This non-exhaustive list brings up some of the key achievements of the Research, Innovation and Dissemination Center for Neuromathematics (RIDC NeuroMat/FAPESP) in 2019. It is not conceived as a Statement of Impact --as the 2018 SOI--, since it may not be seen as an official compte-rendu; it is rather an informal recompilation of key moments of our team. This accounts for activities and milestones since NeuroMat's renewal for six years.
Events
| Nov 21, 2019
The Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat) will hold the “Second NeuroMat Young Researchers Workshop” in São Paulo on November 27. NeuroMat is hosted by the University of São Paulo and funded by the São Paulo Research Foundation (FAPESP). The event's official website is:
neuromat.numec.prp.usp.br/2young. The aim of this meeting is to get members of the NeuroMat team to know more about each other's research. To do so, every Master/PhD student and Postdoc is invited to give a small presentation (around 25 minutes) about their current work. The meeting will take place at the Multipurpose Auditorium at NeuroMat, Av. Prof. Luciano Gualberto, 1171, at the University of São Paulo, São Paulo, Brazil.
Vinícius Lima Cordeiro, Rodrigo Felipe de Oliveira Pena, Cesar Augusto Celis Ceballos, Renan Oliveira Shimoura and Antonio Carlos Roque
Neurons respond to external stimuli by emitting sequences of action potentials (spike trains). In this way, one can say that the spike train is the neuronal response to an input stimulus. Action potentials are “all-or-none” phenomena, which means that a spike train can be represented by a sequence of zeros and ones. In the context of information theory, one can then ask: how much information about a given stimulus the spike train conveys? Or rather, what aspects of the stimulus are encoded by the neuronal response? In this article, an introduction to information theory is presented which consists of historical aspects, fundamental concepts of the theory, and applications to neuroscience. The connection to neuroscience is made with the use of demonstrations and discussions of different methods of the theory of information. Examples are given through computer simulations of two neuron models, the Poisson neuron and the integrate-and-fire neuron, and a cellular automata network model. In the latter case, it is shown how one can use information theory measures to retrieve the connectivity matrix of a network.
R. F. O. Pena, V. Lima, R. O. Shimoura, C. C. Ceballos, H. G. Rotstein and A. C. Roque
The conventional impedance profile of a neuron can identify the presence of resonance and other properties of the neuronal response to oscillatory inputs, such as nonlinear response amplifications, but it cannot distinguish other nonlinear properties such as asymmetries in the shape of the voltage response envelope. Experimental observations have shown that the response of neurons to oscillatory inputs preferentially enhances either the upper or lower part of the voltage envelope in different frequency bands. These asymmetric voltage responses arise in a neuron model when it is submitted to high enough amplitude oscillatory currents of variable frequencies. We show how the nonlinearities associated to different ionic currents or present in the model as captured by its voltage equation lead to asymmetrical response and how high amplitude oscillatory currents emphasize this response. We propose a geometrical explanation for the phenomenon where asymmetries result not only from nonlinearities in their activation curves but also from nonlinearites captured by the nullclines in the phase-plane diagram and from the system’s time-scale separation. In addition, we identify an unexpected frequency-dependent pattern which develops in the gating variables of these currents and is a product of strong nonlinearities in the system as we show by controlling such behavior by manipulating the activation curve parameters. The results reported in this paper shed light on the ionic mechanisms by which brain embedded neurons process oscillatory information.
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.
