Computational neuroimaging strategies for single patient predictions

NeuroImage

Volumn 145, Issue , 2017, Pages 180-199

  Stephan, K E ^a,b,c   Schlagenhauf, F ^d,e   Huys, Q J M ^a   Raman, S ^a   Aponte, E A ^a   Brodersen, K H ^a   Rigoux, L ^a,c   Moran, R J ^b,f   Daunizeau, J ^a,g   Dolan, R J ^b,h   Friston, K J ^b   Heinz, A ^d,i  

^a UNIVERSITY OF ZURICH   (Switzerland)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c MAX PLANCK INSTITUTE FOR NEUROLOGICAL RESEARCH   (Germany)

^d CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^e MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

^f Virgina Institute of Technology   (United States)

^g ICM   (France)

^h MAX PLANCK UCL CENTRE FOR COMPUTATIONAL PSYCHIATRY AND AGEING RESEARCH   (United Kingdom)

ⁱ HUMBOLDT UNIVERSITY   (Germany)

Author keywords

Bayesian; Classification; Clustering; Computational psychiatry; EEG; fMRI; Generative embedding; Generative model; Model comparison; Model evidence; Model selection; Translational neuromodeling

Indexed keywords

ARTICLE; BAYES THEOREM; BIOPHYSICS; CLINICAL ASSESSMENT; CLINICAL DECISION SUPPORT SYSTEM; DATA ANALYSIS; ELECTROENCEPHALOGRAPHY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; IMAGE ANALYSIS; MACHINE LEARNING; MAGNETOENCEPHALOGRAPHY; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MENTAL DISEASE; NEUROANATOMY; NEUROIMAGING; NEUROLOGIC DISEASE; NONHUMAN; OUTCOME ASSESSMENT; PREDICTION; PRIORITY JOURNAL; STATISTICAL ANALYSIS; STATISTICAL MODEL; BRAIN DISEASE; DIAGNOSTIC IMAGING; PROCEDURES; THEORETICAL MODEL;

BRAIN DISEASES; HUMANS; MENTAL DISORDERS; MODELS, THEORETICAL; NEUROIMAGING;

EID: 84977097785     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2016.06.038     Document Type: Article

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