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Resource:Computational Neurobiology and Imaging Center

Name: Resource:Computational Neurobiology and Imaging Center
Description: The goal of The Computational Neurobiology and Imaging Center (CNIC) is to advance research and training in mathematical, computational and modern imaging approaches to understanding the brain and its functions. CNIC researchers study the relationships between neural function and structure at levels ranging from the molecular and cellular, through network organization of the brain. This involves the development of new computational and analytic tools for imaging and visualization of 3-D neural morphology, from the gross topologic characteristics of the dendritic arbor to the fine structure of spines and their synapses. Numerical simulations of neural mechanisms based on these structural data are compared with in-vivo and in-vitro electrophysiological recordings.

The group also develops new theoretical and analytic approaches to exploring the function of neural models of working memory. The goal of this analytic work is to combine biophysically realistic models and simulations with reduced mathematical models that capture essential dynamical behaviors while reproducing the functionally important features of experimental data.

The research areas at CNIC are:

  • Imaging Studies (Imaging): CNIC researchers use a combination of confocal and multi-photon microscopy to obtain high quality images.
  • Volume Integration (Tiling): CNIC developed a Volume Integration and Alignment System (VIAS) to create a single volume from multiple 2D image stacks, each of variable dimensions.
  • Visualization Techniques (Visual): They have developed various software tools to assist in the visualization of datasets, traced models, and spines.
  • Medial Axis Extraction (Arbor): Obtaining the medial axis of a cell (and associated diameters) produces a model which can be imported into morphometric software and compartment modeling programs such as NEURON and GENESIS.
  • Spine Detection and Classification (Spines): CNIC introduces a novel computational approach for detection and shape analysis of neuronal dendritic spines from confocal and multiphoton laser scanning microscopy (CLSM and MPLSM) images, that operates fully in 3D, and is faster and more accurate than existing semi-automated technologies.
  • Applications of Rayburst (Rayburst): The Rayburst Algorithm is a generic shape analysis algorithm, implemented within the CNIC lab as a C software library, and freely available for download.
  • Analysis of Spatially Complex Structures (Spatial): CNIC technology allows for it to be possible to observe and quantify changes in blood vessels and blood flow dynamics in physiological conditions as well as in models of human diseases.
  • Computational Modeling (Modeling): CNIC computational studies explore how morphology influences function in neurons subserving working memory in brain regions including the cortex and the brainstem.
  • Mathematical and Analytic Studies (Math): Analytic programs complement the computational studies by developing theoretical tools for analyzing and better understanding experimental data.
Parent Organization: Mount Sinai School of Medicine; New York; USA
Supporting Agency: Howard Hughes Medical Institute, National Institute on Deafness and Other Communication Disorders, National Institute on Aging, National Institute of Mental Health
Resource Type(s): institutional portal, data visualization software, simulation software
Keywords: electrophysiological, electrophysiology, function, 2d, 3-d, algorithm, alignment, analytic, arbor, behavior, biophysically, blood, brain, brainstem, cell, cellular, computational, confocal, cortex, dendritic, development, disease, human, imaging, integration, in-vitro, in-vivo, laser scanning microscopy, math, mathematical, memory, microscopy, model, molecular, morphology, morphometric, multi-photon, neural, neural function, neurobiology, neuron, neuroscience, physiological, research, simulation, software, spine, stack, structure, synapse, topologic, variable, vessel, visualization, image
Abbreviation: CNIC
Resource: Resource
URL: http://www.mssm.edu/cnic/repository.html
Id: nif-0000-10200
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Retrieved from "http://neurolex.org/wiki/Category:Resource:Computational_Neurobiology_and_Imaging_Center"
Facts about Resource:Computational Neurobiology and Imaging CenterRDF feed
AbbrevCNIC  +
CurationStatuscurated  +
DefiningCitationhttp://www.mssm.edu/cnic/repository.html  +
DefinitionThe goal of The Computational Neurobiology … The goal of The Computational Neurobiology and Imaging Center (CNIC) is to advance research and training in mathematical, computational and modern imaging approaches to understanding the brain and its functions. CNIC researchers study the relationships between neural function and structure at levels ranging from the molecular and cellular, through network organization of the brain. This involves the development of new computational and analytic tools for imaging and visualization of 3-D neural morphology, from the gross topologic characteristics of the dendritic arbor to the fine structure of spines and their synapses. Numerical simulations of neural mechanisms based on these structural data are compared with in-vivo and in-vitro electrophysiological recordings.

The group also develops new theoretical and analytic approaches to exploring the function of neural models of working memory. The goal of this analytic work is to combine biophysically realistic models and simulations with reduced mathematical models that capture essential dynamical behaviors while reproducing the functionally important features of experimental data.

The research areas at CNIC are:

  • Imaging Studies (Imaging): CNIC researchers use a combination of confocal and multi-photon microscopy to obtain high quality images.
  • Volume Integration (Tiling): CNIC developed a Volume Integration and Alignment System (VIAS) to create a single volume from multiple 2D image stacks, each of variable dimensions.
  • Visualization Techniques (Visual): They have developed various software tools to assist in the visualization of datasets, traced models, and spines.
  • Medial Axis Extraction (Arbor): Obtaining the medial axis of a cell (and associated diameters) produces a model which can be imported into morphometric software and compartment modeling programs such as NEURON and GENESIS.
  • Spine Detection and Classification (Spines): CNIC introduces a novel computational approach for detection and shape analysis of neuronal dendritic spines from confocal and multiphoton laser scanning microscopy (CLSM and MPLSM) images, that operates fully in 3D, and is faster and more accurate than existing semi-automated technologies.
  • Applications of Rayburst (Rayburst): The Rayburst Algorithm is a generic shape analysis algorithm, implemented within the CNIC lab as a C software library, and freely available for download.
  • Analysis of Spatially Complex Structures (Spatial): CNIC technology allows for it to be possible to observe and quantify changes in blood vessels and blood flow dynamics in physiological conditions as well as in models of human diseases.
  • Computational Modeling (Modeling): CNIC computational studies explore how morphology influences function in neurons subserving working memory in brain regions including the cortex and the brainstem.
  • Mathematical and Analytic Studies (Math): Analytic programs complement the computational studies by developing theoretical tools for analyzing and better understanding experimental data.
    ter understanding experimental data.
Has default formThis property is a special property in this wiki.Resource  +
Has roleOrganization portal  +, Data visualization software  +, and Simulation software  +
Idnif-0000-10200  +
Is part ofMount Sinai School of Medicine; New York; USA  +
KeywordsElectrophysiological  +, Electrophysiology  +, Function  +, 2d  +, 3-d  +, Algorithm  +, Alignment  +, Analytic  +, Arbor  +, Behavior  +, Biophysically  +, Blood  +, Brain  +, Brainstem  +, Cell  +, Cellular  +, Computational  +, Confocal  +, Cortex  +, Dendritic  +, Development  +, Disease  +, Human  +, Imaging  +, Integration  +, In-vitro  +, In-vivo  +, Laser scanning microscopy  +, Math  +, Mathematical  +, Memory  +, Microscopy  +, Model  +, Molecular  +, Morphology  +, Morphometric  +, Multi-photon  +, Neural  +, Neural function  +, Neurobiology  +, Neuron  +, Neuroscience  +, Physiological  +, Research  +, Simulation  +, Software resource  +, Spine  +, Stack  +, Structure  +, Synapse  +, Topologic  +, Variable  +, Vessel  +, Visualization  +, and Image  +
LabelResource:Computational Neurobiology and Imaging Center  +
ModifiedDate27 June 2012  +
Page has default formThis property is a special property in this wiki.Resource  +
SuperCategoryResource  +
Supporting AgencyHoward Hughes Medical Institute  +, National Institute on Deafness and Other Communication Disorders  +, National Institute on Aging  +, and National Institute of Mental Health  +