In the relentless pursuit of survival, organisms are perpetually faced with the challenge of deciding when to exploit known resources and when to explore uncharted options. This exploration–exploitation trade-off has long captivated neuroscientists and psychologists, who have sought to unravel the neural underpinnings that govern these critical decisions, particularly within rewarding environments. However, the intricate dynamics of exploration under threat or loss conditions have eluded comprehensive understanding. Now, a groundbreaking study employing single-neuron recordings in humans reveals how the amygdala, a pivotal emotional processing hub, orchestrates increased exploratory behavior in aversive contexts, shedding new light on the neural architecture of decision-making under uncertainty.
Exploration and exploitation represent fundamental cognitive strategies. Exploitation involves leveraging existing knowledge to maximize immediate rewards, while exploration is the risky venture into the unknown in search of potentially better outcomes. Historically, much emphasis has been placed on how the brain navigates this dilemma when pursuing rewards. Prior research has implicated prefrontal cortical circuits and subcortical regions in mediating exploratory behaviors driven by anticipated gains. Despite this, the mechanisms driving exploration when individuals attempt to avoid negative outcomes—such as losses or punishments—have remained vague, primarily due to the difficulty of disentangling neural signals in complex, emotionally charged scenarios.
The recent study by Reitich-Stolero, Aberg, Halperin, and colleagues breaks new ground by investigating exploration within mixed valence conditions—both gains and losses—while simultaneously capturing single-neuron activity in human participants. Utilizing a probabilistic learning task that interleaved reward and punishment trials, the research team meticulously recorded neural firing patterns from the amygdala and temporal cortex, regions traditionally linked to emotion processing and memory, respectively. Their approach enabled them to parse out how neurons adjust their signaling prior to decisions to explore in both positive and negative contexts.
A defining revelation of their findings is the identification of two distinct neural components driving exploration. First, a valence-independent rate signal was detected, reflecting a consistent neuronal coding of decision urgency or propensity to explore, regardless of whether the anticipated outcome was a gain or a loss. This suggests that some aspects of the brain’s exploratory machinery function in a generalizable manner. Second, more intriguing is the valence-dependent global noise signal observed preferentially in the amygdala during aversive, or loss-driven, trials. This heightened variability or “neural noise” correlates with an increased tendency to explore when trying to avoid negative outcomes, implicating a specialized amygdala mechanism modulating cautious or risk-sensitive behavior.
The amygdala’s engagement in exploration amid uncertainty links to its well-documented role in processing emotional salience and threat detection. Previous imaging studies have hinted at its involvement, but single-cell resolution provides unprecedented granularity on how neuronal firing patterns translate into adaptive or maladaptive decision strategies. Increased noise in neuronal activity could reflect an intrinsic computational mechanism enabling flexible switching between exploitation and exploration, especially under duress or when outcomes carry potential harm.
Behaviorally, participants exhibited an intriguing asymmetry: they explored more aggressively when confronted with the prospect of losses than gains, a phenomenon that aligns with psychological theories of loss aversion. The neural data align with this behavioral disposition by showing that the amygdala’s elevated noise levels drive this heightened exploratory behavior, suggesting that the emotional weight of potential losses intensifies the neural decision-making noise, resulting in more frequent shifts into exploration mode.
These discoveries carry profound implications for understanding psychiatric conditions characterized by dysregulated exploration-exploitation balance, particularly mood disorders such as anxiety and depression. Elevated amygdala activity is a hallmark in many affective disorders, and this study’s linkage of amygdala noise to increased exploration offers a mechanistic bridge between altered neural dynamics and maladaptive behaviors observed clinically. Patients exhibiting abnormal exploratory patterns, for example, excessive avoidance or risk-seeking in the face of threat, may be rooted in perturbed amygdala signaling.
Furthermore, the identification of two separable components—rate and noise—underlying exploratory decisions provides a conceptual framework that can inform computational models of decision-making. The rate code offers a stable signal guiding the initiation of exploration across contexts, while noise introduces probabilistic variability that may optimize learning and survival under uncertainty. Such dual mechanisms expand the traditional view, which has often emphasized deterministic or reward-driven factors alone.
This study also underscores the temporal cortex’s role in coupling with amygdala signals during exploration. Given the temporal lobes’ involvement in memory encoding, it’s plausible that exploration is not solely a current-state decision but is enriched by integrating past experiences to forecast outcomes. This coordination may enable the brain to weigh historical contingencies alongside emotional signals, thus refining the exploration-exploitation balance adaptively.
Technically, recording single neurons in awake human subjects engaged in complex decision tasks represents a formidable achievement, harnessing rare clinical opportunities presented during neurosurgical procedures. This invasive approach surpasses the resolution limits of functional neuroimaging and offers unparalleled insights into the microcircuit operations that govern cognition. The researchers’ use of probabilistic task design further allows disentanglement of neural patterns linked to reward versus punishment uncertainty, establishing a robust foundation for interpreting the functional significance of observed neural dynamics.
The implications of this research extend beyond understanding basic neuroscience. By illuminating how noise in the amygdala can amplify exploratory tendencies, particularly under threat, it sets the stage for novel interventions that modulate neural variability. Pharmacological agents, neuromodulation techniques, or behavioral therapies aimed at recalibrating amygdala activity hold promise for restoring balanced exploration in patients whose decision-making is skewed by affective disorders.
Moreover, these findings inspire a reevaluation of how computational models incorporate stochasticity and valence in decision processes. Traditional reinforcement learning models may need refinement to account for valence-dependent modulation of internal noise, moving closer to biological realism. This may ultimately lead to better predictive tools for human behavior and tailored approaches in artificial intelligence systems modeling human-like exploration.
In sum, this pioneering work delineates how the amygdala’s firing rate and intrinsic noise collaborate to modulate human exploratory behavior in environments laden with uncertainty and emotional valence. It advances a nuanced understanding of the neural computations underlying decisions to explore or exploit, especially in the context of loss avoidance. The convergence of neural, behavioral, and computational insights spotlights the amygdala as a critical node orchestrating adaptive decision strategies, while also hinting at mechanisms that may go awry in psychiatric pathologies. As exploration remains a cornerstone of learning and survival, unraveling its neural basis continues to be a paramount quest, now propelled forward by these compelling advances.
Subject of Research: Neural mechanisms of exploration and exploitation trade-off in human decision-making under mixed gain and loss conditions, with a focus on amygdala activity.
Article Title: Rate and noise in human amygdala drive increased exploration in aversive learning.
Article References:
Reitich-Stolero, T., Aberg, K.C., Halperin, D. et al. Rate and noise in human amygdala drive increased exploration in aversive learning. Nature (2025). https://doi.org/10.1038/s41586-025-09466-1
Image Credits: AI Generated
