Must analysis of meaning follow analysis of form? A time course analysis

If the cortex is an associative memory, strongly connected cell assemblies will form when neurons in different cortical areas are frequently active at the same time. The cortical distributions of these assemblies must be a consequence of where in the cortex correlated neuronal activity occurred during learning. An assembly can be considered a functional unit exhibiting activity states such as full activation ("ignition") after appropriate sensory stimulation (possibly related to perception) and continuous reverberation of excitation within the assembly (a putative memory process). This has implications for cortical topographies and activity dynamics of cell assemblies forming during language acquisition, in particular for those representing words. Cortical topographies of assemblies should be related to aspects of the meaning of the words they represent, and physiological signs of cell assembly ignition should be followed by possible indicators of reverberation. The following postulates are discussed in detail: (1) assemblies representing phonological word forms are strongly lateralized and distributed over perisylvian cortices; (2) assemblies representing highly abstract words such as grammatical function words are also strongly lateralized and restricted to these perisylvian regions; (3) assemblies representing concrete content words include additional neurons in both hemispheres; (4) assemblies representing words referring to visual stimuli include neurons in visual cortices; and (5) assemblies representing words referring to actions include neurons in motor cortices. Two main sources of evidence are used to evaluate these proposals: (a) imaging studies focusing on localizing word processing in the brain, based on stimulus-triggered event-related potentials (ERPs), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI), and (b) studies of the temporal dynamics of fast activity changes in the brain, as revealed by high-frequency responses recorded in the electroencephalogram (EEG) and magnetoencephalogram (MEG). These data provide evidence for processing differences between words and matched meaningless pseudowords, and between word classes, such as concrete content and abstract function words, and words evoking visual or motor associations. There is evidence for early word class-specific spreading of neuronal activity and for equally specific high-frequency responses occurring later. These results support a neurobiological model of language in the Hebbian tradition. Competing large-scale neuronal theories of language are discussed in light of the data summarized. Neurobiological perspectives on the problem of serial order of words in syntactic strings are considered in closing.

Much research suggests that words comprising more than one morpheme are represented in a "decomposed" manner in the visual word recognition system. In the research presented here, we investigate what information is used to segment a word into its morphemic constituents and, in particular, whether semantic information plays a role in that segmentation. Participants made visual lexical decisions to stem targets preceded by masked primes sharing (1) a semantically transparent morphological relationship with the target (e.g., cleaner-CLEAN), (2) an apparent morphological relationship but no semantic relationship with the target (e.g., corner-CORN), and (3) a nonmorphological form relationship with the target (e.g., brothel-BROTH). Results showed significant and equivalent masked priming effects in cases in which primes and targets appeared to be morphologically related, and priming in these conditions could be distinguished from nonmorphological form priming. We argue that these findings suggest a level of representation at which apparently complex words are decomposed on the basis of their morpho-orthographic properties. Implications of these findings for computational models of reading are discussed.