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Knapen Lab

Computational Cognitive Neuroscience


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We are the Computational Cognitive Neuroscience Lab led by Tomas Knapen. The lab is equally based both at the Cognitive Psychology department at the Vrije Universiteit Amsterdam, and at the Spinoza Centre for Neuroimaging of the Royal Dutch Academy of Sciences.
We perform computational modeling, imaging, psychophysics, and eye movement experiments to investigate how activations in the brain give rise to our conscious awareness of ourselves and the world around us. Our "Spiel" is that we try to understand the structure of the brain's responses, even those of high cognitive function, in light of vision and other sensations. Specifically, we investigate how sensory information intermixes with cognitive factors such as attention, semantic processing, and reward. For more information on the topics we research, please see the science section, or click any of the topics further below on this page.

For information on the procedures that we use in the lab, please consult the lab wiki

And, if you want to follow the goings-on in the lab, you can follow the lab on Twitter:

Follow @tknapen

News from the lab:


  • TiCS review on visuospatial coding out!

    November 16, 2021

    Review on how the brain uses visual space as a fundamental coding mechanism


  • Divisive Normalization paper out in PNAS

    November 15, 2021

    Our new Divisive Normalisation population Receptive Field model explains responses throughout visual cortex.


  • Welcome to the lab, Ron, Ningkai, & Niklas!

    September 1, 2021

    New PhD and Master's students starting this month!


  • A new fMRI paradigm from the lab - Line-Scanning!

    August 20, 2021

    7T fMRI with 100ms TR and 200μm voxel size for "true" laminar fMRI


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Science Topics


Saccadic Adaptation


Plasticity in sensorimotor control


Population Receptive Field Mapping


Mapping how visual-spatial information is encoded in the human brain


Bistable Perception


Dynamic visual decision-making


Connective Field Modeling


Model-based mapping of Topographic Connectivity


Finite Impulse Response Fitting


Estimating event-related responses from time series signals

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