Using high-field functional and quantitative structural MRI to reveal the dynamics of auditory statistical learning and representational change

Fred Dick (primary)
Psychological Sciences
Martina Callaghan (secondary)
Institute of Neurology


Our brains are exceptionally good at extracting important information from the sea of unfamiliar complex sounds around us. However, we are only beginning to how the brain restructures itself to accomplish this learning, and how particular stages of learning may be supported by different neurobiological mechanisms. This PhD project tackles these issues by combining intensive, computationally-informed auditory training paradigms with functional and structural MRI at high field strengths. The project will test hypotheses about the emergence and consolidation of new auditory representations, as well as the relationship of learning success to transient or sustained changes in brain microstructure.


Carey, D., Caprini, F., Allen, M., Lutti, A., Weiskopf, N., Rees, G.,Callaghan, M, & Dick, F. (2018). Quantitative MRI provides markers of intra-, inter-regional, and age-related differences in young adult cortical microstructure. NeuroImage, 182, 429–440.

Carey, D., Rosen, S., Krishnan, S., Pearce, M. T., Shepherd, A., Aydelott, J., & Dick, F. (2015). Generality and specificity in the effects of musical expertise on perception and cognition. Cognition, 137, 81–105.

Dick, F. K., Lehet, M. I., Callaghan, M. F., Keller, T. A., Sereno, M. I., & Holt, L. L. (2017). Extensive Tonotopic Mapping across Auditory Cortex Is Recapitulated by Spectrally Directed Attention and Systematically Related to Cortical Myeloarchitecture. Journal of Neuroscience, 37(50), 12187–12201.

Holt, L. L., Tierney, A. T., Guerra, G., Laffere, A., & Dick, F. (2018). Dimension-selective attention as a possible driver of dynamic, context-dependent re-weighting in speech processing. Hearing Research, 366, 50–64.

Callaghan, M. F., Helms, G., Lutti, A., Mohammadi, S., & Weiskopf, N. (2014). A general linear relaxometry model of R1 using imaging data. Magnetic Resonance in Medicine, 73(3), 1309–1314.

Animal disease, health and welfare
Area of Biology
Techniques & Approaches
BiophysicsImage ProcessingMathematics / StatisticsSimulation / Modelling