Metadata-Version: 2.4
Name: scikit-neuromsi
Version: 1.0.1
Summary: Implementation of multisensory integration models in Python
Author-email: Renato Paredes <paredesrenato92@gmail.com>, "Juan B. Cabral" <jbcabral@unc.edu.ar>
License: Copyright (c) 2021, Paredes, Renato; Cabral, Juan
        All rights reserved.
        
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Project-URL: Homepage, https://github.com/renatoparedes/scikit-neuromsi
Project-URL: Repository, https://github.com/renatoparedes/scikit-neuromsi
Keywords: multisensory integration,computational neuroscience,cognitive modelling,behaviour simulation,perception
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
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: brainpy
Requires-Dist: scipy
Requires-Dist: jaxlib
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Requires-Dist: joblib
Requires-Dist: bidict
Requires-Dist: seaborn
Requires-Dist: xarray
Requires-Dist: tqdm
Requires-Dist: methodtools
Requires-Dist: netcdf4
Requires-Dist: custom_inherit
Requires-Dist: jinja2
Requires-Dist: humanize
Requires-Dist: pympler
Requires-Dist: psutil
Requires-Dist: lz4
Dynamic: license-file

# Scikit-NeuroMSI
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**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)

## Repository and Issues

https://github.com/renatoparedes/scikit-neuromsi


## License

Scikit-NeuroMSI is under
[The 3-Clause BSD License](https://github.com/renatoparedes/scikit-neuromsi/blob/main/LICENSE.txt)

This license allows unlimited redistribution for any purpose as long as
its copyright notices and the license’s disclaimers of warranty are maintained.


## Features

**Scikit-NeuroMSI** was designed to meet three fundamental requirements in the computational study of multisensory integration:

- **Modeling Standardization**: Standardized interface for implementing and analyzing different types of models. The package currently handles the following model families: Maximum Likelihood Estimation, Bayesian Causal Inference, and Neural Networks.

- **Data Processing Pipeline**: Multidimensional data processing across spatial dimensions (1D to 3D spatial coordinates), temporal sequences, and multiple sensory modalities (e.g., visual, auditory, touch).

- **Analysis Tools**: Integrated tools for parameter sweeping across model configurations, result visualisation and export, and statistical analysis of model outputs.

In addition, there is a **core** module with features to facilitate the implementation of new models of multisensory integration.

## Requirements

You need Python 3.10+ 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 .
