Post date: Mar 28, 2016 8:39:23 PM
Navigating the Brain Forest: Center for Neural Informatics, Structures, and Plasticity, Krasnow Institute for Advanced Study, George Mason University
by Sonia Bansal
In this era of the large-scale brain initiative, cataloguing of the brain’s building blocks, neurons, is one of the most fundamental efforts to be undertaken. Our brains can be considered as a dense forest consisting of around 100 billion neurons-the ‘trees’. These neuron trees share a basic structure consisting of ‘roots’, ‘trunk’ and ‘branches’, but are not exactly similar, and in fact have an astonishing diversity that leaves scientists with much to discover. One local DC area research group that is a frontrunner in these efforts is the Center for Neural Informatics, Structures, and Plasticity (CN3) at the Krasnow Institute for Advanced Study of George Mason University, led by Dr. Giorgio Ascoli.
Rubén Armañanzas, research assistant professor, and IT project manager, emphasizes the need for a repository that catalogues these complex branching shapes of neurons, and this is precisely what Dr. Ascoli and his group set out to do. The group is specifically “interested in the description and generation of dendritic morphology, and in its effect on neuronal electrophysiology.” Eventually, they aim to create mega-scale, structurally plausible neural networks to model entire portions of a mammalian brain and share it on the NeuroMorpho.org platform. Since being launched in 2006, this resource has been well appreciated by the research community: “A historic database…the way modern science should proceed” (Luciano Costa, Prof., Sao Paulo Univ., Sao Carlo, Brazil); “Pure dynamite—neuroinformatics made real” (Ted Carnevale, Senior Scientist, Yale Univ., New Haven, CT).
Dr. Armañanzas explains that over the past ten years, the group has progressed in leaps and bounds in providing free 3D digital reconstructions of over 35,000 neurons from dozens of species and brain regions and continues to grow, making it the largest collection of these data (version 6.3 was released on 03/04/2016 and contains 37712 neurons). The group combines various research areas including computational neuroscience, bioinformatics and experimental neuroscience in order to collect neurons traced from studies in microscopy imaging, pharmacology, and development. The data obtained can then be utilized for additional purposes such as brain function modeling. Dr. Armañanzas himself blends his background in computational methods and machine learning with his interest in biology to apply these techniques to gain more knowledge to digitally reconstruct neurons and to “unveil key aspects of neuronal morphogenesis in the developing brain”. He applies information about morphological, physiological, and molecular properties to enhance efforts in automating neuronal classification using robust machine learning techniques. When asked about the favorite aspect of his involvement in this area, he says, “I’d like to think I am a little ant working in a scientific nest, adding my little work everyday to grow something bigger. I like that the research has a broader impact and is open to the public”. One additional goal of the CN3 is to develop “an ecosystem of sharing resources” by working with other initiatives such as BigNeuron (http://alleninstitute.org/bigneuron/about/), BrainInfo(http://braininfo.rprc.washington.edu/) and NEURON (http://www.neuron.yale.edu/neuron/) for the purpose of data mining, education, and outreach. There are very clear-cut de facto policies for sharing resources, and all shared work is cited, with full credit to original authors. Dr. Armañanzas notes that, although initially people from the science community were still reluctant to share data without direct profit, most researchers now have a welcoming attitude towards this kind of sharing system where secondary discoveries and other positive outcomes are closely monitored.
Another venture that Dr. Ascoli’s group is undertaking is the Hippocampome project. Along the lines of the genome project, this knowledge base is designed to cover all aspects of the hippocampus cell types, from structure and activity to function. This project also has its foundations in cataloguing neurons (within the hippocampus). One of the signature décor pieces at the Krasnow Institute at GMU is the wire sculpture of the hippocampus, “Mental Floss”. This is a network model of the hippocampus created in collaboration with a professional DC artist and two Mason students (one art major and one in neuroscience).
Dr. Ascoli’s passion and dedication is pervasive throughout his lab and his group’s research initiatives and tool development have had and continue to have an enormous impact on areas ranging from neurobiology to informatics. He was recently (3-16-15) featured as an invited speaker at SfN-DC Chapter- hosted annual Neuroscience public lecture at AAAS headquarters, and he will soon (3-29-2016) be featured as the guest author in the debut of the new Mason Author Series, which will highlight significant publications of George Mason University faculty and alumni. The neuroscience community in the DMV area is proud to call this group one of its own and we look forward to hearing of more groundbreaking discoveries emanating from this group.
Dr. Giorgio Ascoli
Parekh & Ascoli, 2013
Top Left: Dr. Rubén Armañanzas; Top Right: Brain quilt at Krasnow Institute, George Mason University ; Bottom Left: Hippocampome project board; Bottom Right: ‘Mental Floss’ Hippocampus sculpture.
Research Group contact information:
Dr. Ascoli email address: ascoli (at) gmu (dot) edu
Dr. Rubén Armañanzas: http://mason.gmu.edu/~rarmanan/
2. Ascoli, G. A., Donohue, D. E., & Halavi, M. (2007). NeuroMorpho. Org: a central resource for neuronal morphologies. The Journal of Neuroscience,27(35), 9247-9251.
3. Parekh, R., & Ascoli, G. A. (2013). Neuronal morphology goes digital: a research hub for cellular and system neuroscience. Neuron, 77(6), 1017-1038.
4. Armañanzas, R. & Ascoli, G.A. (2015). Towards the Automatic Classification of Neurons. Trends in Neurosciences, 38(5), 307-318. DOI 10.1016/j.tins.2015.02.004