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A Neurocomputational Model of the N400 and the P600 in Language Processing
Copyright policy )Abstract Ten years ago, researchers using event‐related brain potentials (ERPs) to study language comprehension were puzzled by what looked like a Semantic Illusion: Semantically anomalous, but structurally well‐formed sentences did not affect the N400 component—traditionally taken to reflect semantic integration—but instead produced a P600 effect, which is generally linked to syntactic processing. This finding led to a considerable amount of debate, and a number of complex processing models have been proposed as an explanation. What these models have in common is that they postulate two or more separate processing streams, in order to reconcile the Semantic Illusion and other semantically induced P600 effects with the traditional interpretations of the N400 and the P600. Recently, however, these multi‐stream models have been called into question, and a simpler single‐stream model has been proposed. According to this alternative model, the N400 component reflects the retrieval of word meaning from semantic memory, and the P600 component indexes the integration of this meaning into the unfolding utterance interpretation. In the present paper, we provide support for this “Retrieval–Integration (RI)” account by instantiating it as a neurocomputational model. This neurocomputational model is the first to successfully simulate the N400 and P600 amplitude in language comprehension, and simulations with this model provide a proof of concept of the single‐stream RI account of semantically induced patterns of N400 and P600 modulations.
Microsoft Academic Graph classification: Artificial intelligence business.industry business Semantic memory Utterance Interpretation (logic) Computer science Syntax Semantics N400 Meaning (non-linguistic) Computational linguistics Natural language processing computer.software_genre computer Cognitive science
Artificial Intelligence, Cognitive Neuroscience, Experimental and Cognitive Psychology, Brain, Comprehension, Computer Simulation, Electroencephalography, Evoked Potentials, Humans, Language, Models, Neurological, Nerve Net, Regular Article, Regular Articles, Language comprehension, Event‐related potentials, N400, P600, Retrieval–Integration account, Computational modeling, Neural networks
Artificial Intelligence, Cognitive Neuroscience, Experimental and Cognitive Psychology, Brain, Comprehension, Computer Simulation, Electroencephalography, Evoked Potentials, Humans, Language, Models, Neurological, Nerve Net, Regular Article, Regular Articles, Language comprehension, Event‐related potentials, N400, P600, Retrieval–Integration account, Computational modeling, Neural networks
Microsoft Academic Graph classification: Artificial intelligence business.industry business Semantic memory Utterance Interpretation (logic) Computer science Syntax Semantics N400 Meaning (non-linguistic) Computational linguistics Natural language processing computer.software_genre computer Cognitive science
- Saarland University Germany
- University of Groningen Netherlands
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- Saarland University Germany
- University of Groningen Netherlands
Abstract Ten years ago, researchers using event‐related brain potentials (ERPs) to study language comprehension were puzzled by what looked like a Semantic Illusion: Semantically anomalous, but structurally well‐formed sentences did not affect the N400 component—traditionally taken to reflect semantic integration—but instead produced a P600 effect, which is generally linked to syntactic processing. This finding led to a considerable amount of debate, and a number of complex processing models have been proposed as an explanation. What these models have in common is that they postulate two or more separate processing streams, in order to reconcile the Semantic Illusion and other semantically induced P600 effects with the traditional interpretations of the N400 and the P600. Recently, however, these multi‐stream models have been called into question, and a simpler single‐stream model has been proposed. According to this alternative model, the N400 component reflects the retrieval of word meaning from semantic memory, and the P600 component indexes the integration of this meaning into the unfolding utterance interpretation. In the present paper, we provide support for this “Retrieval–Integration (RI)” account by instantiating it as a neurocomputational model. This neurocomputational model is the first to successfully simulate the N400 and P600 amplitude in language comprehension, and simulations with this model provide a proof of concept of the single‐stream RI account of semantically induced patterns of N400 and P600 modulations.