Tools that contain the Simulator Tool Topic : Analysis

(Category of simulator tools which help analyze the data produced from simulations. This category includes filters and statistics. Frequently these same tools can be used on experimental data.)
No.ToolDescription
1. AP halfwidth measurement for NEURON This simple example shows how to measure half width of Action Potentials (in milliseconds).
2. Average a data file to make a smaller data file This utility will read the file specified in the hoc program and write the file specified in the hoc program with blocks of the input file averaged into a single time point. (See top of hoc file for settings) This is a very simple program!
3. Cross Correlation Tool This GUI tool wraps the Vector.correl function http://www.neuron.yale.edu/neuron/docs/help/neuron/general/classes/vector/vect2.html#$Since Vector.correl is implemented using the fast fourier transform this tool interpolates the vectors in the domain tbegin to tend onto a grid with number of points equal to a power of 2. To do this an "actual dt" is selected which is near the "nominal dt" grid spacing and satisfies (tend-tbegin)/"actual dt" = 2^n where n is an integer.
4. fftilt Low-pass filtering using NEURON's fft() routine
5. MFP For use with the NQS tool available in SimToolDB<p> Organizes conductance and tree information from ModelDB models into a relational database for data-mining.<p>
6. NQS NQS is a databasing program with a query command modeled loosely on the SQL select command. <p> Please see the manual NQS.pdf for details of use.<P> An NQS database must be populated with data to be used. You may wish to download MFP.zip (model fingerprint) which provides an example of NQS use. <p>
7. 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="http://software.incf.org/software/pandora">the PANDORA website</a> for finding documentation and the latest version of the toolbox.
8. 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. ..."
9. Sample Entropy (SampEn) method (Neymotin et al. 2010) "... To determine the complexity of the EEG time series, we calculated the sample entropy (SampEn) .... SampEn is the negative natural logarithm of an estimate of the conditional probability that subseries (epochs) of length m-1 that match pointwise within a tolerance r also match at the mth point. ..."
10. 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.