Neurons repeatedly exposed to similar perceptual experiences fire together and wire together to form ‘meaning kernels’ of concepts. Pulvermueller argues that abstract concepts may be devoid of meaning kernels, because the perceptual experiences that construct abstract concepts are subject to great variation and share few common features. Abstract concept are therefore grounded in the brain through features that belong to ‘meaning halos’, rather than to ‘meaning kernels’.

Embodied theories of grounded semantics postulate that, when word meaning is first acquired, a link is established between symbol and corresponding semantic information present in modality-specific—including primary—sensorimotor cortices of the brain. Direct experimental evidence documenting the emergence of such a link, however, is still missing. Here, we present new neuroimaging results that provide such evidence. We taught participants aspects of the referential meaning of previously unknown, senseless novel spoken words by associating them with either a familiar action or a familiar (...) object. After training, we used functional magnetic resonance imaging to analyze the participants’ brain responses to the new speech items. We found that hearing the newly learnt object-related word sounds selectively triggered activity in the primary visual cortex, as well as secondary and higher visual areas.These results for the first time directly document the formation of a link between the novel, previously meaningless spoken items and corresponding semantic information in primary sensory areas in a category-specific manner, providing experimental support for perceptual accounts of word-meaning acquisition in the brain. (shrink)

For some years there has been a controversy about whether brain state variables such as EEG or neuronal spike trains exhibit chaotic behaviour. Wright & Liley claim that the local dynamics measured by spike trains or local field potentials exhibit chaotic behaviour, but global measures like EEG should be governed by linear dynamics. We propose a different scheme. Based on simulation studies and various experiments, we suggest that the pointwise dimension of EEG time series may provide some valuable information about (...) underlying neuronal generators. (shrink)

Müller's target article aims to summarize approaches to the question of how language elements (phonemes, morphemes, etc.) and rules are laid down in the brain. However, it suffers from being too vague about basic assumptions and empirical predictions of neurobiological models, and the empirical evidence available to test the models is not appropriately evaluated. (1) In a neuroscientific model of language, different cortical localizations of words can only be based on biological principles. These need to be made explicit. (2) Evidence (...) for and against word class differences could be evaluated more rigorously. (3) All (and only) humans are able to learn languages with complex syntactic structures; it is, therefore, not appropriate to deny innateness and universality of syntactic principles. The real question appears to be the following: Which neurobiological principles are the linguistic principles based on? (shrink)

The cell assembly model of language posits that words are laid down in the cortex by discrete sets of neurons distributed over specific parts of the brain. The strong internal links of these “word webs” may not only bind articulatory and acoustic knowledge of a lexical item, they may also link word and meaning; for example, by connecting neuron populations related to word forms to those of actions and perceptions to which the words refer. Therefore, the cortical activation elicited by (...) words should reflect aspects of word meaning, a postulate that has received strong support from recent work using neurophysiological and metabolic imaging. Segalowitz & Lane make the point that this neurobiological model can also be used to predict reaction times in behavioral experiments, using the behavioral distinction between content and function words as an example. We acclaim their view, but warn that response times might be related to different mechanisms at the neuronal level, including the cortical distribution and internal connectivity of cell assemblies along with their mutual connections in the grammatical (syntactic and semantic) network. (shrink)

The following questions are addressed concerning how a theory of lexical access can be realized in the brain: (1) Can a brainlike device function without inhibitory mechanisms? (2) Where in the brain can one expect to find processes underlying access to word semantics, syntactic word properties, phonological word forms, and their phonetic gestures? (3) If large neuron ensembles are the basis of such processes, how can one expect these populations to be connected? (4) In particular, how could one-way, reciprocal, and (...) numbered connections be realized? and, (5) How can a neuroscientific approach for multiple access to the same word in the course of the production of a sentence? Footnotes1 This commentary originally appeared in the Levelt et al. treatment in BBS 22(1) (pp. 52–54). (shrink)

Amit defines cell assemblies aslocal cortical neuron populationswith strong internal connections. However, Hebb himself proposed that cell assemblies are distributed over different cortical areas (nonlocal ortranscortical assemblies). We review evidence from cognitive neuroscience and neuropsychology supporting the assumption that cell assemblies are transcortical.

The HIT model comes close to a view suggested by Donald Hebb, that cognitive representations are organized as distributed neuron webs, cell assemblies, whose components are mutually connected and whose internal connections provide continuous information exchange among sub-components of the representation. Two questions are asked related to (1) the organization of internal connections of a concept representation and (2) the conditions under which information exchange between components are assumed in the HIT model.

True, there may be two language-processing systems, lexicon and syntax. However, could we not say more than that they are computationally and linguistically distinct? Where are they in the brain, why are they where they are, and how can their distinctness and functional properties be explained by biological principles? A brain model of language is necessary to answer these questions. One view is that two different types of corticocortical connections are most important for storing rules and their exceptions: short-range connections (...) within the perisylvian language cortex and long-range connections between this region and other areas. Probabilities of neuroanatomical connections plus associative learning principles explain why different connection bundles specialize in rule storage versus exception learning. Linguistic issues related to language change and plural formation in German are addressed in closing. (shrink)

In this response to multidisciplinary commentaries on the target article, “Words in the brain's language,” additional features of the cell-assembly model are reviewed, as demanded by some of the commentators. Subsequently, methodological considerations on how to perform additional tests of neurobiological language models as well as a discussion of recent data from neuroimaging, neuropsychological, and other behavioral studies in speakers of spoken and sign languages follow. Special emphasis is put on the explanatory power of the cell-assembly model regarding neuropsychological double (...) dissociations. Future perspectives on neural network simulations, neuronal mechanisms of syntax and semantics, and the interaction of attention mechanisms and cell assemblies are pointed out in the final paragraphs. (shrink)