Abstract

Introduction

Conversation is marked by a well-coordinated taking of turns between the listener and the speaker. Although occasionally a speaker will fail to withhold her response until it is her turn to speak, the vast majority of transitions between a speaker’s and a listener’s turns is smooth with minimal gap in between (e.g., Sacks et al., 1974; Stivers et al., 2009). So the ability of a speaker to withhold a planned response seems to be an important component of successful communication. Anecdotally, we are all familiar with the situation of feeling ready to say something, but doing so would cause our utterance to overlap with the speech of our conversation partner. Thus, we withhold our utterance until it is our turn to speak.

The fast and accurate transitions between speaker and listener roles in human conversation are an intriguing achievement considering that conversational turns are not fixed in length nor restricted to a particular phrase or syntactic construction (e.g., Sacks et al., 1974). The issue becomes even more interesting if one considers that a speaker may need about 600 ms to plan and begin to articulate a simple word (e.g., Indefrey and Levelt, 2004). Turn-taking studies have been conducted investigating what enables this precise timing of turn-taking in conversation (e.g., de Ruiter et al., 2006; Magyari and de Ruiter, 2012; Torreira et al., 2015). For example, Magyari et al. (2014) stated, “Given the latency of the speech production process, if speakers are going to come in on time, they must begin the production process well before the end of the other’s turn” (p. 2536; see also Levinson and Torreira, 2015). This points to the potential need to withhold a planned response: If a speaker begins the production process long before it is her time to speak, she may plan an utterance that cannot yet be articulated, as producing it would create overlap with the utterance of her interlocutor. In the present study, we investigate the speaker in a non-conversational setting with the objective of identifying the neurophysiological correlate of her ability to withhold speech.

Researchers have only recently started examining oscillatory brain activity associated with planning and producing speech (e.g., Gehrig et al., 2012; Herman et al., 2013; Jenson et al., 2014). These studies have found that desynchronization in the alpha and beta bands (7–30 Hz), localized to left inferior frontal, motor, and premotor cortex (e.g., Herman et al., 2013), precedes speech onset. This desynchronization has been interpreted in relation to the well-known alpha-beta desynchronization characteristic of preparation and execution of (hand) movements (e.g., Pfurtscheller and Lopes da Silva, 1999; for review Cheyne, 2013). The finding that speech planning has a neurophysiological signature akin to that of general motor preparation (i.e., alpha-beta desynchronization) is exciting because it allows us to link the neural mechanisms supporting speech production to mechanisms supporting other brain functions, such as motor control (see Piai et al., 2015, for further discussion).

However, speakers must also be able to withhold a verbal response that has already been planned. Very little is known about the neurophysiology of this ability. In particular, no study has yet examined oscillatory activity related to withholding a planned verbal response. Note that robust beta power increases have been shown for withholding a planned manual response (i.e., “postural maintenance”, see e.g., Engel and Fries, 2010; Kilavik et al., 2013; for reviews) Previous production studies employing electroencephalography and requiring participants to withhold a planned response have only reported event-related potentials (e.g., Jescheniak et al., 2003). Moreover, those studies were mainly concerned with addressing a psycholinguistic question, rather than with neurophysiological mechanisms of speech.

In the present study, we focus on the neurophysiology of withholding planned speech, as measured through brain oscillations. Although our paradigm does not capture the real dynamics of naturalistic human conversation, it does allow us to investigate a core component of speaking in such a setting. Our participants engaged in planning a verbal response that sometimes had to be withheld. On half of the trials, they planned a response but withheld it until a cue was presented (withhold condition). On the other half of the trials, the response could only be planned after the cue was presented (control condition). Using magnetoencephalography (MEG), we compared pre-speech oscillatory brain responses in these two conditions.

Materials and Methods

Behavioral Procedure

Participants were tested individually in an electrically, acoustically, and magnetically shielded room. The experimenter provided non-magnetic clothes to the participants. Participants were instructed to keep fixation on the center of the screen, to minimize (head) movement during the experimental blocks, and to blink only during the blinking intervals (see below).

In every trial, participants were presented with five strings, and they had to respond to the fifth one (i.e., the imperative stimulus). One of the five strings was a pseudoword that had to be pronounced. This pseudoword was either on the fourth position, in which case the pronunciation had to be withheld and the fifth string served as a go cue (the withhold condition), or it was on the fifth position, in which case it had to be pronounced immediately (the control condition). In the following, we will denote the fifth string as the imperative stimulus, because it triggers the pronunciation of the pseudoword. Thus, in the withhold condition, the imperative stimulus is a consonant string that serves as a go cue for the pronunciation of the pseudoword that is presented as the fourth string. In the control condition, the imperative stimulus is a pseudoword that serves both as a go cue and provides the content of the pronunciation. Speed as well as accuracy were emphasized. Participants then practiced the task with 15 trials. After that, they were brought to the shielded room.

Stimuli were presented through an overhead projector on a screen placed 90 cm in front of the participants. The stimuli were in Arial font, size 20. A trial began with a fixation cross presented for 500 ms. Three consonant strings were then presented in green ink for 300 ms, interleaved with a black screen for 300 ms. The fourth and fifth stimuli were presented in white ink. The fourth stimulus was presented for 300 ms, followed by a black screen of 800 ms. The fifth stimulus (imperative stimulus) was then presented for 1.5 s, followed by *** for 2 s, which was the blinking interval. The use of two colors was intended to better guide participants in differentiating between the three initial consonant strings (presented in green), and the pre-speech and imperative stimuli (in white), discouraging them to count the stimuli. Figure ​Figure11 presents an illustration of the trial structure. The 204 experimental trials were divided into four blocks with self-paced breaks in between.

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Figure 1

An example of a withhold condition (upper) and a control condition (lower) trial. The duration of each event is shown in milliseconds on top of the figure. The time line, relative to the presentation of the pre-speech stimulus, is shown on the bottom in seconds. The width of the black boxes is proportional to the duration of the events in the trial, except for the presentation of the imperative stimulus. The *** presented for 2 s at the end of the trial are not shown. Imperat, imperative; stim, stimulus.

Results

Planned Responses are Articulated Earlier

Figure ​Figure22 (left panel) shows a bean plot of the participants’ RTs (Kampstra, 2008), with the dashed line indicating the group mean and the two filled black lines indicating the mean of each condition. Each short white line represents the median RT of one participant for that condition. The cumulative distribution of participants’ RTs as a function of condition is shown in the right panel. Verbal responses were on average 208 ms faster in the withhold than in the control condition, t₍₁₄₎ = 7.86, p < 0.001, 95% CI (151, 264). The cumulative RT distribution shows that the effect is the result of a shift of the entire distribution as a function of whether participants could prepare their responses before the cue or not. Moreover, the larger difference between the two conditions for the 20% fastest responses is possibly due to the fact that the inter-stimulus interval preceding the pre-speech stimulus is fixed. As such, participants are more likely to predict exactly when to speak.

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Figure 2

Left. Beanplot of the group-average response times (RTs) for the withhold (blue) and control (red) conditions. The dashed line indicates the group mean whereas the two filled lines indicate the mean of each condition. Each short line represents the median RT of each participant. Right. Cumulative distribution of participants’ RTs as a function of condition.

Planning and Withholding Speech Increases EMG Activity

Figure ​Figure33 shows the EMG from the orbicularis oris muscle for each condition. Shaded areas indicate the time intervals associated with the significant clusters. The EMG was increased in the withhold condition relative to control already during the pre-speech interval, and this difference increased further after the imperative stimulus was presented. These observations were confirmed by the cluster-based permutation test, which revealed two temporal clusters that exhibited a larger amplitude in the withhold than in the control condition (p = 0.009 and p < 0.001, respectively). These clusters were detected between 660 ms and 862 ms (left shaded area), and from 925 ms until the end of the segment (i.e., 1500 ms, right shaded area). Thus, we have a physiological indication that participants planned their responses in the withhold condition already prior to the imperative stimulus.

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Figure 3

Group-level electromyogenic activity from the orbicularis oris muscle for the withhold (blue) and control (red) condition. Shaded areas indicate the time intervals associated with the significant clusters.

Cortical Signatures of Planning and Withholding Planned Speech: Frontal Beta-Power Increases and Posterior Alpha-Beta Power Decreases

We statistically compared the withhold and the control condition with respect to time-averaged power (shown in Figure ​Figure4A)4A) as a function of both frequency and space (sensor location). In a cluster-based permutation test, two clusters with significant p values were observed, one over frontal and one over posterior sensors. Figure ​Figure4A4A shows the power spectra for each condition during the pre-speech interval averaged over the significant frontal and posterior sensors shown on top of each spectrum. Figure ​Figure4B4B shows the relative power changes between the withhold and control conditions during the prespeech interval for the significant sensors. Over frontal sensors, power increased in the withhold relative to the control condition (withhold > control, between 5–13%) in the 12–20 Hz range (p = 0.012). This range is indicated by the strong purple color in Figure ​Figure4B.4B. Over posterior sensors, power decreased in the withhold relative to the control condition (withhold < control, between 5–25%) in the 8–30 Hz range (p < 0.001). Figure ​Figure4C4C shows the topographical maps of the relative power changes for two frequency ranges, indicated on top of each map.

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Figure 4

Group-level raw power and relative power changes (withhold vs. control) during the pre-speech interval. (A) Group-level raw power spectra averaged over a group of frontal sensors (left panel) and posterior sensors (right panel) for the withhold (blue) and control (red) conditions. (B) Group-level relative power spectra averaged over a group of frontal (purple) and posterior (green) sensors as shown in the top right corner of panel (B). Significant frequency ranges are indicated by stronger colors (frontal sensors: 12–20 Hz; posterior sensors: 8–30 Hz). (C) Group-level topographical maps of the relative power changes for two frequency ranges (8–30 Hz and 12–20 Hz), indicated on top of each map. Rel, relative.

We source-localized both effects during the pre-speech interval using a frequency-domain beamformer analysis in the 12–20 Hz range, since this frequency range was optimal for the frontal power increases while capturing both the posterior power decreases and the frontal increases. We also statistically compared the withhold and the control condition at the source level using a cluster-level permutation test. Figure ​Figure55 shows the results, masked by the statistically significant clusters, with the color scale indicating the percentage change in power. The results parallel those of the sensor-level analysis: one positive cluster (withhold > control, p = 0.005) over bilateral frontal areas, localized to the superior and middle frontal gyri, and inferior frontal gyrus albeit less strong, and one negative cluster (withhold < control, p < 0.001) over bilateral occipital cortex. When source localizing the effects in the 8–30 Hz range, very similar results were obtained to what we present here.

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Figure 5

Group-level source localization of the power differences (withhold vs. control) between 12–20 Hz during the pre-speech interval. The color bar shows relative (rel) power changes, masked by the statistically significant clusters.

To assess whether the frontal beta power differences during the pre-speech interval are due to a pattern of synchronization or desynchronization relative to baseline, frontal beta power (i.e., 12–20 Hz, statistically significant frontal sensors) was normalized to a baseline period (−0.3–0 s) for each participant. Participants’ normalized mean frontal beta-power and 95% confidence intervals are shown in Figure ​Figure66 for each condition separately. It is clear from the figure that frontal beta-power increases relative to the baseline period in the withhold condition, but remains similar to baseline levels in the control condition (the dashed lines indicate no (0) change from baseline). Participants’ normalized frontal beta-power was assessed statistically by means of a t-test against zero in each condition at an alpha-level of 0.025 to correct for two comparisons. In the withhold condition, frontal beta-power increased during the pre-speech interval relative to baseline, t₍₁₄₎ = 4.22, p < 0.001. In the control condition, frontal beta-power was not significantly different from baseline, t₍₁₄₎ = 0.40, p > 0.696. Finally, a paired-sample t-test indicated that the baseline normalized frontal beta-power was larger in the withhold (mean: 0.086) than in the control (mean: 0.007) condition, t₍₁₄₎ = 3.50, p = 0.004.

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Figure 6

Group-level mean frontal beta-power (12–20 Hz) during the pre-speech interval for the control (left) and withhold (right) condition relative to the baseline period. Error bars indicate 95% confidence intervals.

Frontal Beta Power Increases are not Due to Myogenic Artifacts

Given that the EMG was increased for the withhold relative to the control condition already during the pre-speech interval, it is important to assess whether the power increases below 8 Hz and between 12–20 Hz are caused by myogenic artifacts. Below, we evaluate this possibility for each of these frequency bands.

Firstly, if myogenic activity would explain the beta effect prior to speech, then beta power should be stronger during speech, when myogenic activity is greatest, than preceding speech. Figure ​Figure77 shows the power spectrum for each condition pre-speech and during speech averaged over the frontal sensors indicated in light blue (i.e., the statistically significant frontal sensors). Contrary to the prediction, frontal beta power was lower during speech (orange and black lines) than in the pre-speech interval (blue and red lines) between 12–20 Hz. This observation was confirmed by a repeated measures analysis of variance on the frontal beta-band power as a function of condition (withhold vs. control) and interval (pre-speech vs. during speech) at an alpha level of 0.0125 to correct for four comparisons. Frontal beta power was lower during speech than in the pre-speech interval, as indicated by a main effect of interval, F_(1,15) = 20.55, p < 0.001. Condition and interval interacted, F_(1,15) = 18.60, p < 0.001, indicating that power was lower during speech than preceding speech for the withhold condition, F_(1,15) = 36.76, p < 0.001, but statistically similar for the control condition, F_(1,15) = 5.49, p = 0.035. With respect to the 5–7 Hz range, Figure ​Figure77 suggests that frontal power is similar pre-speech and during speech for both conditions. If 5–7 Hz frontal power during speech, when myogenic activity is greatest, is as high as preceding speech, it would indicate that the 5–7 Hz range is likely contaminated with myogenic activity. A repeated measures analysis of variance was conducted on the frontal power in the 5–7 Hz range as a function of condition (withhold vs. control) and interval (pre-speech vs. during speech) at an alpha level of 0.0125 to correct for four comparisons. Frontal power in the 5–7 Hz range was not statistically different during speech from preceding speech, F_(1,15) < 1, nor different between conditions, F_(1,15) = 4. 20, p = 0.063. Condition and interval did not interact, F_(1,15) < 1. Thus, we can conclude that the frontal power increases between 12–20 Hz during the pre-speech interval are not caused by myogenic artifacts. The frontal power increases between 5–7 Hz, however, are likely caused by muscle activity.

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Figure 7

Group-level raw power spectra as a function of condition during the pre-speech interval (withhold: blue; control: red) and during speech (withhold: orange; control: black) averaged over the frontal sensors indicated on top.

Discussion

In the present study, we investigated the neurophysiology of withholding a planned verbal response through brain oscillations. It has been argued that neuronal oscillations may provide the key to understanding neuronal computations. Under this view, relating neurophysiological signatures in linguistic tasks to the signatures of other cognitive processes could help us understand language function in the context of more basic neurophysiological principles implemented in the brain (see for examples, Piai et al., 2014; Friederici and Singer, 2015).

Preceding the imperative stimulus (during the pre-speech interval), alpha-beta power (8–30 Hz) decreased 5–25% in the withhold relative to the control condition. This power decrease was restricted to occipital sensors and localized mainly to the occipital cortex bilaterally. By contrast, relative beta (12–20 Hz) power increased 5–13% over frontal sensors and was localized to a frontal source (middle and superior frontal gyri, and partly inferior frontal gyrus). Moreover, the EMG recorded from the orbicularis oris muscle was already increased for the withhold relative to the control condition during the pre-speech interval, confirming that participants prepared their responses. Below, we discuss the oscillatory effects in more detail.

The most robust oscillatory signature of preparing to speak is alpha-beta desynchronization in speech motor areas such as left inferior frontal cortex and ventral motor and premotor cortex (e.g., Salmelin and Sams, 2002; Saarinen et al., 2006; Herman et al., 2013; Jenson et al., 2014; Piai et al., 2015). Our results of beta synchronization in superior and middle frontal gyri when withholding a planned verbal response are clearly different from the signature of speech preparation.

An interesting parallel with our beta synchronization effect can be found in instructed delay tasks, such as go/no-go. In a review of these tasks, it was noted that beta synchronization is commonly observed during an interval of stimulus processing while overt movement is withheld until the go signal (Kilavik et al., 2013). This interval in go/no-go tasks is equivalent to our pre-speech interval. In the literature beta synchronization has been found not only over sensorimotor cortex but also extending further into the entire frontal lobe (see Kilavik et al., 2013 for a review of these findings). This suggests that a similar spatial-spectral pattern underlies withholding speech and withholding other types of overt movement. The functional role of this beta synchronization while overt movement is withheld, however, has not been well specified (see for discussion Kilavik et al., 2013). A tentative functional explanation for this beta synchronization may be found in the proposal of Engel and Fries (2010). On their account, if the current sensorimotor or cognitive state has to be maintained, beta activity is increased. In fact, these authors explicitly predict that activity in the beta band should be increased “during delay-periods where the cognitive set has to be maintained following a cue” (p. 160). This prediction fits with our observation of beta-power increases in the withhold condition during the interval when participants prepare but do not execute their verbal responses. Presumably, in this period, the current motor or cognitive state has to be maintained to enable successful speech production.

The maintenance of the sensorimotor state modulates activity in sensorimotor brain regions (see for review, Engel and Fries, 2010). In our case, the sensorimotor areas associated with speech planning would be left inferior frontal cortex and ventral motor and premotor cortex (e.g., Salmelin and Sams, 2002; Saarinen et al., 2006; Herman et al., 2013; Jenson et al., 2014). Yet, the beta-power increases we observed were more prominent in bilateral superior and middle frontal gyri, less so in bilateral inferior frontal gyrus, and (statistically and descriptively) absent in ventral motor and premotor cortex. It could be the case that cognitive-set maintenance would be subserved by dorsolateral prefrontal cortex (e.g., Petrides, 2005; Buschman et al., 2012; Stoll et al., 2015), compatible with our source localization to superior and middle frontal gyri. Modulations of frontal beta-band oscillations have also been found in a study manipulating the demands for cognitive control (Stoll et al., 2015), which is possibly involved in our task. Future studies will hopefully clarify these issues.

Modulations of alpha and beta oscillatory power often reflect expectation and prediction (e.g., van Ede et al., 2010; Arnal and Giraud, 2012; Pomper et al., 2015). Most relevant to the present study, alpha desynchronization in occipital cortex in expectation of a visual stimulus is a well-known finding (e.g., Foxe et al., 1998; Worden et al., 2000; Sauseng et al., 2005; Romei et al., 2010). Activity during our pre-speech interval is likely to encompass the anticipation of (or attention towards) the visually presented imperative stimulus, as well as preparation of the spoken response. The occipital source of our alpha-beta desynchronization speaks in favor of a visual attention interpretation, rather than preparation of the spoken response. Decreases in pre-stimulus posterior alpha-power have been often associated with improvements in visual perception (e.g., van Dijk et al., 2008; Jensen and Mazaheri, 2010; Jensen et al., 2012). There are at least two possibilities regarding attentional differences between the two conditions. One possibility is that in the control condition participants have to maximize visual processing to perceive the imperative stimulus and process its content, which is necessary for articulating the target. Another possibility is that in the withhold condition, the imperative stimulus is treated as a go signal and participants need to be maximally sensitive to it in order to respond as fast as possible upon its presentation. Under the assumption that alpha-band desynchronization reflects improved visual processing, or enhanced excitability of visual cortex (Lange et al., 2013), the first possibility would predict power decreases in the control relative to the withhold condition. However, this is the opposite of what we found. Thus, the power decreases are consistent with the second possibility, that is, the participants trying to be maximally sensitive to the imperative stimulus to respond as fast as possible after having prepared their responses.

It can be argued that the difference between the withhold and control conditions in the pre-speech interval is due to a different working-memory demand. Whereas in the control condition, participants were simply waiting for the imperative stimulus, in the withhold condition, they were maintaining the pseudoword in working memory. Although this hypothesis is compatible with our results, it is unclear whether it can fully account for our frontal beta synchronization effect. Firstly, the predominant oscillatory responses associated with working-memory maintenance are not within the frequency range in which we found power increases (12–20 Hz). In the working memory literature (Roux and Uhlhaas, 2014), oscillations between 4–13 Hz (theta and alpha) and above 30 Hz (gamma) have been associated with working-memory maintenance. Notably, the almost complete absence of beta-band effects in the working-memory literature has led some to question whether beta-band activity is even relevant for working memory (Roux and Uhlhaas, 2014). Moreover, if found, beta-band activity during working-memory maintenance tends to localize to posterior, rather than frontal, brain areas (see for review, Roux and Uhlhaas, 2014). Some form of working memory retention is inevitably involved in the act of withholding speech. In the present study, we did not intend to distinguish between this specific form of working memory retention and other forms (such as those that do not involve motor programming).

Furthermore, it can be argued that the fixed timing of stimulus presentation is a confound in our study because participants learned the timing of stimulus presentation, increasing their expectations. Importantly, however, the fixed timing of presentation was the case for both conditions. Thus, although the expectation of when stimuli will be presented plays a role in our task, it cannot exaplain the observed spectral differences between the two conditions.

In summary, when participants planned a verbal response and withheld it until an imperative stimulus was presented, beta-power (12–20 Hz) increases were observed in frontal brain areas relative to a control condition not involving speech planning and retention. For the same comparison during the same interval, power decreased over a broad range of frequencies (8–30 Hz) in occipital cortex. Both posterior alpha- and beta-power decreases and frontal beta-power increases are comparable to findings in other cognitive tasks not employing language or verbal responses. In keeping with the extant literature, we interpret our beta-power increases in relation to the maintenance of a cognitive (and possibly motor) set during the pre-speech interval. Altogether, these results suggest that a speaker’s ability to plan and withhold speech relies on similar neurophysiological computations as other cognitive functions outside of the language domain.

Author Contributions

Conceptualized and designed the experiment (VP, AR, JR, EM); acquired the data (VP, KD); analyzed the data (VP, KD); wrote the paper (VP, AR, JR, KD, EM). All authors have approved the final version of the paper and agree to be accountable for all aspects of this work.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Footnotes

References