Use of a Bayesian maximum-likelihood classifier to generate training data for brain-machine interfaces (Journal of Neural Engineering (2011) 8, (046009) DOI: 10.1088/1741-2560/8/4/046009);Use of a Bayesian maximum-likelihood classifier to generate training data for brain-machine interfaces

Journal of Neural Engineering

Volumn 8, Issue 4, 2011, Pages

  Ludwig, Kip A ^a   Miriani, Rachel M ^a   Langhals, Nicholas B ^a   Marzullo, Timothy C ^a   Kipke, Daryl R ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMALS; BRAIN COMPUTER INTERFACE; CLASSIFICATION (OF INFORMATION); DECODING; MAXIMUM LIKELIHOOD ESTIMATION; NEURONS;

ALTERNATIVE SOURCE; BAYESIAN MAXIMUM LIKELIHOOD CLASSIFIER; BRAIN MACHINE INTERFACE; CLINICAL DEVICES; DECODING ALGORITHM; EXPERIMENTAL SETTINGS; LOCAL FIELD POTENTIALS; TECHNOLOGICAL LIMITATIONS;

QUALITY CONTROL;

ALGORITHM; ANIMAL BEHAVIOR; ANIMAL EXPERIMENT; ARTICLE; BAYESIAN LEARNING; BRAIN; CALIBRATION; CINGULATE GYRUS; MACHINE; MAXIMUM LIKELIHOOD METHOD; NERVE CELL NETWORK; NONHUMAN; PRIORITY JOURNAL; RAT; TASK PERFORMANCE; TRAINING; ANIMAL; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN CORTEX; COMPUTER INTERFACE; ELECTRODE; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; ELECTROSTIMULATION; EVOKED AUDITORY RESPONSE; INSTRUMENTAL CONDITIONING; NERVE CELL; PHYSIOLOGY; PSYCHOMOTOR PERFORMANCE; SIGNAL PROCESSING; SPRAGUE DAWLEY RAT; STATISTICAL MODEL; VISION;

ANIMALIA;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BEHAVIOR, ANIMAL; CEREBRAL CORTEX; CONDITIONING, OPERANT; ELECTRIC STIMULATION; ELECTRODES, IMPLANTED; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGICAL PHENOMENA; EVOKED POTENTIALS, AUDITORY; LIKELIHOOD FUNCTIONS; NEURONS; PSYCHOMOTOR PERFORMANCE; RATS; RATS, SPRAGUE-DAWLEY; SIGNAL PROCESSING, COMPUTER-ASSISTED; USER-COMPUTER INTERFACE; VISUAL PERCEPTION;

EID: 81355142589     PISSN: 17412560     EISSN: 17412552     Source Type: Journal    
DOI: 10.1088/1741-2560/8/4/049801     Document Type: Erratum

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