Neural ensemble states in prefrontal cortex identified using a hidden Markov model with a modified EM algorithm

Neurocomputing

Volumn 32-33, Issue , 2000, Pages 961-966

  Rainer, Gregor ^a   Miller, Earl K ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Electrophysiology; EM; Estimation maximization algorithm; Hidden Markov model; HMM

Indexed keywords

ALGORITHMS; BRAIN; ELECTROPHYSIOLOGY; MARKOV PROCESSES; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY;

ESTIMATION MAXIMIZATION ALGORITHM; HIDDEN MARKOV MODEL; NEURAL ENSEMBLE STATES;

NEUROLOGY;

ALGORITHM; ANIMAL BEHAVIOR; ANIMAL MODEL; ARTICLE; CONTROLLED STUDY; MONKEY; NERVE CELL NETWORK; NONHUMAN; PREFRONTAL CORTEX; PRIORITY JOURNAL; PROBABILITY; RECORDING; TIME; VISION;

EID: 18344410210     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0925-2312(00)00266-6     Document Type: Article

References (5)

1. Baum L.E., Petrie T. Statistical inference for probabilistic functions of finite state Markov chains. Ann. Math. Stat. 37:1966;1554-1563.
2. Rabiner L.R. A tutorial on hidden-Markov models and selected applications in speech recognition. Proc. IEEE. 77:1989;257-286.
3. Rainer G., Asaad W.F., Miller E.K. Selective representation of relevant information by neurons in the primate prefrontal cortex. Nature. 393:1998;577-579.
4. Radons G., Becker J.D., Dülfer B., Krüger J. Analysis, classification and coding of multielectrode spike trains with hidden Markov models. Biol. Cybernet. 71:1994;387-399.
5. Seidemann E., Meilijson I., Abeles M., Bergmann H., Vaadia E. Simultaneously recorded neurons go through sequences of discrete and stable states in monkeys performing a delayed localization task. J. Neurosci. 15:1996;752-768.