Nikolaus Kriegeskorte spends much of his time researching Artificial intelligence, Neuroscience, Functional magnetic resonance imaging, Brain mapping and Temporal cortex. His work on Computational model, Artificial neural network and Voxel as part of general Artificial intelligence research is frequently linked to Systems neuroscience, thereby connecting diverse disciplines of science. His research integrates issues of Univariate, Circular analysis and Selection in his study of Neuroscience.
Nikolaus Kriegeskorte has researched Functional magnetic resonance imaging in several fields, including Neuronal population and Brain region. His work in Brain mapping addresses issues such as Neuroimaging, which are connected to fields such as Occipitotemporal cortex, Multivoxel pattern analysis, Brain morphometry and Functional brain. His biological study spans a wide range of topics, including Cognitive neuroscience of visual object recognition, Communication, Categorization, Categorical variable and Pattern recognition.
His primary scientific interests are in Artificial intelligence, Pattern recognition, Functional magnetic resonance imaging, Neuroscience and Perception. His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Visual cortex and Computer vision. His Pattern recognition research incorporates elements of Representation, Cognitive neuroscience of visual object recognition and Temporal cortex.
His Functional magnetic resonance imaging research includes elements of Stimulus and Contrast. Brain mapping is the focus of his Neuroscience research. His Perception study combines topics in areas such as Cognitive psychology, Brain activity and meditation, Cognition and Face.
His primary areas of investigation include Artificial intelligence, Perception, Pattern recognition, Functional magnetic resonance imaging and Artificial neural network. In his articles, Nikolaus Kriegeskorte combines various disciplines, including Artificial intelligence and Feed forward. His studies in Perception integrate themes in fields like Caudate nucleus and Cognitive psychology.
Nikolaus Kriegeskorte combines subjects such as Representation, Face and Statistical hypothesis testing with his study of Pattern recognition. His Functional magnetic resonance imaging research is included under the broader classification of Neuroscience. His research investigates the connection with Artificial neural network and areas like Computation which intersect with concerns in Prior probability and Special case.
His scientific interests lie mostly in Artificial intelligence, Artificial neural network, Pattern recognition, Feed forward and Cognitive neuroscience of visual object recognition. As part of his studies on Artificial intelligence, Nikolaus Kriegeskorte often connects relevant subjects like Functional magnetic resonance imaging. The Artificial neural network study combines topics in areas such as Base, Computation and Perception.
Nikolaus Kriegeskorte has included themes like Nonparametric statistics, Statistical hypothesis testing, Test statistic and Parametric statistics in his Pattern recognition study. His work carried out in the field of Cognitive neuroscience of visual object recognition brings together such families of science as Stimulus, Cognition, Generative grammar, MNIST database and Discriminative model. His research in Inference intersects with topics in Prior probability, Mahalanobis distance, Special case, Normal distribution and Neuroscience.
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Circular analysis in systems neuroscience: the dangers of double dipping.
Nikolaus Kriegeskorte;W Kyle Simmons;Patrick S F Bellgowan;Chris I Baker.
Nature Neuroscience (2009)
Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience
Nikolaus Kriegeskorte;Marieke Mur;Peter A Bandettini.
Frontiers in Systems Neuroscience (2008)
Information-based functional brain mapping
Nikolaus Kriegeskorte;Rainer Goebel;Peter Bandettini.
Proceedings of the National Academy of Sciences of the United States of America (2006)
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.
PLOS Computational Biology (2014)
Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing
Annual Review of Vision Science (2015)
Representational geometry: integrating cognition, computation, and the brain
Nikolaus Kriegeskorte;Rogier A. Kievit;Rogier A. Kievit.
Trends in Cognitive Sciences (2013)
A toolbox for representational similarity analysis.
Hamed Nili;Cai Arran Wingfield;Alexander Walther;Li Su.
PLOS Computational Biology (2014)
Individual faces elicit distinct response patterns in human anterior temporal cortex
Nikolaus Kriegeskorte;Elia Formisano;Bettina Sorger;Rainer Goebel.
Proceedings of the National Academy of Sciences of the United States of America (2007)
Comparison of multivariate classifiers and response normalizations for pattern-information fMRI.
Masaya Misaki;Youn Kim;Youn Kim;Peter A. Bandettini;Nikolaus Kriegeskorte;Nikolaus Kriegeskorte.
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