Low-Frequency Oscillations Code Speech during Verbal Working Memory

Abstract

The way the human brain represents speech in memory is still unknown. An obvious characteristic of speech is its evolvement over time. During speech processing, neural oscillations are modulated by the temporal properties of the acoustic speech signal, but also acquired knowledge on the temporal structure of language influences speech perception-related brain activity. This suggests that speech could be represented in the temporal domain, a form of representation that the brain also uses to encode autobiographic memories. Empirical evidence for such a memory code is lacking. We investigated the nature of speech memory representations using direct cortical recordings in the left perisylvian cortex during delayed sentence reproduction in female and male patients undergoing awake tumor surgery. Our results reveal that the brain endogenously represents speech in the temporal domain. Temporal pattern similarity analyses revealed that the phase of frontotemporal low-frequency oscillations, primarily in the beta range, represents sentence identity in working memory. The positive relationship between beta power during working memory and task performance suggests that working memory representations benefit from increased phase separation.SIGNIFICANCE STATEMENT Memory is an endogenous source of information based on experience. While neural oscillations encode autobiographic memories in the temporal domain, little is known on their contribution to memory representations of human speech. Our electrocortical recordings in participants who maintain sentences in memory identify the phase of left frontotemporal beta oscillations as the most prominent information carrier of sentence identity. These observations provide evidence for a theoretical model on speech memory representations and explain why interfering with beta oscillations in the left inferior frontal cortex diminishes verbal working memory capacity. The lack of sentence identity coding at the syllabic rate suggests that sentences are represented in memory in a more abstract form compared with speech coding during speech perception and production.

Keywords: electrocorticography; memory representations; sentence repetition; speech perception; speech production; temporal pattern similarity.

Figure 1.

A, Sentence reproduction paradigm. Participants listened to three-word sentences while a white circle was presented on a screen. This listening phase (in all figures color-coded in green) was followed by a 1.5 s delay in which the sentence had to be maintained in WM (color-coded in yellow). Thereafter, the circle turned green for 1.5 s, which served as a go cue for sentence reproduction (speaking phase, color-coded in blue). The intertrial interval (ITI), which started once the circle turned white, was jittered in duration between 1 and 2 s (0.5 s steps). B, Selected electrodes on a group average reconstructed cortical surface. Individual ECoG sites were transformed nonlinearly into a common space and overlaid on top of a 3D reconstructed average cortical (i.e., pial) surface. Black-rimmed circles represent anatomical center of gravity of electrodes (colored dots) in dorsal motor cortex (blue), ventral motor cortex (red), premotor cortex (green), pars opercularis of the IFG (black), pars triangularis of the IFG (cyan), posterior STG (pink), and mid STG (orange). On the group level, electrodes intertwined; but in individual participants, dorsal motor cortex electrodes were always more dorsal than ventral motor cortex electrodes. In a minority of participants, the functionally defined clusters were located slightly more caudal than the group mean. As a consequence, some participants showed motor-related activity in the postcentral gyrus.

Figure 2.

Group-averaged (A) and exemplary single patient (B) time frequency-resolved data of left perisylvian ECoG during sentence reproduction. All panels: Left to right, Rostrocaudal axis. Top to bottom, Dorsoventral axis. Plots represent averages over clusters of electrodes that share the same spectral pattern over time within an anatomical region. Power is color-coded as the relative change per cent compared with baseline. A value of 1 indicates a change of 100%. Frequency on the y axis (4–160 Hz), time on the x axis (0–5 s with trials locked to auditory sentence onset). Trial phases are illustrated in green (listening), yellow (maintenance), and blue (speaking).

Figure 3.

Perception- and production-related sentence identity coding in time (phase ΔTPSim): group data of left perisylvian ECoG. Plots represent averages over electrodes and participants. For perception-related temporal information coding during listening (green), trials were time-locked on stimulus onset; whereas for the analysis of production-related sentence identity coding during speaking (blue), trials were time-locked on individual speech onsets. Results of the analyses performed on the complex coefficient of phase-locking values of the time frequency-resolved data in the low-frequency range (4–48 Hz) are shown in each region. Significant clusters are framed in white (p < 0.01, stepwise Bonferroni-corrected). Sentence identity coding (phase ΔTPSim) was found in most frequencies almost instantaneously after stimulus onset in most of the studied frequencies and regions. During speaking, phase ΔTPSim was observed in relative higher frequencies and a narrow theta band. Time points on the x axes correspond to the center of the 500 ms analysis window.

Figure 4.

Sentence identity coding (phase ΔTPSim) during verbal WM: group data of left perisylvian ECoG. Plots represent averages over electrodes and participants during the maintenance phase with trials time-locked on the stimulus onset (0 s, top panels), on the different stimulus offsets (0 s, middle panels), and on the individual speech onsets (0 s, bottom panels). Phase ΔTPSim based on the complex coefficient of phase-locking values of the time frequency-resolved data in the low-frequency range (4–48 Hz) are shown in each region. Significant clusters during WM maintenance are framed in white (p < 0.01, stepwise Bonferroni-corrected). Borders of clusters that are too close to stimulus offset or the speech onset to be interpreted as WM-related have been colored in black. Temporal information coding (phase ΔTPSim) was observed during WM in the pars triangularis of the IFG in all of the three analyses. Phase ΔTPSim in motor cortices was first observed after the stimulus was perceived. Phase ΔTPSim in auditory association cortices was primarily observed in WM processes related to stimulus onset, respectively, to speech onset. Time points on the x axes correspond to the middle of the 500 ms analysis window. Significant clusters at the borders of the maintenance phase were not interpreted further because these effects could have been generated by the listening or the speaking phase. S, Speaking.

Figure 5.

Input- and output-related phase and power TPSim. Time points on the x axes correspond to the center of the 500 ms analysis window. A, B, Input-related phase TPSim based on the complex coefficient phase-locking value of the time frequency-resolved data in the low-frequency range (4–48 Hz) of same (A) and different (B) sentence trials. Trials were time-locked on the auditory stimulus onset (0 s). Plots represent averages over electrodes and patients. D, E, Output-related phase TPSim based on the complex coefficient phase-locking value of the time frequency-resolved data in the low-frequency range (4–48 Hz) of same (D) and different (E) sentence trials. Trials were time-locked on individual speech onset (0 s). Plots represent averages over electrodes and patients. Input-related (C) and output-related (F) gamma power TPSim (70–170 Hz) of same (red) and different sentence trials (blue). C, Trials were time-locked on stimulus onset (0 s). F, Trials were time-locked on individual speech onset (0 s). Gray shaded area represents significant ΔTPSim time intervals (p = 0.0243, corrected, ventral motor cortex in C). Plots illustrate representative single electrodes in participant 3.

Figure 6.

A, Response and repetition priming phase ΔTPSim during speech perception and production: group data of left perisylvian ECoG. Plots represent averages over electrodes and participants. For perception-related response and repetition priming phase ΔTPSim during listening (green), trials were time-locked on stimulus onset; whereas for the analysis of production-related response and repetition priming during speaking (blue), trials were time-locked on individual speech onsets. The analysis was performed on the complex coefficient phase-locking value of the time frequency-resolved data in the low-frequency range (4–48 Hz). Significant clusters (p < 0.01, stepwise Bonferroni-corrected) reflecting response priming (red) and repetition priming (blue) are overlaid onto the phase ΔTPSim analyses on sentence identity (related to Fig. 3). Time points on the x axes correspond to the middle of the 500 ms analysis window. B, Response and repetition priming phase ΔTPSim during verbal WM: group data of left perisylvian ECoG. Plots represent averages over electrodes and participants during WM maintenance with trials time-locked on the stimulus onset (0 s, top panels), on the different stimulus offsets (0 s, middle panels), and on the individual speech onsets (0 s, bottom panels). The analysis was performed on the complex coefficient phase-locking value of the time frequency-resolved data in the low-frequency range (4–48 Hz). Significant clusters (p < 0.01, stepwise Bonferroni-corrected) on response priming (red) and repetition priming (blue) are overlaid onto the phase ΔTPSim analyses, reflecting sentence identity coding during verbal WM (related to Fig. 4). Time points on the x axes correspond to the middle of the 500 ms analysis window. S, Speaking.

Figure 7.

Summary figure of sentence identity coding in the beta phase ΔTPSim and the gamma power ΔTPSim. Black-rimmed circles represent regions that coded sentence identity in the phase of beta oscillations. Small colored crosses represent single electrodes that coded sentence identity in broadband gamma power fluctuations. A, Sentence identity coding during listening (left) and speaking (right). B, Sentence identity coding during WM maintenance with trials time-locked on the stimulus onset (left), on the different stimulus offsets (middle), and on the individual speech onsets (right). Whereas input-related sentence identity coding in the beta band was observed in the auditory association cortices and the IFG, beta phase coding in the motor cortex depended on the perception of the entire sentence. There is an overall paucity of electrodes coding sentence identity in the broadband gamma signal compared with coding in the beta band.