.. _sphx_glr_examples_rsa:


Representational similarity analysis
====================================

In the following couple of sections, we will walk through the steps required to conduct representational similarity analysis (RSA) using MVPy.


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    <div class="sphx-glr-thumbcontainer" tooltip="As we did for classification, we will use an MEG dataset of humans performing a visual categorization task. Briefly, participants saw a list of 92 images. Effectively, these images are faces, not faces, human, not human, artificial, etc. For more information, consult MNE&#x27;s documentation or the original paper. Our goal here will be to create a neural RDM and a hypothesis RDM based on the neural data and the corresponding categories and see if we find some similarity between the two.">

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  .. image:: /examples/rsa/images/thumb/sphx_glr_1_rsa_intro_thumb.png
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  :ref:`sphx_glr_examples_rsa_1_rsa_intro.py`

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      <div class="sphx-glr-thumbnail-title">1. Computing RDMs</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This is an example for running an rsa with encoders">

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  .. image:: /examples/rsa/images/thumb/sphx_glr_2_rsa_encoder_thumb.png
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  :ref:`sphx_glr_examples_rsa_2_rsa_encoder.py`

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      <div class="sphx-glr-thumbnail-title">2. RSA encoders</div>
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.. toctree::
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   /examples/rsa/1_rsa_intro
   /examples/rsa/2_rsa_encoder