Electrophysiological Evidence That the Retrosplenial Cortex Displays a Strong and Specific Activation Phased with Hippocampal Theta during Paradoxical (REM) Sleep

Bruna Del Vechio Koike, Kelly Soares Farias, Francesca Billwiller, Daniel Almeida-Filho, Paul-Antoine Libourel, Alix Tiran-Cappello, Régis Parmentier, Wilfredo Blanco, Sidarta Ribeiro, Pierre-Herve Luppi and Claudio Marcos Queiroz

It is widely accepted that cortical neurons are similarly more activated during waking and paradoxical sleep (PS; aka REM) than during slow-wave sleep (SWS). However, we recently reported using Fos labeling that only a few limbic cortical structures including the retrosplenial cortex (RSC) and anterior cingulate cortex (ACA) contain a large number of neurons activated during PS hypersomnia. Our aim in the present study was to record local field potentials and unit activity from these two structures across all vigilance states in freely moving male rats to determine whether the RSC and the ACA are electrophysiologically specifically active during basal PS episodes. We found that theta power was significantly higher during PS than during active waking (aWK) similarly in the RSC and hippocampus (HPC) but not in ACA. Phase–amplitude coupling between HPC theta and gamma oscillations strongly and specifically increased in RSC during PS compared with aWK. It did not occur in ACA. Further, 68% and 43% of the units recorded in the RSC and ACA were significantly more active during PS than during aWK and SWS, respectively. In addition, neuronal discharge of RSC but not of ACA neurons increased just after the peak of hippocampal theta wave. Our results show for the first time that RSC neurons display enhanced spiking in synchrony with theta specifically during PS. We propose that activation of RSC neurons specifically during PS may play a role in the offline consolidation of spatial memories, and in the generation of vivid perceptual scenery during dreaming.

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Mathematics in brain study, "USP Analisa"

Mathematics does not always come down to calculations. It can help to understand even the functioning of the human brain. To explain how this is done and the challenges of Neuromathematics, the "USP Analisa" this week interviews the coordinator of RIDC NeuroMat and professor of the Institute of Mathematics and Statistics (IME) of USP, Antonio Galves, and also the professor of the Faculty of Philosophy, Arts and Sciences of Ribeirão Preto (FFCLRP) of USP, the NeuroMat PI Antonio Carlos Roque da Silva Filho. Rose Talamone, Jornal da USP, 07/12/2017. (In Portuguese)

Hawkes processes with variable length memory and an infinite number of components

Pierre Hodara and Eva Löcherbach

In this paper we propose a model for biological neural nets where the activity of the network is described by Hawkes processes having a variable length memory. The particularity in this paper is that we deal with an infinite number of components. We propose a graphical construction of the process and build, by means of a perfect simulation algorithm, a stationary version of the process. To implement this algorithm, we make use of a Kalikow-type decomposition technique. Two models are described in this paper. In the first model, we associate to each edge of the interaction graph a saturation threshold that controls the influence of a neuron on another. In the second model, we impose a structure on the interaction graph leading to a cascade of spike trains. Such structures, where neurons are divided into layers, can be found in the retina.

Counting results for sparse pseudorandom hypergraphs II

Yoshiharu Kohayakawa, Guilherme Oliveira Mota, Mathias Schacht and Anusch Taraz

We present a variant of a universality result of Rödl (1986) for sparse, 3-uniform hypergraphs contained in strongly jumbled hypergraphs. One of the ingredients of our proof is a counting lemma for fixed hypergraphs in sparse “pseudorandom” hypergraphs, which is proved in the companion paper (Counting results for sparse pseudorandom hypergraphs I).

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The Research, Innovation and Dissemination Center for Neuromathematics is hosted by the University of São Paulo and funded by FAPESP (São Paulo Research Foundation).

 

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