Estimating the posterior probability of LTP failure by sequential bayesian analysis of an imperfect Bernoulli trial model

IEEE Transactions on Biomedical Engineering

Volumn 48, Issue 6, 2001, Pages 670-683

  Bishop, W B ^a  

^a Surveillance Systerns Syracuse   (United States)

Author keywords

Bayes factor; Bayesian statistics; Bernoulli trials; Beta distribution; Excitatory postsynaptic current (EPSC); Long term; Marginalized likelihood function; Noninformative prior density; Posterior distribution

Indexed keywords

ALGORITHMS; ELECTRIC EXCITATION; MATHEMATICAL MODELS; NEUROPHYSIOLOGY; VOLTAGE MEASUREMENT;

TETANICALLY STIMULATED (TS) NEURONS;

BIOELECTRIC POTENTIALS;

ARTICLE; BAYES THEOREM; EXCITATORY POSTSYNAPTIC POTENTIAL; INFORMATION PROCESSING; LONG TERM POTENTIATION; VOLTAGE CLAMP;

ALGORITHMS; BAYES THEOREM; BIOPHYSICS; EXCITATORY POSTSYNAPTIC POTENTIALS; HUMANS; LIKELIHOOD FUNCTIONS; LONG-TERM POTENTIATION; MODELS, NEUROLOGICAL;

EID: 0034993859     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/10.923785     Document Type: Article

References (12)

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3. Asymptotic MAP criteria for model selection
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5. Activation of postsynaptically silent synapses during pairing-induced LTP in CAI hippocampal slice
6. Postsynaptic contribution to long-term potentiation revealed by the analysis of miniature synaptic currents
7. Presynaptic enhancement shown by whole-cell recording of long-term potentiation in hippocampal slices
8. Fractional Bayes factors for model comparison