This title appears in the Scientific Report :
2015
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.
Inferences from a network to a subnetwork and vice versa under an assumption of symmetry
Inferences from a network to a subnetwork and vice versa under an assumption of symmetry
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...
Personal Name(s):  Mana, PierGianLuca (Corresponding author) 

Torre, Emiliano / Rostami, Vahid  
Contributing Institute: 
JARABRAIN; JARABRAIN Theoretical Neuroscience; IAS6 Computational and Systems Neuroscience; INM6 
Imprint: 
2015

DOI: 
10.1101/034199 
Document Type: 
Preprint 
Research Program: 
Supercomputing and Modelling for the Human Brain The Human Brain Project Theory of multiscale neuronal networks Connectivity and Activity Theory, modelling and simulation 
Link: 
Get full text OpenAccess 
Publikationsportal JuSER 
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 maximumentropy principle, are briefly discussed. The meanings and applicability of the assumption of symmetry are also discussed. 