PhD positions: Reading the mind's eye

Are you interested in working within a dynamic team to investigate the neural representations and computations underlying visual mental imagery? Do you want to understand why the experienced vividness of mental images is so different across individuals? Then join the ERC-funded project 'MINDSEYE' as a PhD student.

Job Description
Despite extensive research, we still do not have a comprehensive computational understanding of the mechanisms of the mind’s eye: How do we create mental images? And why are some people better at it than others? How do the various brain regions involved in mental imagery contribute to the unified percept in our mind's eye? Why do we experience imagery so differently ranging from no to extremely vivid mental images?

In the Advanced ERC project "Reading the mind's eye - AI-inspired personalised brain models of mental imagery" of Prof. Rainer Goebel, a novel perspective on mental imagery is proposed, viewing it as a personalised computational process that takes into account individual brain characteristics. The task of this computational process is to progressively transform abstract object descriptions (semantic input) into visual representations (sensory-like output) through feedback connections in the brain’s processing hierarchy.

To unravel the stages of this conversion process, the team will employ ultra-high field fMRI (7 Tesla and beyond) to measure neural activity across the brain at an unparalleled level of detail. This allows to relate mental imagery and its experienced vividness to individual characteristics of cortical layers in feedback and feedforward pathways. Together the team will integrate the sub-millimetre fMRI data into personalised AI-inspired neural network models, test causal contributions of relevant brain areas to mental imagery, and develop a brain-computer interface to train the vividness of mental imagery. While all team members interact and collaborate on all aspects of the project, your work as a PhD student will mainly focus on one approach:
Ultra-high field fMRI to measure activity in feedforward and feedback pathways. You will design psychophysics and fMRI experiments to investigate mental imagery. Besides that you will become a certified user to run ultra-high field fMRI experiments
Non-invasive brain stimulation with TMS to assess the contribution of specific areas to mental image generation. You will design psychophysics, TMS and fMRI experiments to investigate mental imagery. Besides that you will become a certified user to run 3 Tesla fMRI and TMS experiments.
Development of personalized AI inspired brain models informed by fMRI and TMS data. You will develop “text-to-image” generative neural network models of mental imagery. Besides that you will develop laminar neural network architectures separating cortical feedforward and feedback processing streams.
Creation of brain-computer interfaces to recreate mental images and to develop a vividness neurofeedback training program. You will develop a BCI that creates mental images from 7 Tesla laminar fMRI data. Besides that your will become a certified user to run closed-loop ultra-high field fMRI experiments.

You will be part of the ERC ‘MINDSEYE’ team which will be embedded in a very open and cooperative group of colleagues and Pis forming the "Vision" lab (also known as the ‘computational architecture of visual processing streams’ section), which is led by Rainer Goebel. The Vision lab is embedded in the Department of Cognitive Neuroscience at Maastricht University. The Vision lab as well as the whole department work in the spirit of team science, in a very cooperative, collegial, and interdisciplinary work climate. We value and actively engage in local, national and international collaborations. With our empirical, theoretical and computational expertise we aim to contribute to our understanding of the psychological and neural mechanisms of the mind.

Within your chosen project you will have the following responsibilities:
Develop your research experiments/ models.
Analyse obtained data.
Contribute in and integrate your data in AI-inspired models.
Present at international conferences.
Write scientific papers.
Teach in master and bachelor level courses.
Contribute to a nice and open group atmosphere.