☰ Neurotree

Kai Görgen

Affiliations:

BCCN Berlin, Berlin, Berlin, Germany

Area:

Computational Neuroscience; Systems Neuroscience

Google:

Mean distance: 12.79 (cluster 29)

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Cross-listing: Computational Biology Tree

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Parents

Peter König	research assistant	2004-	Universität Osnabrück
Benjamin Blankertz	grad student		BCCN Berlin
Klaus-Robert Müller	grad student		BCCN Berlin
Carlo F. Reverberi	grad student		BCCN Berlin
John Dylan Haynes	grad student	2007-	BCCN Berlin
Michael Brecht	grad student	2007-2009	BCCN Berlin
Pascal Fries	grad student	2008-2009	Donders Center Nijmegen
Felix A. Wichmann	grad student	2007-2010	BCCN Berlin
Laurenz Wiskott	grad student	2007-2010	BCCN Berlin

Children

Collaborators

Martin N. Hebart	collaborator		BCCN Berlin
Joram Soch	collaborator		Bernstein Center for Computational Neuroscience (BCCN) Berlin
Doris Pischedda	collaborator	2012-2016	Charité Berlin

BETA: Related publications

Publications

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Weber S, Christophel T, Görgen K, et al. (2024) Working memory signals in early visual cortex are present in weak and strong imagers. Human Brain Mapping. 45: e26590
Uithol S, Görgen K, Pischedda D, et al. (2023) The effect of context and reason on the neural correlates of intentions. Heliyon. 9: e17231
Zahedi A, Artigas SO, Swaboda N, et al. (2023) Neural correlates of changing food choices while bypassing values. Neuroimage. 274: 120134
Soch J, Görgen K, Heinzle J, et al. (2023) A tightly controlled fMRI dataset for receptive field mapping in human visual cortex. Data in Brief. 47: 109018
Görgen K, Hebart MN, Allefeld C, et al. (2017) The same analysis approach: Practical protection against the pitfalls of novel neuroimaging analysis methods. Neuroimage
Pischedda D, Görgen K, Haynes JD, et al. (2017) Neural Representations of Hierarchical Rule Sets: the Human Control System Represents Rules Irrespective of the Hierarchical Level They Belong to. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Allefeld C, Görgen K, Haynes JD. (2016) Valid population inference for information-based imaging: From the second-level t-test to prevalence inference. Neuroimage
Schultze-Kraft M, Birman D, Rusconi M, et al. (2015) The point of no return in vetoing self-initiated movements. Proceedings of the National Academy of Sciences of the United States of America
Hebart MN, Görgen K, Haynes JD. (2014) The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data. Frontiers in Neuroinformatics. 8: 88
Haufe S, Meinecke F, Görgen K, et al. (2014) On the interpretation of weight vectors of linear models in multivariate neuroimaging. Neuroimage. 87: 96-110

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