A computational model of item-based directed forgetting.

Area of Science:

• Cognitive Psychology
• Computational Neuroscience

Background:

• Item-method directed forgetting influences recognition memory.
• Previous research suggests enhanced encoding of 'remember' cues.

Purpose of the Study:

• To propose and test a retrieval-based explanation for directed forgetting effects.
• To evaluate an instance-based memory model (MINERVA 2) in explaining these effects.

Main Methods:

• Utilized an instance-based memory model (MINERVA 2).
• Imported word representations from latent semantic analysis (LSA) and random permutation model (RPM).
• Simulated Montagliani and Hockley's (2019) directed forgetting paradigm.

Main Results:

• The MINERVA 2 model successfully reproduced Montagliani and Hockley's findings.
• The model explained better foil rejection for forget-cued items without assuming elaborated study encoding.
• Simulations indicated retrieval-time effects influence false recognition of category-related foils.

Conclusions:

• Directed forgetting effects in recognition memory can be explained by retrieval processes.
• The results challenge the necessity of assuming enhanced category-level encoding at study.
• The model provides a formal framework for studying directed forgetting consequences.