Team - MULTISENSORY PERCEPTION, LEARNING AND ATTENTION GROUP

Principal Investigator

Uta Noppeney

Uta is heading the Multisensory Perception, Learning
and Attention lab.

For further information see:
https://www.ru.nl/english/people/noppeney-u/

POST DOCs

Agata Wlaszczyk

about me

In my work, I develop Bayesian computational models to understand how humans combine sensory information and express their confidence in the perception of complex stimuli, such as speech.

Giulio
Degano
(external)

PHDs

Rao
Xie

about me

I am interested in metacognition, particularly its role in perceptual decision-making and the mechanisms of meta-learning, using computational modeling and neuroimaging.

Claire
Pleche

about me

I'm interested in adaptive behavior and decision-making under uncertainty. In my PhD, I study how humans form predictions across senses using psychophysics, M/EEG and Bayesian modeling.

Danting
Meng

about me

I am currently working on statistical learning and prediction error, in multisensory context.

Tommaso
Rinaldini

Kun
Dong

about me

I study top-down control in multisensory perception in many aspects, including attention control, TMS manipulation, and patient studies, where I look for causalities, brain mechanisms, and temporal dynamics.

Wenshu
Lou

about me

I mainly study cross-modal recalibration and meta-cognition from the computational modeling perspective, specifically how causal inference would influence auditory spatial recalibration and how it is quantified under a Bayesian framework.

Xin
Weng

Qiong
Wu

Jochem
Beurskens

about me

I study how humans effectively address the cross-modal binding problem. We come across this problem in many everyday situations, such as when we try to understand a friend in a noisy pub. I am particularly interested in the temporal dynamics of this process, and how the brain performs these complex calculations with its limited resources. In my research use of psychophysics, and Bayesian modelling.

Luis
Glenzer

about me

I decided to pursue a PhD because I am fascinated by the brain as a highly efficient machine that enables us to navigate the world successfully. Therefore, I am excited to study the it's perceptual computations that enable this process. Furthermore, I am deeply interested in consciousness, which shares key properties with our ability to access these computations and form confidence in subsequent actions. In my project, I combine multisensory fMRI experiments with Bayesian modeling and machine-learning.