Analysis and inference of brain links using information theory and non-linear time...
Context trees applied to the statistical modeling of neural spike trains
Grant number: | 17/02035-7 |
Support Opportunities: | Scholarships in Brazil - Doctorate |
Effective date (Start): | March 01, 2017 |
Effective date (End): | November 14, 2020 |
Field of knowledge: | Physical Sciences and Mathematics - Probability and Statistics - Probability |
Principal Investigator: | Jefferson Antonio Galves |
Grantee: | Morgan Florian Thibault André |
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 Neurons, and more generally neural structures are characterized by the large number of its components and the non-trivial dynamic interaction between them (Braitenberg and Schüz, 1998). To describe these structures and resulting phenomena it is necessary to develop a new class of stochastic processes, with values on the space of neural activities and interactions. First steps in this direction have already been done with by NeuroMat in the articles Galves et al. (2015), Duarte et al. (2016) and Brochini et al. (2016). All these papers do statistical model selection in the new class of process introduced in Galves and Löcherbach (2013). The goal of this Ph.D. project is to continue these efforts, by developing the development of the statistical theory needed to analyze samples generated by large systems with interactions of variable range in time and space. | |
News published in Agência FAPESP Newsletter about the scholarship: | |
More itemsLess items | |
TITULO | |
Articles published in other media outlets ( ): | |
More itemsLess items | |
VEICULO: TITULO (DATA) | |
VEICULO: TITULO (DATA) | |