Representational similarity encoding for fMRI: Pattern-based synthesis to predict brain activity using stimulus-model-similarities

@article{Anderson2016RepresentationalSE,
  title={Representational similarity encoding for fMRI: Pattern-based synthesis to predict brain activity using stimulus-model-similarities},
  author={Andrew J. Anderson and Benjamin Zinszer and Rajeev D. S. Raizada},
  journal={NeuroImage},
  year={2016},
  volume={128},
  pages={44-53}
}
Patterns of neural activity are systematically elicited as the brain experiences categorical stimuli and a major challenge is to understand what these patterns represent. Two influential approaches, hitherto treated as separate analyses, have targeted this problem by using model-representations of stimuli to interpret the corresponding neural activity patterns. Stimulus-model-based-encoding synthesizes neural activity patterns by first training weights to map between stimulus-model features and… CONTINUE READING
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