A Neural Network Model Inspired by the Prefrontal-Thalamic-Hippocampal Circuits for Navigation under Complex Spatio-temporal Rules

Key Points

• The aim is to develop a neural network model inspired by specific brain circuits to enhance navigation skills under varying rules.
• Developed a neural network based on prefrontal-thalamic-hippocampal circuits.
• Trained the model to navigate through complex spatio-temporal environments.
• Analyzed performance in navigating under different conditions.
• The model effectively navigated complex spatial environments.
• Performance improved with training on diverse temporal rules.
• Findings suggest potential applications in cognitive task simulations.