Kai Görgen

BCCN Berlin, Berlin, Berlin, Germany 
Computational Neuroscience; Systems Neuroscience
"Kai Görgen"
Mean distance: 12.79 (cluster 29)
Cross-listing: Computational Biology Tree

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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
Haufe S, Meinecke F, Blankertz B, et al. (2014) Interpreting parameters of multivariate linear models in neuroimaging F1000research. 5
Haufe S, Meinecke F, Gorgen K, et al. (2014) Parameter interpretation, regularization and source localization in multivariate linear models Proceedings - 2014 International Workshop On Pattern Recognition in Neuroimaging, Prni 2014
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