Online research in philosophy

In this comment, a picture of ERP research is sketched that is slightly different from Hardcastle's account, in that it emphasises the functional characterisation of ERP components rather than the neurophysiological connections. It is suggested that selection pressure of ERP work on cognitive and neurophysiological theories and vice versa is a more apt metaphor for intertheoretical relations in this field than explanatory extension. Secondly, it is argued that the temporal characteristics of ERP components do not support Hardcastle's claim that they may be used to fix timing in phenomenal consciousness. Although I agree that ERP components, cautiously interpreted, can contribute to the identification of substages of information processing, rather than refuting Dennett and Kinsbourne, her ERP data seem compatible with a multiple drafts model.

I think that some of the arguments in this article are themselves flawed, or are based on an understanding of linguistics that is too narrowly focused on certain versions of generative grammar. For example, the argument that in computational applications purely statistical approaches are in general more successful than rule-based approaches has to be qualified: It holds, or may have hold, for certain applications like machine translation, but not for others, like the generation of text to answer queries to databases. Furthermore, statistical methods have been integrated in certain linguistic theories themselves, like stochastic optimality theory (Boersma & Hayes 2001). The authors also claim that linguistics is not able to come up with leading questions for the cognitive and neurophysiological investigation of language processing. This statement is even more puzzling, as it is difficult to name serious research in psycholinguistics or in neurophysiological aspects of language processing that is not informed by theoretical notions rooted in linguistics, many of them derived from generative grammar. To cite just one case: Recursion has been proposed – perhaps unjustly so – as the single property that distinguishes human language processing from other animal communication systems; this has led to the identification of special brain regions and pathways of recursive language processing (cf. Friederici 2009).

In this essay, I argue that neurophysiological materialism - the thesis that all of our mental contents are caused by non-mental, purely physical brain states - is epistemically self-refuting, and ought to be rejected even if it cannot be otherwise disproved.

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.

Lehar's lively discussion builds on a critique of neural models of vision that is incorrect in its general and specific claims. He espouses a Gestalt perceptual approach rather than one consistent with the “objective neurophysiological state of the visual system” (target article, Abstract). Contemporary vision models realize his perceptual goals and also quantitatively explain neurophysiological and anatomical data.

This commentary elaborates on Gray's conclusion that his neurophysiological model of consciousness might explain how consciousness arises from the brain, but does not address how consciousness evolved, affects behaviour or confers survival value. The commentary argues that such limitations apply to all neurophysiological or other third-person perspective models. To approach such questions the first-person nature of consciousness needs to be taken seriously in combination with third-person models of the brain.

Anatomical studies propose that the primate auditory cortex contains more fields than have actually been functionally confirmed or described. Spatially resolved functional magnetic resonance imaging (fMRI) with carefully designed acoustical stimulation could be ideally suited to extend our understanding of the processing within these fields. However, after numerous experiments in humans, many auditory fields remain poorly characterized. Imaging the macaque monkey is of particular interest as these species have a richer set of anatomical and neurophysiological data to clarify the source of the imaged activity. We functionally mapped the auditory cortex of behaving and of anesthetized macaque monkeys with high resolution fMRI. By optimizing our imaging and stimulation procedures, we obtained robust activity throughout auditory cortex using tonal and band-passed noise sounds. Then, by varying the frequency content of the sounds, spatially specific activity patterns were observed over this region. As a result, the activity patterns could be assigned to many auditory cortical fields, including those whose functional properties were previously undescribed. The results provide an extensive functional tessellation of the macaque auditory cortex and suggest that 11 fields contain neurons tuned for the frequency of sounds. This study provides functional support for a model where three fields in primary auditory cortex are surrounded by eight neighboring ‘‘belt’’ fields in non-primary auditory cortex. The findings can now guide neurophysiological recordings in the monkey to expand our understanding of the processing within these fields. Additionally, this work will improve fMRI investigations of the human auditory cortex.

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.

It's very interesting to see neurophysiological evidence brought to bear on the puzzling question of conscious experience. Many have observed that information-processing models of cognition seem to leave consciousness untouched; it is natural to hope that turning to neurophysiology might lead us to the Holy Grail. Still, I think there are reasons to be skeptical. There are good reasons to suppose that neurophysiological investigation contributes to cognitive explanation at best in virtue of constraining the information-processing structure of cognition. Of course this is a very large and significant role for it to play, but it may be over-optimistic to suppose that it can play some further explanatory role, taking us where information-processing theories cannot. If so, then neurophysiological accounts will be no more and no less successful at dealing with consciousness than information-processing accounts are.

It's very interesting to see neurophysiological evidence brought to bear on the puzzling question of conscious experience. Many have observed that information-processing models of cognition seem to leave consciousness untouched; it is natural to hope that turning to neurophysiology might lead us to the Holy Grail. Still, I think there are reasons to be skeptical. There are good reasons to suppose that neurophysiological investigation contributes to cognitive explanation at best in virtue of constraining the information-processing structure of cognition. Of course this is a very large and significant role for it to play, but it may be over-optimistic to suppose that it can play some further explanatory role, taking us where information-processing theories cannot. If so, then neurophysiological accounts will be no more and no less successful at dealing with consciousness than information-processing accounts are.