NLM-HS: Navigation Learning Model Based on a Hippocampal-Striatal Circuit for Explaining Navigation Mechanisms in...

Area of Science:

• Neuroscience
• Computational Biology
• Cognitive Science

Background:

• The distinct roles of the hippocampus, striatum, and prefrontal cortex in animal navigation are known, but their integrated function remains unclear.
• Understanding how these brain structures interact is crucial for explaining complex navigation behaviors.

Purpose of the Study:

• To develop a computational model (NLM-HS) simulating the integrated function of the hippocampal-striatal circuit in animal navigation.
• To explain the neural mechanisms underlying goal-directed and habitual navigation strategies.

Main Methods:

• Developed a navigation learning model (NLM-HS) incorporating hippocampal (cognitive mapping), striatal (habitual learning), and prefrontal cortex (strategy arbitration) components.
• Simulated the Tolman detour experiment to validate the model's performance.

Main Results:

• The NLM-HS successfully reproduced animal-like environmental cognition and navigation behaviors.
• The integrated model demonstrated faster decision-making and superior adaptivity compared to models relying solely on hippocampal or striatal functions.
• The prefrontal cortex component effectively arbitrated between cognitive and habitual strategies.

Conclusions:

• The NLM-HS provides a plausible computational framework for understanding how the hippocampus, striatum, and prefrontal cortex cooperate in navigation.
• This integrated model offers insights into the flexibility and efficiency of animal navigation strategies.