Founding Editor-in-Chief, Neuroinformatics

The main effort of Dr. Ascoli's lab is to connect the cellular organization of brain networks to cognitive functions such as learning and memory. His laboratory hosts and curates a central inventory of digitally reconstructed neurons in NeuroMorpho.Org and Hippocampome knowledge  base and has developed L-Neuron, a neuron modeling  tool. His  long-term scientific and philosophical goal consists in establishing a working model for the highest cognitive functions such as human consciousness.

NeuroMorpho.Org is the largest collection of publicly accessible 3D neuronal reconstructions. The goal of NeuroMorpho.Org is to provide dense coverage of available reconstruction data for the neuroscience community enabling the full and continuing research potential of existing digital reconstruction data.

Website: neuromorpho.org

NeuroMorpho.Org is the largest centrally curated online repository of digital reconstructions of axonal and dendritic morphologies.

This public resource freely provides light and electron microscopy tracings contributed by more than 220 labs worldwide from over 500 publications.

This resource aims to provide dense coverage of available data by including all digital tracings described in peer-reviewed publications that the authors are willing to share. Although most reconstructions to date are acquired manually or semi-manually, the transition to quasi-automated methods is widely considered as necessary for long-term progress.

Neuron reconstruction is more often related to digital reconstruction of a neuron's morphology from imaging data. Due to the high complexity of neuron morphology and often seen heavy noise in such images, as well as the typically encountered massive amount of image data, it has been widely viewed as one of the most challenging computational tasks for computational neuroscience.

We are specifically interested in the description and generation of dendritic morphology, and in its effect on neuronal electrophysiology. In the long term, we seek to create large-scale, anatomically plausible neural networks to model entire portions of a mammalian brain (such as a hippocampal slice, or a cortical column).

DATE: Monday, 31 October, 2016
TIME: 4:00-5:00pm
LOCATION: Lecture Room (Room 229)
Krasnow Institute Building
George Mason University, Fairfax, VA

National Academies Keck Futures Initiative is a step toward giving researchers another tool in their work. It’s a data overload worth organizing because, as Ascoli points out, such a “knowledge base” could reveal patterns, show untapped areas for future research and cut duplication.

This inaugural event of the series, which is sponsored by the George Mason University Bookstore, was held in the Fenwick Library Main Reading Room, on Tuesday, March 29th, at 2:30 p.m.

Dr. Armañanzas research topics include machine learning, computational neuroscience, and neuroinformatics. In particular, applications within these topics are: knowledge discovery in digital neuronal reconstructions, automatic classification of neuronal types, complex neuromorphic networks, and unveiling key aspects of neuronal morphogenesis in the developing brain.

Prominent research efforts are unveiling how circuits constitute the basic functional units of nervous systems.

Among them, Drosophila is currently the species with more promising results in mapping brain-wide connections at the
individual neuron level. The pioneering FlyCircuit Database has already traced and co-registered the neurite wiring corresponding to approximately 10% (v1.0) and 23% (v1.1) of the cells in the Drosophila brain.

Dr. Polavaram received her Ph.D. in Neuroscience from George Mason University, she has been working for over a decade in the field of Computational Neuroanatomy and Neuroinformatics providing services in software engineering, data management, analytics,  visualization, and applied ontologies. Her current area of research investigates biologically meaningful morphological patterns derived from digitally reconstructed neuronal arbors representing the cellular diversity of the nervous system.

Sumit Nanda research focuses on modelling and simulation of dendritic morphology.

We present the definition of a novel multichannel file structure and corresponding Vaa3D plug-in to handle this new type of data. We also introduce a design to tag dynamic structural changes in a time-coded manner. Next, we illustrate ongoing progress in using the multichannel/time-lapse system on developing neurons in the Drosophila larva. Time-varying images of overall neuronal morphology along with fluorescently labeled subcellular cytoskeletal components are digitally traced into the aforementioned file structures. These new reconstructions enable complete statistical analysis of the structural changes and the underlying molecular processes.

When: Friday 4:00 to 4:30 PM EST
Date: Dec. 2, 2016