The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI

NeuroImage

Volumn 129, Issue , 2016, Pages 320-334

  Lorenz, Romy ^a   Monti, Ricardo Pio ^a   Violante, Inês R ^a   Anagnostopoulos, Christoforos ^a   Faisal, Aldo A ^a   Montana, Giovanni ^a,b   Leech, Robert ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

Bayesian optimization; Brain computer interface; Closed loop; Experimental design; Machine learning; Real time fMRI

Indexed keywords

ADULT; ALGORITHM; ARTICLE; AUDITORY STIMULATION; BAYESIAN LEARNING; CONTRAST TO NOISE RATIO; ELECTROENCEPHALOGRAM; EXPERIMENTAL DESIGN; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HUMAN; HUMAN EXPERIMENT; MALE; NORMAL HUMAN; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SIMULATION; VISUAL STIMULATION; BAYES THEOREM; BRAIN; BRAIN COMPUTER INTERFACE; BRAIN MAPPING; IMAGE PROCESSING; MACHINE LEARNING; NEUROSCIENCE; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PROCEDURES;

ADULT; ALGORITHMS; BAYES THEOREM; BRAIN; BRAIN MAPPING; BRAIN-COMPUTER INTERFACES; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MACHINE LEARNING; MAGNETIC RESONANCE IMAGING; MALE; NEUROSCIENCES;

EID: 84957078157     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2016.01.032     Document Type: Article

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