Mapping language networks using the structural and dynamic brain connectomes

John Del Gaizo, Julius Fridriksson, Grigori Yourganov, Argye E. Hillis, Gregory Hickok, Bratislav Misic, Chris Rorden, Leonardo Bonilha

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Lesion-symptom mapping is often employed to define brain structures that are crucial for human behavior. Even though poststroke deficits result from gray matter damage as well as secondary white matter loss, the impact of structural disconnection is overlooked by conventional lesion-symptom mapping because it does not measure loss of connectivity beyond the stroke lesion. This study describes how traditional lesion mapping can be combined with structural connectome lesion symptom mapping (CLSM) and connectome dynamics lesion symptom mapping (CDLSM) to relate residual white matter networks to behavior. Using data from a large cohort of stroke survivors with aphasia, we observed improved prediction of aphasia severity when traditional lesion symptom mapping was combined with CLSM and CDLSM. Moreover, only CLSM and CDLSM disclosed the importance of temporal-parietal junction connections in aphasia severity. In summary, connectome measures can uniquely reveal brain networks that are necessary for function, improving the traditional lesion symptom mapping approach.

Original languageEnglish (US)
Article numbere0204-17.2017
Issue number5
StatePublished - Sep 1 2017


  • Aphasia
  • Connectome
  • Diffusion tensor imaging
  • Stroke

ASJC Scopus subject areas

  • Neuroscience(all)


Dive into the research topics of 'Mapping language networks using the structural and dynamic brain connectomes'. Together they form a unique fingerprint.

Cite this