Nature Communications (Oct 2023)

Immediate neural impact and incomplete compensation after semantic hub disconnection

  • Zsuzsanna Kocsis,
  • Rick L. Jenison,
  • Peter N. Taylor,
  • Ryan M. Calmus,
  • Bob McMurray,
  • Ariane E. Rhone,
  • McCall E. Sarrett,
  • Carolina Deifelt Streese,
  • Yukiko Kikuchi,
  • Phillip E. Gander,
  • Joel I. Berger,
  • Christopher K. Kovach,
  • Inyong Choi,
  • Jeremy D. Greenlee,
  • Hiroto Kawasaki,
  • Thomas E. Cope,
  • Timothy D. Griffiths,
  • Matthew A. Howard,
  • Christopher I. Petkov

DOI
https://doi.org/10.1038/s41467-023-42088-7
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 17

Abstract

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Abstract The human brain extracts meaning using an extensive neural system for semantic knowledge. Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial. We report intracranial recordings from two patients during a speech prediction task, obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL), a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks, we tested hypotheses ranging from solely neural network disruption to complete compensation by the indirectly affected language-related and speech-processing sites. Immediately after ATL disconnection, we observed neurophysiological alterations in the recorded frontal and auditory sites, providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete, attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework, in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal an immediate impact and capability of the human brain to adjust after losing a brain hub.