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Um die komplexe Dynamik von Neuronen und deren Informationsverarbeitung mittels Pulssequenzen zu verstehen, ist es wichtig, die stationäre Puls-Aktivität zu charakterisieren. Die statistischen Eigenschaften von Pulssequenzen können durch vereinfachte stochastische Neuronenmodelle verstanden werden. Eine gut ausgearbeitete Theorie existiert für die Klasse der Erneuerungsmodelle, welche die statistische Unabhängigkeit der Interspike-Intervalle (ISI) annimmt. Experimente haben jedoch gezeigt, dass viele Neuronen Korrelationen zwischen ISIs aufweisen und daher nicht gut durch einen Erneuerungsprozess beschrieben werden. Solche Korrelationen können durch Nichterneuerungs-Modelle erfasst werden, welche jedoch theoretisch schlecht verstanden sind. Diese Arbeit ist eine analytische Studie von Nichterneuerungs-Modellen, die zwei bedeutende Korrelationsmechanismen untersucht: farbiges Rauschen, welches zeitlich-korrelierten Input darstellt, und negative Puls-Rückkopplung, welche Feuerraten-Adaption realisiert. Für das "Perfect-Integrate-and-Fire" (PIF) Modell, welchen durch ein allgemeines Gauss''sches farbiges Rauschen getrieben ist, werden die Statistiken höherer Ordnung der Output-Pulssequenz hergeleitet, insbesondere der Koeffizient der Variation, der serielle Korrelationskoeffizient (SCC), die ISI-Dichte und der Fano-Faktor. Weiterhin wird die Dynamik des PIF Modells mit Puls-getriggertem Adaptionsstrom und weissem Stromrauschen im Detail analysiert. Die Theorie liefert einen Ausdruck für den SCC, der für schwaches Rauschen aber beliebige Adaptions-Stärke und Zeitskale gültig ist, sowie die lineare Antwortfunktion und das Leistungsspektrum der Pulssequenz. Ausserdem wird gezeigt, dass ein stochastischer Adaptionsstrom wie ein langsames farbiges Rauschen wirkt, was ermöglicht, die dominierende Quellen des Rauschen in einer auditorischen Rezeptorzelle zu bestimmen. Schliesslich wird der SCC für das fluktuations-getriebene Feuerregime berechnet. / To understand the complex dynamics of neurons and its ability to process information using a sequence of spikes, it is vital to characterize its stationary spontaneous spiking activity. The statistical properties of spike trains can be explained by reduced stochastic neuron models that account for various sources of noise. A well-developed theory exists for the class of renewal models, in which the interspike intervals (ISIs) are statistically independent. However, experimental studies show that many neurons are not well described by a renewal process because of correlations between ISIs. Such correlations can be captured by generalized, non-renewal models, which are, however, poorly understood theoretically. This thesis represents an analytical study of non-renewal models, focusing on two prominent correlation mechanisms: colored-noise driving representing temporally correlated inputs, and negative feedback currents realizing spike-frequency adaptation. For the perfect integrate-and-fire (PIF) model driven by a general Gaussian colored noise input, the higher-order statistics of the output spike train is derived using a weak-noise analysis of the Fokker-Planck equation. This includes formulas for the coefficient of variation, the serial correlation coefficient (SCC), the ISI density and the Fano factor. Then, the dynamics of a PIF model with a spike-triggered adaptation and a white-noise current is analyzed in detail. The theory yields an expression for the SCC valid for weak noise but arbitrary adaptation strengths and time scale, and also provides the linear response to time-dependent stimuli and the spike train power spectrum. Furthermore, it is shown that a stochastic adaptation current acts like a slow colored noise, which permits to determine the source of spiking variability observed in an auditory receptor neuron. Finally, the SCC is calculated for the fluctuation-driven spiking regime by assuming discrete states of colored noise or adaptation current.

Recentemente observou-se experimentalmente, Johnson et al. (2010), que fatias organotípicas corticais de rato são capazes de completar padrões espaço-temporais, após serem treinadas. Embora se especule que mecanismos de plasticidade sináptica e homeostática estejam por trás do fenômeno, ainda não existe nenhuma explicação detalhada sobre o assunto. Com o intuito de propor uma explicação clara e consistente para os mecanismos que permeiam a resposta da rede aos estímulos como um todo, nos propomos a estudar este fenômeno por meio de uma rede de neurônios de integração-e-disparo dotada de mecanismos de homeostase intrínseca e de plasticidade sináptica dependente de disparos. O sistema construído foi explorado, de modo a determinar em que condições a rede poderia comportar-se como o sistema real, e treinado de forma similar `a realizada experimentalmente por Johnson et al. (2010). / Recently it has been observed experimentally, Johnson et al. (2010), that organotypic cortical slices of rat are capable of completing spatio-temporal patterns after training. Although it is speculated that synaptic and homeostatic plasticity may have an important role in this phenomenon, there is still no detailed explanation about this subject. In order to propose a clear and consistent explanation for the mechanisms that underlie the network response to stimuli as a whole, we propose to study this phenomenon through a network of integrate-and-fire neurons endowed with intrinsic homeostasis and spike-timing dependent plasticity mechanisms. The constructed system was explored, aiming to determine in which conditions the network could behave as the real system, and trained in a way similar as the experimental one done by Johnson et al. (2010).

O estudo de redes complexas tem despertado muita atenção nos últimos anos, principalmente pela sua capacidade de permitir a análise dos mais diversificados sistemas através de um mesmo conjunto de ferramentas matemáticas e computacionais. Até pouco tempo a ênfase nessa área era sobre o estudo das propriedades estruturas e sua influência em característica globais da dinâmica ocorrendo sobre o sistema. Recentemente foi-se percebendo a riqueza de comportamentos que podemos estudar ao olharmos para grupos de vértices e as interações que ocorrem entre esses grupos, de forma que cada vez mais se torna necessária a criação de uma forma sistemática de quantificar, a nível de nó, como uma dinâmica é influenciada (ou diferenciada) pela estrutura do sistema. Apresentamos nesse trabalho um primeiro passo nessa direção, no qual definimos uma medida que, baseada em características dinâmicas obtidas em diversas condições iniciais, busca comparar o comportamento dos nós presentes no sistema. Através dessa medida encontramos a alta capacidade de modelos de rede geográficas de produzir, por simples flutuações estatísticas, grupos de nós de dinâmica muito distinta em relação ao demais, um fato que não ocorre para uma rede definida de forma semelhante mas não geográfica. Nessas redes conseguimos verificar também se um nó de topologia local distinta dos demais consegue possuir uma dinâmica diferenciada, o que encontramos foi que mesmo em regiões da rede extremamente regulares existe a formação de grupos dinâmicos devido ao efeito da borda dessa região. Saindo de modelos de redes para apresentar aplicações práticas do método, encontramos na rede neuronal do verme Caenorhabditis elegans um conjunto de nós de alta diferenciação dinâmica, que representam os interneurônios do cordão ventral do verme. Adicionalmente encontramos na rede cortical do macaco da família Cercopithecidae uma divisão em relação a regularidade dos sinais dinâmicos, o que indica a presença de comunidades funcionais nessa rede. Além da metodologia de diferenciação desenvolvemos ainda uma ferramenta que busca encontrar de forma totalmente automatizada as características dinâmicas mais relevantes do sistema em estudo, que foi capaz de representar medidas dinâmicas tradicionalmente utilizadas na área. Todos esses resultados abrem caminho para diversas vertentes de estudo, em especial citamos a influência de uma borda irregular no interior de uma região regular, o estudo da rede Caenorhabditis elegans com dinâmicas neuronais mais precisas e a aplicação sistemática de dinâmicas para encontrar a divisão funcional de comunidades em redes direcionadas, um tema que apresenta resultados promissores. / The study of complex networks has drawn much attention over the last years, mainly by virtue of its potential to characterize the most diverse systems through the same mathematical and computational tools. Not long ago the emphasis on this field mostly focused on the effects of the structural properties on the global behavior of a dynamical process taking place in the system. Recently, some studies started to unveil the richness of interactions that occur between groups of nodes when we look at the small scale of interactions occurring in the network. Such findings call for a new systematic methodology to quantify, at node level, how a dynamics is being influenced (or differentiated) by the structure of the underlying system. Here we present a first step towards this direction, in which we define a new measurement that, based on dynamical characteristics obtained for a series of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measurement we find the high capacity of networks generated by geographical models to exhibit, by means of statistical fluctuations, groups of nodes with very distinct dynamics compared to the rest of the network, a behavior that does not occur for a similar non-geographical network. We also verify if a large topological differentiation of a node necessarily reflects on its dynamics. We find that even in very regular regions of the network the nodes tend to form dynamical groups influenced by the border effects. In addition to the network models used, we present practical applications of the methodology by using the neuronal network of the nematode Caenorhabditis elegans, where we show that the interneurons of the ventral cord presents a very large dynamical differentiation when compared to the rest of the network. We also analyze the cortical network of the Cercopithecidae monkey by means of signal communication complexity, finding that it contains two well-defined functional communities. Besides the differentiation measurement, we also presents an useful mechanism for automatically obtaining the relevant dynamical characteristics of the nodes, which showed promising results by obtaining traditional measurements of the area with little effort. All these results pave the way to a range of different studies, of which we highlight the influence of an irregular border on the dynamics taking place inside a regular network region, the study of the neurons of Caenorhabditis elegans using more robust neuronal dynamics and the systematic application of different dynamics in order to find the functional community division of directed networks.

Made available in DSpace on 2016-03-15T19:45:20Z (GMT). No. of bitstreams: 1 Nilton Cesar Nicola.pdf: 3916095 bytes, checksum: fbfd29a597a58618a89f3bb588f9a114 (MD5) Previous issue date: 2011-08-10 / This project became real due to the researcher's interest in new approaches to teaching and in implementing a transdisciplinary teaching proposal. In this case, the proposal consisted of a reading assignment, under different perspectives, of a Machado de Assis's short story. The project was based on Edgar Morin's ideas of the complexity of knowledge of different subjects, and traditional school's simplistic approaches to learning, were questioned. Contextualizing and integrating were the objectives of the work developed by teachers of Reading and Writing Texts, Philosophy, Sociology, Psychology, History , subjects that together with Academic-Scientific and Cultural Activities, are part of the freshman year of the School of Pedagogy at "Faculdade de Ciências Aplicadas e Tecnológica do Litoral Sul/FACSUL". Transdisciplinary projects of such kind may be applicable at any school level, aiming to create a valuable dialogue between areas of knowledge, and also to achieve a more significant and contextualized learning. / O presente projeto nasceu do interesse do pesquisador por novos paradigmas para o ensino e por implementar uma proposta didático-pedagógica transdisciplinar. Neste caso a proposta consistiu na leitura crítica, através de diferentes perspectivas, de um conto de Machado de Assis. Postulou-se, com base nas ideias de Edgar Morin, a complexidade das relações entre as diferentes áreas do conhecimento e se questionaram padrões reducionistas, característicos da filosofia de ensino tradicional. Contextualizar e integrar foram os objetivos do trabalho desenvolvido com os professores de Leitura e Produção de Textos, Filosofia, Sociologia, Psicologia e História, disciplinas que compõem, juntamente com Atividades Acadêmico-Científico-Culturais (AACC), a matriz curricular do primeiro semestre do curso de Pedagogia da Faculdade de Ciências Aplicadas e Tecnológicas do Litoral Sul/FACSUL. Projetos transdisciplinares como este, aplicáveis em todos os níveis, objetivam religar as áreas do conhecimento e valorizar o diálogo entre os saberes, de forma significativa e contextualizadora.

A stochastic leaky integrate-and-fire neuron model was implemented in this study to simulate the spiking activity of the electrosensory "P-unit" receptor neurons of the weakly electric fish Apteronotus leptorhynchus. In the context of sensory coding, these cells have been previously shown to respond in experiment to natural random narrowband signals with either a linear or nonlinear coding scheme, depending on the intrinsic firing rate of the cell in the absence of external stimulation. It was hypothesised in this study that this duality is due to the relation of the stimulus to the neuron's excitation threshold. This hypothesis was validated with the model by lowering the threshold of the neuron or increasing its intrinsic noise, or randomness, either of which made the relation between firing rate and input strength more linear. Furthermore, synchronous P-unit firing to a common input also plays a role in decoding the stimulus at deeper levels of the neural pathways. Synchronisation and desynchronisation between multiple model responses for different types of natural communication signals were shown to agree with experimental observations. A novel result of resonance-induced synchrony enhancement of P-units to certain communication frequencies was also found.

A stochastic leaky integrate-and-fire neuron model was implemented in this study to simulate the spiking activity of the electrosensory "P-unit" receptor neurons of the weakly electric fish Apteronotus leptorhynchus. In the context of sensory coding, these cells have been previously shown to respond in experiment to natural random narrowband signals with either a linear or nonlinear coding scheme, depending on the intrinsic firing rate of the cell in the absence of external stimulation. It was hypothesised in this study that this duality is due to the relation of the stimulus to the neuron's excitation threshold. This hypothesis was validated with the model by lowering the threshold of the neuron or increasing its intrinsic noise, or randomness, either of which made the relation between firing rate and input strength more linear. Furthermore, synchronous P-unit firing to a common input also plays a role in decoding the stimulus at deeper levels of the neural pathways. Synchronisation and desynchronisation between multiple model responses for different types of natural communication signals were shown to agree with experimental observations. A novel result of resonance-induced synchrony enhancement of P-units to certain communication frequencies was also found.

Outsourcing has become a popular mode of developing information system (IS) in practice during the last two decades. Although efforts have been done about evaluating vendors¡¦ capabilities and product¡¦s quality so as to assure high success rate, empirical studies keep reporting that outsourcing is not as successful as expected. Therefore, research based on different perspectives is needed to provide other plausible answers. Draws on this issue, an emerging concept is adopted, called Service-Dominant Logic (S-D logic), which highlights the importance for clients to possess required capabilities in order to maximize the value co-created. Therefore, the goal of this paper is to comprehend and examine critical capabilities that an outsourcing client should possess, and hybrid research model, consisting both traditional and S-D logic was built to reflect our intention. Survey method was then used to test our hypotheses empirically. Data collected from 400 practitioners showed that client¡¦s capabilities have stronger impact on the outcomes variables than conventional variables, such as product quality and vendor¡¦s capabilities. This study contributes to literature by incorporating a new concept, S-D logic, into IS research and emphasizing the critical role of clients¡¦ capabilities.

The time for WIMAX (Worldwide Interoperability for Microwave Access) is coming. Wireless network, a major trend of urban development nowadays, has become a part of modern life. In addition, all the countries have put emphasis on the application of information technology in the field of education. Thus, Ministry of Education in Taiwan actively promotes how to integrate information technology into teaching. In order to combine policies with the development of technology industry, building a wireless teaching environment in junior high schools is now a benchmark of becoming a clever mobile city for Kaohsiung City. As the prosperity of wireless network technology, mobile learning is now the main stream of the ubiquitous society; that is, utilizing modern technology into teaching has become a trend. This research takes the teachers major in humanities and art and the executive directors in the junior high schools in Kaohsiung City as an object of study, probing into the completion of building wireless teaching environments in these schools, the application of wireless network for teaching in the field of humanities and art, and the information literacy in connection with the will to utilize such technology of these teachers. This research bases on Davis¡¦s Technology Acceptance Model, probing into the usefulness, the ease of use and the will to use of teaching with the wireless network with the construction of the wireless environment in the campus and the information literacy of the teachers by the questionnaires. It adopts SPSS15.0 for Windows as well as Amos 7.0 systems to analyze the data and Structural Equation Modeling to proceed to the causal path analysis of the research structure, testing the causal relationship of each variable in this research. At the same time, it uses the data from the questionnaires and the interviews to mutually confirm the conclusion. According to this research, there are five conclusions: 1¡BGender, the seniority of teaching, the function of office and the scale of the school will affect the usefulness, the ease of use, the will to use and the information literacy of teaching with the wireless network. 2¡BSo far the construction of wireless environment of the junior high schools in Kaohsiung city is still not perfect; specifically, only few schools can expand wireless access points by themselves while other schools still maintain 5 access points offered by the Education Bureau. Thus, the access points are installed only in the conference rooms or the special-function classrooms; they are insufficient for the normal classrooms. 3¡BThe teachers in the field of humanities and art generally use internet resources to teach, but many of them can not directly teach on the internet owing to the insufficiency of wireless environment. 4¡BThe information literacy of the teachers has a notably positive effect on the usefulness, the ease of use and the will to use of teaching with the wireless network. 5¡BThe effectiveness of how WIMAX influence the completion of building wireless teaching environment in junior high schools is not so obvious.

A stochastic leaky integrate-and-fire neuron model was implemented in this study to simulate the spiking activity of the electrosensory "P-unit" receptor neurons of the weakly electric fish Apteronotus leptorhynchus. In the context of sensory coding, these cells have been previously shown to respond in experiment to natural random narrowband signals with either a linear or nonlinear coding scheme, depending on the intrinsic firing rate of the cell in the absence of external stimulation. It was hypothesised in this study that this duality is due to the relation of the stimulus to the neuron's excitation threshold. This hypothesis was validated with the model by lowering the threshold of the neuron or increasing its intrinsic noise, or randomness, either of which made the relation between firing rate and input strength more linear. Furthermore, synchronous P-unit firing to a common input also plays a role in decoding the stimulus at deeper levels of the neural pathways. Synchronisation and desynchronisation between multiple model responses for different types of natural communication signals were shown to agree with experimental observations. A novel result of resonance-induced synchrony enhancement of P-units to certain communication frequencies was also found.