Online research in philosophy

I suggest that neurophysiological data, usually interpreted in cognitivist terms, is actually more supportive of dynamic frameworks such as that of Thelen et al. I outline a model of embodied action used to interpret neural data from frontal and parietal cortex, and suggest that it bears strong similarity to the framework described in the target article.

Harnad's main argument can be roughly summarised as follows: due to Searle's Chinese Room argument, symbol systems by themselves are insufficient to exhibit cognition, because the symbols are not grounded in the real world, hence without meaning. However, a symbol system that is connected to the real world through transducers receiving sensory data, with neural nets translating these data into sensory categories, would not be subject to the Chinese Room argument. Harnad's article is not only the starting point for the present debate, but is also a contribution to a longlasting discussion about such questions as: Can a computer think? If yes, would this be solely by virtue of its program? Is the Turing Test appropriate for deciding whether a computer thinks?

Pylyshyn rightly argues that the neuroscientific data supporting the involvement of the visual system in mental imagery is largely irrelevant to the question of the format of imagistic representation. The purpose of this commentary is to support this claim with a further argument.

Concepts are the elementary units of reason and linguistic meaning. They are conventional and relatively stable. As such, they must somehow be the result of neural activity in the brain. The questions are: Where? and How? A common philosophical position is that all concepts—even concepts about action and perception—are symbolic and abstract, and therefore must be implemented outside the brain’s sensory-motor system. We will argue against this position using (1) neuroscientific evidence; (2) results from neural computation; and (3) results about the nature of concepts from cognitive linguistics. We will propose that the sensory-motor system has the right kind of structure to characterise both sensory-motor and more abstract concepts. Central to this picture are the neural theory of language and the theory of cogs, according to which, brain structures in the sensory-motor regions are exploited to characterise the so-called “abstract” concepts that constitute the meanings of grammatical constructions and general inference patterns.

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language. Key Words: efference copies; emulation theory of representation; forward models; Kalman filters; motor control; motor imagery; perception; visual imagery.

Discriminating behavior depends on neural representations in which the sensory activity patterns guiding different responses are decorrelated from one another. Visual information can often be parsimoniously transformed into these behavioral bridge-locus representations within neuro-computational visuo-spatial maps. Isomorphic inverse-optical world representation is not the goal. Nevertheless, such useful transformations can involve neural filling-in. Such a subpersonal representation of information is consistent with personal-level vision theory.

Our subjective sensory experiences are thought to be heavily shaped by interactions between expectations and incoming sensory information. However, the neural mechanisms supporting these interactions remain poorly understood. By using combined psychophysical and functional MRI techniques, brain activation related to the intensity of expected pain and experienced pain was characterized. As the magnitude of expected pain increased, activation increased in the thalamus, insula, prefrontal cortex, anterior cingulate cortex (ACC) and other brain regions. Pain-intensity-related brain activation was identified in a widely distributed set of brain regions but overlapped partially with expectation-related activation in regions, including the anterior insula and ACC. When expected pain was manipulated, expectations of decreased pain powerfully reduced both the subjective experience of pain and activation of pain-related brain regions, such as the primary somatosensory cortex, insular cortex, and ACC. These results confirm that a mental representation of an impending sensory event can significantly shape neural processes that underlie the formulation of the actual sensory experience and provide insight as to how positive expectations diminish the severity of chronic disease states.

Representation and content in some (actual) theories of perception -- Representation in perception and cognition : task analysis, psychological functions, and rule instantiation -- Perception as unconscious inference -- Representation and constraints : the inverse problem and the structure of visual space -- On perceptual constancy -- Getting objects for free (or not) : the philosophy and psychology of object perception -- Color perception and neural encoding : does metameric matching entail a loss of information? -- Objectivity and subjectivity revisited : color as a psychobiological property -- Sense data and the mind body problem -- The reality of qualia -- The sensory core and the medieval foundations of early modern perceptual theory -- Postscript (2008) on Ibn al-Haytham's (Alhacen's) theory of vision -- Attention in early scientific psychology -- Psychology, philosophy, and cognitive science : reflections on the history and philosophy of experimental psychology -- What can the mind tell us about the brain? : psychology, neurophysiology, and constraint -- Introspective evidence in psychology.

It is clear that visual imagery is somehow significantly visual. Some theorists, like Kosslyn, claim that the visual nature of visualisations derives from features of the neural processes which underlie those episodes. Pylyshyn claims, however, that it may merely reflect special features of the contents which we grasp when we visualise things. This paper discusses and rejects Pylyshyn's own attempts to identify the respects in which the contents of visualisations are notably visual. It then offers a novel and very different account of what is distinctively sensory about the contents of sensory images. The paper's alternative account is used in explaining various pieces of phenomenological and behavioural data concerning visualisation. Finally, it is tentatively suggested that the proposed account of the contents of sensory images may also shed light upon some of the neurological data involving visualisation and sensory imagery more generally.

Based on theoretical considerations of Aurell (1979) and Block (1995), we argue that object recognition awareness is distinct from purely sensory awareness and that the former is mediated by neuronal activities in areas that are separate and distinct from cortical sensory areas. We propose that two of the principal functions of neuronal activities in sensory cortex, which are to provide sensory awareness and to effect the computations that are necessary for object recognition, are dissociated. We provide examples of how this dissociation might be achieved and argue that the components of the neuronal activities which carry the computations do not directly enter the awareness of the subject. The results of these computations are sparse representations (i.e., vector or distributed codes) which are activated by the presentation of particular sensory objects and are essentially engrams for the recognition of objects. These final representations occur in the highest order areas of sensory cortex; in the visual analyzer, the areas include the anterior part of the inferior temporal cortex and the perirhinal cortex. We propose, based on lesion and connectional data, that the two areas in which activities provide recognition awareness are the temporopolar cortex and the medial orbitofrontal cortex. Activities in the temporopolar cortex provide the recognition awareness of objects learned in the remote past (consolidated object recognition), and those in the medial orbitofrontal cortex provide the recognition awareness of objects learned in the recent past. The activation of the sparse representation for a particular sensory object in turn activates neurons in one or both of these regions of cortex, and it is the activities of these neurons that provide the awareness of recognition of the object in question. The neural circuitry involved in the activation of these representations is discussed.