Replay shapes abstract cognitive maps for efficient social navigation

Area of Science:

• Cognitive science
• Social neuroscience
• Network science

Background:

• Adaptive social decision-making relies on understanding information flow within social networks.
• Individuals possess limited capacity for direct experience with large social network structures.
• Accurate tracking of information pathways in complex networks remains a key question.

Purpose of the Study:

• To investigate how humans form and utilize mental representations of social network structures.
• To understand the cognitive mechanisms underlying social navigation and information tracking.
• To explore the role of learning and rest in refining social network knowledge.

Main Methods:

• Participants learned social network structures through friendship connections.
• Cognitive mapping and social navigation accuracy were assessed.
• The impact of overnight rest on network representation abstraction was examined using replay-like mechanisms.

Main Results:

• People rapidly cache abstract knowledge of social network structures upon learning connections.
• This cached knowledge facilitates the identification of efficient information routes.
• Overnight rest enhances the abstraction of these cognitive maps, improving navigation for distant network paths.

Conclusions:

• Humans construct and refine cognitive maps of social networks for efficient navigation.
• A replay-like mechanism during rest abstracts these maps, optimizing long-range social communication.
• These findings offer mechanistic insights into human social navigation strategies.