This title appears in the Scientific Report : 2015 

Inferences from a network to a subnetwork and vice versa under an assumption of symmetry
Mana, PierGianLuca (Corresponding author)
Torre, Emiliano / Rostami, Vahid
JARA-BRAIN; JARA-BRAIN
Theoretical Neuroscience; IAS-6
Computational and Systems Neuroscience; INM-6
2015
10.1101/034199
Preprint
Supercomputing and Modelling for the Human Brain
The Human Brain Project
Theory of multi-scale neuronal networks
Connectivity and Activity
Theory, modelling and simulation
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OpenAccess
Please use the identifier: http://hdl.handle.net/2128/9825 in citations.
Please use the identifier: http://dx.doi.org/10.1101/034199 in citations.
This note summarizes some mathematical relations between the probability distributions for the states of a network of binary unitsand a subnetwork thereof, under an assumption of symmetry. These relations are standard results of probability theory, but seem to be rarely used in neuroscience. Some of their consequences for inferences between network and subnetwork, especially in connection with the maximum-entropy principle, are briefly discussed. The meanings and applicability of the assumption of symmetry are also discussed.