NVIZ : An integrated environment for simulation, visualization and analysis of spinal neuronal dynamics

In this article we describe NVIZ, an interactive environment for system level investigation of neural function. NVIZ combines simulation, visualization and analysis in a single software system that encompasses five biological levels of organization, from ion channels to generated behavior. Once a simulation has been completed, cell-level output data can be visualized as height fields (presenting data from an entire population in a compact representation), or within an anatomical model of cat spinal cord. NVIZ provides a set of numerical analysis tools such as histograms, and a variety of 2D plots that permit both population and cell level analysis within the software system. Movement of a visualized limb segment is generated from activity ofmotoneurons, using a novel new algorithm called Net Neural Drive. The linked visualizations in NVIZ provide a powerful means to comprehend neuronal activity generated in complex models involving thousands of cells. The ability to design or modify neural circuits involving multiple populations, followed by simulation, visualization and analysis promotes rapid experimentation and the ability to digest massive amounts of time-varying simulation data. NVIZ is highly scalable, in terms of the number of populations, neurons, and limb segments. Using interactive tools, the visualization can be easily customized to focus on neural activity of interest. We demonstrate the application of NVIZ to understanding locomotion of a single limb joint, using a central pattern generator model.

[1]  D P Bashor,et al.  Pattern Generators for Muscles Crossing More than One Joint , 1998, Annals of the New York Academy of Sciences.

[2]  G. Ascoli Computational Neuroanatomy , 2002, Humana Press.

[3]  I Segev,et al.  Propagation of action potentials along complex axonal trees. Model and implementation. , 1991, Biophysical journal.

[4]  Frédéric E. Theunissen,et al.  NeMoSys: An Approach to Realistic Neural Simulation , 1993 .

[5]  Richard H. Bartels,et al.  Interpolating splines with local tension, continuity, and bias control , 1984, SIGGRAPH.

[6]  Jan G. Bjaalie,et al.  Localization in the brain: new solutions emerging , 2002, Nature Reviews Neuroscience.

[7]  David P. Bashor,et al.  A large-scale model of some spinal reflex circuits , 1998, Biological Cybernetics.

[8]  William Schroeder,et al.  The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics , 1997 .

[9]  Sergiy Yakovenko,et al.  Spatiotemporal activation of lumbosacral motoneurons in the locomotor step cycle. , 2002, Journal of neurophysiology.

[10]  Idan Segev,et al.  Methods in Neuronal Modeling , 1988 .

[11]  Erik De Schutter,et al.  A consumer guide to neuronal modeling software , 1992, Trends in Neurosciences.

[12]  T. Leergaard,et al.  Three‐dimensional topography of corticopontine projections from rat sensorimotor cortex: Comparisons with corticostriatal projections reveal diverse integrative organization , 2004, The Journal of comparative neurology.

[13]  V. Vanderhorst,et al.  Organization of lumbosacral motoneuronal cell groups innervating hindlimb, pelvic floor, and axial muscles in the cat , 1997, The Journal of comparative neurology.

[14]  Ronald J. MacGregor,et al.  Neural and brain modeling , 1987 .

[15]  R. J. MacGregor,et al.  A model for repetitive firing in neurons , 2004, Kybernetik.

[16]  Trygve B. Leergaard,et al.  Three-dimensional computerised atlas of the rat brain stem precerebellar system: approaches for mapping, visualization, and comparison of spatial distribution data , 2001, Anatomy and Embryology.

[17]  G. Edelman Neural Darwinism: The Theory Of Neuronal Group Selection , 1989 .

[18]  Nicholas T. Carnevale,et al.  The NEURON Simulation Environment , 1997, Neural Computation.

[19]  Kalpathi R. Subramanian,et al.  Multilevel Visualization of Spinal Reflex Circuit Simulations , 1997, IEEE Computer Graphics and Applications.

[20]  Trygve B. Leergaard,et al.  Architecture of Sensory Map Transformations , 2002 .

[21]  Kalpathi R. Subramanian,et al.  Visualizing the spinal neuronal dynamics of locomotion , 2004, IS&T/SPIE Electronic Imaging.

[22]  J. Bower,et al.  The Book of GENESIS , 1998, Springer New York.

[23]  Peter A. Getting Reconstruction of small neural networks , 1989 .

[24]  E. Fetz Movement control: Are movement parameters recognizably coded in the activity of single neurons? , 1992 .

[25]  Erik De Schutter,et al.  Nodus: A User Friendly Neuron Simulator for Macintosh Computers , 1993 .