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With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of

The importance of neuronal morphology has been recognized from the early days of neuroscience. Elucidating the functional roles of axonal and dendritic arbors in synaptic integration, signal transmission, network connectivity, and circuit dynamics requires quantitative analyses of digital three-dimensional reconstructions. We extensively searched the scientific literature for all original reports describing reconstructions of neuronal morphology since the advent of this technique three decades ago. From almost 50,000 titles, 30,000 abstracts, and more than 10,000 full-text articles, we identified 902 publications describing ∼44,000 digital reconstructions. Reviewing the growth of this field exposed general research trends on specific animal species, brain regions, neuron types, and experimental approaches. The entire bibliography, annotated with relevant metadata and (wherever available) direct links to the underlying digital data, is accessible at .

Neuronal morphology affects network connectivity, plasticity, and information processing. Uncovering the design principles and functional consequences of dendritic and axonal shape necessitates quantitative analysis and computational modeling of detailed experimental data. Digital reconstructions provide the required neuromorphological descriptions in a parsimonious, comprehensive, and reliable numerical format. NeuroMorpho.Org is the largest webaccessible repository service for digitally reconstructed neurons and one of the integrated resources in the Neuroscience Information Framework (NIF). Here we describe the NeuroMorpho.Org approach as an exemplary experience in designing, creating, populating, and curating a neuroscience digital resource. The simple three-tier architecture of NeuroMorpho.Org (web client, web server, and relational database) encompasses all necessary elements to support a large-scale, integrate-able repository. The data content, while heterogeneous in scientific scope and experimental origin, is unified in format and presentation by an in house standardization protocol. The server application (MRALD) is secure, customizable, and developer-friendly. Centralized processing and expert annotation yields a comprehensive set of metadata that enriches and complements the raw data. The thoroughly tested interface design allows for optimal and effective data search and retrieval. Availability of data in both original and standardized formats ensures compatibility with existing resources and fosters further tool development. Other key functions enable extensive exploration and discovery, including 3D and interactive visualization of branching, frequently measured morphometrics, and reciprocal links to the original PubMed publications. The integration of NeuroMorpho.Org with version-1 of the NIF (NIFv1) provides the opportunity to access morphological data in the context of other relevant resources and diverse subdomains of neuroscience, opening exciting new possibilities in data mining and knowledge discovery. The outcome of such coordination is the rapid and powerful advancement of neuroscience research at both the conceptual and technological level.

Neural networks that undergo acute insults display remarkable reorganization. This injury related plasticity is thought to permit recovery of function in the face of damage that cannot be reversed. Previously, an increase in the transmission strength at Schaffer collateral to CA1 pyramidal cell synapses was observed after long-term activity reduction in organotypic hippocampal slices. Here we report that, following acute preparation of adult rat hippocampal slices and surgical removal of area CA3, input to area CA1 was reduced and Schaffer collateral synapses underwent functional strengthening. This increase in synaptic strength was limited to Schaffer collateral inputs (no alteration to temporoammonic synapses) and acted to normalize postsynaptic discharge, supporting a homeostatic or compensatory response. Short-term plasticity was not altered, but an increase in immunohistochemical labeling of GluA1 subunits was observed in the stratum radiatum (but not stratum moleculare), suggesting increased numbers of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors and a postsynaptic locus of expression. Combined, these data support the idea that, in response to the reduction in presynaptic activity caused by removal of area CA3, Schaffer collateral synapses undergo a relatively rapid increase in functional efficacy likely supported by insertion of more AMPARs, which maintains postsynaptic excitability in CA1 pyramidal neurons. This novel fast compensatory plasticity exhibits properties that would allow it to maintain optimal network activity levels in the hippocampus, a brain structure lauded for its ongoing experience-dependent malleability.

Constructivist learning theory contends that we construct knowledge by experience and that environmental context influences learning. To explore this principle, we examined the cognitive process relational complexity (RC), defined as the number of visual dimensions considered during problem solving on a matrix reasoning task and a well-documented measure of mature reasoning capacity. We sought to determine how the visual environment influences RC by examining the influence of color and visual contrast on RC in a neuroimaging task. To specify the contributions of sensory demand and relational integration to reasoning, our participants performed a non-verbal matrix task comprised of color, no-color line, or black-white visual contrast conditions parametrically varied by complexity (relations 0, 1, 2). The use of matrix reasoning is ecologically valid for its psychometric relevance and for its potential to link the processing of psychophysically specific visual properties with various levels of RC during reasoning. The role of these elements is important because matrix tests assess intellectual aptitude based on these seemingly context-less exercises. This experiment is a first step toward examining the psychophysical underpinnings of performance on these types of problems. The importance of this is increased in light of recent evidence that intelligence can be linked to visual discrimination. We submit three main findings. First, color and black-white visual contrast (BWVC) add demand at a basic sensory level, but contributions from color and from BWVC are dissociable in cortex such that color engages a "reasoning heuristic" and BWVC engages a "sensory heuristic." Second, color supports contextual sense-making by boosting salience resulting in faster problem solving. Lastly, when visual complexity reaches 2-relations, color and visual contrast relinquish salience to other dimensions of problem solving.

The foundations of neuroinformatics as a new multidisciplinary field of science were laid in the late 1980s as advances in both neuroscience and information science made their incorporation possible. Relating the complex structures and functions of the nervous system requires coordination among diverse domains of knowledge, integration across multiple levels of investigation, and fusion of seemingly disparate technical approaches, from molecules to behavior. The challenge of neuroinformatics is to provide a unified computational information framework to enable, facilitate, and foster such an enterprise. In practice, major advances in our understanding of the brain require the development and application of suitable electronic tools to handle, represent, transform, analyze, and synthesize digital neuroscience data. In turn, such a challenge is the key solution to preventing, diagnosing, and treating brain diseases.Neuroinformatics is still in its infancy, and it may be premature to attempt a historical perspective on a field in evolving and dynamic development. In this article, we present an overview of the status of neuroinformatics mostly by means of focused examples. We first state the main areas of neuroinformatics research in broad terms. Next, we describe some of the principal institutional initiative and resources, exemplifying both organizations and funding programs. We then offer several examples of ongoing efforts. This selection is not meant to (and could not possibly) provide a comprehensive account of current neuroinformatics; on the contrary, we wish to illustrate the diversity and breadth of this rapidly growing branch of science. To offer a sense of the depth involved in these programs, we present one specific case our own laboratory is contributing. Finally, we close by venturing a forecast of the future research landscape after the full maturation and blossoming of neuroinformatics.By its own nature, much neuroinformatics content exists on the World Wide Web and in fact mostly consists of its very online presence. It is, thus, impossible (and would be counterproductive) for this review to be devoid of direct references to uniform resource locators (URLs) corresponding to the described information; we therefore include an extensive list of websites. Internet content evolves dynamically, and a static text such as this can provide only a temporary snapshot of journalistic value, destined to age quickly. The same applies to the illustrations, which are all derived from material accessed in April 2007. Neuroinformatics: Premise and PromiseNeuroscience studies all aspects of the nervous system and its development to understand the biological principles of the mind and behavior. Modern neuroscience encompasses many diverse areas of investigation: from the brain's shape and cellular structure (neuroanatomy) to molecular manipulations and chemical composition (neurochemistry) and from bioelectrical plasticity and circuit dynamics (neurophysiology) to the personal and social organization of cognitive syste...

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