scholarly journals The Significance of Delta Wave Among Athletes

2018 ◽  
Vol 7 (3.18) ◽  
pp. 7
Author(s):  
Norsiah Fauzan ◽  
Nor Mazlina Ghazali
Keyword(s):  
Stroop Task ◽  
Gamma Oscillations ◽  
Peak Performance ◽  
Quantitative Electroencephalography ◽  
Alpha Wave ◽  
Sports Activity ◽  
Eyes Closed ◽  
Visual Spatial ◽  
Task Conditions ◽  
The Brain

This article reports on the differences between the physiological response of the brain between athletes and non-athletes by using Quantitative Electroencephalography (QEEG). EEG waves were observed using qEEG and analysis were compared between the two groups.  This research involved 41 undergraduates of Universiti Malaysia Sarawak (UNIMAS). The qEEG recordings were made during the Eyes opened, Eyes Closed, and Stroop task conditions to find out the dominant wave during each of the conditions in different region of the brain. The results revealed higher EEG Delta and Beta1 at frontal region (Fp1, Fp2), somatosensory, (C3, P4) and visual spatial area (P3, P4). Delta, Beta and Gamma wave were dominant while the participants were performing the Stroop Task. Coupling of delta and beta oscillations might be due to the athletes’ anxiety during the Stroop task.  In Eyes Closed state, delta and alpha wave were dominant at the fronto-parietal attention network area. This study contributes to the development of training protocol for neurofeedback training for athletes in preparation for training of peak performance in any sports activity. It is recommended that extensive analysis should be done on the interaction of delta-gamma oscillations in different parts of the brain to find out its implication on attention and emotion during the cognitive process.  

scholarly journals Changes in the Electrical Activity of the Brain in the Alpha and Theta Bands during Prayer and Meditation

2020 ◽  
Vol 17 (24) ◽  
pp. 9567
Author(s):  
Paweł Dobrakowski ◽  
Michal Blaszkiewicz ◽  
Sebastian Skalski
Keyword(s):  
Neural Activity ◽  
Emotional Experience ◽  
Focused Attention ◽  
Eeg Signal ◽  
Alpha Wave ◽  
Spiritual Transcendence ◽  
Eyes Closed ◽  
Activity Integration ◽  
The Brain ◽  
Eeg Pattern

Focused attention meditation (FAM) is a category of meditation based on an EEG pattern, which helps the wandering mind to focus on a particular object. It seems that prayer may, in certain respects, be similar to FAM. It is believed that emotional experience correlates mainly with theta, but also with selective alpha, with internalized attention correlating mainly with the synchronous activity of theta and alpha. The vast majority of studies indicate a possible impact of transcendence in meditation on the alpha wave in EEG. No such reports are available for prayer. Seventeen women and nineteen men aged 27–64 years with at least five years of intensive meditation/prayer experience were recruited to participate in the study. We identified the two largest groups which remained in the meditation trend originating from the Buddhist system (14 people) (Buddhist meditators) and in the Christian-based faith (15 people) (Christian meditators). EEG signal was recorded with open eyes, closed eyes, during meditation/prayer, and relaxation. After the EEG recording, an examination was conducted using the Scale of Spiritual Transcendence. Buddhist meditators exhibited a statistically significantly higher theta amplitude at Cz during meditation compared to relaxation. Meanwhile, spiritual openness favored a higher theta amplitude at Pz during relaxation. Our study did not reveal statistically significant differences in frontal areas with regard to alpha and theta, which was often indicated in previous studies. It seems necessary to analyze more closely the midline activity in terms of dispersed neural activity integration.

scholarly journals Task dependence of neural representations of global scene properties but not scene categories in the prefrontal cortex

2020 ◽  
Author(s):  
Yaelan Jung ◽  
Dirk B. Walther
Keyword(s):  
Prefrontal Cortex ◽  
Visual Cortex ◽  
Scene Perception ◽  
Sound Level ◽  
Task Context ◽  
Complex Scene ◽  
Neural Representations ◽  
Task Conditions ◽  
Scene Content ◽  
The Brain

AbstractNatural scenes deliver rich sensory information about the world. Decades of research has shown that the scene-selective network in the visual cortex represents various aspects of scenes. It is, however, unknown how such complex scene information is processed beyond the visual cortex, such as in the prefrontal cortex. It is also unknown how task context impacts the process of scene perception, modulating which scene content is represented in the brain. In this study, we investigate these questions using scene images from four natural scene categories, which also depict two types of global scene properties, temperature (warm or cold), and sound-level (noisy or quiet). A group of healthy human subjects from both sexes participated in the present study using fMRI. In the study, participants viewed scene images under two different task conditions; temperature judgment and sound-level judgment. We analyzed how different scene attributes (scene categories, temperature, and sound-level information) are represented across the brain under these task conditions. Our findings show that global scene properties are only represented in the brain, especially in the prefrontal cortex, when they are task-relevant. However, scene categories are represented in the brain, in both the parahippocampal place area and the prefrontal cortex, regardless of task context. These findings suggest that the prefrontal cortex selectively represents scene content according to task demands, but this task selectivity depends on the types of scene content; task modulates neural representations of global scene properties but not of scene categories.

The role of different cues in the brain mechanism on visual spatial attention

2006 ◽  
Vol 16 (10) ◽  
pp. 1045-1050
Author(s):  
Song Weiqun ◽  
Lou Yuejia ◽  
Chi Song ◽  
Ji Xunming ◽  
Ling Feng ◽  
...  
Keyword(s):  
Spatial Attention ◽  
Visual Spatial Attention ◽  
Visual Spatial ◽  
Brain Mechanism ◽  
The Brain

Hippocampal-prefrontal theta coupling develops as mice become proficient in associative odorant discrimination learning

2021 ◽  
Author(s):  
Daniel Ramirez-Gordillo ◽  
Andrew A. Parra ◽  
K. Ulrich Bayer ◽  
Diego Restrepo
Keyword(s):  
Learning And Memory ◽  
Discrimination Learning ◽  
Gamma Oscillations ◽  
Oscillatory Activity ◽  
Dependent Protein Kinase ◽  
Dependent Protein ◽  
Theta Phase ◽  
Phase Amplitude ◽  
The Brain

Learning and memory requires coordinated activity between different regions of the brain. Here we studied the interaction between medial prefrontal cortex (mPFC) and hippocampal dorsal CA1 during associative odorant discrimination learning in the mouse. We found that as the animal learns to discriminate odorants in a go-no go task the coupling of high frequency neural oscillations to the phase of theta oscillations (phase-amplitude coupling or PAC) changes in a manner that results in divergence between rewarded and unrewarded odorant-elicited changes in the theta-phase referenced power (tPRP) for beta and gamma oscillations. In addition, in the proficient animal there was a decrease in the coordinated oscillatory activity between CA1 and mPFC in the presence of the unrewarded odorant. Furthermore, the changes in PAC resulted in a marked increase in the accuracy for decoding odorant identity from tPRP when the animal became proficient. Finally, we studied the role of Ca2+/calmodulin-dependent protein kinase II α (CaMKIIα), a protein involved in learning and memory, in oscillatory neural processing in this task. We find that the accuracy for decoding the odorant identity from tPRP decreases in CaMKIIα knockout mice and that this accuracy correlates with behavioral performance. These results implicate a role for PAC and CaMKIIα in olfactory go-no go associative learning in the hippocampal-prefrontal circuit.

Cognitive Analytics for Rapid Stress Relief in Humans Using EEG Based Analysis of Tratak Sadhana (Meditation)

2020 ◽  
Vol 10 (4) ◽  
pp. 1-20
Author(s):  
Swati Kamthekar ◽  
Prachi Deshpande ◽  
Brijesh Iyer
Keyword(s):  
Big Data ◽  
Fractal Dimensions ◽  
Approximate Entropy ◽  
Stress Relief ◽  
Eeg Signals ◽  
Nonlinear Parameters ◽  
Wavelet Entropy ◽  
Rest State ◽  
Eyes Closed ◽  
The Brain

The article reports the effect of Tratak Sadhana (meditation) on humans using electroencephalograph (EEG) signals. EEG represents the brain activities in the form of electrical signals. Due to non-stationary nature of the EEG signals, nonlinear parameters like approximate entropy, wavelet entropy and Higuchi' fractal dimensions are used to assess the variations in EEG rest as well as during Tratak Sadhana, i.e. at a rest state with eyes closed and during Tratak meditation. EEG signals are captured using EPOC Emotive EEG sensor. The sensor has 14 electrodes covering human scalp. Results shows that new practitioners can also achieve a rapid meditative state as compared to other meditation techniques. Further, the Big Data perspective of the present study is discussed. The present study shows that Tratak Sadhana meditation is an effective tool for rapid stress relief in humans.

scholarly journals Attentional Modulation of Visual Spatial Integration: Psychophysical Evidence Supported by Population Coding Modeling

2019 ◽  
Vol 31 (9) ◽  
pp. 1329-1342
Author(s):  
Alessandro Grillini ◽  
Remco J. Renken ◽  
Frans W. Cornelissen
Keyword(s):  
Selective Attention ◽  
Population Coding ◽  
Spatial Integration ◽  
Visual Spatial ◽  
Neural Populations ◽  
Feature Based ◽  
Flow Through ◽  
Opposing Effects ◽  
Neuronal Encoding ◽  
The Brain

Two prominent strategies that the human visual system uses to reduce incoming information are spatial integration and selective attention. Whereas spatial integration summarizes and combines information over the visual field, selective attention can single it out for scrutiny. The way in which these well-known mechanisms—with rather opposing effects—interact remains largely unknown. To address this, we had observers perform a gaze-contingent search task that nudged them to deploy either spatial or feature-based attention to maximize performance. We found that, depending on the type of attention employed, visual spatial integration strength changed either in a strong and localized or a more modest and global manner compared with a baseline condition. Population code modeling revealed that a single mechanism can account for both observations: Attention acts beyond the neuronal encoding stage to tune the spatial integration weights of neural populations. Our study shows how attention and integration interact to optimize the information flow through the brain.

scholarly journals The Neural Correlates of Time: A Meta-analysis of Neuroimaging Studies

2019 ◽  
Vol 31 (12) ◽  
pp. 1796-1826 ◽  
Author(s):  
Andrea Nani ◽  
Jordi Manuello ◽  
Donato Liloia ◽  
Sergio Duca ◽  
Tommaso Costa ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Analytical Investigation ◽  
Neural Systems ◽  
Subcortical Structures ◽  
Time Intervals ◽  
Sense Of Time ◽  
Task Conditions ◽  
Estimation Of Time ◽  
The Brain ◽  
Neuroimaging Techniques

During the last two decades, our inner sense of time has been repeatedly studied with the help of neuroimaging techniques. These investigations have suggested the specific involvement of different brain areas in temporal processing. At least two distinct neural systems are likely to play a role in measuring time: One is mainly constituted of subcortical structures and is supposed to be more related to the estimation of time intervals below the 1-sec range (subsecond timing tasks), and the other is mainly constituted of cortical areas and is supposed to be more related to the estimation of time intervals above the 1-sec range (suprasecond timing tasks). Tasks can then be performed in motor or nonmotor (perceptual) conditions, thus providing four different categories of time processing. Our meta-analytical investigation partly confirms the findings of previous meta-analytical works. Both sub- and suprasecond tasks recruit cortical and subcortical areas, but subcortical areas are more intensely activated in subsecond tasks than in suprasecond tasks, which instead receive more contributions from cortical activations. All the conditions, however, show strong activations in the SMA, whose rostral and caudal parts have an important role not only in the discrimination of different time intervals but also in relation to the nature of the task conditions. This area, along with the striatum (especially the putamen) and the claustrum, is supposed to be an essential node in the different networks engaged when the brain creates our sense of time.

Hippocampus Retains the Periodicity of Gamma Stimulation In Vivo

2002 ◽  
Vol 88 (5) ◽  
pp. 2349-2354 ◽  
Author(s):  
J. E. Mikkonen ◽  
T. Grönfors ◽  
J. J. Chrobak ◽  
M. Penttonen
Keyword(s):  
Information Acquisition ◽  
Pyramidal Cells ◽  
Gamma Oscillations ◽  
Short Term ◽  
Ca1 Pyramidal Cells ◽  
State Dependent ◽  
Hippocampal Ca1 ◽  
Oscillatory Rhythms ◽  
The Brain

Several behavioral state dependent oscillatory rhythms have been identified in the brain. Of these neuronal rhythms, gamma (20–70 Hz) oscillations are prominent in the activated brain and are associated with various behavioral functions ranging from sensory binding to memory. Hippocampal gamma oscillations represent a widely studied band of frequencies co-occurring with information acquisition. However, induction of specific gamma frequencies within the hippocampal neuronal network has not been satisfactorily established. Using both in vivo intracellular and extracellular recordings from anesthetized rats, we show that hippocampal CA1 pyramidal cells can discharge at frequencies determined by the preceding gamma stimulation, provided that the gamma is introduced in theta cycles, as occurs in vivo. The dynamic short-term alterations in the oscillatory discharge described in this paper may serve as a coding mechanism in cortical neuronal networks.

Differential facilitative effects of glucose administration on Stroop task conditions.

2013 ◽  
Vol 127 (6) ◽  
pp. 932-935 ◽  
Author(s):  
Karen R. Brandt ◽  
E. Leigh Gibson ◽  
James M. Rackie
Keyword(s):  
Stroop Task ◽  
Glucose Administration ◽  
Task Conditions

EEG Based BCI Using Visual Imagery Task for Robot Control

2013 ◽  
Vol 61 (2) ◽  
Author(s):  
Husnaini Azmy ◽  
Norlaili Mat Safri
Keyword(s):  
Spectral Power ◽  
Normal Subjects ◽  
Imagery Task ◽  
Non Invasive ◽  
Cortex Area ◽  
Wireless Robot ◽  
Scalp Location ◽  
Task Conditions ◽  
Electroencephalogram Eeg ◽  
The Brain

The aim of this study is to detect the brain activation on scalp by Electroencephalogram (EEG) task–based for brain computer interface (BCI) using wirelessly control robot. EEG was measured in 8 normal subjects for control and task conditions. The objective is to determine one scalp location which will give signals that can be used to control the wireless robot using BCI and EEG, using non invasive and without subject training. In control condition subjects were ask to relax but in task condition, subjects were asked to imagine a star rotating clockwise at position 45 degrees direction pointed by the wireless robot where at this angle the target is located. At position 0 and 90 degree angle subjects were asked to relax since there is no target on that direction. Using EEG spectral power analysis and normalization, the optimum location for this task has been detected at position F8 which is in frontal cortex area and the rhythm happened at alpha frequency band. At this position, the signals from the brain should be able to drive the robot to the required direction by giving correct and accurate signals to robot moving towards target.

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