MUC (Memory, Unification, Control): A Model on the Neurobiology of Language Beyond Single Word Processing

Until not too long ago, the neurobiological model that has dominated our view on the neural architecture of language was the Wernicke-Lichtheim-Geschwind model. In this classical model, the human language faculty was situated in the left perisylvian cortex, with a division of labor between the frontal and temporal regions. Wernicke’s area in left temporal cortex was assumed to subserve the comprehension of speech, whereas Broca’s area in left inferior frontal cortex (LIFC) was claimed to subserve language production. The arcuate fasciculus connected these two areas. This model was based on single word processing. Since then, researchers interested in brain and language have realized that language is more than the concatenation of single words. Research focusing on sentence processing has found that lesions in Broca’s region and adjacent cortex impair not only language production but also language comprehension (Caramazza & Zurif, 1976), whereas lesions in Wernicke’s region not only affect language comprehension but also language production. More recent neuroimaging studies provided further evidence that central aspects of language production and comprehension are subserved by shared neural circuitry (Menenti, Gierhan, Segaert, & Hagoort, 2011; Segaert, Menenti, Weber, Petersson, & Hagoort, 2012). Since the advent of a whole toolkit of neuroimaging techniques, new models of the neural architecture of human language skills have been proposed. Here, I focus mainly on the Memory-UnificationControl (MUC) model as a model that tries to integrate knowledge about language processing beyond single words (Hagoort, 2005, 2013). After describing its three components, I discuss the evidence that has accumulated in support of the model.