Dendritic morphology and microsegregation in the ternary Fe- 1.6% Mn - 0.1 to 0.8 % C alloys have been investigated by quenching the unidirectionally solidified specimens. The microprobe analysis of these specimens showed that the manganese segregation was significantly controlled by the back diffusion. This back diffusion was extremely high in the case of ferritic solidification whereas only a small rise in Cmin was obtained for the austenitic phase. It was found that the manganese microsegregation between the primary arms was always higher than between the secondary arms. The measured segregation ratios indicated a rise with increasing carbon content for both morphologies. No clear effect of cooling rate on segregation was seen for secondary arms and only a sliqht increase was recorded with increasing the cooling rate for primary arms. Secondary dendrite arms solidified to produce asymmecric distribution profiles (saw-tooth or TGZM effect). Measurements of the secondary dendrite arms during qrowth showed that the rate of the coarsening in these manganese steels was higher than other steels resulting in high homogenization between the arms . No tertiary arms have been observed. The primary arms grew mainly in the so-called 'close packed' arrangement and their spacinq did not chanqe with time. By increasing the qrowth rate and the temperature qradient in the liquid a decrease in primary arm spacings was seen. The results agree well with available experimental data in the literature. The microsegregation calculations obtained from the secondary dendrite arm coarseninq model is in a very good agreement with the experimental measurements. The same model without arm coarsening was applied to different primary arm morphologies and the predictions of these models are also in reasonable agreement with observations.

This thesis addresses the problem of how the dendritic structure and other morphological properties of the neuron can determine its pattern recognition performance. The techniques used in this work for generating dendritic trees with different morphologies included the following three methods. Firstly, dendritic trees were produced by exhaustively generating every possible morphology. Where this was not possible due to the size of morphological space, I sampled systematically from the possible morphologies. Lastly, dendritic trees were evolved using an evolutionary algorithm, which varied existing morphologies using selection, mutation and crossover. From these trees, I constructed full compartmental conductance-based models of neurons. I then assessed the performance of the resulting neuronal models by quantifying their ability to discriminate between learned and novel input patterns. The morphologies generated were tested in the presence and absence of active conductances. The results have shown that the morphology does have a considerable effect on pattern recognition performance. In fact, neurons with a small mean depth of their dendritic tree are the best pattern recognizers. Moreover, the performance of neurons is anti-correlated with mean depth. Interestingly, the symmetry of the neuronal morphology does not correlate with performance. This research has also revealed that the evolutionary algorithm could find effective morphologies for both passive models and models with active conductances. In the active model, there was a considerable change in the performance of the original population of neurons, which largely resulted from changes in the morphological parameters such as dendritic compartmental length and tapering. However, no single parameter setting guaranteed good neuronal performance; in three separate runs of the evolutionary algorithm, different sets of well performing parameters were found. In fact, the evolved neurons performed at least five times better than the original hand-tuned neurons. In summary, the combination of morphological parameters plays a key role in determining the performance of neurons in the pattern recognition task and the right combination produces very well performing neurons.

This study investigated the effects of repeated administrations of nicotine (0.7 mg/kg) on dendritic morphology in the nucleus accumbens (NAcc), prefrontal cortex (Cg 3), and parietal cortex (Par 1). Animals were habituated for 3 days to a locomotor box, and after habituation, every second day for 5 weeks rats were placed into the locomotor chamber immediately after a subcutaneous injection of nicotine or saline. Rats demonstrated tolerance to an initial hypoactive response after each nicotine injection, and this was followed by an increase in activity after each injection (behavioral sensitization). This increase in activity was still present on a nicotine challenge after a 2-week abstinence period. One week after the nicotine challenge day, all rats were perfused and brains were removed. These brains we stained using Golgi-Cox procedures, and dendrites from the nucleus accumbens (N Acc), medial frontal cortex (Cg 3) and parietal cortex (Par 1) were analyzed using the camera lucida procedure. Results showed that rats receiving nicotine demonstrated an increase in dendritic length and spine density relative to controls in the NAcc and Cg3 brain areas, but not Par 1. The increase observed in the NAcc was significantly greater than what has been found with amphetamine or cocaine, and possible underlying mechanisms were discussed.

京都大学 / 新制・論文博士 / 博士(医科学) / 乙第13503号 / 論医科博第9号 / 新制||医科||10(附属図書館) / (主査)教授 林 康紀, 教授 髙橋 良輔, 教授 井上 治久 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM

Pesquisas in vivo e in vitro, têm estabelecido uma correlação entre alterações na morfologia dendrítica e a epilepsia. No entanto, ainda não se conhecem em detalhe as consequências dessas modificações, sobre a eletrofisiologia e o padrão de disparo. Também existe um fenômeno que não tem sido completamente explicado, conhecido como o paradoxo do dendrito epiléptico, no qual neurônios piramidais, mesmo com a diminuição dramática do principal lugar de inervação glutamatérgica (como consequência de, por exemplo, uma redução do diâmetro e comprimento das árvores dendríticas), inesperadamente apresentam um estado de hiperexcitabilidade crônica. Nesta pesquisa foram aproveitadas as vantagens de uma abordagem neurocomputacional, para induzir sistematicamente alterações na arquitetura dendrítica do mesmo tipo às observadas na epilepsia, e avaliar os seus efeitos sobre a eletrofisiologia e o padrão de disparo. Para isso foi construído um modelo computacional biologicamente realista, de um neurônio piramidal do neocórtex. O código-fonte do modelo está na linguagem do NEURON, e foi baseado em dados eletrofisiológicos (i.e. propriedades da membrana e condutâncias iônicas) e morfométricos, obtidos in vitro previamente por outros pesquisadores. A análise foi feita com base em parâmetros eletrofisiológicos do padrão de disparo. O nosso modelo sugere uma influencia muito forte da morfologia dendrítica sobre a eletrofisiologia, a geração de potencias de ação e o padrão de disparo. Os resultados obtidos mostram que, mesmo mantendo constantes todos parâmetros biofísicos (que têm a ver com as dinâmicas elétricas dos canais iônicos), é possível induzir um aumento grande no comportamento elétrico e na geração de potenciais de ação, a partir da redução do diâmetro e comprimento das ramificações das árvores dendríticas. Estes resultados, também permitem contribuir no fornecimento de uma explicação para o paradoxo mencionado. / In vivo and in vitro studies had found a correlation between dendritic morphology alterations and epilepsy. Nevertheless, it has not been established in detail the consequences of those modifications, over the electrophysiology and firing pattern. There is also a phenomenon still not completely understood, known as the epileptic dendrite paradox, in which pyramidal neurons with a dramatic reduction in the principal place of glutamatergic innervation (due to, for example, a loss in dendritic trees\' diameter and length), unexpectedly present a chronic hyperexcitable state. In this study we took advantage of a neurocomputational approach, to systematically induce dendritic alterations of the same type as observed in Epilepsy, and evaluate their effect over the electrophysiology and firing behavior. With that purpose in mind, we constructed a biologically realistic computational model of a pyramidal neuron of the neocortex. For this model, it was implemented the programming language (hoc) of the NEURON software, and was elaborated based on electrophysiological data (i.e. membrane properties and ionic conductances), and morphological measurements, taken in vitro previously by other investigators. The analysis was done from electrophysiological parameters of the firing pattern. Our model suggests a great influence of dendritic morphology over the electrophysiology, spike generation and firing pattern. The results obtained show that, even when all the biophysical parameters involved in ion channel dynamics are maintained constant, it is possible to induce a strong increase in electric behavior and spike firing, from a reduction in the length and diameter of the dendritic trees\' ramifications. These results, also contribute to a explanation of the mentioned paradox.

Pesquisas in vivo e in vitro, têm estabelecido uma correlação entre alterações na morfologia dendrítica e a epilepsia. No entanto, ainda não se conhecem em detalhe as consequências dessas modificações, sobre a eletrofisiologia e o padrão de disparo. Também existe um fenômeno que não tem sido completamente explicado, conhecido como o paradoxo do dendrito epiléptico, no qual neurônios piramidais, mesmo com a diminuição dramática do principal lugar de inervação glutamatérgica (como consequência de, por exemplo, uma redução do diâmetro e comprimento das árvores dendríticas), inesperadamente apresentam um estado de hiperexcitabilidade crônica. Nesta pesquisa foram aproveitadas as vantagens de uma abordagem neurocomputacional, para induzir sistematicamente alterações na arquitetura dendrítica do mesmo tipo às observadas na epilepsia, e avaliar os seus efeitos sobre a eletrofisiologia e o padrão de disparo. Para isso foi construído um modelo computacional biologicamente realista, de um neurônio piramidal do neocórtex. O código-fonte do modelo está na linguagem do NEURON, e foi baseado em dados eletrofisiológicos (i.e. propriedades da membrana e condutâncias iônicas) e morfométricos, obtidos in vitro previamente por outros pesquisadores. A análise foi feita com base em parâmetros eletrofisiológicos do padrão de disparo. O nosso modelo sugere uma influencia muito forte da morfologia dendrítica sobre a eletrofisiologia, a geração de potencias de ação e o padrão de disparo. Os resultados obtidos mostram que, mesmo mantendo constantes todos parâmetros biofísicos (que têm a ver com as dinâmicas elétricas dos canais iônicos), é possível induzir um aumento grande no comportamento elétrico e na geração de potenciais de ação, a partir da redução do diâmetro e comprimento das ramificações das árvores dendríticas. Estes resultados, também permitem contribuir no fornecimento de uma explicação para o paradoxo mencionado. / In vivo and in vitro studies had found a correlation between dendritic morphology alterations and epilepsy. Nevertheless, it has not been established in detail the consequences of those modifications, over the electrophysiology and firing pattern. There is also a phenomenon still not completely understood, known as the epileptic dendrite paradox, in which pyramidal neurons with a dramatic reduction in the principal place of glutamatergic innervation (due to, for example, a loss in dendritic trees\' diameter and length), unexpectedly present a chronic hyperexcitable state. In this study we took advantage of a neurocomputational approach, to systematically induce dendritic alterations of the same type as observed in Epilepsy, and evaluate their effect over the electrophysiology and firing behavior. With that purpose in mind, we constructed a biologically realistic computational model of a pyramidal neuron of the neocortex. For this model, it was implemented the programming language (hoc) of the NEURON software, and was elaborated based on electrophysiological data (i.e. membrane properties and ionic conductances), and morphological measurements, taken in vitro previously by other investigators. The analysis was done from electrophysiological parameters of the firing pattern. Our model suggests a great influence of dendritic morphology over the electrophysiology, spike generation and firing pattern. The results obtained show that, even when all the biophysical parameters involved in ion channel dynamics are maintained constant, it is possible to induce a strong increase in electric behavior and spike firing, from a reduction in the length and diameter of the dendritic trees\' ramifications. These results, also contribute to a explanation of the mentioned paradox.