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Neural correlates of top-down modulation of haptic shape versus roughness perception.

Stefanie MuellerBenjamin de HaasAnna MetzgerKnut DrewingKatja Fiehler
Published in: Human brain mapping (2019)
Exploring an object's shape by touch also renders information about its surface roughness. It has been suggested that shape and roughness are processed distinctly in the brain, a result based on comparing brain activation when exploring objects that differed in one of these features. To investigate the neural mechanisms of top-down control on haptic perception of shape and roughness, we presented the same multidimensional objects but varied the relevance of each feature. Specifically, participants explored two objects that varied in shape (oblongness of cuboids) and surface roughness. They either had to compare the shape or the roughness in an alternative-forced-choice-task. Moreover, we examined whether the activation strength of the identified brain regions as measured by functional magnetic resonance imaging (fMRI) can predict the behavioral performance in the haptic discrimination task. We observed a widespread network of activation for shape and roughness perception comprising bilateral precentral and postcentral gyrus, cerebellum, and insula. Task-relevance of the object's shape increased activation in the right supramarginal gyrus (SMG/BA 40) and the right precentral gyrus (PreCG/BA 44) suggesting that activation in these areas does not merely reflect stimulus-driven processes, such as exploring shape, but also entails top-down controlled processes driven by task-relevance. Moreover, the strength of the SMG/PreCG activation predicted individual performance in the shape but not in the roughness discrimination task. No activation was found for the reversed contrast (roughness > shape). We conclude that macrogeometric properties, such as shape, can be modulated by top-down mechanisms whereas roughness, a microgeometric feature, seems to be processed automatically.
Keyphrases
  • magnetic resonance imaging
  • magnetic resonance
  • machine learning
  • healthcare
  • white matter
  • deep learning
  • health information
  • network analysis
  • diffusion weighted imaging