Cell Reports (Nov 2023)

Predictability alters information flow during action observation in human electrocorticographic activity

  • Chaoyi Qin,
  • Frederic Michon,
  • Yoshiyuki Onuki,
  • Yohei Ishishita,
  • Keisuke Otani,
  • Kensuke Kawai,
  • Pascal Fries,
  • Valeria Gazzola,
  • Christian Keysers

Journal volume & issue
Vol. 42, no. 11
p. 113432

Abstract

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Summary: The action observation network (AON) has been extensively studied using short, isolated motor acts. How activity in the network is altered when these isolated acts are embedded in meaningful sequences of actions remains poorly understood. Here we utilized intracranial electrocorticography to characterize how the exchange of information across key nodes of the AON—the precentral, supramarginal, and visual cortices—is affected by such embedding and the resulting predictability. We found more top-down beta oscillation from precentral to supramarginal contacts during the observation of predictable actions in meaningful sequences compared to the same actions in randomized, and hence less predictable, order. In addition, we find that expectations enabled by the embedding lead to a suppression of bottom-up visual responses in the high-gamma range in visual areas. These results, in line with predictive coding, inform how nodes of the AON integrate information to process the actions of others.

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