Code associated with the paper Social-affective features drive human representations of observed actions. The repository contains:
code for analyzing behavioral similarity judgments collected via the Meadows platform. This includes data processing, feature extraction, representational similarity analysis, and variance partitioning.
code for analyzing EEG data collected while participants watched videos of naturalistic actions. This includes data processing, artefact rejection, multivariate decoding, time-resolved representational similarity analysis and variance partitioning.
This repository contains a set of functions (that have expanded over a few years) to run SVM decoding of sensor-space and source-space MEG data using the LibLinear/LibSVM libraries and the Fieldtrip toolbox.
If you mainly use Fieldtrip, they give you a quick way to add some multivariate analyses, including time-resolved & searchlight decoding with iterated cross-validation and various preprocessing options, randomization-based statistics with correction for multiple comparisons, temporal generalization, accuracy/classifier weight plots, and representational similarity analysis.
A demo with some example data is available here.