Displaying publications 1 - 20 of 64 in total

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  1. Amperometric microbiosensor as an alternative tool for investigation of D-serine in brain
    Mohd Zain Z, Ab Ghani S, O'Neill RD
    Amino Acids, 2012 Nov;43(5):1887-94.
    PMID: 22865247 DOI: 10.1007/s00726-012-1365-0
    This paper discusses the application of a reagentless, selective microbiosensor as a useful alternative tool for monitoring D-serine in neural samples. The main components of the 125-μm-diameter disk biosensor were D-amino acid oxidase for D-serine sensitivity (linear region slope, 61 ± 7 μA cm(-2) mM(-1); limit of detection, 20 nM), and poly-phenylenediamine for rejection of electroactive interference. The response time of the biosensor was of the order of 1 s, ideal for 'real-time' monitoring, and detection of systemically administered D-serine in brain extracellular fluid is demonstrated. Exploitation of this probe might resolve queries involving regulation of D-serine in excitotoxicity, and modulation of N-methyl-D-aspartate receptor function by D-serine and glycine in the central nervous system.
    Matched MeSH terms: Brain/physiology
  2. Fulltext Habenula kisspeptin retrieves morphine impaired fear memory in zebrafish
    Sivalingam M, Ogawa S, Parhar IS
    Sci Rep, 2020 11 11;10(1):19569.
    PMID: 33177592 DOI: 10.1038/s41598-020-76287-9
    The habenula is an evolutionarily conserved brain structure, which has recently been implicated in fear memory. In the zebrafish, kisspeptin (Kiss1) is predominantly expressed in the habenula, which has been implicated as a modulator of fear response. Hence, in the present study, we questioned whether Kiss1 has a role in fear memory and morphine-induced fear memory impairment using an odorant cue (alarm substances, AS)-induced fear avoidance paradigm in adult zebrafish, whereby the fear-conditioned memory can be assessed by a change of basal place preference (= avoidance) of fish due to AS-induced fear experience. Subsequently, to examine the possible role of Kiss1 neurons-serotonergic pathway, kiss1 mRNA and serotonin levels were measured. AS exposure triggered fear episodes and fear-conditioned place avoidance. Morphine treatment followed by AS exposure, significantly impaired fear memory with increased time-spent in AS-paired compartment. However, fish administered with Kiss1 (10-21 mol/fish) after morphine treatment had significantly lower kiss1 mRNA levels but retained fear memory. In addition, the total brain serotonin levels were significantly increased in AS- and Kiss1-treated groups as compared to control and morphine treated group. These results suggest that habenular Kiss1 might be involved in consolidation or retrieval of fear memory through the serotonin system.
    Matched MeSH terms: Brain/physiology
  3. Acute social defeat stress upregulates gonadotrophin inhibitory hormone and its receptor but not corticotropin-releasing hormone and ACTH in the Male Nile Tilapia (Oreochromis niloticus)
    Thomas FSK, Higuchi Y, Ogawa S, Soga T, Parhar IS
    Peptides, 2021 04;138:170504.
    PMID: 33539873 DOI: 10.1016/j.peptides.2021.170504
    Stress impairs the hypothalamic-pituitary-gonadal (HPG) axis, probably through its influence on the hypothalamic-pituitary-adrenal (= interrenals in the teleost, HPI) axis leading to reproductive failures. In this study, we investigated the response of hypothalamic neuropeptides, gonadotropin-inhibitory hormone (GnIH), a component of the HPG axis, and corticotropin-releasing hormone (CRH) a component of the HPI axis, to acute social defeat stress in the socially hierarchical male Nile tilapia (Oreochromis niloticus). Localization of GnIH cell bodies, GnIH neuronal processes, and numbers of GnIH cells in the brain during acute social defeat stress was studied using immunohistochemistry. Furthermore, mRNA levels of GnIH and CRH in the brain together with GnIH receptor, gpr147, and adrenocorticotropic hormone (ACTH) in the pituitary were quantified in control and socially defeated fish. Our results show, the number of GnIH-immunoreactive cell bodies and GnIH mRNA levels in the brain and the levels of gpr147 mRNA in the pituitary significantly increased in socially defeated fish. However, CRH and ACTH mRNA levels did not change during social defeat stress. Further, we found glucocorticoid type 2b receptor mRNA in laser captured immunostained GnIH cells. These results show that acute social defeat stress activates GnIH biosynthesis through glucocorticoid receptors type 2b signalling but does not change the CRH and ACTH mRNA expression in the tilapia, which could lead to temporary reproductive dysfunction.
    Matched MeSH terms: Brain/physiology
  4. Drowsiness detection during different times of day using multiple features
    Sahayadhas A, Sundaraj K, Murugappan M
    Australas Phys Eng Sci Med, 2013 Jun;36(2):243-50.
    PMID: 23719977 DOI: 10.1007/s13246-013-0200-6
    Driver drowsiness has been one of the major causes of road accidents that lead to severe trauma, such as physical injury, death, and economic loss, which highlights the need to develop a system that can alert drivers of their drowsy state prior to accidents. Researchers have therefore attempted to develop systems that can determine driver drowsiness using the following four measures: (1) subjective ratings from drivers, (2) vehicle-based measures, (3) behavioral measures and (4) physiological measures. In this study, we analyzed the various factors that contribute towards drowsiness. A total of 15 male subjects were asked to drive for 2 h at three different times of the day (00:00-02:00, 03:00-05:00 and 15:00-17:00 h) when the circadian rhythm is low. The less intrusive physiological signal measurements, ECG and EMG, are analyzed during this driving task. Statistically significant differences in the features of ECG and sEMG signals were observed between the alert and drowsy states of the drivers during different times of day. In the future, these physiological measures can be fused with vision-based measures for the development of an efficient drowsiness detection system.
    Matched MeSH terms: Brain/physiology*
  5. Neural network classification of autoregressive features from electroencephalogram signals for brain-computer interface design
    Huan NJ, Palaniappan R
    J Neural Eng, 2004 Sep;1(3):142-50.
    PMID: 15876633
    In this paper, we have designed a two-state brain-computer interface (BCI) using neural network (NN) classification of autoregressive (AR) features from electroencephalogram (EEG) signals extracted during mental tasks. The main purpose of the study is to use Keirn and Aunon's data to investigate the performance of different mental task combinations and different AR features for BCI design for individual subjects. In the experimental study, EEG signals from five mental tasks were recorded from four subjects. Different combinations of two mental tasks were studied for each subject. Six different feature extraction methods were used to extract the features from the EEG signals: AR coefficients computed with Burg's algorithm, AR coefficients computed with a least-squares (LS) algorithm and adaptive autoregressive (AAR) coefficients computed with a least-mean-square (LMS) algorithm. All the methods used order six applied to 125 data points and these three methods were repeated with the same data but with segmentation into five segments in increments of 25 data points. The multilayer perceptron NN trained by the back-propagation algorithm (MLP-BP) and linear discriminant analysis (LDA) were used to classify the computed features into different categories that represent the mental tasks. We compared the classification performances among the six different feature extraction methods. The results showed that sixth-order AR coefficients with the LS algorithm without segmentation gave the best performance (93.10%) using MLP-BP and (97.00%) using LDA. The results also showed that the segmentation and AAR methods are not suitable for this set of EEG signals. We conclude that, for different subjects, the best mental task combinations are different and proper selection of mental tasks and feature extraction methods are essential for the BCI design.
    Matched MeSH terms: Brain/physiology*
  6. Fulltext A System for True and False Memory Prediction Based on 2D and 3D Educational Contents and EEG Brain Signals
    Bamatraf S, Hussain M, Aboalsamh H, Qazi EU, Malik AS, Amin HU, et al.
    Comput Intell Neurosci, 2016;2016:8491046.
    PMID: 26819593 DOI: 10.1155/2016/8491046
    We studied the impact of 2D and 3D educational contents on learning and memory recall using electroencephalography (EEG) brain signals. For this purpose, we adopted a classification approach that predicts true and false memories in case of both short term memory (STM) and long term memory (LTM) and helps to decide whether there is a difference between the impact of 2D and 3D educational contents. In this approach, EEG brain signals are converted into topomaps and then discriminative features are extracted from them and finally support vector machine (SVM) which is employed to predict brain states. For data collection, half of sixty-eight healthy individuals watched the learning material in 2D format whereas the rest watched the same material in 3D format. After learning task, memory recall tasks were performed after 30 minutes (STM) and two months (LTM), and EEG signals were recorded. In case of STM, 97.5% prediction accuracy was achieved for 3D and 96.6% for 2D and, in case of LTM, it was 100% for both 2D and 3D. The statistical analysis of the results suggested that for learning and memory recall both 2D and 3D materials do not have much difference in case of STM and LTM.
    Matched MeSH terms: Brain/physiology*
  7. Fulltext Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders
    Arloth J, Bogdan R, Weber P, Frishman G, Menke A, Wagner KV, et al.
    Neuron, 2015 Jun 03;86(5):1189-202.
    PMID: 26050039 DOI: 10.1016/j.neuron.2015.05.034
    Depression risk is exacerbated by genetic factors and stress exposure; however, the biological mechanisms through which these factors interact to confer depression risk are poorly understood. One putative biological mechanism implicates variability in the ability of cortisol, released in response to stress, to trigger a cascade of adaptive genomic and non-genomic processes through glucocorticoid receptor (GR) activation. Here, we demonstrate that common genetic variants in long-range enhancer elements modulate the immediate transcriptional response to GR activation in human blood cells. These functional genetic variants increase risk for depression and co-heritable psychiatric disorders. Moreover, these risk variants are associated with inappropriate amygdala reactivity, a transdiagnostic psychiatric endophenotype and an important stress hormone response trigger. Network modeling and animal experiments suggest that these genetic differences in GR-induced transcriptional activation may mediate the risk for depression and other psychiatric disorders by altering a network of functionally related stress-sensitive genes in blood and brain.
    Matched MeSH terms: Brain/physiology*
  8. A new brain-computer interface design using fuzzy ARTMAP
    Palaniappan R, Paramesran R, Nishida S, Saiwaki N
    IEEE Trans Neural Syst Rehabil Eng, 2002 Sep;10(3):140-8.
    PMID: 12503778
    This paper proposes a new brain-computer interface (BCI) design using fuzzy ARTMAP (FA) neural network, as well as an application of the design. The objective of this BCI-FA design is to classify the best three of the five available mental tasks for each subject using power spectral density (PSD) values of electroencephalogram (EEG) signals. These PSD values are extracted using the Wiener-Khinchine and autoregressive methods. Ten experiments employing different triplets of mental tasks are studied for each subject. The findings show that the average BCI-FA outputs for four subjects gave less than 6% of error using the best triplets of mental tasks identified from the classification performances of FA. This implies that the BCI-FA can be successfully used with a tri-state switching device. As an application, a proposed tri-state Morse code scheme could be utilized to translate the outputs of this BCI-FA design into English letters. In this scheme, the three BCI-FA outputs correspond to a dot and a dash, which are the two basic Morse code alphabets and a space to denote the end (or beginning) of a dot or a dash. The construction of English letters using this tri-state Morse code scheme is determined only by the sequence of mental tasks and is independent of the time duration of each mental task. This is especially useful for constructing letters that are represented as multiple dots or dashes. This combination of BCI-FA design and the tri-state Morse code scheme could be developed as a communication system for paralyzed patients.
    Matched MeSH terms: Brain/physiology
  9. Fulltext Gut microbiota composition during infancy and subsequent behavioural outcomes
    Loughman A, Ponsonby AL, O'Hely M, Symeonides C, Collier F, Tang MLK, et al.
    EBioMedicine, 2020 Feb;52:102640.
    PMID: 32062351 DOI: 10.1016/j.ebiom.2020.102640
    BACKGROUND: Despite intense interest in the relationship between gut microbiota and brain development, longitudinal data from human studies are lacking. This study aimed to investigate the relationship between the composition of gut microbiota during infancy and subsequent behavioural outcomes.

    METHODS: A subcohort of 201 children with behavioural outcome measures was identified within a longitudinal, Australian birth-cohort study. The faecal microbiota were analysed at 1, 6, and 12 months of age. Behavioural outcomes were measured at 2 years of age.

    FINDINGS: In an unselected birth cohort, we found a clear association between decreased normalised abundance of Prevotella in faecal samples collected at 12 months of age and increased behavioural problems at 2 years, in particular Internalizing Problem scores. This association appeared independent of multiple potentially confounding variables, including maternal mental health. Recent exposure to antibiotics was the best predictor of decreased Prevotella.

    INTERPRETATION: Our findings demonstrate a strong association between the composition of the gut microbiota in infancy and subsequent behavioural outcomes; and support the importance of responsible use of antibiotics during early life.

    FUNDING: This study was funded by the National Health and Medical Research Council of Australia (1082307, 1147980, 1129813), The Murdoch Children's Research Institute, Barwon Health, Deakin University, Perpetual Trustees, and The Shepherd Foundation. The funders had no involvement in the data collection, analysis or interpretation, trial design, recruitment or any other aspect pertinent to the study.

    Matched MeSH terms: Brain/physiology
  10. Gene and protein expression profiles of JAK-STAT signalling pathway in the developing brain of the Ts1Cje down syndrome mouse model
    Lee HC, Md Yusof HH, Leong MP, Zainal Abidin S, Seth EA, Hewitt CA, et al.
    Int J Neurosci, 2019 Sep;129(9):871-881.
    PMID: 30775947 DOI: 10.1080/00207454.2019.1580280
    Aims: The JAK-STAT signalling pathway is one of the key regulators of pro-gliogenesis process during brain development. Down syndrome (DS) individuals, as well as DS mouse models, exhibit an increased number of astrocytes, suggesting an imbalance of neurogenic-to-gliogenic shift attributed to dysregulated JAK-STAT signalling pathway. The gene and protein expression profiles of JAK-STAT pathway members have not been characterised in the DS models. Therefore, we aimed to profile the expression of Jak1, Jak2, Stat1, Stat3 and Stat6 at different stages of brain development in the Ts1Cje mouse model of DS. Methods: Whole brain samples from Ts1Cje and wild-type mice at embryonic day (E)10.5, E15, postnatal day (P)1.5; and embryonic cortex-derived neurospheres were collected for gene and protein expression analysis. Gene expression profiles of three brain regions (cerebral cortex, cerebellum and hippocampus) from Ts1Cje and wild-type mice across four time-points (P1.5, P15, P30 and P84) were also analysed. Results: In the developing mouse brain, none of the Jak/Stat genes were differentially expressed in the Ts1Cje model compared to wild-type mice. However, Western blot analyses indicated that phosphorylated (p)-Jak2, p-Stat3 and p-Stat6 were downregulated in the Ts1Cje model. During the postnatal brain development, Jak/Stat genes showed complex expression patterns, as most of the members were downregulated at different selected time-points. Notably, embryonic cortex-derived neurospheres from Ts1Cje mouse brain expressed lower Stat3 and Stat6 protein compared to the wild-type group. Conclusion: The comprehensive expression profiling of Jak/Stat candidates provides insights on the potential role of the JAK-STAT signalling pathway during abnormal development of the Ts1Cje mouse brains.
    Matched MeSH terms: Brain/physiology*
  11. Fulltext An EEG Database and Its Initial Benchmark Emotion Classification Performance
    Seal A, Reddy PPN, Chaithanya P, Meghana A, Jahnavi K, Krejcar O, et al.
    Comput Math Methods Med, 2020;2020:8303465.
    PMID: 32831902 DOI: 10.1155/2020/8303465
    Human emotion recognition has been a major field of research in the last decades owing to its noteworthy academic and industrial applications. However, most of the state-of-the-art methods identified emotions after analyzing facial images. Emotion recognition using electroencephalogram (EEG) signals has got less attention. However, the advantage of using EEG signals is that it can capture real emotion. However, very few EEG signals databases are publicly available for affective computing. In this work, we present a database consisting of EEG signals of 44 volunteers. Twenty-three out of forty-four are females. A 32 channels CLARITY EEG traveler sensor is used to record four emotional states namely, happy, fear, sad, and neutral of subjects by showing 12 videos. So, 3 video files are devoted to each emotion. Participants are mapped with the emotion that they had felt after watching each video. The recorded EEG signals are considered further to classify four types of emotions based on discrete wavelet transform and extreme learning machine (ELM) for reporting the initial benchmark classification performance. The ELM algorithm is used for channel selection followed by subband selection. The proposed method performs the best when features are captured from the gamma subband of the FP1-F7 channel with 94.72% accuracy. The presented database would be available to the researchers for affective recognition applications.
    Matched MeSH terms: Brain/physiology
  12. Expression of neuropeptide Y and gonadotropin-releasing hormone gene types in the brain of female Nile tilapia (Oreochromis niloticus) during mouthbrooding and food restriction
    Das K, Ogawa S, Kitahashi T, Parhar IS
    Peptides, 2019 02;112:67-77.
    PMID: 30389346 DOI: 10.1016/j.peptides.2018.10.009
    A cichlid fish, the Nile tilapia (Oreochromis niloticus), is a maternal mouthbrooder, which exhibits minimum energy expenditure and slower ovarian cycles during mouthbrooding. The objective of this study was to observe changes in the gene expression of key neuropeptides involved in the control of appetite and reproduction, including neuropeptide Y a (NPYa), reproductive neuropeptides: gonadotropin-releasing hormone (GnRH1, GnRH2 and GnRH3) and kisspeptin (Kiss2) during mouthbrooding (4- and 12-days), 12-days of food restriction and 12-days of food restriction followed by refeeding. The food restriction regime showed a significant increase in npya mRNA levels in the telencephalon. However, there were no significant alterations in npya mRNA levels during mouthbrooding. gnrh1 mRNA levels were significantly lower in mouthbrooding female as compared with females with food restriction. gnrh3 mRNA levels were also significantly lower in female with 12-days of mouthbrooding, 12-days of food restriction followed by 12-days of refeeding when compared with controls. There were no significant differences in gnrh2 and kiss2 mRNA levels between groups under different feeding regimes. No significant changes were observed in mRNA levels of receptors for peripheral metabolic signaling molecules: ghrelin (GHS-R1a and GHS-R1b) and leptin (Lep-R). These results suggested that unaffected npya mRNA levels in the telencephalon might contribute to suppression of appetite in mouthbrooding female tilapia. Furthermore, lower gnrh1 and gnrh3 mRNA levels may influence the suppression of reproductive functions such as progression of ovarian cycle and reproductive behaviours, while GnRH2 and Kiss2 may not play a significant roles in reproduction under food restriction condition.
    Matched MeSH terms: Brain/physiology
  13. A rapid event-related potential (ERP) method for point-of-care evaluation of brain function: development of the Halifax Consciousness Scanner
    Sculthorpe-Petley L, Liu C, Hajra SG, Parvar H, Satel J, Trappenberg TP, et al.
    J Neurosci Methods, 2015 Apr 30;245:64-72.
    PMID: 25701685 DOI: 10.1016/j.jneumeth.2015.02.008
    Event-related potentials (ERPs) may provide a non-invasive index of brain function for a range of clinical applications. However, as a lab-based technique, ERPs are limited by technical challenges that prevent full integration into clinical settings.
    Matched MeSH terms: Brain/physiology*
  14. Genomic instantiation of consciousness in neurons through a biophoton field theory
    Cacha LA, Poznanski RR
    J Integr Neurosci, 2014 Jun;13(2):253-92.
    PMID: 25012712 DOI: 10.1142/S0219635214400081
    A theoretical framework is developed based on the premise that brains evolved into sufficiently complex adaptive systems capable of instantiating genomic consciousness through self-awareness and complex interactions that recognize qualitatively the controlling factors of biological processes. Furthermore, our hypothesis assumes that the collective interactions in neurons yield macroergic effects, which can produce sufficiently strong electric energy fields for electronic excitations to take place on the surface of endogenous structures via alpha-helical integral proteins as electro-solitons. Specifically the process of radiative relaxation of the electro-solitons allows for the transfer of energy via interactions with deoxyribonucleic acid (DNA) molecules to induce conformational changes in DNA molecules producing an ultra weak non-thermal spontaneous emission of coherent biophotons through a quantum effect. The instantiation of coherent biophotons confined in spaces of DNA molecules guides the biophoton field to be instantaneously conducted along the axonal and neuronal arbors and in-between neurons and throughout the cerebral cortex (cortico-thalamic system) and subcortical areas (e.g., midbrain and hindbrain). Thus providing an informational character of the electric coherence of the brain - referred to as quantum coherence. The biophoton field is realized as a conscious field upon the re-absorption of biophotons by exciplex states of DNA molecules. Such quantum phenomenon brings about self-awareness and enables objectivity to have access to subjectivity in the unconscious. As such, subjective experiences can be recalled to consciousness as subjective conscious experiences or qualia through co-operative interactions between exciplex states of DNA molecules and biophotons leading to metabolic activity and energy transfer across proteins as a result of protein-ligand binding during protein-protein communication. The biophoton field as a conscious field is attributable to the resultant effect of specifying qualia from the metabolic energy field that is transported in macromolecular proteins throughout specific networks of neurons that are constantly transforming into more stable associable representations as molecular solitons. The metastability of subjective experiences based on resonant dynamics occurs when bottom-up patterns of neocortical excitatory activity are matched with top-down expectations as adaptive dynamic pressures. These dynamics of on-going activity patterns influenced by the environment and selected as the preferred subjective experience in terms of a functional field through functional interactions and biological laws are realized as subjectivity and actualized through functional integration as qualia. It is concluded that interactionism and not information processing is the key in understanding how consciousness bridges the explanatory gap between subjective experiences and their neural correlates in the transcendental brain.
    Matched MeSH terms: Brain/physiology*
  15. A comparison of brain phantom relative permittivity with CST simulation library and existing research
    Chew KM, Seman N, Sudirman R, Yong CY
    Biomed Mater Eng, 2014;24(6):2161-7.
    PMID: 25226914 DOI: 10.3233/BME-141027
    The development of human-like brain phantom is important for data acquisition in microwave imaging. The characteristics of the phantom should be based on the real human body dielectric properties such as relative permittivity. The development of phantom includes the greymatter and whitematter regions, each with a relative permittivity of 38 and 28 respectively at 10 GHz frequency. Results were compared with the value obtained from the standard library of Computer Simulation Technology (CST) simulation application and the existing research by Fernandez and Gabriel. Our experimental results show a positive outcome, in which the proposed mixture was adequate to represent real human brain for data acquisition.
    Matched MeSH terms: Brain/physiology*
  16. The effects of aging on the brain activation pattern during a speech perception task: an fMRI study
    Manan HA, Franz EA, Yusoff AN, Mukari SZ
    Aging Clin Exp Res, 2015 Feb;27(1):27-36.
    PMID: 24906677 DOI: 10.1007/s40520-014-0240-0
    In the present study, brain activation associated with speech perception processing was examined across four groups of adult participants with age ranges between 20 and 65 years, using functional MRI (fMRI). Cognitive performance demonstrates that performance accuracy declines with age. fMRI results reveal that all four groups of participants activated the same brain areas. The same brain activation pattern was found in all activated areas (except for the right superior temporal gyrus and right middle temporal gyrus); brain activity was increased from group 1 (20-29 years) to group 2 (30-39 years). However, it decreased in group 3 (40-49 years) with further decreases in group 4 participants (50-65 years). Result also reveals that three brain areas (superior temporal gyrus, Heschl's gyrus and cerebellum) showed changes in brain laterality in the older participants, akin to a shift from left-lateralized to right-lateralized activity. The onset of this change was different across brain areas. Based on these findings we suggest that, whereas all four groups of participants used the same areas in processing, the engagement and recruitment of those areas differ with age as the brain grows older. Findings are discussed in the context of corroborating evidence of neural changes with age.
    Matched MeSH terms: Brain/physiology*
  17. Asynchronous brain machine interface-based control of a wheelchair
    Hema CR, Paulraj MP, Yaacob S, Adom AH, Nagarajan R
    Adv Exp Med Biol, 2011;696:565-72.
    PMID: 21431597 DOI: 10.1007/978-1-4419-7046-6_57
    A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is based on only two electrodes and operated by motor imagery of four states. A recurrent neural classifier is proposed for the classification of the four mental states. The real-time experiment results of four subjects are reported and problems emerging from asynchronous control are discussed.
    Matched MeSH terms: Brain/physiology
  18. EEG spectral analysis on Muslim prayers
    Doufesh H, Faisal T, Lim KS, Ibrahim F
    Appl Psychophysiol Biofeedback, 2012 Mar;37(1):11-8.
    PMID: 21965118 DOI: 10.1007/s10484-011-9170-1
    This study investigated the proposition of relaxation offered by performing the Muslim prayers by measuring the alpha brain activity in the frontal (F3-F4), central (C3-C4), parietal (P3-P4), and occipital (O1-O2) electrode placements using the International 10-20 System. Nine Muslim subjects were asked to perform the four required cycles of movements of Dhuha prayer, and the EEG were subsequently recorded with open eyes under three conditions, namely, resting, performing four cycles of prayer while reciting the specific verses and supplications, and performing four cycles of acted salat condition (prayer movements without any recitations). Analysis of variance (ANOVA) tests revealed that there were no significant difference in the mean alpha relative power (RP(α)) between the alpha amplitude in the Dhuha prayer and the acted conditions in all eight electrode positions. However, the mean RP(α) showed higher alpha amplitude during the prostration position of the Dhuha prayer and acted condition at the parietal and occipital regions in comparison to the resting condition. Findings were similar to other studies documenting increased alpha amplitude in parietal and occipital regions during meditation and mental concentration. The incidence of increased alpha amplitude suggested parasympathetic activation, thus indicating a state of relaxation. Subsequent studies are needed to delineate the role of mental concentration, and eye focus, on alpha wave amplitude while performing worshipping acts.
    Matched MeSH terms: Brain/physiology
  19. A study on discrete wavelet-based noise removal from EEG signals
    Asaduzzaman K, Reaz MB, Mohd-Yasin F, Sim KS, Hussain MS
    Adv Exp Med Biol, 2010;680:593-9.
    PMID: 20865544 DOI: 10.1007/978-1-4419-5913-3_65
    Electroencephalogram (EEG) serves as an extremely valuable tool for clinicians and researchers to study the activity of the brain in a non-invasive manner. It has long been used for the diagnosis of various central nervous system disorders like seizures, epilepsy, and brain damage and for categorizing sleep stages in patients. The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly. Result of this study shows that WF Daubechies 8 (db8) provides the best noise removal from the raw EEG signal of healthy patients, while WF orthogonal Meyer does the same for epileptic patients. This algorithm is intended for FPGA implementation of portable biomedical equipments to detect different brain state in different circumstances.
    Matched MeSH terms: Brain/physiology
  20. Enhanced mu rhythm extraction using blind source separation and wavelet transform
    Ng SC, Raveendran P
    IEEE Trans Biomed Eng, 2009 Aug;56(8):2024-34.
    PMID: 19457744 DOI: 10.1109/TBME.2009.2021987
    The mu rhythm is an electroencephalogram (EEG) signal located at the central region of the brain that is frequently used for studies concerning motor activity. Quite often, the EEG data are contaminated with artifacts and the application of blind source separation (BSS) alone is insufficient to extract the mu rhythm component. We present a new two-stage approach to extract the mu rhythm component. The first stage uses second-order blind identification (SOBI) with stationary wavelet transform (SWT) to automatically remove the artifacts. In the second stage, SOBI is applied again to find the mu rhythm component. Our method is first compared with independent component analysis with discrete wavelet transform (ICA-DWT) as well as SOBI-DWT, ICA-SWT, and regression method for artifact removal using simulated EEG data. The results showed that the regression method is more effective in removing electrooculogram (EOG) artifacts, while SOBI-SWT is more effective in removing electromyogram (EMG) artifacts as compared to the other artifact removal methods. Then, all the methods are compared with the direct application of SOBI in extracting mu rhythm components on simulated and actual EEG data from ten subjects. The results showed that the proposed method of SOBI-SWT artifact removal enhances the extraction of the mu rhythm component.
    Matched MeSH terms: Brain/physiology*
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