How activation, entanglement, and searching a semantic network contribute to event memory.

Free-association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long-lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist-cuing, primed free-association, intralist-cuing, and single-item recognition tasks. The findings also show that when a related word is presented in order to cue the recall of a studied word, the cue activates the target in an array of related words that distract and reduce the probability of the target's selection. The activation of the semantic network produces priming benefits during encoding, and search costs during retrieval. In extralist cuing, recall is a negative function of cue-to-distractor strength, and a positive function of neighborhood density, cue-to-target strength, and target-to-cue strength. We show how these four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks, indicating that the contribution of the semantic network varies with the context provided by the task. Finally, we evaluate spreading-activation and quantum-like entanglement explanations for the priming effects produced by neighborhood density.

Contextual models and the non-Newtonian paradigm.

Biological systems exhibit a wide range of contextual effects, and this often makes it difficult to construct valid mathematical models of their behaviour. In particular, mathematical paradigms built upon the successes of Newtonian physics make assumptions about the nature of biological systems that are unlikely to hold true. After discussing two of the key assumptions underlying the Newtonian paradigm, we discuss two key aspects of the formalism that extended it, Quantum Theory (QT). We draw attention to the similarities between biological and quantum systems, motivating the development of a similar formalism that can be applied to the modelling of biological processes.

Is there something quantum-like about the human mental lexicon?

Following an early claim by Nelson & McEvoy (35) suggesting that word associations can display 'spooky action at a distance behaviour', a serious investigation of the potentially quantum nature of such associations is currently underway. In this paper quantum theory is proposed as a framework suitable for modelling the human mental lexicon, specifically the results obtained from both intralist and extralist word association experiments. Some initial models exploring this hypothesis are discussed, and experiments capable of testing these models proposed.