Cargando…
Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures
Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient's self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness,...
Autores principales: | Cetin, Mustafa S., Houck, Jon M., Rashid, Barnaly, Agacoglu, Oktay, Stephen, Julia M., Sui, Jing, Canive, Jose, Mayer, Andy, Aine, Cheryl, Bustillo, Juan R., Calhoun, Vince D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5070283/ https://www.ncbi.nlm.nih.gov/pubmed/27807403 http://dx.doi.org/10.3389/fnins.2016.00466 |
Ejemplares similares
-
Combination of Resting State fMRI, DTI, and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA
por: Sui, Jing, et al.
Publicado: (2013) -
Multimodal Neuroimaging in Schizophrenia: Description and Dissemination
por: Aine, C. J., et al.
Publicado: (2017) -
Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects
por: Rashid, Barnaly, et al.
Publicado: (2014) -
Towards a brain‐based predictome of mental illness
por: Rashid, Barnaly, et al.
Publicado: (2020) -
Schizophrenia Shows Disrupted Links between Brain Volume and Dynamic Functional Connectivity
por: Abrol, Anees, et al.
Publicado: (2017)