339 research outputs found
Electrical Compartmentalization in Neurons
The dendritic tree of neurons plays an important role in information processing in the brain. While it is thought that dendrites require independent subunits to perform most of their computations, it is still not understood how they compartmentalize into functional subunits. Here, we show how these subunits can be deduced from the properties of dendrites. We devised a formalism that links the dendritic arborization to an impedance-based tree graph and show how the topology of this graph reveals independent subunits. This analysis reveals that cooperativity between synapses decreases slowly with increasing electrical separation and thus that few independent subunits coexist. We nevertheless find that balanced inputs or shunting inhibition can modify this topology and increase the number and size of the subunits in a context-dependent manner. We also find that this dynamic recompartmentalization can enable branch-specific learning of stimulus features. Analysis of dendritic patch-clamp recording experiments confirmed our theoretical predictions.Peer reviewe
Current practice in software development for computational neuroscience and how to improve it
Almost all research work in computational neuroscience involves software. As
researchers try to understand ever more complex systems, there is a continual
need for software with new capabilities. Because of the wide range of questions
being investigated, new software is often developed rapidly by individuals or
small groups. In these cases, it can be hard to demonstrate that the software
gives the right results. Software developers are often open about the code they
produce and willing to share it, but there is little appreciation among
potential users of the great diversity of software development practices and
end results, and how this affects the suitability of software tools for use in
research projects. To help clarify these issues, we have reviewed a range of
software tools and asked how the culture and practice of software development
affects their validity and trustworthiness. We identified four key questions
that can be used to categorize software projects and correlate them with the
type of product that results. The first question addresses what is being
produced. The other three concern why, how, and by whom the work is done. The
answers to these questions show strong correlations with the nature of the
software being produced, and its suitability for particular purposes. Based on
our findings, we suggest ways in which current software development practice in
computational neuroscience can be improved and propose checklists to help
developers, reviewers and scientists to assess the quality whether particular
pieces of software are ready for use in research
Structural Plasticity Controlled by Calcium Based Correlation Detection
Hebbian learning in cortical networks during development and adulthood relies on the presence of a mechanism to detect correlation between the presynaptic and the postsynaptic spiking activity. Recently, the calcium concentration in spines was experimentally shown to be a correlation sensitive signal with the necessary properties: it is confined to the spine volume, it depends on the relative timing of pre- and postsynaptic action potentials, and it is independent of the spine's location along the dendrite. NMDA receptors are a candidate mediator for the correlation dependent calcium signal. Here, we present a quantitative model of correlation detection in synapses based on the calcium influx through NMDA receptors under realistic conditions of irregular pre- and postsynaptic spiking activity with pairwise correlation. Our analytical framework captures the interaction of the learning rule and the correlation dynamics of the neurons. We find that a simple thresholding mechanism can act as a sensitive and reliable correlation detector at physiological firing rates. Furthermore, the mechanism is sensitive to correlation among afferent synapses by cooperation and competition. In our model this mechanism controls synapse formation and elimination. We explain how synapse elimination leads to firing rate homeostasis and show that the connectivity structure is shaped by the correlations between neighboring inputs
PyNEST: A Convenient Interface to the NEST Simulator
The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 104 neurons and 107 to 109 synapses. NEST is implemented in C++ and can be used on a large range of architectures from single-core laptops over multi-core desktop computers to super-computers with thousands of processor cores. Python (http://www.python.org) is a modern programming language that has recently received considerable attention in Computational Neuroscience. Python is easy to learn and has many extension modules for scientific computing (e.g. http://www.scipy.org). In this contribution we describe PyNEST, the new user interface to NEST. PyNEST combines NEST's efficient simulation kernel with the simplicity and flexibility of Python. Compared to NEST's native simulation language SLI, PyNEST makes it easier to set up simulations, generate stimuli, and analyze simulation results. We describe how PyNEST connects NEST and Python and how it is implemented. With a number of examples, we illustrate how it is used
Review komatiites: from Earth’s geological settings to planetary and astrobiological contexts
23 pages (final publisher version), 55 pages (attached post-print version).-- Published online: 15 February 2007.-- ArXiv pre-print available at: http://arxiv.org/abs/physics/0512118Komatiites are fascinating volcanic rocks. They are among the most ancient lavas of the Earth following the 3.8 Ga pillow basalts at Isua and they represent some of the oldest ultramafic magmatic rocks preserved in the Earth’s crust at 3.5 Ga. This fact, linked to their particular features (high magnesium content, high melting temperatures, low dynamic viscosities, etc.), has attracted the community of geoscientists since their discovery in the early sixties, who have tried to determine their origin and understand their meaning in the context of terrestrial mantle evolution. In addition, it has been proposed that komatiites are not restricted to our planet, but they could be found in other extraterrestrial settings in our Solar System (particularly on Mars and Io). It is important to note that komatiites may be extremely significant in the study of the origins and evolution of Life on Earth. They not only preserve essential geochemical clues of the interaction between the pristine Earth rocks and atmosphere, but also may have been potential suitable sites for biological processes to develop. Thus, besides reviewing the main geodynamic, petrological and geochemical characteristics of komatiites, this paper also aims to widen their investigation beyond the classical geological prospect, calling attention to them as attractive rocks for research in Planetology and Astrobiology.We acknowledge the grant support of the National Institute of Aerospace Technique "Esteban Terradas" (INTA)—Centro de Astrobiología.Peer reviewe
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