The rhythm of predictive coding
This project investigates the role of brain oscillations in the mechanisms involved in predictive coding. Predictive coding is an influential framework of cortical organisation. However, the canonical predictive coding model treats cortical processing as a stationary process: input remains constant and the sensory hierarchy converges on a minimum-error computational solution. Of course, the real world is dynamic and ever-changing, and existing predictive coding models could not handle time-variant input. However, earlier this year, PI Hogendoorn proposed an extension to the canonical predictive coding framework that not only allows predictive coding to process time-variant input, but that would allow also the network to compensate for the delays that inevitably accumulate during neural transmission (Hogendoorn & Burkitt, eNeuro 2019). This project investigates how this might be achieved at the neural level.
The project will commence at UoM, where the graduate researcher will be trained by PI Hogendoorn in the theoretical basis of predictive coding and related concepts and start collecting psychophysical and EEG data. They will transfer to HUJI after year 1 to receive additional training in time-frequency analyses of both behaviour and EEG signals in the lab of PI Landau, and learn to identify the signatures of rhythmic neural mechanisms in those signals as well as carry out further analyses. In the final year of candidature, the graduate researcher will return to UoM to finalise the thesis and integrate the empirical work with the theoretical framework of predictive coding under the guidance of PI Hogendoorn.
Dr Hinze Hogendoorn – Senior Research Fellow, Melbourne School of Psychological Sciences, The University of Melbourne
A/Prof Ayelet Landau – Assistant Professor, Dept of Cognitive Sciences and Psychology, Hebrew University of Jerusalem