Decoding neural representations of human tool use from fMRI response patterns

Contributors:
  1. Diana Tonin
  2. Janak Saada

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Description: Most neuroimaging experiments that investigate how tools and their associated actions are represented in the brain use visual paradigms where objects and body parts are displayed as 2D images and no real movements are performed. These studies have discovered a tight relationship between hand- and tool-selective areas in LOTC and IPS, thought to reflect action-related processing but this claim has never been directly investigated. Here we addressed this by testing whether independently visually-defined category-selective areas were sensitive to real action properties involving 3D tools using fMRI MVPA.

Wiki

These materials accompany work currently reported in a pre-print here: Knights, E., Mansfield, C., Tonin, D., Saada, J. Smith, F.W. & Rossit, S. (2020). Hand-selective visual regions represent how to grasp 3D tools for use: brain decoding during real actions. bioRxiv, https://doi.org/10.1101/2020.10.14.339606

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Components

  • Data - BIDS MRI

    All MRI data (fMRI real action, fMRI localizer and anatomical scans) is open

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  • Data - ROI

    Region of interest decoding and univariate data

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  • Real action videos exemplars

    Videos from MRI compatible infrared camera of hand movements during real action study

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  • Experiment Code & Stimuli - Real action


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  • Experiment Code & Stimuli - Visual localizer

    Code and stimuli for the Bodies, Tools, Hands and Chairs visual localizer.

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  • Code - BIDS Conversion

    Code used to convert MRI dicom data for saving in openneuro

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  • Presentations

    Rossit, Knights, Tonin & 3 more
    Presentations of our data at academic conferences

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