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Related Experiment Video

Updated: Jun 28, 2025

Novel Object Exploration as a Potential Assay for Higher Order Repetitive Behaviors in Mice
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Dopamine encoding of novelty facilitates efficient uncertainty-driven exploration.

Yuhao Wang1, Armin Lak2, Sanjay G Manohar3

  • 1MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.

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Animals explore new environments by assessing reward uncertainties. A novel basal ganglia model, using dopamine for novelty signals, drives efficient, uncertainty-based exploration, outperforming other strategies.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Reinforcement Learning

Background:

  • Animals must explore unfamiliar environments to learn action-reward associations and optimize decision-making.
  • Effective exploration requires assessing and utilizing uncertainties in action-reward knowledge.

Purpose of the Study:

  • To propose a novel computational model of the basal ganglia for uncertainty-driven exploration.
  • To investigate the role of striatal pathways and dopaminergic neurons in estimating reward uncertainty and novelty signals.

Main Methods:

  • Developed a computational model of basal ganglia function, integrating direct and indirect striatal pathways for reward mean and variance estimation.
  • Utilized electrophysiological data to validate the basal ganglia model.
  • Fitted exploration strategies derived from the neural model to behavioral data.
  • Compared model-inspired exploration strategies against classic algorithms like Upper Confidence Bound (UCB) in simulations.

Main Results:

  • The proposed basal ganglia model effectively estimates reward distribution means and variances.
  • Electrophysiological data supported the model's representation of basal ganglia function.
  • Strategies inspired by the basal ganglia model demonstrated superior performance in simulations compared to UCB.
  • Model-fitting to behavioral data yielded results comparable to idealized normative models.

Conclusions:

  • Transient dopamine signals encoding novelty in the basal ganglia contribute to uncertainty representation.
  • This uncertainty representation efficiently drives exploration in reinforcement learning.
  • The model provides a biologically plausible mechanism for optimal decision-making under uncertainty.