Transcranial magnetic stimulation: a brief review on the principles and applications

Renan Hiroshi Matsuda, Gabriela Pazin Tardelli, Carlos Otávio Guimarães, Victor Hugo Souza and Oswaldo Baffa Filho

Transcranial magnetic stimulation is a noninvasive method of the human cortex stimulation. Known as TMS, the technique was introduced by Barker et al. in 1985. Its operation is based on the Faraday’s Law, in which an intense magnetic feld that varies rapidly is able to induce an electric feld in the surface of the brain, depolarizing the neurons in the cerebral cortex. Due to its versatility, TMS is currently used for both research and clinical applications. Among the clinical applications, TMS is used as a diagnostic tool and also as a therapeutic technique for some neurodegenerative diseases and psychiatric disorders such as depression, Parkinson’s disease and tinnitus. As for the diagnostic tool, motor mapping is a technique to delineate the area of representation of the target muscle in its cortical surface, whose applicability may be in studies of the cerebral physiology to evaluate damage to the motor cortex and corticospinal tract. This review aims to introduce the physics, the basic elements, the biological principles and the main applications of transcranial magnetic stimulation.

Brain math is the subject of a podcast produced at USP

This week "Agência FAPESP" website featured an article about the new RIDC NeuroMat podcast, specially addressing the publication of the second episode of the program. The aim of the podcast is to spread the research developed by NeuroMat, at the interface between neurobiology and mathematics.

The program addresses three main themes: the neuronal spiking systems model developed by the CEPID NeuroMat team; the statistical framework needed to rigorously address the “statistical brain” conjecture; and the processes of construction and production of the state-of-the science in Brazil right now.

Videos to explain, promote NeuroMat ongoing research directions

The NeuroMat dissemination team has launched a series of short videos on which young researchers describe briefly questions they tackle and their ongoing work. As of now, four videos were distributed with junior NeuroMat researchers Fernando Araujo Najman, Fernanda Torres, Arthur Lopes da Silva Valencio, and Luiggi Lustosa.

Asymptotically Deterministic Time of Extinction for a Stochastic System of Spiking Neurons

Morgan André

We consider a countably infinite system of spiking neurons. In this model each neuron has a membrane potential which takes value in the non-negative integers. Each neuron is also associated with two point processes. The first one is a Poisson process of some parameter γ, representing the \textit{leak times}, that is the times at which the membrane potential of the neuron is spontaneously reset to 0. The second point process, which represents the \textit{spiking times}, has a non-constant rate which depends on the membrane potential of the neuron at time t. This model was previously proven to present a phase transition with respect to the parameter γ. It was also proven that the renormalized time of extinction of a finite version of the system converges in law toward an exponential random variable when the number of neurons goes to infinity, which indicates a metastable behavior. Here we prove a result which is in some sense the symmetrical of this last result: we prove that when γ>1 (super-critical) the renormalized time of extinction converges in probability to 1.

A Matemática no Cérebro: the new Neuromat podcast

This month on "Jornal da USP" website, there was a report about the NeuroMat podcast, "A Matemática do Cérebro", developed by the NeuroMat Dissemination Team and by Antonio Galves, NeuroMat coordinator, and Eduardo Vicente, professor from the Department of Film, Radio and TV (CTR) of ECA/USP.

The article covered the first two episodes of the podcast. It also talked about CEPID NeuroMat's work and how the epidodes were created to talk about the research developed at the center, with the interface between neurobiology and mathematics.

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