On nonlinearity in neural encoding models applied to the primary visual cortex

Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansions of the input variables (enlarging the number of inputs) or train a simple but different model for each area of the data domain. Spline-based models are popular within the first category. Kernel smoothing methods fall into the second category. Whereas the first choice is useful for globally characterizing complex functions, the second is very handy for temporal data and is able to include inner-state subject variations. Also, interactions among stimuli are considered. We compare state-of-the-art firing rate prediction methods with some more sophisticated spline-based nonlinear methods: multivariate adaptive regression splines and sparse additive models. We also study the impact of kernel smoothing. Finally, we explore the combination of various local models in an incremental learning procedure. Our goal is to demonstrate that appropriate nonlinearity treatment can greatly improve the results. We test our hypothesis on both synthetic data and real neuronal recordings in cat primary visual cortex, giving a plausible explanation of the results from a biological perspective.

Estudio de vibraciones de las voladuras de producción en la cantera de Buruntza y su afección sobre el tramo de la red ferroviaria Andoain – Urnieta (País Vasco)

El estudio de vibraciones tiene por objetivo fijar una banda de seguridad para proteger la nueva línea ferroviaria de alta velocidad Madrid – Vitoria – San Sebastián (tramo Andoain – Urnieta).Las tomas de datos han permitido el cálculo de unas leyes de amortiguación de la propagación de las ondas de vibración que permiten predecir cuál será la magnitud de vibración generada a una cierta distancia de la explotación cuando se detona una carga de explosivo determinada. Así mismo, se lleva a cabo un análisis de las concentraciones de energía (vibraciones) que podrían producirse durante una voladura tipo de producción atendiendo a diferentes secuencias de disparo. Con este método, basado en el disparo de un “barreno semilla” de similares condiciones de carga y arranque que un barreno típico de producción, se pretende resaltar la importancia que tiene el rango de las frecuencias en el proceso de generación y transmisión de vibraciones en el terreno, y consecuentemente en los criterios de protección de estructuras frente a tales vibraciones. ABSTRACT The aim of the vibration study is to set a security band to protect the Spanish high speed train (AVE) which goes Madrid-Vitoria-San Sebastian (section Andoain- Urnieta). The data gathered has made possible the calculation of absorption laws of propagation of vibrating waves, that allow the prediction of the magnitude created at a certain distance of the detonation of a known explosive. In addition, an analysis of the energy concentrations that could appear during a blasting in different sequences is made. With this method based on the firing of a seed drill with similar load and boot conditions of a common production drill, is intended to highlight the importance of the frequency range in the process of vibrations transmission and generation in the field, and consequently the importance in the structures protection criteria against these vibrations.

Developmental Expression of Kv Potassium Channels at the Axon Initial Segment of Cultured Hippocampal Neurons

Axonal outgrowth and the formation of the axon initial segment (AIS) are early events in the acquisition of neuronal polarity. The AIS is characterized by a high concentration of voltage-dependent sodium and potassium channels. However, the specific ion channel subunits present and their precise localization in this axonal subdomain vary both during development and among the types of neurons, probably determining their firing characteristics in response to stimulation. Here, we characterize the developmental expression of different subfamilies of voltage-gated potassium channels in the AISs of cultured mouse hippocampal neurons, including subunits Kv1.2, Kv2.2 and Kv7.2. In contrast to the early appearance of voltage-gated sodium channels and the Kv7.2 subunit at the AIS, Kv1.2 and Kv2.2 subunits were tethered at the AIS only after 10 days in vitro. Interestingly, we observed different patterns of Kv1.2 and Kv2.2 subunit expression, with each confined to distinct neuronal populations. The accumulation of Kv1.2 and Kv2.2 subunits at the AIS was dependent on ankyrin G tethering, it was not affected by disruption of the actin cytoskeleton and it was resistant to detergent extraction, as described previously for other AIS proteins. This distribution of potassium channels in the AIS further emphasizes the heterogeneity of this structure in different neuronal populations, as proposed previously, and suggests corresponding differences in action potential regulation.

Progress on optimization of the solar cell fabrication process by impurity-to-efficiency predictive simulator

To optimize the last high temperature step of a standard solar cell fabrication process (the contact cofiring step), the aluminium gettering is incorporated in the Impurity-to-Efficiency simulation tool, so that it models the phosphorus and aluminium co-gettering effect on iron impurities. The impact of iron on the cell efficiency will depend on the balance between precipitate dissolution and gettering. Gettering efficiency is similar in a wide range of peak temperatures (600-850 ºC), so that this peak temperature can be optimized favoring other parameters (e.g. ohmic contact). An industrial co-firing step can enhance the co-gettering effect by adding a temperature plateau after the peak of temperature. For highly contaminated materials, a short plateau (menor que 2 min) at low temperature (600 ºC) is shown to reduce the dissolved iron.

Precipitated iron: a limit on gettering efficacy in multicrystalline silicon

A phosphorus diffusion gettering model is used to examine the efficacy of a standard gettering process on interstitial and precipitated iron in multicrystalline silicon. The model predicts a large concentration of precipitated iron remaining after standard gettering for most as-grown iron distributions. Although changes in the precipitated iron distribution are predicted to be small, the simulated post-processing interstitial iron concentration is predicted to depend strongly on the as-grown distribution of precipitates, indicating that precipitates must be considered as internal sources of contamination during processing. To inform and validate the model, the iron distributions before and after a standard phosphorus diffusion step are studied in samples from the bottom, middle, and top of an intentionally Fe-contaminated laboratory ingot. A census of iron-silicide precipitates taken by synchrotron-based X-ray fluorescence microscopy confirms the presence of a high density of iron-silicide precipitates both before and after phosphorus diffusion. A comparable precipitated iron distribution was measured in a sister wafer after hydrogenation during a firing step. The similar distributions of precipitated iron seen after each step in the solar cell process confirm that the effect of standard gettering on precipitated iron is strongly limited as predicted by simulation. Good agreement between the experimental and simulated data supports the hypothesis that gettering kinetics is governed by not only the total iron concentration but also by the distribution of precipitated iron. Finally, future directions based on the modeling are suggested for the improvement of effective minority carrier lifetime in multicrystalline silicon solar cells.