Magnetoencephalography Measurements Research Articles

Non-invasive measurement of rat auditory evoked fields using an optically pumped atomic magnetometer: Effects of task manipulation

Optically pumped magnetometers (OPMs) have become a favorable tool for magnetoencephalography (MEG) measurement, offering a non-invasive method of measurement. OPMs do not require cryogenic environments, sensors can be more closely aligned with the brain. We employed a passive single-stimulus paradigm in conjunction with OPMs with a sensitivity of 20 fT/ Hz to investigate the auditory response of rats to inter-stimulus interval (ISI) and frequencies, recording the rat auditory event-related magnetic fields (ERMFs). Our findings include: (1) Auditory evoked fields can be detected non-invasively by OPMs; (2) The amplitude of the rat auditory ERMFs varies with changes in ISI, with more pronounced amplitude changes observed after 5 s; (3) When the sound stimulus frequency is altered at the same ISI, the amplitude of the rats ERMFs changes with frequency, indicating significant differences in attention. Our method offers a valuable tool for the clinical application of a single stimulus paradigm and opens up a new avenue for research on the brain magnetic field detections.

Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation

IntroductionTranscranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain.MethodsMEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05).ResultsThe 8-min tPBM enabled significant increases in alpha (8–12 Hz) and beta (13–30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side.DiscussionMEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.

The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions.

Most parts of speech are voiced, exhibiting a degree of periodicity with a fundamental frequency and many higher harmonics. Some neural populations respond to this temporal fine structure, in particular at the fundamental frequency. This frequency-following response to speech consists of both subcortical and cortical contributions and can be measured through EEG as well as through magnetoencephalography (MEG), although both differ in the aspects of neural activity that they capture: EEG is sensitive to both radial and tangential sources as well as to deep sources, whereas MEG is more restrained to the measurement of tangential and superficial neural activity. EEG responses to continuous speech have shown an early subcortical contribution, at a latency of around 9 msec, in agreement with MEG measurements in response to short speech tokens, whereas MEG responses to continuous speech have not yet revealed such an early component. Here, we analyze MEG responses to long segments of continuous speech. We find an early subcortical response at latencies of 4-11 msec, followed by later right-lateralized cortical activities at delays of 20-58 msec as well as potential subcortical activities. Our results show that the early subcortical component of the FFR to continuous speech can be measured from MEG in populations of participants and that its latency agrees with that measured with EEG. They furthermore show that the early subcortical component is temporally well separated from later cortical contributions, enabling an independent assessment of both components toward further aspects of speech processing.

Automated extraction of heart rate variability from magnetoencephalography signals

Magnetoencephalography (MEG) measures magnetic fluctuations in the brain generated by neural processes, some of which, such as cardiac signals, are generally removed as artifacts and discarded. However, heart rate variability (HRV) has long been regarded as a biomarker related to autonomic function, suggesting the cardiac signal in MEG contains valuable information that can provide supplemental health information about a patient. To enable access to these ancillary HRV data, we created an automated extraction tool capable of capturing HRV directly from raw MEG data with artificial intelligence. Five scans were conducted with simultaneous MEG and electrocardiogram (ECG) acquisition, which provides a ground truth metric for assessing our algorithms and data processing pipeline. In addition to directly comparing R-peaks between the MEG and ECG signals, this work explores the variation of the corresponding HRV output in time, frequency, and non-linear domains. After removing outlier intervals and aligning the ECG and derived cardiac MEG signals, the RMSE between the RR-intervals of each was RMSE1 = 2 ms, RMSE2 = 2 ms, RMSE3 = 8 ms, RMSE4 = 4 ms, RMSE5 = 13 ms. The findings indicate that cardiac artifacts from MEG data carry sufficient signal to approximate an individual's HRV metrics.

Design and methodology for a proof of mechanism study of individualized neuronavigated continuous Theta burst stimulation for auditory processing in adolescents with autism spectrum disorder.

It has been suggested that aberrant excitation/inhibition (E/I) balance and dysfunctional structure and function of relevant brain networks may underlie the symptoms of autism spectrum disorder (ASD). However, the nomological network linking these constructs to quantifiable measures and mechanistically relating these constructs to behavioral symptoms of ASD is lacking. Herein we describe a within-subject, controlled, proof-of-mechanism study investigating the pathophysiology of auditory/language processing in adolescents with ASD. We utilize neurophysiological and neuroimaging techniques including magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG) metrics of language network structure and function. Additionally, we apply a single, individually targeted session of continuous theta burst stimulation (cTBS) as an experimental probe of the impact of perturbation of the system on these neurophysiological and neuroimaging outcomes. MRS, fMRI, and MEG measures are evaluated at baseline and immediately prior to and following cTBS over the posterior superior temporal cortex (pSTC), a region involved in auditory and language processing deficits in ASD. Also, behavioral measures of ASD and language processing and DWI measures of auditory/language network structures are obtained at baseline to characterize the relationship between the neuroimaging and neurophysiological measures and baseline symptom presentation. We hypothesize that local gamma-aminobutyric acid (GABA) and glutamate concentrations (measured with MRS), and structural and functional activity and network connectivity (measured with DWI and fMRI), will significantly predict MEG indices of auditory/language processing and behavioral deficits in ASD. Furthermore, a single session of cTBS over left pSTC is hypothesized to lead to significant, acute changes in local glutamate and GABA concentration, functional activity and network connectivity, and MEG indices of auditory/language processing. We have completed the pilot phase of the study (n=20 Healthy Volunteer adults) and have begun enrollment for the main phase with adolescents with ASD (n=86; age 14-17). If successful, this study will establish a nomological network linking local E/I balance measures to functional and structural connectivity within relevant brain networks, ultimately connecting them to ASD symptoms. Furthermore, this study will inform future therapeutic trials using cTBS to treat the symptoms of ASD.

Neurophysiological brain function predicts response to cognitive rehabilitation and mindfulness in multiple sclerosis: a randomized trial

BackgroundCognitive treatment response varies highly in people with multiple sclerosis (PwMS). Identification of mechanisms is essential for predicting response.ObjectivesThis study aimed to investigate whether brain network function predicts response to cognitive rehabilitation therapy (CRT) and mindfulness-based cognitive therapy (MBCT).MethodsPwMS with cognitive complaints completed CRT, MBCT, or enhanced treatment as usual (ETAU) and performed three measurements (baseline, post-treatment, 6-month follow-up). Baseline magnetoencephalography (MEG) measures were used to predict treatment effects on cognitive complaints, personalized cognitive goals, and information processing speed (IPS) using mixed models (secondary analysis REMIND-MS study).ResultsWe included 105 PwMS (96 included in prediction analyses; 32 CRT, 31 MBCT, 33 ETAU), and 56 healthy controls with baseline MEG. MEG did not predict reductions in complaints. Higher connectivity predicted better goal achievement after MBCT (p = 0.010) and CRT (p = 0.018). Lower gamma power (p = 0.006) and higher connectivity (p = 0.020) predicted larger IPS benefits after MBCT. These MEG predictors indicated worse brain function compared to healthy controls (p < 0.05).ConclusionsBrain network function predicted better cognitive goal achievement after MBCT and CRT, and IPS improvements after MBCT. PwMS with neuronal slowing and hyperconnectivity were most prone to show treatment response, making network function a promising tool for personalized treatment recommendations.Trial registrationThe REMIND-MS study was prospectively registered in the Dutch Trial registry (NL6285; https://trialsearch.who.int/Trial2.aspx?TrialID=NTR6459).

Low noise magnetic field compensation based on differential biplanar coils with small coil constant

Magnetic field noise is a key factor limiting the resolution of quantum precise measurement. In active magnetic field compensation systems, the large coil constant and fixed noise of the coil and current source, respectively, cause excessive noise. This study proposes a differential biplanar coils (DBCs) design method by comprehensively optimizing two sets of biplanar coils with differential evolution (DE) algorithm, which can reduce the coil constant by two magnitude orders while ensuring high uniformity. The peak-to-peak magnetic field at the center point is reduced to 0.8 pT, and the magnetic field noise is reduced to 8 fT/Hz, which is a reduction of 94.4%. The low noise active magnetic compensation system based on the differential biplanar coils can improve the accuracy of the magnetic shielding room (MSR) internal magnetic field control and reduce magnetic field noise effectively. The proposed method contributes to generating a near-zero magnetic field environment with low magnetic field noise, which is critical to promoting magnetoencephalography (MEG) measurements.

Magnetic noise analysis for small magnetically shielded room in different environmental magnetic fields

The compact high-performance magnetically shielded room (MSR) provides near-zero magnetic field environment for low-cost magnetoencephalography (MEG) measurements. Predicting the level of magnetic noise in the MSR under different magnetic field holds significant importance for the deployment of MEG systems. In this paper, the magnetic noise of MSR in different operational conditions is studied. The magnetic noise in MSR is modeled as residual environmental noise, material one, and additional one. A quantitative model for magnetic noise calculation is established, leading to the definition of the Weak Shielding Factor (WSF), which establishes a relationship between the environment magnetic noise and MSR one. Verification experiments are conducted using a compact MSR, a magnetically shielded box, and a cylindrical magnetically shielded bucket. The average magnetic noise error between calculated and measured values in 1–100 Hz range for the three shielding structures are 8.29%, 12.33%, and 7.50%, respectively, which shows the effectiveness of the proposed method.

Magnetic cortical oscillations associated with subjective auditory coolness during paired comparison of time-varying HVAC sounds.

The impressions of heating, ventilation, and air conditioning (HVAC) sounds are important for the comfort people experience in their living spaces. Revealing neural substrates of the impressions induced by HVAC sounds can help to develop neurophysiological indices of the comfort of HVAC sounds. There have been numerous studies on the brain activities associated with the pleasantness of sounds, but few on the brain activities associated with the thermal impressions of HVAC sounds. Seven time-varying HVAC sounds were synthesized as stimuli using amplitude modulation. Six participants took part in subjective evaluation tests and MEG measurements. Subjective coolness of the HVAC sounds was measured using the paired comparison method. Magnetoencephalographic (MEG) measurements were carried out while participants listened to and compared the time-varying HVAC sounds. Time-frequency analysis and cluster-based analysis were performed on the MEG data. The subjective evaluation tests showed that the subjective coolness of the amplitude-modulated HVAC sounds was affected by the modulation frequency, and that there was individual difference in subjective coolness. A cluster-based analysis of the MEG data revealed that the brain activities of two participants significantly differed when they listened to cooler or less cool HVAC sounds. The frontal low-theta (4-5 Hz) and the temporal alpha (8-13 Hz) activities were observed. The frontal low-theta and the temporal alpha activities may be associated with the coolness of HVAC sound. This result suggests that the comfort level of HVAC sound can be evaluated and individually designed using neurophysiological measurements.

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

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. 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. 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. 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.

Lateralization of delta band power in magnetoencephalography (MEG) in patients with unilateral focal epilepsy and its relation to verbal fluency.

Delta power is a clinically established biomarker for abnormal brain processes. However, in patients with unilateral focal epilepsy (FE) it is still not well understood, how it relates to the epileptogenic zone and to neurocognitive functioning. The aim of the present study was thus to assess how delta power relates to the affected hemisphere, whether lateralization strength differs between the patients, and how changes in delta power correlate with cognitive functioning. We retrospectively studied patients with left (LFE) and right FE (RFE) who had undergone a resting-state magnetoencephalography measurement. We computed global and hemispheric delta power and lateralization indices and examined whether delta power correlates with semantic and letter verbal fluency (former being a marker for language and verbal memory, latter for executive functions) in 26 FE patients (15 LFE, 11 RFE) and 10 healthy controls. Delta power was increased in FE patients compared to healthy controls. However, the increase across hemispheres was related to the site of the epileptic focus: On group level, LFE patients showed higher delta power in both hemispheres, whereas RFE patients primarily exhibited higher delta power in the ipsilateral right hemisphere. Both groups showed co-fluctuations of delta power between the hemispheres. Besides, delta power correlated negatively only with letter verbal fluency. The findings confirm and provide further evidence that delta power is a marker of pathological activity and abnormal brain processes in FE. Delta power dynamics differ between patient groups, indicating that delta power could offer additional diagnostic value. The negative association of delta power and letter verbal fluency suggests that executive dysfunctions are related to low frequency abnormalities.

Electrophysiological Brain Source Imaging via Combinatorial Search with Provable Optimality

Electrophysiological Source Imaging (ESI) refers to reconstructing the underlying brain source activation from non-invasive Electroencephalography (EEG) and Magnetoencephalography (MEG) measurements on the scalp. Estimating the source locations and their extents is a fundamental tool in clinical and neuroscience applications. However, the estimation is challenging because of the ill-posedness and high coherence in the leadfield matrix as well as the noise in the EEG/MEG data. In this work, we proposed a combinatorial search framework to address the ESI problem with a provable optimality guarantee. Specifically, by exploiting the graph neighborhood information in the brain source space, we converted the ESI problem into a graph search problem and designed a combinatorial search algorithm under the framework of A* to solve it. The proposed algorithm is guaranteed to give an optimal solution to the ESI problem. Experimental results on both synthetic data and real epilepsy EEG data demonstrated that the proposed algorithm could faithfully reconstruct the source activation in the brain.

On the Geometric Sensitivity of the MEG Inversion Algorithm

Magnetoencephalography (MEG) is a non-invasive technique that measures the magnetic fields produced by brain's electrical currents. The basic inverse problem of magnetoencephalography (MEG) consists in estimating the neuronal current in the brain from the measurement of the magnetic field outside the head. The relative inversion algorithms, existing in medical devices, for the identification of excitation sources inside the brain using MEG data, are based on the assumption that the geometry of the brain-head system is spherical. Here, we present the error of identification of the dipole {({varvec{r}}}_{0}, {varvec{Q}}) using the inversion algorithm of spherical geometry. In particular, taking magnetoencephalographic measurements from realistic ellipsoidal model and using these data in a spherical model lead to a structural error. For the purpose of this paper, we make numerical investigation for different positions of the source, especially, locating sources at different depths and see how the error depends on depth. These results may have useful implications for the interpretation of the reconstructions obtained via the existing approaches.

Unsupervised representation learning of spontaneous MEG data with nonlinear ICA

Resting-state magnetoencephalography (MEG) data show complex but structured spatiotemporal patterns. However, the neurophysiological basis of these signal patterns is not fully known and the underlying signal sources are mixed in MEG measurements. Here, we developed a method based on the nonlinear independent component analysis (ICA), a generative model trainable with unsupervised learning, to learn representations from resting-state MEG data. After being trained with a large dataset from the Cam-CAN repository, the model has learned to represent and generate patterns of spontaneous cortical activity using latent nonlinear components, which reflects principal cortical patterns with specific spectral modes. When applied to the downstream classification task of audio-visual MEG, the nonlinear ICA model achieves competitive performance with deep neural networks despite limited access to labels. We further validate the generalizability of the model across different datasets by applying it to an independent neurofeedback dataset for decoding the subject's attentional states, providing a real-time feature extraction and decoding mindfulness and thought-inducing tasks with an accuracy of around 70% at the individual level, which is much higher than obtained by linear ICA or other baseline methods. Our results demonstrate that nonlinear ICA is a valuable addition to existing tools, particularly suited for unsupervised representation learning of spontaneous MEG activity which can then be applied to specific goals or tasks when labelled data are scarce.

Test-retest reliability of electroencephalographic and magnetoencephalographic measures elicited during language tasks: A literature review.

Electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings during language processing can provide relevant insights on neuroplasticity in clinical populations (including patients with aphasia). To use EEG and MEG in a longitudinal way, the outcome measures should be consistent across time in healthy individuals. Therefore, the current study provides a review on the test-retest reliability of EEG and MEG measures elicited during language paradigms in healthy adults. PubMed, Web of Science and Embase were searched for relevant articles based on specific eligibility criteria. In total, 11 articles were included in this literature review. The test-retest reliability of the P1, N1 and P2 issystematically considered to be satisfactory, whereas findings are more variable for event-related potentials/fields occurring later in time. The within subject consistency of EEG and MEG measures during language processing can be influenced by multiple variables such as the stimulus presentation mode, the offline reference choice and the required amount of cognitive resources during the task. To conclude, most of the available results are favourable regarding the longitudinal use of EEG and MEG measures elicited during language paradigms in healthy young individuals. In view to the use of these techniques in patients with aphasia, future research should focus on whether the same findings apply to different age groups.

Temporal hierarchy of cortical responses reflects core-belt-parabelt organization of auditory cortex in musicians.

Human auditory cortex (AC) organization resembles the core-belt-parabelt organization in nonhuman primates. Previous studies assessed mostly spatial characteristics; however, temporal aspects were little considered so far. We employed co-registration of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in musicians with and without absolute pitch (AP) to achieve spatial and temporal segregation of human auditory responses. First, individual fMRI activations induced by complex harmonic tones were consistently identified in four distinct regions-of-interest within AC, namely in medial Heschl's gyrus (HG), lateral HG, anterior superior temporal gyrus (STG), and planum temporale (PT). Second, we analyzed the temporal dynamics of individual MEG responses at the location of corresponding fMRI activations. In the AP group, the auditory evoked P2 onset occurred ~25ms earlier in the right as compared with the left PT and ~15ms earlier in the right as compared with the left anterior STG. This effect was consistent at the individual level and correlated with AP proficiency. Based on the combined application of MEG and fMRI measurements, we were able for the first time to demonstrate a characteristic temporal hierarchy ("chronotopy") of human auditory regions in relation to specific auditory abilities, reflecting the prediction for serial processing from nonhuman studies.

Detection of the 40 Hz auditory steady-state response with optically pumped magnetometers

Magnetoencephalography (MEG) is a functional neuroimaging technique that noninvasively detects the brain magnetic field from neuronal activations. Conventional MEG measures brain signals using superconducting quantum interference devices (SQUIDs). SQUID-MEG requires a cryogenic environment involving a bulky non-magnetic Dewar flask and the consumption of liquid helium, which restricts the variability of the sensor array and the gap between the cortical sources and sensors. Recently, miniature optically pumped magnetometers (OPMs) have been developed and commercialized. OPMs do not require cryogenic cooling and can be placed within millimeters from the scalp. In the present study, we arranged six OPM sensors on the temporal area to detect auditory-related brain responses in a two-layer magnetically shielded room. We presented the auditory stimuli of 1 kHz pure-tone bursts with 200 ms duration and obtained the M50 and M100 components of auditory-evoked fields. We delivered the periodic stimuli with a 40 Hz repetition rate and observed the gamma-band power changes and inter-trial phase coherence of auditory steady-state responses at 40 Hz. We found that the OPM sensors have a performance comparable to that of conventional SQUID-MEG sensors, and our results suggest the feasibility of using OPM sensors for functional neuroimaging and brain–computer interface applications.

Spin exchange optically pumped nuclear spin self compensation system for moving magnetoencephalography measurement.

Recording moving magnetoencephalograms (MEGs ), in which a person's head can move freely as the brain's magnetic field is recorded, has been a key subject in recent years. Here, we describe a method based on an optically pumped atomic co-magnetometer (OPACM) for recording moving MEGs. In the OPACM, hyper-polarized nuclear spins produce a magnetic field that blocks the background fluctuation low-frequency magnetic field noise while the rapidly changing MEG signal is recorded. In this study, the magnetic field compensation was studied theoretically, and we found that the compensation is closely related to several parameters such as the electron spin magnetic field, nuclear spin magnetic field, and holding magnetic field. Furthermore, the magnetic field compensation was optimized based on a theoretical model . We also experimentally studied the magnetic field compensation and measured the responses of the OPACM to different magnetic field frequencies. We show that the OPACM clearly suppresses low-frequency (under 1 Hz) magnetic fields. However, the OPACM responses to magnetic field frequencies around the band of the MEG. A magnetic field sensitivity of 3 fT/Hz1/2 was achieved. Finally, we performed a simulation of the OPACM during utilization for moving MEG recording. For comparison, the traditional compensation system for moving MEG recording is based on a coil that is around 2 m in dimension , while our compensation system is only 2 mm in dimension .

Detection of deviance in Japanese kanji compound words.

Reading fluency is based on the automatic visual recognition of words. As a manifestation of the automatic processing of words, an automatic deviance detection of visual word stimuli can be observed in the early stages of visual recognition. To clarify whether this phenomenon occurs with Japanese kanji compounds—since their lexicality is related to semantic association—we investigated the brain response by utilizing three types of deviants: differences in font type, lexically correct or incorrect Japanese kanji compound words and pseudo-kanji characters modified from correct and incorrect compounds. We employed magnetoencephalography (MEG) to evaluate the spatiotemporal profiles of the related brain regions. The study included 22 adult native Japanese speakers (16 females). The abovementioned three kinds of stimuli containing 20% deviants were presented during the MEG measurement. Activity in the occipital pole region of the brain was observed upon the detection of font-type deviance within 250 ms of stimulus onset. Although no significant activity upon detecting lexically correct/incorrect kanji compounds or pseudo-kanji character deviations was observed, the activity in the posterior transverse region of the collateral sulcus (pCoS)—which is a fusiform neighboring area—was larger when detecting lexically correct kanji compounds than when detecting pseudo-kanji characters. Taken together, these results support the notion that the automatic detection of deviance in kanji compounds may be limited to a low-level feature, such as the stimulus stroke thickness.

Mapping the Imagined Speech Location on the Brain Scalp Through Magnetoencephalography (MEG)

People with autism speech disorders, paralysis, or muteness cannot communicate via speech. These individuals can think but cannot express and create overt speech. As a result, the system must obtain and interpret the electric and magnetic signal developed at the Scalp during imagined or intended speech. These magnetic signals are termed MEG (Magnetoencephalography), and electrical signals are named EEG (Electroencephalography). This technology must be wearable, non-invasive, and easy to use daily. To make the system wearable, the location of the electrode is essential. Since the EEG has good temporal resolution but poor spatial resolution, mapping the area on the Scalp of imagined speech is difficult. Similarly, the MEG has an excellent spatial resolution. But the MEG signal is weak, only up to 10-9 T to detect. Therefore, the delicate magnetic field in the brain due to imagined speech can be seen only by an OPM (Optically Pumped Magnetometer) or SQUID sensor. This paper explores a slightly different type of sensor based on an optically pumped magnetometer with a low cost as the cost of SQUID and OPM is large. A self-made magnetic sensor is used to map the location on the Scalp. The MEG and EEG measurement has been done in terms of PSD (Power Spectral Density). An analysis calculates the deviation compared with a different located point on the Scalp. The area on the Scalp of imagined speech was selected with the help of a literature review. The EEG measurement has done to confirm the location.