Predicting naming responses based on pre-articulatory electrical activity in individuals with aphasia

Janina Wilmskoetter, John Del Gaizo, Lorelei Phillip, Roozbeh Behroozmand, Ezequiel Gleichgerrcht, Julius Fridriksson, Ellyn Riley, Leonardo Bonilha

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Objective: To investigate whether pre-articulatory neural activity could be used to predict correct vs. incorrect naming responses in individuals with post-stroke aphasia. Methods: We collected 64-channel high density electroencephalography (hdEEG) data from 5 individuals with chronic post-stroke aphasia (2 female/3 male, median age: 54 years) during naming of 80 concrete images. We applied machine learning on continuous wavelet transformed hdEEG data separately for alpha and beta energy bands (200 ms pre-stimulus to 1500 ms post-stimulus, but before articulation), and determined whether electrode/time-range/energy (ETE) combinations were predictive of correct vs incorrect responses for each participant. Results: The five participants correctly named between 30% and 70% of the 80 stimuli correctly. We observed that pre-articulatory scalp EEG ETE combinations could predict correct vs incorrect responses with accuracies ranging from 63% to 80%. For all but one participant, the prediction accuracies were statistically better than chance. Conclusions: Our findings indicate that pre-articulatory neural activity may be used to predict correct vs incorrect naming responses for some individuals with aphasia. Significance: The individualized pre-articulatory neural pattern associated with correct naming responses could be used to both predict naming problems in aphasia and lead to the development of brain stimulation strategies for treatment.

Original languageEnglish (US)
Pages (from-to)2153-2163
Number of pages11
JournalClinical Neurophysiology
Issue number11
StatePublished - Nov 2019


  • Aphasia
  • EEG
  • Machine learning
  • Naming
  • Stroke

ASJC Scopus subject areas

  • Sensory Systems
  • Neurology
  • Clinical Neurology
  • Physiology (medical)


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