Word frequency effect in written production: Evidence from ERPs and neural oscillations

Abstract

It has been widely documented that word frequency (WF) modulates language processing in various input and output modalities. WF effect has also been reported in the domain of written production; however, how WF affects written production is a controversial issue. The present study attempts to investigate the time course of and neural oscillation underlying the WF effect in handwritten production. Participants were asked to handwrite pictures names of high versus low WF, while concurrently recording EEG. EEG trials were extracted time‐locked to picture onsets and then submitted to event‐related potential analysis and time–frequency analysis. WF affected ERPs in the time windows of around 98–160 and 282–360 ms after picture onsets. More importantly, WF modulated the evoked and induced theta‐band (4–8 Hz) neural oscillations in the time window of around 36–240 and 244–472 ms, respectively. Considering the time course of language production and the role of theta‐band oscillation in long‐term memory retrieval, we suggest that the two stages of the WF effect, respectively, reflect conceptual preparation and retrieval of orthographic word‐forms in written production.

Distinguishing fine structure and summary representation of sound textures from neural activity

“…This sample size was estimated through simulations. We used the procedure described in Wang and Zhang (2021; for details on sample size estimation see Supplementary Expanded Methods in appendix 1 and Figure S1). All participants were healthy, fully informed on the scopes of the experiment, signed a written informed consent prior to testing, and received a monetary compensation.…”

A prime-masked ERP investigation on phonology in visual word processing among bilingual speakers of alphasyllabic and alphabetic orthographies

“…The sample size is comparable with the studies that used similar methodology to investigate phonological processing using EEG 5 , 14 , 15 , 23 , 29 , 37 . The sample size was also adequate in detecting differences in ERPs between two conditions in a within-subject design with 80% power (using data simulation for cluster-based permutation tests 38 ). The study was approved by the ethics committee at the College of Health Professions, Manipal Academy of Higher Education.…”

Understanding Language Attrition through Orthography

“…Besides, such differences might be expected to be observable not only at a quantitative level (i.e., differences in the amplitude of a particular component between control and experimental samples) but, importantly, at qualitative level, i.e., differences between both groups in the recruitment of a particular brain signal along the linguistic processing addressed), because such differences have been pointed out as those clearly indicative of L1 attrition (e.g., Steinhauer and Kasparian 2019;Kasparian andSteinhauer 2016, 2017). Similarly, the use of other on-line methods such as handwriting on digital tablets may help to identify attriter patterns at the initial stages of orthographic production, because this methodology captures the temporal dynamics of the writing process (e.g., Barbier and Spinelli-Jullien 2009;Kandel et al 2019;Kandel and Soler 2010;Roux et al 2013;Wang and Zhang 2021). In this way, differences between mono-and biliterate populations under conditions of orthographic L1-L2 overlap (i.e., in the number and duration of eye fixations, in the amplitude, latency or frequency of the EEG/MEG signals or in the latency, letter duration, pauses and kinematics of handwriting patterns) could provide valuable information regarding the underlying neuro-cognitive mechanisms of L1 orthographic attrition and clarify the causes of this phenomenon from a neuroscientific perspective.…”