Judgments of Frequency and Recency in a Distributed Memory Model.

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Memory Research

Background:

• The Theory of Distributed Associative Memory (TODAM) provides a framework for understanding associative memory.
• TODAM2 enhances the original theory with features like context, auto-associations, and dual bases for richer memory representation.
• Existing models struggle to fully explain complex memory interactions such as differential forgetting and attention.

Purpose of the Study:

• To derive and apply the memory-probe dot product expressions for TODAM2 in 2x2 experimental designs.
• To test the applicability of TODAM2 to judgments of frequency (JOF) and judgments of recency (JOR).
• To investigate the relationship between item and associative information in memory recall.

Main Methods:

• Derivation of basic dot product expressions for TODAM2 for item and pair probes.
• Application of these expressions to analyze experimental data for JOF and JOR.
• An experiment using post-cuing to control encoding strategies for single-item JOF and JOR.

Main Results:

• TODAM2, with an added attenuation factor for repetition, successfully fits JOR data.
• JOF data fits were adequate but consistently predicted a stronger dependence between item and associative information than observed.
• The model's ability to explain differential forgetting and attention was explored.

Conclusions:

• TODAM2 offers a viable model for understanding associative memory, particularly for recency judgments.
• Further refinement is needed to accurately capture the interplay between item and associative information in frequency judgments.
• The model provides insights into the complex dynamics of memory recall and information processing.