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Updated: Apr 20, 2026

Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese
Published on: April 1, 2016
Dynamic reconfiguration of the language network preceding onset of speech in picture naming
Mia Liljeström1, Jan Kujala, Claire Stevenson
1Brain Research Unit, O.V. Lounasmaa Laboratory, Aalto University, Aalto, Finland; Aalto NeuroImaging, Aalto University, Aalto, Finland; Department of Neurological Sciences, University of Helsinki, HY, Finland; Department of Neurology, Helsinki University Central Hospital, HUS, Finland.
Abstract:
Language production is a complex neural process that requires the interplay between multiple specialized cortical regions. We investigated modulations in large-scale cortical networks underlying preparation for speech production by contrasting cortico-cortical coherence for overt and silent picture naming in an all-to-all connectivity analysis. To capture transient, frequency-specific changes in functional connectivity we analyzed the magnetoencephalography data in two consecutive 300-ms time windows. Within the first 300 ms following picture onset beta frequency coherence was increased for overt naming in a network of regions comprising the bilateral parieto-temporal junction and medial cortices, suggesting that overt articulation modifies selection processes involved in speech planning. In the late time window (300-600 ms after picture onset) beta-range coherence was enhanced in a network that included the ventral sensorimotor and temporal cortices. Coherence in the gamma band was simultaneously reduced between the ventral motor cortex and supplementary motor area, bilaterally. The results suggest functionally distinct roles for beta (facilitatory) and gamma (suppressive) band interactions in speech production, with strong involvement of the motor cortex in both frequency bands. Overall, a striking difference in functional connectivity between the early and late time windows was observed, revealing the dynamic nature of large-scale cortical networks that support language and speech. Our results demonstrate that as the naming task evolves in time, the global connectivity patterns change, and that these changes occur (at least) on the time-scale of a few hundred milliseconds. More generally, these results bear implications for how we view large-scale neural networks underlying task performance.
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