His main research concerns Neuroscience, Schizophrenia, Bipolar disorder, Neuroimaging and Psychosis. Many of his studies on Neuroscience involve topics that are commonly interrelated, such as Magnetic resonance imaging. David C. Glahn interconnects Internal medicine and Corpus callosum in the investigation of issues within Schizophrenia.
His research in Bipolar disorder intersects with topics in Mood disorders, Clinical psychology and Thalamus. His Neuroimaging research incorporates themes from Myelin, Dementia, Brain size, Physiology and Splenium. His work deals with themes such as Meta-analysis, Amygdala and Bipolar I disorder, which intersect with Psychosis.
His primary areas of investigation include Neuroscience, Bipolar disorder, Cognition, Schizophrenia and Psychiatry. His Neuroscience study focuses mostly on Neuroimaging, Prefrontal cortex, Brain mapping, Working memory and Functional magnetic resonance imaging. In his research, Corpus callosum is intimately related to White matter, which falls under the overarching field of Neuroimaging.
The concepts of his Bipolar disorder study are interwoven with issues in Major depressive disorder, Resting state fMRI, Audiology and Clinical psychology. His Cognition research incorporates elements of Cognitive psychology and Genome-wide association study. Schizophrenia is often connected to Psychosis in his work.
David C. Glahn mainly focuses on Neuroimaging, Cognition, Schizophrenia, Copy-number variation and Neuroscience. His Neuroimaging study introduces a deeper knowledge of Psychiatry. His studies deal with areas such as Brain morphometry, Audiology and Clinical psychology as well as Cognition.
The study incorporates disciplines such as White matter, Bipolar disorder, Mood disorders and Data set in addition to Schizophrenia. His Bipolar disorder research focuses on Major depressive disorder and how it connects with Autism spectrum disorder. Many of his research projects under Neuroscience are closely connected to Correlation with Correlation, tying the diverse disciplines of science together.
David C. Glahn focuses on Neuroimaging, Schizophrenia, Neuroscience, Cortical surface and Major depressive disorder. While the research belongs to areas of Neuroimaging, David C. Glahn spends his time largely on the problem of Brain asymmetry, intersecting his research to questions surrounding Sample size determination, Depression, Magnetic resonance imaging, Meta-analysis and Thalamus. His Schizophrenia study combines topics from a wide range of disciplines, such as White matter, Machine learning, Physical medicine and rehabilitation and Artificial intelligence.
His work focuses on many connections between Neuroscience and other disciplines, such as Brain size, that overlap with his field of interest in Brain morphometry. His Major depressive disorder study integrates concerns from other disciplines, such as Bipolar disorder and Autism spectrum disorder. David C. Glahn has researched Cortex in several fields, including Genome-wide association study, Genetic variation, Brain mapping and Genetic architecture.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Correspondence of the brain's functional architecture during activation and rest.
Stephen M. Smith;Peter T. Fox;Karla L. Miller;David C. Glahn.
Proceedings of the National Academy of Sciences of the United States of America (2009)
Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions
Tara A. Niendam;Angela R. Laird;Kimberly L. Ray;Y. Monica Dean.
Cognitive, Affective, & Behavioral Neuroscience (2012)
Meta-analysis of 41 Functional Neuroimaging Studies of Executive Function in Schizophrenia
Michael J. Minzenberg;Angela R. Laird;Sarah Thelen;Cameron S. Carter.
Archives of General Psychiatry (2009)
Cortical Thickness or Grey Matter Volume? The Importance of Selecting the Phenotype for Imaging Genetics Studies
Anderson M. Winkler;Peter V. Kochunov;John Blangero;Laura Almasy.
Behavioral interpretations of intrinsic connectivity networks
Angela R. Laird;P. Mickle Fox;Simon B. Eickhoff;Jessica A. Turner.
Journal of Cognitive Neuroscience (2011)
ALE meta-analysis: Controlling the false discovery rate and performing statistical contrasts
Angela R. Laird;P. Mickle Fox;Cathy J. Price;David C. Glahn.
Human Brain Mapping (2005)
Beyond hypofrontality: A quantitative meta-analysis of functional neuroimaging studies of working memory in schizophrenia
David C. Glahn;J. Daniel Ragland;Adir Abramoff;Jennifer Barrett.
Human Brain Mapping (2005)
Meta-analysis of gray matter anomalies in schizophrenia: application of anatomic likelihood estimation and network analysis.
David C. Glahn;Angela R. Laird;Ian Ellison-Wright;Sarah M. Thelen.
Biological Psychiatry (2008)
The anatomy of first-episode and chronic schizophrenia: an anatomical likelihood estimation meta-analysis.
M.R.C.P. Ian Ellison-Wright;David C. Glahn;Angela R. Laird;B.S. Sarah M. Thelen.
American Journal of Psychiatry (2008)
Identification of common variants associated with human hippocampal and intracranial volumes
Jason L Stein;Sarah E Medland;Sarah E Medland;Alejandro Arias Vasquez;Alejandro Arias Vasquez;Derrek P Hibar.
Nature Genetics (2012)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: