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Differences in right hemisphere fNIRS activation associated with executive network during performance of the lateralized attention network tast by elite, expert and novice ice hockey athletes

Yu M, Xu S, Hu H, Li S, Yang G

Behav Brain Res, 2023 Apr 12;443:114209.
PMID: 36368444 DOI: 10.1016/j.bbr.2022.114209

OBJECTIVE: We investigated brain activity associated with executive control attention network in elite, expert, and novice female ice hockey athletes during the revised lateralized attention network tast to determine whether the neural correlates of performance differ by skill level.
METHODS: We collected and analyzed functional near-infrared spectroscopy data of 38 participants while performing the revised lateralized attention network tast.
RESULTS: Elite players were significantly faster than novices (p = .005), and the experts' overall accuracy rate (ACC) was higher than that of novices (p = .001). The effect of the executive network on reaction time was higher in novices than in elite players (p = .008) and experts (p = .004). The effect of the executive network on the ACC was lower in elite players than in experts (p = .009) and novices (p = .010). Finally, elite player had higher flanker conflict effects on RT (p = .005) under the invalid cue condition. the effect of the alertness network and orientation on the ACC was lower in elite players than in novices (p = .000) and experts (p = .022). Changes in the blood oxygen level-dependent signal related to the flanker effect were significantly different in the right dorsolateral prefrontal cortex (F=3.980, p = .028) and right inferior frontal gyrus (F=3.703, p = .035) among the three groups. Elit players showed more efficient executive control (reduced conflict effect on ACC) (p = .006)in the RH.The changes related to the effect of blood oxygen level on orienting were significantly different in the right frontal eye fields (F=3.883, p = .030) among the three groups, Accompanied by significant activation of the right dorsolateral prefrontal cortex(p = .026).
CONCLUSION: Our findings provide partial evidence of the superior cognitive performance and high neural efficiency of elite ice hockey players during cognitive tasks. These results demonstrate the right hemisphere superiority for executive control.We also found that specific brain activation in hockey players does not show a clear and linear relationship with skill level.

Matched MeSH terms: Brain/physiology
Fulltext The Decline of Cortical Beta Oscillation on the Function of Eye-hand Coordination in the Healthy Elderly

Manor R, Cheaha D, Perimal E, Sathirapanya P, Kumarnsit E, Samerphob N

In Vivo, 2023;37(4):1649-1657.
PMID: 37369513 DOI: 10.21873/invivo.13250

BACKGROUND/AIM: There seems to be a correlation between changes in movement patterns with aging and brain activation. In the preparation and execution of movements, neural oscillations play an important role. In this study, cortical high frequency brain oscillations were analyzed in 15 healthy young adults and 15 elderly adults who participated in eye-hand coordination tasks.
PATIENTS AND METHODS: The brain activities of healthy young and older adults were recorded using electroencephalography (EEG).
RESULTS: Elderly participants spent significantly more time completing the task than young participants. During eye-hand coordination in elderly groups, beta power decreased significantly in the central midline and parietal brain regions. The data suggest that healthy elderly subjects had intact cognitive performance, but relatively poor eye-hand coordination associated with loss of beta brain oscillation in the central midline and parietal cortex and reduced ability to attentional movement.
CONCLUSION: Beta frequency in the parietal brain sites may contribute to attentional movement. This could be an important method for monitoring cognitive brain function changes as the brain ages.

Matched MeSH terms: Brain/physiology
Tracking of EEG activity using motion estimation to understand brain wiring

Nisar H, Malik AS, Ullah R, Shim SO, Bawakid A, Khan MB, et al.

Adv Exp Med Biol, 2015;823:159-74.
PMID: 25381107 DOI: 10.1007/978-3-319-10984-8_9

The fundamental step in brain research deals with recording electroencephalogram (EEG) signals and then investigating the recorded signals quantitatively. Topographic EEG (visual spatial representation of EEG signal) is commonly referred to as brain topomaps or brain EEG maps. In this chapter, full search full search block motion estimation algorithm has been employed to track the brain activity in brain topomaps to understand the mechanism of brain wiring. The behavior of EEG topomaps is examined throughout a particular brain activation with respect to time. Motion vectors are used to track the brain activation over the scalp during the activation period. Using motion estimation it is possible to track the path from the starting point of activation to the final point of activation. Thus it is possible to track the path of a signal across various lobes.

Matched MeSH terms: Brain/physiology*
Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network

Jahidin AH, Megat Ali MS, Taib MN, Tahir NM, Yassin IM, Lias S

Comput Methods Programs Biomed, 2014 Apr;114(1):50-9.
PMID: 24560277 DOI: 10.1016/j.cmpb.2014.01.016

This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies.

Matched MeSH terms: Brain/physiology*
Two dimensional affective state distribution of the brain under emotion stimuli

Yaacob H, Karim I, Wahab A, Kamaruddin N

Annu Int Conf IEEE Eng Med Biol Soc, 2012;2012:6052-5.
PMID: 23367309 DOI: 10.1109/EMBC.2012.6347374

Emotions are ambiguous. Many techniques have been employed to perform emotion prediction and to understand emotional elicitations. Brain signals measured using electroencephalogram (EEG) are also used in studies about emotions. Using KDE as feature extraction technique and MLP for performing supervised learning on the brain signals. It has shown that all channels in EEG can capture emotional experience. In addition it was also indicated that emotions are dynamic as represented by the level of valence and the intensity of arousal. Such findings are useful in biomedical studies, especially in dealing with emotional disorders which can results in using a two-channel EEG device for neurofeedback applications.

Matched MeSH terms: Brain/physiology*
A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison

Hamada M, Zaidan BB, Zaidan AA

J Med Syst, 2018 Jul 24;42(9):162.
PMID: 30043178 DOI: 10.1007/s10916-018-1020-8

The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept is limited. To extend research in this area, the researchers explored and analysed the academic articles published within the mentioned scope. Thus, in this paper a systematic review is carried out to map and draw the research scenery for EEG human emotion into a taxonomy. Systematically searched all articles about the, EEG human emotion based music in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 1999 to 2016. These databases feature academic studies that used EEG to measure brain signals, with a focus on the effects of music on human emotions. The screening and filtering of articles were performed in three iterations. In the first iteration, duplicate articles were excluded. In the second iteration, the articles were filtered according to their titles and abstracts, and articles outside of the scope of our domain were excluded. In the third iteration, the articles were filtered by reading the full text and excluding articles outside of the scope of our domain and which do not meet our criteria. Based on inclusion and exclusion criteria, 100 articles were selected and separated into five classes. The first class includes 39 articles (39%) consists of emotion, wherein various emotions are classified using artificial intelligence (AI). The second class includes 21 articles (21%) is composed of studies that use EEG techniques. This class is named 'brain condition'. The third class includes eight articles (8%) is related to feature extraction, which is a step before emotion classification. That this process makes use of classifiers should be noted. However, these articles are not listed under the first class because these eight articles focus on feature extraction rather than classifier accuracy. The fourth class includes 26 articles (26%) comprises studies that compare between or among two or more groups to identify and discover human emotion-based EEG. The final class includes six articles (6%) represents articles that study music as a stimulus and its impact on brain signals. Then, discussed the five main categories which are action types, age of the participants, and number size of the participants, duration of recording and listening to music and lastly countries or authors' nationality that published these previous studies. it afterward recognizes the main characteristics of this promising area of science in: motivation of using EEG process for measuring human brain signals, open challenges obstructing employment and recommendations to improve the utilization of EEG process.

Matched MeSH terms: Brain/physiology
Fulltext Theorizing how the brain encodes consciousness based on negentropic entanglement

Poznanski RR, Cacha LA, Latif AZA, Salleh SH, Ali J, Yupapin P, et al.

J Integr Neurosci, 2019 03 30;18(1):1-10.
PMID: 31091842 DOI: 10.31083/j.jin.2019.01.105

The physicality of subjectivity is explained through a theoretical conceptualization of guidance waves informing meaning in negentropically entangled non-electrolytic brain regions. Subjectivity manifests its influence at the microscopic scale of matter originating from de Broglie 'hidden' thermodynamics as action of guidance waves. The preconscious experienceability of subjectivity is associated with a nested hierarchy of microprocesses, which are actualized as a continuum of patterns of discrete atomic microfeels (or "qualia"). The mechanism is suggested to be through negentropic entanglement of hierarchical thermodynamic transfer of information as thermo-qubits originating from nonpolarized regions of actin-binding proteinaceous structures of nonsynaptic spines. The resultant continuous stream of intrinsic information entails a negentropic action (or experiential flow of thermo-quantum internal energy that results in a negentropic force) which is encoded through the non-zero real component of the mean approximation of the negentropic force as a 'consciousness code'. Consciousness consisting of two major subprocesses: (1) preconscious experienceability and (2) conscious experience. Both are encapsulated by nonreductive physicalism and panexperiential materialism. The subprocess (1) governing "subjectivity" carries many microprocesses leading to the actualization of discrete atomic microfeels by the 'consciousness code'. These atomic microfeels constitute internal energy that results in the transfer intrinsic information in terms of thermo-qubits. These thermo-qubits are realized as thermal entropy and sensed by subprocess (2) governing "self-awareness" in conscious experience.

Matched MeSH terms: Brain/physiology*
Developmental programing of thirst and sodium appetite

Mecawi AS, Macchione AF, Nuñez P, Perillan C, Reis LC, Vivas L, et al.

Neurosci Biobehav Rev, 2015 Apr;51:1-14.
PMID: 25528684 DOI: 10.1016/j.neubiorev.2014.12.012

Thirst and sodium appetite are the sensations responsible for the motivated behaviors of water and salt intake, respectively, and both are essential responses for the maintenance of hydromineral homeostasis in animals. These sensations and their related behaviors develop very early in the postnatal period in animals. Many studies have demonstrated several pre- and postnatal stimuli that are responsible for the developmental programing of thirst and sodium appetite and, consequently, the pattern of water and salt intake in adulthood in need-free or need-induced conditions. The literature systematically reports the involvement of dietary changes, hydromineral and cardiovascular challenges, renin-angiotensin system and steroid hormone disturbances, and lifestyle in these developmental factors. Therefore, this review will address how pre- and postnatal challenges can program lifelong thirst and sodium appetite in animals and humans, as well as which neuroendocrine substrates are involved. In addition, the possible epigenetic molecular mechanisms responsible for the developmental programing of drinking behavior, the clinical implications of hydromineral disturbances during pre- and postnatal periods, and the developmental origins of adult hydromineral behavior will be discussed.

Matched MeSH terms: Brain/physiology
Human memory retention and recall processes. A review of EEG and fMRI studies

Amin H, Malik AS

Neurosciences (Riyadh), 2013 Oct;18(4):330-44.
PMID: 24141456

Human memory is an important concept in cognitive psychology and neuroscience. Our brain is actively engaged in functions of learning and memorization. Generally, human memory has been classified into 2 groups: short-term/working memory, and long-term memory. Using different memory paradigms and brain mapping techniques, psychologists and neuroscientists have identified 3 memory processes: encoding, retention, and recall. These processes have been studied using EEG and functional MRI (fMRI) in cognitive and neuroscience research. This study reviews previous research reported for human memory processes, particularly brain behavior in memory retention and recall processes with the use of EEG and fMRI. We discuss issues and challenges related to memory research with EEG and fMRI techniques.

Matched MeSH terms: Brain/physiology*
Model-based neuroimaging for cognitive computing

Poznanski RR

J Integr Neurosci, 2009 Sep;8(3):345-69.
PMID: 19938210

The continuity of the mind is suggested to mean the continuous spatiotemporal dynamics arising from the electrochemical signature of the neocortex: (i) globally through volume transmission in the gray matter as fields of neural activity, and (ii) locally through extrasynaptic signaling between fine distal dendrites of cortical neurons. If the continuity of dynamical systems across spatiotemporal scales defines a stream of consciousness then intentional metarepresentations as templates of dynamic continuity allow qualia to be semantically mapped during neuroimaging of specific cognitive tasks. When interfaced with a computer, such model-based neuroimaging requiring new mathematics of the brain will begin to decipher higher cognitive operations not possible with existing brain-machine interfaces.

Matched MeSH terms: Brain/physiology*
Fulltext Randomised prior feedback modulates neural signals of outcome monitoring

Mushtaq F, Wilkie RM, Mon-Williams MA, Schaefer A

Neuroimage, 2016 Jan 15;125:868-879.
PMID: 26497268 DOI: 10.1016/j.neuroimage.2015.10.046

Substantial evidence indicates that decision outcomes are typically evaluated relative to expectations learned from relatively long sequences of previous outcomes. This mechanism is thought to play a key role in general learning and adaptation processes but relatively little is known about the determinants of outcome evaluation when the capacity to learn from series of prior events is difficult or impossible. To investigate this issue, we examined how the feedback-related negativity (FRN) is modulated by information briefly presented before outcome evaluation. The FRN is a brain potential time-locked to the delivery of decision feedback and it is widely thought to be sensitive to prior expectations. We conducted a multi-trial gambling task in which outcomes at each trial were fully randomised to minimise the capacity to learn from long sequences of prior outcomes. Event-related potentials for outcomes (Win/Loss) in the current trial (Outcomet) were separated according to the type of outcomes that occurred in the preceding two trials (Outcomet-1 and Outcomet-2). We found that FRN voltage was more positive during the processing of win feedback when it was preceded by wins at Outcomet-1 compared to win feedback preceded by losses at Outcomet-1. However, no influence of preceding outcomes was found on FRN activity relative to the processing of loss feedback. We also found no effects of Outcomet-2 on FRN amplitude relative to current feedback. Additional analyses indicated that this effect was largest for trials in which participants selected a decision different to the gamble chosen in the previous trial. These findings are inconsistent with models that solely relate the FRN to prediction error computation. Instead, our results suggest that if stable predictions about future events are weak or non-existent, then outcome processing can be determined by affective systems. More specifically, our results indicate that the FRN is likely to reflect the activity of positive affective systems in these contexts. Importantly, our findings indicate that a multifactorial explanation of the nature of the FRN is necessary and such an account must incorporate affective and motivational factors in outcome processing.

Matched MeSH terms: Brain/physiology*
Fulltext Eating with our eyes: From visual hunger to digital satiation

Spence C, Okajima K, Cheok AD, Petit O, Michel C

Brain Cogn, 2016 12;110:53-63.
PMID: 26432045 DOI: 10.1016/j.bandc.2015.08.006

One of the brain's key roles is to facilitate foraging and feeding. It is presumably no coincidence, then, that the mouth is situated close to the brain in most animal species. However, the environments in which our brains evolved were far less plentiful in terms of the availability of food resources (i.e., nutriments) than is the case for those of us living in the Western world today. The growing obesity crisis is but one of the signs that humankind is not doing such a great job in terms of optimizing the contemporary food landscape. While the blame here is often put at the doors of the global food companies - offering addictive foods, designed to hit 'the bliss point' in terms of the pleasurable ingredients (sugar, salt, fat, etc.), and the ease of access to calorie-rich foods - we wonder whether there aren't other implicit cues in our environments that might be triggering hunger more often than is perhaps good for us. Here, we take a closer look at the potential role of vision; Specifically, we question the impact that our increasing exposure to images of desirable foods (what is often labelled 'food porn', or 'gastroporn') via digital interfaces might be having, and ask whether it might not inadvertently be exacerbating our desire for food (what we call 'visual hunger'). We review the growing body of cognitive neuroscience research demonstrating the profound effect that viewing such images can have on neural activity, physiological and psychological responses, and visual attention, especially in the 'hungry' brain.

Matched MeSH terms: Brain/physiology*
Simultaneous EEG-fMRI for working memory of the human brain

Ahmad RF, Malik AS, Kamel N, Reza F, Abdullah JM

Australas Phys Eng Sci Med, 2016 Jun;39(2):363-78.
PMID: 27043850 DOI: 10.1007/s13246-016-0438-x

Memory plays an important role in human life. Memory can be divided into two categories, i.e., long term memory and short term memory (STM). STM or working memory (WM) stores information for a short span of time and it is used for information manipulations and fast response activities. WM is generally involved in the higher cognitive functions of the brain. Different studies have been carried out by researchers to understand the WM process. Most of these studies were based on neuroimaging modalities like fMRI, EEG, MEG etc., which use standalone processes. Each neuroimaging modality has some pros and cons. For example, EEG gives high temporal resolution but poor spatial resolution. On the other hand, the fMRI results have a high spatial resolution but poor temporal resolution. For a more in depth understanding and insight of what is happening inside the human brain during the WM process or during cognitive tasks, high spatial as well as high temporal resolution is desirable. Over the past decade, researchers have been working to combine different modalities to achieve a high spatial and temporal resolution at the same time. Developments of MRI compatible EEG equipment in recent times have enabled researchers to combine EEG-fMRI successfully. The research publications in simultaneous EEG-fMRI have been increasing tremendously. This review is focused on the WM research involving simultaneous EEG-fMRI data acquisition and analysis. We have covered the simultaneous EEG-fMRI application in WM and data processing. Also, it adds to potential fusion methods which can be used for simultaneous EEG-fMRI for WM and cognitive tasks.

Matched MeSH terms: Brain/physiology*
ConnectViz: Accelerated Approach for Brain Structural Connectivity Using Delaunay Triangulation

Adeshina AM, Hashim R

Interdiscip Sci, 2016 Mar;8(1):53-64.
PMID: 26260066 DOI: 10.1007/s12539-015-0274-9

Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using compute unified device architecture, extending the previously proposed SurLens Visualization and computer aided hepatocellular carcinoma frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, USA. Significantly, our proposed framework is able to generate and extract points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.

Matched MeSH terms: Brain/physiology*
On the binaural brain entrainment indicating lower heart rate variability

Palaniappan R, Phon-Amnuaisuk S, Eswaran C

Int J Cardiol, 2015;190:262-3.
PMID: 25932800 DOI: 10.1016/j.ijcard.2015.04.175
Matched MeSH terms: Brain/physiology*
Fulltext Local context influences memory for emotional stimuli but not electrophysiological markers of emotion-dependent attention

Barnacle GE, Tsivilis D, Schaefer A, Talmi D

Psychophysiology, 2018 04;55(4).
PMID: 29023754 DOI: 10.1111/psyp.13014

Emotional enhancement of free recall can be context dependent. It is readily observed when emotional and neutral scenes are encoded and recalled together in a "mixed" list, but diminishes when these scenes are encoded separately in "pure" lists. We examined the hypothesis that this effect is due to differences in allocation of attention to neutral stimuli according to whether they are presented in mixed or pure lists, especially when encoding is intentional. Using picture stimuli that were controlled for semantic relatedness, our results contradicted this hypothesis. The amplitude of well-known electrophysiological markers of emotion-related attention-the early posterior negativity (EPN), the late positive potential (LPP), and the slow wave (SW)-was higher for emotional stimuli. Crucially, the emotional modulation of these ERPs was insensitive to list context, observed equally in pure and mixed lists. Although list context did not modulate neural markers of emotion-related attention, list context did modulate the effect of emotion on free recall. The apparent decoupling of the emotional effects on attention and memory, challenges existing hypotheses accounting for the emotional enhancement of memory. We close by discussing whether findings are more compatible with an alternative hypothesis, where the magnitude of emotional memory enhancement is, at least in part, a consequence of retrieval dynamics.

Matched MeSH terms: Brain/physiology*
How do Asians perceive Caucasian eyes? Electrophysiological correlates of perceiving racial differences from the eyes region of the face

Yong MH, Lim XL, Schaefer A

Neurosci Lett, 2020 02 16;720:134759.
PMID: 31952988 DOI: 10.1016/j.neulet.2020.134759

Past research has found that several brain event-related potentials (ERPs) were sensitive to the perception of ethnic differences displayed on human faces. This body of research suggests that the phenomenon of "race perception" involves a cascade of cognitive processes that includes both automatic and overt attentional mechanisms. However, most of these studies used stimuli depicting whole faces rather than stimuli depicting separate facial features. Therefore, it is still largely unknown if ERP responses to racial differences are the result of a holistic processing of the whole face, or whether they can be accounted for by the perception of single facial features. To address this issue, we examined whether a single facial feature, the eyes region, can provide sufficient information to trigger known ERP correlates of race perception such as the P2, the N400 and the Late Positive Complex (LPC). Specifically, we showed pictures depicting only the eyes region of Caucasian and Asian faces to a sample of Asian participants. We found that the P2 was larger for other-race (OR) compared to same-race (SR) eyes, and that the N400 was larger for SR compared to OR eyes. The effects on the P2 may suggest an enhanced vigilance response to OR eyes whereas the N400 effect could reflect a signal of familiarity triggered by SR eyes. These results indicate that a specific facial feature, the eyes region, can account for known effects of race perception on early brain potentials. Our findings also indicate that well-known early neural correlates of race perception can be triggered in the absence of a holistic processing of the whole face.

Matched MeSH terms: Brain/physiology*
Molecular evolutionary and 3D protein structural analyses of Lactobacillus fermentum elongation factor Tu, a novel brain health promoting factor

Ong JS, Liu YW, Liong MT, Choi SB, Tsai YC, Low WY

Genomics, 2020 11;112(6):3915-3924.
PMID: 32629096 DOI: 10.1016/j.ygeno.2020.06.052

The role of microbiota in gut-brain communication has led to the development of probiotics promoting brain health. Here we report a genomic study of a Lactobacillus fermentum PS150 and its patented bioactive protein, elongation factor Tu (EF-Tu), which is associated with cognitive improvement in rats. The L. fermentum PS150 circular chromosome is 2,238,401 bp and it consists of 2281 genes. Chromosome comparisons with other L. fermentum strains highlighted a cluster of glycosyltransferases as potential candidate probiotic factors besides EF-Tu. Molecular evolutionary analyses on EF-Tu genes (tuf) in 235 bacteria species revealed one to three copies of the gene per genome. Seven tuf pseudogenes were found and three species only possessed pseudogenes, which is an unprecedented finding. Protein variability analysis of EF-Tu showed five highly variable residues (40 K, 41G, 42 L, 44 K, and 46E) on the protein surface, which warrant further investigation regarding their potential roles as binding sites.

Matched MeSH terms: Brain/physiology*
Effects of Muslims praying (Salat) on EEG gamma activity

Doufesh H, Ibrahim F, Safari M

Complement Ther Clin Pract, 2016 Aug;24:6-10.
PMID: 27502795 DOI: 10.1016/j.ctcp.2016.04.004

This study investigates the difference of mean gamma EEG power between actual and mimic Salat practices in twenty healthy Muslim subjects. In the actual Salat practice, the participants were asked to recite and performing the physical steps in all four stages of Salat; whereas in the mimic Salat practice, they were instructed to perform only the physical steps without recitation. The gamma power during actual Salat was statistically higher than during mimic Salat in the frontal and parietal regions in all stages. In the actual Salat practice, the left hemisphere exhibited significantly higher mean gamma power in all cerebral regions and all stages, except the central-parietal region in the sitting position, and the frontal area in the bowing position. Increased gamma power during Salat, possibly related to an increase in cognitive and attentional processing, supports the concept of Salat as a focus attention meditation.

Matched MeSH terms: Brain/physiology*
Visual brain activity patterns classification with simultaneous EEG-fMRI: A multimodal approach

Ahmad RF, Malik AS, Kamel N, Reza F, Amin HU, Hussain M

Technol Health Care, 2017;25(3):471-485.
PMID: 27935575 DOI: 10.3233/THC-161286

BACKGROUND: Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map the brain activity. For getting a high spatial and temporal resolution of the brain at the same time, simultaneous EEG-fMRI seems to be fruitful.
METHODS: In this article, we propose a new method based on simultaneous EEG-fMRI data and machine learning approach to classify the visual brain activity patterns. We acquired EEG-fMRI data simultaneously on the ten healthy human participants by showing them visual stimuli. Data fusion approach is used to merge EEG and fMRI data. Machine learning classifier is used for the classification purposes.
RESULTS: Results showed that superior classification performance has been achieved with simultaneous EEG-fMRI data as compared to the EEG and fMRI data standalone. This shows that multimodal approach improved the classification accuracy results as compared with other approaches reported in the literature.
CONCLUSIONS: The proposed simultaneous EEG-fMRI approach for classifying the brain activity patterns can be helpful to predict or fully decode the brain activity patterns.

Matched MeSH terms: Brain/physiology

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