Brain Waves Research Articles

Critical analysis of Parkinson’s disease detection using EEG sub-bands and gated recurrent unit

Parkinson’s disease, the second most common neurodegenerative disorder in the world. A progressive disease, which can worsen over time and lead to complications like mild cognitive impairments and dementia. The accurate diagnosis of Parkinson’s Disease (PD) remains a critical challenge in medical engineering. This study explores the potential of brain wave patterns for PD detection in healthy and unhealthy patients. The Power Spectral Density (PSD) and proposed PD detection model based on the Gated Recurrent Unit (GRU) is used to analyze brain activities. It was found that the detection of PD in patients was improved by classifying the RAW EEG in conjunction with the sub-bands using PSD as a feature and GRU as a classifier. The performance matrices including accuracy, precision, recall, and F1-score fall within a range of 90% to 98% for alpha, beta, and gamma sub-bands, while the area under the curve in the case of receiver operating characteristics curve achieved the maximum value of 1.00. To assess the differences between the groups with Parkinson’s disease and the healthy group, a statistical significance test was performed. The power spectral density of the two groups differed statistically significantly, according to the results, indicating that they could be useful as biomarkers for the identification of Parkinson’s disease. The results are compared and validated with the standard performance measures.

Study to examine the effect of Brain Gym on brain waves and concentration in athletes: Paper protocol

Brain function is crucial in achieving peak performance. This can determine a person’s motor control and psychological state, such as motivation, attention, goal setting, memory, self-control, decision-making, and concentration. Spontaneous activity of various physical organs such as the brain, heart, and muscles can be a reference when this behavior occurs. This protocol paper aims to determine whether brain exercises can influence athletes’ brain wave activity and concentration levels. The quasi-experimental method used a pretest-posttest control group design involving 68 futsal athletes. Group 1 will use Brain Gym with instrumental music, Group 2 will use Brain Gym with aromatherapy, and Group 3 will use Brain Gym with both aromatherapy and instrumental music. The research will take place at UNPARI, Lubuklinggau, South Sumatra. The results of this research can serve as a basis for developing mental training methods based on the psychophysiological impact of brain wave activity and athletes’ concentration. This highlights the need for better-designed training programs to optimize performance.

The Effect of the Root Bark of Lycium chinense (Lycii Radicis Cortex) on Experimental Periodontitis and Alveolar Bone Loss in Sprague-Dawley Rats

Lycii Radicis Cortex (LRC), the dried root bark of Lycium chinese Mill., has traditionally been used as a medicinal herb in East Asia to treat fever and hyperhidrosis. In the present study, we investigated the effects of LRC extract on ligation-induced experimental periodontitis and associated alveolar bone loss in rats. Twenty-four hours after ligation placement, LRC was orally administered once daily for 10 days. Firstly, LRC administration inhibited anaerobic bacterial proliferation and inflammatory cell infiltration in gingival tissues. Additionally, LRC exhibited anti-inflammatory effects by reducing the expression of inflammatory mediators, including prostaglandin E2, interleukin-1β, and tumor necrosis factor-α. LRC treatment also downregulated mRNA expression of these inflammatory mediators in lipopolysaccharide-stimulated RAW 264.7 cells by inhibiting the mitogen-activated protein kinases and nuclear factor-κB (NF-κB) signaling pathways. Furthermore, LRC showed an antioxidant effect by decreasing the malondialdehyde level and inducible nitric oxide synthase activity in gingival tissues. Moreover, LRC effectively prevented the connective tissue degradation by inhibiting matrix metalloproteinase-8 expression and the loss of collagen-occupied areas in gingival tissues. LRC also decreased the receptor activator of NF-κB ligand/osteoprotegerin (RANKL/OPG) ratio, as well as the number and occupied areas of osteoclasts on the alveolar bone surface, thereby inhibiting alveolar bone loss. In summary, these findings suggest that LRC is a promising medicinal herb for alleviating periodontitis and related alveolar bone loss through its antimicrobial, anti-inflammatory, and antioxidant properties.

Multimodal neuroimaging of hierarchical cognitive control

Cognitive control enables us to translate our knowledge into actions, allowing us to flexibly adjust our behavior, according to environmental contexts, our internal goals, and future plans. Multimodal neuroimaging and neurostimulation techniques have proven essential for advancing our understanding of how cognitive control emerges from the coordination of distributed neuronal activities in the brain. In this review, we examine the literature on multimodal studies of cognitive control. We explore how these studies provide converging evidence for a novel, multiplexed model of cognitive control, in which neural oscillations support different levels of control processing along a functionally hierarchical organization of distinct frontoparietal networks.

Case Study : Observation of Reducing Heartburn Pain in Gastroesophageal Reflux Disease (Gerd) With Hypnotherapy

Hypnotherapy is a form of psychological treatment that utilizes hypnosis to assist in addressing specific mental and physical ailments. It can also be employed for altering habits. Hypnotherapy operates by inducing a hypnotic state in the subject, lowering brain waves to alpha-theta levels for relaxation and enhanced acceptance of suggestions in the subconscious. The aim is to improve psychological issues, emotions, and conduct. The study was carried out on two patients at the Lee Chen Thung Primary Clinic in Jakarta, Indonesia. Sampling was conducted by adhering to specific criteria for selection and administering the GERD-Q questionnaire. The patients included in the study had to have GERD-Q scores higher than 7 and frequently use PPIs for their stomach issues. Management of GERD can be done with drug therapy or pharmacology and non-pharmacology therapy. One of the non-pharmacology therapies that can be given is hypnotherapy. Patients who satisfied the criteria were provided with hypnotherapy in order to alleviate their heartburn symptoms. The process of hypnotherapy can help the body to stimulate the release of endorphins. Endorphins act as the body's innate pain relievers. Following hypnotherapy, patients underwent eval_uation for 1 week using numeric rating scale. Both patients experienced a decrease in pain levels following hypnotherapy.

The Mindful Brain at Rest: Neural Oscillations and Aperiodic Activity in Experienced Meditators

Abstract Objectives Previous research has demonstrated that mindfulness meditation is associated with a variety of benefits, including improved mental health. Researchers have suggested these benefits may be underpinned by differences in neural oscillations. However, previous studies measuring neural oscillations have not controlled for non-oscillatory neural activity, the power spectrum of which follows a 1/f distribution (whereby the power of neural activity at each frequency is inversely proportional to that frequency (such that as frequency increases, power decreases)) and contributes to power measurements within oscillation frequencies of interest. We applied recently developed methods to determine if past findings related to neural oscillations in meditation are present even after controlling for non-oscillatory 1/f activity. Method Forty-eight experienced meditators and 44 demographically matched non-meditators provided resting electroencephalography (EEG) recordings. Whole-scalp EEG comparisons (topographical ANOVAs) were used to test for differences between meditators and non-meditators in the distribution or global power of activity for theta, alpha, beta, and gamma oscillations, and for the 1/f components slope and intercept using the extended Better OSCillation detection toolbox. Results Results indicated that meditators showed differences in theta, alpha, and gamma oscillatory power compared to non-meditators (all p < 0.05). Post hoc testing suggested that the oscillatory differences were primarily driven by differences in the distribution of neural activity between meditators and non-meditators, rather than differences in the overall power across all scalp electrodes. Conclusions Our results suggest that experience with meditation is associated with higher oscillatory power and altered distributions of theta, alpha, and gamma oscillations, even after controlling for non-oscillatory 1/f activity. Band-specific differences in oscillatory activity may be a mechanism through which meditation leads to neurophysiological benefits. Preregistration This study was not preregistered.

Compensatory mechanisms amidst demyelinating disorders: insights into cognitive preservation.

Demyelination disrupts the transmission of electrical signals in the brain and affects neurodevelopment in children with disorders such as multiple sclerosis and myelin oligodendrocyte glycoprotein-associated disorders. Although cognitive impairments are prevalent in these conditions, some children maintain cognitive function despite substantial structural injury. These findings raise an important question: in addition to the degenerative process, do compensatory neural mechanisms exist to mitigate the effects of myelin loss? We propose that a multi-dimensional approach integrating multiple neuroimaging modalities, including diffusion tensor imaging, magnetoencephalography and eye-tracking, is key to investigating this question. We examine the structural and functional connectivity of the default mode and executive control networks due to their significant roles in supporting higher-order cognitive processes. As cognitive proxies, we examine saccade reaction times and direction errors during an interleaved pro- (eye movement towards a target) and anti-saccade (eye movement away from a target) task. 28 typically developing children, 18 children with multiple sclerosis and 14 children with myelin oligodendrocyte glycoprotein-associated disorders between 5 and 18.9 years old were scanned at the Hospital for Sick Children. Tractography of diffusion MRI data examined structural connectivity. Intracellular and extracellular microstructural parameters were extracted using a white matter tract integrity model to provide specific inferences on myelin and axon structure. Magnetoencephalography scanning was conducted to examine functional connectivity. Within groups, participants had longer saccade reaction times and greater direction errors on the anti- versus pro-saccade task; there were no group differences on either task. Despite similar behavioural performance, children with demyelinating disorders had significant structural compromise and lower bilateral high gamma, higher left-hemisphere theta and higher right-hemisphere alpha synchrony relative to typically developing children. Children diagnosed with multiple sclerosis had greater structural compromise relative to children with myelin oligodendrocyte glycoprotein-associated disorders; there were no group differences in neural synchrony. For both patient groups, increased disease disability predicted greater structural compromise, which predicted longer saccade reaction times and greater direction errors on both tasks. Structural compromise also predicted increased functional connectivity, highlighting potential adaptive functional reorganisation in response to structural compromise. In turn, increased functional connectivity predicted faster saccade reaction times and fewer direction errors. These findings suggest that increased functional connectivity, indicated by increased alpha and theta synchrony, may be necessary to compensate for structural compromise and preserve cognitive abilities. Further understanding these compensatory neural mechanisms could pave the way for the development of targeted therapeutic interventions aimed at enhancing these mechanisms, ultimately improving cognitive outcomes for affected individuals.

Binaural beats at 0.25 Hz shorten the latency to slow-wave sleep during daytime naps

Binaural beats can entrain neural oscillations and modulate behavioral states. However, the effect of binaural beats, particularly those with slow frequencies (< 1 Hz), on sleep remains poorly understood. We hypothesized that 0.25-Hz beats can entrain neural oscillations and enhance slow-wave sleep by shortening its latency or increasing its duration. To investigate this, we included 12 healthy participants (six women; mean age, 25.4 ± 2.6 years) who underwent four 90-min afternoon nap sessions, comprising a sham condition (without acoustic stimulation) and three binaural-beat conditions (0, 0.25, or 1 Hz) with a 250-Hz carrier tone. The acoustic stimuli, delivered through earphones, were sustained throughout the 90-min nap period. Both N2- and N3- latencies were shorter in the 0.25-Hz binaural beats condition than in the sham condition. We observed no significant results regarding neural entrainment at slow frequencies, such as 0.25 and 1 Hz, and the modulation of sleep oscillations, including delta and sigma activity, by binaural beats. In conclusion, this study demonstrated the potential of binaural beats at slow frequencies, specifically 0.25 Hz, for inducing slow-wave sleep in generally healthy populations.

Machine-Learning-Based Depression Detection Model from Electroencephalograph (EEG) Data Obtained by Consumer-Grade EEG Device

Background/Objectives: There have been attempts to detect depression using medical-grade electroencephalograph (EEG) data based on a machine learning approach. EEG has garnered interest as a method for assessing brainwaves by attaching electrodes to the scalp to obtain electrical activity in the brain. Recently, machine learning has been applied to the EEG data to detect depression, with encouraging results. Specifically, studies using medical-grade EEG data have shown that depression can be accurately detected. However, there is a need to expand the range of applications by achieving a score with machine learning using simpler consumer-grade brain wave sensors. At present, a sufficient score has not been achieved.; Methods: To improve the score of depression detection, we quantified various EEG indices to train models such as power spectrum, asymmetry, complexity, and functional connectivity. In addition, feature selection was performed to ensure that the model learns only promising EEG indices for depression detection. The feature selection methods were Light Gradient Boosting Machine (LightGBM) feature importance, mutual information, ReliefF and ElasticNet coefficients. The selected EEG indices were learned by the LightGBM model, which is reported to be as accurate as the latest deep learning models. In cross-validation, the independence of test and training data was ensured to avoid excessively calculated score; Results: The results showed that the Macro F1 score was 91.59%, suggesting that a consumer-grade EEG can detect depression. In addition, analysis of the EEG indices selected by feature selection indicated that the Macro F1 score was about 80% for single EEG indices such as differential entropy in the frequency band β and functional connectivity in the left frontal region in the frequency band 1–128 Hz; Conclusions: Although the data were obtained from a consumer-grade EEG, the results suggest that these EEG indices are promising for detection depression.

Differential modulations of theta and beta oscillations by audiovisual congruency in letter-speech sound integration.

The integration of visual letters and speech sounds is a crucial part of learning to read. Previous studies investigating this integration have revealed a modulation by audiovisual (AV) congruency, commonly known as the congruency effect. To investigate the cortical oscillations of the congruency effects across different oscillatory frequency bands, we conducted a Japanese priming task in which a visual letter was followed by a speech sound. We analyzed the power and phase properties of oscillatory activities in the theta and beta bands between congruent and incongruent letter-speech sound (L-SS) pairs. Our results revealed stronger theta-band (5-7Hz) power in the congruent condition and cross-modal phase resetting within the auditory cortex, accompanied by enhanced inter-trial phase coherence (ITPC) in the auditory-related areas in response to the congruent condition. The observed congruency effect of theta-band power may reflect increased neural activities in the left auditory region during L-SS integration. Additionally, theta ITPC findings suggest that visual letters amplify neuronal responses to the following corresponding auditory stimulus, which may reflect the differential cross-modal influences in the primary auditory cortex. In contrast, decreased beta-band (20-35 Hz) oscillatory power was observed in the right centroparietal regions for the congruent condition. The reduced beta power seems to be unrelated to the processing of AV integration, but may be interpreted as the brain response to predicting auditory sounds during language processing. Our data provide valuable insights by indicating that oscillations in different frequency bands contribute to the disparate aspects of L-SS integration.

Neural Synchrony of Minds and Machines: Hippocampal Mechanisms to Advance AI and Virtual Networks

Abstract Artificial intelligence (AI) predicts behavior by learning from user data collected through digitally mediated interfaces. Virtual spaces---such as online social networks---extend the physical world into virtual worlds, leveraging AI technologies to transform user behavior into digital assets by mimicking the brain’s reinforcement networks. Social media platforms utilize AI to manipulate user behavior through rewards that can diverge from the user’s intended goals. This misalignment fragments user behavior and cognition, resulting in virtual disembodiment. Presented is a conceptual mechanism based on the hippocampus to synchronize AI and the brain, synthesizing the user’s physical and mental presence in virtual spaces.

Research to reduce pain and increase comfort using skin cleaning materials

During her nursing career, Professor Emeritus Hiroko Shimizu focused on the need for nursing care to promote and support patient recovery and found that the use of steam cloths helped relax patients and reduce their physical and mental pain. Shimizu is affiliated with Kagawa University and has been working to investigate the impact of skin cleaning materials on the brain waves of patients. Shimizu and her collaborators set out to create something that could warm people affected by disasters and relieve the pain of cancer patients. The researchers were the first to employ a method invented by Professor Ichirou Ishimaru to measure moisture using near-infrared two-dimensional Fourier spectrometry. They measured moisture smearing on the skin and found a softening and smoothing effect on the skin. This led them to develop a steam-generating cleaning tool that induces relaxation without a towel or cloth. Part of Shimizu’s work concentrates on developing new techniques and measurement methods needed to verify her findings. The researchers also used text analysis of the subjects’ statements and psychological images to project their thoughts and attitudes towards the care provided, as well as an electroencephalogram analysis by a neurologist, Visiting Professor Tetsuo Toge, to correlate the results. Shimizu plans to incorporate an analysis of steam volume and moisture or images with temperature and humidity into her considerations. In one study, Professor Hidekuni Takao, who shared Professor Shimizu's research, is working as the representative of a Japan Science and Technology Agency (JST)-CREST project to develop a rare device to measure the shape of the skin surface. The goal is that the integrated semiconductor tactile sensor the researchers are developing will have equal or even greater sensitivity and performance than that of a human fingerprint.

Inter-brain synchrony is associated with greater shared identity within naturalistic conversational pairs.

Inter-brain synchrony occurs between individuals who feel connected socially, but how synchrony relates to felt connectedness under naturalistic social interaction has remained enigmatic. We hypothesized that inter-brain synchrony between naturally interacting individuals might be associated with the internalization of a social identity, a link between an individual's personal identity and the social group to which the individual belongs. A convenience sample of sixty participants were split into dyads and interacted naturalistically on a social task. Through mapping EEG oscillatory waveforms onto a conceptual model categorizing the formation of a social identity within a naturalistic conversation, greater inter-brain synchrony was observed in the emergent stage within the formation of a social identity compared to earlier stages, where a social identity was not present. We provide evidence for greater neural synchrony related to higher socio-psychological connectedness during the development of social identity under naturalistic social interaction.

Impact of age-related hearing loss on decompensation of left DLPFC during speech perception in noise: a combined EEG-fNIRS study.

Understanding speech-in-noise is a significant challenge for individuals with age-related hearing loss (ARHL). Evidence suggests that increased activity in the frontal cortex compensates for impaired speech perception in healthy aging older adults. However, whether older adults with ARHL still show preserved compensatory function and the specific neural regulatory mechanisms underlying such compensation remains largely unclear. Here, by utilizing a synchronized EEG-fNIRS test, we investigated the neural oscillatory characteristics of the theta band and synchronous hemodynamic changes in the frontal cortex during a speech recognition task in noise. The study included healthy older adults (n = 26, aged 65.4 ± 2.8), those with mild hearing loss (n = 26, aged 66.3 ± 3.8), and those with moderate to severe hearing loss (n = 26, aged 67.5 ± 3.7). Results showed that, relative to healthy older adults, older adults with ARHL exhibited lower activation and weakened theta band neural oscillations in the left dorsolateral prefrontal cortex (DLPFC) under noisy conditions, and this decreased activity correlated with high-frequency hearing loss. Meanwhile, we found that the connectivity of the frontoparietal network was significantly reduced, which might depress the top-down articulatory prediction function affecting speech recognition performance in ARHL older adults. The results suggested that healthy aging older adults might exhibit compensatory attentional resource recruitment through a top-down auditory-motor integration mechanism. In comparison, older adults with ARHL reflected decompensation of the left DLPFC involving the frontoparietal integration network during speech recognition tasks in noise.

Exploring Electrophysiological Responses to Hypnosis in Patients with Fibromyalgia

Background/Objectives: Hypnosis shows great potential for managing patients suffering from fibromyalgia and chronic pain. Several studies have highlighted its efficacy in improving pain, quality of life, and reducing psychological distress. Despite its known feasibility and efficacy, the mechanisms of action remain poorly understood. Building on these insights, this innovative study aims to assess neural activity during hypnosis in fibromyalgia patients using high-density electroencephalography (EEG) and self-reported measures. Methods: Thirteen participants with fibromyalgia were included in this study. EEG recordings were done during resting state and hypnosis conditions. After both conditions, levels of pain, comfort, absorption, and dissociation were assessed using a numerical rating scale. Time perception was collected via an open-ended question. The study was prospectively registered in the ClinicalTrials.gov public registry (NCT04263324). Results: Neural oscillations showed increased theta power during hypnosis in the left parietal and occipital electrodes, increased beta power in the frontal and left temporal electrodes, and increased slow-gamma power in the frontal and left parietal electrodes. Functional connectivity using pairwise-phase consistency measures showed decreased connectivity in the frontal electrodes during hypnosis. Graph-based measures, the node strength, and the cluster coefficient were lower in frontal electrodes in the slow-gamma bands during hypnosis compared to resting state. Key findings indicate significant changes in neural oscillations and brain functional connectivity, suggesting potential electrophysiological markers of hypnosis in this patient population.

Arginine vasopressin induces analgesic effects and inhibits pyramidal cells in the anterior cingulate cortex in spared nerve injured mice.

Neuropathic pain (NP) is a severe disease caused by a primary disease or lesion affecting the somatosensory nervous system. It`s reported that NP is related to the increased activity of glutamatergic pyramidal cells and changed neural oscillations in the anterior cingulate cortex (ACC). Arginine vasopressin (AVP), a neurohypophyseal hormone, has been shown to cause pain-alleviating effects when applied to peripheral system. However, the extent to which, and the mechanisms by which, AVP induces analgesic effects in the central nervous system remain unclear. In the present study, we observed that intranasal delivery of AVP inhibited mechanical pain, thermal pain and spontaneous pain sensitivity in mice with spared nerve injury. Meanwhile, AVP application exclusively reduced the FOS expression in the pyramidal cells but not interneurons in the ACC. In vivo electrophysiological recording of the ACC further showed that AVP application not only inhibited the theta oscillation in local field potential analysis, but also reduced the firing rate of spikes of pyramidal cells in the ACC in neuropathic pain mice. In summary, AVP induce analgesic effects by inhibiting neural theta oscillations and the spiking of pyramidal cells of the ACC in mice with neuropathic pain, which should provide new potential noninvasive methods for clinical treatment of chronic pain.

Effects of continuous theta burst stimulation on contralateral primary motor cortex: a concurrent TMS-EEG study.

Continuous theta burst stimulation (cTBS) is a noninvasive brain stimulation technique. cTBS modulation is an effective treatment for motor dysfunction rehabilitation in post-stroke patients. However, there's currently a lack of research on the effects of cTBS stimulation on the contralesional hemisphere. To better understand the role of cTBS in motor rehabilitation, we investigated the neuroregulatory mechanisms of cTBS in the contralateral cortex using transcranial magnetic stimulation-evoked electroencephalography (TMS-EEG). In this randomized, sham-controlled, single-blind study, 18 healthy subjects received two separate stimulation conditions: cTBS or sham stimulation applied to the left primary motor cortex (M1). TMS-EEG measurements were taken before and immediately after stimulation. We investigated the TMS-evoked potentials (TEPs), evoked oscillatory responses (EOR), and phase synchronization index (PSI) of TMS-EEG. The effects of cTBS were analyzed using two-way repeated-measures analysis of variance (RMANOVA). There was a significant "cTBS condition × time" interaction effect on the theta and gamma bands of EOR, and on interhemisphere PSI (inter-PSI) and global PSI in both cTBS stimulation conditions. (theta: F = 4.526, P = 0.041; gamma: F = 5.574, P = 0.024; inter-PSI: F = 5.028, P = 0.032; global PSI: F = 5.129, P = 0.030). After real cTBS modulation, the energy in the theta and gamma frequency bands was significantly higher than before (theta: F = 5.747, P = 0.022; gamma: F = 5.545, P = 0.024). The inter-PSI and global PSI significantly increased after real cTBS modulation (inter-PSI: F = 6.209, P = 0.018; global PSI: F = 6.530, P = 0.015). cTBS modulation significantly increased EOR and PSI in contralateral brain regions, thereby enhancing cortical excitability and cortical functional connectivity throughout the brain. This provides a theoretical basis for cTBS neuromodulation in patients with stroke.NEW & NOTEWORTHY In right-handed individuals, the left hemisphere exhibits higher excitability. According to hemispheric competition theory, applying continuous theta burst stimulation (cTBS) to inhibit excitability in the left hemisphere can reduce its inhibitory effect on the right, thereby promoting neural excitability. This study applied cTBS to the left M1 of healthy individuals and, for the first time, recorded transcranial magnetic stimulation-evoked electroencephalography (TMS-EEG) from the right M1 to analyze the effects of cTBS on cortical oscillations and network connectivity in the contralateral cortex.

Neural Correlates of Psychedelic, Sleep, and Sedated States Support Global Theories of Consciousness.

Understanding neural mechanisms of consciousness remains a challenging question in neuroscience. A central debate in the field concerns whether consciousness arises from global interactions that involve multiple brain regions or focal neural activity, such as in sensory cortex. Additionally, global theories diverge between the Global Neuronal Workspace (GNW) hypothesis, which emphasizes frontal and parietal areas, and the Integrated Information Theory (IIT), which focuses on information integration within posterior cortical regions. To disentangle the global vs. local and frontoparietal vs. posterior dilemmas, we measured global functional connectivity and local neural synchrony with functional magnetic resonance imaging (fMRI) data across a spectrum of conscious states in humans induced by psychedelics, sleep, and deep sedation. We found that psychedelic states are associated with increased global functional connectivity and decreased local neural synchrony. In contrast, non-REM sleep and deep sedation displayed the opposite pattern, suggesting that consciousness arises from global brain network interactions rather than localized activity. This mirror-image pattern between enhanced and diminished states was observed in both anterior-posterior (A-P) and posterior-posterior (P-P) brain regions but not within the anterior part of the brain alone. Moreover, anterior transmodal regions played a key role in A-P connectivity, while both posterior transmodal and posterior unimodal regions were critical for P-P connectivity. Overall, these findings provide empirical evidence supporting global theories of consciousness in relation to varying states of consciousness. They also bridge the gap between two prominent theories, GNW and IIT, by demonstrating how different theories can converge on shared neuronal mechanisms.

PsyneuroNet architecture for multi-class prediction of neurological disorders

Early detection and diagnosis of psychiatric disorders are crucial for timely intervention, improved treatment outcomes, and preventing complications. The purpose of this study is to use artificial intelligence methods to diagnose symptoms of psychiatric conditions such as depression, schizophrenia, sleep disorder, and Alzheimer’s disease in epileptic patients using EEG data. The research uses a cross-validation procedure with ten iterations and looks at three data sets: the CHB-MIT dataset with EEG recordings from neonatal subjects, the DEAP dataset containing physiological signals and emotional ratings, and the OpenNeuro dataset containing multichannel EEG. Preprocessing involves dividing the EEG signals into five brain wave frequency components and applying filtering techniques for further analysis. We introduce a novel architecture called PsyneuroNet, which aims to improve feature extraction and prediction accuracy for real-time psychiatric disorder recognition and integrates three key components: cross-normalization across convolution, a bidirectional long-short-term memory network (Bi-LSTM), and an enhanced intuition-based convolutional neural network (ICNN). The proposed methodology is evaluated based on the 99.65% prediction accuracy achieved on the CHB-MIT dataset, the 97.27% prediction accuracy achieved on the DEAP dataset, and the 98.08% prediction accuracy achieved on the OpenNeuro dataset for prediction problems. The proposed method outperforms the state-of-the-art approaches in terms of accuracy by 3.64%, with a sensitivity of 99.65%, a specificity of 99.75%, and a very low false positive rate per hour (FPR/h) of 0.3%, all achieved by using ten folds cross-validation. The PsyneuroNet’s capability to classify a diverse range of neurological disorders within a single architecture is noteworthy. This versatility makes the model suitable for addressing a broad spectrum of clinical scenarios. The model’s ability to generalize effectively to unseen data, as demonstrated by testing its performance on the DEAP and OpenNeuro datasets after training on CHB-MIT data, is a significant aspect of novelty.

Potentiation of Motor Adaptation Via Cerebellar tACS: Characterization of the Stimulation Frequency.

Motor adaptation is critical to update motor tasks in new or modified environmental conditions. While the cerebellum supports error-based adaptations, its neural implementation is partially known. By controlling the frequency of cerebellar transcranial alternating current stimulation (c-tACS), we can test the influence of neural oscillation from the cerebellum for motor adaptation. Two independent experiments were conducted. In Experiment 1, 16 participants received four c-tACS protocols (45Hz, 50Hz, 55Hz, and sham) on four different days while they practiced a visuomotor adaptation task (30 degrees CCW) with variable intensity (within-subject design). In Experiment 2, 45 participants separated into three groups received the effect of 45Hz, 55Hz c-tACS, and sham, respectively (between-subject design), performing the same visuomotor task with a fixed intensity (0.9mA). In Experiment 1, 45Hz and 50Hz of c-tACS accelerated motor adaptation when participants performed the task only for the first time, independent of the time interval between sessions or the stimulation intensity. The effect of active c-tACS was ratified in Experiment 2, where 45Hz c-tACS benefits motor adaptation during the complete practice period. Reaction time, velocity, or duration of reaching are not affected by c-tACS. Cerebellar alternating current stimulation is an effective strategy to potentiate visuomotor adaptations. Frequency-dependent effects on the gamma band, especially for 45Hz c-tACS, ratify the oscillatory profile of cerebellar processes behind the motor adaptation. This can be exploited in future interventions to enhance motor learning.