mTRF-Toolbox

A MATLAB package for modelling multivariate stimulus-response data

https://cnspworkshop.net

Versión 2.7 (37,7 MB)
825 Descargas
(5)
1 dic 2024

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Crosse, Michael J., et al. “Linear Modeling of Neurophysiological Responses to Speech and Other Continuous Stimuli: Methodological Considerations for Applied Research.” Frontiers in Neuroscience, vol. 15, Frontiers Media SA, Nov. 2021, doi:10.3389/fnins.2021.705621.

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Más información sobre Statistics and Machine Learning Toolbox en Help Center y MATLAB Answers.

Información general

Compatibilidad con la versión de MATLAB

  • Compatible con cualquier versión

Compatibilidad con las plataformas

  • Windows
  • macOS
  • Linux
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Versión Publicado Notas de la versión
2.7

See release notes for this release on GitHub: https://github.com/mickcrosse/mTRF-Toolbox/releases/tag/v2.7
2.6

See release notes for this release on GitHub: https://github.com/mickcrosse/mTRF-Toolbox/releases/tag/v2.6
2.5

See release notes for this release on GitHub: https://github.com/mickcrosse/mTRF-Toolbox/releases/tag/v2.5
2.4

See release notes for this release on GitHub: https://github.com/mickcrosse/mTRF-Toolbox/releases/tag/v2.4
2.3

The following updates were made to v2.3:

1. Fixed correlation broadcasting issue for older versions
2. Fixed verbose issue for older versions

Thanks to Maya Kaufman for flagging the above issues.
2.2

The following updates were made to v2.2:

1. Fixed MSE input argument bug
2. Stabilized correlation for DC signals
3. Reshaped output of mTRFtransform to match encoding model
4. Added lag type to model summary
2.1

The following updates were made to v2.1:
Error metrics no longer based on ranked data for Spearman option
No more NaNs in multivariate metrics for Spearman option
Transformation of 3D decoders now possible
Plotting code now compatible with backward

2.0.3

Added function for CV data partitioning, added feature for equal fold generation, changed AMI metric to ADI metric for attention decoder optimization, added feature for specifying evaluation metrics.
2.0.2

New structuring of toolbox, new functions and features, new example scripts, faster and memory-efficient cross-validation, no additional MathWorks toolboxes required.
2.0.1

* Migrated parsevarargin within main functions
* Fixed bug for specifying model type
* Improved indexing and readability
* Removed coherent motion dataset
* Updated license
2.0.0

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.