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Modeling collaborative memory with SAM.

Willa M Mannering¹, Suparna Rajaram², Richard M Shiffrin³

¹Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA. manneringwilla@gmail.com.

Memory & Cognition

|October 25, 2024

Summary

This summary is machine-generated.

Collaborative inhibition, where groups recall less than individuals, is explained by a computational model. The Search of Associative Memory (SAM) model shows how group recall cues disrupt individual memory retrieval.

Keywords:

Cognitive modeling Collaborative inhibition Collaborative memory

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Area of Science:

Cognitive Psychology
Computational Neuroscience
Human Memory

Background:

Human memory research predominantly uses isolated individuals, neglecting group dynamics.
Collaborative inhibition is a key phenomenon in collaborative memory, where groups underperform compared to individuals in recall tasks.
Existing theories lack formal computational modeling guidance.

Purpose of the Study:

To develop a computational framework for collaborative free recall using the Search of Associative Memory (SAM) model.
To test if a scaled SAM model can explain collaborative inhibition.
To provide a unified theoretical basis for both individual and collaborative memory.

Main Methods:

Scaling the Search of Associative Memory (SAM) model to simulate multiple agents recalling collaboratively.
Implementing a mechanism where group recall acts as retrieval cues for individual SAM models.
Analyzing model outputs to identify the emergence of collaborative inhibition.

Main Results:

The scaled SAM model naturally produced collaborative inhibition.
The model's results support the "retrieval disruption" hypothesis.
The framework successfully unifies individual and collaborative memory phenomena within SAM.

Conclusions:

The Search of Associative Memory (SAM) model provides a unified computational theory for human memory, encompassing both individual and collaborative recall.
The retrieval disruption hypothesis is computationally supported as an explanation for collaborative inhibition.
This framework enables future predictions regarding group size, shared knowledge, and false memory dynamics.