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Random fields and probability distributions with given marginals on randomly correlated systems: a general method and a problem from theoretical neuroscience

Carlo Fulvi Mari

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A class of families of marginal probabilities on sets of discrete random variables is studied and a necessary and sufficient condition for the consistency of the given marginals is provided. This result allows one to verify the consistency of the marginals through a Boltzmann statistical analysis.

The procedure is then applied in order to verify the hypotheses assumed in a recent model of neocortical associative areas, according to which connected modules of neurons are simultaneously active with probability higher than chance, and inter-modular connections are very diluted. The verification becomes a typical problem of extremely diluted spin systems in Boltzmann-Gibbs ensemble. The results presented here justify the assumptions made in the neuroscientific theory, and an upper bound to the inter-modular activity correlation is found.


PACS

02.50.Cw Probability theory

05.40.-a Fluctuation phenomena, random processes, noise, and Brownian motion

02.50.Ng Distribution theory and Monte Carlo studies

MSC

60E05 Distributions: general theory

60D05 Geometric probability, stochastic geometry, random sets (See also 52A22, 53C65)

60G60 Random fields

65C20 Models, numerical methods (See also 68U20)

Subjects

Computational physics

Statistical physics and nonlinear systems

Dates

Issue 1 (14 January 2000)

Received 29 March 1999



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