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The neural and physiological mechanisms of the conscious experience

Lead Research Organisation: University of Birmingham
Department Name: School of Psychology

Abstract

Despite considerable understanding of the neurocognitive processes that support perception of external stimuli, we understand little about the neural basis of the associated subjective experience of what it is like to be conscious. A great deal of neural processing of sensory stimuli can occur without an associated subjective experience, so what is the neural basis of subjective experience? Within the field of perception, several theories consider the brain to be a probabilistic machine that is constantly trying to more accurately predict its sensory input. In this way, the perceptual experience is thought to be shaped both by the sensory input itself, and the individual's expectations about what that input is most likely to be. Similarly, predictive processing models have been proposed in the field of self-awareness, which frame the subjective experience of presence and emotion as the result of the brain attempting to accurately predict activity of the body's internal organs. In this sense, the 'what it is like' of experience may be reflected in the brain's evaluation of the body's response to sensory input, e.g., some evidence links processing of consciously perceived events with accelerations in heartrate.
This project aims to characterise the concurrent neural and physiological events that accompany subjective experience in healthy individuals. We will develop cognitive paradigms to isolate specific forms of subjective experience, e.g. the experience of comprehending a piece of speech or feeling your heartbeat. We will apply state-of-the-art methods of electrophysiology including event-related potentials, time-frequency analyses, and source reconstruction, alongside recordings of peripheral physiology including electrocardiogram and respiration to investigate neural and physiological correlates of these experiences. This multimodal data will be explored in the context of existing and novel computational models of predition error minimisation.

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/T00746X/1 30/09/2020 29/09/2028
2595336 Studentship BB/T00746X/1 03/10/2021 02/10/2025