Online research in philosophy

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.

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. Key Words: associative learning; cell assembly; cognition; cortex; ERP; EEG; fMRI; language; lexicon; MEG; PET; word category.

Green offers us two options: either connectionist models are literal models of brain activity or they are mere instruments, with little or no ontological significance. According to Green, only the first option renders connectionist models genuinely explanatory. I think there is a third possibility. Connectionist models are not literal models of brain activity, but neither are they mere instruments. They are abstract, IDEALISED models of the brain that are capable of providing genuine explanations of cognitive phenomena.

The idea of representing words with cell assemblies is very appealing. However, syntactic sequences need to be represented as well. This cannot be done by using the activity levels of assemblies. Instead, structural relations and operations between assemblies are needed to achieve serial order in syntactic word strings.

Empirical evidence suggests that high frequency electrographic activity is involved in active representation of meaningful entities in the cortex. Theoretical work suggests that distributed cell assemblies also represent meaningful entities. However, we are still some way from understanding how these two are related. This commentary also makes suggestions for further investigation of the neural basis of language at the level of both words and sentence planning.

Within the Hebbian paradigm the mechanism for integrating cell assemblies oscillating with different frequencies remains unclear. We hypothesize that such an integration may occur in cortical “interaction foci” that unite synchronously oscillated assemblies through hard-wired connections, synthesizing the information from various functional systems of the brain.

Pulvermüller restricts himself to an unnecessarily narrow range of evidence to support his claims. Evidence from neural modeling and behavioral experiments provides further support for an account of words encoded as transcortical cell assemblies. A cognitive neuroscience of language must include a range of methodologies (e.g., neural, computational, and behavioral) and will need to focus on the on-line processes of real-time language processing in more natural contexts.

Pulvermüller assumes that words are represented as associations of two cell assemblies formed according to Hebb's coincidence rule. This seems to correspond to the linguistic notion that words consist of lexemes connected to lemmas. Standard examples from theoretical linguistics, however, show that lemmas and lexemes have properties that go beyond coincidence-based assemblies. In particular, they are inherently disposed toward combinatorial operations; push-down storage, modelled by decreasing reverberation in cell assemblies, cannot capture this. Hence, even if the language capacity has an associationist characterization at some level, it cannot just be co-occurrence-based assembly formation.

Pulvermüller's work in extending Hebb's theory into the realm of language is exciting. However, we feel that what he characterizes as a single cell assembly is actually a set of cooperating cell assemblies that form parts of larger cognitive structures. These larger structures account more easily for a variety of phenomena, including the psycholinguistic.

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.