Re: *cochlea*: inner ear models in Python (Dan Goodman )

Subject: Re: *cochlea*: inner ear models in Python
From:    Dan Goodman  <dg.auditory@xxxxxxxx>
Date:    Fri, 22 Aug 2014 14:10:09 +0100

Since everyone is talking about Python and auditory modelling, I'd just like to mention "Brian" and "Brian Hears". These are free, open source Python packages for neural and auditory modelling, respectively, which you can find here: Our focus is on providing components to develop new auditory models (filter banks, neural modelling, etc.) rather than implementations of existing models, although we do have a few of these implemented as well (and Brian is nicely compatible with Marek Rudnicki's cochlea package). Dan Goodman (on behalf of the Brian team) On 21/08/2014 15:46, Brown, Christopher A wrote: > As one who switched to Python as my full-time scientific environment > years ago, I am very happy to see its well-deserved increase in popularity. > > -Chris > > On 08/20/2014 07:08 AM, Dr. Lowel P. O'Mard wrote: >> Hi Etienne and Everybody, >> >> Just to remind everybody that the Development System for Auditory >> Modelling (DSAM) RunDSAMSim application also provides a Python >> interface, and allows complete access to all of the models available >> in DSAM. No doubt "Cochlea*" is a worthy competitor to the DSAM >> RunDSAMSim application, as it seems to have similar functionality. >> The RunDSAMSim python interface links directly to the C/C++ DSAM library. >> >> DSAM provides a flexible environment for both novice and advanced >> users to run auditory models on all platforms (Windows ™, Ubuntu, >> Fedora, Mac OS, etc.). It provides immediate access to auditory models >> such as the Zilany and Bruce (2006, 2007), Meddis et al. (2001) >> auditory nerve models and the Auditory Image Model (AIM) by Patterson >> et al. (2001). In all it provides seven different published auditory >> nerve models using both linear and non-linear basilar membrane >> frequency selectivity, including the DRNL and Gamma-Chirp models. It >> also provides several neural cell models including an ultra-fast >> implementation of the Hudgkin-Huxley neural cell which operates at 80% >> the speed of a simple point neuron model (the McGregor Model). Other >> auditory models, analysis functions, threaded processing and sound >> file support are also provided. A 320 page manual is available for >> DSAM that provides detailed information on how simulations can be >> created and controlled. >> In 2012 DSAM joined the ever growing band of scientists who are >> turning to Python as their analysis and visualisation programming >> language. Because the standard Python “ctypes” foreign function >> library is used to create the interface DSAM can be run on any >> platform for which Python is available. >> Self-installing packages (Windows[tm], Ubuntu and Fedora) for >> RunDSAMSim , SAMS , the DSAM_SDK and other source archives are >> available from the “Downloads” page of the DSAM website: >> The “Applications” page provides information on >> the afore mentioned application packages. >> >> Sincere regards, >> >> ...Lowel. >> > >

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Electrical Engineering Dept., Columbia University