The N400 component of the ERP as semantic network error: Insights from feature-based connectionist attractor models of word meaning

Abstract

Event Abstract Back to Event The N400 component of the ERP as semantic network error: Insights from feature-based connectionist attractor models of word meaning Milena Rabovsky1* and Ken McRae2 1 Humboldt University Berlin, Psychology, Germany 2 University of Western Ontario, Psychology, Canada The N400 component of the event-related brain potential (ERP) is widely used in research on language and semantic memory. Although the component’s relation to semantic processing is well-established, the specific computational mechanisms underlying N400 generation are currently not clear. We explored the mechanisms underlying the N400 by examining which parameters in a connectionist model of word meaning most closely covary with N400 amplitudes. The model has 30 input units representing word form that map onto 2526 directly interconnected semantic feature units representing word meaning, according to semantic feature production norms. We simulated a number of N400 effects obtained in human empirical research: influences of semantic priming, lexical frequency, number of features (NOF; also possibly a proxy for concreteness), and repetition, as well as influences of frequency and NOF on repetition effects. Cross-entropy error values were consistently in the same direction as N400 amplitudes. Like N400 amplitudes, error values were larger for low frequency words, larger for words with many features, and decreased for semantically related target words as well as repeated words. Furthermore, the repetition-induced decrease was stronger for low frequency words, and for words with many semantic features. In contrast, there was less of a correspondence between total semantic activation and the N400. Like N400 amplitudes, activation was larger for words with many semantic features. However, activation also tended to increase with frequency, repetition and semantic priming which is opposite to well-established N400 results, and may be more in line with increased activation facilitating decision latencies in lexical and semantic tasks. Our results suggest an interesting relation between N400 amplitudes and error values in connectionist models of meaning. In psychological terms, error values in connectionist models have been conceptualized as implicit prediction error, and we discuss the possibility that N400 amplitudes may reflect this implicit prediction error in semantic memory. Keywords: connectionist model, ERP, N400, Prediction error, Semantic memory, Word meaning Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012. Presentation Type: Poster Topic: Learning, plasticity, memory Citation: Rabovsky M and McRae K (2012). The N400 component of the ERP as semantic network error: Insights from feature-based connectionist attractor models of word meaning. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00242 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 09 May 2012; Published Online: 12 Sep 2012. * Correspondence: Miss. Milena Rabovsky, Humboldt University Berlin, Psychology, Berlin, Germany, milena.rabovsky@hu-berlin.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Milena Rabovsky Ken McRae Google Milena Rabovsky Ken McRae Google Scholar Milena Rabovsky Ken McRae PubMed Milena Rabovsky Ken McRae Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.