Nikolaus Kriegeskorte
Nikolaus Kriegeskorte
Professor of Psychology and Neuroscience, Columbia University
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Cited by
Cited by
Representational similarity analysis-connecting the branches of systems neuroscience
N Kriegeskorte, M Mur, PA Bandettini
Frontiers in systems neuroscience 2, 249, 2008
Circular analysis in systems neuroscience: the dangers of double dipping
N Kriegeskorte, WK Simmons, PSF Bellgowan, CI Baker
Nature neuroscience 12 (5), 535-540, 2009
Information-based functional brain mapping
N Kriegeskorte, R Goebel, P Bandettini
Proceedings of the National Academy of Sciences 103 (10), 3863-3868, 2006
Matching categorical object representations in inferior temporal cortex of man and monkey
N Kriegeskorte, M Mur, DA Ruff, R Kiani, J Bodurka, H Esteky, K Tanaka, ...
Neuron 60 (6), 1126-1141, 2008
Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation
SM Khaligh-Razavi, N Kriegeskorte
PLoS computational biology 10 (11), e1003915, 2014
Deep neural networks: a new framework for modeling biological vision and brain information processing
N Kriegeskorte
Annual review of vision science 1 (1), 417-446, 2015
Representational geometry: integrating cognition, computation, and the brain
N Kriegeskorte, RA Kievit
Trends in cognitive sciences 17 (8), 401-412, 2013
A deep learning framework for neuroscience
BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ...
Nature neuroscience 22 (11), 1761-1770, 2019
A toolbox for representational similarity analysis
H Nili, C Wingfield, A Walther, L Su, W Marslen-Wilson, N Kriegeskorte
PLoS computational biology 10 (4), e1003553, 2014
Best practices in data analysis and sharing in neuroimaging using MRI
TE Nichols, S Das, SB Eickhoff, AC Evans, T Glatard, M Hanke, ...
Nature neuroscience 20 (3), 299-303, 2017
Individual faces elicit distinct response patterns in human anterior temporal cortex
N Kriegeskorte, E Formisano, B Sorger, R Goebel
Proceedings of the National Academy of Sciences 104 (51), 20600-20605, 2007
Comparison of multivariate classifiers and response normalizations for pattern-information fMRI
M Misaki, Y Kim, PA Bandettini, N Kriegeskorte
Neuroimage 53 (1), 103-118, 2010
Neural correlates of trust
F Krueger, K McCabe, J Moll, N Kriegeskorte, R Zahn, M Strenziok, ...
Proceedings of the National Academy of Sciences 104 (50), 20084-20089, 2007
Revealing representational content with pattern-information fMRI—an introductory guide
M Mur, PA Bandettini, N Kriegeskorte
Social cognitive and affective neuroscience 4 (1), 101-109, 2009
Reliability of dissimilarity measures for multi-voxel pattern analysis
A Walther, H Nili, N Ejaz, A Alink, N Kriegeskorte, J Diedrichsen
Neuroimage 137, 188-200, 2016
Cognitive computational neuroscience
N Kriegeskorte, PK Douglas
Nature neuroscience 21 (9), 1148-1160, 2018
Neural network models and deep learning
N Kriegeskorte, T Golan
Current Biology 29 (7), R231-R236, 2019
Cortical capacity constraints for visual working memory: dissociation of fMRI load effects in a fronto-parietal network
DEJ Linden, RA Bittner, L Muckli, JA Waltz, N Kriegeskorte, R Goebel, ...
Neuroimage 20 (3), 1518-1530, 2003
Representational dynamics of object vision: the first 1000 ms
T Carlson, DA Tovar, A Alink, N Kriegeskorte
Journal of vision 13 (10), 1-1, 2013
Recurrence is required to capture the representational dynamics of the human visual system
TC Kietzmann, CJ Spoerer, LKA Sörensen, RM Cichy, O Hauk, ...
Proceedings of the National Academy of Sciences 116 (43), 21854-21863, 2019
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