Clinical Neurophysiology
Volume 120, Issue 1 , Pages 41-50, January 2009

The effect of mastication on human cognitive processing: A study using event-related potentials

  • Kiwako Sakamoto

      Affiliations

    • Department of Integrative Physiology, National Institute for Physiological Sciences, Myodaiji, Okazaki 444-8585, Japan
    • Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies, Hayama, Kanagawa, Japan
    • Corresponding Author InformationCorresponding author. Address: Department of Integrative Physiology, National Institute for Physiological Sciences, Myodaiji, Okazaki 444-8585, Japan. Tel.: +81 564 55 7810; fax: +81 564 52 7913.
    • ,
  • Hiroki Nakata

      Affiliations

    • Department of Integrative Physiology, National Institute for Physiological Sciences, Myodaiji, Okazaki 444-8585, Japan
    • School of Health Sciences, Nagoya University, Nagoya, Japan
    • ,
  • Ryusuke Kakigi

      Affiliations

    • Department of Integrative Physiology, National Institute for Physiological Sciences, Myodaiji, Okazaki 444-8585, Japan
    • Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies, Hayama, Kanagawa, Japan

Accepted 1 October 2008.

Article Outline

Abstract 

Objective

The purpose of the present study was to clarify the effect of mastication on cognitive processing using reaction time (RT) and event-related potentials (ERPs).

Methods

The two experiments consisted of two conditions, Mastication (chewing gum) and Control (relaxing without chewing gum) in Experiment 1, and Jaw Movement (opening and closing the jaw) and Finger Tapping (tapping the right index finger) in Experiment 2. The subjects performed four sessions of an auditory oddball paradigm. RT and ERPs were recorded in these four sessions, Pre (before chewing), and Post 1, Post 2 and Post 3 (after chewing).

Results

In Mastication for RT and the peak latencies of P300 and N100, the values were significantly longer in Pre than in Post 2 or Post 3. By contrast, in Control, Jaw Movement, and Finger Tapping, they were almost identical among sessions or significantly shorter in Pre than in Post 2 or Post 3.

Conclusions

Mastication influences cognitive processing time as reflected by RT and the latency of ERP waveforms.

Significance

This is the first study investigating the effect of mastication on the central nervous system using event-related potentials.

Keywords: Chewing, P300, P3, P3b, N100, N1, Electroencephalography

 

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1. Introduction 

Mastication consists of the activities of the lower jaw and masticatory muscles concerned with rhythmic and voluntary movement. The motor command for this sequential rhythmic movement is generated by a neural population in the central pattern generator (CPG) of the brainstem (Nakamura and Katakura, 1995, Nakamura et al., 2004). Recent neuroimaging studies using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) in humans have reported that several regions of the brain are activated during mastication, including the primary somatosensory cortex (SI), primary motor cortex (MI), supplementary motor area (SMA), premotor area (PM), prefrontal cortex (PFC), insula, posterior parietal cortex (PPC), thalamus, striatum, and cerebellum (Momose et al., 1997, Onozuka et al., 2002, Onozuka et al., 2003, Tamura et al., 2003, Takada and Miyamoto, 2004, Takahashi et al., 2007). Thus, these studies suggest that mastication is a complicated movement generated from a neural population in the brainstem and a neural network including several brain regions.

Some studies have reported an effect of mastication on psychological tests relating to arousal (Endo et al., 1982, Nageishi et al., 1993, Otomaru et al., 2003), energy expenditure and heart rate (Suzuki et al., 1992, Suzuki et al., 1994), choice reaction time (Chu, 1994), and working memory (Wilkinson et al., 2002, Baker et al., 2004, Stephens and Tunney, 2004, Hirano et al., 2008). Several neurophysiological studies have also tried to clarify the effect by recording background electroencephalography (EEG) activity (Endo et al., 1982, Masumoto et al., 1999, Morinushi et al., 2000); however, there is contradictory evidence showing no significant change in memory (Tucha et al., 2004, Johnson and Miles, 2007), and background EEG (Suzuki et al., 1989, Masumoto et al., 1998) after gum-chewing. Therefore, the effect of mastication has been a matter of debate, and it is not well known why mastication modulates cognitive performances and background EEG, even though a significant effect has been found. Consequently, objective methods and indexes are needed to investigate the effect in detail, instead of psychological and working memory tests.

Based on the research background, the present study used event-related potentials (ERPs) obtained by time-locked averaging EEG to evaluate the effect of mastication on the central nervous system (CNS). In human ERP studies, P300 or P3b is one of the most widely studied components with a parietal distribution on the scalp, and has been linked to the cognitive processes of context updating, context closure, and event-categorization (Donchin and Coles, 1988, Kok, 2001, Bledowski et al., 2004). P300 occurs 300–600ms after a target stimulus in oddball paradigms, wherein two stimuli are presented in a random series with one of the two, that to which the subject is instructed to respond, occurring relatively infrequently (Jeon and Polich, 2001). The amplitude of P300 is proportional to the amount of attentional resources devoted to a given task (Wickens et al., 1983, Kramer and Strayer, 1988, Schubert et al., 1998), whereas the latency is considered a measure of stimulus classification speed or stimulus evaluation time (Kutas et al., 1977) and is generally unrelated to response selection processes (McCarthy and Donchin, 1981, Pfefferbaum et al., 1983). To our knowledge, no study has examined the effects of mastication on P300. Therefore, we aimed to evaluate whether the peak latency and/or amplitude of this component are influenced by mastication.

In addition to P300, we focused on an earlier negative component, N100 or N1, which has been recorded just prior to P300 during auditory oddball paradigms. N100 has a frontocentral distribution on the scalp, and is detected approximately 100ms after auditory stimulus onset, indicating neural activities relating to auditory processing. Thus, we also focused on the peak latency and amplitude of N100 as an index of auditory processing.

Here we show a significant effect of mastication on ERPs waveforms.

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2. Methods 

2.1. Subjects 

Eleven normal right-handed subjects (eight males and three females; mean age 30.9years, range 24–42) participated in Experiment 1, and nine normal right-handed subjects (eight males and one female; mean age 30.6years, range 25–43) participated in Experiment 2. None of the subjects had a history of neurological or psychiatric disorder. Seven subjects joined both experiments. Informed consent was obtained from all subjects, but they were not told the aim of these experiments to avoid the effect of information and the intended bias on all data. The study was approved by the Ethics Committee of the National Institute for Physiological Sciences, Okazaki, Japan.

2.2. Experiment 1 

The experiment consisted of two conditions, Mastication and Control, each performed on a different day. Half of the subjects began with the Mastication condition and half with the Control condition. The Mastication condition comprised four sessions of recordings at different times: Pre, Post 1, Post 2, and Post 3. In each session, the subjects performed an auditory oddball paradigm for approximately five minutes. After one session, the subjects were asked to chew gum for five minutes at a relaxed self-pace. In total, there were three gum-chewing intervals. The Control condition included the same four sessions (Pre, Post 1, Post 2, and Post 3), but the subjects were instructed to relax without chewing gum in each interval (see Fig. 1). The present study used Post 2 and Post 3 as well as Post 1 for two reasons. First, indeed, previous studies investigating background EEG compared a control Pre recording with only a Post recording after 3-min gum-chewing (Masumoto et al., 1998, Masumoto et al., 1999, Morinushi et al., 2000), but we wondered whether the effect of mastication was found in Post 1 after only 5-min mastication. Second, if there was a real effect, we wanted to investigate how the effect changed with repetitive sessions. For Mastication, a special gum base that was odorless and tasteless was prepared (CAT21 Chewing Pellet, NAMITEC Co., Ltd., Osaka, Japan). This gum was made of polyvinyl acetate, wax, and polyisobutylene, based on the Japan food hygiene law. The auditory stimulation was an auditory pure tone (55dB sound pressure level, 500ms duration, 10ms rise time, 10ms fall time), presented binaurally through headphones. The probability of the stimulus for target tones (2000Hz) and standard tones (1000Hz) was 20% and 80%, respectively, in a random series. The interstimulus interval was 2s. The subjects had to respond by pushing a button with their right thumb as quickly as possible only after the presentation of a target stimulus. During the recordings, the subjects were instructed to keep their eyes open and look at a small fixation point positioned in front of them at a distance of approximately 1m. One session comprised 150 epochs of stimulation, which included 30 epochs for the target stimuli and 120 epochs for the standard stimuli. The practice session consisted of 10 stimuli before the recordings.

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  • Fig. 1. 

    Protocol for the Mastication and Control conditions in Experiment 1, and the Jaw Movement and Finger Tapping conditions in Experiment 2. In each condition, the subjects performed four oddball sessions. In Mastication, the subjects were asked to chew a gum base that was odorless and tasteless during the intervals between sessions for five minutes. In Control, the subjects were instructed to relax without gum-chewing during the intervals. In Jaw Movement, the subjects were asked to open and close their jaw during the intervals between sessions for five minutes. In Finger Tapping, the subjects were instructed to tap their right index finger during the intervals.

2.3. Experiment 2 

The experiment consisted of two conditions, Jaw Movement and Finger Tapping, each performed on a different day from Experiment 1. Half of the subjects began with Jaw Movement and half with Finger Tapping condition. The procedure of this experiment was the same as Experiment 1. In Jaw Movement, the subjects were asked to open and close their jaw at their own pace during each interval (Fig. 1), and were asked not to bite to avoid the effect of tactile afferent information. In Finger Tapping, the subjects were instructed to tap their right index finger at their own relaxed pace during each interval (Fig. 1). Tasks involving repetitive muscle activity or movement of other body parts would be needed to clarify whether the modulation of ERPs waveforms was specific to mastication. In addition, gum-chewing is a fairly complex behavior, including rhythmic movement of the jaw muscle, tactile sensations of the several organs in the oral cavity, tongue movement, and secretion of saliva. Each of these components may contribute differentially to brain activation; therefore, we performed rhythmic jaw movement without an object in the mouth during the resting interval.

2.4. EEG recordings and analysis 

EEGs were recorded with Ag/AgCl disk electrodes placed on the scalp at Fz, Cz, Pz, C3, and C4, according to the International 10–20 System. Each scalp electrode was referenced to linked earlobes. The ground electrode was placed at Fpz. To eliminate eye movements or blinks exceeding 100μV, an electro-oculogram (EOG) was recorded bipolarly with a pair of electrodes placed 2cm lateral to the lateral canthus of the right eye and 2cm above the upper edge of the right orbit. The impedance was maintained at less than 5kΩ. All of the EEG signals were collected on a signal processor (Neuropack MEB-2200 system, Nihon-Kohden, Tokyo, Japan). The analysis epoch for ERPs was 1000ms including a prestimulus baseline period of 100ms. The bandpass filter was set at 0.1–50Hz and the sampling rate was 1000Hz. No digital filter was applied off-line. The peak amplitude and latency of the N100 and P300 components were measured at 70–135ms and 260–500ms, respectively. The amplitudes were measured baseline-to-peak. In the standard stimuli of the oddball paradigm, we analyzed only N100, because of the absence of the P300 component. When measuring the peak latency and amplitude of the P300 component, some subjects showed double peaks of P300. In this case, we determined the value at the larger peak of the waveform than the smaller peak.

For the analysis of N100 and P300, the data on peak amplitude and latency were subjected to analyses of variances (ANOVAs) with repeated measures using as within-subjects factors, Condition (Mastication vs. Control), Session (Pre, Post 1, Post 2, and Post 3), and Electrode (Fz, Cz, Pz, C3, and C4) in Experiment 1. The same ANOVA was also performed using within-subjects factors, Condition (Jaw Movement vs. Finger Tapping), Session, and Electrode in Experiment 2. The behavioral data on the mean RT were subjected to a two-way ANOVA with repeated measures using as within-subjects factors, Condition and Session. For all repeated measures factors with more than two levels, it was tested whether Mauchly’s sphericity assumption was violated. If the result of Mauchly’s test was significant and the assumption of sphericity was violated, the Greenhouse–Geisser adjustment was used to correct the sphericity by altering the degrees of freedom using a correction coefficient epsilon. When significant effects were identified, the Bonferroni post-hoc multiple comparison was adjusted to identify specific differences among conditions. Statistical significance was set at p<0.05.

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3. Results 

3.1. Behavioral data in Experiment 1 

Upper figures of Fig. 2 show the mean RT with standard error in Experiment 1. For the mean RT, a significant effect of Condition-Session was found (F(3,30)=12.139, p<0.001, ε=0.674). This interaction indicated that there was a difference of the mean RT between the Mastication and Control conditions with repeated sessions. Post-hoc testing revealed the RT in Pre for Mastication to be significantly longer than that in Post 1, Post 2, and Post 3 (p<0.001, respectively), and the RT in Post 1 for Control to be significantly shorter than that in Post 3 (p<0.05), with a stronger tendency in Pre than in Post 3 (p=0.057). The mean RT in Mastication was 284.3 (SE ±17.9)ms at Pre, 245.4 (±12.1)ms at Post 1, 241.7 (±10.7)ms at Post 2, and 235.9ms (±9.9)ms at Post 3. The mean RT in Control was 260.7 (±13.5)ms at Pre, 254.6 (±17.9)ms at Post 1, 263.9 (±19.4)ms at Post 2, and 288.0ms (±23.2)ms at Post 3.

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  • Fig. 2. 

    Upper figures: (A) Mean reaction time (RT) for the Mastication and Control conditions in Experiment 1. (B) The value of differences between the pre and post conditions. The value for Pre is set at 0ms. Black circles indicate the RT in Mastication, and gray squares show the RT in Control. Bars indicate standard errors. A significant effect of Condition–Session was found. Lower figures: (A) Mean RT in the Jaw Movement and Finger Tapping conditions in Experiment 2. (B) The value of differences between pre and post conditions. White circles indicate the RT in Jaw Movement, and black squares show the RT in Finger Tapping. There was a significant main effect of Session.

3.2. ERP data in Experiment 1 

Fig. 3, Fig. 4 show the grand-averaged ERP waveforms after target stimuli in Experiment 1. Clear waveforms were recorded from all subjects in all sessions, thus the P300 and N100 components were determined at all electrodes.

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  • Fig. 3. 

    Grand-averaged waveforms of P300 at Pz for the Mastication and Control conditions in Experiment 1. Figures on the left show the waveforms in Mastication, with black triangles indicating the peak latency of P300. The dotted-line indicates the peak latency of P300 in Pre. of note, the peak clearly occurs earlier in Post 3 than in Pre. Figures on the right show the waveforms in Control, with gray triangles indicating the peak latency of P300. Again the dotted-line indicates the peak latency of P300 in Pre. The peak is almost the same among sessions or a little longer in the Post sessions than in Pre.

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  • Fig. 4. 

    Grand-averaged waveforms of the target N100 component at Cz in Mastication and Control across all subjects. Figures on the left show the waveforms in Mastication, with black triangles indicating the peak latency of N100. The dotted-line indicates the peak latency of N100 in Pre. of note, the latency is clearly shorter in the Post sessions than in Pre. Figures on the right show the waveforms in Control, with gray triangles indicating the peak latency of N100. Again the dotted-line indicates the peak latency of N100 in Pre. The peak latencies are similar among sessions.

The ANOVAs for the peak latency of P300 revealed a significant effect of Condition-Session (F(3,30)=6.410, p<0.01, ε=0.593), indicating a difference between Mastication and Control with repeated sessions. The Post-hoc test in Mastication with collapsing the factor of Electrode demonstrated the peak latency of P300 to be significantly shorter in Post 3 than in Pre and Post 1 (p<0.01, and p<0.05, respectively). Post-hoc test in Control with collapsing the factor of Electrode did not show significant differences among sessions (Fig. 5).

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  • Fig. 5. 

    Upper figures show the mean peak latency of P300 at Pz and Cz in Experiment 1. Black circles and gray squares demonstrate Mastication and Control, respectively. The value was set at 0ms, based on the Pre session. Bars indicate standard errors. The ANOVAs for the peak latency of P300 revealed a significant effect of Condition–Session. Lower figures show the mean peak latency of target N100 at Fz and Cz. ANOVAs for the peak latency of target N100 also revealed a significant effect of Condition–Session.

The ANOVAs for the peak amplitude of P300 revealed a significant main effect of Electrode (F(4,40)=14.888, p<0.001, ε=0.607). Post-hoc test with collapsing factors of Condition and Session revealed that the amplitude of P300 was significantly larger at Pz than at Fz and C3 (p<0.001, respectively), Cz than Fz and C3 (p<0.001 and 0.01, respectively), and C4 than Fz and C3 (p<0.01 and 0.061 (strong tendency), respectively). Consistent with many previous studies, the peak amplitude of P300 was largest at Pz (Table 1).

Table 1. The peak amplitudes on N100 and P300 components during each condition in Experiment 1.
N100 (μV)P300 (μV)
PrePost 1Post 2Post 3PrePost 1Post 2Post 3
Gum
Fz−7.0 (0.8)−6.8 (0.9)−7.7 (0.8)−7.3 (0.9)7.9 (0.6)9.5 (0.8)8.1 (1.0)8.2 (0.9)
Cz−6.1 (0.8)−5.2 (0.7)−5.8 (0.6)−5.6 (0.8)10.8 (1.2)13.8 (1.6)12.0 (1.6)11.9 (1.8)
Pz−3.3 (0.7)−2.9 (0.6)−2.5 (0.5)−3.1 (0.8)12.9 (1.2)14.8 (1.7)13.0 (1.2)12.7 (1.5)
C3−6.4 (0.7)−5.7 (0.8)−6.1 (0.8)−5.7 (0.8)8.4 (1.1)10.1 (1.3)9.1 (1.2)8.6 (1.4)
C4−4.7 (0.6)−4.5 (0.5)−4.9 (0.5)−4.6 (0.7)10.2 (1.1)12.7 (1.2)10.9 (1.4)10.8 (1.3)

Control
Fz−7.0 (0.6)−7.4 (1.0)−6.5 (0.8)−5.6 (1.4)7.8 (1.0)7.2 (1.0)6.6 (0.8)5.9 (0.8)
Cz−5.3 (0.7)−5.8 (0.9)−5.4 (0.6)−5.7 (0.7)11.3 (1.6)11.3 (1.7)10.0 (1.1)9.0 (0.9)
Pz−2.4 (0.6)−3.3 (0.6)−2.9 (0.6)−3.5 (0.8)12.5 (1.6)12.7 (1.5)11.6 (1.3)10.4 (0.6)
C3−5.8 (0.6)−6.0 (0.8)−5.5 (0.7)−5.5 (0.6)8.9 (1.4)8.3 (1.3)7.6 (1.1)7.1 (0.9)
C4−5.1 (0.7)−5.8 (0.9)−4.9 (0.6)−5.2 (0.6)10.5 (1.2)10.8 (1.4)10.1 (1.0)9.4 (0.9)

Data are expressed as means (standard error, SE).

Then, we performed ANOVAs for the peak latency of N100 in target trials. The analysis revealed a significant effect of Condition-Session (F(3,30)=2.923, p<0.05, ε=0.813), indicating a difference in the peak latency of N100 between Mastication and Control with repeated sessions. Post-hoc test in Mastication with collapsing the factor of Electrode demonstrated the peak latency of N100 to be significantly shorter in Post 2 and Post 3 than in Pre (p<0.05, respectively). Post-hoc test in Control did not demonstrate significant differences among sessions (Fig. 4, Fig. 5).

ANOVAs for the peak amplitude of N100 in target trials showed a significant main effect of Electrode (F(4,40)=18.365, p<0.001, ε=0.479). Post hoc procedure with collapsing factors of Condition and Session revealed that the amplitude of target N100 was significantly larger at Fz than at Pz and C4 (p<0.001 and 0.01, respectively), Cz than Pz (p<0.001), C3 than Pz (p< 0.001), and C4 than Pz (p<0.01). These results indicate that the amplitude of N100 in target trials is largest at Fz (Table 1).

In ANOVAs for the peak latency of N100 in standard trials, there were no significant main effects or interactions. The ANOVAs for the peak amplitude of standard N100 revealed a significant main effect of Electrode (F(4,40)=25.931, p<0.001, ε=0.484). Post-hoc test with collapsing factors of Condition and Session demonstrated the amplitude of N100 to be significantly larger at Fz than at Pz, C3, and C4 (p<0.001, p<0.01 and 0.01, respectively), Cz than Pz and C4 (p<0.001 and 0.01, respectively), C3 than Pz (p<0.001), and C4 than Pz (p<0.01) (Supplementary Table S1).

3.3. Behavioral data in Experiment 2 

Lower figures of Fig. 2 show the mean RT with standard error in Experiment 2. For the mean RT, a significant main effect of Session was found (F(3,24)=5.391, p<0.01, ε=0.673). Post-hoc test with collapsing the factor of Condition revealed that the RT was significantly shorter in Pre than in Post 3 (p<0.01). The mean RT in Jaw Movement was 304.1 (SE±46.0)ms at Pre, 352.0 (±78.3)ms at Post 1, 332.4 (±59.8)ms at Post 2, and 430.7ms (±93.4)ms at Post 3. The mean RT in Finger Tapping was 278.3 (±44.4)ms at Pre, 335.4 (±55.9)ms at Post 1, 320.1 (±50.5)ms at Post 2, and 320.3ms(±41.0)ms at Post 3.

3.4. ERP data in Experiment 2 

Fig. 6 and Supplementary Figure S1 show the grand-averaged ERP waveforms after target stimuli in Experiment 2. Clear waveforms were recorded from all subjects in all sessions, thus the P300 and N100 components were determined at all electrodes. In Fig. 6, the grand-averaged waveform of Finger Tapping at Post 3, two peaks were recorded, and it seemed that the amplitude of the first component was larger than that of the second component. To determine the morphology of the waveforms in more detail, we investigated the individual waveforms, because there was a possibility that the waveforms from some subjects affected the grand-averaged peak. Supplementary Figure S2 shows individual waveforms from all subjects. In this figure, subject 9 showed a larger amplitude at the first peak, indicated by a black triangle; however, this latency peaked very early, within 260ms after stimulation (249ms), which was out of definition to determine the peak latency and amplitude of P300 in the present study. Therefore, we identified the second peak as the true P300 shown by a gray triangle, which was consistent with the definition of previous P300 studies using an auditory oddball paradigm (Rogers et al., 1991, O’Donnell et al., 1993, Carrillo-de-la-Peña and Cadaveira, 2000, Kececi et al., 2006).

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  • Fig. 6. 

    Grand-averaged waveforms of P300 at Pz for the Jaw Movement and Finger Tapping conditions in Experiment 2. Figures on the left show the waveforms in Jaw Movement, with black triangles indicating the peak latency of P300. The dotted line indicates the peak latency of P300 in Pre. Figures on the right show the waveforms in Finger Tapping, with gray triangles indicating the peak latency of P300. Again, the dotted line indicates the peak latency of P300 in Pre.

ANOVAs for the peak latency of P300 revealed a significant main effect of Session (F(3,24)=6.950, p<0.01, ε=0.574). Post-hoc test with collapsing factors of Condition and Electrode revealed that the P300 latency was significantly shorter in Pre than in Post 2 and Post 3 (p<0.05 and 0.01, respectively) (Fig. 7). There were no other main effects and interactions of Condition, indicating that the difference between Jaw Movement and Finger Tapping did not exist in terms of the peak latency of P300.

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  • Fig. 7. 

    Upper figures show the mean peak latency of P300 at Pz and Cz in Experiment 2. White circles and black squares demonstrate Jaw Movement and Finger Tapping, respectively. The value was set at 0ms, based on the Pre session. Bars indicate standard errors. ANOVAs for the peak latency of P300 revealed a significant main effect of Session.

ANOVAs for the peak amplitude of P300 revealed a significant main effect of Session (F(3,24)=4.821, p<0.01, ε=0.732). Post-hoc test with collapsing factors of Condition and Electrode revealed that the P300 amplitude was significantly larger in Pre than in Post 2 and Post 3 (p<0.05, respectively). In addition, there was a significant main effect of Electrode (F(4,32)=10.435, p<0.01, ε=0.352). A post-hoc procedure with collapsing factors of Condition and Session demonstrated that the amplitude of P300 was significantly larger at Pz than at Fz and C3 (p<0.001 and 0.05, respectively), Cz than Fz (p<0.001), and C4 than Fz (P<0.05). There were no other main effects and interactions of Condition on the peak amplitude of P300 (Table 2).

Table 2. The peak amplitudes on N100 and P300 components during each condition in Experiment 2.
N100 (μV)P300 (μV)
PrePost 1Post 2Post 3PrePost 1Post 2Post 3
JM
Fz−7.2 (1.0)−7.4 (0.9)−7.9 (1.2)−6.3 (0.9)6.7 (0.6)3.7 (1.2)3.0 (1.4)3.4 (1.8)
Cz−5.8 (1.1)−6.0 (0.8)−6.5 (1.1)−4.8 (0.7)11.0 (1.4)8.8 (1.5)6.4 (1.4)7.5 (1.4)
Pz−3.3 (0.9)−3.5 (0.5)−4 (1.1)−2.8 (0.6)11.6 (1.3)10.6 (1.8)7.6 (1.4)8.2 (1.0)
C3−5.8 (1.1)−5.5 (0.6)−5.9 (1.0)−4.6 (0.7)8.5 (1.1)6.3 (1.1)5.3 (1.1)6.1 (1.1)
C4−5.3 (0.9)−5.0 (0.6)−5.3 (0.9)−3.9 (0.6)9.6 (0.9)8.3 (1.0)6.4 (1.2)6.8 (0.8)

FT
Fz−7.2 (1.1)−6.7 (0.9)−7.2 (1.0)−6.9 (0.6)6.6 (1.4)6.3 (1.0)5.6 (1.1)5.2 (1.3)
Cz−6.2 (1.1)−6.0 (1.0)−5.6 (1.1)−6.4 (0.8)10.6 (1.9)9.6 (1.2)8.8 (1.3)8.3 (1.5)
Pz−3.6 (0.8)−4.0 (1.0)−3.2 (0.8)−4.3 (0.8)11.7 (2.0)10.1 (1.2)9.7 (1.3)8.3 (1.4)
C3−5.6 (0.8)−5.5 (0.9)−5.6 (1.0)−5.6 (0.6)8.7 (1.6)8.1 (1.0)7.0 (1.1)6.9 (1.3)
C4−5.0 (1.0)−5.2 (0.7)−4.5 (0.8)−5.1 (0.8)9.5 (1.8)9.0 (1.3)8.2 (1.1)8.0 (1.2)

Data are expressed as means (standard error, SE). JM, Jaw Movement, FT, Finger Tapping.

ANOVAs for the peak latency of N100 in target trials revealed no significant main effect and interaction (Fig. 7).

ANOVAs for the peak amplitude of N100 in target trials showed a significant main effect of Electrode (F(4,32)=27.506, p<0.001, ε=0.527). Post-hoc procedure with collapsing factors of Condition and Session revealed that the amplitude of target N100 was significantly larger at Fz than at Cz, Pz, C3 and C4 (p<0.05, 0.001, 0.01, and 0.001, respectively), Cz than Pz (p<0.001), and C3 than Pz (p<0.001). There were no other main effects and interaction of Condition and Session on the peak amplitude of N100 (Table 2).

In ANOVAs for the peak latency of N100 in standard trials, there were no significant main effects or interactions. ANOVAs for the peak amplitude of standard N100 revealed a significant main effect of Electrode (F(4,32)=56.990, p<0.001, ε=0.620). Post-hoc test with collapsing factors of Condition and Session demonstrated the amplitude of N100 to be significantly larger at Fz than at Pz, C3 and C4 (p<0.001, respectively), Cz than Pz, C3 and C4 (p<0.001, 0.01, 0.001, respectively), C3 than Pz (p<0.001), and C4 than Pz (p<0.001) (Supplementary Table S2).

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4. Discussion 

Here we showed the effect of mastication on human cognitive processing using RT and ERPs. In Mastication of Experiment 1, RT was significantly longer in Pre than in Post 1, Post 2, and Post 3. The peak latency of P300 component showed that Pre and Post 1 were significantly longer than Post 3. The peak latency of N100 component also showed that Pre was significantly longer than Post 2 and Post 3. In both components, there was no difference between Pre and Post 1. By contrast, in Control of Experiment 1, RT was clearly shorter in Pre and Post 1 than in Post 3. There were no significant differences in P300 and N100 latencies among conditions and sessions. In Jaw Movement and Finger Tapping conditions of Experiment 2, RT was significantly shorter in Pre than that in Post 3. P300 latency was also significantly shorter in Pre than in Post 2 and Post 3. There were no significant differences in N100 latency among sessions. The P300 amplitude during Experiment 2 was significantly larger in Pre than in Post 2 and Post 3.

Several studies have shown that the act of mastication, even without calorie intake, has beneficial psychological effects, alters the state of arousal, and facilitates high scores on working memory tests (see Introduction). Masumoto and colleagues reported a change in the frequency of some components of the power spectrum in background EEGs after gum-chewing (Masumoto et al., 1999). They suggested that the chewing of gum had a relaxing effect on concentration. However, to our knowledge, no neurophysiological study has evaluated the effect of mastication on the CNS by recording ERPs.

In the Jaw Movement condition of Experiment 2, similar effects to the Mastication condition of Experiment 1 were not recorded on RT, P300, and N100. This result indicates that mastication with an object in the mouth is an important factor rather than rhythmic jaw movement alone. As mentioned in the Methods section, gum-chewing is a fairly complex behavior, including rhythmic movement of the jaw muscle, tactile sensations of several organs in the oral cavity, tongue movement, and secretion of saliva. Since we prepared a special gum base that was odorless and tasteless, factors of odor and taste could be ruled out; therefore, we inferred that the multiple factors elicited by gum-chewing affected the CNS. Takada and Miyamoto (2004), using fMRI, reported that the neurons in frontal and parietal cortices were more activated during gum-chewing than during sham gum-chewing. They suggested that this fronto-parietal network contributes to higher cognitive information processing. In the Finger Tapping of our Experiment 2, the subjects tapped their right index finger, but there were no significant effects on shortening RT, P300, and N100. This task, involving repetitive muscle activity or movement of other body parts, clarified that the modulation of ERPs waveforms was specific to mastication.

RT is an important measure in understanding sensorimotor performance in humans (Schmidt, 2000), and defined as the time from stimulus onset to the response, including components such as stimulus evaluation and response selection (Doucet and Stelmack, 1999). Therefore, our findings concerning the modulation of RT in Mastication indicate the sequential processing from stimulus input to response output to be sped up by the effect of mastication. On the other hand, RTs in Control, Jaw Movement, and Finger Tapping were clearly or significantly longer in Post 3 than in Pre (Fig. 2).

Many studies have demonstrated relationships between RT and the components of ERPs, such as P300, during discrimination tasks. The latency of P300 has been considered a measure of stimulus classification speed or stimulus evaluation time (Kutas et al., 1977, Kamijo et al., 2004). Some investigations have shown that there is a correlation between the peak latency of P300 and RT (Kutas et al., 1977, Roth et al., 1978, Ritter et al., 1979, Pfefferbaum et al., 1983), but P300 latency is generally unrelated to the response selection process (Donchin, 1981, McCarthy and Donchin, 1981, Pfefferbaum et al., 1983). This claim is based on the following observation. When stimulus evaluation demands are increased, both RT and the latency of P300 tend to increase, but when response-processing demands are increased, often only RT increases (Doucet and Stelmack, 1999, Kamijo et al., 2004). In the Mastication condition of the current study, the peak latency of P300 was significantly shorter in Post 3 than in Pre and Post 1 (Fig. 5). This finding indicates that just like RT, the latency of P300 can be affected by mastication. That is, mastication influences the speed of the stimulus evaluation in human cognitive processing.

By contrast, the P300 latency in Control did not show significant differences among sessions (Fig. 5), and that in Jaw Movement and Finger Tapping was significantly shorter in Pre than in Post 2 and Post 3 (Fig. 7). It is well recognized that the latency of P300 increases with task difficulty (Courchesne et al., 1977, Kutas et al., 1977, Ford et al., 1982). However, the present study used the same oddball paradigm during the recordings, and the subjects were not engaged in tasks requiring a high mental workload. Thus, the relationship between task difficulty and the delay in latency of P300 would be excluded in the present study, which was consistent with a previous study investigating effects of habituation. For instance, Polich (1989) showed a delay in the latency of P300 with repeated target-trial presentations. P300 has been theoretically interpreted as reflecting the context- and memory-updating process (Donchin, 1981). We considered that the delay of P300 latency elicited by repeated sessions in the present study indicated delay of these updating processes, and this result was related to the effect of habituation. Moreover, the peak amplitude of P300 in Experiment 2 was significantly larger in Pre than in Post 2 and Post 3 (Table 2), which was in line with some P300 studies reporting the effects of repetition and habituation (Polich, 1989, Lew and Polich, 1993, Carrillo-de-la-Peña and Garcı´a-Larrea, 1999). The mechanisms for the attenuation of P300 amplitude and the delay of P300 latency are not entirely clear, but these studies have suggested a decrease in arousal through successive trains of stimuli, a lower degree of cognitive involvement in the discrimination task across blocks, a decrease in the novelty or surprise value of the target with repeated testing, or a shift to automatic processing of targets as the task progresses. In addition, since the modulation of peak latency and amplitude of P300 by repeated sessions was larger in Jaw Movement and Finger Tapping than Control (Fig. 5, Fig. 7), we suspected the effect of fatigue as the reason for this particular phenomenon found in Experiment 2. Some previous studies reported that fatigue affected the peak amplitude and latency of P300 (Kaseda et al., 1998, Kuroiwa et al., 2002). For instance, Kuroiwa and colleagues showed that P300 was prolonged in latency and decreased in amplitude after sustained muscle contraction of left hand gripping for 20min (Kuroiwa et al., 2002). They suggested that fatigue, caused by peripheral muscle contraction for a long period, affected the CNS. In the present study, since Jaw Movement and Finger Tapping are not usual in daily life, compared to simple mastication with objects in the mouth, we assumed that fatigue from repeated sessions occurred in Experiment 2.

As for the peak latency of target N100 in Mastication, Post 2 and Post 3 were significantly shorter than Pre (Fig. 4, Fig. 5). On the other hand, for the peak latency of standard (non-target) N100, there was no effect of repeated presentation in Mastication (Supplementary Table S1). In addition, since this effect of the latency of target N100 was found only in Mastication, not in Control, Jaw Movement, and Finger Tapping, these findings suggest that mastication is effective on the latency of target N100. Indeed, it might be difficult to interpret the shortened latency of target N100 because the effect of mastication was not recorded on the amplitude of target N100. We speculated that target detection processing, which was included in target N100 and is needed to perform tasks by pushing a button, was shortened by the effect of mastication, while simple auditory processing was not affected. As reported in the literature, N100, commonly elicited by simple auditory stimuli, is a composite of multiple components (Näätänen and Picton, 1987) with generators around Heschl’s gyrus and the planum temporale (Reite et al., 1994, Altmann et al., 2008; Okamoto et al., 2007), the frontal cortex (Giard et al., 1994, Anderer et al., 1998, Atcherson et al., 2006), parietal regions (Knight et al., 1980), and anterior cingulate cortex (Tzourio et al., 1997). Atcherson and colleagues suggested that the presence of frontal sources was attributable to the use of cognitive and motor tasks. Some fMRI and PET studies investigating responsible regions for target detection of auditory oddball stimuli have reported neural activities in the frontal cortex, temporal gyrus, and parietal cortex, which were also related to generator mechanisms of N100 (Tzourio et al., 1997, Linden et al., 1999, Kiehl et al., 2001, Stevens et al., 2005). The present study can not predict which regions generating N100 were affected by mastication, but the data suggest that target detection processing in target stimuli of the oddball paradigm is influenced more than auditory processing.

As mentioned above, many studies have reported the effect of mastication in tests such as psychology, working memory, and background EEG, but the mechanisms of the effect are still unclear. Our results showed that this effect was also found in ERP waveform and there appeared to be several possible explanations.

A first hypothesis, which is already mentioned, is the effect of mastication with an object in the mouth.

The second is that mastication influences arousal. It is well established that the level of arousal is adjusted by the neural activity of the brainstem, as clarified by Moruzzi and Magoun (1949) who electrically stimulated the mesencephalic reticular formation of cats when EEGs signified a sleep-like state. On the onset of stimulation, there was a rapid and dramatic change of the EEG reflecting the awake brain (Moruzzi and Magoun, 1949; reviewed in Siegel, 2004). Based on their findings, the reticular formation in the brainstem and the neural pathways basic to the cortical arousal response became known as the ascending reticular activating system (ARAS). The ARAS has two pathways, dorsal and ventral. The dorsal pathway activates the cortex via the thalamus. The ventral pathway does so via the hypothalamus and basal forebrain. We consider the ARAS to be affected by mastication, because rhythmic mastication is generated by a central pattern generator (CPG) in the brainstem (Nakamura and Katakura, 1995, Nakamura et al., 2004, Yamada et al., 2005, Lund and Kolta, 2006). Many studies have reported that the CPG is driven not only by mastication, but also by cyclic movements such as stepping, walking, and pedaling (Dietz, 2003, Yuste et al., 2005, Zehr et al., 2007). After these exercises, ERP-based studies found that the peak latency and/or amplitude of P300 changed (Ploch and Kok, 1995, Nakamura et al., 1999, Yagi et al., 1999, Magnié et al., 2000, Hillman et al., 2003, Kamijo et al., 2004, Kamijo et al., 2007). Magnié et al., 2000, Yagi et al., 1999 suggest that the arousal level has an important influence on ERP waveforms. Indeed, this hypothesis might be rejected, since Jaw Movement without gum and Finger Tapping did not facilitate RT and P300 in Experiment 2; however, these movements are not usually performed in daily life, compared to gum-chewing, walking, and pedaling, even if Jaw Movement without gum and Finger Tapping are rhythmic movements. Thus, it may be possible that Jaw Movement without gum and Finger Tapping did not drive CPG precisely. If so, we can not reject this hypothesis at present, and further studies are needed to clarify this in more detail.

A third hypothesis is the effect of motor-related activities elicited by mastication. Repetitive electrical stimulation of a certain area of the cerebral cortex induces rhythmic jaw movements in many species, including monkeys (Lund and Lamarre, 1974, Huang et al., 1989), cats (Nakamura and Kubo, 1978, Iwata et al., 1985, Iwata et al., 1990), guinea pigs (Goldberg and Tal, 1978, Nozaki et al., 1986a, Nozaki et al., 1986b), and rabbits (Lund et al., 1984, Liu et al., 1993). Such rhythmic jaw movements with coordinated rhythmic movements of the tongue and facial organs as well as the secretion of saliva are known collecting as fictive mastication, and the cortical regions involved in these rhythmic jaw movements are termed the ‘cortical masticatory area (CMA)’ (Nakamura and Katakura, 1995, Yamada et al., 2005). At present, the descending input from the CMA is considered the major source generating and activating the masticatory CPG (Nakamura and Katakura, 1995). The CMA includes several cortical regions, such as the face MI, the face SI, the area immediately lateral to the face MI, and a deep area at the inner surface of the frontal operculum (Huang et al., 1989). Recent neuroimaging studies have also found a neural network involving the SMI, SMA, PM, PFC, insula, PPC, thalamus, striatum, and cerebellum (Momose et al., 1997, Onozuka et al., 2002, Onozuka et al., 2003, Tamura et al., 2003, Takada and Miyamoto, 2004, Takahashi et al., 2007). However, this hypothesis would be rejected, because Jaw Movement without gum in Experiment 2 did not facilitate RT and P300.

A fourth hypothesis is the effect of serotonergic (5-HT) neurons. Jacobs and Fornal (1993) reported that the activity of 5-HT neurons was enhanced by voluntary rhythmic movement, such as mastication, locomotion, and respiration, which was modeled in animals (Veasey et al., 1995). In addition, recent studies in humans have demonstrated a close relationship between the 5-HT induced by rhythmic movement and the effect on background EEG and the nociceptive flexion reflex (Fumoto et al., 2004, Mohri et al., 2005). Indeed, since our study did not assess the level of 5-HT during the present study, we could only provide a suggestion to explain the effect of mastication. Further studies might be needed to clarify this hypothesis.

Of course, there is a possibility that one or more of the above hypotheses may interact.

The relationship between cognitive function and mastication is still unknown in humans. A few studies have obtained data from the elderly (Miura et al., 2003, Weyant et al., 2004). Miura and colleagues (2003) showed that elderly aged over 65 with dementia had a significantly smaller number of teeth, occlusal area, and bite force, than normal elderly, suggesting that masticatory function in the elderly is associated with cognitive status. Weyant and colleagues also reported a significant association between limitations of oral function and depression. These reports may suggest a masticatory function in human cognitive processing.

In conclusion, the current study investigated the effect of mastication on RT, and P300 and N100 components. In the Mastication condition, RT and the peak latencies of P300 and N100 were shorter post-sessions, especially in Post 3, compared to Pre. In the Control, Jaw Movement, and Finger Tapping conditions, by contrast, these effects were not found. These findings indicate an effect of mastication on the CNS. However, the present study could not address directly the main cause of the effect. Further studies will be needed to clarify the precise mechanisms for the effect of mastication on the CNS.

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Acknowledgement 

We are very grateful to Mr. Y. Takeshima for technical support during this study.

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Appendix A. Supplementary data 

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  • Supplementary Figure S1. 

    Grand-averaged waveforms of the target N100 component at Cz in Jaw Movement and Finger Tapping across all subjects. Figures on the left show the waveforms in Jaw Movement, with black triangles indicating the peak latency of N100. The dotted line indicates the peak latency of N100 in Pre. Figures on the right show the waveforms in Finger Tapping, with gray triangles indicating the peak latency of N100. Again, the dotted line indicates the peak latency of N100 in Pre.

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  • Supplementary Figure S2. 

    Individual waveforms of Finger Tapping at Post 3 recorded at Pz. Gray triangles show the determined P300. In subject 9, a black triangle is shown, but this latency was out of definition for P300. The dotted line indicates stimulus onset.

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Table S1.

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Table S2.

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PII: S1388-2457(08)01004-3

doi:10.1016/j.clinph.2008.10.001

Clinical Neurophysiology
Volume 120, Issue 1 , Pages 41-50, January 2009

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