How
consciousness emerges from the physical matter of the brain remains one of the
greatest mysteries of science. However, as a result of modern neuroscience and
brain imaging techniques, theories of the neural mechanisms underlying
conscious experience are starting to be proposed. For example, there are
theories concerning synchronous firing of neurons and consciousness and there
are explanations that focus on brain regions, e.g. the what and where pathways
from visual cortex. In addition, neural network modelling is playing an
important role in this debate. For example, explanations focussing on
synchronous neural spiking have been investigated using neural network
simulations.
There is considerable room for PhD level research on using neural networks to simulate theories of consciousness. One direction would be to develop models of how methods such as Rapid Serial Visual Presentation (RSVP), Continuous Flash Suppression and masking work in psychological studies of perception. It is well known that following a stimulus by a mask or presenting simultaneous competing stimulation under binocular presentation can prevent conscious experience of the stimulus. However, even though we have no awareness of the stimulus, our motor and cognitive systems still respond to it.
Despite the fact that such “subliminal” presentation has been empirically investigated very extensively and indeed many theories of its functioning exist, there is currently no comprehensive computational model of these phenomena. Thus, a possible avenue for a PhD in this area would be to construct neural network models of the competing theories of subliminal presentation in order to verify their validity. This research could be performed within the context of Bowman & Wyble’s Simultaneous Type/ Serial Token model of temporal attention and working memory encoding, which encapsulates a broad position on subliminality. It would also employ EEG and perhaps also simultaneous EEG and fMRI.
Bowman, H. and Wyble, B. (2007). The Simultaneous Type, Serial Token Model of Temporal Attention and Working Memory. Psychological Review 114:38-70.
Wyble, B. et al. (2011). Attentional Episodes in Visual Perception. Journal of Experimental Psychology: General 140:182-196.