19,649 research outputs found

    Self-generated neural activity : models and perspective

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    Poster presentation: The brain is autonomously active and this self-sustained neural activity is in general modulated, but not driven, by the sensory input data stream [1,2]. Traditionally one has regarded this eigendynamics as resulting from inter-modular recurrent neural activity [3]. Understanding the basic modules for cognitive computation is, in this view, the primary focus of research and the overall neural dynamics would be determined by the the topology of the intermodular pathways. Here we examine an alternative point of view, asking whether certain aspects of the neural eigendynamics have a central functional role for overall cognitive computation [4,5]. Transiently stable neural activity is regularly observed on the cognitive time-scale of 80–100 ms, with indications that neural competition [6] plays an important role in the selection of the transiently stable neural ensembles [7], also denoted winning coalitions [8]. We report on a theory approach which implements these two principles, transient-state dynamics and neural competition, in terms of an associative neural network with clique encoding [9]. A cognitive system [10] with a non-trivial internal eigendynamics has two seemingly contrasting tasks to fulfill. The internal processes need to be regular and not chaotic on one side, but sensitive to the afferent sensory stimuli on the other side. We show, that these two contrasting demands can be reconciled within our approach based on competitive transient-state dynamics, when allowing the sensory stimuli to modulate the competition for the next winning coalition. By testing the system with the bars problem, we find an emerging cognitive capability. Only based on the two basic architectural principles, neural competition and transient-state dynamics, with no explicit algorithmic encoding, the system performs on its own a non-linear independent component analysis of input data stream. The system has rudimentary biological features. All learning is local Hebbian-style, unsupervised and online. It exhibits an ever-ongoing eigendynamics and at no time is the state or the value of synaptic strengths reset or the system restarted; there is no separation between training and performance. We believe that this kind of approach – cognitive computation with autonomously active neural networks – to be an emerging field, relevant both for system neuroscience and synthetic cognitive systems

    The seniority conundrum: bail out countries but bail in private, short-term creditors? CEPS Commentary, 6 December 2010

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    Despite its large size relative to the small Irish economy, the bailout announced by the Eurogroup following its meeting of 28 November 2010 is not working, as evidenced by the continuing rise in risk premiums. CEPS Director Daniel Gros argues in this commentary that part of the problem lies in a seemingly innocuous provision in the proposed permanent successor to the current European Financial Stability Facility in 2013. The argument is tricky, but at the heart of the problem lies the insistence that rescue financing is senior to private debt while simultaneously ruling out rescheduling of short-term debt

    Germany as Scapegoat. CEPS Commentary, 10 December 2013

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    Germany has been an attractive target for external-deficit countries in Europe and beyond, but beating up on Germany alone appears to be the wrong way to get results. This CEPS Commentary by Daniel Gros argues that the discussion of Germany’s surplus confuses the issues in two ways. First, he points out that although the German economy and its surplus loom large in the context of Europe, an adjustment by Germany alone would only modestly benefit the eurozone periphery. Second, in the global context, he finds that adjustment by Germany alone would benefit many countries a little, but other surplus countries including Russia, China and Japan, would benefit disproportionally

    Autonomous Dynamics in Neural networks: The dHAN Concept and Associative Thought Processes

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    The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules

    The Bank Resolution Compromise: Incomplete, but workable? CEPS Commentary, 19 December 2013

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    Calling the Single Resolution Mechanism an “inelegant step in the right direction”, this Commentary singles out the Single Resolution Fund, with its considerable mutualisation of risk, as the key advance – but one that will require changes over time in the extremely complex decision-making mechanisms agreed

    Europe in the IMF

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    Next time must be different. CEPS Commentaries, 4 November 2009

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    In signing the Lisbon Treaty on November 3rd, Czech President Václav Klaus brought to an anti-climatic close years of protracted and often acrimonious negotiations to overhaul the European Union’s institutional infrastructure. The EU's reform treaty is now fully ratified and is expected to enter into force on 1 December 2009. However frustrating and bruising the ratification experience may have been, it is hoped that the whole saga will have the unintended (but finally, positive) consequence of strengthening the determination of those wishing to ensure that the next round of treaty change can enter into force even if one or more member countries is not willing or able to agree to it

    The Treaty on Stability, Coordination and Governance in the Economic and Monetary Union (aka Fiscal Compact). CEPS Commentary, 8 March 2012

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    All in all, this Commentary finds that the Fiscal Compact signed on 2 March 2012 by all member states of the EU (except the UK and the Czech Republic) may be long on good intentions but is rather short on substance. The main danger is that that it has been oversold and in no way constitutes a first step towards fiscal or political union. It is likely that the ratification process (e.g. the referendum in Ireland) and then the implementation process in some difficult countries (e.g. France) will receive a lot of attention and create a distorted impression of the importance of the Fiscal Compact. Once the initial excitement is over, however and national fiscal rules have been put in place, this Treaty will quietly be forgotten

    Competitiveness pact: flawed economies? CEPS Commentary, 18 March 2011

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    The economic philosophy behind the Competitiveness Pact now before the European Council can be summarized by two hypotheses: 1. If we fix (relative?) wages, no external imbalances can arise since relative costs determine export performance. 2. Higher productivity always means more ‘competitiveness’, and is thus always useful to reduce divergences. On first sight, this Commentary finds that both theses seem to make sense, but on closer inspection, neither corresponds to reality
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