Tools that contain the Modeling Application : MATLAB (web link to model) (Home Page)

( MATLAB integrates mathematical computing, visualization, and a powerful language to provide a flexible environment for technical computing. The open architecture makes it easy to use MATLAB and its companion products to explore data, create algorithms, and create custom tools that provide early insights and competitive advantages.)
1. PANDORA Neural Analysis Toolbox <p>PANDORA is a Matlab Toolbox that makes database management accessible from your electrophysiology project. <p>PANDORA works by extracting user-defined characteristics from raw neural data (e.g., voltage traces) and creating numerical database tables from them. These tables can then be subjected to further analyses, such as invariant effects, statistical, correlation, and principal components. Publication-ready plots can be produced with an embedded plotting system. <p> PANDORA's features are: <ul> <li>Works offline within Matlab; <li>requires no external software; <li>is object oriented and allows easy extensions; <li>can easily tie with existing Matlab scripts; <li>can query a database as in SQL. </ul> <p>See <a href="">the PANDORA website</a> for finding documentation and the latest version of the toolbox.
2. Robust formant tracking (Mustafa and Bruce 2006) "Several algorithms have been developed for tracking formant frequency trajectories of speech signals, however most of these algorithms are either not robust in real-life noise environments or are not suitable for real-time implementation. The algorithm presented in this paper obtains formant frequency estimates from voiced segments of continuous speech by using a time-varying adaptive filterbank to track individual formant frequencies. The formant tracker incorporates an adaptive voicing detector and a gender detector for formant extraction from continuous speech, for both male and female speakers. ..."
3. SimTracker - Parallel NEURON network model simulation management & analysis The SimTracker tool streamlines the entire modeling process, from code writing/versioning and simulation design to execution of simulations on a variety of machines (local, remote supercomputer, NSG) to organization and analysis of simulation results. It also provides tools to: - characterize model components (cells, synapses, ion channels) in experimentalist-friendly ways - read in experimental data and fit model components using that data (in conjunction with NEURON's Multiple Run Fitter) - Explore the parameter space of the model - Share model specifications and results online in an interactive manner, as an alternative to placing all the figures/tables into a supplemental PDF for a publication, although LaTeX code for a PDF can also be generated.