Dendritic and axonal morphologies play fundamental roles in physiological brain function and pathological dysfunction by affecting synaptic integration, spike train transmission, and circuit connectivity. Incorporating existing and forthcoming experimental data into accurate, full-scale, and biologically plausible neural network simulations is important for quantitatively bridging the sub-cellular and systems-levels. We successfully designed, implemented, and freely distributed to the community computer software and databases to reconstruct, analyze, visualize, simulate, and share the 3D tree-like shape of neurons from many labeling and visualization techniques, developmental stages, and experimental conditions. We imaged by light microscopy, digitally traced, and shared new data, and we provided our peers with the electronic means of freely doing the same. Moreover, we combined those data with computational models of membrane biophysics to investigate the neuronal structure-activity relationship. We propose to expand this research approach with two specific aims. The first is to augment the power, scope, and usability of the NeuroMorpho.Org repository of digital tracings. We plan to triple the number of shared reconstructions, adding new species, brain regions, and neuron types. Moreover, we will enhance the search functionality with a "semantic" engine using state-of-the-art ontologies. We will also extend the domain and format of distributed data to include circuitry, multi-channel information, and temporal sequences.
The second aim i s to develop a new knowledge base of neuron types in the hippocampus and entorhinal cortex by quantifying their morphological, physiological, and molecular properties from published reports. The hippocampal formation is one of the most studied brain regions, underlies autobiographic memory storage and spatial representation, and is prominently involved in devastating neurological disease, including epilepsy and Alzheimer's. Yet, our conceptual understanding of how the hippocampus works is limited compared to the wealth of available knowledge about its neurons, because it is difficult to find and integrate all relevant data scattered in thousands of papers. We will identify all published information and annotate it with specific pointers to the source documents in the peer- reviewed literature. The resulting open-source portal (Hippocampome.Org) will enable the derivation of potential circuit connectivity and the predictive simulation of network-wide spiking activity. We will make this application especially relevant to neuropathology by linking specific neuron types to diseases involving the hippocampus, and demonstrate its potential with a new model of learning disabilities based on impaired structural plasticity.

Public Health Relevance

Generation and Description of Neuronal Morphology &Connectivity Brain connectivity and the intricate tree-like shape of individual nerve cells underli cognitive and physiological functions, and are dramatically altered in almost all known neurological disorders. Using state-of-the-art information technology, statistical analysis, and computational modeling, this project will quantify, synthesize, and freely share a massive amount of complex neuroscience information on (1) neuronal morphology in general and (2) all major properties of every known neuron types in an exemplary brain region. These developments will allow us to create detailed, biologically plausible, full-scale quantitatively predictive models of cognitive function and neurological disease. The impact on the research community will be multiplied by public distribution of both simulation and program codes as well as all underlying data collected for the long lasting benefit of scientific advancement and public health.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Special Emphasis Panel (NOIT)
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Liu, Yuan
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George Mason University
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Ascoli, Giorgio A (2014) A community spring for neuroscience data sharing. Neuroinformatics 12:509-11
DeFelipe, Javier; Lopez-Cruz, Pedro L; Benavides-Piccione, Ruth et al. (2013) New insights into the classification and nomenclature of cortical GABAergic interneurons. Nat Rev Neurosci 14:202-16
Sugihara, Izumi; Brown, Kerry M; Ascoli, Giorgio A (2013) New insights on vertebrate olivo-cerebellar climbing fibers from computerized morphological reconstructions. Bioarchitecture 3:38-41
Ferrante, Michele; Migliore, Michele; Ascoli, Giorgio A (2013) Functional impact of dendritic branch-point morphology. J Neurosci 33:2156-65
Parekh, Ruchi; Ascoli, Giorgio A (2013) Neuronal morphology goes digital: a research hub for cellular and system neuroscience. Neuron 77:1017-38
Martone, Maryann E; Ascoli, Giorgio A (2013) Connecting connectomes. Neuroinformatics 11:389-92
Ropireddy, D; Bachus, S E; Ascoli, G A (2012) Non-homogeneous stereological properties of the rat hippocampus from high-resolution 3D serial reconstruction of thin histological sections. Neuroscience 205:91-111
Baker, John L; Perez-Rosello, Tamara; Migliore, Michele et al. (2011) A computer model of unitary responses from associational/commissural and perforant path synapses in hippocampal CA3 pyramidal cells. J Comput Neurosci 31:137-58
Donohue, Duncan E; Ascoli, Giorgio A (2011) Automated reconstruction of neuronal morphology: an overview. Brain Res Rev 67:94-102
Ropireddy, Deepak; Scorcioni, Ruggero; Lasher, Bonnie et al. (2011) Axonal morphometry of hippocampal pyramidal neurons semi-automatically reconstructed after in vivo labeling in different CA3 locations. Brain Struct Funct 216:1-15

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