Navegando por Autor "Viol, Aline"

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Bandgap oscillation in quasiperiodic carbon-BN nanoribbons
(Elsevier, 2014-02) Pedreira, Danilo Oliveira; Azevedo, Sérgio; Bezerra, Claudionor Gomes; Viol, Aline; Viswanathan, Gandhimohan M.; Ferreira, Mauro S.
In this work we address the effects of quasiperiodic disorder on the physical properties of nanoribbons, composed by BN and C, constructed according to the Fibonacci quasiperiodic sequence. We assume BN and C as the building blocks of the resulting quasiperiodic structure. The density of states and energy band gap were obtained through ab-initio calculations based on the density functional theory. We report the effects of the quasiperiodic disorder on the oscillatory behavior of the specific heat, in the low temperature regime, and on the behavior of the energy band gap. In particular, we show that the electronic energy band gap oscillates as a function of the Fibonacci generation index n. Our results suggest that the choice of the building block materials of the quasiperiodic sequence, with appropriate band gap energies, may lead to a tuneable band gap of quasiperiodic nanoribbons
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy?
(2014) Onias, Heloisa; Viol, Aline; Palhano-Fontes, Fernanda; Andrade, Katia C.; Sturzbecher, Marcio; Viswanathan, Gandhimohan; Araújo, Dráulio Barros de
Functional magnetic resonance imaging (fMRI) has just completed 20 years of existence. It currently serves as a research tool in a broad range of human brain studies in normal and pathological conditions, as is the case of epilepsy. To date, most fMRI studies aimed at characterizing brain activity in response to various active paradigms. More recently, a number of strategies have been used to characterize the low-frequency oscillations of the ongoing fMRI signals when individuals are at rest. These datasets have been largely analyzed in the context of functional connectivity, which inspects the covariance of fMRI signals from different areas of the brain. In addition, resting state fMRI is progressively being used to evaluate complex network features of the brain. These strategies have been applied to a number of different problems in neuroscience, which include diseases such as Alzheimer's, schizophrenia, and epilepsy. Hence, we herein aimed at introducing the subject of complex network and how to use it for the analysis of fMRI data. This appears to be a promising strategy to be used in clinical epilepsy. Therefore, we also review the recent literature that has applied these ideas to the analysis of fMRI data in patients with epilepsy.
Characterizing complex networks using entropy-degree diagrams: unveiling changes in functional brain connectivity induced by ayahuasca
(2019-01-30) Viol, Aline; Palhano-Fontes, Fernanda; Onias, Heloisa; Araújo, Dráulio Barros de; Hövel, Philipp; Viswanathan, Gandhi M.
With the aim of further advancing the understanding of the human brain’s functional connectivity, we propose a network metric which we term the geodesic entropy. This metric quantifies the Shannon entropy of the distance distribution to a specific node from all other nodes. It allows to characterize the influence exerted on a specific node considering statistics of the overall network structure. The measurement and characterization of this structural information has the potential to greatly improve our understanding of sustained activity and other emergent behaviors in networks. We apply this method to study how the psychedelic infusion Ayahuasca affects the functional connectivity of the human brain in resting state. We show that the geodesic entropy is able to differentiate functional networks of the human brain associated with two different states of consciousness in the awaking resting state: (i) the ordinary state and (ii) a state altered by ingestion of the Ayahuasca. The functional brain networks from subjects in the altered state have, on average, a larger geodesic entropy compared to the ordinary state. Finally, we discuss why the geodesic entropy may bring even further valuable insights into the study of the human brain and other empirical networks.
Information parity increases on functional brain networks under influence of a psychedelic substance
(IOP Publishing, 2023-03) Viol, Aline; Mohan, Madras Viswanathan Gandhi; Soldatkina, Oleksandra; Fontes, Fernanda Palhano Xavier de; Ventura, Heloisa Helena dos Santos Onias; Araujo, Draulio Barros de; Hövel, Philipp
The physical basis of consciousness is one of the most intriguing open questions that contemporary science aims to solve. By approaching the brain as an interactive information system, complex network theory has greatly contributed to understand brain process in different states of mind. We study a non-ordinary state of mind by comparing resting-state functional brain networks of individuals in two different conditions: before and after the ingestion of the psychedelic brew Ayahuasca. In order to quantify the functional, statistical symmetries between brain region connectivity, we calculate the pairwise information parity of the functional brain networks. Unlike the usual approach to quantitative network analysis that considers only local or global scales, information parity instead quantifies pairwise statistical similarities over the entire network structure. We find an increase in the average information parity on brain networks of individuals under psychedelic influences. Notably, the information parity between regions from the limbic system and frontal cortex is consistently higher for all the individuals while under the psychedelic influence. These findings suggest that the resemblance of statistical influences between pair of brain regions activities tends to increase under Ayahuasca effects. This could be interpreted as a mechanism to maintain the network functional resilience

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Navegando por Autor "Viol, Aline"