Dynamical Entropy Production in Spiking Neuron Networks in the Balanced State

We demonstrate deterministic extensive chaos in the dynamics of large sparse networks of theta neurons in the balanced state. The analysis is based on numerically exact calculations of the full spectrum of Lyapunov exponents, the entropy production rate and the attractor dimension. Extensive chaos is found in inhibitory networks and becomes more intense when an excitatory population is included. We find a strikingly high rate of entropy production that would limit information representation in cortical spike patterns to the immediate stimulus response.Comment: 4 pages, 4 figure

Real time forecasts of inflation: the role of financial variables

We present a mixed-frequency model for daily forecasts of euro area inflation. The model combines a monthly index of core inflation with daily data from financial markets; estimates are carried out with the MIDAS regression approach. The forecasting ability of the model in real-time is compared with that of standard VARs and of daily quotes of economic derivatives on euro area inflation. We find that the inclusion of daily variables helps to reduce forecast errors with respect to models that consider only monthly variables. The mixed-frequency model also displays superior predictive performance with respect to forecasts solely based on economic derivatives.forecasting inflation, real time forecasts, dynamic factor models, MIDAS regression, economic derivatives

FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure

In this paper a dynamic factor model with mixed frequency is proposed (FaMIDAS), where the past observations of high frequency indicators are used following the MIDAS approach. This structure is able to represent with richer dynamics the information content of the economic indicators and produces smoothed factors and forecasts. In addition, it is particularly suited for real time forecast as it reduces the problem of the unbalanced data set and of the revisions in preliminary data. In the empirical application we specify and estimate a FaMIDAS to forecast Italian quarterly GDP. The short-term forecasting performance is evaluated against other mixed frequency models in a pseudo-real time experiment, also allowing for pooled forecast from factor models.Mixed frequency models, Dynamic factor Models, MIDAS, Forecasting

The economic consequences of euro area modelling shortcuts

The available empirical evidence suggests that non-negligible differences in economic structures persist among euro area countries. Because of these asymmetries, an area-wide modelling approach is arguably less reliable, from a strictly statistical viewpoint, than a multi-country one. This paper revolves around the following issue: are those (statistically detectable) asymmetries of any practical relevance when it comes to supporting monetary policy decision-making? To answer this question, we compute optimal parameter values of a Taylor-type rule, using two simple area-wide and multi-country models for the three largest economies in the euro area, and compare the corresponding optimized loss functions. The results suggest that the welfare under performance of an area-wide modelling approach is likely to be far from trifling.euro area, aggregation, monetary policy rules

FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure

In this paper a dynamic factor model with mixed frequency is proposed (FaMIDAS), where the past observations of high frequency indicators are used following the MIDAS approach. This structure is able to represent with richer dynamics the information content of the economic indicators and produces smoothed factors and forecasts. In addition, the Kalman filter is applied, which is particularly suited for dealing with unbalanced data set and revisions in the preliminary data. In the empirical application for the Italian quarterly GDP the short-term forecasting performance is evaluated against other mixed frequency models in a pseudo-real time experiment, also allowing for pooled forecast from factor models.mixed frequency models, dynamic factor models, MIDAS,forecasting.

Come un’isola ricorda : riflessioni dal fieldwork

The relation between anthropology and history, as well as that between history and social memory, have always been controversial, because of what may be termed a reciprocal amnesia, or worse, the confusion of roles and spaces. Well before its “reflexive turn” anthropology, albeit aware of the importance of history, produced descriptions of isolated populations immersed in a timeless present or representing their past through cyclical and repetitive schemes. This was congenial to a simultaneity hyphen based analysis where myths, rites, kinship and so on could be routed in the same logic. Moreover the indistinct and narrative face of every oral and autobiographical testimony, its subjectivity, and the lack of a shared method in the witness recollection only made things worse. Nevertheless, the critical use of the different disciplines could permit a more complex and articulate understanding of past and present structures through which a collectivity represents and communicates itself and its values, reiterating the same configuration and discovering other ways to rethink it. As shown in interviews carried out with two Maltese informants, the local interpretative and reified structure of the Maltese milieu assumes the definite and accepted shape of a political “irresoluble” opposition, traces the paths and the steps of a life story, organizes in a divided vision a certain temporal course. But the possibility to delve deep in the complexity of each particular narrative can also make a breach for further, alternative and more complex representations of their context, both synchronic and diachronic. The study is based on a long term fieldwork in Malta. The main sources are the narratives of a good number of informants. My sample was based on a number of criteria including and depending on the position occupied in the political and cultural field, as well as the networks they are embedded in. They belonged both to the official, institutional field rather than the popular one and come from every part of the island. I met some of them only for one formal taped interview, while with others I managed to entertain a more engaged relation consisting of multiple meetings during which the level of reciprocal trust grew into ever stronger confidence. The fieldwork includes also participation in political meetings and public events as well as indepth analyses of written sources.peer-reviewe

Aggregation bias in macro models: does it matter foir the euro area?

The euro area represents a case-study of great institutional relevance for the econometric problem of aggregation bias. The available data can be used to analyze the area either with aggregate or with country-specific models. The choice should be the result of a statistical comparison between the two options, with respect to the specific model. In this paper we suggest a representation of the aggregation error based on unobservable components and explicitly conceived for aggregations over a small number of economies. In the empirical application two alternative models are estimated: the first specifies the main euro countries while the other refers to the whole area. We then evaluate the aggregation error either from the viewpoint of a comparison of the two models with standard methods, or looking at the components of the representation suggested here. Both categories of results indicate non-negligible aggregation errors for the euro area.aggregation bias, euro-area modeling

Glypican-1 proteoliposomes enhance growth factor activity for therapeutic angiogenesis

Peripheral arterial disease affects more than 27 million patients in the United States. PAD can lead to peripheral limb ischemia and result in non-healing foot ulcers. Currently, surgical therapies such a stenting, grafting, and bypass, exist for treatment of ischemia, but these treatments are prone to long-term failure. These treatments also only successfully yield beneficial results about 25% of the time. Alternatively, regenerative therapies that stimulate the growth of new vasculature have great potential for treating peripheral and myocardial ischemia. Growth factor based therapies that induce neovascularization have shown promising results in animal models, but have limited success in clinical trials. This discrepancy is most likely a result of growth factor resistance brought on by diseases that lead to peripheral vascular disease. Here, we have developed a new method for enhancing the activity of growth factors in growth factor resistant disease states such as diabetes and hyperlipidemia. Our novel method delivers the growth factor co-receptor glypican-1 embedded in a liposomal carrier to create a glypican-1 proteoliposome (a “glypisome”). By co-delivering the co-receptor glypican-1 along with the growth factor, we hope to overcome growth factor resistance associated with long-term disease. Here we optimize glypisome composition to maximize angiogenic response when co-delivered with growth factors, through the use of in vitro endothelial assays and explore what mechanisms bring about this change in activity. Then we determine therapeutic potential of co-delivering glypisomes with growth factors in vivo by assessing neovascularization in healthy and disease mouse models of ischemia. We also explore overcoming disease mediated growth factor resistance by delivering glioblastoma-derived exosomes as a naturally occurring alternative to the glypisomes that we have developed. We test these exosomes in both in vitro endothelial assays and in vivo with a mouse hind limb ischemia model. We demonstrate that delivering these co-receptors in conjunction with the growth factor will allow us to overcome the disease phenotype and lead to a viable growth factor therapy for peripheral arterial disease.Biomedical Engineerin

Explicit recognition of emotional facial expressions is shaped by expertise: evidence from professional actors

Can reading others' emotional states be shaped by expertise? We assessed processing of emotional facial expressions in professional actors trained either to voluntary activate mimicry to reproduce character's emotions (as foreseen by the “Mimic Method”), or to infer others' inner states from reading the emotional context (as foreseen by “Stanislavski Method”). In explicit recognition of facial expressions (Experiment 1), the two experimental groups differed from each other and from a control group with no acting experience: the Mimic group was more accurate, whereas the Stanislavski group was slower. Neither acting experience, instead, influenced implicit processing of emotional faces (Experiment 2). We argue that expertise can selectively influence explicit recognition of others' facial expressions, depending on the kind of “emotional expertise”