| Semantic memory is the subsystem of human memory that stores knowledge of concepts or meanings, as opposed to life specific experiences. The organization of concepts within semantic memory can be understood as a semantic network, where the concepts (nodes) are associated (linked) to others depending on perceptions, similarities, etc. Lexical access is the complementary part of this system and allows the exploration and retrieval of such organized knowledge. While conceptual information is stored under certain underlying organization (and thus gives rise to a specific topology), it is crucial to have an accurate access to any of the information units, e.g. the concepts, for efficiently retrieving semantic information for real-time needs. An example of an information retrieval process occurs during verbal fluency tasks, and it is known to involve two different mechanisms: clustering, or generating words within a subcategory, and, when a subcategory is exhausted, switching to a new subcategory. We extended a previous model denominated 'switcher-random-walks' by reducing switching transitions to those not available through clustering and by adding the concept of working memory to the system (a FIFO buffer). This new model represents a minimal cognitive retrieval system consisting of a structured information explored by a dual mechanism which is filtered a posteriori by a memory buffer. We evaluated the importance of such memory buffer in combination with switching activity and their effect in minimizing repetitions during the exploration of four different network models (scale-free, small-world, random and random-modular). |
|