Events
| Jun 24, 2026
The Research, Innovation and Dissemination Center for Neuromathematics (RIDC NeuroMat) will hold its closing event, “Celebrating 13 Years of Research at NeuroMat: a Look at the Past and the Future,” on June 24–25, 2026, at the Multipurpose Auditorium of NeuroMat, located in the Antonio Galves Building (NeuroMat headquarters), São Paulo, Brazil.
This two-day workshop will bring together researchers, collaborators, and students to celebrate NeuroMat’s scientific achievements and to reflect on the research perspectives and new directions that have emerged from its activities over more than a decade. The event will feature a series of thematic sessions covering stochastic neuronal networks, the statistical brain hypothesis, computational modeling, and neurobiological and clinical applications, highlighting the breadth and impact of NeuroMat’s contributions.
The program includes invited talks by leading researchers from Brazil and abroad, with both in-person and remote presentations, as well as a special tribute to Antonio Galves. Topics range from stochastic modeling of neural systems and large-scale computational models to applications in neuroimaging, brain stimulation, and neurological disease.
Events
| May 5, 2026
We study a class of heterogeneous random networks where the degree distribution follows a power law and each node's dynamics is governed by a random dynamical system interacting with neighboring nodes via a random coupling function. We characterize hub behavior through the mean-field, subject to statistically controlled fluctuations. In particular, we prove that fluctuations remain small over exponentially long time scales and obtain Berry–Esseen estimates for the fluctuation statistics at any fixed time. Our results provide an explanation for several numerical observations: a scaling relation between system size and the frequency of large fluctuations, system-size-induced desynchronization, and the Gaussian behavior of the fluctuations.
Events
| Mar 25, 2026
We investigate the metastability and extinction time of a finite discrete- time system composed of a large number of interacting components. The system is Markovian with respect to the potential profiles of the components, which are simultaneously subject to leakage and gain effects. We show that the only invariant measure is the null configuration and that it is reached in finite time. Additionally, the system exhibits a metastable state and a metastable barrier, which governs the timescale of the system’s lifetime. We identify a critical parameter, below which the extinction time is independent of system size. Above this critical value, the extinction time depends on the number of components, exhibiting infinitely many scaling behaviors governed by a nontrivial relationship among leakage, gain, and system size.
Events
| Jul 24, 2025
Transcranial Magnetic Stimulation: Breakthroughs in Instrumentation and Neuromodulation is a workshop organized by the Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat) to discuss Transcranial Magnetic Stimulation (TMS) as a methodology to study brain behavior.
Events
| Jul 10, 2025
On September 4th, RIDC NeuroMat will host the Seminar Open Science and Scientific Dissemination - Challenges and Opportunities. This will be a space dedicated to exploring the intersections between innovative research and best practices in education and scientific communication.
The Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat), hosted by the University of São Paulo (USP), Brazil, and funded by the São Paulo Research Foundation (FAPESP), is offering two post-doctoral fellowships for recent PhDs with outstanding research potential. The fellowship will involve collaborations with research teams and laboratories associated with NeuroMat, strictly related to ongoing research lines developed by the NeuroMat, for more details visit our website. The project may be developed at the laboratories of USP, campuses of São Paulo or Ribeirão Preto, or at UNICAMP, Campinas, in person.
