Differential Formation of Motor Cortical Dynamics during Movement Preparation According to the Predictability of Go Timing.

The motor cortex not only executes but also prepares movement, as motor cortical neurons exhibit preparatory activity that predicts upcoming movements. In movement preparation, animals adopt different strategies in response to uncertainties existing in nature such as the unknown timing of when a predator will attack-an environmental cue informing "go." However, how motor cortical neurons cope with such uncertainties is less understood. In this study, we aim to investigate whether and how preparatory activity is altered depending on the predictability of "go" timing. We analyze firing activities of the anterior lateral motor cortex in male mice during two auditory delayed-response tasks each with predictable or unpredictable go timing. When go timing is unpredictable, preparatory activities immediately reach and stay in a neural state capable of producing movement anytime to a sudden go cue. When go timing is predictable, preparation activity reaches the movement-producible state more gradually, to secure more accurate decisions. Surprisingly, this preparation process entails a longer reaction time. We find that as preparatory activity increases in accuracy, it takes longer for a neural state to transition from the end of preparation to the start of movement. Our results suggest that the motor cortex fine-tunes preparatory activity for more accurate movement using the predictability of go timing.

Quantifying the contribution of subject and group factors in brain activation.

Research in neuroscience often assumes universal neural mechanisms, but increasing evidence points toward sizeable individual differences in brain activations. What remains unclear is the extent of the idiosyncrasy and whether different types of analyses are associated with different levels of idiosyncrasy. Here we develop a new method for addressing these questions. The method consists of computing the within-subject reliability and subject-to-group similarity of brain activations and submitting these values to a computational model that quantifies the relative strength of group- and subject-level factors. We apply this method to a perceptual decision-making task (n = 50) and find that activations related to task, reaction time, and confidence are influenced equally strongly by group- and subject-level factors. Both group- and subject-level factors are dwarfed by a noise factor, though higher levels of smoothing increases their contributions relative to noise. Overall, our method allows for the quantification of group- and subject-level factors of brain activations and thus provides a more detailed understanding of the idiosyncrasy levels in brain activations.

Effect of Static Posture on Online Performance of P300-Based BCIs for TV Control.

To implement a practical brain-computer interface (BCI) for daily use, continuing changes in postures while performing daily tasks must be considered in the design of BCIs. To examine whether the performance of a BCI could depend on postures, we compared the online performance of P300-based BCIs built to select TV channels when subjects took sitting, recline, supine, and right lateral recumbent postures during BCI use. Subjects self-reported the degrees of interference, comfort, and familiarity after BCI control in each posture. We found no significant difference in the BCI performance as well as the amplitude and latency of P300 and N200 among the four postures. However, when we compared BCI accuracy outcomes normalized within individuals between two cases where subjects reported relatively more positively or more negatively about using the BCI in a particular posture, we found higher BCI accuracy in those postures for which individual subjects reported more positively. As a result, although the change of postures did not affect the overall performance of P300-based BCIs, the BCI performance varied depending on the degree of postural comfort felt by individual subjects. Our results suggest considering the postural comfort felt by individual BCI users when using a P300-based BCI at home.

Improvement of P300-Based Brain-Computer Interfaces for Home Appliances Control by Data Balancing Techniques.

The oddball paradigm used in P300-based brain-computer interfaces (BCIs) intrinsically poses the issue of data imbalance between target stimuli and nontarget stimuli. Data imbalance can cause overfitting problems and, consequently, poor classification performance. The purpose of this study is to improve BCI performance by solving this data imbalance problem with sampling techniques. The sampling techniques were applied to BCI data in 15 subjects controlling a door lock, 15 subjects an electric light, and 14 subjects a Bluetooth speaker. We explored two categories of sampling techniques: oversampling and undersampling. Oversampling techniques, including random oversampling, synthetic minority oversampling technique (SMOTE), borderline-SMOTE, support vector machine (SVM) SMOTE, and adaptive synthetic sampling, were used to increase the number of samples for the class of target stimuli. Undersampling techniques, including random undersampling, neighborhood cleaning rule, Tomek's links, and weighted undersampling bagging, were used to reduce the class size of nontarget stimuli. The over- or undersampled data were classified by an SVM classifier. Overall, some oversampling techniques improved BCI performance while undersampling techniques often degraded performance. Particularly, using borderline-SMOTE yielded the highest accuracy (87.27%) and information transfer rate (8.82 bpm) across all three appliances. Moreover, borderline-SMOTE led to performance improvement, especially for poor performers. A further analysis showed that borderline-SMOTE improved SVM by generating more support vectors within the target class and enlarging margins. However, there was no difference in the accuracy between borderline-SMOTE and the method of applying the weighted regularization parameter of the SVM. Our results suggest that although oversampling improves performance of P300-based BCIs, it is not just the effect of the oversampling techniques, but rather the effect of solving the data imbalance problem.

Anti-adipogenic and anti-obesity activities of purpurin in 3T3-L1 preadipocyte cells and in mice fed a high-fat diet.

BACKGROUND: The body responds to overnutrition by converting stem cells to adipocytes. In vitro and in vivo studies have shown polyphenols and other natural compounds to be anti-adipogenic, presumably due in part to their antioxidant properties. Purpurin is a highly antioxidative anthraquinone and previous studies on anthraquinones have reported numerous biological activities in cells and animals. Anthraquinones have also been used to stimulate osteoblast differentiation, an inversely-related process to that of adipocyte differentiation. We propose that due to its high antioxidative properties, purpurin administration might attenuate adipogenesis in cells and in mice. METHODS: Our study will test the effect purpurin has on adipogenesis using both in vitro and in vivo models. The in vitro model consists of tracking with various biomarkers, the differentiation of pre-adipocyte to adipocytes in cell culture. The compound will then be tested in mice fed a high-fat diet. Murine 3T3-L1 preadipocyte cells were stimulated to differentiate in the presence or absence of purpurin. The following cellular parameters were measured: intracellular reactive oxygen species (ROS), membrane potential of the mitochondria, ATP production, activation of AMPK (adenosine 5'-monophosphate-activated protein kinase), insulin-induced lipid accumulation, triglyceride accumulation, and expression of PPARγ (peroxisome proliferator activated receptor-γ) and C/EBPα (CCAAT enhancer binding protein α). In vivo, mice were fed high fat diets supplemented with various levels of purpurin. Data collected from the animals included anthropometric data, glucose tolerance test results, and postmortem plasma glucose, lipid levels, and organ examinations. RESULTS: The administration of purpurin at 50 and 100 µM in 3T3-L1 cells, and at 40 and 80 mg/kg in mice proved to be a sensitive range: the lower concentrations affected several measured parameters, whereas at the higher doses purpurin consistently mitigated biomarkers associated with adipogenesis, and weight gain in mice. Purpurin appears to be an effective antiadipogenic compound. CONCLUSION: The anthraquinone purpurin has potent in vitro anti-adipogenic effects in cells and in vivo anti-obesity effects in mice consuming a high-fat diet. Differentiation of 3T3-L1 cells was dose-dependently inhibited by purpurin, apparently by AMPK activation. Mice on a high-fat diet experienced a dose-dependent reduction in induced weight gain of up to 55%.

A simulation study on the effects of neuronal ensemble properties on decoding algorithms for intracortical brain-machine interfaces.

BACKGROUND: Intracortical brain-machine interfaces (BMIs) harness movement information by sensing neuronal activities using chronic microelectrode implants to restore lost functions to patients with paralysis. However, neuronal signals often vary over time, even within a day, forcing one to rebuild a BMI every time they operate it. The term "rebuild" means overall procedures for operating a BMI, such as decoder selection, decoder training, and decoder testing. It gives rise to a practical issue of what decoder should be built for a given neuronal ensemble. This study aims to address it by exploring how decoders' performance varies with the neuronal properties. To extensively explore a range of neuronal properties, we conduct a simulation study. METHODS: Focusing on movement direction, we examine several basic neuronal properties, including the signal-to-noise ratio of neurons, the proportion of well-tuned neurons, the uniformity of their preferred directions (PDs), and the non-stationarity of PDs. We investigate the performance of three popular BMI decoders: Kalman filter, optimal linear estimator, and population vector algorithm. RESULTS: Our simulation results showed that decoding performance of all the decoders was affected more by the proportion of well-tuned neurons that their uniformity. CONCLUSIONS: Our study suggests a simulated scenario of how to choose a decoder for intracortical BMIs in various neuronal conditions.

The composition of a bioprocessed shiitake (Lentinus edodes) mushroom mycelia and rice bran formulation and its antimicrobial effects against Salmonella enterica subsp. enterica serovar Typhimurium strain SL1344 in macrophage cells and in mice.

BACKGROUND: Human infection by pathogenic Salmonella bacteria can be acquired by consuming of undercooked meat products and eggs. Antimicrobial resistance against antibiotics used in medicine is also a major concern. To help overcome these harmful effects on microbial food safety and human health, we are developing novel antimicrobial food-compatible formulations, one of which is described in the present study. METHODS: The composition of a bioprocessed (fermented) rice bran extract (BPRBE) from Lentinus edodes liquid mycelia culture was evaluated using gas chromatography and mass spectrometry, and the mechanism of its antibacterial effect against Salmonella Typhimurium, strain SL1344 was investigated in macrophage cells and in mice. RESULTS: BPRBE stimulated uptake of the bacteria into RAW 264.7 murine macrophage cells. Activation of the cells was confirmed by increases in NO production resulting from the elevation of inducible nitric oxide synthase (iNOS) mRNA, and in protein expression. Salmonella infection down-regulated the expression of the following protein biomarkers of autophagy (a catabolic process for stress adaptation of cellular components): Beclin-1, Atg5, Atg12, Atg16, LC3-I and LC3-II. BPRBE promoted the upregulation of protein expressions that induced bacterial destruction in autolysosomes of RAW 264.7 cells. ELISA analysis of interferon IFN-ß showed that inflammatory cytokine secretion and bactericidal activity had similar profiles, suggesting that BPRBE enhances cell-autonomous and systemic bactericidal activities via autophagic capture of Salmonella. The treatment also elicited increased excretion of bacteria in feces and their decreased translocation to internal organs (cecum, mesenteric lymph node, spleen, and liver). CONCLUSIONS: The antibiotic mechanism of BPRBE involves the phagocytosis of extracellular bacteria, autophagic capture of intracellular bacteria, and prevention of translocation of bacteria across the intestinal epithelial cells. The new bioprocessing combination of mushroom mycelia and rice brans forms a potentially novel food formulation with in vivo antimicrobial properties that could serve as a functional antimicrobial food and medical antibiotic.

A Wearable Wrist Band-Type System for Multimodal Biometrics Integrated with Multispectral Skin Photomatrix and Electrocardiogram Sensors.

Multimodal biometrics are promising for providing a strong security level for personal authentication, yet the implementation of a multimodal biometric system for practical usage need to meet such criteria that multimodal biometric signals should be easy to acquire but not easily compromised. We developed a wearable wrist band integrated with multispectral skin photomatrix (MSP) and electrocardiogram (ECG) sensors to improve the issues of collectability, performance and circumvention of multimodal biometric authentication. The band was designed to ensure collectability by sensing both MSP and ECG easily and to achieve high authentication performance with low computation, efficient memory usage, and relatively fast response. Acquisition of MSP and ECG using contact-based sensors could also prevent remote access to personal data. Personal authentication with multimodal biometrics using the integrated wearable wrist band was evaluated in 150 subjects and resulted in 0.2% equal error rate ( EER ) and 100% detection probability at 1% FAR (false acceptance rate) ( PD . 1 ), which is comparable to other state-of-the-art multimodal biometrics. An additional investigation with a separate MSP sensor, which enhanced contact with the skin, along with ECG reached 0.1% EER and 100% PD . 1 , showing a great potential of our in-house wearable band for practical applications. The results of this study demonstrate that our newly developed wearable wrist band may provide a reliable and easy-to-use multimodal biometric solution for personal authentication.

Structure-Antioxidative and Anti-Inflammatory Activity Relationships of Purpurin and Related Anthraquinones in Chemical and Cell Assays.

Anthraquinone (9,10-anthraquinone) and several hydroxy derivatives, including purpurin (1,2,4-trihydroxyanthraquinone), anthrarufin (1,5-dihydroxyanthraquinone), and chrysazin (1,8-dihydroxyanthraquinone), were evaluated for antioxidative and anti-inflammatory activities in chemical assays and mammalian cells (murine macrophage RAW 264.7 cells). Several tests were used to assess their activities: 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical; ABTS radical cation; hydrogen peroxide scavenging; reduction of potassium ferricyanide; chelation of ferrous ions; inhibition of lipid peroxidation; inhibition of nitric oxide generation; scavenging of the intracellular hydroxyl radical; expression of NLRP3 polypeptide for inflammasome assembly; and quantitation of proinflammatory cytokine interleukin 1ß (IL-1ß) for inflammasome activation. The results show that purpurin, from the root of the madder plant (Rubia tinctorum L.), exhibited the highest antioxidative activity in both chemical and cultured cell antioxidant assays. The antioxidative activities of the other three anthraquinones were lower than that of purpurin. In addition, purpurin could down-regulate NLRP3 inflammasome assembly and activation, suggesting that it might protect foods against oxidative damage and prevent in vivo oxidative stress and inflammation. Structure-activity relationships and the significance of the results for food quality and human health are discussed.

Adaptation of cortical activity to sustained pressure stimulation on the fingertip.

BACKGROUND: Tactile adaptation is a phenomenon of the sensory system that results in temporal desensitization after an exposure to sustained or repetitive tactile stimuli. Previous studies reported psychophysical and physiological adaptation where perceived intensity and mechanoreceptive afferent signals exponentially decreased during tactile adaptation. Along with these studies, we hypothesized that somatosensory cortical activity in the human brain also exponentially decreased during tactile adaptation. The present neuroimaging study specifically investigated temporal changes in the human cortical responses to sustained pressure stimuli mediated by slow-adapting type I afferents. METHODS: We applied pressure stimulation for up to 15 s to the right index fingertip in 21 healthy participants and acquired functional magnetic resonance imaging (fMRI) data using a 3T MRI system. We analyzed cortical responses in terms of the degrees of cortical activation and inter-regional connectivity during sustained pressure stimulation. RESULTS: Our results revealed that the degrees of activation in the contralateral primary and secondary somatosensory cortices exponentially decreased over time and that intra- and inter-hemispheric inter-regional functional connectivity over the regions associated with tactile perception also linearly decreased or increased over time, during pressure stimulation. CONCLUSION: These results indicate that cortical activity dynamically adapts to sustained pressure stimulation mediated by SA-I afferents, involving changes in the degrees of activation on the cortical regions for tactile perception as well as in inter-regional functional connectivity among them. We speculate that these adaptive cortical activity may represent an efficient cortical processing of tactile information.

Intra- and inter-hemispheric effective connectivity in the human somatosensory cortex during pressure stimulation.

BACKGROUND: Slow-adapting type I (SA-I) afferents deliver sensory signals to the somatosensory cortex during low-frequency (or static) mechanical stimulation. It has been reported that the somatosensory projection from SA-I afferents is effective and reliable for object grasping and manipulation. Despite a large number of neuroimaging studies on cortical activation responding to tactile stimuli mediated by SA-I afferents, how sensory information of such tactile stimuli flows over the somatosensory cortex remains poorly understood. In this study, we investigated tactile information processing of pressure stimuli between the primary (SI) and secondary (SII) somatosensory cortices by measuring effective connectivity using dynamic causal modeling (DCM). We applied pressure stimuli for 3 s to the right index fingertip of healthy participants and acquired functional magnetic resonance imaging (fMRI) data using a 3T MRI system. RESULTS: DCM analysis revealed intra-hemispheric effective connectivity between the contralateral SI (cSI) and SII (cSII) characterized by both parallel (signal inputs to both cSI and cSII) and serial (signal transmission from cSI to cSII) pathways during pressure stimulation. DCM analysis also revealed inter-hemispheric effective connectivity among cSI, cSII, and the ipsilateral SII (iSII) characterized by serial (from cSI to cSII) and SII-level (from cSII to iSII) pathways during pressure stimulation. CONCLUSIONS: Our results support a hierarchical somatosensory network that underlies processing of low-frequency tactile information. The network consists of parallel inputs to both cSI and cSII (intra-hemispheric), followed by serial pathways from cSI to cSII (intra-hemispheric) and from cSII to iSII (inter-hemispheric). Importantly, our results suggest that both serial and parallel processing take place in tactile information processing of static mechanical stimuli as well as highlighting the contribution of callosal transfer to bilateral neuronal interactions in SII.

Development of a simple pressure and heat stimulator for intra- and interdigit functional magnetic resonance imaging.

For this study, we developed a simple pressure and heat stimulator that can quantitatively control pressure and provide heat stimulation to intra- and interdigit areas. The developed stimulator consists of a control unit, drive units, and tactors. The control unit controls the stimulation parameters, such as stimulation types, intensity, time, and channel, and transmits a created signal of stimulation to the drive units. The drive units operate pressure and heat tactors in response to commands from the control unit. The pressure and heat tactors can display various stimulation intensities quantitatively, apply stimulation continuously, and adjust the stimulation areas. Additionally, they can easily be attached to and detached from the digits. The developed pressure and heat stimulator is small in total size, easy to install, and inexpensive to manufacture. The new stimulator operated stably in a magnetic resonance imaging (MRI) environment without affecting the obtained images. A preliminary functional magnetic resonance imaging (fMRI) experiment confirmed that differences in activation of somatosensory areas were induced from the pressure and heat stimulation. The developed pressure and heat stimulator is expected to be utilized for future intra- and interdigit fMRI studies on pressure and heat stimulation.

Disruption of alpha oscillation propagation in patients with schizophrenia.

OBJECTIVE: Propagation of electroencephalogram (EEG) oscillations, often referred to as traveling waves, reflects the role of brain oscillations in neural information transmission. This propagation can be distorted by brain disorders such as schizophrenia that features disconnection of neural information transmission (i.e., disconnection syndrome). However, this possibility of the disruption of EEG oscillation propagation in patients with schizophrenia remains largely unexplored. METHODS: Using a publicly shared dataset (N = 19 and 24; patients with schizophrenia and healthy controls, respectively), we investigated EEG oscillation propagation by analyzing the local phase gradients (LPG) of alpha (8-12 Hz) oscillations in both healthy participants and patients with schizophrenia. RESULTS: Our results showed significant directionality in the propagation of alpha oscillations in healthy participants. Specifically, alpha oscillations propagated in an anterior-to-posterior direction along mid-line and a posterior-to-anterior direction laterally. In patients with schizophrenia, some of alpha oscillation propagation were notably disrupted, particularly in the central midline area where alpha oscillations propagated from anterior to posterior areas. CONCLUSION: Our finding lends support to the hypothesis of a disconnection syndrome in schizophrenia, underscoring a disruption in the anterior-to-posterior propagation of alpha oscillations. SIGNIFICANCE: This study identified disruption of alpha oscillation propagation observed in scalp EEG as a biomarker for schizophrenia.

A method to find temporal structure of neuronal coactivity patterns with across-trial correlations.

BACKGROUND: The across-trial correlation of neurons' coactivity patterns emerges to be important for information coding, but methods for finding their temporal structures remain largely unexplored. NEW METHOD: In the present study, we propose a method to find time clusters in which coactivity patterns of neurons are correlated across trials. We transform the multidimensional neural activity at each timing into a coactivity pattern of binary states, and predict the coactivity patterns at different timings. We devise a method suitable for these coactivity pattern predictions, call general event prediction. Cross-temporal prediction accuracy is then used to estimate across-trial correlations between coactivity patterns at two timings. We extract time clusters from the cross-temporal prediction accuracy by a modified k-means algorithm. RESULTS: The feasibility of the proposed method is verified through simulations based on ground truth. We apply the proposed method to a calcium imaging dataset recorded from the motor cortex of mice, and demonstrate time clusters of motor cortical coactivity patterns during a motor task. COMPARISON WITH EXISTING METHODS: While the existing cosine similarity method, which does not account for across-trial correlation, shows temporal structures only for contralateral neural responses, the proposed method reveals those for both contralateral and ipsilateral neural responses, demonstrating the effect of across-trial correlations. CONCLUSIONS: This study introduces a novel method for measuring the temporal structure of neuronal ensemble activity.

Meditation-type specific reduction in infra-slow activity of electroencephalogram.

Purpose: Meditation is renowned for its positive effects on cognitive abilities and stress reduction. It has been reported that the amplitude of electroencephalographic (EEG) infra-slow activity (ISA, < 0.1 Hz) is reduced as the stress level decreases. Consequently, we aimed to determine if EEG ISA amplitude decreases as a result of meditation practice across various traditions. Methods: To this end, we analyzed an open dataset comprising EEG data acquired during meditation sessions from experienced practitioners in the Vipassana tradition-which integrates elements of focused attention and open monitoring, akin to mindfulness meditation-and in the Himalayan Yoga and Isha Shoonya traditions, which emphasize focused attention and open monitoring, respectively. Results: A general trend was observed where EEG ISA amplitude tended to decrease in experienced meditators from these traditions compared to novices, particularly significant in the 0.03-0.08 Hz band for Vipassana meditators. Therefore, our analysis focused on this ISA frequency band. Specifically, a notable decrease in EEG ISA amplitude was observed in Vipassana meditators, predominantly in the left-frontal region. This reduction in EEG ISA amplitude was also accompanied by a decrease in phase-amplitude coupling (PAC) between the ISA phase and alpha band (8-12 Hz) amplitude, which implied decreased neural excitability fluctuations. Conclusion: Our findings suggest that not only does EEG ISA amplitude decrease in experienced meditators from traditions that incorporate both focused attention and open monitoring, but this decrease may also signify a diminished influence of neural excitability fluctuations attributed to ISA.

Brain-computer interface in critical care and rehabilitation.

This comprehensive review explores the broad landscape of brain-computer interface (BCI) technology and its potential use in intensive care units (ICUs), particularly for patients with motor impairments such as quadriplegia or severe brain injury. By employing brain signals from various sensing techniques, BCIs offer enhanced communication and motor rehabilitation strategies for patients. This review underscores the concept and efficacy of noninvasive, electroencephalogram-based BCIs in facilitating both communicative interactions and motor function recovery. Additionally, it highlights the current research gap in intuitive "stop" mechanisms within motor rehabilitation protocols, emphasizing the need for advancements that prioritize patient safety and individualized responsiveness. Furthermore, it advocates for more focused research that considers the unique requirements of ICU environments to address the challenges arising from patient variability, fatigue, and limited applicability of current BCI systems outside of experimental settings.

Behavior can be decoded across the cortex when individual differences are considered.

Group-level analyses have typically associated behavioral signatures with a constrained set of brain areas. Here we show that two behavioral metrics - reaction time (RT) and confidence - can be decoded across the cortex when each individual is considered separately. Subjects (N=50) completed a perceptual decision-making task with confidence. We built models decoding trial-level RT and confidence separately for each subject using the activation patterns in one brain area at a time after splitting the entire cortex into 200 regions of interest (ROIs). At the group level, we replicated previous results by showing that both RT and confidence could be decoded from a small number of ROIs (12.0% and 3.5%, respectively). Critically, at the level of the individual, both RT and confidence could be decoded from most brain regions even after Bonferroni correction (90.0% and 72.5%, respectively). Surprisingly, we observed that many brain regions exhibited opposite brain-behavior relationships across individuals, such that, for example, higher activations predicted fast RTs in some subjects but slow RTs in others. These results were further replicated in a second dataset. Lastly, we developed a simple test to determine the robustness of decoding performance, which showed that several hundred trials per subject are required for robust decoding. These results show that behavioral signatures can be decoded from a much broader range of cortical areas than previously recognized and suggest the need to study the brain-behavior relationship at both the group and the individual level.

Multiple brain activation patterns for the same task.

Meaningful variation in internal states that impacts cognition and behavior remains challenging to discover and characterize. Here we leveraged trial-to-trial fluctuations in the brain-wide signal recorded using functional MRI to test if distinct sets of brain regions are activated on different trials when accomplishing the same task. Across three different perceptual decision-making experiments, we estimated the brain activations for each trial. We then clustered the trials based on their similarity using modularity-maximization, a data-driven classification method. In each experiment, we found multiple distinct but stable subtypes of trials, suggesting that the same task can be accomplished in the presence of widely varying brain activation patterns. Surprisingly, in all experiments, one of the subtypes exhibited strong activation in the default mode network, which is typically thought to decrease in activity during tasks that require externally focused attention. The remaining subtypes were characterized by activations in different task-positive areas. The default mode network subtype was characterized by behavioral signatures that were similar to the other subtypes exhibiting activation with task-positive regions. Finally, in a fourth experiment, we tested whether multiple activation patterns would also appear for a qualitatively different, working memory task. We again found multiple subtypes of trials with differential activation in frontoparietal control, dorsal attention, and ventral attention networks. Overall, these findings demonstrate that the same cognitive tasks are accomplished through multiple brain activation patterns.

A comprehensive dataset for home appliance control using ERP-based BCIs with the application of inter-subject transfer learning.

Brain-computer interfaces (BCIs) have a potential to revolutionize human-computer interaction by enabling direct links between the brain and computer systems. Recent studies are increasingly focusing on practical applications of BCIs-e.g., home appliance control just by thoughts. One of the non-invasive BCIs using electroencephalography (EEG) capitalizes on event-related potentials (ERPs) in response to target stimuli and have shown promise in controlling home appliance. In this paper, we present a comprehensive dataset of online ERP-based BCIs for controlling various home appliances in diverse stimulus presentation environments. We collected online BCI data from a total of 84 subjects among whom 60 subjects controlled three types of appliances (TV: 30, door lock: 15, and electric light: 15) with 4 functions per appliance, 14 subjects controlled a Bluetooth speaker with 6 functions via an LCD monitor, and 10 subjects controlled air conditioner with 4 functions via augmented reality (AR). Using the dataset, we aimed to address the issue of inter-subject variability in ERPs by employing the transfer learning in two different approaches. The first approach, "within-paradigm transfer learning," aimed to generalize the model within the same paradigm of stimulus presentation. The second approach, "cross-paradigm transfer learning," involved extending the model from a 4-class LCD environment to different paradigms. The results demonstrated that transfer learning can effectively enhance the generalizability of BCIs based on ERP across different subjects and environments.

Long-lasting forms of plasticity through patterned ultrasound-induced brainwave entrainment.

Achieving long-lasting neuronal modulation with low-intensity, low-frequency ultrasound is challenging. Here, we devised theta burst ultrasound stimulation (TBUS) with gamma bursts for brain entrainment and modulation of neuronal plasticity in the mouse motor cortex. We demonstrate that two types of TBUS, intermittent and continuous TBUS, induce bidirectional long-term potentiation or depression-like plasticity, respectively, as evidenced by changes in motor-evoked potentials. These effects depended on molecular pathways associated with long-term plasticity, including N-methyl-d-aspartate receptor and brain-derived neurotrophic factor/tropomyosin receptor kinase B activation, as well as de novo protein synthesis. Notably, bestrophin-1 and transient receptor potential ankyrin 1 play important roles in these enduring effects. Moreover, pretraining TBUS enhances the acquisition of previously unidentified motor skills. Our study unveils a promising protocol for ultrasound neuromodulation, enabling noninvasive and sustained modulation of brain function.