Welcome to the page of Dr. Tim Christian Kietzmann. I am an Assistant Professor at the Donders Institute for Brain, Cognition and Behaviour (Radboud University), and a Research Associate at the MRC Cognition and Brain Science Unit (University of Cambridge). I investigate principles of neural information processing using tools from machine learning and deep learning, applied to neuroimaging data recorded at high temporal (EEG/MEG) and spatial (fMRI) resolution. Feel free to contact me with any questions or paper requests, and follow me on twitter (@TimKietzmann) for latest updates.

Research Interests

Cognitive Neuroscience meets Machine Learning. Our research group aims to understand the computational processes by which the brain and artificial agents can efficiently and robustly derive meaning from the world around us. We ask how the brain acquires versatile representations from the statistical regularities in the input, how sensory information is dynamically transformed in the cortical network, and which information is extracted by the brain to support higher-level cognition. To find answers to these questions, we develop and employ machine learning techniques to discover and model structure in high-dimensional neural data.

As a target modality, we focus on vision, the most dominant of our senses both neurally and perceptually. To gain insight into the intricate system that enables us to see, the group advances along two interconnected lines of research: machine learning for discovery in neuroimaging data, and deep neural network modelling. This interdisciplinary work combines machine learning, computational neuroscience, computer vision, and semantics. Our work is therefore at the heart of the emerging field of cognitive computational neuroscience.

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Twitter Feed

Twitter friends - a while back I asked for your input on resources for writing and presenting. We have compiled the input I received at https://t.co/NhXyHY7we4. Please feel free to share with your colleagues and trainees. Thank you again for your help.

The neuromatch 2.0 conference is starting Monday! We've got several talks, two Oxford-style debates (one on the role of learning & the other on the usefulness of Bayesian models), a panel on data-sharing & a GUIS event. But if you want participate, you've got to register 👇 https://t.co/VWL5jz4qPG

Really strong auditory bistable stimulus. You can also make it say "brain needle" and "green storm". https://t.co/7ezn2uO8MI

How does the brain keep track of its uncertainty? We found neural gain variability to represent stimulus uncertainty across the visual hierarchy, and explain these findings with a stochastic variant of divisive normalization: https://t.co/DvN1pMAY97

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