(ConsciousComputation) Computational components of conscious awareness
Lead Research Organisation:
University College London
Department Name: Experimental Psychology
Abstract
At any one moment in time we are aware of only a fraction of the information processed by our brains. We may be aware of the detail of a visual scene, a painting, or the words on a page, and yet remain unaware of our digestion, breathing or feel of the clothes on our skin. Even when conscious level is held constant - when we are awake, and attentive - the contents of awareness may vary, and do so in ways that are independent of other aspects of mental function - for instance, the experience of mind-wandering while driving, despite continuing to steer, change gear, and respond to changes in traffic. In recent decades, new tools and techniques have been developed to characterise dissociations between performance and awareness. However, the psychological, computational and neural mechanisms that enable awareness of mental contents remain poorly understood.
ConsciousComputation aims to reverse engineer how human awareness judgments are formed. I will test a new model that proposes that awareness depends on global, abstract representations of the presence or absence of mental contents. To test this theory I will combine psychophysics, computational model simulations and recent advances in human neuroimaging (including 7 Tesla fMRI and optically-pumped MEG) to visualise the neurocomputational components supporting awareness judgments at an unprecedented level of detail.
My proposal addresses a foundational challenge for 21st century science: why certain aspects of (biological or artificial) information processing are conscious, and others are not. An answer to this question will revolutionise how we understand the difference between aware and unaware mental states - with widespread ramifications for psychological theory, mental health treatments, and our understanding of personal-level autonomy and conscious thought. The findings of ConsciousComputation will open up new research frontiers and create a cognitive computational neuroscience of conscious awareness.
ConsciousComputation aims to reverse engineer how human awareness judgments are formed. I will test a new model that proposes that awareness depends on global, abstract representations of the presence or absence of mental contents. To test this theory I will combine psychophysics, computational model simulations and recent advances in human neuroimaging (including 7 Tesla fMRI and optically-pumped MEG) to visualise the neurocomputational components supporting awareness judgments at an unprecedented level of detail.
My proposal addresses a foundational challenge for 21st century science: why certain aspects of (biological or artificial) information processing are conscious, and others are not. An answer to this question will revolutionise how we understand the difference between aware and unaware mental states - with widespread ramifications for psychological theory, mental health treatments, and our understanding of personal-level autonomy and conscious thought. The findings of ConsciousComputation will open up new research frontiers and create a cognitive computational neuroscience of conscious awareness.
