What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Artificial intelligence
- Statistics
Neuroscience, Electroencephalography, Resting state fMRI, Artificial intelligence and Functional magnetic resonance imaging are his primary areas of study.
The Neuroscience study combines topics in areas such as Lyapunov exponent and Brain model.
Viktor K. Jirsa has researched Electroencephalography in several fields, including Working memory, Complex system, Local field potential and Epilepsy.
His studies in Resting state fMRI integrate themes in fields like Functional networks, Neuroimaging, Diffusion MRI and Brain mapping.
The various areas that Viktor K. Jirsa examines in his Artificial intelligence study include Dynamical systems theory, Nerve net, Cortical surface, Magnetoencephalography and Dynamics.
His Functional magnetic resonance imaging research is multidisciplinary, relying on both Data mining, Functional connectivity and Model order.
His most cited work include:
- Emerging concepts for the dynamical organization of resting-state activity in the brain. (1150 citations)
- Emerging concepts for the dynamical organization of resting-state activity in the brain. (1150 citations)
- The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields (726 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Neuroscience, Artificial intelligence, Electroencephalography, Resting state fMRI and Connectome.
His Neuroscience study typically links adjacent topics like Diffusion MRI.
The concepts of his Artificial intelligence study are interwoven with issues in Dynamical systems theory, Machine learning, Pattern recognition and Dynamics.
His Electroencephalography study integrates concerns from other disciplines, such as Neurophysiology and Functional magnetic resonance imaging.
The Resting state fMRI study combines topics in areas such as Default mode network, Functional connectivity, Brain mapping and Dynamics.
His study in Connectome is interdisciplinary in nature, drawing from both Brain network, Network model and Neuroinformatics.
He most often published in these fields:
- Neuroscience (52.37%)
- Artificial intelligence (26.81%)
- Electroencephalography (22.71%)
What were the highlights of his more recent work (between 2018-2021)?
- Neuroscience (52.37%)
- Epilepsy (14.20%)
- Connectome (16.72%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Neuroscience, Epilepsy, Connectome, Artificial intelligence and Neuroimaging.
His is doing research in Brain network, Electroencephalography, Resting state fMRI, Intracranial Electroencephalography and Human brain, both of which are found in Neuroscience.
His work investigates the relationship between Electroencephalography and topics such as Statistical physics that intersect with problems in Representation.
His Resting state fMRI research is multidisciplinary, relying on both Voltage-sensitive dye, Functional magnetic resonance imaging, Cog and Dynamics.
His study looks at the intersection of Epilepsy and topics like Artificial neural network with Spherical harmonics and Basis function.
His Artificial intelligence research incorporates themes from Machine learning and Functional connectivity.
Between 2018 and 2021, his most popular works were:
- The Scientific Case for Brain Simulations (47 citations)
- Transmission time delays organize the brain network synchronization. (33 citations)
- Controlling seizure propagation in large-scale brain networks. (33 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Artificial intelligence
- Statistics
Viktor K. Jirsa mainly focuses on Neuroscience, Resting state fMRI, Epilepsy, Connectome and Electroencephalography.
Many of his studies involve connections with topics such as Dynamical systems theory and Neuroscience.
His Resting state fMRI research is multidisciplinary, incorporating elements of Functional magnetic resonance imaging and Functional connectivity.
His research in Epilepsy intersects with topics in Organizing principle, Cognitive psychology, Brain activity and meditation and Bifurcation theory.
His Connectome study combines topics from a wide range of disciplines, such as Virtual mouse, Functional organization and Structural connectome.
In his study, Stereoelectroencephalography, Human brain, Brain mapping and Feature is strongly linked to Diffusion MRI, which falls under the umbrella field of Electroencephalography.
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