighing’ the reliability of each model as more information becomes available. Initially, the amygdala samples both action and stimulus-based approaches, but as experience accumulates, it preferentially commits to whichever model demonstrates higher predictive accuracy. This adaptability facilitates efficient and context-sensitive decision-making, optimizing reward acquisition by exploiting the most dependable learning strategy at any given moment.
Crucially, lesions or damage to the amygdala disrupt this precise arbitration, leading to suboptimal learning and inflexible behavioral outcomes. Study participants with compromised amygdala function showed a marked bias toward defaulting on action-based learning from the beginning, failing to appropriately adjust their reliance on stimulus-based cues. This bias hampers exploration, fostering rigid patterns that can be disadvantageous in dynamic environments, aiding in explaining conflicting findings from previous research where amygdala damage either impaired or enhanced stimulus-driven learning depending on task demands.
This emerging framework positions the amygdala not as a vestigial remnant of primal fear but as a pivotal arbiter amidst complex neural computations, guiding the brain’s choices about how to approach uncertain learning problems. As Soltani summarizes, the amygdala “promotes exploration between alternative models,” allowing individuals to deviate from default behaviors and learn from novel experiences, ultimately finding the most reliable internal model to navigate reality effectively.
Beyond basic neuroscience, these insights carry profound implications for psychological treatment paradigms, especially in handling phobias and anxiety disorders. Patients often become locked in stimulus-driven avoidance behaviors—compulsively associating fear with specific stimuli such as spiders, generating rigid responses that are difficult to override. The new model suggests therapeutic strategies that encourage shifting attention away from the fear-provoking stimulus toward active behavioral exploration may be more effective. For example, gradually interacting with the object of fear through a series of controlled actions could engage the amygdala’s arbitration function, fostering flexible learning and diminishing maladaptive stimulus-locked fear responses.
Such an approach reframes exposure therapy by leveraging the amygdala’s ability to favor action-based learning pathways, which tend to produce more reliable outcome predictions and enable cognitive flexibility. This reframing could represent a significant advance in our understanding and treatment of anxiety, suggesting novel interventions that promote exploration and resilience even in the face of deep-seated fears.
Intriguingly, this refined understanding of the amygdala reflects its evolutionary trajectory, now appreciated as a brain structure rooted in survival yet adapted for increasingly abstract integrative processes. As one of the oldest brain regions, its foundational role in threat detection and immediate reaction has been augmented by flexible, deliberative functions afforded by expanded connections to cortical areas, including the prefrontal cortex. This expansion allows the amygdala to influence decision-making processes far beyond reflexive fear, integrating diverse streams of information to arbitrate between competing learning models dynamically.
Moving forward, the Dartmouth research team is pursuing further investigations into the interplay between the amygdala and prefrontal cortex during decision-making tasks, utilizing neural recordings and rodent models to dissect specific pathways that facilitate this arbitration. Their collaborative work with UCLA aims to unravel the intricate circuitry governing this process, shedding light on how higher-order brain regions communicate with ancient limbic structures to orchestrate adaptive behavior.
This research not only challenges long-standing dogma about the amygdala’s function but also opens new avenues for understanding cognitive flexibility, learning under uncertainty, and emotion regulation. It stands to transform both basic neuroscience and clinical practice by highlighting the amygdala’s sophisticated role as a neural arbitrator—a conductor integrating disparate learning systems to optimize human decision-making in a complex, often uncertain world.
Subject of Research: Not applicable
Article Title: Contribution of amygdala to dynamic model arbitration under uncertainty
News Publication Date: 28-Nov-2025
Web References: http://dx.doi.org/10.1038/s41467-025-66745-1
Keywords: Neuroscience; Behavioral neuroscience; Cognitive neuroscience; Adaptive systems; Brain structure; Amygdala; Cognition; Risk perception; Decision making
