Origin coordinate influence on performance of temporally extended signal space separation in magnetoencephalography.

OBJECTIVE: Temporally extended signal space separation (tSSS) is a powerful method for artifact suppression in magnetoencephalography (MEG). Because tSSS first separates MEG signals coming from inside and outside a certain sphere, definition of the sphere origin is important. For this study, we explored the influence of origin choice on tSSS performance in spontaneous and evoked activity from epilepsy patients. METHODS: Interictal epileptiform discharges (IEDs) and somatosensory evoked fields (SEFs) were processed with two tSSSs: one with the default origin of (0, 0, 40 mm) in the head coordinate, and the other with an individual origin estimated using each patient's anatomical magnetic resonance imaging (MRI). Equivalent current dipoles (ECDs) were calculated for the data. The ECD location and quality of estimation were compared across conditions. RESULTS: MEG data from 21 patients revealed marginal differences in ECD location, but the estimation quality inferred from goodness of fit (GOF) and confidence volume (CV) was better for the tSSS with individual origins. This choice affected IEDs more than it affected SEFs. CONCLUSIONS: Individual sphere model resulted in better GOF and CV. SIGNIFICANCE: Application of tSSS using an individual origin would be more desirable when available. This parameter might influence spontaneous activity more strongly.

Correlation of motor-auditory cross-modal and auditory unimodal N1 and mismatch responses of schizophrenic patients and normal subjects: an MEG study.

Introduction: It has been suggested that the positive symptoms of schizophrenic patients (hallucinations, delusions, and passivity experience) are caused by dysfunction of their internal and external sensory prediction errors. This is often discussed as related to dysfunction of the forward model that executes self-monitoring. Several reports have suggested that dysfunction of the forward model in schizophrenia causes misattributions of self-generated thoughts and actions to external sources. There is some evidence that the forward model can be measured using the electroencephalography (EEG) and magnetoencephalography (MEG) components such as N1 (m) and mismatch negativity (MMN) (m). The objective in this MEG study is to investigate differences in the N1m and MMNm-like activity generated in motor-auditory cross-modal tasks in normal control (NC) subjects and schizophrenic (SC) patients, and compared that activity with N1m and MMNm in the auditory unimodal task. Methods: The N1m and MMNm/MMNm-like activity were recorded in 15 SC patients and 12 matched NC subjects. The N1m-attenuation effects and peak amplitude of MMNm/MMNm-like activity of the NC and SC groups were compared. Additionally, correlations between MEG measures (N1m suppression rate, MMNm, and MMNm-like activity) and clinical variables (Positive and Negative Syndrome Scale (PANSS) scores and antipsychotic drug (APD) dosages) in SC patients were investigated. Results: It was found that (i) there was no significant difference in N1m-attenuation for the NC and SC groups, and that (ii) MMNm in the unimodal task in the SC group was significantly smaller than that in the NC group. Further, the MMNm-like activity in the cross-modal task was smaller than that of the MMNm in the unimodal task in the NC group, but there was no significant difference in the SC group. The PANSS positive symptoms and general psychopathology score were moderately negatively correlated with the amplitudes of the MMNm-like activity, and the APD dosage was moderately negatively correlated with the N1m suppression rate. However, none of these correlations reached statistical significance. Discussion: The findings suggest that schizophrenic patients perform altered predictive processes differently from healthy subjects in latencies reflecting MMNm, depending on whether they are under forward model generation or not. This may support the hypothesis that schizophrenic patients tend to misattribute their inner experience to external agents, thus leading to the characteristic schizophrenia symptoms.

Investigating the technical feasibility of magnetoencephalography during transcranial direct current stimulation.

Introduction: Magnetoencephalography (MEG) can measure weak magnetic fields produced by electrical brain activity. Transcranial direct current stimulation (tDCS) can affect such brain activities. The concurrent application of both, however, is challenging because tDCS presents artifacts on the MEG signal. If brain activity during tDCS can be elucidated by MEG, mechanisms of plasticity-inducing and other effects of tDCS would be more comprehensively understood. We tested the technical feasibility of MEG during tDCS using a phantom that produces an artificial current dipole simulating focal brain activity. An earlier study investigated estimation of a single oscillating phantom dipole during tDCS, and we systematically tested multiple dipole locations with a different MEG device. Methods: A phantom provided by the manufacturer was used to produce current dipoles from 32 locations. For the 32 dipoles, MEG was recorded with and without tDCS. Temporally extended signal space separation (tSSS) was applied for artifact rejection. Current dipole sources were estimated as equivalent current dipoles (ECDs). The ECD modeling quality was assessed using localization error, amplitude error, and goodness of fit (GOF). The ECD modeling performance with and without tDCS, and with and without tSSS was assessed. Results: Mean localization errors of the 32 dipoles were 1.70 ± 0.72 mm (tDCS off, tSSS off, mean ± standard deviation), 6.13 ± 3.32 mm (tDCS on, tSSS off), 1.78 ± 0.83 mm (tDCS off, tSSS on), and 5.73 ± 1.60 mm (tDCS on, tSSS on). Mean GOF findings were, respectively, 92.3, 87.4, 97.5, and 96.7%. Modeling was affected by tDCS and restored by tSSS, but improvement of the localization error was marginal, even with tSSS. Also, the quality was dependent on the dipole location. Discussion: Concurrent tDCS-MEG recording is feasible, especially when tSSS is applied for artifact rejection and when the assumed location of the source of activity is favorable for modeling. More technical studies must be conducted to confirm its feasibility with different source modeling methods and stimulation protocols. Recovery of single-trial activity under tDCS warrants further research.

Order of statistical learning depends on perceptive uncertainty.

Statistical learning (SL) is an innate mechanism by which the brain automatically encodes the n-th order transition probability (TP) of a sequence and grasps the uncertainty of the TP distribution. Through SL, the brain predicts a subsequent event (e n+1 ) based on the preceding events (e n ) that have a length of "n". It is now known that uncertainty modulates prediction in top-down processing by the human predictive brain. However, the manner in which the human brain modulates the order of SL strategies based on the degree of uncertainty remains an open question. The present study examined how uncertainty modulates the neural effects of SL and whether differences in uncertainty alter the order of SL strategies. It used auditory sequences in which the uncertainty of sequential information is manipulated based on the conditional entropy. Three sequences with different TP ratios of 90:10, 80:20, and 67:33 were prepared as low-, intermediate, and high-uncertainty sequences, respectively (conditional entropy: 0.47, 0.72, and 0.92 bit, respectively). Neural responses were recorded when the participants listened to the three sequences. The results showed that stimuli with lower TPs elicited a stronger neural response than those with higher TPs, as demonstrated by a number of previous studies. Furthermore, we found that participants adopted higher-order SL strategies in the high uncertainty sequence. These results may indicate that the human brain has an ability to flexibly alter the order based on the uncertainty. This uncertainty may be an important factor that determines the order of SL strategies. Particularly, considering that a higher-order SL strategy mathematically allows the reduction of uncertainty in information, we assumed that the brain may take higher-order SL strategies when encountering high uncertain information in order to reduce the uncertainty. The present study may shed new light on understanding individual differences in SL performance across different uncertain situations.

Aphasia and a Dual-Stream Language Model in a 4-Year-Old Female with Landau-Kleffner Syndrome.

Landau-Kleffner syndrome (LKS) is a rare neurological disorder characterized by acquired aphasia. LKS presents with distinctive electroencephalography (EEG) findings, including diffuse continuous spike and wave complexes (CSW), particularly during sleep. There has been little research on the mechanisms of aphasia and its origin within the brain and how it recovers. We diagnosed LKS in a 4-year-old female with an epileptogenic zone located primarily in the right superior temporal gyrus or STG (nondominant side). In the course of her illness, she had early signs of motor aphasia recovery but was slow to regain language comprehension and recover from hearing loss. We suggest that the findings from our patient's brain imaging and the disparity between her recovery from expressive and receptive aphasias are consistent with the dual-stream model of speech processing in which the nondominant hemisphere also plays a significant role in language comprehension. Unlike aphasia in adults, the right-hemisphere disorder has been reported to cause delays in language comprehension and gestures in early childhood. In the period of language acquisition, it requires a process of understanding what the words mean by integrating and understanding the visual, auditory, and contextual information. It is thought that the right hemisphere works predominantly with respect to its integrating role.

Perceptual uncertainty modulates auditory statistical learning: A magnetoencephalography study.

Statistical learning allows comprehension of structured information, such as that in language and music. The brain computes a sequence's transition probability and predicts future states to minimise sensory reaction and derive entropy (uncertainty) from sequential information. Neurophysiological studies have revealed that early event-related neural responses (P1 and N1) reflect statistical learning - when the brain encodes transition probability in stimulus sequences, it predicts an upcoming stimulus with a high transition probability and suppresses the early event-related responses to a stimulus with a high transition probability. This amplitude difference between high and low transition probabilities reflects statistical learning effects. However, how a sequence's transition probability ratio affects neural responses contributing to statistical learning effects remains unknown. This study investigated how transition-probability ratios or conditional entropy (uncertainty) in auditory sequences modulate the early event-related neuromagnetic responses of P1m and N1m. Sequence uncertainties were manipulated using three different transition-probability ratios: 90:10%, 80:20%, and 67:33% (conditional entropy: 0.47, 0.72, and 0.92 bits, respectively). Neuromagnetic responses were recorded when participants listened to sequential sounds with these three transition probabilities. Amplitude differences between lower and higher probabilities were larger in sequences with transition-probability ratios of 90:10% and smaller in sequences with those of 67:33%, compared to sequences with those of 80:20%. This suggests that the transition-probability ratio finely tunes P1m and N1m. Our study also showed larger amplitude differences between frequent- and rare-transition stimuli in P1m than in N1m. This indicates that information about transition-probability differences may be calculated in earlier cognitive processes.

Musical expertise facilitates statistical learning of rhythm and the perceptive uncertainty: A cross-cultural study.

The brain extracts statistical regularities from sequential information around our environment. This is referred to as statistical learning (SL). Statistical learning is considered an innate function in the human brain and contributes to the brain's development. Within the framework of predictive coding, this learning system allows us to predict a future state to minimize sensory reaction and resolve uncertainty around the world. By auditory statistical learning, over the brain's development, humans become able to comprehend language and music. An increasing number of studies has revealed that Western-classical musical training optimizes the brain's probabilistic model of music and enhances the accuracy of perceptive uncertainty (entropy) in newly encountered melody. No study, however, investigates how musical training modulates the probabilistic model of rhythm, and how the musical culture tunes them. The present study investigated how SL of temporal sequences with and without a beat is reflected in neural responses, and how the SL is modulated by the two types of musical training in different cultures: Western- and Japanese-classical music (i.e., Hougaku). The neural representation showed evidence that the SL effects of beat sequence were prominent in the left hemisphere. This finding was larger in Western- and Japanese-classical musicians compared with non-musicians. Further, the entropy (uncertainty) of the sequences negatively correlated with neural effects of SL, mainly in the left hemisphere of the both Western- and Japanese-classical musicians. These suggest that, regardless of musical culture, musical training may generally facilitate SL of rhythm. However, the specific neural components showed differences between groups of musicians: an earlier component, referred to as P1, represented the left lateralization for perceptive uncertainty in both groups of musicians, whereas a later component, referred to as N1, represented the left lateralization only in Japanese Classical musicians. These findings may suggest that the types of musical training differently modulate neural representation of underlying temporal SL, particularly global processing of uncertainty rather than local processing of transitional probability. The present study sheds new light on the neurophysiological account of Japanese classical music.

Long-Term Undiagnosed Nonconvulsive Status Epilepticus Identified by Urgent Electroencephalography with Hyperventilation Activation.

Nonconvulsive status epilepticus (NCSE) might be underdiagnosed in cases where clinical symptoms are ambiguous. If a patient exhibits ictal psychiatric symptoms such as NCSE presentation and is misdiagnosed as having a psychiatric disorder, the patient may be treated in psychiatry settings, where continuous electroencephalography (cEEG), the gold standard for NCSE diagnosis, is typically not used. Herein, we report our experience with a patient having NCSE who exhibited psychiatric symptoms and remained misdiagnosed for many years. We also included a brief review of the relevant literature. Our experience with this patient presents two clinically significant points: (1) clinicians should consider NCSE in the differential diagnosis of interictal psychosis when patients with epilepsy, in whom the seizure type is unknown, repeatedly present transient psychiatric symptoms, and (2) urgent EEG with hyperventilation activation during acute periods may help diagnose patients with suspected NCSE.

Concurrent Statistical Learning of Ignored and Attended Sound Sequences: An MEG Study.

In an auditory environment, humans are frequently exposed to overlapping sound sequences such as those made by human voices and musical instruments, and we can acquire information embedded in these sequences via attentional and nonattentional accesses. Whether the knowledge acquired by attentional accesses interacts with that acquired by nonattentional accesses is unknown, however. The present study examined how the statistical learning (SL) of two overlapping sound sequences is reflected in neurophysiological and behavioral responses, and how the learning effects are modulated by attention to each sequence. SL in this experimental paradigm was reflected in a neuromagnetic response predominantly in the right hemisphere, and the learning effects were not retained when attention to the tone streams was switched during the learning session. These results suggest that attentional and nonattentional learning scarcely interact with each other and that there may be a specific system for nonattentional learning, which is independent of attentional learning.

Aphasic status epilepticus preceding tumefactive left hemisphere lesion in anti-MOG antibody associated disease.

INTRODUCTION: Anti-myelin oligodendrocyte glycoprotein (MOG) antibodies have recently been associated with epilepsy with FLAIR hyperintense cortical lesions on MRI. Association between anti-MOG antibodies and epilepsy without detectable structural brain lesion on MRI is unknown. CASE REPORT: A 48-year-old right-handed man with a four-and-a-half year history of anti-MOG antibody associated demyelinating disease presented with persistent global aphasia. Brain MRI showed no new lesion or cortical lesion in the left hemisphere. Electroencephalogram, magnetoencephalography, and brain perfusion single-photon emission computed tomography suggested epileptic foci in the left temporal and parietal lobes, and the patient's aphasia transiently responded to intravenous diazepam, compatible with aphasic status epilepticus. Cerebrospinal fluid showed mildly elevated cell count and positive oligoclonal bands. The patient only partially responded to antiepileptic drugs but responded to steroid pulse therapy. Six months later, the patient again exhibited global aphasia. Brain MRI showed tumefactive white matter lesion in the left temporo-parietal lobes. CONCLUSION: Autoimmune epilepsy without obvious causative lesion on MRI can be seen in the course of anti-MOG antibody associated demyelinating disease. The subsequent emergence of tumefactive lesion closely located to the epileptic foci may suggest some association between autoimmune epilepsy and demyelinating lesions.

Lack of correlation between phonetic magnetic mismatch field and plasma d-serine levels in humans.

OBJECTIVE: Uncovering molecular bases for auditory language processing in the human brain is a fundamental scientific challenge. The power and latency of the magnetic mismatch field (MMF) elicited by phoneme change, which are magnetoencephalographic indices of language function in its early stage of information processing, are theoretically thought to be modulated by N-methyl-d-aspartate-type glutamate receptor (NMDAR) function, but no study has yet assessed this possibility. We have thus sought to demonstrate an association between phonetic MMF power/latency and levels of plasma d-serine, an intrinsic co-agonist of glycine binding sites on NMDAR, in adults. METHODS: The MMF response to phoneme changes was recorded using 204-channel magnetoencephalography in 61 healthy, right-handed, Japanese adults. Plasma levels of d- and l-serine were measured for each participant. RESULTS: We did not find a significant correlation between MMF power/latency and plasma serine levels. CONCLUSIONS: Despite a sufficient sample size, we failed to find an association between the physiological markers of the early stage of information processing of language in the auditory cortex and biomarkers indexing glutamatergic function. SIGNIFICANCE: Our study did not indicate that a molecular index of glutamatergic function could be a surrogate marker for the early stage of information processing of language in humans.

Single, but not dual, attention facilitates statistical learning of two concurrent auditory sequences.

When we are exposed to a novel stimulus sequence, we can learn the sequence by extracting a statistical structure that is potentially embedded in the sequence. This mechanism is called statistical learning, and is considered a fundamental and domain-general process that is innate in humans. In the real-world environment, humans are inevitably exposed to auditory sequences that often overlap with one another, such as speech sound streams from multiple speakers or entangled melody lines generated by multiple instruments. The present study investigated how single and dual attention modulates brain activity, reflecting statistical learning when two auditory sequences were presented simultaneously. The results demonstrated that the effect of statistical learning had more pronounced neural activity when listeners paid attention to only one sequence and ignored the other, rather than paying attention to both sequences. Biased attention may thus be an essential strategy when learners are exposed to multiple information streams.

Statistical learning of an auditory sequence and reorganization of acquired knowledge: A time course of word segmentation and ordering.

Previous neural studies have supported the hypothesis that statistical learning mechanisms are used broadly across different domains such as language and music. However, these studies have only investigated a single aspect of statistical learning at a time, such as recognizing word boundaries or learning word order patterns. In this study, we neutrally investigated how the two levels of statistical learning for recognizing word boundaries and word ordering could be reflected in neuromagnetic responses and how acquired statistical knowledge is reorganised when the syntactic rules are revised. Neuromagnetic responses to the Japanese-vowel sequence (a, e, i, o, and u), presented every .45s, were recorded from 14 right-handed Japanese participants. The vowel order was constrained by a Markov stochastic model such that five nonsense words (aue, eao, iea, oiu, and uoi) were chained with an either-or rule: the probability of the forthcoming word was statistically defined (80% for one word; 20% for the other word) by the most recent two words. All of the word transition probabilities (80% and 20%) were switched in the middle of the sequence. In the first and second quarters of the sequence, the neuromagnetic responses to the words that appeared with higher transitional probability were significantly reduced compared with those that appeared with a lower transitional probability. After switching the word transition probabilities, the response reduction was replicated in the last quarter of the sequence. The responses to the final vowels in the words were significantly reduced compared with those to the initial vowels in the last quarter of the sequence. The results suggest that both within-word and between-word statistical learning are reflected in neural responses. The present study supports the hypothesis that listeners learn larger structures such as phrases first, and they subsequently extract smaller structures, such as words, from the learned phrases. The present study provides the first neurophysiological evidence that the correction of statistical knowledge requires more time than the acquisition of new statistical knowledge.

Familial Influences on Mismatch Negativity and Its Association with Plasma Glutamate Level: A Magnetoencephalographic Study in Twins.

Mismatch negativity (MMN) or its magnetic counterpart (magnetic mismatch negativity; MMNm) is regarded as a promising biomarker for schizophrenia. Previous electroencephalographic studies of MMN have demonstrated a moderate-to-high heritability for MMN amplitudes. N-methyl-D-aspartate receptor-dependent glutamatergic neurotransmission is implicated in MMN generation. We hypothesized that the differences between identical twins in MMNm variables might be associated with differences in plasma levels of amino acids involved in glutamatergic neurotransmission. Thirty-three pairs of monozygotic (MZ) and 10 pairs of dizygotic (DZ) twins underwent MMNm recording. The MMNm in response to tone duration changes, tone frequency changes, and phonemic changes was recorded using 204-channel magnetoencephalography. Of these, 26 MZ and 7 DZ twin pairs underwent blood sampling for determination of plasma amino acid levels. MMNm peak strength showed relatively high correlations in both MZ and DZ twin pairs. The differences in MMNm latencies tended to correlate with the differences in plasma amino acid levels within MZ pairs, while no significant correlation was observed after the Bonferroni correction. We observed a familial trait in MMNm strength. The differences in MMN latency in MZ twins might be influenced by changes in glutamate levels and glutamate-glutamine cycling; however, the results need to be replicated.

Pitch-class distribution modulates the statistical learning of atonal chord sequences.

The present study investigated whether neural responses could demonstrate the statistical learning of chord sequences and how the perception underlying a pitch class can affect the statistical learning of chord sequences. Neuromagnetic responses to two chord sequences of augmented triads that were presented every 0.5s were recorded from fourteen right-handed participants. One sequence was a series of 360 chord triplets, each of which consisted of three chords in the same pitch class (clustered pitch-classes sequences). The other sequence was a series of 360 chord triplets, each of which consisted of three chords in different pitch classes (dispersed pitch-classes sequences). The order of the triplets was constrained by a first-order Markov stochastic model such that a forthcoming triplet was statistically defined by the most recent triplet (80% for one; 20% for the other two). We performed a repeated-measures ANOVA with the peak amplitude and latency of the P1m, N1m and P2m. In the clustered pitch-classes sequences, the P1m responses to the triplets that appeared with higher transitional probability were significantly reduced compared with those with lower transitional probability, whereas no significant result was detected in the dispersed pitch-classes sequences. Neuromagnetic significance was concordant with the results of familiarity interviews conducted after each learning session. The P1m response is a useful index for the statistical learning of chord sequences. Domain-specific perception based on the pitch class may facilitate the domain-general statistical learning of chord sequences.

Magnetoencephalographic recording of auditory mismatch negativity in response to duration and frequency deviants in a single session in patients with schizophrenia.

AIM: Auditory mismatch negativity (MMN) and its magnetoencephalographic (MEG) counterpart (MMNm) are an established biological index in schizophrenia research. MMN in response to duration and frequency deviants may have differential relevance to the pathophysiology and clinical stages of schizophrenia. MEG has advantage in that it almost purely detects MMNm arising from the auditory cortex. However, few previous MEG studies on schizophrenia have simultaneously assessed MMNm in response to duration and frequency deviants or examined the effect of chronicity on the group difference. METHODS: Forty-two patients with chronic schizophrenia and 74 matched control subjects participated in the study. Using a whole-head MEG, MMNm in response to duration and frequency deviants of tones was recorded while participants passively listened to an auditory sequence. RESULTS: Compared to healthy subjects, patients with schizophrenia exhibited significantly reduced powers of MMNm in response to duration deviant in both hemispheres, whereas MMNm in response to frequency deviant did not differ between the two groups. These results did not change according to the chronicity of the illness. CONCLUSION: These results, obtained by using a sequence-enabling simultaneous assessment of both types of MMNm, suggest that MEG recording of MMN in response to duration deviant may be a more sensitive biological marker of schizophrenia than MMN in response to frequency deviant. Our findings represent an important first step towards establishment of MMN as a biomarker for schizophrenia in real-world clinical psychiatry settings.

Frequency characteristics of neuromagnetic auditory steady-state responses to sinusoidally amplitude-modulated sweep tones.

OBJECTIVE: This study aimed to capture the neuronal frequency characteristics, as indexed by the auditory steady-state response (ASSR), relative to physical characteristics of constant sound pressure levels (SPLs). Relationship with perceptual characteristics (loudness model) was also examined. METHODS: Neuromagnetic 40-Hz ASSR was recorded in response to sinusoidally amplitude-modulated sweep tones with carrier frequency covering the frequency range of 0.1-12.5kHz. Sound intensity was equalized at 50-, 60-, and 70-dB SPL with an accuracy of ±0.5-dB SPL at the phasic peak of the modulation frequency. Corresponding loudness characteristics were modeled by substituting the detected individual hearing thresholds into a standard formula (ISO226:2003(E)). RESULTS: The strength of the ASSR component was maximum at 0.5kHz, and it decreased linearly on logarithmic scale toward lower and higher frequencies. Loudness model was plateaued between 0.5 and 4kHz. CONCLUSIONS: Frequency characteristics of the ASSR were not equivalent to those of SPL and loudness model. Factors other than physical and perceptual frequency characteristics may contribute to characterizing the ASSR. SIGNIFICANCE: The results contribute to the discussion of the most efficient signal summation for the generation of the ASSR at 0.5kHz and efficient neuronal processing at higher frequencies, which require less energy to retain equal perception.

Dry phantom for magnetoencephalography -Configuration, calibration, and contribution.

BACKGROUND: An artificial object that imitates human brain activity is called "phantom" and is used for evaluation of magnetoencephalography (MEG) systems. The accuracy of the phantom itself had not been guaranteed in the previous studies, although role of the phantom is to evaluate the accuracy of MEG measurement. The purposes of this paper are to develop a novel MEG phantom that can be calibrated and to demonstrate the advantages of the calibrated phantoms. NEW METHOD: We proposed and fabricated a practical dry phantom that is composed of 50 isosceles-triangle coils based on Ilmoniemi's model. This phantom was calibrated based on three-dimensional measurement of the current paths in the phantom and on numerical calculations. RESULTS: The calibrated positions of the equivalent current dipoles (ECDs) shifted 0.83mm, on average, from the designed positions. The uncertainties of the calibrated ECDs were also evaluated, by combining the uncertainties which could reasonably be attributed to them. COMPARISON WITH EXISTING METHOD(S): Furthermore, we demonstrated performance of the developed phantom through experimental evaluation of an MEG system. The results of this evaluation differed from those obtained using an uncalibrated phantom. Moreover, the calibrated phantom can provide detailed information regarding the uncertainty of the measurement and also the uncertainty of the phantom itself. CONCLUSIONS: A more appropriate evaluation of MEG measurements can be achieved using a calibrated phantom.

Mastication accelerates Go/No-go decisional processing: An event-related potential study.

OBJECTIVE: The purpose of the present study was to investigate the effect of mastication on Go/No-go decisional processing using event-related potentials (ERPs). METHOD: Thirteen normal subjects underwent seven sessions of a somatosensory Go/No-go paradigm for approximately 4min; Pre, and Post 1, 2, 3, 4, 5, and 6. The Control condition included the same seven sessions. The RT and standard deviation were recorded, and the peak amplitude and latency of the N140 and P300 components were analyzed. RESULTS: The RT was significantly shorter in Mastication than in Control at Post 1-3 and 4-6. The peak latency of N140 was earlier in Mastication than in Control at Post 4-6. The latency of N140 was shortened by repeated sessions in Mastication, but not by those in Control. The peak latency of P300 was significantly shorter in Mastication than in Control at Post 4-6. The peak latency of P300 was significantly longer in Control with repeated sessions, but not in Mastication. CONCLUSIONS: These results suggest that mastication may influence response execution processing in Go trials, as well as response inhibition processing in No-go trials. SIGNIFICANCE: Mastication accelerated Go/No-go decisional processing in the human brain.