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Dynamical models consisting of networks of neural masses commonly assume that the interactions between neural populations are via additive or diffusive coupling. When using the additive coupling, a population’s activity is affected by the sum of the activities of neighbouring populations. In contrast, when using the diffusive coupling a neural population is affected by the sum of the differences between its activity and the activity of its neighbours. These two coupling functions have been used interchangeably for similar applications. In this study, we show that the choice of coupling can lead to strikingly different brain network dynamics. We focus on a phenomenological model of seizure transitions that has been used both with additive and diffusive coupling in the literature. We consider small networks with two and three nodes, as well as large random and scale-free networks with 64 nodes. We further assess resting-state functional networks inferred from magnetoencephalography (MEG) from people with juvenile myoclonic epilepsy (JME) and healthy controls. To characterize the seizure dynamics on these networks, we use the escape time, the brain network ictogenicity (BNI) and the node ictogenicity (NI), which are measures of the network’s global and local ability to generate seizure activity. Our main result is that the level of ictogenicity of a network is strongly dependent on the coupling function. Overall, we show that networks with additive coupling have a higher propensity to generate seizures than those with diffusive coupling. We find that people with JME have higher additive BNI than controls, which is the hypothesized BNI deviation between groups, while the diffusive BNI provides opposite results. Moreover, we find that the nodes that are more likely to drive seizures in the additive coupling case are more likely to prevent seizures in the diffusive coupling case, and that these features correlate to the node’s number of connections. Consequently, previous results in the literature involving such models to interrogate functional or structural brain networks could be highly dependent on the choice of coupling. Our results on the MEG functional networks and evidence from the literature suggest that the additive coupling may be a better modeling choice than the diffusive coupling, at least for BNI and NI studies. Thus, we highlight the need to motivate and validate the choice of coupling in future studies involving network models of brain activity.

The discrimination of similar episodes and places, and their representation as distinct memories, depend on a process called pattern separation that relies on the circuitry of the hippocampal dentate gyrus (DG). Mossy cells (MCs) are key neurons in the circuitry, but how they influence DG network dynamics, function, and seizure risk has not been fully elucidated. We found the net impact of MCs was inhibitory at physiological frequencies connected with learning and behaviour, and their absence associated with deficits in pattern separation and spatial memory; at higher frequencies, their net impact was excitatory, and their absence protected against seizures. Thus, MCs influence DG outputs in a highly dynamic manner that varies with frequency and context.One-Sentence SummaryHippocampal mossy cells are required for learning and memory; but their absence protects against seizures.

Models of networks of populations of neurons commonly assume that the interactions between neural populations are via additive or diffusive coupling. When using the additive coupling, a population’s activity is affected by the sum of the activities of neighbouring populations. In contrast, when using the diffusive coupling a neural population is affected by the sum of the differences between its activity and the activity of its neighbours. These two coupling functions have been used interchangeably for similar applications. Here, we show that the choice of coupling can lead to strikingly different brain network dynamics. We focus on a model of seizure transitions that has been used both with additive and diffusive coupling in the literature. We consider networks with two and three nodes, and large random and scale-free networks with 64 nodes. We further assess functional networks inferred from magnetoencephalography (MEG) from people with epilepsy and healthy controls. To characterize the seizure dynamics on these networks, we use the escape time, the brain network ictogenicity (BNI) and the node ictogenicity (NI), which are measures of the network’s global and local ability to generate seizures. Our main result is that the level of ictogenicity of a network is strongly dependent on the coupling function. We find that people with epilepsy have higher additive BNI than controls, as hypothesized, while the diffusive BNI provides the opposite result. Moreover, individual nodes that are more likely to drive seizures with one type of coupling are more likely to prevent seizures with the other coupling function. Our results on the MEG networks and evidence from the literature suggest that the additive coupling may be a better modelling choice than the diffusive coupling, at least for BNI and NI studies. Thus, we highlight the need to motivate and validate the choice of coupling in future studies.Author summaryMost models of brain dynamics assume that distinct brain regions interact in either an additive or a diffusive way. With additive coupling, each brain region sums incoming signals. In contrast, with diffusive coupling, each region sums the differences between its own signal and incoming signals. Although they are different, these two couplings have been used for very similar applications, particularly within models of epilepsy. Here we assessed the effect of this choice on seizure behaviour. Using a model of seizures and both artificial and real brain networks, we showed that the coupling choice can lead to very different seizure dynamics. We found that networks that are more prone to seizures using one coupling, are less prone to them using the other. Likewise, individual brain regions that are more likely to drive seizures when using additive coupling, are more likely to prevent them when using diffusive coupling. Using real brain networks, we found that the additive coupling predicted higher seizure propensity in people with epilepsy compared to healthy controls, whereas the diffusive coupling did not. Our results highlight the need to justify the choice of coupling used and show that the additive coupling may be a better option in some applications.

O periodo de isolamento social devido a propagacao do coronavirus demandou alteracoes cotidianas, inclusive, na educacao. Este estudo objetivou relatar a experiencia da monitoria de Anatomia Humana com atividades on-line, utilizando a plataforma Google Meet. Por meio da interacao durante as aulas e da avaliacao dos resultados de um formulario preenchido pelos alunos, concluiu-se que a aulas de monitoria on-line auxiliaram os estudantes no aprendizado do conteudo da Anatomia e ajudaram a manter uma rotina de estudos.

Este estudo teve como objetivo avaliar as implicacoes do uso de cafeina por atletas e seus efeitos no desempenho em esportes competitivos. Nossa hipotese e que as propriedades ergogenicas da cafeina sao beneficas para o desempenho do exercicio em todos os tipos de intensidade e duracao, embora seu maior efeito possa ser observado em atividades aerobicas sustentadas de alta intensidade. Trata-se de uma revisao sistematica da literatura com meta-analise e meta-resumo sobre os efeitos da cafeina na atividade fisica. A revisao e baseada em publicacoes cientificas encontradas na National Library of Medicine (Medline) disponiveis na Biblioteca Nacional de Medicina dos Estados Unidos (PubMed), acessada em http://www.ncbi.nlm.nih.gov/pubmed e SCOPUS (Elsevier) por meio do Portal CAFe CAPES, acesso via http://www.periodicos.capes.gov.br/. Esta pesquisa foi realizada seguindo as recomendacoes metodologicas do PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis). A cafeina influencia a atividade fisica de forma linear, pois mudancas na variavel cafeina acompanham mudancas na variavel atividade fisica. Para interpretacao, devem ser consideradas as variaveis independentes relacionadas a atividade fisica como idade e estilo de vida e dependentes considerando o desfecho da influencia na atividade fisica. O numero de estudos observados para alguns efeitos da cafeina na atividade fisica confirmou os efeitos ergogenicos da cafeina. Foi visto que os atletas seriam mais beneficiados em eventos de uma hora de duracao se consumissem quantidades moderadas de cafeina antes do exercicio. O nivel moderado de cafeina geraria efeito ergogenico suficiente e diminuiria possiveis efeitos colaterais. A cafeina tambem pode facilitar o desempenho muscular anaerobio em atletas de competicao. A meta-analise demonstrou que existe uma associacao da suplementacao de cafeina e aumento no desempenho de atletas em diversas situacoes. Esta metanalise demonstrou que existe uma associacao da suplementacao de cafeina com o aumento do desempenho de atletas em diversas situacoes. Assim, confirmando os efeitos ergogenicos da cafeina. Foi visto que os atletas seriam mais beneficiados em eventos de uma hora de duracao se consumissem quantidades moderadas de cafeina antes do exercicio. O nivel moderado de cafeina geraria efeito ergogenico suficiente e diminuiria possiveis efeitos colaterais. A cafeina tambem pode facilitar o desempenho muscular anaerobio em atletas competitivos. A associacao da cafeina com outras substâncias minimiza a fadiga central em resposta aos esportes coletivos, mas esse efeito nao foi encontrado em esportes individuais. Alem disso, a cafeina aumentou o estado de alerta, o humor e a funcao cognitiva apos o exercicio.

Highlights • Computational modelling is combined with MEG to differentiate people with juvenile myoclonic epilepsy from healthy controls. • Brain network ictogenicity (BNI) was found higher in people with juvenile myoclonic epilepsy relative to healthy controls. • BNI’s classification accuracy in our cohort was 73%., Objective For people with idiopathic generalized epilepsy, functional networks derived from their resting-state scalp electrophysiological recordings have shown an inherent higher propensity to generate seizures than those from healthy controls when assessed using the concept of brain network ictogenicity (BNI). Herein we tested whether the BNI framework is applicable to resting-state magnetoencephalography (MEG) from people with juvenile myoclonic epilepsy (JME). Methods The BNI framework consists in deriving a functional network from apparently normal brain activity, placing a mathematical model of ictogenicity into the network and then computing how often such network generates seizures in silico. We considered data from 26 people with JME and 26 healthy controls. Results We found that resting-state MEG functional networks from people with JME are characterized by a higher propensity to generate seizures (i.e., higher BNI) than those from healthy controls. We found a classification accuracy of 73%. Conclusions The BNI framework is applicable to MEG and was capable of differentiating people with epilepsy from healthy controls. Significance The BNI framework may be applied to resting-state MEG to aid in epilepsy diagnosis.

Resumo Apesar das dificuldades enfrentadas na vivência de suas sexualidades, a educação sexual de pessoas autistas costuma ser negligenciada. Neste sentido, esta pesquisa objetiva identificar as demandas de autistas sobre sua sexualidade, alinhando-se ao paradigma da neurodiversidade. Trata-se de uma pesquisa de natureza qualitativa realizada de setembro de 2017 a outubro de 2018, com 14 autistas oralizados, com idades de 15 a 17 anos, matriculados em escolas regulares. A coleta dos dados foi realizada por entrevistas semiestruturadas e avaliadas segundo a análise temática de conteúdo. Identificaram-se 2 categorias analíticas: “processos discursivos e a imagética do ‘anjo azul’” e “diversidade na diversidade: a sexualidade de autistas como processos singulares”. Os resultados que embora pessoas autistas se desenvolvam fisicamente e sexualmente de acordo com os estágios típicos de desenvolvimento, existem singularidades que não deveriam ser ignoradas. Todavia, a construção de falsas crenças fomenta a negação da sexualidade de pessoas autistas. Conclui-se que o estabelecimento de ações efetivas de educação sexual e de suporte à sexualidade da pessoa autista requer uma mudança paradigmática, que ancore-se no modelo social de deficiência. Abstract Despite the difficulties in living their sexualities, the sexual education of autistic people is often neglected. In this sense, this research aims to identify autistic people’s demands on their sexualities, in line with the neurodiversity paradigm. This qualitative research was carried out from September 2017 to October 2018, with 14 autistic children aged 15 to 17 enrolled in regular schools. Data were collected by semi-structured interviews and analyzed according to the thematic content analysis. Two analytical categories were identified: “discursive processes and the ‘blue angel’ imagery”; and “diversity in diversity: the sexuality of autistic people as singular processes”. The results show that, while autistic people grow physically and sexually according to the typical development stages, some singularities should not be ignored. However, the construction of false beliefs encourages the denial of autistic people’s sexuality. We can conclude that the establishment of effective actions of sexual education and support to the sexuality of the autistic person requires a paradigmatic change anchored in the social model of disability.

Despite the difficulties in living their sexualities, the sexual education of autistic people is often neglected. In this sense, this research aims to identify autistic people's demands on their sexualities, in line with the neurodiversity paradigm. This qualitative research was carried out from September 2017 to October 2018, with 14 autistic children aged 15 to 17 enrolled in regular schools. Data were collected by semi-structured interviews and analyzed according to the thematic content analysis. Two analytical categories were identified: "discursive processes and the 'blue angel' imagery"; and "diversity in diversity: the sexuality of autistic people as singular processes". The results show that, while autistic people grow physically and sexually according to the typical development stages, some singularities should not be ignored. However, the construction of false beliefs encourages the denial of autistic people's sexuality. We can conclude that the establishment of effective actions of sexual education and support to the sexuality of the autistic person requires a paradigmatic change anchored in the social model of disability.Apesar das dificuldades enfrentadas na vivência de suas sexualidades, a educação sexual de pessoas autistas costuma ser negligenciada. Neste sentido, esta pesquisa objetiva identificar as demandas de autistas sobre sua sexualidade, alinhando-se ao paradigma da neurodiversidade. Trata-se de uma pesquisa de natureza qualitativa realizada de setembro de 2017 a outubro de 2018, com 14 autistas oralizados, com idades de 15 a 17 anos, matriculados em escolas regulares. A coleta dos dados foi realizada por entrevistas semiestruturadas e avaliadas segundo a análise temática de conteúdo. Identificaram-se 2 categorias analíticas: “processos discursivos e a imagética do ‘anjo azul’” e “diversidade na diversidade: a sexualidade de autistas como processos singulares”. Os resultados que embora pessoas autistas se desenvolvam fisicamente e sexualmente de acordo com os estágios típicos de desenvolvimento, existem singularidades que não deveriam ser ignoradas. Todavia, a construção de falsas crenças fomenta a negação da sexualidade de pessoas autistas. Conclui-se que o estabelecimento de ações efetivas de educação sexual e de suporte à sexualidade da pessoa autista requer uma mudança paradigmática, que ancore-se no modelo social de deficiência.

Highlights • Computational modelling is combined with scalp EEG to assess epilepsy lateralization. • Our approach proved useful in informing lateralization in 12 out of 15 individuals studied. • The framework proposed may be used to aid deciding where to implant intracranial electrodes., Objective The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework to interrogate scalp EEG and determine epilepsy lateralization to aid in electrode implantation. Methods We use eLORETA to map source activities from seizure epochs recorded from scalp EEG and consider 15 regions of interest (ROIs). Functional networks are then constructed using the phase-locking value and studied using a mathematical model. By removing different ROIs from the network and simulating their impact on the network’s ability to generate seizures in silico, the framework provides predictions of epilepsy lateralization. We consider 15 individuals from the EPILEPSIAE database and study a total of 62 seizures. Results were assessed by taking into account actual intracranial implantations and surgical outcome. Results The framework provided potentially useful information regarding epilepsy lateralization in 12 out of the 15 individuals (p=0.02, binomial test). Conclusions Our results show promise for the use of this framework to better interrogate scalp EEG to determine epilepsy lateralization. Significance The framework may aid clinicians in the decision process to define where to implant electrodes for intracranial monitoring.

Epileptic seizures are generally classified as either focal or generalized. It had been traditionally assumed that focal seizures imply localized brain abnormalities, whereas generalized seizures involve widespread brain pathologies. However, recent evidence suggests that large-scale brain networks are involved in the generation of focal seizures, and generalized seizures can originate in localized brain regions. Herein we study how network structure and tissue heterogeneities underpin the emergence of focal and widespread seizure dynamics. Mathematical modeling of seizure emergence in brain networks enables the clarification of the characteristics responsible for focal and generalized seizures. We consider neural mass network dynamics of seizure generation in exemplar synthetic networks and we measure the variance in ictogenicity across the network. Ictogenicity is defined as the involvement of network nodes in seizure activity, and its variance is used to quantify whether seizure patterns are focal or widespread across the network. We address both the influence of network structure and different excitability distributions across the network on the ictogenic variance. We find that this variance depends on both network structure and excitability distribution. High variance, i.e., localized seizure activity, is observed in networks highly heterogeneous with regard to the distribution of connections or excitabilities. However, networks that are both heterogeneous in their structure and excitability can underlie the emergence of generalized seizures, depending on the interplay between structure and excitability. Thus, our results imply that the emergence of focal and generalized seizures is underpinned by an interplay between network structure and excitability distribution.

Evidence suggests that brain network dynamics is a key determinant of brain function and dysfunction. Here we propose a new framework to assess the dynamics of brain networks based on recurrence analysis. Our framework uses recurrence plots and recurrence quantification analysis to characterize dynamic networks. For resting-state magnetoencephalographic dynamic functional networks (dFNs), we have found that functional networks recur more quickly in people with epilepsy than healthy controls. This suggests that recurrence of dFNs may be used as a biomarker of epilepsy. For stereo electroencephalography data, we have found that dFNs involved in epileptic seizures emerge before seizure onset, and recurrence analysis allows us to detect seizures. We further observe distinct dFNs before and after seizures, which may inform neurostimulation strategies to prevent seizures. Our framework can also be used for understanding dFNs in healthy brain function and in other neurological disorders besides epilepsy., Comment: 77 pages, 11 figures; note: the acknowledgments section is the most complete in this arxiv version (compared to the published version in EJN)

Network models of brain dynamics provide valuable insight into the healthy functioning of the brain and how this breaks down in disease. A pertinent example is the use of network models to understand seizure generation (ictogenesis) in epilepsy. Recently, computational models have emerged to aid our understanding of seizures and to predict the outcome of surgical perturbations to brain networks. Such approaches provide the opportunity to quantify the effect of removing regions of tissue from brain networks and thereby search for the optimal resection strategy. Here, we use computational models to elucidate how sets of nodes contribute to the ictogenicity of networks. In small networks we fully elucidate the ictogenicity of all possible sets of nodes and demonstrate that the distribution of ictogenicity across sets depends on network topology. However, the full elucidation is a combinatorial problem that becomes intractable for large networks. Therefore, we combine computational models with a genetic algorithm to search for minimal sets of nodes that contribute significantly to ictogenesis. We demonstrate the potential applicability of these methods in practice by identifying optimal sets of nodes to resect in networks derived from 20 individuals who underwent resective surgery for epilepsy. We show that they have the potential to aid epilepsy surgery by suggesting alternative resection sites as well as facilitating the avoidance of brain regions that should not be resected.

PURPOSE Several questionnaires have been used for functional evaluation. They must be translated and adapted transculturally, these instruments need to be valid, reliable, and sensitive according to the population. This review identified the questionnaires which were adapted transculturally in Brazilian Portuguese, to verify the methodological quality. METHODS A search was performed in the PubMed, BIREME, SportDiscus, SciELO, Scopus, Science Direct, and Web of Science. The methodological quality was evaluated by the COnsensus-based Standards for Health Measurement INstruments (COSMIN) Risk of Bias checklist. For cross-cultural translation and adaptation studies, the properties of measurement of structural validity, internal consistency (IC), cross-cultural validity, reliability, measurement error, and criterion validity were analyzed. RESULTS A total of 4564 articles were found; 10 fulfilled the inclusion criteria. The psychometrics properties verified were IC; criterion validity; reproducibility; floor/ceiling effect and responsiveness. Criterion validity was the best criterion evaluated. The main failures were related to sample size, and the most deficient properties were IC, reliability, and error of measure. CONCLUSIONS The studies verified presented "inadequate" final score using COSMIN. Although specific questionnaires for ankle evaluation have been cross culturally validated in Brazilian Portuguese, their methodological quality was generally low, as verified through the analysis of their psychometric properties. IMPLICATIONS FOR REHABILITATION The questionnaires which were cross culturally adapted to Brazilian Portuguese were shown to be of low methodological quality. In using them careful consideration needs to be given to the psychometrics of each measure. Caution should be exercised in making clinical decisions drawn from the results.

As atividades experimentais representam recurso indiscutível no processo ensino – aprendizagem. Para alunos de graduação essas práticas se tornam mais eficientes quando tratadas de forma contextualizada. Métodos físicos de análises são alternativas simples, de baixo custo e rápidas na verificação da autenticidade de óleos essenciais com alto valor comercial, além de oferecer didática experimental que facilita o aprendizado de discentes dos cursos de química e áreas afins. Entre os parâmetros físicos destacam-se densidade, índice de refração e rotação óptica, que regulamentam a comercialização de fitoterápicos no Brasil. O presente estudo tem como objetivo fornecer alternativas de atividade experimental no ensino de química voltado para aplicação prática relacionada a regulamentação na comercialização de óleo essencial com alto valor agregado e produção científica na área. Os óleos essenciais foram obtidos por hidrodestilação. A densidade, o índice de refração e a rotação específica foram medidos em aparelhos específicos. O óleo essencial de candeeiro obteve maior rotação específica (-58,75° à -59,25°). O índice de refração foi maior para o pau-de-óleo (1,501560 ± 0,000000 nD). A densidade foi superior para o óleo essencial da marangaba vermelha (0,98 ±0,015 g/mL). Alterações na composição química de óleos essenciais apresentam mudanças significativas nas suas propriedades físicas, estas podem ser facilmente identificadas com a ajuda de aparelhos de fácil acesso e manuseio, garantindo eficiência das suas propriedades biológicas. Os estudantes, podem desenvolver habilidades profissionais para identificação dessas características, possibilidade esta, que representa motivação no processo de ensino-aprendizagem.

Neuronal network dynamics depends on network structure. In this paper we study how network topology underpins the emergence of different dynamical behaviors in neuronal networks. In particular, we consider neuronal network dynamics on Erd\H{o}s-R\'enyi (ER) networks, regular random (RR) networks, ring lattices, and all-to-all networks. We solve analytically a neuronal network model with stochastic binary-state neurons in all the network topologies, except ring lattices. Given that apart from network structure, all four models are equivalent, this allows us to understand the role of network structure in neuronal network dynamics. Whilst ER and RR networks are characterized by similar phase diagrams, we find strikingly different phase diagrams in the all-to-all network. Neuronal network dynamics is not only different within certain parameter ranges, but it also undergoes different bifurcations (with a richer repertoire of bifurcations in ER and RR compared to all-to-all networks). This suggests that local heterogeneity in the ratio between excitation and inhibition plays a crucial role on emergent dynamics. Furthermore, we also observe one subtle discrepancy between ER and RR networks, namely ER networks undergo a neuronal activity jump at lower noise levels compared to RR networks, presumably due to the degree heterogeneity in ER networks that is absent in RR networks. Finally, a comparison between network oscillations in RR networks and ring lattices shows the importance of small-world properties in sustaining stable network oscillations., Comment: 9 pages, 4 figures