Important models of memory

Recognition Model

Focuses on how individuals recognize previously encountered information.

Recognition Failure

Refers to the inability to recognize a previously encountered stimulus despite having encountered it.

ACT (Adaptive Control of Thought) Model

Focuses on the cognitive processes underlying human memory and learning, with key components like Production System and Memory Structures.

Semantic Networks

Represents knowledge as a network of interconnected concepts, facilitating retrieval through spreading activation.

Latent Semantic Analysis (LSA)

A computational method for analyzing relationships between documents and the terms they contain, reducing dimensionality to uncover latent semantic structures.

SAM (Search, Activation, and Model)

Focuses on how memories are searched for and activated, with key components like Search, Activation, and Model.

Minerva 2 Model

Focuses on memory retrieval based on the similarity between cues and stored traces, explaining forgetting curves and retrieval cue impact.

ToDAM (Temporal Context Model)

Memory retrieval influenced by temporal context, with memories associated with specific temporal contexts enhancing retrieval.

CHARM (Contextualized Hierarchical Attentive Retrieval Model)

Combines contextual and hierarchical aspects of memory retrieval, using contextual information to guide the retrieval of hierarchical memories.

PDP Modeling (Parallel Distributed Processing)

Represents memory through a network of interconnected units, involving both automatic and controlled processes for memory retrieval.