What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Artificial intelligence
- Statistics
Marcus Kaiser focuses on Artificial neural network, Artificial intelligence, Neuroscience, Topology and Modular design.
His Artificial neural network study frequently involves adjacent topics like Theoretical computer science.
His research integrates issues of Node, Visual field, Position and Computer vision in his study of Artificial intelligence.
He conducts interdisciplinary study in the fields of Neuroscience and Concatenation through his works.
His research in Topology intersects with topics in Spatial organization, Connectome and Field.
His Complex network research incorporates themes from Neuroanatomy and Nerve net.
His most cited work include:
- Organization, development and function of complex brain networks (1622 citations)
- Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems (494 citations)
- A tutorial in connectome analysis: topological and spatial features of brain networks. (250 citations)
What are the main themes of his work throughout his whole career to date?
Marcus Kaiser mainly focuses on Neuroscience, Artificial neural network, Artificial intelligence, Connectome and Network analysis.
His work deals with themes such as Dementia with Lewy bodies and Dementia, which intersect with Neuroscience.
The various areas that Marcus Kaiser examines in his Artificial neural network study include Network topology, Biological neural network, Theoretical computer science and Topology.
His Artificial intelligence study incorporates themes from Node, Modularity, Spatial network and Pattern recognition.
His study focuses on the intersection of Connectome and fields such as Diffusion MRI with connections in the field of Temporal lobe.
In his papers, Marcus Kaiser integrates diverse fields, such as Network analysis, Complex network, Bioinformatics and Nerve net.
He most often published in these fields:
- Neuroscience (54.88%)
- Artificial neural network (29.77%)
- Artificial intelligence (28.37%)
What were the highlights of his more recent work (between 2018-2021)?
- Neuroscience (54.88%)
- Scalability (12.56%)
- Dementia (10.70%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Neuroscience, Scalability, Dementia, Use case and Software design.
In his articles, Marcus Kaiser combines various disciplines, including Neuroscience and Cell type.
His studies in Dementia integrate themes in fields like Disease progression, Centrality and Cognition.
Marcus Kaiser has included themes like Dynamic functional connectivity and Dynamic network analysis in his Cognition study.
His Use case research is multidisciplinary, relying on both Multi-core processor, Baseline, Distributed computing and Speedup.
His biological study spans a wide range of topics, including Artificial neural network, Computational model, Artificial intelligence and Synthetic biology.
Between 2018 and 2021, his most popular works were:
- Dysfunctional brain dynamics and their origin in Lewy body dementia. (29 citations)
- Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer's disease. (29 citations)
- A Scalable Test Suite for Continuous Dynamic Multiobjective Optimization (18 citations)
In his most recent research, the most cited papers focused on:
- Neuroscience
- Artificial intelligence
- Statistics
His main research concerns Neuroscience, Dementia, Scalability, Entrainment and Wilson–Cowan model.
His Neuroscience research is multidisciplinary, incorporating elements of White matter and Network dynamics.
His White matter research is multidisciplinary, incorporating perspectives in Precentral gyrus, Neurology and Atrophy.
His studies examine the connections between Dementia and genetics, as well as such issues in Resting state fMRI, with regards to EEG microstates, Functional magnetic resonance imaging and Ministate.
His Neuroimaging research includes themes of Disease progression, Centrality, Fornix, Diffusion MRI and Temporal lobe.
His Dementia with Lewy bodies research is multidisciplinary, incorporating elements of Dual regression, Dynamic functional connectivity, Cognition and Dynamic network analysis.
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