What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Neuroscience
- Statistics
Her primary areas of study are Neuroscience, Cognition, Brain mapping, Complex network and Human brain.
The concepts of her Neuroscience study are interwoven with issues in Cluster analysis and Set.
Her Cognition study incorporates themes from Motor skill, Control reconfiguration, Cognitive science, Network science and Dynamic network analysis.
Her Brain mapping study combines topics in areas such as Resting state fMRI, Frontal lobe and Default mode network.
Her Complex network study integrates concerns from other disciplines, such as Graph theory, Data mining, Modularity and Magnetoencephalography.
Her research integrates issues of Cerebral cortex, Multivariate statistics, Diffusion MRI and Neuroimaging in her study of Human brain.
Her most cited work include:
- Small-World Brain Networks (1757 citations)
- Dynamic reconfiguration of human brain networks during learning. (1061 citations)
- Functional Connectivity and Brain Networks in Schizophrenia (999 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of investigation include Neuroscience, Cognition, Artificial intelligence, Network science and Cognitive science.
Her study focuses on the intersection of Neuroscience and fields such as White matter with connections in the field of Diffusion MRI.
Her work is dedicated to discovering how Cognition, Dynamic network analysis are connected with Network dynamics and other disciplines.
Her research in Artificial intelligence intersects with topics in Machine learning, Theoretical computer science and Pattern recognition.
Danielle S. Bassett has included themes like Network architecture and Graph theory in her Network science study.
Her Resting state fMRI study frequently links to related topics such as Connectome.
She most often published in these fields:
- Neuroscience (32.53%)
- Cognition (21.31%)
- Artificial intelligence (15.71%)
What were the highlights of her more recent work (between 2019-2021)?
- Neuroscience (32.53%)
- Cognition (21.31%)
- Cognitive science (10.58%)
In recent papers she was focusing on the following fields of study:
Danielle S. Bassett spends much of her time researching Neuroscience, Cognition, Cognitive science, Network science and Controllability.
She regularly links together related areas like Citation in her Neuroscience studies.
Her work carried out in the field of Cognition brings together such families of science as Connectome and Neuroimaging.
Her Cognitive science research includes elements of Network architecture, Structure, Computational model and Set.
Her Network science research is multidisciplinary, incorporating perspectives in Modularity, Mental health, Psychiatry, Co morbidity and Curiosity.
Her Controllability study combines topics from a wide range of disciplines, such as Cognitive psychology, Theoretical computer science, Centrality, Metric and Network controllability.
Between 2019 and 2021, her most popular works were:
- Questions and controversies in the study of time-varying functional connectivity in resting fMRI (111 citations)
- The extent and drivers of gender imbalance in neuroscience reference lists. (83 citations)
- Development of structure–function coupling in human brain networks during youth (56 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Neuroscience
- Statistics
Danielle S. Bassett focuses on Neuroscience, Cognition, Cognitive science, Network science and Structure.
Danielle S. Bassett merges Neuroscience with Downstream in her research.
Her Cognition research incorporates themes from Network dynamics, Controllability and Brain mapping.
Her studies deal with areas such as Network architecture, Artificial neural network, Default mode network and Computational model as well as Cognitive science.
Her Network science research integrates issues from Neural function, Graph theory and Session.
Her work in Structure covers topics such as Information theory which are related to areas like Telecommunications network, Divergence, Complex network and Information processing.
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