Metabolism Of Brain Signals On Human Sleep : a review of mechanisms of action

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Metabolism Of Brain Signals On Human Sleep : a review of mechanisms of action

Background The global research shows that people suffer from a variety of sleep disorders and human actions are the result of neuronal function inside his brain, the feedback of this function can be received and processed as a signal emitted from the surface of the skull. EEG device can receive and record brain signals. Researchers have used a variety of methods to obtain and pre-process signals, extract and reduce the characteristics and types of classifiers in various studies. Research shows that there are three general states of wakefulness (stage 1 + REM sleep) and (stage 2 + deep sleep) separated by the EEG signal. Methods The study was performed in accordance with the PRISMA guidelines. A total of 740 articles were found from scientific literature databases (PubMed, Scopus, Web of Science and Wiley Online Library ). After all exclusions, a final total of 64 articles were included in this review. The randomized controlled trials that have assessed at least one therapeutic outcome measured before and after intervention were included in the final analysis. Results A total of 64 studies were identified at the screening step. In the identification phase, total of 11 records were excluded from the further assessment and 53 records were entered into the screening phase in which Clinical Trial, Review, Books, Editorial were excluded from the review. In the eligibility stage, 49 records remained in the study where total of 34 studies were included for detailed review. Due to the heterogeneities in the available variables as well as the target aspects, the authors decided to review the studies comprehensively. Conclusions However, due to some concerns about its effectiveness, more targeted experiments are needed to identify more accurate targets and pathways responsible for the metabolism of its brain signals.

Investigating the Role of Having an Avatar in Virtual Reality on Pain Alleviation and Embodiment in Patients With Pain Using Electroencephalogram: A Neuroimaging Protocol

Chronic Pain (CP) is prevalent in industrialized countries and stands among the top 10 causes of disability. Given the widespread problems of pharmacological treatments such as opioids, a need to find alternative therapeutic approaches has emerged. Virtual Reality (VR) has shown potential as a non-pharmacological alternative for controlling pain over the past 20 years. The effectiveness of VR has been demonstrated in treating CP, and it has been suggested that VR’s analgesic effects may be associated with the Sense of Embodiment (SoE): the sensation of being inside, having and controlling a virtual body in VR. Studies have shown correlations among brain signals, reported pain and a SoE, and correlations have been observed between using an avatar in VR and pain alleviation among CP patients. However, little has been published about the changes in brain physiology associated with having an avatar in VR, and current published studies present methodological issues. Defining a proper methodology to investigate the underlying brain mechanisms of pain, a SoE associated with having an avatar in VR, and its effect on reducing pain in CP patients is key to the emerging field of VR-analgesia. Here, we propose an intervention trial design (test/intervention/test) to evaluate the effects of having a virtual avatar in VR on pain levels and SoE in CP patients using Electroencephalogram (EEG) recordings. Resting-state EEG recordings, perceived pain levels, and SoE scores will be collected before and after the VR intervention. Patients diagnosed with CP will be recruited from local pain clinics and pseudo-randomly assigned to one of two groups—with or without an avatar. Patients will experience a 10-min VR intervention built to treat CP while their EEG signals are recorded. In articulating the study procedure, we propose a framework for future studies that explores the mechanisms of VR-analgesia in patients with chronic pain.

Region-specific complexity of the intracranial EEG in the sleeping human brain

As the brain is a complex system with occurrence of self-similarity at different levels, a dedicated analysis of the complexity of brain signals is of interest to elucidate the functional role of various brain regions across the various stages of vigilance. We exploited intracranial electroencephalogram data from 38 cortical regions using the Higuchi fractal dimension (HFD) as measure to assess brain complexity, on a dataset of 1772 electrode locations. HFD values depended on sleep stage and topography. HFD increased with higher levels of vigilance, being highest during wakefulness in the frontal lobe. HFD did not change from wake to stage N2 in temporo-occipital regions. The transverse temporal gyrus was the only area in which the HFD did not differ between any two vigilance stages. Interestingly, HFD of wakefulness and stage R were different mainly in the precentral gyrus, possibly reflecting motor inhibition in stage R. The fusiform and parahippocampal gyri were the only areas showing no difference between wakefulness and N2. Stages R and N2 were similar only for the postcentral gyrus. Topographical analysis of brain complexity revealed that sleep stages are clearly differentiated in fronto-central brain regions, but that temporo-occipital regions sleep differently.

Are Brain–Computer Interfaces Feasible With Integrated Photonic Chips?

The present paper examines the viability of a radically novel idea for brain–computer interface (BCI), which could lead to novel technological, experimental, and clinical applications. BCIs are computer-based systems that enable either one-way or two-way communication between a living brain and an external machine. BCIs read-out brain signals and transduce them into task commands, which are performed by a machine. In closed loop, the machine can stimulate the brain with appropriate signals. In recent years, it has been shown that there is some ultraweak light emission from neurons within or close to the visible and near-infrared parts of the optical spectrum. Such ultraweak photon emission (UPE) reflects the cellular (and body) oxidative status, and compelling pieces of evidence are beginning to emerge that UPE may well play an informational role in neuronal functions. In fact, several experiments point to a direct correlation between UPE intensity and neural activity, oxidative reactions, EEG activity, cerebral blood flow, cerebral energy metabolism, and release of glutamate. Therefore, we propose a novel skull implant BCI that uses UPE. We suggest that a photonic integrated chip installed on the interior surface of the skull may enable a new form of extraction of the relevant features from the UPE signals. In the current technology landscape, photonic technologies are advancing rapidly and poised to overtake many electrical technologies, due to their unique advantages, such as miniaturization, high speed, low thermal effects, and large integration capacity that allow for high yield, volume manufacturing, and lower cost. For our proposed BCI, we are making some very major conjectures, which need to be experimentally verified, and therefore we discuss the controversial parts, feasibility of technology and limitations, and potential impact of this envisaged technology if successfully implemented in the future.