Online research in philosophy

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 traces the differences in brain activity associated with function and content words. The model considers words displayed primarily in isolation. Research on letter detection suggests that what distinguishes function from content words are their roles in text. Hence a model that fails to consider context effects on the processing of words provides an insufficient accounting of word representation in the brain.

The EEG and MEG studies cited in the target article found reduced gamma band power following pseudowords in comparison with words. Pulvermüller interprets this power difference in terms of reverberating lexical cell assemblies. An alternative interpretation in terms of latency jitter in the gamma band following pseudowords is proposed that does not appeal to lexical cell assemblies.

Norris, McQueen & Cutler provide two possible explanations for neighborhood effects. The first suggests that nonwords that are more similar to words tend to activate those words more than do less similar nonwords, and the second is based on sequential probabilities between phonemes. Unfortunately, neither explanation is sufficient to explain all reported neighborhood effects.

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.

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.

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.

When words are read, the visual cortex is activated, independent of whether visual or motor associations are elicited. This word-evoked brain activity is significantly influenced by semantic meaning. Such effects occur very early after stimulus presentation (at latencies between 80 and 130 msec), indicating that semantic meaning activates different neuronal assemblies in the human visual cortex when words are processed.

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.