In a groundbreaking study illuminating the neural underpinnings of goal-directed behavior, researchers have unveiled how dopamine signaling within the striatum orchestrates complex spatial navigation by encoding trajectory errors, in addition to its well-known role in signaling cue value. This novel insight challenges the traditional view that striatal dopamine primarily reflects reward expectation, revealing that dopamine release dynamically integrates real-time movement feedback to optimize behavioral guidance.
The investigation centered on understanding how animals continuously monitor and adjust their path toward a goal, a process requiring the brain to assess both the speed and direction of ongoing movement relative to an optimal trajectory. While past research had firmly established that striatal dopamine release correlates with reward-predictive cues, the mechanisms by which dopamine may incorporate an animal’s immediate locomotion metrics to refine navigation remained unclear. By employing advanced multi-region fiber photometry in tandem with sophisticated behavioral assays in mice, this study dissected the simultaneous encoding of navigational trajectory errors and learned cue values by striatal dopamine.
Their experiments revealed that dopamine signaling encodes what the authors term “bidirectional trajectory errors” — a neural measure quantifying the discrepancy between the animal’s current movement vector and the most efficient route to a goal. Intriguingly, these trajectory signals manifested independently from dopamine responses to reward-associated cues, suggesting that dopamine neurons multiplex distinct information streams related to both motivation and motor guidance. Such multiplexing enables the brain to maintain motivational vigor while fine-tuning spatial behavior, a dual function crucial for adaptive navigation in dynamic environments.
Further analyses demonstrated that the trajectory error signals arise from integration of sensory inputs corresponding to locomotion dynamics and visual flow information. This finding highlights dopamine’s sensitivity to multimodal sensorimotor feedback, reinforcing a broader computational role than previously appreciated. The ability of dopamine signals to reflect real-time trajectory deviations opens new avenues for understanding how reinforcement learning algorithms are neurally instantiated, particularly in mapping sensory feedback to action adjustments to maximize goal attainment.
To model these complex dopamine dynamics, the researchers turned to classical reinforcement learning frameworks, specifically examining the reward prediction error (RPE) term, which traditionally quantifies discrepancies between expected and received rewards. Their computational simulations showed that a standard RPE algorithm, furnished with mixed sensorimotor inputs, could simultaneously reproduce dopamine’s encoding of cue value and trajectory errors. However, distinct state-space representations were necessary for each signal type, suggesting that while the underlying reinforcement learning mechanism may be common, its neural inputs and outputs diverge to support parallel motivational and navigational functions.
Anatomically, the study mapped the spatiotemporal patterns of dopamine release across the striatum using wide-scale multi-fiber arrays. This approach uncovered overlapping but partially segregated representations of trajectory error and cue value that varied in timing and regional prevalence. Such spatial multiplexing underscores how the striatum integrates diverse information streams within separate but interacting circuits, enabling complex behavioral computations within a highly interconnected neural substrate.
The implications of separating dopamine’s guidance and motivational signals resonate deeply with the broader neuroscience community. It reframes dopamine not merely as a scalar ‘teaching signal’ for reward but as a nuanced mediator balancing ongoing movement control and reward anticipation. This duality breaks ground for novel theories on how the brain achieves flexible, context-dependent decision-making by dynamically partitioning dopaminergic information processing across neural ensembles.
Moreover, this research holds translational promise for understanding and treating disorders characterized by disrupted dopamine signaling, such as Parkinson’s disease, addiction, and schizophrenia. By identifying distinct dopamine signatures that encode trajectory errors versus motivational value, new biomarkers and therapeutic targets could emerge to better address specific aspects of impaired motor and cognitive function.
The study also inspires exciting technological prospects. The demonstration that dopamine release conveys navigation-relevant error metrics suggests potential for developing brain-machine interfaces or neuroprosthetics that harness such signals to improve motor learning and adaptive control. Real-time monitoring of dopaminergic trajectory error representations could enhance closed-loop systems designed to assist patients with motor deficits or augment human-computer interaction in complex environments.
On a fundamental neuroscience level, this research exemplifies how modern recording techniques integrated with computational modeling can unravel multiplexed neural codes previously masked by aggregate measurements. The revelation that dopamine neurons can concurrently broadcast multiple, functionally distinct messages challenges classical conceptions of neural signaling and calls for re-examination of other neuromodulatory systems under similar paradigms.
Ultimately, this study expands our understanding of dopamine’s role in behavior, positioning it as a multitasking neuromodulator essential not only for motivating animals towards rewards but also for guiding their precise movements through space. By bridging reinforcement learning theory with detailed neural measurements, the authors provide a compelling framework for decoding how the brain flexibly aligns internal states with external cues to achieve purposeful navigation.
As research continues to probe the multifaceted nature of dopamine and its circuits, new discoveries are expected to reshape the landscape of behavioral neuroscience and neuropsychiatric therapeutics. This transformative work paves the way for future investigations into how distinct dopaminergic signals are selectively routed and integrated across brain regions to support complex goal-directed behaviors in naturalistic settings.
Subject of Research: Striatal dopamine signaling in goal-directed navigation and reinforcement learning mechanisms.
Article Title: Striatum-wide dopamine encodes trajectory errors separated from value.
Article References:
Brown, E.H., Zi, Y., Vu, MA. et al. Striatum-wide dopamine encodes trajectory errors separated from value. Nature (2026). https://doi.org/10.1038/s41586-025-10083-1
Image Credits: AI Generated
DOI: https://doi.org/10.1038/s41586-025-10083-1
Tags: bidirectional trajectory errorsdopamine and behavioral guidancedopamine role in spatial learningfiber photometry in neurosciencegoal-directed spatial navigationlocomotion metrics in navigationmulti-region dopamine recordingneural basis of movement correctionneural integration of cue value and movementreward prediction vs movement feedbackstriatum dopamine signalingtrajectory error encoding
