Full text in Portuguese.
by Antonio Carlos Roque*
To make sense of neural connectivity is among the key challenges in neuroscience. This remains fundamentally a neuromathematical challenge, to the extent that the mathematical theory to understand patterns of connectivity is still to be made, but also also a communicational challenge, since it requires the bridging of relevant but still unconnected fields, such as experimental neurophysiology, neuroanatomy, functional imaging, probability, statistics and computer science. These two challenges are the core of the scientific project of FAPESP’s Research, Innovation and Dissemination Center for Neuromathematics (RIDC NeuroMat), which held from November 23 to 27 the workshop “Random Graphs in the Brain,” at the University of São Paulo, Brazil.
The collaboration between Mathematics and Neuroscience has evolved in the last five years, from being just a tentative association of interest and exchange to building a joint research agenda that could lead to fundamental progress in the understanding of the brain. This is the general view of mathematician Remco van der Hofstad, who has been at the forefront of this collaboration and co-organizes the workshop “Random Graphs in the Brain,” that the Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat) will host at the end of November in São Paulo. The workshop's official website is: neuromat.numec.prp.usp.br/rgbrain. Professor in probability at Eindhoven University of Technology and scientific director of the European Institute for Statistics, Probability, Stochastic Operations Research and its Applications (EURANDOM), Hofstad discusses challenges and perspectives of modeling at the neuronal and functional levels. He has been the leading person of the workshop on “Random Graphs and the Brain,” in 2011, in Eindhoven, and in the interview that follows makes sense of the evolution of the understanding of brain connectivity. "To some extent, we are moving from an attempt to establish a collaboration among neuroscientists and mathematicians to organizing joint research. In 2011, random graph theory and brain theory needed to be bridged, now we moved further and this is evident in the title change from 2011 and 2015. Things are getting more concrete.”
NeuroMat research-team members have been involved in quantifying semantics as a means of understanding behavior and in a recent publication have tested automated speech analyses combined with machine learning processes to predict psychosis onset in youths at clinical high-risk for psychosis. NeuroMat members Guillermo Cecchi, from the IBM T. J. Watson Research Center, Sidarta Ribeiro, from the Federal University of Rio Grande do Norte, Mauro Copelli, from the Federal University of Pernambuco, and colleagues have shown that speech features predicted later psychosis development with 100% accuracy. NeuroMat is the São Paulo Research Foundation (FAPESP)’s Research, Innovation and Dissemination Center for Neuromathematics (RIDC NeuroMat) and was launched in 2013 to contribute to creating a mathematical framework for neuroscience.