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Updated: Jan 22, 2026

Transcranial Direct Current Stimulation tDCS of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition
Published on: July 13, 2019
Task load modulates tDCS effects on language performance
Lílian Rodrigues de Almeida1, Paul A Pope1, Peter C Hansen1
1School of Psychology, University of Birmingham, Birmingham, UK.
Abstract:
Transcranial direct current stimulation (tDCS) effects in cognition are inconsistent across studies. This study aimed to discuss why typical models might be insufficient to explain these effects, and to investigate a brain state factor, task load, with behavioral experiments on phonological processing. The motor theory of speech perception states that motor codes for articulation take part in speech perception, a view sharpened by neuroimaging findings, which show that the motor role in phonological processing is weighted by the nature of the tasks. Three groups of 20 participants, each under a different tDCS condition (anodal, cathodal, or sham), performed a categorical perception (CP), a lexical decision (LD), and a word naming (WN) task while stimulated on the pars opercularis of the left inferior frontal gyrus, a language area typically involved with the motor role. These tasks were assumed to be subserved by a network of nodes which included the target, believed to be increasingly relevant for performance from speech perception to speech production. A-tDCS facilitation and C-tDCS downregulation should directly increase with the relevance of the target for the task. Downregulation of a low relevance node could result in facilitation by compensation from other nodes. Overall, our brain stimulation findings support the neuroimaging literature in that motor participation in phonological processing depends on task nature and show that tDCS effects are modulated by task load relative to the target. Outcomes such as the improved performance following cathodal tDCS in CP and WN suggest that compensatory mechanisms may take place when the tasks involve more complex neuronal networks.
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