Combinatorial structures and processing in Neural Blackboard Architectures

We discuss and illustrate Neural Blackboard Architectures (NBAs) as the basis for variable binding and combinatorial processing the brain. We focus on the NBA for sentence structure. NBAs are based on the notion that conceptual representations are in situ, hence cannot be copied or transported. Novel combinatorial struc- tures can be formed with these representations by embedding them in NBAs. We discuss and illustrate the main characteristics of this form of combinatorial pro- cessing. We also illustrate the NBA for sentence structures by simulating neural activity as found in recently reported intracranial brain observations. Furthermore, we will show how the NBA can account for ambiguity resolution and garden path effects in sentence processing

The necessity of connection structures in neural models of variable binding

In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other (‘connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures

The state of MIIND

MIIND (Multiple Interacting Instantiations of Neural Dynamics) is a highly modular multi-level C++ framework, that aims to shorten the development time for models in Cognitive Neuroscience (CNS). It offers reusable code modules (libraries of classes and functions) aimed at solving problems that occur repeatedly in modelling, but tries not to impose a specific modelling philosophy or methodology. At the lowest level, it offers support for the implementation of sparse networks. For example, the library SparseImplementationLib supports sparse random networks and the library LayerMappingLib can be used for sparse regular networks of filter-like operators. The library DynamicLib, which builds on top of the library SparseImplementationLib, offers a generic framework for simulating network processes. Presently, several specific network process implementations are provided in MIIND: the Wilson–Cowan and Ornstein–Uhlenbeck type, and population density techniques for leaky-integrate-and-fire neurons driven by Poisson input. A design principle of MIIND is to support detailing: the refinement of an originally simple model into a form where more biological detail is included. Another design principle is extensibility: the reuse of an existing model in a larger, more extended one. One of the main uses of MIIND so far has been the instantiation of neural models of visual attention. Recently, we have added a library for implementing biologically-inspired models of artificial vision, such as HMAX and recent successors. In the long run we hope to be able to apply suitably adapted neuronal mechanisms of attention to these artificial models

Новый взгляд на творчество М. Горького: обзор научных публикаций последнего пятнадцатилетия

Проблема переосмысления творческого наследия русского писателя М. Горького является одной из самых актуальных в современном литературоведении. Кризис методологии, затронувший гуманитарные науки в конце XX века, привел к пересмотру многих казавшихся неоспоримыми истин в горьковедении. В статье предложен краткий аналитический обзор тех исследований последних пятнадцати лет, в которых представлены наиболее перспективные результаты, значимые с точки зрения нового подхода к изучению творчества М. Горького.The problem of a new view on the creative heritage of a Russian writer Maxim Gorky is one of the more urgent in modern literary criticism. Late XX century methodological crisis of humanities has led to a revision of most principles in Gorky studies that had earlier seemed irrefutable. A shot analytical review of the last 15 years' most valuable researches is offered in the article

Assessment of spatial and temporal patterns of green and blue water flows under natural conditions in inland river basins in Northwest China

In arid and semi-arid regions freshwater resources have become scarcer with increasing demands from socioeconomic development and population growth. Until recently, water research and management has maily focused on blue water but ignored green water. Furthermore, in data poor regions hydrological low under natural conditions are poorly characterised but are a prerequisite to inform future water resources management. Here we report on spatial and temporal patterns of both blue and green water flows that can be expected under natural conditions as simulated by the Soil and Water Assessment Tool (SWAT) for the Heihe river basin, the second largest inland river basin in Northwest China. Calibration ad validation at two hydrological stations show good performance of the SWAT model in modelling hydrological processes. The total green and blue water flows were 22.05-25.51 billion m3 in the 2000s for the Heihe river basin. Blue water flows are larger in upstream sub-basins than in downstream sub-basins mainly due to high precipitation and a large amount of snow and melting water in upstream. Green water flows are distributed more homogeneously among different sub-basins. The green water coefficient was 87%-89% in the 2000s for the entire river basin, varying from around 80%90% in up-and mid-stream sub-basins to above 90% in downstream sub-basins. This is much higher than reported green water coefficients in many other river basins. The spatial patterns of green water coefficients were closely linked to dominant land covers (e.g. snow cover upstream and desert downstream) and climate conditions (e.g. high precipitation upstream and low precipitation downstream). There are no clear consistent historical trends of change in green and blue water flows and the green water coefficient at both the river basin and sub-basin levels. This study provides insights into green and blue water endowments under natural conditions for the entire Heihe river basin at the sub-basin level. The results are helpful to benchmark the natural flows of water in the basin as part of improved water resources management in the inland river basins of China