%0 Journal Article
%4 sid.inpe.br/mtc-m21b/2018/03.02.15.57
%2 sid.inpe.br/mtc-m21b/2018/03.02.15.57.10
%@doi 10.1103/PhysRevE.97.022303
%@issn 1539-3755
%F self-archiving-INPE-MCTIC-GOV-BR
%T Inference of topology and the nature of synapses, and the flow of information in neuronal networks
%D 2018
%9 journal article
%A Borges, F. S.,
%A Lameu, Ewandson Luiz,
%A Iarosz, K. C.,
%A Protachevicz, P. R.,
%A Caldas, I. L.,
%A Viana, R. L.,
%A Macau, Elbert Einstein Nehrer,
%A Batista, A. M.,
%A Baptista, M. S.,
%@affiliation Universidade de São Paulo (USP)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade de São Paulo (USP)
%@affiliation Universidade Estadual de Ponta Grossa (UEPG)
%@affiliation Universidade de São Paulo (USP)
%@affiliation Universidade Federal do Paraná (UFPR0
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade de São Paulo (USP)
%@affiliation University of Aberdeen
%B Physical Review E
%V 97
%N 2
%P e022303
%X The characterization of neuronal connectivity is one of the most important matters in neuroscience. In this work, we show that a recently proposed informational quantity, the causal mutual information, employed with an appropriate methodology, can be used not only to correctly infer the direction of the underlying physical synapses, but also to identify their excitatory or inhibitory nature, considering easy to handle and measure bivariate time series. The success of our approach relies on a surprising property found in neuronal networks by which nonadjacent neurons do understand each other (positive mutual information), however, this exchange of information is not capable of causing effect (zero transfer entropy). Remarkably, inhibitory connections, responsible for enhancing synchronization, transfer more information than excitatory connections, known to enhance entropy in the network. We also demonstrate that our methodology can be used to correctly infer directionality of synapses even in the presence of dynamic and observational Gaussian noise, and is also successful in providing the effective directionality of intermodular connectivity, when only mean fields can be measured.
%@language en
%3 borges_inference.pdf