Beta Gamma Research Articles

Intracranial EEG-Based Directed Functional Connectivity in Alpha to Gamma Frequency Range Reflects Local Circuits of the Human Mesiotemporal Network.

To date, it is largely unknown how frequency range of neural oscillations measured with EEG is related to functional connectivity. To address this question, we investigated frequency-dependent directed functional connectivity among the structures of mesial and anterior temporal network including amygdala, hippocampus, temporal pole and parahippocampal gyrus in the living human brain. Intracranial EEG recording was obtained from 19 consecutive epilepsy patients with normal anterior mesial temporal MR imaging undergoing intracranial presurgical epilepsy diagnostics with multiple depth electrodes. We assessed intratemporal bidirectional functional connectivity using several causality measures such as Granger causality (GC), directed transfer function (DTF) and partial directed coherence (PDC) in a frequency-specific way. In order to verify the obtained results, we compared the spontaneous functional networks with intratemporal effective connectivity evaluated by means of SPES (single pulse electrical stimulation) method. The overlap with the evoked network was found for the functional connectivity assessed by the GC method, most prominent in the higher frequency bands (alpha, beta and low gamma), yet vanishing in the lower frequencies. Functional connectivity assessed by means of DTF and PCD obtained a similar directionality pattern with the exception of connectivity between hippocampus and parahippocampal gyrus which showed opposite directionality of predominant information flow. Whereas previous connectivity studies reported significant divergence between spontaneous and evoked networks, our data show the role of frequency bands for the consistency of functional and evoked intratemporal directed connectivity. This has implications for the suitability of functional connectivity methods in characterizing local brain circuits.

PCR GeneScan Analysis of Rearranged Immunoglobulin or T-Cell Receptor Genes for Clonality Diagnostics in Suspect Lymphoproliferations.

Assessment of the presence of clonal lymphoproliferations via polymerase chain reaction (PCR)-based analysis of rearranged immunoglobulin (IG) or T-cell receptor (TR) genes is a valuable method in the diagnosis of suspect lymphoproliferative disorders. Additionally, this methodology can be used for evaluating dissemination of lymphoma cells and for studying the clonal relationship between multiple (different locations) and consecutive (over time) lymphomas. Here we describe an integrated approach to assess clonality via analysis of Ig heavy chain (IGH), Ig kappa (IGK), TCR beta (TRB), and TCR gamma (TRG) gene rearrangements, based on the standardized multiplex PCRs as originally developed by the European BIOMED-2 consortium (currently named EuroClonality). The described protocol covers the pre-analytical phase of DNA isolation (from formalin-fixed paraffin-embedded and fresh tissues, body fluids, peripheral blood, and bone marrow), the analytical phase of PCR GeneScan analysis, and the post-analytical interpretation of the obtained profiles, following established guidelines.

Oscillatory features of German–English sentence processing: Evidence from an EEG study

Aims and objectives: In this study, we investigated the neural oscillatory patterns occurring during sentence-level overt bilingual processing tasks on 46 German–English bilinguals with the intention of finding out if there were task-specific oscillations for this language pair. Methodology: Four tasks, including Language 2 (L2) listening, Language 1 (L1) speaking, L2 shadowing (i.e., repeating a segment of an utterance), and backward interpreting (i.e., orally translating L2 sentences to L1), were implemented with the technique of electroencephalography (EEG). Data and analysis: Data included demographic indices, neural oscillation metrics, and oral production scores from participants. Static spectral analysis, time–frequency analysis, principal components analysis, cross-frequency coupling, and inferential statistics were applied to the data. Findings: The sensory task and articulatory tasks differed greatly in the delta–theta band and the beta–gamma band in terms of time–frequency dynamics. Analyses also revealed variations in a frontal/prefrontal theta component and a distinct gamma component across the four tasks. Moreover, we found a right fronto-temporal theta–gamma coupling unique to backward interpreting. Originality: The task-wise comparison experiment paradigm has rarely been implemented in neuroimaging research on language, especially so in EEG research on bilingualism. Significance: The findings provide novel insights for the understanding of language conversion mechanism and may benefit the training of professional interpreters.

The alpha beta gamma of the labor market

We access a long panel dataset of US workers to document the extent to which individuals are heterogeneous with respect to their pattern of transitions across employment states. We find that heterogeneity is well approximated by three latent types: αs, βs and γs. Workers of type α leave unemployment quickly and, once they find a job, they are likely to keep it for more than 2 years. Workers of type γ find employment slowly and, once they do find a job, they are likely to leave it within 1 year. We use our empirical findings to calibrate a search-theoretic model in which workers are heterogeneous with respect to the parameters governing their employment transitions. We find that αs move quickly out of unemployment to employment because they have large gains from trade, and they are likely to stay on a job for more than 2 years because their productivity is similar in different jobs. In contrast, γs exit unemployment slowly because their gains from trade are small, and they are likely to leave a job within 1 year because they are much more productive in a small fraction of jobs than in the majority of jobs. We find that a negative shock to aggregate productivity leads to a large and persistent increase in unemployment that is mainly driven by γ-workers. The predictions of the model align well with the unemployment dynamics observed during the Great Recession.

Enhancement of beta spectrometry using double scintillators and ML-based unfolding

We present a novel beta spectrometer that consists of two identical plastic scintillators with one scintillator screened by a thin copper plate as a beta shield. The screened scintillator responds only to gamma photons while the other scintillator responds to both beta particles and gamma photons. The spectrometer’s response to beta and gamma radiations was characterized by experiments and Monte Carlo simulations. The gamma responses of the scintillators were in good agreement in most energy region while the screened scintillator showed a notable gamma attenuation in the low energy region below 150 keV. Comparison of the simulated and measured pulse height spectra showed good agreements for both beta and gamma radiations. For beta spectrum analysis, a simple gamma subtraction method and a convolutional neural network (CNN)-based method were investigated for various mixed beta–gamma fields. The subtraction method showed good accuracy in most energy regions while a notable overestimation of beta fluence was observed in the low energy region, which was caused by the gamma attenuation effect of the screened scintillator. The outcomes of the CNN method showed good agreements with the true beta fluence spectra for the validation dataset, however, the CNN model led to a significant overestimation for a dataset produced using the radionuclides that have not been used in the training datasets. To take the advantages of the outperforming features of both unfolding methods, a hybrid algorithm was deduced by applying a tolerance range to the subtraction result.

Compromised actin dynamics underlie the orofacial cleft in Baraitser-Winter Cerebrofrontofacial syndrome with a variant in ACTB.

Craniofacial anomalies encompassing the orofacial cleft are associated with > 30% of systemic congenital malformations. Baraitser-Winter Cerebrofrontofacial syndrome (BWCFF) is a rare genetic disorder attributed to variants in the actin beta (ACTB) or actin gamma genes that are correlated with a range of craniofacial abnormalities, including cleft lip and/or palate. The underlying pathological mechanism of BWCFF remains elusive, and it is necessary to investigate the etiology of orofacial clefts in patients with BWCFF. In this study, we identified a missense variant (c.1043C > T: p.S348L) in the ACTB gene of a patient with BWCFF and concomitant cleft lip and palate. Furthermore, we performed functional assessments of this variant using various disease models such as the MDCK cell line and Xenopus laevis. These models revealed a compromised capacity of mutated ACTB to localize to the epithelial junction, consequently affecting the behavior of epithelial cells. Additionally, we discovered that the mutated ACTB exhibited an impaired ability to bind PROFILIN1, a critical factor in actin polymerization. This defective ability may contribute to the molecular etiology of aberrant epithelial cell adhesion and migration, resulting in orofacial cleft formation in BWCFF.

Total Radiological Dose and Safety Assessment of Workers in Radioactive Liquid Waste Storage Location in Al Tuwaitha Site

This study aims to determine the total effective dose (external and internal) in the radioactive liquid Waste Hall (WH) in the Radiochemistry Laboratories building (RCL) in Al- Tuwaitha site in order to estimate the radiation risk for workers in this place. The external effective dose was calculated by an indirect method using ThermoLuminescent Dosimeters (LiF: Mg, Ti (TLD-100)) by placing them in the waste hall for one month. The internal effective dose was estimated by collecting eight air samples (environmental samples) from different locations in WH using an air sampler pump (Sniffer) to collect air samples loaded with particles or dust which are deposited on cellulose filter papers (φ 125mm). This was done for two flow rates the lowest and the highest values of the air sampler pump of 5CFM and 20CFM, respectively.The filter papers were chemically treated using the digestion method. The radionuclides in these samples were measured using a gamma spectrometry system equipped with a high-purity germanium detector (HPGe), and the radioactivity concentration was measured using a gross alpha beta gamma system. The results showed 137Cs of low concentration was deposited on the filter paper. The total annual effective dose rate (external and internal) results showed that the highest in WH was (6358.97μSv/year) for the low probability scenario and (1589.74 μSv/year) for the realistic scenario.

Unveiling the hidden: a deep learning approach to unraveling subzone-specific changes in peripapillary atrophy in type 2 diabetes.

This study aimed to evaluate the optical coherence tomography angiography (OCTA) changes in subzones of peripapillary atrophy (PPA) among type 2 diabetic patients (T2DM) with or without diabetic retinopathy (DR) using well-designed deep learning models. A multi-task joint deep-learning model was trained and validated on 2,820 images to automate the determination and quantification of the microstructure and corresponding microcirculation of beta zone and gamma zone PPA. This model was then applied in the cross-sectional study encompassing 44 eyes affected by non-proliferative diabetic retinopathy (NPDR) and 46 eyes without DR (NDR). OCTA was utilized to image the peripapillary area in four layers: superficial capillary plexus (SCP), deep capillary plexus (DCP), choroidal capillary (CC) and middle-to-large choroidal vessel (MLCV). The patients in both groups were matched for age, sex, BMI, and axial length. The width and area of the gamma zone were significantly smaller in NPDR group compared to the NDR group. Multiple linear regression analysis revealed a negative association between the diagnosis of DR and the width and area of the gamma zone. The gamma zone exhibited higher SCP, DCP and MLCV density than the beta zone, while the beta zone showed higher CC density than the gamma zone. In comparison to the NDR group, the MLCV density of gamma zone was significantly lower in NPDR group, and this density was positively correlated with the width and area of the gamma zone. DR-induced peripapillary vascular changes primarily occur in gamma zone PPA. After eliminating the influence of axial length, our study demonstrated a negative correlation between DR and the gamma zone PPA. Longitudinal studies are required to further elucidate the role of the gamma zone in the development and progression of DR.

Neural networks for the analysis of 2D radio-xenon beta gamma spectra

Atmospheric traces of radioactive xenon can be a strong indicator for underground nuclear fission reactions. 131mXe, 133Xe, 133mXe and 135Xe are the primary gaseous isotopes/isomers currently used to identify and classify nuclear events. During decay, each of these radioactive species produces a unique beta-gamma energy spectra, which can be measured using beta-gamma coincidence counting. Current operational Xe beta-gamma spectrum analysis software relies on Region of Interest (ROI) counting (Bowyer et al. in J Environ Radioact 59(2):139–151, 2002). This algorithm occasionally produces mismeasurements, especially when quantifying meta-stable isomers, due to overlapping ROIs and shifts in detector calibration in fielded systems over time (Ringbom and Axelsson in Appl Radiat Isot 156:108950, 2020). In an attempt to better de-convolve overlapping isotope spectra we have developed a technique that applies a supervised neural-network implemented in TensorFlow with Keras to classify and quantify the isotopes and mixtures of isomers based on their beta-gamma spectra—similar to image recognition. From this, we have improved upon the false-positive rate for classification and regression models, however challenges remain with dealing with differing detector energy calibrations and with estimating measurement uncertainty.

Early Embryonic Development in Agriculturally Important Species.

The fertilization of oocytes ovulated by pigs, sheep, cows, and horses is not considered a limiting factor in successful establishment of pregnancy. Pig, sheep, and cow embryos undergo cleavage to the blastocyst stage, hatch from the zona pellucida, and undergo central-type implantation. Hatched blastocysts of pigs, sheep, and cows transition from tubular to long filamentous forms to establish surface area for exchange of nutrients and gases with the uterus. The equine blastocyst, surrounded by external membranes, does not elongate but migrates throughout the uterine lumen before attaching to the uterine luminal epithelium (LE) to begin implantation. Pregnancy recognition signaling in pigs requires the trophectoderm to express interleukin 1 beta, estrogens, prostaglandin E2, and interferon gamma. Sheep and cow conceptus trophectoderm expresses interferon tau that induces interferon regulatory factor 2 that inhibits transcription of estrogen and oxytocin receptors by uterine epithelia. This prevents oxytocin-induced luteolytic pulses of prostaglandin F2-alpha from regressing the corpora lutea, as well as ensuring the secretion of progesterone required for maintenance of pregnancy. The pregnancy recognition signal produced by equine blastocysts is not known. Implantation in these species requires interactions between extracellular matrix (ECM) proteins and integrins as the conceptus undergoes apposition and firm attachment to the uterine LE. This review provides details with respect to early embryonic development and the transition from spherical to filamentous conceptuses in pigs, sheep, and cows, as well as pre-implantation development of equine blastocysts and implantation of the conceptuses.

Modulation of neuronal activity in human centromedian nucleus during an auditory attention and working memory task

Centromedian nucleus (CM) is one of several intralaminar nuclei of the thalamus and is thought to be involved in consciousness, arousal, and attention. CM has been suggested to play a key role in the control of attention, by regulating the flow of information to different brain regions such as the ascending reticular system, basal ganglia, and cortex. While the neurophysiology of attention in visual and auditory systems has been studied in animal models, combined single unit and LFP recordings in human have not, to our knowledge, been reported. Here, we recorded neuronal activity in the CM nucleus in 11 patients prior to insertion of deep brain stimulation electrodes for the treatment of epilepsy while subjects performed an auditory attention task. Patients were requested to attend and count the infrequent (p = 0.2) odd or "deviant" tones, ignore the frequent standard tones and report the total number of deviant tones at trial completion. Spikes were discriminated, and LFPs were band pass filtered (5–45 Hz). Average peri‑stimulus time histograms and spectra were constructed by aligning on tone onsets and statistically compared. The firing rate of CM neurons showed selective, multi-phasic responses to deviant tones in 81% of the tested neurons. Local field potential analysis showed selective beta and low gamma (13–45 Hz) modulations in response to deviant tones, also in a multi-phasic pattern. The current study demonstrates that CM neurons are under top-down control and participate in the selective processing during auditory attention and working memory. These results, taken together, implicate the CM in selective auditory attention and working memory and support a role of beta and low gamma oscillatory activity in cognitive processes. It also has potential implications for DBS therapy for epilepsy and non-motor symptoms of PD, such as apathy and other disorders of attention.

Hanning FIR window filtering analysis for EEG signals

The window function is a mathematical function in signal processing that is multiplied by a signal to lessen or eliminate the impact of undesired characteristics such as spectral leakage and edge effects that might arise while analyzing finite-duration signals. The Hanning window is just one of several window functionalities available. It is designed to gradually taper the endpoints of a signal to zero, reducing spectral leakage in the frequency domain. Filtering is commonly employed in Electroencephalography (EEG) signal processing to remove noise, artifacts, or undesired frequency components while retaining the desired information. Filtering techniques include band pass, low pass, and high pass and band reject filtering. Hanning window technique using low pass, high pass, band pass, and band reject is used for filtering of EEG signal. The response time analysis for the Hanning window is calculated using low, high, band pass, and band-reject filters for different types of EEG waves alpha, beta gamma, theta, and delta using the signal processing simulation tool MATLAB 2023. The response time for delta wave using a low pass filter has a low response time of 14.125 sec which is comparatively less than another filter. For theta wave high pass filter has a low response time of 11.965 seconds. For alpha wave low pass filter has a low response time of 16.706 seconds whereas for beta wave low pass filter has a low response time of 15.202 seconds. For gamma waves high pass filter has a low response time of 11.349 seconds. Hanning band-reject filter has proven low response time for delta, theta, and gamma waveforms of 16.475 seconds, 16.182 seconds, and 17.743 seconds respectively. The novelty of the work is that the Hanning window improves frequency resolution by balancing the main lobe width with side lobe attenuation Hanning band-reject filter is suited best to figure out the widest main-lobe peak and highest peak for different EEG waveforms.

Neural consequences of 5-Hz transcranial alternating current stimulation over right hemisphere: An eLORETA EEG study

IntroductionTranscranial alternating current stimulation (tACS) at 5-Hz to the right hemisphere can effectively alleviate anxiety symptoms. This study aimed to explore the neural mechanisms that drive the therapeutic benefits. MethodsWe collected electroencephalography (EEG) data from 24 participants with anxiety disorders before and after a tACS treatment session. tACS was applied over the right hemisphere, with 1.0 mA at F4, 1.0 mA at P4, and 2.0 mA at T8 (10–10 EEG convention). With eLORETA, we transformed the scalp signals into the current source density in the cortex. We then assessed the differences between post- and pre-treatment brain maps across multiple spectra (delta to low gamma) with non-parametric statistics. ResultsWe observed a trend of heightened power in alpha and reduced power in mid-to-high beta and low gamma, in accord with the EEG markers of anxiolytic effects reported in previous studies. Additionally, we observed a consistent trend of de-synchronization at the stimulating sites across spectra. ConclusiontACS 5-Hz over the right hemisphere demonstrated EEG markers of anxiety reduction. The after-effects of tACS on the brain are intricate and cannot be explained solely by the widely circulated entrainment theory. Rather, our results support the involvement of plasticity mechanisms in the offline effects of tACS.

Insights into the structural and functional analysis of impact of the missense mutations on α-synuclein: an in silico study

BackgroundAlpha synuclein (α-synuclein) is coded by SNCA gene and found in a helical form with phospholipids or in an unfolded arrangement in the cytosol and belongs to the synuclein family other than beta synuclein and gamma synuclein. It is a short protein made of 140 amino acids with three domains: an N-terminal lipid binding helix, a non-amyloid-ß component (NAC), and an acidic tail at the C-terminus. α-Synuclein is present in aggregated and fibrillar form in Lewy bodies and its association has been related to multiple system atrophy (MSA), Parkinson’s disease (PD), and Dementia with Lewy bodies (DLB). Our objective is to investigate and prioritise the possible nsSNPs in the α-synuclein protein that have been potentially connected to human neurodegenerative diseases.ResultsWe used the series of computational tools to predict the mutation's harmful effect on three-dimensional structure of α-synuclein based on consensus approach. Our findings pointed to a significant computational blueprint for discovering nsSNPs connected to neurodegenerative illnesses from a large SNP data set while also minimising the expenses of experimentally showing harmful nsSNPs.ConclusionsThe prioritised G25S (rs1433622151), V66E (rs1261243630), and V77D (rs745815563) mutations can be employed in additional experimental studies to assess the α-synuclein protein mutation in relation to neurodegenerative illnesses and develop a therapeutics against them.Graphical

Neurophysiological features of STN LFP underlying sleep fragmentation in Parkinson’s disease

BackgroundSleep fragmentation is a persistent problem throughout the course of Parkinson’s disease (PD). However, the related neurophysiological patterns and the underlying mechanisms remained unclear.MethodWe recorded subthalamic nucleus (STN) local field...

EEG spectral power in developmental coordination disorder and attention-deficit/hyperactivity disorder: a pilot study.

Developmental coordination disorder (DCD) and attention-deficit/hyperactivity disorder (ADHD) overlap in symptoms and often co-occur. Differentiation of DCD and ADHD is crucial for a better understanding of the conditions and targeted support. Measuring electrical brain activity with EEG may help to discern and better understand the conditions given that it can objectively capture changes and potential differences in brain activity related to externally measurable symptoms beneficial for targeted interventions. Therefore, a pilot study was conducted to exploratorily examine neurophysiological differences between adults with DCD and/or ADHD at rest. A total of N = 46 adults with DCD (n = 12), ADHD (n = 9), both DCD + ADHD (n = 8), or typical development (n = 17) completed 2 min of rest with eyes-closed and eyes-open while their EEG was recorded. Spectral power was calculated for frequency bands: delta (0.5-3 Hz), theta (3.5-7 Hz), alpha (7.5-12.5 Hz), beta (13-25 Hz), mu (8-13 Hz), gamma (low: 30-40 Hz; high: 40-50 Hz). Within-participants, spectral power in a majority of waveforms significantly increased from eyes-open to eyes-closed conditions. Groups differed significantly in occipital beta power during the eyes-open condition, driven by the DCD versus typically developing group comparison. However, other group comparisons reached only marginal significance, including whole brain alpha and mu power with eyes-open, and frontal beta and occipital high gamma power during eyes-closed. While no strong markers could be determined to differentiate DCD versus ADHD, we theorize that several patterns in beta activity were indicative of potential motor maintenance differences in DCD at rest. Therefore, larger studies comparing EEG spectral power may be useful to identify neurological mechanisms of DCD and continued differentiation of DCD and ADHD.

Detection of Language Lateralization Using Spectral Analysis of EEG.

Language lateralization relies on expensive equipment and can be difficult to tolerate. We assessed if lateralized brain responses to a language task can be detected with spectral analysis of electroencephalography (EEG). Twenty right-handed, neurotypical adults (28 ± 10 years; five males) performed a verb generation task and two control tasks (word listening and repetition). We measured changes in EEG activity elicited by tasks (the event-related spectral perturbation [ERSP]) in the theta, alpha, beta, and gamma frequency bands in two language (superior temporal and inferior frontal [ST and IF]) and one control (occipital [Occ]) region bilaterally. We tested whether language tasks elicited (1) changes in spectral power from baseline (significant ERSP) at any region or (2) asymmetric ERSPs between matched left and right regions. Left IF beta power (-0.37±0.53, t = -3.12, P = 0.006) and gamma power in all regions decreased during verb generation. Asymmetric ERSPs (right > left) occurred between the (1) IF regions in the beta band (right vs. left difference of 0.23±0.37, t(19) = -2.80, P = 0.0114) and (2) ST regions in the alpha band (right vs. left difference of 0.48±0.63, t(19) = -3.36, P = 0.003). No changes from baseline or hemispheric asymmetries were noted in language regions during control tasks. On the individual level, 16 (80%) participants showed decreased left IF beta power from baseline, and 16 showed ST alpha asymmetry. Eighteen participants (90%) showed one of these two findings. Spectral EEG analysis detects lateralized responses during language tasks in frontal and temporal regions. Spectral EEG analysis could be developed into a readily available language lateralization modality.

Molecular docking study, and ADMET analysis for the synthesized novel Zn(II) complexes as potential SARS-CoV-2 inhibitors

A new SARS-CoV-2 virus and its variants including omicron created a pandemic situation and caused more deaths in worldwide prompted many researchers to explore potential drug candidates. In this connection, we explored the first-of-its-kind report on computational studies such as molecular docking, and ADMET properties of Zn(II) complexes. The studies revealed the novel zinc complexes have high binding affinities with the SARS-CoV-2 spike glycoprotein (6vxx) alpha variant (7EKF), beta variant (7ekg), gamma variant (7EKC), delta variant (7V8B), and the omicron variant (7T9J). Molecular docking results of RMSD for SARS-CoV-2 beta variant (7ekg) and gamma variant (7EKC) are within excellent chemical stability in their protein-ligand complex state and should be effective in the biological system. ADME studies provided the better results with no adverse effect of toxicity related AMES along with absence of hepatotoxicity and skin sensitization when compared to Molnupiravir drug and it has a greater hepatotoxicity. This study could open further exploration of these novel zinc complexes for SARS-CoV-2 inhibition.

BRAIN AND CREATIVITY

Great ideas seem to come out of nowhere. Now we are one step closer to understanding how they appear. The areas responsible for language and creativity are thought to compete in the brain, which may explain why some people with brain damage suddenly become artists. Originality - or the ability to think of new ideas that do not occur to many people - is the key aspect of creativity. Researchers are trying to determine the mechanism by which originality is established. While creativity is generated by the right hemisphere of the brain, it is suppressed by language-specific processes in the left hemisphere: “Language regions may compete with the right hemisphere's ability to produce creative ideas.” This would explain why when areas responsible for language processing are affected, originality appears to increase. A brilliant idea is not enough to qualify a person as creative. Creativity is among the human characteristics whose mysteries we are still trying to understand. It seems almost impossible to find a clear definition for it, and it is equally difficult to look for its origins in the human brain. Many researchers define creativity as a special performance that is both new and appropriate. If we look at creativity as a concept rather than a trait, a number of factors must be considered. For example, an ingenious idea must be realized in such a way that it is visible and useful to others. Only a person who succeeds in this can truly be called creative. Creativity is a complex process that requires the activation of several areas of the brain. So far it is not clear whether creativity requires a specific neural architecture or not. At the root of all thoughts, emotions and behaviors is communication between neurons. Brain waves are the products of synchronized electrical impulses resulting from the communication of masses of neurons. The speed of brain waves is measured in Hz and are divided into categories that delineate slow, moderate and fast waves. They change according to activities or feelings. The electroencephalograph measures brain waves of different frequencies in the brain by using sensors placed on the scalp, the frequency representing the recurrence of a wave in one second. If any of these frequencies are deficient, excessive or difficult to access, psychic performance can suffer. Learning about brain waves and brain wave frequencies is key to understanding how to navigate and reprogram the mind, and to access deeper levels of consciousness. In neuroscience, there are five distinct brainwave frequencies, namely Beta waves, Alpha waves, Theta waves, Delta waves, and Gamma waves. Each frequency has its own set of characteristics representing a specific level of brain activity and a corresponding unique state of consciousness.

Novel epoxy-bPBD-BisMSB composite plastic scintillator for alpha, beta and gamma radiation detection

A composite plastic scintillator is prepared by uniform dispersion of organic fluorophores 2-(4-Biphenylyl)-5-(4-tert-butylphenyl)-1,3,4-oxadiazole (b-PBD) and 1,4-bis(2-methylstyryl) benzene (Bis-MSB) in epoxy resin followed by curing at room temperature. The developed scintillator is strong blue emitter (425 nm), confirmed by 365 nm UV excited Photo luminescence and beta particle (90Sr-90Y) excited Radio-luminescence characterizations. The developed scintillator is highly transparent (~ 70%) to emitted light wavelength. Moreover, the scintillator’s blue emission is appropriate for photomultiplier tube (PMT) based scintillation measurement due to its maximum peak spectral response in blue region. Alpha, beta and gamma radiation detection were performed on PMT coupled scintillators of sizes Ø50 mm × 1 mm, Ø50 mm × 5 mm and Ø50 mm × 25 mm respectively. Pulse height spectra were recorded using 1 k Multichannel analyser (MCA) using various reference radiation sources. All scintillators demonstrated promising response to the respective radiations. Absolute detection efficiency of alpha scintillator is obtained as 32% (241Am), 86% of that of standard plastic scintillator EJ-212. Beta endpoint energy and gamma Compton edges showed linear variation w.r.t. corresponding channel numbers. Detection efficiency of beta and gamma scintillator is found to be 35.7% (90Sr-90Y) and 6.7% (136Cs) respectively. The developed scintillator has potential to be used for radioactivity contamination & gamma dose rate measurement applications.