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  The neural and physiological mechanisms of conscious experience

   School of Psychology

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  Dr D Cruse, Dr H Bowman  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

We are all familiar with subjective experience - for example, the experience of enjoying a favourite piece of music. Indeed, subjective experience is the essence of culture and of being human, and its absence or reduction leads to severe consequences for health, wellbeing, social relationships, and quality of life. The philosopher Thomas Nagel called these subjective experiences “something that it is like” to be conscious. Despite considerable understanding of the neurocognitive processes that support perception of that auditory stimulus, we understand little about the neural basis of the associated subjective experience of what it is like to be conscious. Indeed, a great deal of neural processing of sensory stimuli can (and does) occur without an associated subjective experience. What, then, 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. These so-called prediction error minimisation models of perception provide compelling explanations of a range of perceptual phenomena and associated neural data. While some consider that subjective experience emerges late in the neural processing pipeline after the probabilistic mechanisms have run their course, this early/late pre-conscious/conscious distinction is not consistent with all available data, including that collected by the proposed PhD supervisors. Thus, the relationship between predictive neural mechanisms and subjective experience remains a key target for study. Within the field of self-awareness, similar predictive processing models have also been proposed, which frame the subjective experience of presence and emotion as the result of the brain attempting to accurately predict the 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. For example, some evidence links processing of consciously perceived events with accelerations in heart-rate.

The objective of the PhD project is to characterise the concurrent neural and physiological events that accompany subjective experience in healthy individuals, and thereby begin to delineate the “what it is like” of consciousness. To this end, the student will develop cognitive paradigms to isolate specific forms of subjective experience, for example, the experience of comprehending a piece of speech or of feeling your heartbeat. The student 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 the electrocardiogram and respiratory rate to investigate the neural and physiological correlates of these experiences. Furthermore, the student will investigate their multimodal data in the context of existing and novel computational models of prediction error minimisation.

Funding Notes

Funding (stipend and fees) provided by the Midlands Integrative Biosciences Training Partnership. To apply, visit here: (Follow links for info on applying to projects at the University of Birmingham)


Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11(2), 127–138.

Raimondo, F., et al. (2017). Brain-heart interactions reveal consciousness in non-communicating patients. Annals of Neurology, 88(4), 578-591.

Shirazibeheshti, A., et al. (2018). Placing meta-stable states of consciousness within the predictive coding hierarchy: The deceleration of the accelerated prediction error. Consciousness and Cognition, 63, 123-142.

Wacongne, C., Changeux, J. P., & Dehaene, S. (2012). A Neuronal Model of Predictive Coding Accounting for the Mismatch Negativity. Journal of Neuroscience, 32(11), 3665-3678.

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