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The ability to synthesize realistic patterns of neural activity is crucial for studying neural information processing. Here we used the Generative Adversarial Networks (GANs) framework to simulate the concerted activity of a population of neurons. We adapted the Wasserstein-GAN variant to facilitate the generation of unconstrained neural population activity patterns while still benefiting from parameter sharing in the temporal domain. We demonstrate that our proposed GAN, which we termed Spike-GAN, generates spike trains that match accurately the first- and second-order statistics of datasets of tens of neurons and also approximates well their higher-order statistics. We applied Spike-GAN to a real dataset recorded from salamander retina and showed that it performs as well as state-of-the-art approaches based on the maximum entropy and the dichotomized Gaussian frameworks. Importantly, Spike-GAN does not require to specify a priori the statistics to be matched by the model, and so constitutes a more flexible method than these alternative approaches. Finally, we show how to exploit a trained Spike-GAN to construct 'importance maps' to detect the most relevant statistical structures present in a spike train. Spike-GAN provides a powerful, easy-to-use technique for generating realistic spiking neural activity and for describing the most relevant features of the large-scale neural population recordings studied in modern systems neuroscience. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 699829.

The ability to synthesize realistic patterns of neural activity is crucial for studying neural information processing. Here we used the Generative Adversarial Networks (GANs) framework to simulate the concerted activity of a population of neurons. We adapted the Wasserstein-GAN variant to facilitate the generation of unconstrained neural population activity patterns while still benefiting from parameter sharing in the temporal domain. We demonstrate that our proposed GAN, which we termed Spike-GAN, generates spike trains that match accurately the first- and second-order statistics of datasets of tens of neurons and also approximates well their higher-order statistics. We applied Spike-GAN to a real dataset recorded from salamander retina and showed that it performs as well as state-of-the-art approaches based on the maximum entropy and the dichotomized Gaussian frameworks. Importantly, Spike-GAN does not require to specify a priori the statistics to be matched by the model, and so constitutes a more flexible method than these alternative approaches. Finally, we show how to exploit a trained Spike-GAN to construct 'importance maps' to detect the most relevant statistical structures present in a spike train. Spike-GAN provides a powerful, easy-to-use technique for generating realistic spiking neural activity and for describing the most relevant features of the large-scale neural population recordings studied in modern systems neuroscience. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 699829.

The ability to synthesize realistic patterns of neural activity is crucial for studying neural information processing. Here we used the Generative Adversarial Networks (GANs) framework to simulate the concerted activity of a population of neurons. We adapted the Wasserstein-GAN variant to facilitate the generation of unconstrained neural population activity patterns while still benefiting from parameter sharing in the temporal domain. We demonstrate that our proposed GAN, which we termed Spike-GAN, generates spike trains that match accurately the first- and second-order statistics of datasets of tens of neurons and also approximates well their higher-order statistics. We applied Spike-GAN to a real dataset recorded from salamander retina and showed that it performs as well as state-of-the-art approaches based on the maximum entropy and the dichotomized Gaussian frameworks. Importantly, Spike-GAN does not require to specify a priori the statistics to be matched by the model, and so constitutes a more flexible method than these alternative approaches. Finally, we show how to exploit a trained Spike-GAN to construct 'importance maps' to detect the most relevant statistical structures present in a spike train. Spike-GAN provides a powerful, easy-to-use technique for generating realistic spiking neural activity and for describing the most relevant features of the large-scale neural population recordings studied in modern systems neuroscience. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 699829.

Recent studies have pointed out that the neural code may use multiplexing to encode unique information at different temporal scales of spike trains. However, how to mathematically separate out the different components of a neural code and to identify the unique contribution of each time scale to sensory coding and behaviour has remained an open challenge. Here we investigated this problem by developing a novel approach to spike train analysis based on a popular image compression method, the Laplacian Pyramid Decomposition (LPD). This technique allows us to express the neuronal response in a basis that characterises different temporal scales (see figure). Using the LPD as a framework, we have analytically calculated the information contained in each temporal scale as follows: first, we have separated the information about the stimuli into two components: the information that each scale provides and the information that is redundant across different temporal scales. In a second step, we have performed a short time-scale series expansion of these two components in order to quantify the amount of information that one scale contains about another. We then showed that the first order approximation of this contamination is non-symmetric: it can be non-zero only from coarse to fine scales. Furthermore, when the stimuli do not elicit any fine pattern in the neural response, the first order components of the information contained in all scales are equal. Taking these results into account, and assuming a firing rate regime in which the first order component of the information dominates, we propose a method to attribute redundant information to a specific scale and hence obtain a well-interpretable separation of scale-specific information. Our method aims at separating information uniquely contained in each scale and thereby provides a promising analysis method to study in detail the advantages and limitations of a multiplexed neural code. ; This project has received funding from the European Union's Future and Emerging ...

Resumo: Nesse artigo, focamos o aumento do consumo de psicotrópicos por mulheres. Estudos recentes indicam uma variação de gênero em relação ao uso desses medicamentos. Mulheres com idade média de 40 anos seriam o principal grupo consumidor. A partir de um diálogo entre a sociologia econômica e mundo digital, o artigo explora discursos e espaços de aconselhamento do mundo digital. Analisamos qual apelo de imagem da mulher surge e como essa imagem pode potencializar o consumo de psicotrópicos. A metodologia incluiu revisão bibliográfica e etnografia virtual no Instagram, investigando influenciadoras que se dirigem às mulheres entre 40 e 50 anos. Essa pesquisa foi realizada ao longo do ano de 2022. Concluímos mostrando um aspecto de espelhamento da imagem da mulher empreendedora de si no mundo digital como corolário do esvaziamento dos espaços de solidariedade e associado ao recurso de psicotrópicos.

Esta investigação tem como objetivo verificar o conhecimento popular e o conhecimento científico das mães de bebês com icterícia em tratamento com fototerapia. Tratou-se de uma pesquisa de campo, com observação direta e abordagem qualitativa, baseada no Discurso do Sujeito Coletivo (DSC), realizada em meados de 2011. A pesquisa foi realizada em uma maternidade estadual na cidade de Mafra em Santa Catarina, com mães de bebês em fototerapia para o tratamento da icterícia. Evidenciaram-se 7 ideias centrais e 11 DSCs. Os resultados revelaram que as mães entrevistadas não reconheceram a icterícia neonatal como um agravo, assim como a fototerapia como medida de tratamento. Evidenciou-se que as mães trazem consigo crenças e conhecimentos populares sobre a icterícia, os quais precisam ser respeitados e valorizados para o fortalecimento do vínculo e do cuidado.

RESUMO Foi analisada a utilização dos recursos transferidos de outras instâncias federativas aos blocos de financiamento da saúde pelos municípios de Santa Catarina. Trata-se de um estudo descritivo dos anos de 2009 e 2015. Observou-se que os municípios investem recursos próprios em saúde muito além do recomendado legalmente, no entanto, não conseguem fazer uso integral dos recursos de transferência direta efetuados pelo estado e pela União aos blocos de financiamento da saúde. Nota-se, porém, diminuição expressiva no montante de recurso subutilizado no período analisado, o que sinaliza a melhoria da capacidade de gestão dos recursos de transferência direta.

Recent studies have pointed out that the neural code may use multiplexing to encode unique information at different temporal. Here we investigate in detail the information encoded in the spiking activity of a neuron by computing the unique contribution that each temporal scale makes to it. We do this by analytically inferring the derivative of the information with respect to the precision with which the neural response is measured. We propose the Information Jitter Derivative (IJD) method, which uses a jitter approach to modify the precision of the neural response. The IJD allows to infer the temporal scales playing a relevant role in the encoding of the information contained in the response of a neuron to a given set of stimuli. We validated the IJD on simulated data. We further demonstrated its usefulness on real neural responses recorded from the retinal ganglion cells (RGCs) of the axolotl salamander and show that these cells carry the information about fine and coarse features of a visual scene using different temporal scales. ; Presented at the BARCCSYN Conference, Barcelona, June, 2017. http://www.crm.cat/en/Activities/Curs_2016-2017/Pages/BARCCSYN-2017.aspx This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 699829 and under the Marie Sklodowska-Curie grant agreement No 659227.

http://dx.doi.org/10.5007/1807-0221.2016v13n23p71Considera-se que o Brasil atualmente esteja na liderança do uso de agrotóxicos no mundo. Tendo em vista a carência de informações sobre os tipos e quantidades de agrotóxicos comercializados no país e sobre a forma como são aplicados nas lavouras, neste trabalho estruturou-se um banco de dados a partir de receituários agronômicos expedidos em uma região agrícola do Estado de Santa Catarina. A análise qualitativa dos receituários mostrou que esses documentos não informam os agricultores sobre o uso adequado e seguro dos agrotóxicos. Em termos quantitativos, verificou-se que os herbicidas constituíram a maior parte dos agrotóxicos receitados e que cerca de um terço do total era constituído por produtos altamente tóxicos. Um número reduzido de profissionais habilitados foi responsável pela assinatura das receitas, o que indica que a maioria dos receituários analisados no estudo não se baseou em um diagnóstico fitossanitário feito diretamente no local da manifestação do problema.

http://dx.doi.org/10.5007/1807-0221.2016v13n21p132Com a necessidade de buscar alternativas para a produção de um alimento mais saudável e com baixo nível de toxicologia tanto para as pessoas como para o meio ambiente. As chamadas caldas e fertilizantes orgânicos vêm com esse propósito, na qual são utilizadas na agricultura orgânica. Com este intuito as oficinas objetivaram levar aos agricultores técnicas de preparo e uso da calda bordalesa e sulfocálcica para o controle de insetos e doenças, bem como a produção de fertilizante orgânico, por meio do processo de compostagem. Realizada em assentamentos rurais no município de Itapiúna no Ceará para agricultores rurais, levou informações que podem utilizar tranquilamente em suas propriedades, principalmente por se tratar de fácil execução e com baixo custo, tanto as caldas como a compostagem, houve grande interesse pela aprendizagem por parte dos agricultores.