mTRF-Toolbox

Version 2.3 (36.4 MB) by Mick Crosse
A MATLAB Package for Relating Neural Signals to Continuous Stimuli
455 Downloads
Updated 2 Feb 2024

mTRF-Toolbox is a MATLAB package for modelling multivariate stimulus-response data, suitable for neurophysiological data such as MEG, EEG, sEEG, ECoG and EMG. It can be used to model the functional relationship between neuronal populations and dynamic sensory inputs such as natural scenes and sounds, or build neural decoders for reconstructing stimulus features and developing real-time applications such as brain-computer interfaces (BCIs).

Cite As

Crosse, Michael J., et al. “The Multivariate Temporal Response Function (MTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli.” Frontiers in Human Neuroscience, vol. 10, Frontiers Media SA, Nov. 2016, doi:10.3389/fnhum.2016.00604.

View more styles
MATLAB Release Compatibility
Created with R2017b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes
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

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.