PhD, MSc, MA (Cantab)
Senior Postdoctoral Research Scientist
I am interested in how neurons represent and process sensory information, particularly under naturalistic conditions. To investigate this, I use electrophysiological recording to measure how neurons respond to complex sounds, and then build computational models to understand those responses.
I obtained my PhD at Cambridge University with David Tolhurst, working on computational models of neurons in the visual system. I continued this work as a postdoc with Jack Gallant at the University of California Berkeley. In 2006, I moved to Oxford to work in Andy King's group, to work on neural coding in the auditory system.
I lecture for the MSc in Neuroscience and the BA in Biomedical Sciences. I also give tutorials on sensory neuroscience and neural coding to second- and third-year medical students.
Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.
Harper NS. et al, (2016), PLoS Comput Biol, 12
Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing.
Willmore BDB. et al, (2016), J Neurosci, 36, 280 - 289
Measuring the Performance of Neural Models.
Schoppe O. et al, (2016), Front Comput Neurosci, 10
Hearing in noisy environments: noise invariance and contrast gain control.
Willmore BDB. et al, (2014), J Physiol, 592, 3371 - 3381
Constructing noise-invariant representations of sound in the auditory pathway.
Rabinowitz NC. et al, (2013), PLoS Biol, 11