The effects of background speech or noise on visually based cognitive tasks has been widely investigated; however, little is known about how the brain works during such cognitive tasks when music, having a powerful function of evoking emotions, is used as the background sound. The present study used event-related potentials to examine the effects of background music on neural responses during reading comprehension and their modulation by musical arousal. Thirty-nine postgraduates judged the correctness of sentences about world knowledge without or with background music (high-arousal music and low-arousal music). The participants’ arousal levels were reported during the experiment. The results showed that the N400 effect, elicited by world knowledge violations versus correct controls, was significantly smaller for silence than those for high- and low-arousal music backgrounds, with no significant difference between the two musical backgrounds. This outcome might have occurred because the arousal levels of the participants were not affected by the high- and low-arousal music throughout the experiment. These findings suggest that background music affects neural responses during reading comprehension by increasing the difficulty of semantic integration, and thus extend the irrelevant sound effect to suggest that the neural processing of visually based cognitive tasks can also be affected by music.
The human brain usually must manage multi-modal information, such as visual and auditory information, simultaneously in the real world. Auditory inputs can hinder visual processing when both visual and auditory stimuli are presented1,2,3. Even if people are instructed to focus on visual inputs while ignoring auditory inputs, the ignored background sounds still interfere with visual processing. A typical example of this phenomenon is the irrelevant speech effect (for a review, see Vasilev et al.4), suggesting that task-irrelevant background speech disrupts the recall of visually presented digits5,6 and text7,8, proofreading9, and sentence or passage comprehension10,11,12. This effect could be attributed to the same cognitive process used for focal tasks, such as semantic processing, when meaningful speech is used as the background stimulus13,14. However, even when the background sounds are noise, this interference effect also occurs15,16,17. Such an effect might be explained by the limited capacity theory of Kahneman18, which posits that the amount of attention is limited, and performing multiple tasks leads to a competition for limited resources when their combined demands exceed the available resources, resulting in poor performance on one task due to an insufficient supply of attention.
Unlike speech or noise, music has a remarkable function of evoking and affecting listeners’ emotions19,20. Background music provides a unique window into how the brain works when music and cognitive tasks are presented simultaneously. Previous studies have primarily focused on the effects of background music on reading comprehension. Some behavioural studies have shown that reading comprehension can be improved using background music, such as Mozart’s music21,22,23, highly repetitive music with a narrow tonal range24 and songs25. In contrast, other studies have shown negative effects of background music on reading comprehension using hip-hop music26, UK garage-style music17, slow-tempo music by Bach27, fast and loud music28, familiar non-lyrical music29,30, and songs31,32,33,34 as background music. The discrepancy between these behavioural studies could be due to the differences in music and listeners. Indeed, the effects of background music on reading comprehension depend on music style26, music characteristics (such as tempo and complexity)24,27, and lyrics32. On the other hand, some individual factors, such as musical preferences35 and music expertise36, have been suggested to influence the effects of background music. For example, non-preferred, rather than preferred, background music disrupts reading comprehension35. Similarly, background music interferes with reading comprehension for musicians but not for non-musicians36.
Notably, the aforementioned findings were drawn from behavioural investigations. To our knowledge, only one EEG study has examined the effects of the type of background music on cognitive performance, brain wave activity, and heart rate during reading comprehension37. In that study, classical and dubstep music pieces were used as background music. Although the reading comprehension performance was better with the classical music than with the dubstep music background at the behavioural level, the type of background music had no effect on brain activity or physiological responses during reading comprehension. Indeed, even during face encoding, no differences in cortical activity between the background music and silence conditions were found38. The absence of the effect of background music is consistent with a recent study suggesting that background music has no effect on inhibitory functions, as evidenced by no differences in influences on inhibitory functions among relaxing, exciting background music and silence conditions at both the behavioural and electrophysiological levels39. To date, however, little is known about how the brain works when reading tasks are accompanied by background music or not. Thus, one goal of the present study was to investigate how background music affects neural responses during reading comprehension using ERPs.
When music and cognitive tasks are presented successively, music listening can induce a positive mood, increase arousal levels, and improve subsequent cognitive processing40. Indeed, this facilitatory effect has been confirmed in spatial tasks40,41,42,43. Because the music and cognitive task were presented successively in these studies, further examining whether musical arousal can affect cognitive processing when music and cognitive tasks are presented simultaneously is important. Thus, the second goal of the present study was to investigate whether the arousal level of background music modulates the neural responses during reading comprehension.
The present study focused on world knowledge, an essential component of reading comprehension44. Indeed, successful reading comprehension and language understanding have been suggested to rely on the utilization of acquired world knowledge45,46. Previous studies have demonstrated that world knowledge violations elicited a larger N400 than correct sentences47,48,49,50. The N400 is an ERP index of semantic processing (for a review, see Kutas and Federmeier51). The increased amplitude of N400 reflects the increased difficulty of semantic integration52,53,54, suggesting that more effort is required to integrate the meaning of a stimulus into the preceding contexts55,56,57 or prior world knowledge (for a review, see Lau, Phillips and Poeppel58).
Thus, the goals of the present study were to examine the effects of background music on neural responses to world knowledge integration and its modulation by musical arousal, with a 3 (group: high-arousal music, low-arousal music, and silence) × 2 (sentence type: correct vs world knowledge violation) mixed design. First, we included high- and low-arousal music as two types of background music because music-evoked arousal may mediate the effects of prior exposure to music on subsequent cognitive processing40,59,60. Participants reported their arousal levels during the entire experiment to demonstrate the effect of musical listening on the level of arousal. Second, each participant completed reading comprehension in one of three backgrounds, silence or low- or high-arousal music, to exclude the carry-over effect. Third, each sentence was presented word by word, and the last word of each correct sentence was changed to form a sentence with a world knowledge violation. Fourth, both the high- and low-arousal musical excerpts used in our study were unfamiliar instrumental music expressing positive emotions to control for the influences of musical familiarity on reading comprehension. Finally, three pretests were conducted to ensure the validity of the stimuli. The first pretest assessed the emotional valence and arousal levels of the background music that we used. The second pretest ensured that the originally created sentences were unambiguous, and the last pretest confirmed a significant difference in reasonableness between the two types of sentences. We expected that, if background music is as distracting as irrelevant speech61 or noise17, the N400 effect for silence should be smaller than that for background music.
The results of the mean accuracy and mean reaction times (RTs) are summarized in Table 1. Based on previous studies62,63,64, trials with incorrect judgement and trials with RTs shorter than 200 ms or longer than 1500 ms were excluded from the calculations of mean RTs. Regarding the mean accuracy, a nonparametric ANOVA-type statistic (ATS) taking group (high-arousal music, low-arousal music and silence) as the whole-plot factor and sentence type (correct vs. world knowledge violation) as the sub-plot factor was conducted. No significant effects were found for either the main effects of group [ATS(1.99) = 0.38, p = 0.683] and sentence type [ATS(1) = 0.99, p = 0.319] or the interaction between group and sentence type [ATS(1.86) = 0.92, p = 0.392]. For the mean RTs, a two-way mixed analysis of variance (ANOVA) taking group as the between-subjects factor and sentence type as the within-subjects factor revealed no significant effects for either the main effects for group [F(2, 36) = 1.65, p = 0.207, ηp2 = 0.08] and sentence type [F(1, 36) = 1.53, p = 0.224, ηp2 = 0.04] or their interaction [F(2, 36) = 0.66, p = 0.525, ηp2 = 0.04]. These results suggested that our participants concentrated on the reading task during the experiment and understood the sentences well.
To examine whether background music can induce emotional arousal, the participants’ arousal levels were reported 15 times throughout the experiment. A nonparametric ATS taking group as the whole-plot factor and time (T1, T2, T3, …, T15) as the sub-plot factor was conducted. As shown in Fig. 1, neither the main effects for group [ATS(1.93) = 0.68, p = 0.502] and time [ATS(7.02) = 1.44, p = 0.183] nor their interaction was significant [ATS(10.61) = 1.14, p = 0.329]. These results indicated that the participants’ arousal levels were not affected by the background music.
Figure 2 shows the electric brain responses to correct sentences and sentences with world knowledge violations and topographical maps for the different groups. As shown, world knowledge violations elicited a larger N400 than correct sentences in the time windows of 200–450 ms, with a broad scalp distribution. However, the magnitude of the N400 effect seemed to differ between the groups with and without background music. Because we focused on the influences of background music and the differences associated with the N400 effect, only the significant effects related to group or sentence type are reported in the following paragraphs.
For the midline electrodes, a three-way mixed ANOVA taking group as the between-subjects factor and sentence type and anteriority (anterior, central and posterior) as the within-subjects factors was conducted. A significant main effect was found for sentence type [F(1,36) = 118.36, p < 0.001, ηp2 = 0.77], indicating that world knowledge violations elicited a larger N400 than correct sentences. A significant two-way interaction was also found between group and sentence type [F(2,36) = 9.22, p = 0.001, ηp2 = 0.34] owing to a larger N400 elicited by world knowledge violations than by correct sentences in the silence [F(1,36) = 8.03, p = 0.008, ηp2 = 0.18], low-arousal music [F(1,36) = 73.17, p < 0.001, ηp2 = 0.67], and high-arousal music groups [F(1,36) = 55.61, p < 0.001, ηp2 = 0.61]. Furthermore, a significant two-way interaction between sentence type and anteriority was also observed [F(1.59,57.15) = 8.61, p = 0.001, ηp2 = 0.19], reflecting that a larger N400 was elicited by world knowledge violations than by correct sentences in the anterior [F(1,36) = 22.13, p < 0.001, ηp2 = 0.38], central [F(1,36) = 113.24, p < 0.001, ηp2 = 0.76], and posterior regions [F(1,36) = 116.76, p < 0.001, ηp2 = 0.76].
A two-way mixed ANOVA taking group as the between-subjects factor and anteriority as the within-subjects factor was conducted to further examine whether differences existed in the magnitude of the N400 effect among the three groups. A significant main effect was found for group [F(2,36) = 9.20, p = 0.001, ηp2 = 0.34]. Pairwise comparisons revealed a smaller N400 effect in the silence group than in the low-arousal music (p = 0.001) and high-arousal music groups (p = 0.007), but the latter two groups did not differ from each other (p > 0.05). A significant main effect was also found for anteriority [F(1.43,51.29) = 8.96, p = 0.002, ηp2 = 0.20]. Pairwise comparisons showed a larger N400 effect in the central versus anterior region (p < 0.001), but no differences were found between the central and posterior regions (p > 0.05) or between the anterior and posterior regions (p > 0.05). The interaction between group and anteriority was not significant (p > 0.05).
For the electrodes in the lateral regions, a four-way mixed ANOVA taking group as the between-subjects factor and sentence type, anteriority and hemisphere (left vs. right) as the within-subjects factors was conducted. A significant main effect of sentence type was found [F(1,36) = 113.29, p < 0.001, ηp2 = 0.76], indicating that world knowledge violations elicited a larger N400 than correct sentences. A significant two-way interaction was also found between group and sentence type [F(2,36) = 7.13, p = 0.002, ηp2 = 0.28] owing to a larger N400 elicited by world knowledge violations than by correct sentences in the silence [F(1,36) = 9.64, p = 0.004, ηp2 = 0.21], low-arousal music [F(1,36) = 52.15, p < 0.001, ηp2 = 0.59], and high-arousal music groups [F(1,36) = 65.75, p < 0.001, ηp2 = 0.65]. A significant two-way interaction between group and hemisphere was also observed [F(2,36) = 3.36, p = 0.046, ηp2 = 0.16], indicating that both the low-arousal music [F(1,36) = 6.82, p = 0.013, ηp2 = 0.16] and high-arousal music groups [F(1,36) = 29.18, p < 0.001, ηp2 = 0.45] exhibited stronger neural responses in the left than right hemisphere, while the silence group showed a marginally significant difference in neural responses between the left and right hemispheres [F(1,36) = 3.80, p = 0.059, ηp2 = 0.10]. Furthermore, the two-way interaction between sentence type and anteriority was also significant [F(1.33,48.00) = 4.50, p = 0.029, ηp2 = 0.11], indicating that a larger N400 was elicited by world knowledge violations than by correct sentences in the anterior [F(1,36) = 26.82, p < 0.001, ηp2 = 0.43], central [F(1,36) = 109.78, p < 0.001, ηp2 = 0.75], and posterior regions [F(1,36) = 156.93, p < 0.001, ηp2 = 0.81].
A nonparametric ATS taking group as the whole-plot factor and anteriority and hemisphere as the sub-plot factors was conducted to further examine whether differences existed in the magnitude of the N400 effect among the three groups. A significant main effect was found for group [ATS(1.94) = 5.55, p = 0.004]. Pairwise comparisons revealed a smaller N400 effect in the silence group than in the low-arousal music (p = 0.018) and high-arousal music groups (p = 0.012), but the latter two groups did not differ from each other (p > 0.05). A significant main effect was also found for anteriority [ATS(1.27) = 4.37, p = 0.027]. Pairwise comparisons revealed a larger N400 effect in the central than in the anterior region (p < 0.001), but no differences were found between the central and posterior regions (p > 0.05) or between the anterior and posterior regions (p > 0.05). No other main effects or interactions were significant (ps > 0.05).
The present study used ERPs to investigate the effects of background music on neural responses during reading comprehension and its modulation by musical arousal level. The results showed that a larger N400 was elicited in response to world knowledge violations than correct controls during reading comprehension either with or without background music. However, the N400 effect for silence was significantly smaller than those for high- and low-arousal music backgrounds, with no significant difference between the two musical backgrounds. The arousal levels of the participants were not affected by the high- and low-arousal music during the experiment. These findings suggest that background music influenced the neural responses during reading comprehension, and the musical arousal level did not alter the effects of background music on reading comprehension.
The main finding of the present study is that reading comprehension elicited a larger N400 effect with background music than without background music. The classical N400 effect, which manifests in a larger negative amplitude for semantically incongruent sentences than for congruent sentences, reflects semantic processing51,65,66. This N400 effect has also been observed in response to sentences with world knowledge violations47,48,49,50,67,68,69. The amplitude of N400 is assumed to reflect the difficulty of integrating the coming word into the preceding context52,53,54. The higher that the difficulty of integrating the violations into the preceding context or world knowledge is, and the greater that the efforts deployed by the brain for the integration are, the larger that the N400 is52,53,54,55,56,57. Therefore, the different N400 effects in our study could indicate that the background music groups required more effort deployed by the brain to integrate violated words into pre-existing world knowledge than the silence group. In other words, compared with the silent context, the presence of background music increased the difficulty of neural processing during reading comprehension.
Our findings can be interpreted according to the limited capacity theory18 and the distraction hypothesis70, suggesting that individuals’ attention resources are limited and that concurrent tasks compete for available attention. When the required resources exceed the available resources, the tasks interfere with each other. In the present study, because the presence of background music might demand attention resources, the attention resources used to complete reading comprehension were reduced, resulting in difficulties in sentence integration, eventually manifested as a larger N400 effect.
Another finding of the present study is that no significant difference was observed in the N400 effect between the high- and low-arousal music groups, consistent with Burkhard et al.39 who showed no different effects on inhibitory function between the relaxing and exciting background music conditions. This finding could be attributed to the constant arousal levels of our participants during the entire experiment. Specifically, neither the high- nor low-arousal background music induced emotional arousal during the experiment. Indeed, previous studies have also found that background music fails to induce emotional arousal71,72. The failure to induce emotional arousal during cognitive processing could be explained by the characteristics of the background music. Emotionally touching background music can possibly enhance participants’ arousal levels relative to background music that is not emotionally touching73. On the other hand, the competition for attention resources during cognitive processing could also account for the failure to induce emotional arousal. Specifically, although background music affected reading comprehension in the present study, the attention resources available for listening to background music were limited due to competition for attention resources. In this case, background music might not be sufficient to increase participants’ arousal levels when presented with reading tasks.
Although the reading stimuli in the present study were written in Chinese, an ideographic language, this fact is not a limitation of the study. Specifically, previous studies have demonstrated that world knowledge violations can elicit an N400 effect relative to correct controls, not only in Chinese48,68 but also in other languages using alphabets, such as English49,69, Dutch50,74 and German47,67,75. These findings indicate that the difference between ideographic and alphabetic languages does not affect the neural processing of world knowledge integration in sentence comprehension. On the other hand, regarding the background music, our background stimuli were selected from Western tonal music composed in the Baroque and Classical periods. It is well known that Western tonal music has been widely spread in many areas of the world. Due to familiarity with tonal conventions of Western music, both Western76,77 and Chinese listeners78,79 can process Western tonal structures and exhibit similar neural responses to these tonal structures. Therefore, our findings could be applicable to many other populations who speak alphabetic languages.
In conclusion, the present findings showed that the presence of background music influences neural responses during reading comprehension regardless of whether the music is of high or low arousal. Our findings extend the irrelevant sound effect, suggesting that the processing of visually based cognitive tasks can be disrupted not only by task-irrelevant background speech6,7,9,10 or noise15,16,17 but also by music. Indeed, when music is presented prior to the cognitive task, a unique facilitatory effect of music occurs on non-music cognitive processing because prior exposure to music can induce participants’ emotions and subsequently improve subsequent cognitive tasks40,59,60. However, when presented simultaneously with the reading task, neither high- nor low-arousal music increased participants' arousal levels. In this case, background music might become a source of distraction for reading tasks since both compete for available attention, thus increasing the difficulty of semantic integration during reading comprehension.
A prior power analysis using G*Power software, version 22.214.171.1240, was conducted to determine the minimum sample size. To detect interactions with 80% statistical power, an alpha level of 0.05, and a medium effect size (ƒ = 0.25), we needed at least 12 participants in each group. Given that the habit of using background music can affect reading comprehension25,34,81, 39 postgraduates who preferred listening to music (n = 26) or a silent environment (n = 13) during reading were recruited for this study to control for the potential effect of this habit. They were then assigned to the low- and high-arousal music groups or the silence group based on their reading habits. The three groups (13 participants for each group) were matched by sex, age, and years of education (see Table 2). All of the participants were right-handed, with normal hearing and normal or corrected-to-normal vision. None had received musical training, and had any previous history of psychiatric or neurological disorders. The protocol for the experiment was approved by the Ethics Committee of Shanghai Normal University in China and conducted in line with the Declaration of Helsinki. All of the participants provided informed consent prior to the experiment and were paid for their participation.
For background music stimuli, six pieces of fast-tempo and six pieces of slow-tempo music in major mode were originally selected as the high- and low-arousal music clips, respectively, given that major mode and fast-tempo music tends to induce a positive mood and increase arousal levels, whereas minor mode and slow-tempo music tends to induce a more negative mood and lower arousal levels59. All music excerpts were orchestral music without voice or lyrics selected from Western tonal music composed in the Baroque, Classical, or Romantic periods. The music stimuli were normalized to − 3 dB and saved as monaural .wav files with a sampling rate of 44.1 kHz and 16-bit resolution by means of Adobe Audition software, version CS6 (Adobe System Inc., San Jose, CA, USA).
A pretest was conducted to assess the emotional valence and arousal levels of the selected music excerpts. Sixteen musically untrained participants who preferred listening to music during reading were asked to rate each music excerpt with regard to perceived valence and arousal on two 6-point scales (valence: 1 = very negative, 6 = very positive; arousal: 1 = very calming, 6 = very exciting). Moreover, they were asked to report whether they were familiar with the music excerpts. None of them participated in the subsequent ERP experiment. To avoid distraction from the reading task resulting from changes in different music excerpts during playing, only two unfamiliar music excerpts with the highest or lowest arousal level were chosen as the background music stimuli. Specifically, the high-arousal music excerpt was selected from Handel’s Oboe Sonata in B-flat Major, HWV 357, Movement I (Andante), while the low-arousal music was selected from Mozart’s Violin Concerto No.1 in B-flat Major, K.207, Movement III (Presto). Paired sample t tests showed that high-arousal (arousal: M = 5.44, SD = 0.63; valence: M = 5.13, SD = 0.81) and low-arousal music (arousal: M = 3.38, SD = 0.81; valence: M = 4.75, SD = 0.68) differed significantly in perceived arousal levels [t(15) = − 10.69, p < 0.001, d = 2.80] and matched in perceived valence [t(15) = − 1.70, p = 0.111, d = 0.50].
For sentence stimuli, 90 original Chinese sentences expressing world knowledge were created. Each sentence consisted of three to seven words. The second pretest was conducted to ensure that all of the sentences were unambiguous. Nine participants who did not participate in the formal experiment read each sentence in which the last word (critical word) had been deleted, and then completed the sentence with the word that they thought was most reasonable. Thus, 77 sentences to which all of the participants answered correctly were chosen as correct sentences. Seventy-seven sentences with world knowledge violations were then created by replacing the last word of the correct sentences with a word that violated world knowledge (see Table 3). The word frequency of the last word in the two types of sentences was matched (p > 0.05). A third pretest was conducted to determine whether a difference existed in reasonableness between the two types of sentences. Twelve participants not participating in the formal experiment were recruited to rate the reasonableness of all 154 sentences on a 5-point scale (from 1 = very unreasonable to 5 = very reasonable). Paired sample t-tests showed that correct sentences (M = 4.69, SD = 0.25) and sentences with world knowledge violations (M = 1.06, SD = 0.05) differed significantly in reasonableness (t(11) = 53.28, p < 0.001, d = 15.84).
Stimulus presentation and response timing were controlled by E-Prime 1.0 (Psychology Software Tools Inc., Sharpsburg, PA, USA), on a computer. Before the formal experiment, four trials were administered for practice. Each trial started with a red fixation point in the middle of the screen with a black background for 800 ms, followed by a 400-ms blank screen. After the blank screen, a sentence was presented word by word. The duration of each word presentation was 400 ms, except that the last critical word with a dot was presented for 3000 ms. A 400-ms blank screen appeared between subsequent words. To maintain participants’ attention on the reading comprehension task, when the critical word appeared, the participants were instructed to press either the F key with the left hand or the J key with the right hand on a standard keyboard to indicate whether the sentence was correct. The association between response button (F or J) and response (correct or incorrect) was counterbalanced across participants in each group. Given that the dominant hand responds more rapidly than the non-dominant hand in motor tasks82,83, counterbalancing between the response button and response would control for the interference effects of handedness. Additionally, the counterbalancing design might avoid any lateralization of topographies associated with particular response button assignments. The trials were presented in pseudorandom order such that the same sentence type was maximally presented three times in a row. The trial scheme with detailed time sequence is shown in Fig. 3.
During the trials, background music was played throughout via Edifier R101V loudspeakers (Edifier Technology Co., Ltd., Beijing, China) for the high- and low-arousal music groups, while no music was played for the silence group. EEG recording started after practice trials and ended after completing the task. In addition, the arousal levels experienced by the participants were measured using a 6-point scale (from 1 = very calming to 6 = very exciting). Throughout the experiment, a total of 15 arousal ratings were obtained from each participant. To control for familiarity with the music and musical preference, following the ERP experiment, the participants were asked to report whether they had heard the music before and whether they liked it. All of the participants reported being unfamiliar with the music and liking it.
EEG recording and data analysis
EEG activity was continuously recorded from 64 Ag/AgCl scalp electrodes positioned on an elastic cap according to the international 10–20 system using the ActiveTwo Biosemi System (Biosemi, Amsterdam, Netherlands). The Common Mode Sense (CMS) active electrode and the Driven Right Leg (DRL) passive electrode were used as the reference and ground, respectively. EEG signals were recorded at a sampling rate of 2048 Hz.
The acquired EEG signals were preprocessed offline using the EEGLAB 14.1.2b84 and ERPLAB 7.0.0 toolboxes85 run in MATLAB 2016a (MathWorks Inc., Natick, MA, USA). To reduce the size of the data files, raw data were downsampled to 256 Hz. Data were bandpass filtered with cutoffs of 0.1 and 25 Hz. Subsequently, data with large artefacts caused by body movements, channel drifts and muscle activity were first rejected manually. The data were then referenced to the average activity of the left and right mastoid electrodes. Epochs were extracted ranging from 200 ms before to 1000 ms after the onset of the critical word with a baseline interval from -200 to 0 ms. Next, all of the segmented data were subjected to independent component analysis (ICA) to identify components associated with eye blinks and eye movements. Individual components were inspected, and components associated with eye blinks and eye movements were removed. Additionally, using an automatic moving window peak-to-peak function with a window width of 200 ms and a step size of 100 ms, epochs were rejected as artefacts when the voltage exceeded 100 μV. Based on the behavioural data, only trials with correct responses were finally averaged by each condition for each participant at each electrode. Specifically, for the correct sentence, the mean number of valid trials was 66.77 (SD = 6.30) in the silence condition, 63.23 (SD = 11.48) in the low-arousal music condition, and 60.23 (SD = 8.80) in the high-arousal music condition. For sentences with world knowledge violations, the mean number of valid trials was 67.38 (SD = 7.76) in the silence condition, 63.15 (SD = 12.37) in the low-arousal music condition, and 60.85 (SD = 10.07) in the high-arousal music condition. A non-parametric ANOVA-type statistic showed no significant difference in the mean number of valid trials across all conditions (ps > 0.05).
Based on visual inspection and previous studies of language comprehension86,87, a time window of 200–450 ms (i.e., N400 component) after the onset of the critical word was used for statistical analysis. We computed the mean amplitude values for nine regions of interest (ROIs): left anterior (FP1, AF7, AF3, F5, F3, and F1), left central (FC5, FC3, FC1, C5, C3, C1, CP5, CP3, and CP1), left posterior (P5, P3, P1, PO3, and O1), right anterior (FP2, AF8, AF4, F6, F4, and F2), right central (FC6, FC4, FC2, C6, C4, C2, CP6, CP4, and CP2), right posterior (P6, P4, P2, PO4, and O2), anterior midline (FPz, AFz, and Fz), central midline (FCz, Cz, and CPz), and posterior midline (Pz, POz, and Oz). When the data met the assumption of normality (Shapiro–Wilk test with p > 0.05), mixed ANOVA was performed with SPSS 25 (IBM SPSS Inc., Chicago, IL, USA), for the electrodes in the midline and lateral regions separately. Nevertheless, when the data deviated from normality (Shapiro–Wilk test with p < 0.05), the nonparametric ATS was conducted with the nparLD 2.188 package in R software, version 3.6.3. For the electrodes in the midline regions, group (high-arousal music, low-arousal music and silence) was considered as the between-subjects factor, whereas sentence type (correct vs. world knowledge violation) and anteriority (anterior, central and posterior) were considered as the within-subjects factors. For the electrodes in the lateral regions, hemisphere (left vs. right) was added as an additional within-subjects factor. In addition, to compare the magnitude of the N400 effect, statistical analysis was also performed for difference waves (subtracting the correct sentences from the sentences with world knowledge violations) in the midline and lateral regions separately. Only the significant effects containing the main experimental variables (group and sentence type) are reported. When any significant interactions were found, pairwise comparisons adjusted by Bonferroni correction were conducted. When the data violated the sphericity assumption, the degrees of freedom were adjusted with the Greenhouse–Geisser correction.
Dunifon, C. M., Rivera, S. & Robinson, C. W. Auditory stimuli automatically grab attention: Evidence from eye tracking and attentional manipulations. J. Exp. Psychol. Hum. Percept. Perform. 42, 1947–1958 (2016).
Robinson, C. W. & Sloutsky, V. M. When audition dominates vision: Evidence from cross-modal statistical learning. Exp. Psychol. 60, 113–121 (2013).
Sloutsky, V. M. & Napolitano, A. C. Is a picture worth a thousand words? Preference for auditory modality in young children. Child Dev. 74, 822–833 (2003).
Vasilev, M. R., Kirkby, J. A. & Angele, B. Auditory distraction during reading: A Bayesian meta-analysis of a continuing controversy. Perspect. Psychol. Sci. 13, 567–597 (2018).
Ellermeier, W., Kattner, F., Ueda, K., Doumoto, K. & Nakajima, Y. Memory disruption by irrelevant noise-vocoded speech: Effects of native language and the number of frequency bands. J. Acoust. Soc. Am. 138, 1561–1569 (2015).
Röer, J. P., Bell, R., Körner, U. & Buchner, A. A semantic mismatch effect on serial recall: Evidence for interlexical processing of irrelevant speech. J. Exp. Psychol. Learn. Mem. Cogn. 45, 515–525 (2018).
Halin, N., Marsh, J. E., Hellman, A., Hellström, I. & Sörqvist, P. A shield against distraction. J. Appl. Res. Mem. Cogn. 3, 31–36 (2014).
Bell, R., Buchner, A. & Mund, I. Age-related differences in irrelevant-speech effects. Psychol. Aging 23, 377–391 (2008).
Halin, N., Marsh, J. E., Haga, A., Holmgren, M. & Sörqvist, P. Effects of speech on proofreading: Can task-engagement manipulations shield against distraction?. J. Exp. Psychol. Appl. 20, 69–80 (2014).
Murphy, D. R., Bailey, H., Pearson, M. & Albert, G. The irrelevant speech effect among younger and older adults: The influence of background noises on reading comprehension. Exp. Aging Res. 44, 162–178 (2018).
Yan, G., Meng, Z., Liu, N., He, L. & Paterson, K. B. Effects of irrelevant background speech on eye movements during reading. Q. J. Exp. Psychol. 71, 1270–1275 (2018).
Sörqvist, P., Halin, N. & Hygge, S. Individual differences in susceptibility to the effects of speech on reading comprehension. Appl. Cogn. Psychol. 24, 67–76 (2010).
Marsh, J. E., Hughes, R. W. & Jones, D. M. Auditory distraction in semantic memory: A process-based approach. J. Mem. Lang. 58, 682–700 (2008).
Marsh, J. E., Hughes, R. W. & Jones, D. M. Interference by process, not content, determines semantic auditory distraction. Cognition 110, 23–38 (2009).
Dobbs, S., Furnham, A. & McClelland, A. The effect of background music and noise on the cognitive test performance of introverts and extraverts. Appl. Cogn. Psychol. 25, 307–313 (2011).
Ljung, R., Sörqvist, P. & Hygge, S. Effects of road traffic noise and irrelevant speech on children’s reading and mathematical performance. Noise Health 11, 194–198 (2009).
Furnham, A. & Strbac, L. Music is as distracting as noise: The differential distraction of background music and noise on the cognitive test performance of introverts and extraverts. Ergonomics 45, 203–217 (2002).
Kahneman, D. Attention and Effort (Prentice-Hall, Englewood Cliffs, 1973).
Bullack, A., Büdenbender, N., Roden, I. & Kreutz, G. Psychophysiological responses to ‘“happy”’ and ‘“sad”’ music: A replication study. Music Percept. 35, 502–517 (2018).
Cowen, A. S., Fang, X., Sauter, D. & Keltner, D. What music makes us feel: At least 13 dimensions organize subjective experiences associated with music across different cultures. Proc. Natl. Acad. Sci. USA 17, 1924–1934 (2020).
Khaghaninejad, M. S., Motlagh, H. S. & Chamacham, R. How does Mozart's music affect the reading comprehension of Iranian EFL learners of both genders? Int. J. Human. Cult. Stud. 489–499. https://www.researchgate.net/publication/303192685. Accessed Sept 2018 (2016).
Rashidi, N. & Faham, F. The effect of classical music on the reading comprehension of Iranian students. Theory Pract. Lang. Stud. 1, 74–82 (2011).
Su, Y. N. et al. How does Mozart’s music affect children’s reading? The evidence from learning anxiety and reading rates with e-books. J. Educ. Technol. Soc. 20, 101–112 (2017).
Kiger, D. M. Effects of music information load on a reading comprehension task. Percept. Mot. Ski. 69, 531–534 (1989).
Doyle, M. & Furnham, A. The distracting effects of music on the cognitive test performance of creative and non-creative individuals. Think Skills Creativ. 7, 1–7 (2012).
Chou, P. T. Attention drainage effect: How background music effects concentration in Taiwanese college students. J. Scholar. Teach. Learn. 10, 36–46 (2010).
Kallinen, K. Reading news from a pocket computer in a distracting environment: Effects of the tempo of background music. Comput. Hum. Behav. 18, 537–551 (2002).
Thompson, W. F., Schellenberg, E. G. & Letnic, A. K. Fast and loud background music disrupts reading comprehension. Psychol. Music 40, 700–708 (2012).
Avila, C., Furnham, A. & McClelland, A. The influence of distracting familiar vocal music on cognitive performance of introverts and extraverts. Psychol. Music 40, 84–93 (2011).
Kasiri, F. The impact of non-lyrical Iranian traditional music on reading comprehension performance of Iranian EFL learners: The case of gender, attitude, and familiarity. Proced. Soc. Behav. Sci. 199, 157–162 (2015).
Zhang, H., Miller, K., Cleveland, R. & Cortina, K. How listening to music affects reading: Evidence from eye tracking. J. Exp. Psychol. Learn. Mem. Cogn. 44, 1778–1791 (2018).
Perham, N. & Currie, H. Does listening to preferred music improve reading comprehension performance?. Appl. Cogn. Psychol. 28, 279–284 (2014).
Christopher, E. A. & Shelton, J. T. Individual differences in working memory predict the effect of music on student performance. J. Appl. Res. Mem. Cogn. 6, 167–173 (2017).
Anderson, S. A. & Fuller, G. B. Effect of music on reading comprehension of junior high school students. Sch. Psychol. 25, 178–187 (2010).
Johansson, R., Holmqvist, K., Mossberg, F. & Lindgren, M. Eye movements and reading comprehension while listening to preferred and non-preferred study music. Psychol. Music 40, 339–356 (2011).
Patston, L. L. M. & Tippett, L. J. The effect of background music on cognitive performance in musicians and nonmusicians. Music Percept. 29, 173–183 (2011).
Alexander, J., Firouzbakht, P., Glennon, L. & Lang, M. Effects of music type on reading comprehension performance and other physiological factors. J. Adv. Stud. Sci. https://jass.neuro.wisc.edu/2012/01. Accessed Sept 2018 (2012).
Proverbio, A. M. & De Benedetto, F. Auditory enhancement of visual memory encoding is driven by emotional content of the auditory material and mediated by superior frontal cortex. Biol. Psychol. 132, 164–175 (2018).
Burkhard, A., Elmer, S., Kara, D., Brauchli, C. & Jäncke, L. The effect of background music on inhibitory functions: An ERP study. Front. Hum. Neurosci. 12, 293 (2018).
Thompson, W. F., Schellenberg, E. G. & Husain, G. Arousal, mood, and the Mozart effect. Psychol. Sci. 12, 248–251 (2001).
Smith, A., Waters, B. & Jones, H. Effects of prior exposure to office noise and music on aspects of working memory. Noise Health 12, 235–243 (2010).
Nantais, K. M. & Schellenberg, E. G. The Mozart effect: An artifact of preference. Psychol. Sci. 10, 370–373 (1999).
Rauscher, F. H., Shaw, G. L. & Ky, K. N. Music and spatial task performance. Nature 365, 611 (1993).
Hirsch, E. D. Reading comprehension requires knowledge of words and the world. Am. Educ. 27, 10–22 (2003).
Best, R., Ozuru, Y., Floyd, R. G. & McNamara, D. S. Children’s text comprehension: Effects of genre, knowledge, and text cohesion. In Proceedings of the Seventh International Conference of the Learning Sciences (eds Barab, S. A. et al.) 37–42 (Erlbaum, Mahwah, 2006).
McNamara, D. S., Floyd, R. G., Best, R. & Louwerse, M. World knowledge driving young readers’ comprehension difficulties. In Proceedings of the Sixth International Conference on Learning Sciences (eds Yasmin, Y. B. et al.) 326–333 (Erlbaum, Mahwah, 2004).
Dudschig, C., Maienborn, C. & Kaup, B. Is there a difference between stripy journeys and stripy ladybirds? The N400 response to semantic and world-knowledge violations during sentence processing. Brain Cogn. 103, 38–49 (2016).
Xu, G., Zhong, W., Jin, H. & Mo, L. An ERP study on how subsequent sentence context can influence previous world knowledge constraints. J. Neurolinguist. 33, 96–103 (2015).
Nakano, H., Saron, C. & Swaab, T. Y. Speech and span: Working memory capacity impacts the use of animacy but not of world knowledge during spoken sentence comprehension. J. Cogn. Neurosci. 22, 2886–2898 (2010).
Hagoort, P., Hald, L., Bastiaansen, M. & Petersson, K. M. Integration of word meaning and world knowledge in language comprehension. Science 304, 438–441 (2004).
Kutas, M. & Federmeier, K. D. Thirty years and counting: Finding meaning in the N400 component of the event-related brain potential (ERP). Annu. Rev. Psychol. 62, 621–647 (2011).
Chwilla, D. J., Brown, C. M. & Hagoort, P. The N400 as a function of the level of processing. Psychophysiology 32, 274–285 (1995).
Brown, C. & Hagoort, P. The processing nature of the N400: Evidence from masked priming. J. Cogn. Neurosci. 5, 34–44 (1993).
Holcomb, P. J. Semantic priming and stimulus degradation: Implications for the role of the N400 in language processing. Psychophysiology 30, 47–61 (1993).
Gold, R., Faust, M. & Goldstein, A. Semantic integration during metaphor comprehension in Asperger syndrome. Brain Lang. 113, 124–134 (2010).
Aldunate, N., López, V., Cornejo, C., Moënne-Loccoz, C. & Carré, D. Analytical and holistic approaches influence the semantic integration: Evidence from the N400 effect. Rev. Signos 52, 217–241 (2019).
Benau, E. M., Morris, J. & Couperus, J. W. Semantic processing in children and adults: Incongruity and the N400. J. Psycholinguist. Res. 40, 225–239 (2011).
Lau, E. F., Phillips, C. & Poeppel, D. A cortical network for semantics: (De) constructing the N400. Nat. Rev. Neurosci. 9, 920–933 (2008).
Husain, G., Thompson, W. F. & Schellenberg, E. F. Effects of musical tempo and mode on arousal, mood, and spatial abilities. Music Percept. 20, 151–171 (2002).
Schellenberg, E. G., Nakata, T., Hunter, P. G. & Tamoto, S. Exposure to music and cognitive performance: Tests of children and adults. Psychol. Music 35, 5–19 (2007).
Alley, T. R. & Greene, M. E. The relative and perceived impact of irrelevant speech, vocal music and non-vocal music on working memory. Curr. Psychol. 27, 277–289 (2008).
Gaspelin, N., Ruthruff, E., Jung, K., Cosman, J. D. & Vecera, S. P. Does low perceptual load enable capture by colour singletons?. J. Cogn. Psychol. 24, 735–750 (2012).
Hasegawa, K. The size-value compatibility effect. Sci. Rep. 10, 5383 (2020).
Spinelli, E., Meunier, F. & Seigneuric, A. Spoken word recognition with gender-marked context. Ment. Lex. 1, 277–297 (2006).
Kutas, M. & Federmeier, K. D. Electrophysiology reveals semantic memory use in language comprehension. Trends Cogn. Sci. 4, 463–470 (2000).
Kutas, M. & Hillyard, S. A. Reading senseless sentences: Brain potentials reflect semantic incongruity. Science 207, 203–205 (1980).
Dudschig, C., Mackenzie, I. G., Maienborn, C., Kaup, B. & Leuthold, H. Negation and the N400: Investigating temporal aspects of negation integration using semantic and world-knowledge violations. Lang. Cogn. Neurosci. 34, 309–319 (2019).
Jin, H. et al. The time course of world knowledge integration in sentence comprehension. Acta Psychol. Sin. 41, 565–571 (2009).
Martin, C. D., Garcia, X., Breton, A., Thierry, G. & Costa, A. From literal meaning to veracity in two hundred milliseconds. Front. Hum. Neurosci. 8, 40 (2014).
Shek, V. & Schubert, E. Background music at work: A literature review and some hypotheses. In Proceedings of the Second International Conference on Music Communication Science (eds Stevens, C. et al.) 87–91 (HCSNet, University of Western Sydney, Sydney, 2009).
Jäncke, L. & Sandmann, P. Music listening while you learn: No influence of background music on verbal learning. Behav. Brain Funct. 6, 3 (2010).
Lehmann, J. A. M. & Seufert, T. The influence of background music on learning in the light of different theoretical perspectives and the role of working memory capacity. Front. Psychol. 8, 1902 (2017).
Proverbio, A. M. et al. The effect of background music on episodic memory and autonomic responses: Listening to emotionally touching music enhances facial memory capacity. Sci. Rep. 5, 15219 (2015).
Hald, L. A., Steenbeek-Planting, E. G. & Hagoort, P. The interaction of discourse context and world knowledge in online sentence comprehension. Evidence from the N400. Brain Res. 1146, 210–218 (2007).
Metzner, P., von der Malsburg, T., Vasishth, S. & Rösler, F. Brain responses to world knowledge violations: A comparison of stimulus- and fixation-triggered event-related potentials and neural oscillations. J. Cogn. Neurosci. 27, 1017–1028 (2015).
Krumhansl, C. L. & Kessler, E. J. Tracing the dynamic changes in perceived tonal organization in a spatial representation of musical keys. Psychol. Rev. 89, 334–368 (1982).
Koelsch, S., Gunter, T., Friederici, A. D. & Schröger, E. Brain indices of music processing: “Nonmusicians” are musical. J. Cogn. Neurosci. 12, 520–541 (2000).
Jiang, C., Liu, F. & Thompson, W. F. Impaired explicit processing of musical syntax and tonality in a group of Mandarin-speaking congenital amusics. Music Percept. 33, 401–413 (2016).
Zhou, L., Liu, F., Jiang, J., Jiang, H. & Jiang, C. Abnormal neural responses to harmonic syntactic structures in congenital amusia. Psychophysiology 56, e13394 (2019).
Faul, F., Erdfelder, E., Lang, A. & Buchner, A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175–191 (2007).
Etaugh, C. & Ptasnik, P. Effects of studying to music and post-study relaxation on reading comprehension. Percept. Mot. Skills 55, 141–142 (1982).
Peters, M. & Durding, B. Left-handers and right-handers compared on a motor task. J. Mot. Behav. 11, 103–111 (1979).
Todor, J. I., Kyprie, P. M. & Price, H. L. Lateral asymmetries in arm, wrist and finger movements. Cortex 18, 515–523 (1983).
Delorme, A. & Makeig, S. EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–21 (2004).
Lopez Calderon, J. & Luck, S. J. ERPLAB: An open-source toolbox for the analysis of event-related potentials. Front. Hum Neurosci. 8, 213 (2014).
Weber-Fox, C. Neural systems for sentence processing in stuttering. J. Speech Lang. Hear. Res. 44, 814–825 (2001).
Iakimova, G. et al. Behavioral measures and event-related potentials reveal different aspects of sentence processing and comprehension in patients with major depression. J. Affect. Disord. 113, 188–194 (2008).
Noguchi, K., Gel, Y. R., Brunner, E. & Konietschke, F. nparLD: An R software package for the nonparametric analysis of longitudinal data in factorial experiments. J. Stat. Softw. 50, 20 (2012).
This work was supported by a grant from the National Natural Science Foundation of China (31470972).
The authors declare no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Du, M., Jiang, J., Li, Z. et al. The effects of background music on neural responses during reading comprehension. Sci Rep 10, 18651 (2020). https://doi.org/10.1038/s41598-020-75623-3