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Functional modularity of semantic memory revealed by event-related brain potentials
Book chapter

Functional modularity of semantic memory revealed by event-related brain potentials

John Kounios
Neural Basis of Semantic Memory, pp 65-104
22 Mar 2007

Abstract

Theorists have faced a lack of consensus about basic properties of mind and brain. Of these basic properties, perhaps the most important is whether mind and brain are best conceived of as consisting of a number of independently functioning processing modules (e.g. Donders, 1868; Posner & Raichle, 1994; Sternberg, 1969, 1998, 2001), or rather as a single entity consisting of a large number of massively interacting parts (e.g. Anderson, 1995; Rumelhart, McClelland, & the PDP Research Group, 1986). Answering this question is extremely important, because the answer necessarily directs the course of both theory construction and experimentation in cognitive psychology and cognitive neuroscience, and the study of semantic memory in particular.As a contribution toward clarifying this issue, this chapter demonstrates how event-related potentials (ERPs) can be used to detect, isolate, and analyze functional neural modules, with special attention to functional modularity in semantic information processing. The method and analyses described in this chapter are also applicable to the closely related technique of magnetoencephalography (MEG; Hämäläinen, Hari, Ilmoniemi, Knuutila, & Lounasmaa, 1993), as well as to ERPs. The approach described here is based on a well-known physical property of electric fields in a volume conductor such as the brain, namely, that electric fields generated by separate sources combine by summation (Kutas & Dale, 1997; Nunez, 1981, 1990). Expanding on earlier work (Kounios, 1996; see also Kounios & Holcomb, 1992; Sternberg, 2001), this chapter shows how factorial experimental design can enable independent manipulation of these separate sources, yielding additive contributions to the aggregate electric field detectable at the scalp.

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Web of Science research areas
Neuroimaging
Neurosciences
Psychology
Psychology, Experimental
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