Bolsa para comunicação científica (BJC-2)

O Centro de Pesquisa, Inovação e Difusão em Neuromatemática (CEPID NeuroMat) oferece uma bolsa para recém formados e profissionais de comunicação social interessados em fazer parte da equipe de difusão científica desse centro de excelência da FAPESP.

Mixing rates for potentials of non-summable variations

Christophe Gallesco and Daniel Y. Takahashi

Mixing rates and decay of correlations for dynamics defined by potentials with summable variations are well understood, but little is known for non-summable variations. In this paper, we exhibit upper bounds for these quantities in the case of dynamics defined by potentials with square summable variations. We obtain these bounds as corollaries of a new block coupling inequality between pair of dynamics starting with different histories. As applications of our results, we prove a new weak invariance principle and a Chernoff-type inequality.

Selective Inhibition of Mirror Invariance for Letters Doubles Reading Fluency

Ana Raquel Torres, Natália B. Mota, Nery Adamy, Janaina Weissheimer, Angela Naschold, Mauro Copelli, Felipe Pegado and Sidarta G. Ribeiro

Mirror invariance, a visual mechanism that emerges early in human development, enables a prompt recognition of mirror images. This visual capacity, useful to recognize objects, faces, and places from both left and right perspectives is also present in primates, pigeons, and cephalopods. Notwithstanding, the same visual mechanism is suspected to be the source of a specific difficulty for a relatively recent human invention-reading-by creating confusion between mirror-letters (eg, bd in the Latin alphabet). Here we show that mirror invariance represents a major leash for reading fluency acquisition in first graders. We used a causal approach, specifically targeting mirror invariance for letters and observing an unprecedented twofold increase in reading fluency. This gain is achieved with as little as 7.5 hours of multisensory-motor training for mirror letters, mostly with eyes closed, in a synergic combination with post-training sleep. Indeed, the magnitude, automaticity, and duration of this learning were greatly enhanced by sleep, which keeps the gains perfectly intact even after 4 months, being critical to double reading fluency with such short training. The results were consistently replicated in three randomized controlled trials using an ecologically valid school-based design. They not only reveal an extreme case of cognitive plasticity in humans (ie, the inhibition of at least~ 25 million years-old visual mechanism in just three weeks) for a cultural activity (reading) but at the same time also show a simple and cost-effective way to unleash the reading fluency potential of millions of children worldwide.

The effect of graph connectivity on metastability in a stochastic system of spiking neurons

Morgan André and Léo Planche

We consider a continuous-time stochastic model of spiking neurons. In this model, we have a finite or countable number of neurons which are vertices in some graph G where the edges indicate the synaptic connection between them. We focus on metastability, understood as the property for the time of extinction of the network to be asymptotically memory-less, and we prove that this model exhibits two different behaviors depending on the nature of the specific underlying graph of interaction G that is chosen.

Structural differences between REM and non-REM dream reports assessed by graph analysis

Sidarta Ribeiro, Joshua M Martin, Danyal Wainstein, Natalia B Mota, Sergio A Mota-Rolim, John Fontenele Araújo and Mark Solms

Dream reports collected after rapid eye movement sleep (REM) awakenings are, on average, longer, more vivid, bizarre, emotional and story-like compared to those collected after non-REM. However, a comparison of the word-to-word structural organization of dream reports is lacking, and traditional measures that distinguish REM and non-REM dreaming may be confounded by report length. This problem is amenable to the analysis of dream reports as non-semantic directed word graphs, which provide a structural assessment of oral reports, while controlling for individual differences in verbosity. Against this background, the present study had two main aims: Firstly, to investigate differences in graph structure between REM and non-REM dream reports, and secondly, to evaluate how non-semantic directed word graph analysis compares to the widely used measure of report length in dream analysis. To do this, we analyzed a set of 125 dream reports obtained from 19 participants in controlled laboratory awakenings from REM and N2 sleep. We found that: (1) graphs from REM sleep possess a larger connectedness compared to those from N2; (2) measures of graph structure can predict ratings of dream complexity, where increases in connectedness and decreases in randomness are observed in relation to increasing dream report complexity; and (3) measures of the Largest Connected Component of a graph can improve a model containing report length in predicting sleep stage and dream complexity. These results indicate that dream reports sampled after REM awakening have on average a larger connectedness compared to those sampled after N2 (i.e. words recur with a longer range), a difference which appears to be related to underlying differences in dream complexity. Altogether, graph analysis represents a promising method for dream research, due to its automated nature and potential to complement report length in dream analysis.

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