Work

Common component classification: What can we learn from machine learning?

Year: 2010

Type: article

Source: NeuroImage

DOI: 10.1016/j.neuroimage.2010.05.065

Authors: Ariana Anderson, Jennifer S. Labus, Eduardo P. Vianna, Emeran A. Mayer, Mark S. Cohen

Institution: University of California, Los Angeles

Language: English

Topic: Functional Brain Connectivity Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute on Drug Abuse, National Institute of Diabetes and Digestive and Kidney Diseases, National Center for Complementary and Integrative Health

Awards: Effective connectivity of central response to IBS, Comprehensive Training in Neuroimaging Fundamentals and Applications, Mind/Brain/Body Interactions in Stress-Related Disorders, Perception and Modulation of Visceral Sensation, Real-Time Automated Detection of Craving States with fMRI and EEG, G3405585365, Real-Time Automated Detection of Craving States with fMRI and EEG, G5660074825, G7970454297, G8770586347, G9000217100

OpenAlex ID: W2045362471

FWCI:

Cites: 37

Cited by: 4

Related to: 10