2022 - Research.com Rising Star of Science Award
Danilo Bzdok focuses on Neuroscience, Neuroimaging, Brain mapping, Cognition and Cortex. His work deals with themes such as Meta-analysis, Resting state fMRI, Inference and Neuroinformatics, which intersect with Neuroimaging. He has researched Inference in several fields, including Activation likelihood estimation, Data mining and Contrast.
The Data mining study combines topics in areas such as Probability distribution, Resampling, False discovery rate and Word error rate. His Brain mapping research includes themes of Voxel and Task-positive network. His Cognition research incorporates elements of Cognitive psychology and Amygdala.
His main research concerns Cognition, Neuroscience, Neuroimaging, Artificial intelligence and Cognitive psychology. His study focuses on the intersection of Cognition and fields such as Cognitive science with connections in the field of Social neuroscience. His work in Neuroscience is not limited to one particular discipline; it also encompasses Schizophrenia.
The study incorporates disciplines such as Meta-analysis, Functional magnetic resonance imaging, Inference and Data science in addition to Neuroimaging. Danilo Bzdok has included themes like Statistical hypothesis testing, Data mining and Biomedicine in his Inference study. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Functional connectivity.
His scientific interests lie mostly in Cognition, Neuroscience, Artificial intelligence, Cognitive psychology and Neuroimaging. In the subject of general Cognition, his work in Inferior parietal lobe is often linked to Specialization, thereby combining diverse domains of study. In the field of Neuroscience, his study on Neural substrate, Connectomics and Social cognition overlaps with subjects such as Association.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Prefrontal cortex. He combines subjects such as Variation, Social support, Brain network and Loneliness with his study of Cognitive psychology. Danilo Bzdok undertakes interdisciplinary study in the fields of Neuroimaging and Simple through his works.
Danilo Bzdok mainly focuses on Machine learning, Artificial intelligence, Cognitive psychology, Cognition and Neuroimaging. The various areas that Danilo Bzdok examines in his Machine learning study include Enhanced Data Rates for GSM Evolution, Sample size determination and Regression. His Artificial intelligence study integrates concerns from other disciplines, such as Contrast and Multivariate statistics.
His study on Cognition is covered under Neuroscience. His Neuroscience study frequently links to other fields, such as Diffusion MRI. His Neuroimaging research includes elements of Diagnostic marker, Gender identity and Functional brain.
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Activation likelihood estimation meta-analysis revisited.
Simon B. Eickhoff;Danilo Bzdok;Danilo Bzdok;Angela R. Laird;Florian Kurth.
Statistics versus machine learning
Danilo Bzdok;Naomi Altman;Martin Krzywinski.
Nature Methods (2018)
Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy.
Danilo Bzdok;Leonhard Schilbach;Kai Vogeley;Karla Schneider.
Brain Structure & Function (2012)
Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation.
Simon B. Eickhoff;Thomas E. Nichols;Angela R. Laird;Felix Hoffstaedter.
Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation
Simon B. Eickhoff;Danilo Bzdok;Danilo Bzdok;Angela R. Laird;Christian Roski.
An Investigation of the Structural, Connectional, and Functional Subspecialization in the Human Amygdala
Danilo Bzdok;Angela R. Laird;Karl Zilles;Peter T. Fox.
Human Brain Mapping (2013)
Machine Learning for Precision Psychiatry: Opportunities and Challenges.
Danilo Bzdok;Danilo Bzdok;Andreas Meyer-Lindenberg.
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging (2018)
Characterization of the temporo-parietal junction by combining data-driven parcellation, complementary connectivity analyses, and functional decoding
Danilo Bzdok;Robert Langner;Leonhard Schilbach;Oliver Jakobs.
Connectivity-based parcellation: Critique and implications
Simon B. Eickhoff;Simon B. Eickhoff;Bertrand Thirion;Gaël Varoquaux;Danilo Bzdok.
Human Brain Mapping (2015)
The role of the right temporoparietal junction in attention and social interaction as revealed by ALE meta-analysis
S C Krall;Claudia Rottschy;E Oberwelland;Danilo Bzdok.
Brain Structure & Function (2015)
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