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Representations of neuronal interaction statistics

Grant number: 19/22219-0
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Start date: December 01, 2019
End date: November 30, 2022
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
Principal Investigator:Jefferson Antonio Galves
Grantee:Karine Damásio Guimarães
Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat, AP.CEPID

Abstract

Significant empirical evidence shows that the graph of interactions in the brain at different scales can change in time. Analysis of these huge data bases generates large numbers of statistical parameters and structural information. In order to be useful, these results have to be (re)presented in a form that best exploits the natural strengths of our visual system. The choice of proper coordinates in the space of parameters is fundamental for this goal. An effective way to visualize the interaction parameters of a hundred neurons is to consider mathematically mapping of a covariance matrix (obtained by standard statistical analysis of the firing histories) to a set of distances that satisfy the axioms of a distance metric. The advantage of such a map is that our visual system is naturally better equipped to grasp and manipulate geometric concepts like distances. The goal of this project is to develop (or choose), implement, and evaluate effective representations of neuronal interaction parameters. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
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Scientific publications
(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)
GUIMARAES, KARINE; DUARTE, ALINE. A Network-Level Stochastic Model for Pacemaker GABAergic Neurons in Substantia Nigra Pars Reticulata. MATHEMATICS, v. 11, n. 17, p. 11-pg., . (19/22219-0, 13/07699-0)