The predictive basis of intensity and loudness processing

Generative models of perception, such as predictive coding, are mainstays of contemporary neuroscience.

Whilst there is abundant evidence and theory concerning what is predicted and when it is expected, little is known about how predictive models influence how strongly sensations are received (i.e. their intensity, or its perceptual counterparts such as loudness).

This proposal builds upon the handful of studies demonstrating the existence of predictive processing of intensity, and on my own published work demonstrating that pathological states of perception (i.e. tinnitus) can be understood, and objectified, as pervasive states of aberrant sensory predictions.

Its goal is a clear picture of the function and neurobiological basis of predictive intensity processing, which might subsequently lead to diagnostic and therapeutic avenues for clinical disorders such as tinnitus, chronic pain and fibromyalgia.

The investigative approach is multifaceted, examining a range of hierarchical levels through a progression of paradigm complexity, and using complementary neuroimaging modalities, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG) and functional MRI.

The predominant focus is auditory intensity (and loudness) in normal-hearing controls, with a subset of successful paradigms being run in clinical populations (to demonstrate the practical relevance of measures obtained), and in the somatosensory system (to demonstrate modality-independent commonalities).