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Eating tools in hand activate the brain systems for eating action: A transcranial magnetic stimulation study Kaori Yamaguchi a,n, Kimihiro Nakamura a,b, Tatsuhide Oga c, Yasoichi Nakajima a a

National Rehabilitation Center for Persons with Disabilities, Research Institute, 4-1 Namiki, Tokorozawa 359-8555, Japan Human Brain Research Center, Kyoto University Graduate School of Medicine, 54 Shogoin, Kyoto 606-8507, Japan c Toranomon Hopital, Kajigaya Department of Rehabilitation ,1-3-1 Kajigaya, Takatsu-ku, Kawasaki, Kanagawa 213-8587, Japan b

art ic l e i nf o

a b s t r a c t

Article history: Received 26 December 2013 Received in revised form 19 April 2014 Accepted 4 May 2014

There is increasing neuroimaging evidence suggesting that visually presented tools automatically activate the human sensorimotor system coding learned motor actions relevant to the visual stimuli. Such crossmodal activation may reflect a general functional property of the human motor memory and thus can be operating in other, non-limb effector organs, such as the orofacial system involved in eating. In the present study, we predicted that somatosensory signals produced by eating tools in hand covertly activate the neuromuscular systems involved in eating action. In Experiments 1 and 2, we measured motor evoked response (MEP) of the masseter muscle in normal humans to examine the possible impact of tools in hand (chopsticks and scissors) on the neuromuscular systems during the observation of food stimuli. We found that eating tools (chopsticks) enhanced the masseter MEPs more greatly than other tools (scissors) during the visual recognition of food, although this covert change in motor excitability was not detectable at the behavioral level. In Experiment 3, we further observed that chopsticks overall increased MEPs more greatly than scissors and this tool-driven increase of MEPs was greater when participants viewed food stimuli than when they viewed non-food stimuli. A joint analysis of the three experiments confirmed a significant impact of eating tools on the masseter MEPs during food recognition. Taken together, these results suggest that eating tools in hand exert a category-specific impact on the neuromuscular system for eating. & 2014 Published by Elsevier Ltd.

Keywords: Eating action Masseter muscles Motor-evoked potential (MEP) Sensorimotor Transcranial magnetic stimulation (TMS)

1. Introduction Eating is the most fundamental biological requirement for all living organisms. For humans, in particular, eating is not a simple neuromuscular process but a more complex, learned behavior sensitive to other psychophysical and socio-cultural factors. Indeed, human eating behavior has been studied extensively in variously different disciplines of social, psychological and biomedical sciences. In the medical literature, for instance, most previous studies on eating have focused on the disease prevention and dietary intervention for cardiovascular and metabolic disorders (Clark et al., 2004; Eriksson et al., 2006; Eertmans et al., 2001), end-stage illness such as cancer and dementia (Manthorpe & Watson, 2003; Palecek et al., 2010) and bulimia or anorexia nervosa (Kaye, 2008; Schebendach et al., 2008). Recent neuroscience research has further shed light on neuroanatomical underpinnings of eating behavior, including the frontal insulaoperculum and orbitofrontal regions involved in gustatory semantics

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Corresponding author. Tel.: þ 81 4 2995 3100. E-mail address: [email protected] (K. Yamaguchi).

(Simmons, Martin & Barsalou, 2005; Barrós-Loscertales et al., 2012) and the hypothalamic region involved in food intake (Berthoud, 2002) and reward seeking (Harris, Wimmer & Aston-Jones, 2005). For humans, however, eating action is also a more complex sensorimotor process which relies on a skilled control of eating tools (e.g. forks and knives). That is, the typical act of eating in humans consists of a learned sequence of visuomotor processing, including the visual recognition of food, motoric control of eating tools and coordinated movements of cranial and pharyngeal muscles for mastication and swallowing. Notably, however, despite the large number of previous biomedical studies on eating, remarkably little is known about this neuromuscular mechanism involved in eating action. Given the fact that such complex coordinated sequence of visual and motor systems is generally acquired in early stages of life and habitually utilized across lifespan, it is likely that normal humans should have a strongly interconnected neuromuscular circuit involved in eating action (Cattaneo et al., 2007). Indeed, several lines of behavioral and neuropsychological evidences suggest that somatosensory stimulation induced by tools in hand activates the human motor system coding relevant actions. For instance, a behavioral study with “apraxic” patients

http://dx.doi.org/10.1016/j.neuropsychologia.2014.05.003 0028-3932/& 2014 Published by Elsevier Ltd.

Please cite this article as: Yamaguchi, K., et al. Eating tools in hand activate the brain systems for eating action: A transcranial magnetic stimulation study. Neuropsychologia (2014), http://dx.doi.org/10.1016/j.neuropsychologia.2014.05.003i

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has shown that motor planning dysfunction can be ameliorated when these patients hold real tools in hand (Goldenberg, Hentze & Hermsdö rfer, 2004). Similarly, clinical observations of severely demented patients with eating difficulty suggest that eating utensils in hand can facilitate voluntary eating action (Osborn & Marshall, 1993). These observations may generally concur with the well-known theory of “affordance”, whereby the implicit physical attributes of perceived objects constrain and interact with the observer's motor action and its planning (Derbyshire, Ellis & Tucker, 2006; Ranganathan, Lee, Brown & Newell, 2011; Sartori, Straulino & Castiello, 2011). At the neural level, many previous studies suggest that the visual observation of tools activates the frontoparietal regions storing the semantic and action-related knowledge of skilled tool use (Johnson-Frey, 2004; Vingerhoets, 2008; Chao et al., 1999; Beauchamp et al., 2002; Martin et al., 1996). Such cross-modal activation may reflect a general functional property of the human motor system, because the similar activation of learned motor memory is known to be triggered by external stimuli in various other modalities, including written numerals (Sato, Cattaneo, Rizzolatti & Gallese, 2007), musical sounds (Haueisen & Knö sche, 2001) and flavor (Parma, Ghirardello, Tirindelli & Castiello, 2011a; Parma et al., 2011b). In particular, food-related sensory stimuli can also exert a cross-modal effect on the motor system, since it has been shown that sniffing alimentary odorants increases the motor excitability of hand muscles during the observation of grasped food (Rossi et al., 2008). It is therefore possible that somatosensory stimulation from eating tools can covertly activate the neuromuscular systems involved in eating action. To our knowledge, however, no previous work has examined the hypothesized link between the human neuromuscular system and eating tools. In the present study, we tested this prediction using transcranial magnetic stimulation (TMS) in healthy humans. Specifically, we hypothesized that eating tools in hand should activate the neuromuscular system involved in eating action during the visual observation of food stimuli. We first examined whether tactile stimulation by eating tools can modulate motor evoked potentials (MEPs) from jaw muscles (masseter, see Section 2) while participants made semantic judgment about edible objects (Experiments 1 and 2). We observed that the masseter MEPs increased more greatly when participants held eating tools than when they held other hand-operated tools in their dominant hand. In Experiment 3, we further included food and non-food objects as visual stimuli to assess whether this modulatory effect by eating tools is specific to edible objects or rather it is generalized to other, non-edible objects. We confirmed that chopsticks overall increased MEPs more greatly than scissors and this tool-driven increase of MEPs was greater when participants viewed food stimuli than when they viewed non-food stimuli. Therefore, the observed increase in the motor excitability of the jaw muscles relies not on the direct motor activation by tactile input, but on the integrated longdistance signals via the visual object recognition system and hand sensorimotor system.

2. Material and methods 2.1. Participants A total of 36 native Japanese students (age range 23–28 years) participated in the present study (3 males and 9 females for Experiment 1, 4 males and 8 females for Experiment 2, and 3 males and 9 females for Experiment 3). All were righthanded on the Edinburgh Handedness Inventory (Oldfield, 1971) and had normal or corrected-to-normal vision. All of them habitually used chopsticks with their right hand and were on fasting for at least 1 h prior to the experiment. None had either a history of neurological or psychiatric disorders or any other contraindication to TMS (Wassermann, 1998; Rossi, Hallett, Rossini & Pascual-Leone, 2009). Written

informed consent was obtained from all participants prior to commencing the study in a manner approved by the institutional ethical committee. 2.2. Behavioral paradigm All behavioral paradigms were programmed using E-prime software (Psychology Software Tools, USA). For Experiment 1, we used a semantic categorization task with visually presented food stimuli. Stimulus materials included 100 color photographs of food, half representing hot food (e.g. noodles, fried chicken) and the other half cold or room-temperature food (e.g. salad, sushi). Normal Japanese adults can easily use chopsticks when eating these food items. Each trial consisted of a sequence of central fixation (1500 ms) and a target on the center of the screen (600 ms, Fig. 1A). Participants responded by key-press, either with their left index finger when target pictures represented hot food or with their left middle finger when otherwise. The experimental session consisted of eight blocks of 25 trials (total 200 trials). In each block lasting  75 s, participants held either chopsticks or scissors in their

Fig. 1. Behavioral paradigm. (A) Sequence of stimuli. Each trial consisted of central fixation (1500 ms) and a picture of food (600 ms) presented on the center of the screen. Participants made semantic judgment about food stimuli in Experiment 1 (hot vs. cold) and Experiment 2 (sweet vs. non-sweet) and oddball detection of non-food targets in Experiment 3 (see Section 2 for detail). (B) Experimental set-up. Participants are seated facing a PC monitor and responded to visual stimuli by keypress with their left fingers while holding either chopsticks or scissors in their right hand. Participants are unable to see the tools in their right hand placed behind a 40  30 cm2 blank white board throughout the experimental session. In each trial, a single-pulse TMS synchronized with the onset of visual targets is delivered to the face area of the left motor cortex. (C) Overall waveform of the masseter MEPs averaged across participants in Experiment 1. The overall magnitude (  3 mV) and latency (  7 ms) of the observed MEPs are highly compatible with the previously known pattern of the masseter MEPs (Guggisberg et al., 2001; Pearce et al., 2003; Jaberzadeh et al., 2008).

Please cite this article as: Yamaguchi, K., et al. Eating tools in hand activate the brain systems for eating action: A transcranial magnetic stimulation study. Neuropsychologia (2014), http://dx.doi.org/10.1016/j.neuropsychologia.2014.05.003i

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right hand (Fig. 1B). We chose chopsticks and scissors as tool stimuli, because both of them are commonly used in everyday life and strongly associated with specific hand postures and learned motor patterns. Participants received eight alternating blocks (i.e. four for chopsticks and four for scissors,), switching from one tool to another at the end of each block. Half of them started with chopsticks, while the other half with scissors. After 30–40 practice trials, each participant received 200 trials in which each of the 100 items appeared twice in a pseudo-random order. During the experimental session, participants were unable to see their right hand and the tools placed behind a blank white board, and were requested to respond as quickly and as accurately as possible while keeping their right hand at rest. In Experiment 2, we performed a different semantic categorization task using a separate set of 100 color photographs (half sweet/half non-sweet items). Most of these sweet items (e.g. cake, pudding) are eaten with other utensils than chopsticks, such as spoons and forks. In each trial, participants judged whether or not target pictures represented sweet food. All other experimental settings were the same as in Experiment 1. In Experiment 3, an oddball detection task was performed in a single session which comprised eight blocks of 29 trials each (232 trials in total). Visual stimulus materials consisted of 116 color photographs, i.e. 50 for food (e.g. noodle, grilled fish), 50 for common household non-food objects (e.g. clothes, brush), and 16 for plants (e.g. arranged flower, cactus in the pot). The food items are most commonly eaten with chopsticks. Using the same event sequence as Experiments 1 and 2, each of these images was presented twice in a random order throughout the session. Like in Experiments 1 and 2, participants responded by key-press, either with their left index finger when deviant targets (plants) appeared on the screen or with their left middle finger when otherwise. Due to a technical error, accuracy data were recorded only for eight participants in Experiments 1 and 2 and for ten participants in Experiment 3. 2.3. EMG/TMS procedure Participants were comfortably seated on the chair while facing a computer screen. Electromyographic (EMG) recording was performed with a Neuropack MEB2208 system (Nihon Kohden, Japan). EMG signal was band-pass filtered (30 Hz– 3 kHz, sampling rate 5 kHz), digitalized and stored for offline analysis. Surface EMG of the right masseter muscle was recorded using pairs of Ag–AgCl surface electrodes positioned at the muscle belly of masseter and at the level of lower border of the mandible. We elected to measure the masseter MEPs because (1) the masseter muscle has a large muscle belly over the jaw surface and because (2) its typical MEP waveform has been well documented in the literature (Guggisberg, Dubach, Hess, Wüthrich & Mathis, 2001; Pearce, Miles, Thompson & Nordstrom, 2003; Jaberzadeh, Sakuma, Zoghi, Miles & Nordstrom, 2008). The ground electrode was placed on the processus mastoideus. A single-pulse TMS was delivered using two MagStim200 magnetic stimulators connected to a 70 mm figure-of-eight coil through a BiStim module (Magstim, UK). The coil was kept tangential to the skull with the handle pointing backward parallel to the midline. Prior to starting the experimental session, a resting motor threshold from the right hand muscles was defined for each participant as the lowest intensity of stimulation that produced 5 MEPs out of 10 consecutive magnetic pulses with at least 50 μV of amplitude (Rossini et al., 1994). By reference to the previous TMS studies on the masseter muscle (Guggisberg et al., 2001; Pearce et al., 2003; Jaberzadeh et al., 2008), we then searched an optimal stimulation point for eliciting a typical MEP waveform individually for each participant. The coil was oriented at 120 relative to a fronto-dorsal line and positioned in an area 5–10 cm lateral to the vertex and 0–5 cm frontal to the bi-auricular line. The coil orientation is thought to determine the direction of the relevant inducing current and thus is critical for eliciting the masseter MEPs (Guggisberg et al., 2001). This procedure allowed us to deliver magnetic pulse to the masseter muscle area selectively while keeping a spatial separation from the hand muscles area that is 42 cm dorsal to the facial muscle area (Classen et al., 1998). A single optimal scalp spot for inducing the maximal MEPs in the right masseter muscle was then searched individually for each participant. In each trial, a single pulse synchronized to the onset of target images (Fig. 1) was applied to the face area of the left motor cortex at an intensity of 120% of the motor threshold. We expected that the precisely timed TMS would effectively interfere with the visuomotor neural system for eating action, because a single magnetic pulse at this stimulus intensity can suppress the local neuronal activity for approximately 100–200 ms (Moliadze, Zhao, Eysel & Funke, 2003), whereas covert motor activation induced by visually presented tools is also known to appear at 100–200 ms after the onset of visual stimuli (Handy et al., 2003). The same intensity of magnetic pulses was used for all three experiments. 2.4. Data analysis Individual MEPs were visually inspected and rejected if they were contaminated with a voluntary contraction or large fluctuations in the baseline before TMS. The overall waveform of the observed MEP (Fig. 1C) was well consistent with those reported in previous studies on the human masseter muscles (Guggisberg et al., 2001; Pearce et al., 2003; Jaberzadeh et al., 2008). For each trial, a peak-to-peak MEP amplitude was determined by finding the minimum and maximum values within a 10 ms time window from 5 ms to 15 ms after TMS. Because of the

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well-known large inter-individual variability of MEPs (Kiers, Cros, Chiappa & Fang, 1993; Ellaway et al., 1998), we elected to transform the MEP amplitudes into Z scores for each experiment. These Z scores were then submitted to Shapiro–Wilk test for normality and Levene test for homoscedasticity. These preliminary analyses confirmed that the present MEP data met the assumption of normality (p 40.1% for all experiments) and homogeneity of variance (p 40.1% for all experiments) required for subsequent analyses of variance (ANOVA).

3. Results 3.1. Experiment 1: semantic categorization (hot vs. cold) Behaviorally, participants performed the semantic categorization task with only a few errors (mean error rate (SD) ¼8.56 (4.42)%). Mean reaction times (RTs) for correct responses and MEPs are summarized in Fig. 2A. We first assessed the RT data using a 2  2 ANOVA with tool (chopsticks and scissors) and food (hot and cold) as within-participant factors. However, this analysis revealed that the main effects and their interaction were all nonsignificant (p4 0.09 for all). We next examined MEPs using the same 2  2 ANOVA as in behavioral RT analysis. Chopsticks overall increased MEPs by 3.4% relative to scissors. Indeed, there was a significant main effect of tool (F(1,11) ¼5.66, p o0.04). On the other hand, the effect of food neither reached significance (F(1,11) ¼1.10, p4 0.3) nor interacted with the effect of tool type (Fo1). Together, these results suggest that when visual stimuli are restricted to edible items, chopsticks produce a significant increase in the masseter MEPs during the visual recognition of food and that this covert change in the neuromasticatory system is not detectable at the behavioral level. 3.2. Experiment 2: semantic categorization (sweet vs. non-sweet) The mean error rate (SD) during semantic sweet/non-sweet categorization was 11.38(4.72)%. We examined RT data (Fig. 2B) using 2  2 ANOVA with tool (chopsticks and scissors) and food (sweet and non-sweet) as within-participant factors. The main effect of stimulus category was highly significant (F(1,10) ¼146.24, p¼ o0.001), suggesting that participants recognized sweet items faster (  18 ms) than non-sweet items. The effect of tool also showed a trend of significance (F(1,11) ¼4.29, p ¼0.07), whereas stimulus-by-tool interaction was non-significant (Fo1). For MEPs, there was a significant effect of tool (F(1,11) ¼6.33, po 0.03), suggesting that chopsticks produced greater MEPs relative to scissors. On the other hand, the effect of food and the interaction between the main effects were both non-significant (Fo1 for both). These results are consistent with the significant facilitatory effect of tools observed in Experiment 1 and support that eating tools can increase the excitability of the neuromuscular system for eating. 3.3. Experiment 3: oddball detection The mean error rate (SD) during oddball detection was 4.90 (3.11)%. We examined RT data (Fig. 2C) using 2  2 ANOVA with visual stimulus category (food and non-food) and tool (chopsticks and scissors) as within-participant factors. The main effect of tool did not approach statistical significance (Fo 1), suggesting that chopsticks were recognized as quickly as scissors. However, the effect of visual category was marginally significant (F(1,11) ¼ 4.26, p¼ 0.06), suggesting that participants tended to respond to food stimuli slightly faster (  6 ms) than to non-food stimuli. Significant interaction was observed between tool and stimulus category (F(1,11) ¼ 5.97, p ¼0.03). We then examined MEPs using the same 2  2 ANOVA as in behavioral RT analysis. The main effect of tool was far from

Please cite this article as: Yamaguchi, K., et al. Eating tools in hand activate the brain systems for eating action: A transcranial magnetic stimulation study. Neuropsychologia (2014), http://dx.doi.org/10.1016/j.neuropsychologia.2014.05.003i

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K. Yamaguchi et al. / Neuropsychologia ∎ (∎∎∎∎) ∎∎∎–∎∎∎

Fig. 3. Tool-induced changes in MEP across the three experiments (joint analysis).For each experiment, the magnitude of MEP is plotted with respect to the type of tools. The effect of tool is marginally significant across three experiments (po0.06) and does not change with task (p40.3). Error bars represent the standard error of the mean.

3.4. Joint analysis of three experiments

Fig. 2. Behavioral results and mean MEPs during semantic categorization (Experiments 1 and 2) and oddball detection (Experiment 3). Peak-to-peak MEP amplitudes are transformed into Z scores for each experiment. At the behavioral level, chopsticks and scissors produce no significant difference in RT across three experiments. On the other hand, chopsticks overall increase MEPs more greatly than scissors in Experiments 1 and 2. In Experiment 3, tool-driven increase of MEPs is greater when participants view food stimuli than when they view non-food stimuli. Error bars represent the standard error of the mean.

significance (Fo1). On the other hand, food items slightly increased MEPs relative to non-food items (0.6%), but this change was not significant (F(1,11) ¼1.34, p 40. 2). However, relative to scissors, chopstick increased MEPs by 1.0% for food stimuli and by 0.3% for non-food stimuli. This differential effect on MEP resulted in a significant crossover interaction between visual category and tool (F(1,11) ¼ 6.86, p ¼ 0.02). Taken together, these results from behavioral and MEP data suggest that eating tools exert a specific impact on the visuomotor system involved in eating during visual food recognition.

We made an additional between-task analysis to estimate the global impact of tool during food recognition by pooling the MEP data from three experiments. Namely, we extracted the MEP data for food stimuli from Experiment 3 and collapsed them with MEPs from Experiments 1 and 2. The magnitude of MEP is plotted for each tool type with respect to tasks in Fig. 3. We then ran 3  2 ANOVA with tool (chopsticks and scissors) and task (oddball detection, hot/cold categorization, sweet/non-sweet categorization) and obtained a marginally significant effect of tool (F(1,33)¼ 3.86, po0.06), which did not change with task (interaction: F(2,33)¼ 1.16, p40.3). The effect of task was non-significant (F(2,33)¼1.01, p40.3). Lastly, we examined whether the observed impact of tools on MEP was correlated with behavioral RTs for each experiment. We first determined the magnitude of “tool-induced effects” for each participant by subtracting RTchopsticks from RTscissors and MEPchopsticks from MEPscissors, and then plotted the MEP effects against the RT effects for each experiment. This analysis revealed only weak and non-significant correlation between RTs and MEPs for Experiment 1 (r ¼0.39, p 40.2) and Experiment 2 (r ¼0.52, p ¼0.18). As for Experiment 3, the magnitude of correlation was even weaker and did not approach significance (p 40.5).

4. Discussion For humans, typical eating action comprises a complex and probably overlearned sequence of visual object recognition, skilled use of eating tools and coordinated movements of craniopharyngeal muscles for mastication and swallowing. We predicted that somatosensory stimulation from eating utensils can covertly

Please cite this article as: Yamaguchi, K., et al. Eating tools in hand activate the brain systems for eating action: A transcranial magnetic stimulation study. Neuropsychologia (2014), http://dx.doi.org/10.1016/j.neuropsychologia.2014.05.003i

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activate the neuromuscular systems involved in eating action. At the behavioral level, however, we observed that overall effects of eating tools were non-significant across the three experiments. Whereas eating tools produced some differential impact (  6 ms) on visual recognition between food and non-food stimuli in Experiment 3, the effect of tool category did not interact with the type of food, either in Experiment 1 or in Experiment 2. These results therefore suggest that eating tools produce no or only minor change in behavioral measures during the visual recognition of food stimuli. Importantly, however, the observed lack of behavioral effects should not be taken as suggesting the total absence of neural activations during these tasks, because these behavioral measures generally reflect the final outcome of various processing stages intervening between stimulus perception and motor response (Naccache & Dehaene, 2001). Indeed, at the neuromuscular level, the present MEP results revealed that eating tools exerted a measurable impact on the motor excitability of the masseter muscles. That is, the MEP data from Experiments 1 and 2 showed that eating tools (chopsticks) enhanced the masseter MEPs more greatly than other tools (scissors) during the visual recognition of food. This effect of tool is consistent across the two experiments and therefore independent of the functional requirements of behavioral tasks. In Experiment 3, we further examined whether such tool-driven increase of the masseter MEPs occurs specifically for food stimuli and not for other non-food stimuli. Our results revealed that, like in Experiments 1 and 2, chopsticks overall increased MEPs more greatly than scissors, whereas this tool-related modulation of MEP was greater when participants viewed food stimuli than when they viewed non-food stimuli. A joint analysis of the three experiments further confirmed a significant effect of eating tools on the masseter MEPs during food recognition. Taken together, these results suggest that although undetectable at the behavioral level, eating tools exert a specific impact on the neural network involved in eating during visual food recognition. Obviously, however, it remains open to what extent the observed effect of eating tools is specific to the masseter muscle. That is, it is likely that such covert motor activation can spread to other facial and laryngeal muscles involved in eating during the visual observation of food stimuli. This remaining question should be addressed in future studies by measuring MEPs from other facial or limb muscles. Nevertheless, we propose that the present findings are in good accord with the notion that the distributed neuromuscular systems involved in eating action constitute a tightly interconnected network (Cattaneo et al., 2007) and further suggest that this neuromuscular coupling can be almost automatically driven by eating utensils in hand. This covert motor activation by eating tools also concurs with the previous behavioral and neuroimaging studies showing cross-modal motor activation by other sensory modality inputs, including musical sounds (Haueisen & Knö sche, 2001), written numerals (Sato et al., 2007) and flavor (Parma et al., 2011a). The present results therefore extend these previous findings by showing that multisensory inputs from somatosensory and visual stimuli can modulate the motor excitability of the orofacial muscles. Functional magnetic resonance imaging (fMRI) with normal humans studies has shown that tool use and its observation engage the distributed fronto-parietal network coding the relevant semantic, motoric and perceptual knowledge (Chao & Martin, 2000; Johnson-Frey, 2004; Vingerhoets, 2008; Bach, Peelen & Tipper, 2010; Costantini, Ambrosini, Sinigaglia & Gallese, 2011; Turella, Tubaldi, Erb, Grodd & Castiello, 2012). While these previous studies suggest a strong link between tool use and the sensorimotor system involved in its execution (e.g. grasping action and spatial direction of action), the present results further suggest that covert motor activation by eating tool stimuli can spread beyond the motor

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hand region coding relevant actions and extend even to the anatomically distinct jaw muscles involved in mastication. On the other hand, it is important to note that the observed crossmodal activation occurs only with effective visual and tactile inputs from food stimuli and eating utensils. That is, tactile inputs from eating tools alone are probably not sufficient to produce the covert motor activation of the masseter muscles, because in Experiment 3, the magnitude of MEPs for non-food trials almost never changed between chopsticks and scissors. Rather, tool-induced increase in MEP appeared only in food trials, while the same finding was also obtained in Experiments 1 and 2. These findings suggest that the modulatory influence over the masseter MEP emerges only when participants view edible objects, and thus does not generalize to other, non-edible objects. Indeed, cross-modal activation during eating action has been shown to rely on a complex neuromuscular system that is highly sensitive to the categorical difference between food and non-food items (Cattaneo et al., 2007). Although its entire stretch remains almost unknown, the putative neuromusclular system for eating may form a distributed and tightly interconnected network. This seems to concur with a previous fMRI study showing that food odors activate broadly distributed brain regions (Tubaldi et al., 2011), including the fronto-pareital region involved in action understanding and bilateral temporal regions previously associated with sematic knowledge (Chao & Martin, 2000; Johnson-Frey, 2004; Vingerhoets, 2008; Bach et al., 2010; Costantini et al., 2011; Turella et al., 2012) and further extending to the distant piriform and orbitofrontal areas involved in odor and gustatory processing (Tubaldi et al., 2011). Taken together, it may be said that simultaneous visual and tactile inputs from food stimuli and eating utensils effectively activate the entire neuromuscular network for eating action, which in turn generates and sends excitatory signals down to the jaw muscles involved in eating. This may provide a neurofunctional account for the clinical observations that eating tools in hand often serve to improve some neurological disorders related to eating action, including motor planning dysfunction in apraxic patients (Goldenberg et al., 2004) and eating difficulty in severely demented patients (Osborn & Marshall, 1993).

5. Conclusions The present results from three experiments revealed that the motor excitability of the masseter muscles consistently increased when participants held eating tools in hand. We further confirmed that the observed change in the motor excitability is mediated by the integrated long-distance signals via the visual object recognition system and hand sensorimotor system, rather than by the direct motor activation by tactile input. These results suggest that typical eating action in humans is achieved by a tightly interconnected network which comprises distributed neuromuscular systems involved in visual object recognition, skilled tool use and mastication.

Acknowledgments This work was supported by Takeda Science Foundation. References Bach, P., Peelen, M. V., & Tipper, S. P. (2010). On the role of object information in action observation: an fMRI study. Cerebral Cortex, 20, 2798–2809. Barrós-Loscertales, A., González, J., Pulvermüller, F., Ventura-Campos, N., Bustamante, J. C., Costumero, V., et al. (2012). Reading salt activates gustatory brain regions: fMRI evidence for semantic grounding in a novel sensory modality. Cerebral Cortex, 22, 2554–2563. Berthoud, H.-R. (2002). Multiple neural systems controlling food intake and body weight. Neuroscience & Biobehavioral Reviews, 26, 393–428.

Please cite this article as: Yamaguchi, K., et al. Eating tools in hand activate the brain systems for eating action: A transcranial magnetic stimulation study. Neuropsychologia (2014), http://dx.doi.org/10.1016/j.neuropsychologia.2014.05.003i

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Please cite this article as: Yamaguchi, K., et al. Eating tools in hand activate the brain systems for eating action: A transcranial magnetic stimulation study. Neuropsychologia (2014), http://dx.doi.org/10.1016/j.neuropsychologia.2014.05.003i

Eating tools in hand activate the brain systems for eating action: a transcranial magnetic stimulation study.

There is increasing neuroimaging evidence suggesting that visually presented tools automatically activate the human sensorimotor system coding learned...
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