Statistical causality in the EEG for the study of cognitive functions in healthy and pathological brains

Understanding brain functions requires not only information about the spatial localization of neural activity, but also about the dynamic functional links between the involved groups of neurons, which do not work in an isolated way, but rather interact together through ingoing and outgoing connections. The work carried on during the three years of PhD course returns a methodological framework for the estimation of the causal brain connectivity and its validation on simulated and real datasets (EEG and pseudo-EEG) at scalp and source level. Important open issues like the selection of the best algorithms for the source reconstruction and for time-varying estimates were addressed. Moreover, after the application of such approaches on real datasets recorded from healthy subjects and post-stroke patients, we extracted neurophysiological indices describing in a stable and reliable way the properties of the brain circuits underlying different cognitive states in humans (attention, memory). More in detail: I defined and implemented a toolbox (SEED-G toolbox) able to provide a useful validation instrument addressed to researchers who conduct their activity in the field of brain connectivity estimation. It may have strong implication, especially in methodological advancements. It allows to test the ability of different estimators in increasingly less ideal conditions: low number of available samples and trials, high inter-trial variability (very realistic situations when patients are involved in protocols) or, again, time varying connectivity patterns to be estimate (where stationary hypothesis in wide sense failed). A first simulation study demonstrated the robustness and the accuracy of the PDC with respect to the inter-trials variability under a large range of conditions usually encountered in practice. The simulations carried on the time-varying algorithms allowed to highlight the performance of the existing methodologies in different conditions of signals amount and number of available trials. Moreover, the adaptation of the Kalman based algorithm (GLKF) I implemented, with the introduction of the preliminary estimation of the initial conditions for the algorithm, lead to significantly better performance. Another simulation study allowed to identify a tool combining source localization approaches and brain connectivity estimation able to provide accurate and reliable estimates as less as possible affected to the presence of spurious links due to the head volume conduction. The developed and tested methodologies were successfully applied on three real datasets. The first one was recorded from a group of healthy subjects performing an attention task that allowed to describe the brain circuit at scalp and source level related with three important attention functions: alerting, orienting and executive control. The second EEG dataset come from a group of healthy subjects performing a memory task. Also in this case, the approaches under investigation allowed to identify synthetic connectivity-based descriptors able to characterize the three main memory phases (encoding, storage and retrieval). For the last analysis I recorded EEG data from a group of stroke patients performing the same memory task before and after one month of cognitive rehabilitation. The promising results of this preliminary study showed the possibility to follow the changes observed at behavioural level by means of the introduced neurophysiological indices

Method to measure off-axis displacements based on the analysis of the intensity distribution of a vortex beam

We study the properties of the Fraunhofer diffraction patterns produced by Gaussian beams crossing spiral phase plates. We show, both analytically and numerically, that off-axis displacements of the input beam produce asymmetric diffraction patterns. The intensity profile along the direction of maximum asymmetry shows two different peaks. We find that the intensity ratio between these two peaks decreases exponentially with the off-axis displacement of the incident beam, the decay being steeper for higher strengths of the optical singularity of the spiral phase plate. We analyze how this intensity ratio can be used to measure small misalignments of the input beam with a very high precision.Comment: 8 pages, 4 figures. Accepted for publication in PR

Robot adoption and FDI driven transformation in the automotive industry

This paper explores the relationship between inward foreign direct investments and the adoption of industrial robots, across different segments of the automotive value chain. Using the International Federation of Robotics and FDI Market datasets at a fine level of disaggregation of the automotive sector, we investigate the extent to which FDIs are related to the operational stock of industrial robots in 34 countries over the period 2005-2014. We find distinct patterns linking FDIs and robot adoption for different groups of countries and for different segments of the automotive value chain, that, is assembling and components production. With some relevant exceptions, FDIs are found to be highly correlated with robot adoption in the assembling segment across major leading countries. However, this correlation becomes weak for components production. To explain this differential role of FDIs in robot adoption, we formulate hypotheses around the country-specific drivers of robotisation for the components segment by pointing to the role of domestic ecosystems of suppliers and industrial policy as drivers of technology absorption and diffusion

Electroencephalography (EEG)-Derived Markers to Measure Components of Attention Processing

Although extensively studied for decades, attention system remains an interesting challenge in neuroscience field. The Attention Network Task (ANT) has been developed to provide a measure of the efficiency for the three attention components identified in the Posner’s theoretical model: alerting, orienting and executive control. Here we propose a study on 15 healthy subjects who performed the ANT. We combined advanced methods for connectivity estimation on electroencephalographic (EEG) signals and graph theory with the aim to identify neuro-physiological indices describing the most important features of the three networks correlated with behavioral performances. Our results provided a set of band-specific connectivity indices able to follow the behavioral task performances among subjects for each attention component as defined in the ANT paradigm. Extracted EEG-based indices could be employed in future clinical applications to support the behavioral assessment or to evaluate the influence of specific attention deficits on Brain Computer Interface (BCI) performance and/or the effects of BCI training in cognitive rehabilitation applications

Determinação das Curvas IDF para região sul do Brasil utilizando modelos estacionário e não estacionário

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia Sanitária e Ambiental.Curvas de Intensidade-Duração-Frequência (IDF) são amplamente utilizadas para a concepção de projetos hidráulicos de infraestrutura. Tradicionalmente, as técnicas desenvolvidas para este propósito são fundamentadas no conceito de estacionariedade das séries históricas de precipitação. Devido aos efeitos das mudanças climáticas no ciclo hidrológico, este conceito vem sendo questionado pela comunidade científica. Nesse contexto, a identificação de tendências em eventos extremos pluviométricos levou ao desenvolvimento e uso de modelos não estacionários para a análise de frequência de eventos extremos de precipitação. Contudo, devido à incerteza associada à detecção e estimativa de tendência nas séries históricas disponíveis, assim como à incerteza intrínseca ao se realizar qualquer previsão de cenários futuros, ainda não existe um consenso quanto à utilização de modelos estacionários ou modelos não estacionários. Neste trabalho, realizou-se uma comparação de desempenho entre o uso de modelos estacionário e não estacionário utilizando a distribuição Generalizada de Valor Extremo (GEV). Foram analisadas 696 estações pluviométricas relativas à região sul do Brasil. Estes dados são diários e foram disponibilizados pela Agência Nacional de Águas. Os valores dos parâmetros da distribuição GEV e a incerteza associada à sua estimativa foram obtidos a partir da Inferência Bayesiana. A seleção de modelos com base nos critérios de informação e com os valores da função de verossimilhança para o conjunto ótimo de parâmetros sugerem a escolha de um modelo não estacionário, principalmente para séries temporais em que há a presença de tendência significativa no período de calibração. Entretanto, quando a incerteza acerca da estimativa dos parâmetros da distribuição de extremos é considerada, o suporte ao modelo não estacionário decresce significativamente. Estes resultados indicam que o acréscimo de incerteza promovido pela adição de complexidade é uma das principais limitações do uso de modelos não estacionários na análise de frequência de extremos, e que a presença de tendência significativa em um registro histórico não é uma condição suficiente para justificar o uso de um modelo não estacionário

100 MHz Amplitude and Polarization Modulated Optical Source for Free-Space Quantum Key Distribution at 850 nm

We report on an integrated photonic transmitter of up to 100 MHz repetition rate, which emits pulses centered at 850 nm with arbitrary amplitude and polarization. The source is suitable for free space quantum key distribution applications. The whole transmitter, with the optical and electronic components integrated, has reduced size and power consumption. In addition, the optoelectronic components forming the transmitter can be space-qualified, making it suitable for satellite and future space missions.Comment: 6 figures, 2 table

Produação de Hortaliças orgânicas e sustentabilidade em área de proteção ambiental no distrito de Guará, Guarapuava-PR

Anais do 35º Seminário de Extensão Universitária da Região Sul - Área temática: Meio AmbienteO Paraná é atualmente o estado que apresenta maior produção e consumo de alimentos orgânicos. A realização da agricultura orgânica é fundamental para a promoção da saúde e sustentabilidade ambiental e social, principalmente em Áreas de Proteção Ambiental. O local escolhido para realização das atividades do projeto foi o Faxinal dos Elias, localizado na APA da Serra da Esperança, tendo como objetivos o auxílio na produção de hortaliças, certificação orgânica, proteção de nascentes e destinação correta dos resíduos inorgânicos. Após visita aos moradores foram definidas as famílias participantes e estas passaram a receber auxílio na produção de hortaliças e adequação para a agricultura orgânica, proteção de fontes de água e recolhimento e destinação correta dos resíduos inorgânicos. A agricultura orgânica poderá ser uma alternativa de geração de renda e agregação de valor, permitindo a permanência e subsistência dessas famílias a partir do ambiente rura

Unveiling structure and dynamics of global digital production technology

This research pioneers the construction of a novel Digital Production Technology Classification (DPTC) based on the latest Harmonised Commodity Description and Coding System (HS2017) of the World Customs Organisation. The DPTC enables the identification and comprehensive analysis of 127 tradable products associated with digital production technologies (DPTs). The development of this classification offers a substantial contribution to empirical research and policy analysis. It enables an extensive exploration of international trade in DPTs, such as the identification of emerging trade networks comprising final goods, intermediate components, and instrumentation technologies and the intricate regional and geopolitical dynamics related to DPTs. In this paper, we deploy our DPTC within a network analysis methodological framework to analyse countries' engagements with DPTs through bilateral and multilateral trade. By comparing the trade networks in DPTs in 2012 and 2019, we unveil dramat ic shifts in the global DPTs' network structure, different countries' roles, and their degree of centrality. Notably, our findings shed light on China's expanding role and the changing trade patterns of the USA in the digital technology realm. The analysis also brings to the fore the increasing significance of Southeast Asian countries, revealing the emergence of a regional hub within this area, characterised by dense bilateral networks in DPTs. Furthermore, our study points to the fragmented network structures in Europe and the bilateral dependencies that developed there. Being the first systematic DPTC, also deployed within a network analysis framework, we expect the classification to become an indispensable tool for researchers, policymakers, and stakeholders engaged in research on digitalisation and digital industrial policy