What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Neuroscience
- Magnetic resonance imaging
His primary scientific interests are in Neuroscience, Magnetic resonance imaging, Functional magnetic resonance imaging, Cognitive psychology and Human brain.
Neuroscience is closely attributed to Brain size in his research.
His Magnetic resonance imaging research includes themes of Cerebral cortex, EEG-fMRI and Epilepsy surgery.
His Functional magnetic resonance imaging research includes elements of Audiology, Face perception, Fusiform face area, Temporal dynamics of music and language and Visual cortex.
His work deals with themes such as Neuroscience of multilingualism, Working memory, Prefrontal cortex, Cognition and First language, which intersect with Cognitive psychology.
In his study, Pattern recognition, Iterative reconstruction, Artificial intelligence and Neuroimaging is strongly linked to Gyrification, which falls under the umbrella field of Human brain.
His most cited work include:
- A network of occipito-temporal face-sensitive areas besides the right middle fusiform gyrus is necessary for normal face processing. (534 citations)
- Early alteration of structural and functional brain development in premature infants born with intrauterine growth restriction (367 citations)
- A Surface-Based Approach to Quantify Local Cortical Gyrification (349 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Neuroscience, Magnetic resonance imaging, White matter, Electroencephalography and Diffusion MRI.
His study in Neuroscience focuses on Human brain, Functional magnetic resonance imaging, Epilepsy, Temporal lobe and Gyrification.
The concepts of his Functional magnetic resonance imaging study are interwoven with issues in Lateralization of brain function, Cognitive psychology, Face perception, Fusiform face area and Functional imaging.
He interconnects Neuroimaging, Artificial intelligence and Pattern recognition in the investigation of issues within Gyrification.
The study incorporates disciplines such as Cerebral cortex, Internal medicine, Nuclear medicine, Pathology and Nuclear magnetic resonance in addition to Magnetic resonance imaging.
His White matter research is multidisciplinary, incorporating elements of Segmentation, Endocrinology and Brainstem.
He most often published in these fields:
- Neuroscience (30.07%)
- Magnetic resonance imaging (20.26%)
- White matter (13.73%)
What were the highlights of his more recent work (between 2012-2021)?
- Neuroscience (30.07%)
- Materials science (5.88%)
- Human brain (8.50%)
In recent papers he was focusing on the following fields of study:
François Lazeyras spends much of his time researching Neuroscience, Materials science, Human brain, White matter and Tractography.
Neuroscience is closely attributed to Medical physics in his study.
His Human brain research includes elements of Brain atlas, Gyrification and Brain segmentation.
His study in White matter is interdisciplinary in nature, drawing from both Topology, Stepwise regression, Effects of sleep deprivation on cognitive performance and Brain organization.
His work carried out in the field of Tractography brings together such families of science as Gyrus, Temporal lobe, Epilepsy and Lobe.
The Magnetic resonance imaging study combines topics in areas such as Basal ganglia, Internal medicine, Oncology and Neuropsychology.
Between 2012 and 2021, his most popular works were:
- Total activation: fMRI deconvolution through spatio-temporal regularization (74 citations)
- Dielectric pads and low- B1+ adiabatic pulses: Complementary techniques to optimize structural T1w whole-brain MP2RAGE scans at 7 tesla (43 citations)
- Micro-Structural Brain Alterations in Aviremic HIV+ Patients with Minor Neurocognitive Disorders: A Multi-Contrast Study at High Field (35 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Magnetic resonance imaging
- Neuroscience
His scientific interests lie mostly in Data mining, Materials science, Neuroscience, Context and Neurocognitive.
His research integrates issues of Deconvolution, Regularization, Imaging phantom and Visual perception in his study of Data mining.
Deconvolution is closely attributed to Magnetic resonance imaging in his work.
The concepts of his Magnetic resonance imaging study are interwoven with issues in Resting state fMRI, Voxel, Artificial intelligence and Pattern recognition.
His Neuroscience research integrates issues from Medical physics and Multimodal imaging.
His Neurocognitive research is multidisciplinary, incorporating perspectives in Gyrus, Connectome, Connectomics and Tractography, Diffusion MRI.
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