Metadata-Version: 2.1
Name: scikit-neuromsi
Version: 0.0.1
Summary: Implementation of multisensory integration models in Python
Home-page: https://github.com/renatoparedes/scikit-neuromsi
Author: Renato Paredes
Author-email: paredesrenato92@gmail.com
License: 3 Clause BSD
Description: # scikit-neuromsi
        
        [![scikit-neuromsi](https://github.com/renatoparedes/scikit-neuromsi/actions/workflows/skneuromsi_ci.yml/badge.svg)](https://github.com/renatoparedes/scikit-neuromsi/actions/workflows/skneuromsi_ci.yml)
        [![Documentation Status](https://readthedocs.org/projects/scikit-neuromsi/badge/?version=latest)](https://scikit-neuromsi.readthedocs.io/en/latest/?badge=latest)
        [![Coverage Status](https://coveralls.io/repos/github/renatoparedes/scikit-neuromsi/badge.svg?branch=main)](https://coveralls.io/github/renatoparedes/scikit-neuromsi?branch=main)
        [![https://github.com/leliel12/diseno_sci_sfw](https://img.shields.io/badge/DiSoftCompCi-FAMAF-ffda00)](https://github.com/leliel12/diseno_sci_sfw)
        [![License: BSD-3-Clause](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
        
        **Scikit-neuromsi** is an open-source Python framework that simplifies the implementation of neurocomputational models of multisensory integration.
        
        ## Motivation
        
        Research on the the neural process by which unisensory signals are combined to form a significantly different multisensory response has grown exponentially in the recent years. Nevertheless, there is as yet no unified theoretical approach to multisensory integration. We believe that building a framework for multisensory integration modelling would greatly contribute to originate a unifying theory that narrows the gap between neural and behavioural multisensory responses. 
        
        ## Contact
        Renato Paredes (paredesrenato92@gmail.com)
        
        ## Features
        
        **Scikit-neuromsi** currently has three classes which implement neurocomputational 
        models of multisensory integration.
        
        The available modules are:
        
        - **alais_burr2004**: implements the near-optimal bimodal integration
            employed by Alais and Burr (2004) to reproduce the Ventriloquist Effect.
        
        - **ernst_banks2002**: implements the visual-haptic maximum-likelihood
            integrator employed by Ernst and Banks (2002) to reproduce the visual-haptic task.
        
        - **kording2007**: implements the Bayesian Causal Inference model for
            Multisensory Perception employed by Kording et al. (2007) to reproduce
            the Ventriloquist Effect.
        
        In addition, there is a **core** module with features to facilitate the implementation of new models of multisensory integration.
        
        ## Requirements
        
        You need Python 3.9+ to run scikit-neuromsi.
        
        ## Installation
        
        Run the following command:
        
                $ pip install scikit-neuromsi 
        
        or clone this repo and then inside the local directory execute:
        
                $ pip install -e .
Keywords: multisensory integration,computational neuroscience,cognitive modelling,behaviour simulation,perception
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
