Hogendoorn/Landau joint PhD projects

Dr Hinze Hogendoorn & Dr Ayelet Landau

UoM Dr Hinze Hogendoorn: hhogendoorn@unimelb.edu.au

Senior Research Fellow, Melbourne School of Psychological Sciences, The University of Melbourne

timinglab.org

HUJI A/Prof Ayelet Landau: Ayelet.Landau@mail.huji.ac.il

Assistant Professor, Dept of Cognitive Sciences and Psychology, Hebrew University of Jerusalem

landaulab.com

 

Submissions should include:

a) a cover letter addressing the motivation for the application and the selection criteria

b) a curriculum vitae with the relevant information  (including previous publications)

c) a transcript of recent university marks and certificates of previous degree(s).

For any questions or for submission of applications please email Hinze Hogendoorn at hhogendoorn@unimelb.edu.au. Applications will be considered until the position is filled.

 

Project 1: Home base – UoM

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 successful candidate will start this project at UoM, where he/she will be trained by PI Hogendoorn in the theoretical basis of predictive coding and related concepts and start collecting psychophysical and EEG data. He/she 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 his/her candidature, the student 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.

Year 1: UoM – training in the theoretical basis of predictive coding and related concepts and start collecting psychophysical and EEG data

Year 2: HUJI – training in time-frequency analyses of both behaviour and EEG signals, learning to identify the signatures of rhythmic neural mechanisms in those signals as well as carry out further analyses

Year 3: UoM –  finalise the thesis and integrate the empirical work with the theoretical framework of predictive coding

 

The successful candidate will have:

– An Undergraduate (with Honours) or Master’s degree in Cognitive (neuro)science, Biology, Psychology, Computer Science, or related discipline

– An affinity with programming, including demonstrable programming skill in Matlab

– Excellent English communication skills (written and spoken)

– Intrinsic motivation, initiative, and an ability to work independently

– An affinity for international collaboration

– Previous research experience with experimental psychology or cognitive neuroscience techniques (psychophysics, EEG, fMRI, TMS etc) is desirable.

 

Project 2: Home base – HUJI

Decoding the rhythms of cognition

This project investigates the representational content of brain rhythms: the actual information contained in each of the cycles of cortical excitability that the brain produces during perception. Better understanding the content of rhythmic fluctuations in physiology and behavior will allow us to elucidate the underlying neural architecture. To address this aim we will apply multivariate pattern analysis (MVPA) techniques to time-resolved EEG recordings to investigate the contents of each cycle in a given oscillation.

The successful candidate will start this project at HUJI, where he/she will be trained by PI Landau in neural oscillations, the possible neural mechanisms that might underlie them, and the psychophysical and neuroimaging paradigms that can be applied to study them. He/she will design and collect the first psychophysical and EEG data, and then transfer to UoM for Year 2, where he/she will be trained by PI Hogendoorn in MVPA analysis of EEG data. Finally, in Year 3 the candidate will return to HUJI to finalise his/her thesis and integrate the experimental findings with the state-of-the-art in our understanding of brain rhythms under the supervision of PI Landau.

Year 1: HUJI – training in neural oscillations, the possible neural mechanisms that might underlie them, and the psychophysical and neuroimaging paradigms that can be applied to study them

Year 2: UoM – training MVPA analysis of EEG data

Year 3: HUJI – finalise thesis and integrate the experimental findings with the state-of-the-art in our understanding of brain rhythms

 

The successful candidate will have:

– An Undergraduate (with Honours) or Master’s degree in Cognitive (neuro)science, Biology, Psychology, Computer Science, or related discipline

– An affinity with programming, including demonstrable programming skill in Matlab

– Excellent English communication skills (written and spoken)

– Intrinsic motivation, initiative, and an ability to work independently

– An affinity for international collaboration

– Previous research experience with experimental psychology or cognitive neuroscience techniques (psychophysics, EEG, fMRI, TMS etc) is desirable.