Perception is a central means by which we come to represent and be aware of particulars in the world. I argue that an adequate account of perception must distinguish between what one perceives and what one's perceptual experience is of or about. Through capacities for visual completion, one can be visually aware of particular parts of a scene that one nevertheless does not see. Seeing corresponds to a basic, but not exhaustive, way in which one can be visually aware of (...) an item. I discuss how the relation between seeing and visual awareness should be explicated within a representational account of the mind. Visual awareness of an item involves a primitive kind of reference: one is visually aware of an item when one's visual perceptual state succeeds in referring to that particular item and functions to represent it accurately. Seeing, by contrast, requires more than successful visual reference. Seeing depends additionally on meta-semantic facts about how visual reference happens to be fixed. The notions of seeing and of visual reference are both indispensable to an account of perception, but they are to be characterized at different levels of representational explanation. (shrink)

The Emergic Cognitive Model (ECM) is a unified computational model of visual filling-in based on the Emergic Network architecture. The Emergic Network was designed to help realize systems undergoing continuous change. In this thesis, eight different filling-in phenomena are demonstrated under a regime of continuous eye movement (and under static eye conditions as well). -/- ECM indirectly demonstrates the power of unification inherent with Emergic Networks when cognition is decomposed according to finer-grained functions supporting change. These can interact to raise (...) additional emergent behaviours via cognitive re-use, hence the Emergic prefix throughout. Nevertheless, the model is robust and parameter free. Differential re-use occurs in the nature of model interaction with a particular testing paradigm. -/- ECM has a novel decomposition due to the requirements of handling motion and of supporting unified modelling via finer functional grains. The breadth of phenomenal behaviour covered is largely to lend credence to our novel decomposition. -/- The Emergic Network architecture is a hybrid between classical connectionism and classical computationalism that facilitates the construction of unified cognitive models. It helps cutting up of functionalism into finer-grains distributed over space (by harnessing massive recurrence) and over time (by harnessing continuous change), yet simplifies by using standard computer code to focus on the interaction of information flows. Thus while the structure of the network looks neurocentric, the dynamics are best understood in flowcentric terms. Surprisingly, dynamic system analysis (as usually understood) is not involved. An Emergic Network is engineered much like straightforward software or hardware systems that deal with continuously varying inputs. Ultimately, this thesis addresses the problem of reduction and induction over complex systems, and the Emergic Network architecture is merely a tool to assist in this epistemic endeavour. -/- ECM is strictly a sensory model and apart from perception, yet it is informed by phenomenology. It addresses the attribution problem of how much of a phenomenon is best explained at a sensory level of analysis, rather than at a perceptual one. As the causal information flows are stable under eye movement, we hypothesize that they are the locus of consciousness, howsoever it is ultimately realized. (shrink)