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PUBLIC DOMAIN NOTICE

National Institute on Deafness and Other Communication Disorders

This software/database is a "United States Government Work" 
under the terms of the United States Copyright Act. It was 
written as part of the author's official duties as a United 
States Government employee and thus cannot be copyrighted. 
This software/database is freely available to the public for 
use. The NIDCD and the U.S. Government have not placed any 
restriction on its use or reproduction. 

Although all reasonable efforts have been taken to ensure 
the accuracy and reliability of the software and data, the 
NIDCD and the U.S. Government do not and cannot warrant the
performance or results that may be obtained by using this 
software or data. The NIDCD and the U.S. Government disclaim 
all warranties, express or implied, including warranties of 
performance, merchantability or fitness for any particular 
purpose.

Please cite the author in any work or product based on this 
material.
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Large-Scale Neural Modeling software (LSNM)

Section on Brain Imaging and Modeling
Voice, Speech and Language Branch
National Institute on Deafness and Other Communication Disorders
National Institutes of Health

This README file was last modified on May 8, 2015.

Subdirectories within the "lsnm" repository:

* auditory: 

Software that simulates auditory working memory during a delay match to sample task. It includes batch processing written in Unix bash and C++ to simulate multi-trial and multi-subject experiments, as well as matlab scripts for input generation and post-processing / visualization of output data.

* visual: 

Software that simulates visual working memory during a delay match to sample task. It includes batch processing written in Unix bash and C++ to simualte multi-trial and multi-subject experiments, as well as matlab scrpits for input generation and post-processing / visualization of output data.

* single-trial:

Light-weight piece of software that simulates one single trial of visual working memory during a delay match to sample task experiment.

* documents: 

Documents that describe the theory and implementation of LSNM.