World's Best Scientists 2026 revealed!
Nikolaus Kriegeskorte

Nikolaus Kriegeskorte

D-Index & Metrics

Neuroscience

D-Index
74
Citations
33312
World Ranking
2063
National Ranking
982

Engineering and Technology

D-Index
66
Citations
30866
World Ranking
1365
National Ranking
447

Overview

Nikolaus Kriegeskorte is affiliated with Columbia University in the United States. Their research spans the fields of neuroscience and computer science, with a particular focus on cognitive neuroscience, computer vision and pattern recognition, and artificial intelligence. They have contributed extensively to topics such as neural dynamics and brain function, face recognition and perception, functional brain connectivity studies, visual perception and processing mechanisms, visual attention and saliency detection, child and animal learning development, and action observation and synchronization.

Their notable recent publications include:

  • The neuroconnectionist research programme, 2023, published in Nature Reviews. Neuroscience
  • Neural tuning and representational geometry, 2021, published in Nature Reviews. Neuroscience
  • Individual differences among deep neural network models, 2020, published in Nature Communications
  • An ecologically motivated image dataset for deep learning yields better models of human vision, 2021, published in Proceedings of the National Academy of Sciences
  • Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision, 2020, published in PLoS Computational Biology

Nikolaus Kriegeskorte frequently collaborates with co-authors including Tal Golan, Benjamin Peters, Tim C. Kietzmann, Katherine R. Storrs, and Heiko H. Schütt. These collaborations are reflected in numerous publications across their research domains.

Their work has been published extensively in venues such as:

  • Journal of Vision
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • Zenodo (CERN European Organization for Nuclear Research)

The research by Nikolaus Kriegeskorte addresses complex mechanisms underlying brain function and perception, employing computational models and empirical data to explore how neural systems support cognitive processes. Their interdisciplinary approach integrates methods from neuroscience, machine learning, and psychology to investigate visual recognition, neural coding, and learning development.

Best Publications

  • Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

    Nikolaus Kriegeskorte;Marieke Mur;Peter A Bandettini

  • Circular analysis in systems neuroscience: the dangers of double dipping.

    Nikolaus Kriegeskorte;W Kyle Simmons;Patrick S F Bellgowan;Chris I Baker

  • Information-based functional brain mapping

    Nikolaus Kriegeskorte;Rainer Goebel;Peter Bandettini

  • Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey

    Nikolaus Kriegeskorte;Marieke Mur;Marieke Mur;Douglas A. Ruff;Roozbeh Kiani

  • Deep supervised, but not unsupervised, models may explain IT cortical representation.

    Seyed Mahdi Khaligh-Razavi;Nikolaus Kriegeskorte

  • Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing

    Nikolaus Kriegeskorte

  • Representational geometry: integrating cognition, computation, and the brain

    Nikolaus Kriegeskorte;Rogier A. Kievit;Rogier A. Kievit

  • A deep learning framework for neuroscience

    Blake A Richards;Timothy P Lillicrap;Philippe Beaudoin;Yoshua Bengio;Yoshua Bengio

  • A toolbox for representational similarity analysis.

    Hamed Nili;Cai Arran Wingfield;Alexander Walther;Li Su

  • Best practices in data analysis and sharing in neuroimaging using MRI.

    Thomas E Nichols;Samir Das;Samir Das;Simon B Eickhoff;Simon B Eickhoff;Alan C Evans;Alan C Evans

  • Reliability of dissimilarity measures for multi-voxel pattern analysis.

    Alexander Walther;Alexander Walther;Hamed Nili;Naveed Ejaz;Arjen Alink

  • Individual faces elicit distinct response patterns in human anterior temporal cortex

    Nikolaus Kriegeskorte;Elia Formisano;Bettina Sorger;Rainer Goebel

  • Comparison of multivariate classifiers and response normalizations for pattern-information fMRI.

    Masaya Misaki;Youn Kim;Youn Kim;Peter A. Bandettini;Nikolaus Kriegeskorte;Nikolaus Kriegeskorte

  • Cognitive computational neuroscience

    Nikolaus Kriegeskorte;Pamela K. Douglas

  • Neural network models and deep learning.

    Nikolaus Kriegeskorte;Tal Golan

  • Neural correlates of trust

    Frank Krueger;Kevin McCabe;Jorge Moll;Nikolaus Kriegeskorte

  • Revealing representational content with pattern-information fMRI—an introductory guide

    Marieke Mur;Peter A. Bandettini;Nikolaus Kriegeskorte

  • Representational dynamics of object vision: The first 1000 ms

    Thomas Carlson;Thomas Carlson;David A. Tovar;Arjen Alink;Nikolaus Kriegeskorte

  • Cortical capacity constraints for visual working memory: dissociation of fMRI load effects in a fronto-parietal network.

    David Edmund Johannes Linden;Robert A. Bittner;Lars Muckli;James A. Waltz

  • Recurrence is required to capture the representational dynamics of the human visual system

    Tim C. Kietzmann;Tim C. Kietzmann;Courtney J. Spoerer;Lynn K. A. Sörensen;Radoslaw M. Cichy

  • Deep neural networks: a new framework for modelling biological vision and brain information processing

    Nikolaus Kriegeskorte

Frequent Co-Authors

Peter A. Bandettini
Peter A. Bandettini National Institutes of Health
James B. Rowe
James B. Rowe University of Cambridge
Thomas A. Carlson
Thomas A. Carlson University of Sydney
Kendrick Kay
Kendrick Kay University of Minnesota
Rainer Goebel
Rainer Goebel Maastricht University
Jörn Diedrichsen
Jörn Diedrichsen University of Western Ontario
Pascal Belin
Pascal Belin Aix-Marseille University
Wolf Singer
Wolf Singer Ernst Strüngmann Institute for Neuroscience
Olaf Hauk
Olaf Hauk MRC Cognition and Brain Sciences Unit

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