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Hierarchical Mixture Models in Neurological Transmission Analysis

Publication ,  Journal Article
West, M
Published in: Journal of the American Statistical Association
June 1, 1997

Hierarchically structured mixture models are studied in the context of data analysis and inference on neural synaptic transmission characteristics in mammalian, and other, central nervous systems. Mixture structures arise due to uncertainties about the stochastic mechanisms governing the responses to electrochemical stimulation of individual neurotransmitter release sites at nerve junctions. Models attempt to capture such scientific features as the sensitivity of individual synaptic transmission sites to electrochemical stimuli and the extent of their electrochemical responses when stimulated. This is done via suitably structured classes of prior distributions for parameters describing these features. Such priors may be structured to permit assessment of currently topical scientific hypotheses about fundamental neural function. Posterior analysis is implemented via stochastic simulation. Several data analyses are described to illustrate the approach, with resulting neurophysiological insights in some recently generated experimental contexts. Further developments and open questions, both neurophysiological and statistical, are noted. © 1997 Taylor & Francis Group, LLC.

Duke Scholars

Published In

Journal of the American Statistical Association

DOI

EISSN

1537-274X

ISSN

0162-1459

Publication Date

June 1, 1997

Volume

92

Issue

438

Start / End Page

587 / 606

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 3802 Econometrics
  • 1603 Demography
  • 1403 Econometrics
  • 0104 Statistics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
West, M. (1997). Hierarchical Mixture Models in Neurological Transmission Analysis. Journal of the American Statistical Association, 92(438), 587–606. https://doi.org/10.1080/01621459.1997.10474011
West, M. “Hierarchical Mixture Models in Neurological Transmission Analysis.” Journal of the American Statistical Association 92, no. 438 (June 1, 1997): 587–606. https://doi.org/10.1080/01621459.1997.10474011.
West M. Hierarchical Mixture Models in Neurological Transmission Analysis. Journal of the American Statistical Association. 1997 Jun 1;92(438):587–606.
West, M. “Hierarchical Mixture Models in Neurological Transmission Analysis.” Journal of the American Statistical Association, vol. 92, no. 438, June 1997, pp. 587–606. Scopus, doi:10.1080/01621459.1997.10474011.
West M. Hierarchical Mixture Models in Neurological Transmission Analysis. Journal of the American Statistical Association. 1997 Jun 1;92(438):587–606.

Published In

Journal of the American Statistical Association

DOI

EISSN

1537-274X

ISSN

0162-1459

Publication Date

June 1, 1997

Volume

92

Issue

438

Start / End Page

587 / 606

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 3802 Econometrics
  • 1603 Demography
  • 1403 Econometrics
  • 0104 Statistics