Multiple time scales of temporal response in pyramidal and fast spiking cortical neurons

Neural dynamic processes correlated over several time scales are found in vivo, in stimulus-evoked as well as spontaneous activity, and are thought to affect the way sensory stimulation is processed. Despite their potential computational consequences, a systematic description of the presence of multiple time scales in single cortical neurons is lacking. In this study, we injected fast spiking and pyramidal (PYR) neurons in vitro with long-lasting episodes of step-like and noisy, in-vivo-like current. Several processes shaped the time course of the instantaneous spike frequency, which could be reduced to a small number (1-4) of phenomenological mechanisms, either reducing (adapting) or increasing (facilitating) the neuron's firing rate over time. The different adaptation/facilitation processes cover a wide range of time scales, ranging from initial adaptation (<10 ms, PYR neurons only), to fast adaptation (<300 ms), early facilitation (0.5-1 s, PYR only), and slow (or late) adaptation (order of seconds). These processes are characterized by broad distributions of their magnitudes and time constants across cells, showing that multiple time scales are at play in cortical neurons, even in response to stationary stimuli and in the presence of input fluctuations. These processes might be part of a cascade of processes responsible for the power-law behavior of adaptation observed in several preparations, and may have far-reaching computational consequences that have been recently described.

A multiple source model for 6 MV photon beam dose calculations using Monte Carlo

A multiple source model (MSM) for the 6 MV beam of a Varian Clinac 2300 C/D was developed by simulating radiation transport through the accelerator head for a set of square fields using the GEANT Monte Carlo (MC) code. The corresponding phase space (PS) data enabled the characterization of 12 sources representing the main components of the beam defining system. By parametrizing the source characteristics and by evaluating the dependence of the parameters on field size, it was possible to extend the validity of the model to arbitrary rectangular fields which include the central 3 x 3 cm2 field without additional precalculated PS data. Finally, a sampling procedure was developed in order to reproduce the PS data. To validate the MSM, the fluence, energy fluence and mean energy distributions determined from the original and the reproduced PS data were compared and showed very good agreement. In addition, the MC calculated primary energy spectrum was verified by an energy spectrum derived from transmission measurements. Comparisons of MC calculated depth dose curves and profiles, using original and PS data reproduced by the MSM, agree within 1% and 1 mm. Deviations from measured dose distributions are within 1.5% and 1 mm. However, the real beam leads to some larger deviations outside the geometrical beam area for large fields. Calculated output factors in 10 cm water depth agree within 1.5% with experimentally determined data. In conclusion, the MSM produces accurate PS data for MC photon dose calculations for the rectangular fields specified.

Multiple GABA receptors in rabbit retina

The task of encoding and processing complex sensory input requires many types of transsynaptic signals. This requirement is served in part by an extensive group of neurotransmitter substances which may include thirty or more different compounds. At the next level of information processing, the existence of multiple receptors for a given neurotransmitter appears to be a widely used mechanism to generate multiple responses to a given first messenger (Snyder and Goodman, 1980). Despite the wealth of published data on GABA receptors, the existence of more than one GABA receptor was in doubt until the mid 1980's. Presently there is still disagreement on the number of types of GABA receptors, estimates for which range from two to four (DeFeudis, 1983; Johnston, 1985). Part of the problem in evaluating data concerning multiple receptor types is the lack of information on the number of gene products and their subsequent supramolecular organization in different neurons. In order to evaluate the question concerning the diversity of GABA receptors in the nervous system, we must rely on indirect information derived from a wide variety of experimental techniques. These include pharmacological binding studies to membrane fractions, electrophysiological studies, localization studies, purification studies, and functional assays. Almost all parts of the central and peripheral nervous system use GABA as a neurotransmitter, and these experimental techniques have therefore been applied to many different parts of the nervous system for the analysis of GABA receptor characteristics. We are left with a large amount of data from a wide variety of techniques derived from many parts of the nervous system. When this project was initiated in 1983, there were only a handful of pharmacological tools to assess the question of multiple GABA receptors. The approach adopted was to focus on a single model system, using a variety of experimental techniques, in order to evaluate the existence of multiple forms of GABA receptors. Using the in vitro rabbit retina, a combination of pharmacological binding studies, functional release studies and partial purification studies were undertaken to examine the GABA receptor composition of this tissue. Three types of GABA receptors were observed: Al receptors coupled to benzodiazepine and barbiturate modulation, and A2 or uncoupled GABA-A receptors, and GABA-B receptors. These results are evaluated and discussed in light of recent findings by others concerning the number and subtypes of GABA receptors in the nervous system. ^

Immune cell trafficking across the barriers of the central nervous system in multiple sclerosis and stroke

Each year about 650,000 Europeans die from stroke and a similar number lives with the sequelae of multiple sclerosis (MS). Stroke and MS differ in their etiology. Although cause and likewise clinical presentation set the two diseases apart, they share common downstream mechanisms that lead to damage and recovery. Demyelination and axonal injury are characteristics of MS but are also observed in stroke. Conversely, hallmarks of stroke, such as vascular impairment and neurodegeneration, are found in MS. However, the most conspicuous common feature is the marked neuroinflammatory response, marked by glia cell activation and immune cell influx. In MS and stroke the blood-brain barrier is disrupted allowing bone marrow-derived macrophages to invade the brain in support of the resident microglia. In addition, there is a massive invasion of auto-reactive T-cells into the brain of patients with MS. Though less pronounced a similar phenomenon is also found in ischemic lesions. Not surprisingly, the two diseases also resemble each other at the level of gene expression and the biosynthesis of other proinflammatory mediators. While MS has traditionally been considered to be an autoimmune neuroinflammatory disorder, the role of inflammation for cerebral ischemia has only been recognized later. In the case of MS the long track record as neuroinflammatory disease has paid off with respect to treatment options. There are now about a dozen of approved drugs for the treatment of MS that specifically target neuroinflammation by modulating the immune system. Interestingly, experimental work demonstrated that drugs that are in routine use to mitigate neuroinflammation in MS may also work in stroke models. Examples include Fingolimod, glatiramer acetate, and antibodies blocking the leukocyte integrin VLA-4. Moreover, therapeutic strategies that were discovered in experimental autoimmune encephalomyelitis (EAE), the animal model of MS, turned out to be also effective in experimental stroke models. This suggests that previous achievements in MS research may be relevant for stroke. Interestingly, the converse is equally true. Concepts on the neurovascular unit that were developed in a stroke context turned out to be applicable to neuroinflammatory research in MS. Examples include work on the important role of the vascular basement membrane and the BBB for the invasion of immune cells into the brain. Furthermore, tissue plasminogen activator (tPA), the only established drug treatment in acute stroke, modulates the pathogenesis of MS. Endogenous tPA is released from endothelium and astroglia and acts on the BBB, microglia and other neuroinflammatory cells. Thus, the vascular perspective of stroke research provides important input into the mechanisms on how endothelial cells and the BBB regulate inflammation in MS, particularly the invasion of immune cells into the CNS. In the current review we will first discuss pathogenesis of both diseases and current treatment regimens and will provide a detailed overview on pathways of immune cell migration across the barriers of the CNS and the role of activated astrocytes in this process. This article is part of a Special Issue entitled: Neuro inflammation: A common denominator for stroke, multiple sclerosis and Alzheimer's disease, guest edited by Helga de Vries and Markus Swaninger.

Input Price Variation Across Locations and a Generalized Measure of Cost Efficiency

We propose a nonparametric model for global cost minimization as a framework for optimal allocation of a firm's output target across multiple locations, taking account of differences in input prices and technologies across locations. This should be useful for firms planning production sites within a country and for foreign direct investment decisions by multi-national firms. Two illustrative examples are included. The first example considers the production location decision of a manufacturing firm across a number of adjacent states of the US. In the other example, we consider the optimal allocation of US and Canadian automobile manufacturers across the two countries.

Abstract multiple specialization and its application to program parallelization.

Program specialization optimizes programs for known valúes of the input. It is often the case that the set of possible input valúes is unknown, or this set is infinite. However, a form of specialization can still be performed in such cases by means of abstract interpretation, specialization then being with respect to abstract valúes (substitutions), rather than concrete ones. We study the múltiple specialization of logic programs based on abstract interpretation. This involves in principie, and based on information from global analysis, generating several versions of a program predicate for different uses of such predicate, optimizing these versions, and, finally, producing a new, "multiply specialized" program. While múltiple specialization has received theoretical attention, little previous evidence exists on its practicality. In this paper we report on the incorporation of múltiple specialization in a parallelizing compiler and quantify its effects. A novel approach to the design and implementation of the specialization system is proposed. The resulting implementation techniques result in identical specializations to those of the best previously proposed techniques but require little or no modification of some existing abstract interpreters. Our results show that, using the proposed techniques, the resulting "abstract múltiple specialization" is indeed a relevant technique in practice. In particular, in the parallelizing compiler application, a good number of run-time tests are eliminated and invariants extracted automatically from loops, resulting generally in lower overheads and in several cases in increased speedups.

Operational modal analisys using joint statistical analysis of multiple records

In Operational Modal Analysis (OMA) of a structure, the data acquisition process may be repeated many times. In these cases, the analyst has several similar records for the modal analysis of the structure that have been obtained at di�erent time instants (multiple records). The solution obtained varies from one record to another, sometimes considerably. The differences are due to several reasons: statistical errors of estimation, changes in the external forces (unmeasured forces) that modify the output spectra, appearance of spurious modes, etc. Combining the results of the di�erent individual analysis is not straightforward. To solve the problem, we propose to make the joint estimation of the parameters using all the records. This can be done in a very simple way using state space models and computing the estimates by maximum-likelihood. The method provides a single result for the modal parameters that combines optimally all the records.

Iterative bit- and power allocation in correlated MIMO systems

In this contribution a novel iterative bit- and power allocation (IBPA) approach has been developed when transmitting a given bit/s/Hz data rate over a correlated frequency non-selective (4× 4) Multiple-Input MultipleOutput (MIMO) channel. The iterative resources allocation algorithm developed in this investigation is aimed at the achievement of the minimum bit-error rate (BER) in a correlated MIMO communication system. In order to achieve this goal, the available bits are iteratively allocated in the MIMO active layers which present the minimum transmit power requirement per time slot.

Estrogen increases synaptic connectivity between single presynaptic inputs and multiple postsynaptic CA1 pyramidal cells: A serial electron-microscopic study

Dendritic spines are sites of the vast majority of excitatory synaptic input to hippocampal CA1 pyramidal cells. Estrogen has been shown to increase the density of dendritic spines on CA1 pyramidal cell dendrites in adult female rats. In parallel with increased spine density, estrogen has been shown also to increase the number of spine synapses formed with multiple synapse boutons (MSBs). These findings suggest that estrogen-induced dendritic spines form synaptic contacts with preexisting presynaptic boutons, transforming some previously single synapse boutons (SSBs) into MSBs. The goal of the current study was to determine whether estrogen-induced MSBs form multiple synapses with the same or different postsynaptic cells. To quantify same-cell vs. different-cell MSBs, we filled individual CA1 pyramidal cells with biocytin and serially reconstructed dendrites and dendritic spines of the labeled cells, as well as presynaptic boutons in synaptic contact with labeled and unlabeled (i.e., different-cell) spines. We found that the overwhelming majority of MSBs in estrogen-treated animals form synapses with more than one postsynaptic cell. Thus, in addition to increasing the density of excitatory synaptic input to individual CA1 pyramidal cells, estrogen also increases the divergence of input from individual presynaptic boutons to multiple postsynaptic CA1 pyramidal cells. These findings suggest the formation of new synaptic connections between previously unconnected hippocampal neurons.

Estudo e implementação de sinais de excitação aplicados em identificação de sistemas multivariáveis.

Devido à crescente implementação do Controle Preditivo baseado em Modelo (MPC) em outros processos além de refino e plantas petroquímicas, que geralmente possuem múltiplas entradas e saídas, tem-se um aumento na demanda de modelos gerados por identificação de sistemas. Identificar modelos que representem fielmente a dinâmica do processo depende em grande medida das características dos sinais de excitação dos processos. Assim, o foco deste trabalho é realizar um estudo dos sinais típicos usados em identificação de sistemas, PRBS e GBN, em uma abordagem multivariável. O estudo feito neste trabalho parte das características da geração dos sinais individualmente, depois é feita uma análise de correlação cruzada dos sinais de entrada, observando a influência desta sobre os resultados de identificação. Evitar uma alta correlação entre os sinais de entrada permite determinar o efeito de cada entrada sobre a saída no processo de identificação. Um ponto importante no projeto de sinais de identificação de sistemas multivariáveis é a frequência dos mesmos para conseguir excitar os processos nas regiões de frequência de operação normal e assim extrair a maior informação dinâmica possível do processo. As características estudadas são avaliadas por meio de testes em três plantas simuladas diferentes, categorizadas como mal, medianamente e bem condicionadas. Estas implementações foram feitas usando sinais GBN e PRBS de diferentes frequências. Expressões para a caracterização dos sinais de excitação foram avaliadas identificando os processos em malha aberta e malha fechada. Para as plantas mal condicionadas foram implementados sinais compostos por uma parte completamente correlacionada e uma parte não-correlacionada, conhecido como método de dois passos. Finalmente são realizados experimentos de identificação em uma aplicação em tempo real de uma planta piloto de neutralização de pH. Os testes realizados na planta foram feitos visando avaliar os estudos de frequência e correlação em uma aplicaficção real. Os resultados mostram que a condição de sinais completamente descorrelacionados n~ao deve ser cumprida para ter bons resultados nos modelos identificados. Isto permite ter mais exibilidade na geração do conjunto de sinais de excitação.

Recovery of multiple amplitude levels from a DQPSK NRZ signal using a single Mach-Zehnder Interferometer

In this research the recovery of a DQPSK signal will be demonstrated using a single Mach-Zehnder Interferometer (MZI). By changing the phase delay in one of the arms it will be shown that different delays will produce different output levels. It will also be shown that with a certain level of phase shift the DQPSK signal can be converted into four different equally spaced optical power levels. With each decoded level representing one of the four possible bit permutations. By using this additional phase shift in one of the arms the number of MZIs required for decoding can be reduced from two to one.

Multiple criteria optimization of contemporary logistics distribution network problems

In the contemporary customer-driven supply chain, maximization of customer service plays an equally important role as minimization of costs for a company to retain and increase its competitiveness. This article develops a multiple-criteria optimization approach, combining the analytic hierarchy process (AHP) and an integer linear programming (ILP) model, to aid the design of an optimal logistics distribution network. The proposed approach outperforms traditional cost-based optimization techniques because it considers both quantitative and qualitative factors and also aims at maximizing the benefits of deliverer and customers. In the approach, the AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to some critical customer-oriented criteria. The results of AHP prioritization are utilized as the input of the ILP model, the objective of which is to select the best warehouses at the lowest possible cost. In this article, two commercial packages are used: including Expert Choice and LINDO.

Characterization of human mesenchymal stem cells from multiple donors and the implications for large scale bioprocess development

Cell-based therapies have the potential to contribute to global healthcare, whereby the use of living cells and tissues can be used as medicinal therapies. Despite this potential, many challenges remain before the full value of this emerging field can be realized. The characterization of input material for cell-based therapy bioprocesses from multiple donors is necessary to identify and understand the potential implications of input variation on process development. In this work, we have characterized bone marrow derived human mesenchymal stem cells (BM-hMSCs) from multiple donors and discussed the implications of the measurable input variation on the development of autologous and allogeneic cell-based therapy manufacturing processes. The range of cumulative population doublings across the five BM-hMSC lines over 30 days of culture was 5.93, with an 18.2% range in colony forming efficiency at the end of the culture process and a 55.1% difference in the production of interleukin-6 between these cell lines. It has been demonstrated that this variation results in a range in the process time between these donor hMSC lines for a hypothetical product of over 13 days, creating potential batch timing issues when manufacturing products from multiple patients. All BM-hMSC donor lines demonstrated conformity to the ISCT criteria but showed a difference in cell morphology. Metabolite analysis showed that hMSCs from the different donors have a range in glucose consumption of 26.98 pmol cell−1 day−1, Lactate production of 29.45 pmol cell−1 day−1 and ammonium production of 1.35 pmol cell−1 day−1, demonstrating the extent of donor variability throughout the expansion process. Measuring informative product attributes during process development will facilitate progress towards consistent manufacturing processes, a critical step in the translation cell-based therapies.

Optimization Problem in a Class of Linear System. Application to Multiple Drug Administration

2000 Mathematics Subject Classification: 62H15, 62P10.

Improved data visualisation through multiple dissimilarity modelling

Popular dimension reduction and visualisation algorithms rely on the assumption that input dissimilarities are typically Euclidean, for instance Metric Multidimensional Scaling, t-distributed Stochastic Neighbour Embedding and the Gaussian Process Latent Variable Model. It is well known that this assumption does not hold for most datasets and often high-dimensional data sits upon a manifold of unknown global geometry. We present a method for improving the manifold charting process, coupled with Elastic MDS, such that we no longer assume that the manifold is Euclidean, or of any particular structure. We draw on the benefits of different dissimilarity measures allowing for the relative responsibilities, under a linear combination, to drive the visualisation process.