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)
Project #
Application #
Study Section
Special Emphasis Panel (NOIT)
Program Officer
Liu, Yuan
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
George Mason University
Organized Research Units
United States
Zip Code
Akram, Masood A; Nanda, Sumit; Maraver, Patricia et al. (2018) An open repository for single-cell reconstructions of the brain forest. Sci Data 5:180006
Nanda, Sumit; Chen, Hanbo; Das, Ravi et al. (2018) Design and implementation of multi-signal and time-varying neural reconstructions. Sci Data 5:170207
Hamilton, D J; White, C M; Rees, C L et al. (2017) Molecular fingerprinting of principal neurons in the rodent hippocampus: A neuroinformatics approach. J Pharm Biomed Anal 144:269-278
Rees, Christopher L; White, Charise M; Ascoli, Giorgio A (2017) Neurochemical Markers in the Mammalian Brain: Structure, Roles in Synaptic Communication, and Pharmacological Relevance. Curr Med Chem 24:3077-3103
Rees, Christopher L; Moradi, Keivan; Ascoli, Giorgio A (2017) Weighing the Evidence in Peters' Rule: Does Neuronal Morphology Predict Connectivity? Trends Neurosci 40:63-71
Das, Ravi; Bhattacharjee, Shatabdi; Patel, Atit A et al. (2017) Dendritic Cytoskeletal Architecture Is Modulated by Combinatorial Transcriptional Regulation in Drosophila melanogaster. Genetics 207:1401-1421
Ascoli, Giorgio A; Maraver, Patricia; Nanda, Sumit et al. (2017) Win-win data sharing in neuroscience. Nat Methods 14:112-116
Hamilton, D J; Wheeler, D W; White, C M et al. (2017) Name-calling in the hippocampus (and beyond): coming to terms with neuron types and properties. Brain Inform 4:1-12
Ascoli, Giorgio A (2016) On the Data-Driven Road from Neurology to Neuronomy. Neuroinformatics 14:251-2
Ascoli, Giorgio A; Wheeler, Diek W (2016) In search of a periodic table of the neurons: Axonal-dendritic circuitry as the organizing principle: Patterns of axons and dendrites within distinct anatomical parcels provide the blueprint for circuit-based neuronal classification. Bioessays 38:969-76

Showing the most recent 10 out of 78 publications