What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Functional magnetic resonance imaging
- Magnetic resonance imaging
His primary scientific interests are in Neuroscience, Artificial intelligence, Machine learning, Orbitofrontal cortex and Prefrontal cortex.
His Artificial intelligence research incorporates elements of Cognitive science and Multimodal neuroimaging.
His work on Granger causality and Model selection is typically connected to Causality as part of general Machine learning study, connecting several disciplines of science.
His Granger causality research includes elements of Brain mapping and Autoregressive model.
His Autoregressive model research incorporates themes from Region of interest, Regression analysis and Voxel.
His study in Prefrontal cortex is interdisciplinary in nature, drawing from both Cognitive psychology, Sensory system and Superior parietal lobule.
His most cited work include:
- Mapping directed influence over the brain using Granger causality and fMRI. (832 citations)
- Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping. (573 citations)
- Effective connectivity: Influence, causality and biophysical modeling (282 citations)
What are the main themes of his work throughout his whole career to date?
Alard Roebroeck mainly investigates Neuroscience, Diffusion MRI, Magnetic resonance imaging, Artificial intelligence and Human brain.
His work on Brain mapping, Functional magnetic resonance imaging, Premovement neuronal activity and Posterior parietal cortex as part of general Neuroscience research is often related to Subthalamic nucleus, thus linking different fields of science.
His Functional magnetic resonance imaging study incorporates themes from Cognition, Brain activity and meditation and Orbitofrontal cortex.
His work deals with themes such as White matter and Algorithm, which intersect with Diffusion MRI.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Granger causality and Computer vision.
The Granger causality study combines topics in areas such as Cognitive science and Autoregressive model.
He most often published in these fields:
- Neuroscience (32.67%)
- Diffusion MRI (25.74%)
- Magnetic resonance imaging (14.85%)
What were the highlights of his more recent work (between 2018-2021)?
- Human brain (11.88%)
- Materials science (4.95%)
- Diffusion MRI (25.74%)
In recent papers he was focusing on the following fields of study:
Alard Roebroeck focuses on Human brain, Materials science, Diffusion MRI, Biomedical engineering and Magnetic resonance imaging.
His research in Diffusion MRI intersects with topics in Isotropy and Multi contrast.
His studies deal with areas such as Paraformaldehyde and Fixation as well as Biomedical engineering.
Alard Roebroeck works in the field of Magnetic resonance imaging, focusing on White matter in particular.
Alard Roebroeck is studying Tractography, which is a component of White matter.
Alard Roebroeck has researched Tractography in several fields, including Neuroimaging and Scanner.
Between 2018 and 2021, his most popular works were:
- The mesoSPIM initiative: open-source light-sheet microscopes for imaging cleared tissue (57 citations)
- Ex vivo diffusion MRI of the human brain: Technical challenges and recent advances (37 citations)
- Characterizing microstructural tissue properties in multiple sclerosis with diffusion MRI at 7 T and 3 T: The impact of the experimental design (23 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Functional magnetic resonance imaging
- Magnetic resonance imaging
Diffusion MRI, Human brain, Ex vivo, White matter and Magnetic resonance imaging are his primary areas of study.
His Human brain study is related to the wider topic of Neuroscience.
Ex vivo overlaps with fields such as Tractography, Ultra high resolution and Biomedical engineering in his research.
His work in the fields of Fractional anisotropy overlaps with other areas such as Materials science.
His work on Axonal pathology as part of general Magnetic resonance imaging research is frequently linked to Kurtosis, thereby connecting diverse disciplines of science.
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