What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Neuroscience
- Statistics
His primary areas of investigation include Neuroscience, Artificial intelligence, Bayesian inference, Bayes' theorem and Dynamic causal modelling.
His work is dedicated to discovering how Neuroscience, Cognitive psychology are connected with Perception and Dopamine and other disciplines.
His Artificial intelligence study integrates concerns from other disciplines, such as Neuroimaging, Free parameter, Applied mathematics and Pattern recognition.
His Bayesian inference study combines topics in areas such as Conditional probability and Conditional probability distribution.
The study incorporates disciplines such as Cognition, Machine learning and Inference in addition to Bayes' theorem.
Klaas E. Stephan combines subjects such as Resting state fMRI, Theoretical computer science and Causal model with his study of Dynamic causal modelling.
His most cited work include:
- A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data (3194 citations)
- Empathic neural responses are modulated by the perceived fairness of others (1229 citations)
- Bayesian model selection for group studies. (1053 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Neuroscience, Artificial intelligence, Functional magnetic resonance imaging, Cognitive psychology and Bayesian inference.
The Artificial intelligence study combines topics in areas such as Machine learning, Causal model and Pattern recognition.
Klaas E. Stephan has researched Causal model in several fields, including Dynamic causal modelling and Brain mapping.
His study in Functional magnetic resonance imaging is interdisciplinary in nature, drawing from both Resting state fMRI, Internal medicine, Neuroimaging and Dorsolateral prefrontal cortex.
The concepts of his Cognitive psychology study are interwoven with issues in Perception, Cognition, Impulsivity, Antisaccade task and Reinforcement learning.
His Bayesian inference research is included under the broader classification of Bayesian probability.
He most often published in these fields:
- Neuroscience (68.89%)
- Artificial intelligence (34.14%)
- Functional magnetic resonance imaging (37.17%)
What were the highlights of his more recent work (between 2018-2021)?
- Neuroscience (68.89%)
- Functional magnetic resonance imaging (37.17%)
- Cognitive psychology (38.18%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Neuroscience, Functional magnetic resonance imaging, Cognitive psychology, Sensory system and Internal medicine.
His research is interdisciplinary, bridging the disciplines of Impulsivity and Neuroscience.
Klaas E. Stephan has included themes like Resting state fMRI, Aspirin, Generative model and Dorsolateral prefrontal cortex in his Functional magnetic resonance imaging study.
His Cognitive psychology research incorporates themes from Cognition, Anterior insula, Anxiety, Bayesian inference and Reinforcement learning.
His work investigates the relationship between Bayesian inference and topics such as Inference that intersect with problems in Bayesian probability, Schizophrenia, Paranoia and Situational ethics.
The study incorporates disciplines such as Interoception, Perception, Electroencephalography, Stimulus and Metacognition in addition to Sensory system.
Between 2018 and 2021, his most popular works were:
- Pathophysiological and cognitive mechanisms of fatigue in multiple sclerosis (45 citations)
- Focus of attention modulates the heartbeat evoked potential. (44 citations)
- Focus of attention modulates the heartbeat evoked potential. (44 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Neuroscience
- Statistics
His scientific interests lie mostly in Neuroscience, Impulsivity, Stimulus, Cognitive psychology and Sensory system.
Klaas E. Stephan frequently studies issues relating to Multiple sclerosis and Neuroscience.
Klaas E. Stephan works mostly in the field of Impulsivity, limiting it down to concerns involving Ventromedial prefrontal cortex and, occasionally, Ventral striatum and Disinhibition.
Klaas E. Stephan interconnects Speech recognition, Functional imaging, Categorical variable, Neuroplasticity and General linear model in the investigation of issues within Stimulus.
His biological study spans a wide range of topics, including Functional magnetic resonance imaging, Cognition and Reinforcement learning.
His work deals with themes such as Mismatch negativity, Inference, Perception and Bayesian inference, which intersect with Sensory system.
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