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Using multivariate assessments on infant EEG data to investigate visual category representations.

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Visual Category Representations in the Infant Brain

This repository provides MATLAB example codes used in the study "Visual category representations in the infant brain ("VCR_infant" in short)".

You can clone this repository to local using:

git clone https://github.com/siyingxie/VCR_infant.git

Example analyses

IMPORTANT: To run the examples, a LIBSVM toolbox is required. Please see the "Dependency" and "Installation" sections for details.

Here are six examples analyses in the study.

  • Decode object categories in time (runtime: ~ 2 min)
    example_decodingintime.m
  • Decode object categories in time and frequency (runtime: ~ 5 min)
    example_decodingtimefrequency.m
  • Time generalization analysis (runtime: ~ 1 min)
    example_decodingtimegeneralization.m 
  • Relate category representations in infants and adults (runtime: ~ 1 min)
    example_rsatimegeneralization.m 
  • Relate oscillation-based category representations in infants and adults (runtime: ~ 1 min)
    example_rsatimefrequency.m
  • Relate category representations to computational models* (runtime: ~ 1 min)
    example_rsatomodels.m

*Gabor filter model and VGG-19 deep neural network trained on object categorization

Dependency

Resource/Software Source/Identifier
Example data* [https://osf.io/ruxfg]
LIBSVM toolbox♰ [https://github.com/cjlin1/libsvm; RRID: SCR_010243]

* They will be automatically downloaded while running the examples (via setup.m) if they have not already been downloaded.

♰ The toolbox needs to be downloaded and installed manually. (See "Installation" for details.)

Installation

The examples require LIBSVM (e.g., version-3.25) toolbox, and please add the toolbox as follows:

  • To clone the LIBSVM.git repository to the /code directory, please use:

    cd VCR_infant/code
    git clone https://github.com/cjlin1/libsvm.git
  • If you are on Unix systems, you will need to compile the toolbox. Please refer to the steps in LIBSVM.readme.

    A quick walk-through:

    • On MATLAB command window, please type:
    >> cd libsvm/matlab
    >> matlabroot % check your $MATLABROOT
    >> edit Makefile 
    • On MATLAB editor, please manually edit the "Makefile":
    a) In line:3, change the "MATLABDIR ?= " to your $MATLABROOT 
    b) save the "Makefile"
    • Back to the MATLAB command window, please type:
    >> make % it will take a few seconds to compile 

    For more details, please see LIBSVM.readme.

Required customized functions

These customized functions are provided in the repository.

  • averagetimepoints.m
  • averagetrials.m
  • correlatevectors.m
  • covCor.m
  • cvmvnn.m
  • setup.m
  • timefrexdecomp.m
  • vectorizerdm.m

Visualization

The expected outputs from the examples:

Results for single participants:

Model RDMs details:

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Using multivariate assessments on infant EEG data to investigate visual category representations.

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