General-Purpose Monitoring during Speech Production

Abstract

The concept of "monitoring" refers to our ability to control our actions on-line. Monitoring involved in speech production is often described in psycholinguistic models as an inherent part of the language system. We probed the specificity of speech monitoring in two psycholinguistic experiments where electroencephalographic activities were recorded. Our focus was on a component previously reported in nonlinguistic manual tasks and interpreted as a marker of monitoring processes. The error negativity (Ne, or error-related negativity), thought to originate in medial frontal areas, peaks shortly after erroneous responses. A component of seemingly comparable properties has been reported, after errors, in tasks requiring access to linguistic knowledge (e.g., speech production), compatible with a generic error-detection process. However, in contrast to its original name, advanced processing methods later revealed that this component is also present after correct responses in visuomotor tasks. Here, we reported the observation of the same negativity after correct responses across output modalities (manual and vocal responses). This indicates that, in language production too, the Ne reflects on-line response monitoring rather than error detection specifically. Furthermore, the temporal properties of the Ne suggest that this monitoring mechanism is engaged before any auditory feedback. The convergence of our findings with those obtained with nonlinguistic tasks suggests that at least part of the monitoring involved in speech production is subtended by a general-purpose mechanism.

Independent Distractor Frequency and Age-of-Acquisition Effects in Picture–Word Interference: fMRI Evidence for Post-lexical and Lexical Accounts according to Distractor Type

“…This type of monitor was proposed by de Zubicaray and colleagues (2001,2006) based upon results from their fMRI studies of SI effects, and appended to Harleyʼs (1993) connectionist computational model in a successful simulation of the SI effect (Hockey, Wiles, & de Zubicaray, 2005). Other neuroimaging studies have reached similar conclusions concerning the monitoring role of ACC in speech production (e.g., Riès, Janssen, Dufau, Alario, & Burle, 2011;Christoffels, Formisano, & Schiller, 2007). Alternatively, the activity might also be considered consistent with Roelofsʼ (2008) LSC account in which ACC performs a role in attentional control during speech production.…”

The time course of visual influences in letter recognition

“…In order to reduce electromyographic (EMG) artifacts related to the articulation of the target letter on the EEG signal, we used a blind source separation algorithm based on canonical correlation analysis (BSS-CCA), which separates sources on the basis of their degree of autocorrelation (De Vos et al, 2010; see also Riès, Janssen, Dufau, Alario, & Burle, 2011). BSS-CCA method was applied on nonoverlapping consecutive windows of 1.2 s (corresponding to the maximum length of an epoch), enabling the targeting of local EMG bursts related to articulation (we used the EEGLAB plug-in Automatic Artifact Removal, implemented by Gómez-Herrero; available at www.cs.tut.fi/~gomezher/projects/eeg/software.htm#aar).…”

How do speakers coordinate? Evidence for prediction in a joint word-replacement task

“…Note that we do not assume that processes are specific to speech, nor that the stopping process and the re-planning process need to belong to the same domain in order for interference to occur (as long as they have access to a common pool of resources). Stopping and resuming speech could indeed rely on a general-purpose monitoring system (see Riès, Janssen, Dufau, Alario, & Burle, 2011).…”