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Inferring neural activity interaction graphs

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:
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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
ANDRE, MORGAN. A Result of Metastability for an Infinite System of Spiking Neurons. Journal of Statistical Physics, v. 177, n. 5, p. 984-1008, . (17/02035-7)
ANDRE, MORGAN; PLANCHE, LEO. The effect of graph connectivity on metastability in a stochastic system of spiking neurons. Stochastic Processes and their Applications, v. 131, p. 292-310, . (17/02035-7, 19/14367-0, 13/07699-0)
ROMARO, C.; NAJMAN, F. A.; ANDRE, M.. A Numerical Study of the Time of Extinction in a Class of Systems of Spiking Neurons. Journal of Statistical Physics, v. 190, n. 2, p. 16-pg., . (13/07699-0, 17/02035-7)
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
ANDRÉ, Morgan Florian Thibault. Phase transition and metastability in a stochastic system of spiking neurons. 2020. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) São Paulo.

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