Search

This study investigates the complex relationship between upper limb movement direction and macroscopic neural signals in the brain, which is critical for understanding brain-computer interfaces (BCI). Conventional BCI research has primarily focused on a local area, such as the contralateral primary motor cortex (M1), relying on the population-based decoding method with microelectrode arrays. In contrast, macroscopic approaches such as electroencephalography (EEG) and magnetoencephalography (MEG) utilize numerous electrodes to cover broader brain regions. This study probes the potential differences in the mechanisms of microscopic and macroscopic methods. It is important to determine which neural activities effectively predict movements. To investigate this, we analyzed MEG data from nine right-handed participants while performing arm-reaching tasks. We employed dynamic statistical parametric mapping (dSPM) to estimate source activity and built a decoding model composed of long short-term memory (LSTM) and a multilayer perceptron to predict movement trajectories. This model achieved a high correlation coefficient of 0.79 between actual and predicted trajectories. Subsequently, we identified brain regions sensitive to predicting movement direction using the integrated gradients (IG) method, which assesses the predictive contribution of each source activity. The resulting salience map demonstrated a distribution without significant differences across motor-related regions, including M1. Predictions based solely on M1 activity yielded a correlation coefficient of 0.42, nearly half as effective as predictions incorporating all source activities. This suggests that upper limb movements are influenced by various factors such as movement coordination, planning, body and target position recognition, and control, beyond simple muscle activity. All of the activities are needed in the decoding model using macroscopic signals. Our findings also revealed that contralateral and ipsilateral hemispheres contribute equally to movement prediction, implying that BCIs could potentially benefit patients with brain damage in the contralateral hemisphere by utilizing brain signals from the ipsilateral hemisphere. In conclusion, this study demonstrates that macroscopic activity from large brain regions significantly contributes to predicting upper limb movement. Non-invasive BCI systems would require a comprehensive collection of neural signals from multiple brain regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors whose names are listed in “Macroscopic brain dynamics beyond contralateral primary motor cortex for movement prediction” certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Although one can recognize the environment by soundscape substituting vision to auditory signal, whether subjects could perceive the soundscape as visual or visual-like sensation has been questioned. In this study, we investigated hierarchical process to elucidate the recruitment mechanism of visual areas by soundscape stimuli in blindfolded subjects. Twenty-two healthy subjects were repeatedly trained to recognize soundscape stimuli converted by visual shape information of letters. An effective connectivity method called dynamic causal modeling (DCM) was employed to reveal how the brain was hierarchically organized to recognize soundscape stimuli. The visual mental imagery model generated cortical source signals of five regions of interest better than auditory bottom-up, cross-modal perception, and mixed models. Spectral couplings between brain areas in the visual mental imagery model were analyzed. While within-frequency coupling is apparent in bottom-up processing where sensory information is transmitted, cross-frequency coupling is prominent in top-down processing, corresponding to the expectation and interpretation of information. Sensory substitution in the brain of blindfolded subjects derived visual mental imagery by combining bottom-up and top-down processing., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Tactile and movement-related somatosensory perceptions are crucial for our daily lives and survival. Although the primary somatosensory cortex is thought to be the key structure of somatosensory perception, various cortical downstream areas are also involved in somatosensory perceptual processing. However, little is known about whether cortical networks of these downstream areas can be dissociated depending on each perception, especially in human. We address this issue by combining data from direct cortical stimulation (DCS) for eliciting somatosensation and data from high-gamma band (HG) elicited during tactile stimulation and movement tasks. We found that artificial somatosensory perception is elicited not only from conventional somatosensory-related areas such as the primary and secondary somatosensory cortices but also from a widespread network including superior/inferior parietal lobules and premotor cortex. Interestingly, DCS on the dorsal part of the fronto-parietal area including superior parietal lobule and dorsal premotor cortex often induces movement-related somatosensations, whereas that on the ventral one including inferior parietal lobule and ventral premotor cortex generally elicits tactile sensations. Furthermore, the HG mapping results of the movement and passive tactile stimulation tasks revealed considerable similarity in the spatial distribution between the HG and DCS functional maps. Our findings showed that macroscopic neural processing for tactile and movement-related perceptions could be segregated., Competing Interests: Declaration of Competing Interest The authors declare that there are no competing financial interests regarding the publication of this paper., (Copyright © 2023. Published by Elsevier Inc.)

Cerebral cortical representation of motor kinematics is crucial for understanding human motor behavior, potentially extending to efficient control of the brain-computer interface. Numerous single-neuron studies have found the existence of a relationship between neuronal activity and motor kinematics such as acceleration, velocity, and position. Despite differences between kinematic characteristics, it is hard to distinguish neural representations of these kinematic characteristics with macroscopic functional images such as electroencephalography (EEG) and magnetoencephalography (MEG). The reason might be because cortical signals are not sensitive enough to segregate kinematic characteristics due to their limited spatial and temporal resolution. Considering different roles of each cortical area in producing movement, there might be a specific cortical representation depending on characteristics of acceleration, velocity, and position. Recently, neural network modeling has been actively pursued in the field of decoding. We hypothesized that neural features of each kinematic parameter could be identified with a high-performing model for decoding with an explainable AI method. Time-series deep neural network (DNN) models were used to measure the relationship between cortical activity and motor kinematics during reaching movement. With DNN models, kinematic parameters of reaching movement in a 3D space were decoded based on cortical source activity obtained from MEG data. An explainable artificial intelligence (AI) method was then adopted to extract the map of cortical areas, which strongly contributed to decoding each kinematics from DNN models. We found that there existed differed as well as shared cortical areas for decoding each kinematic attribute. Shared areas included bilateral supramarginal gyri and superior parietal lobules known to be related to the goal of movement and sensory integration. On the other hand, dominant areas for each kinematic parameter (the contralateral motor cortex for acceleration, the contralateral parieto-frontal network for velocity, and bilateral visuomotor areas for position) were mutually exclusive. Regarding the visuomotor reaching movement, the motor cortex was found to control the muscle force, the parieto-frontal network encoded reaching movement from sensory information, and visuomotor areas computed limb and gaze coordination in the action space. To the best of our knowledge, this is the first study to discriminate kinematic cortical areas using DNN models and explainable AI., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Little is known about the functional substrate for memory function differences in patients with left or right mesial temporal lobe epilepsy (mTLE) associated with hippocampal sclerosis (HS) from an electrophysiological perspective. To characterize these differences, we hypothesized that hippocampal theta connectivity in the resting-state might be different between patients with left and right mTLE with HS and be correlated with memory performance., Methods: Resting-state hippocampal theta connectivity, identified via whole-brain magnetoencephalography, was evaluated. Connectivity and memory function in 41 patients with mTLE with HS (left mTLE=22; right mTLE=19) were compared with those in 46 age-matched healthy controls and 28 patients with focal cortical dysplasia (FCD) but without HS., Results: Connectivity between the right hippocampus and the left middle frontal gyrus was significantly stronger in patients with right mTLE than in patients with left mTLE. Moreover, this connectivity was positively correlated with delayed verbal recall and recognition scores in patients with mTLE. Patients with left mTLE had greater delayed recall impairment than patients with right mTLE and FCD. Similarly, delayed recognition performance was worse in patients with left mTLE than in patients with right mTLE and FCD. No significant differences in memory function between patients with right mTLE and FCD were detected. Patients with right mTLE showed significantly stronger hippocampal theta connectivity between the right hippocampus and left middle frontal gyrus than patients with FCD and left mTLE., Conclusion: Our results suggest that right hippocampal-left middle frontal theta connectivity could be a functional substrate that can account for differences in memory function between patients with left and right mTLE. This functional substrate might be related to different compensatory mechanisms against the structural hippocampal lesions in left and right mTLE groups. Given the positive correlation between connectivity and delayed verbal memory function, hemispheric-specific hippocampal-frontal theta connectivity assessment could be useful as an electrophysiological indicator of delayed verbal memory function in patients with mTLE with HS., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Alcohol's function as a regulator of emotions has long been denoted in figures of speech, most famously 'in vino, veritas' (in wine, truth). In contrast, we ask whether an individual's self-reported alcohol consumption and related attitudes can be correlated with the words they use to write about alcohol. Participants completed an open-ended essay as part of a survey on alcohol attitudes and behaviors. We used a computerized technique, the Meaning Extraction Method, to summarize the responses into thematic tropes, and correlated these with quantitative measurements of demographics, attitudes and behaviors. Participants were recruited using a random population postal survey in the UK (n=1001). Principal components analysis identified regular co-occurring words, to locate themes in the responses. Seven themes were identified that corresponded to both negative and positive aspects of alcohol consumption ranging from concern for the influence of alcohol on others (e.g., children and family) to participants' own enjoyment of alcohol (e.g., social drinking). Small but significant correlations suggested a relationship between the essay responses and individual consumption patterns and attitudes., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

In mammals, human chorionic gonadotropin (hCG), a luteinizing hormone (LH) analogue, induces MAPK3/1 phosphorylation in the granulosa cells and this event is largely dependent on epidermal growth factor receptor (EGFR) activity. However, whether this mechanism also works in other vertebrates such as fish remains unknown. Here, we showed that treatment of cultured zebrafish ovarian follicle cells with hCG also resulted in MAPK3/1 phosphorylation without affecting the total protein level of MAPK3/1. The phosphorylation level peaked at 5 min and then declined to the basal level after 40 min of hCG treatment. Further experiment showed that H89 (a PKA inhibitor) could abolish hCG-stimulated MAPK3/1 phosphorylation, but had no effect on EGF-induced phosphorylation, suggesting a mediating role for cAMP/PKA in hCG activation of MAPK3/1. On the other hand, AG1478 (an EGFR inhibitor) completely blocked EGF-stimulated MAPK3/1 phosphorylation, but had no effect on the hCG-induced MAPK3/1 phosphorylation. These data indicate that similar to its action in mammals, hCG/LH also stimulated MAPK3/1 phosphorylation in the zebrafish ovarian follicle cells; however, unlike the situation in the mammalian ovary, the hCG-stimulated MAPK3/1 phosphorylation in cultured zebrafish ovarian follicle cells was independent of EGFR., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Somatosensory evoked responses are known to be modulated by previous interfering stimuli. Here, we first investigated the modulatory effects of interfering stimuli with different intensities on somatosensory evoked magnetic field in human primary (S1) and secondary (S2) somatosensory cortices. In the control condition of the study, test stimulus, set to strong intensity, was delivered to the left median nerve. Interfering stimuli with three different levels of intensity from weak (WI) through moderate (MI) and finally to strong (SI) were interspersed to the left median nerve between the test stimuli in each interfering condition. The cortical responses to the test stimulus were modeled with equivalent current dipoles in the contralateral S1 and bilateral S2 cortices from 17 subjects. The amplitude of the N20m deflection from the S1 was not changed by any interfering stimuli, whereas the amplitude of later P35m deflection was reduced by MI stimulus. The amplitude of P60m deflection was reduced by MI and SI stimuli. The extent of amplitude reduction of the bilateral S2 response was markedly increased as intensity of interfering stimuli increased from weak to moderate, but further reduction by the SI stimuli compared to MI stimuli was not observed. Those results indicated that somatosensory cortical activation in the S1 (P35m and P60m) and S2 were modulated by intensity of interfering stimuli. Our findings of a greater gating effect on the bilateral S2 compared to the contralateral S1 indicate that S2 may play an important role in temporal integration of different intensity levels of somatosensory inputs., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The purpose of this study was to develop a novel approach for objectively estimating the locations of ictal onset zones by electrocorticography (ECoG). Conventional ECoG analyses have been performed using a 2-D space comprised of intracranial electrodes. Thus, despite the fact that ECoG data have much higher signal-to-noise ratios than electroencephalographic data, ECoG inherently requires a priori information to locate the electrodes, and thus, it is difficult to estimate the depth of epileptogenic foci using this technique. Accordingly, the authors considered that a 3-D approach is needed to determine the presence of an epileptogenic focus in the complex structure of the cortex. However, no source localization procedure has been devised to determine the location of a primary ictal source using ECoG. The authors utilized a spatiotemporal source localization technique using the first principal vectors. A directed transfer function was then employed for the time series of potential ictal sources to compute their causal inter-relationships, from which the primary sources responsible for ictal onset could be localized. Monte-Carlo simulation studies were performed to validate the feasibility and reliability of the proposed ECoG source localization technique, and the obtained results demonstrated that the mean of localization errors with a signal to white Gaussian noise ratio of 5 dB did not exceed 5 mm, even when the source was located approximately 20 mm away from the nearest electrode. This validated ictal source localization approach was applied to a number of ictal ECoG data sets from six successfully operated epilepsy patients. The resultant 3-D ictal source locations were found to coincide with surgical resection areas and with traditional 2-D electrode-based source estimates. The authors believe that this proposed ECoG-based ictal source localization method will be found useful, especially when ictal sources are located in a deep sulcus or beyond recording planes., (Copyright 2010 Elsevier Inc. All rights reserved.)

We investigated familiarity with, knowledge of, and attitudes toward epilepsy among teachers in elementary schools in Korea, where there is profound prejudice against epilepsy. Most of the teachers thought that epilepsy is a genetic disease. They agreed that children with epilepsy (CWE) should attend regular classes (although with some restriction of school activities) because their academic achievement would be comparable to that of children without epilepsy. However, half of the teachers opposed having CWE in their own classes because they feared a child having a seizure during class and they felt they lacked knowledge of first-aid for seizures. Those teachers who had inaccurate clinical knowledge of epilepsy also demonstrated negative attitudes toward the marriage and employment of persons with epilepsy. We conclude that information about epilepsy should be included in teacher training programs so as to increase their level of knowledge of epilepsy and correct prejudices against epilepsy., ((c) 2009 Elsevier Inc. All rights reserved.)

Some patients with epilepsy have difficulty performing complex language tasks due to the long duration of the disease and cognitive side effects of antiepileptic drugs. Therefore, a simple passive paradigm would be useful for determining the language dominance lateralization in epilepsy patients. The goal of this study was to develop an efficient and non-invasive analysis method for determining language dominance in epilepsy patients. To this end, magnetoencephalography was performed while an auditory stimulus sequence comprised of two one-syllable spoken words was presented to 17 subjects in an oddball paradigm without subject response. The time-frequency difference between deviant and standard sounds was then analyzed in the source space using a spatial filtering method that was based on minimum-norm estimation. The laterality index was estimated in language-related regions of interest (ROI). The results were compared to the traditional lateralization method using the Wada test. Beta band oscillation activity decreased during deviant stimulation, and the lateralization of the decrease was in good agreement with the Wada test, in the posterior part of the inferior frontal gyrus in 94% of the subjects and in the posterior part of the superior temporal gyrus in 71% of the subjects. In conclusion, the ROI-based time-frequency difference between deviant and standard sounds can be used to assess language lateralization in accordance with the Wada test.

This study evaluated quantitatively the synchronization between the magnetoencephalography (MEG) and electromyography (EMG) signals and developed a novel method for the determination of the synchronization in order to increase the reliability of the source analysis of the oscillatory motor cortex activity. The new method is based on our observation that there are large variances in the time lag due to relatively low muscle-cortex synchronization which reduces the signal-to-noise ratio of the MEG signal when averaged in direct synchrony with the rectified EMG peaks. To improve the localization of the motor cortex activity, time-frequency analysis was performed for each epoch coinciding with an EMG peak to reject the weak oscillatory activity and artifacts. In addition, the MEG signals were shifted to maximize the coherence between MEG and rectified EMG by determining for each accepted epoch the time lag resulting in a maximum cross-correlation. An experiment was carried out using 30 subjects in order to determine the applicability of this method to a real situation. The synchronization and the results of the corresponding source analysis based on the novel method were compared with the data obtained using the non-phase-shift method and Hilbert approach detecting EMG phase. The results showed that the synchronization was significantly enhanced and the signal-to-noise ratio of the MEG signals improved, and that the localized dipoles of all subjects were well clustered at the motor cortex. This method, based on shifting the MEG epochs according to the simultaneously measured time lag, considerably improves the performance of the averaging and localization of the rhythmic activity of the motor cortex.