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September 10, 2025Open Access

Flexible navigation with neuromodulated cognitive maps

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Computational model demonstrates efficient mapping in novel environments, highlighting reward-driven navigation and adaptability.

The model enables efficient exploration and goal-oriented navigation by developing cognitive maps in real-time, which is crucial for spatial tasks.
Achieving effective one-shot mapping, our approach significantly outperforms traditional reinforcement learning methods that require extensive training epochs.
The integration of neuromodulatory signals allows the model to adapt and refine its spatial representations based on environmental feedback and rewards.
Observations of dynamic changes in neuronal density and tuning field size highlight parallels with experimental findings on hippocampal spatial cells.

Danieli et al. (2025) studied this question.

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