Search results for: right brain training
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4758

Search results for: right brain training

4698 Classification of EEG Signals Based on Dynamic Connectivity Analysis

Authors: Zoran Šverko, Saša Vlahinić, Nino Stojković, Ivan Markovinović

Abstract:

In this article, the classification of target letters is performed using data from the EEG P300 Speller paradigm. Neural networks trained with the results of dynamic connectivity analysis between different brain regions are used for classification. Dynamic connectivity analysis is based on the adaptive window size and the imaginary part of the complex Pearson correlation coefficient. Brain dynamics are analysed using the relative intersection of confidence intervals for the imaginary component of the complex Pearson correlation coefficient method (RICI-imCPCC). The RICI-imCPCC method overcomes the shortcomings of currently used dynamical connectivity analysis methods, such as the low reliability and low temporal precision for short connectivity intervals encountered in constant sliding window analysis with wide window size and the high susceptibility to noise encountered in constant sliding window analysis with narrow window size. This method overcomes these shortcomings by dynamically adjusting the window size using the RICI rule. This method extracts information about brain connections for each time sample. Seventy percent of the extracted brain connectivity information is used for training and thirty percent for validation. Classification of the target word is also done and based on the same analysis method. As far as we know, through this research, we have shown for the first time that dynamic connectivity can be used as a parameter for classifying EEG signals.

Keywords: dynamic connectivity analysis, EEG, neural networks, Pearson correlation coefficients

Procedia PDF Downloads 170
4697 The Non-Linear Analysis of Brain Response to Visual Stimuli

Authors: H. Namazi, H. T. N. Kuan

Abstract:

Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes.

Keywords: visual stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

Procedia PDF Downloads 525
4696 Dynamic Behavior of Brain Tissue under Transient Loading

Authors: Y. J. Zhou, G. Lu

Abstract:

In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.

Keywords: analytical method, mechanical responses, spherical wave propagation, traumatic brain injury

Procedia PDF Downloads 238
4695 The Intervention Effect of Gratitude Skills Training on the Reduction of Loneliness

Authors: T. Sakai, A. Aikawa

Abstract:

This study defined 'gratitude skills training' as a social skills training which would become a new intervention method about gratitude intervention. The purpose of this study was to confirm the intervention effect of gratitude skills training on the reduction of loneliness. The participants in this study were university students (n = 36). A waiting list control design was used, in which the participants were assigned either to a training group (n = 18) or a waiting list control group (n = 18); the latter group took the same training after the first group had been trained. The two-week gratitude skills training comprised of three sessions (50 minutes per each of sessions). In the three sessions, the guidebook and the homework developed in this study were used. Results showed that gratitude skills training improved the participants’ gratitude skills. The results also indicated the intervention effect of gratitude skills training on the reduction of loneliness during the follow-up after three weeks. This study suggests that gratitude skills training can reduce loneliness. The gratitude skills training has a possibility of becoming a new treatment to reduce loneliness.

Keywords: gratitude skills, loneliness, social skills training, well-being

Procedia PDF Downloads 158
4694 Melatonin Suppresses the Brain Injury after Cerebral Ischemia/Reperfusion in Hyperglycemic Rats

Authors: Dalia O. Saleha, Gehad A. Abdel Jaleela, Sally W. Al-Awdana

Abstract:

Diabetes mellitus (DM) is known to exacerbate cerebral ischemic injury. The present study aimed to investigate the anti-oxidant and anti-inflammatory effects of oral supplementation of melatonin (MLN) on cerebral injury caused by middle cerebral artery occlusion and reperfusion (MCAO/Re) in streptozotocin (STZ)-induced hyperglycemic rats. Hyperglycemia was induced by a single injection of STZ (55mg/kg; i.p.), six weeks later the cerebral injury was induced by MCAO/Re. Twenty-four hours after the MCAO/Re the MLN (10 mg/kg) was injected for 14 consecutive days. Results of the present study revealed that MCAO/Re in STZ-induced hyperglycemia in rats causes an increase in the oxidative stress biomarkers; it increased brain lipid peroxidation (measured as malondialdehyde; MDA) and brain level of nitric oxide (NO). Moreover, MCAO/Reproduces a prominent increase in the brain inflammatory markers viz. interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis nuclear factor-alpha (TNF-α). Oral treatment of MCAO/Re in STZ-induced hyperglycemic rats with MLN (10 mg/kg) for two weeks restored the brain levels of MDA, GSH, NO, IL-6, IL-1β and the TNF-α. MLN succeeded to suppress the exacerbation of damage in the brain of hyperglycemic rats. These results suggest that daily intake of MLN attenuates the exacerbation of cerebral ischemic injury in a diabetic state, which may be attributed to anti-oxidant and anti-inflammatory effects in the brain.

Keywords: melatonin, brain injury, cerebral ischemia/reperfusion, hyperglycemia, rats

Procedia PDF Downloads 125
4693 Employers' Occupational Health and Safety Training Obligations in Framework Directive and Training Procedure and Rules in Turkey

Authors: Nuray Gökçek Karaca, Berrin Gökçek

Abstract:

Employers occupational safety and health training obligations are regulated in 89/391/EEC Framework Directive and also in 6331 numbered Occupational Health and Safety Law in Turkey. The main objective of this research is to determine and evaluate the employers’ occupational health and safety training obligations in Framework Directive in comparison with the 6331 numbered Occupational Health and Safety Law and to examine training principles in Turkey. For this purpose, employers’ occupational health and safety training obligations examined in Framework Directive and Occupational Health and Safety Law. This study carried out through comparative scanning model and literature model. The research data were collected through European Agency and ministry legislations. As a result, employers’ occupational health and safety training obligations in the 6331 numbered Occupational Health and Safety Law are compatible with the 89/391/EEC numbered Framework Directive and training principles are determined by in different ways like the trained workers, training issues, training period, training time, and trainers. In this study, employers’ training obligations are evaluated in detail.

Keywords: directive, occupational health and safety, training, work accidences

Procedia PDF Downloads 309
4692 Characterization of 3D-MRP for Analyzing of Brain Balancing Index (BBI) Pattern

Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analysed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).

Keywords: power spectral density, 3D EEG model, brain balancing, mean relative power, different mean relative power

Procedia PDF Downloads 446
4691 The Analysis of Brain Response to Auditory Stimuli through EEG Signals’ Non-Linear Analysis

Authors: H. Namazi, H. T. N. Kuan

Abstract:

Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to auditory stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to auditory stimuli but provide us with very good recommendations for clinical purposes.

Keywords: auditory stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure

Procedia PDF Downloads 511
4690 Comparing the Detection of Autism Spectrum Disorder within Males and Females Using Machine Learning Techniques

Authors: Joseph Wolff, Jeffrey Eilbott

Abstract:

Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

Procedia PDF Downloads 181
4689 Brain-Computer Interface System for Lower Extremity Rehabilitation of Chronic Stroke Patients

Authors: Marc Sebastián-Romagosa, Woosang Cho, Rupert Ortner, Christy Li, Christoph Guger

Abstract:

Neurorehabilitation based on Brain-Computer Interfaces (BCIs) shows important rehabilitation effects for patients after stroke. Previous studies have shown improvements for patients that are in a chronic stage and/or have severe hemiparesis and are particularly challenging for conventional rehabilitation techniques. For this publication, seven stroke patients in the chronic phase with hemiparesis in the lower extremity were recruited. All of them participated in 25 BCI sessions about 3 times a week. The BCI system was based on the Motor Imagery (MI) of the paretic ankle dorsiflexion and healthy wrist dorsiflexion with Functional Electrical Stimulation (FES) and avatar feedback. Assessments were conducted to assess the changes in motor improvement before, after and during the rehabilitation training. Our primary measures used for the assessment were the 10-meters walking test (10MWT), Range of Motion (ROM) of the ankle dorsiflexion and Timed Up and Go (TUG). Results show a significant increase in the gait speed in the primary measure 10MWT fast velocity of 0.18 m/s IQR = [0.12 to 0.2], P = 0.016. The speed in the TUG was also significantly increased by 0.1 m/s IQR = [0.09 to 0.11], P = 0.031. The active ROM assessment increased 4.65º, and IQR = [ 1.67 - 7.4], after rehabilitation training, P = 0.029. These functional improvements persisted at least one month after the end of the therapy. These outcomes show the feasibility of this BCI approach for chronic stroke patients and further support the growing consensus that these types of tools might develop into a new paradigm for rehabilitation tools for stroke patients. However, the results are from only seven chronic stroke patients, so the authors believe that this approach should be further validated in broader randomized controlled studies involving more patients. MI and FES-based non-invasive BCIs are showing improvement in the gait rehabilitation of patients in the chronic stage after stroke. This could have an impact on the rehabilitation techniques used for these patients, especially when they are severely impaired and their mobility is limited.

Keywords: neuroscience, brain computer interfaces, rehabilitat, stroke

Procedia PDF Downloads 70
4688 Exposure to Radio Frequency Waves of Mobile Phone and Temperature Changes of Brain Tissue

Authors: Farhad Forouharmajd, Hossein Ebrahimi, Siamak Pourabdian

Abstract:

Introduction: Prevalent use of cell phones (mobile phones) has led to increasing worries about the effect of radiofrequency waves on the physiology of human body. This study was done to determine different reactions of the temperatures in different depths of brain tissue in confronting with radiofrequency waves of cell phones. Methodology: This study was an empirical research. A cow's brain tissue was placed in a compartment and the effects of radiofrequency waves of the cell phone was analyzed during confrontation and after confrontation, in three different depths of 2, 12, and 22 mm of the tissue, in 4 mm and 4 cm distances of the tissue to a cell phone, for 15 min. Lutron thermometer was used to measure the tissue temperatures. Data analysis was done by Lutron software. Findings: The rate of increasing the temperature at the depth of 22 mm was higher than 2 mm and 12mm depths, during confrontation of the brain tissue at the distance of 4 mm with the cell phone, such that the tissue temperatures at 2, 12, and 22 mm depths increased by 0.29 ˚C, 0.31 ˚C, and 0.37 ˚C, respectively, relative to the base temperature (tissue temperature before confrontation). Moreover, the temperature of brain tissue at the distance of 4 cm by increasing the tissue depth was more than other depths. Increasing the tissue temperature also existed by increasing the brain tissue depth after the confrontation with the cell phone. The temperature of the 22 mm depth increased with higher speed at the time confrontation. Conclusion: Not only radiofrequency waves of cell phones increased the tissue temperature in all the depths of the brain tissue, but also the temperature due to radiofrequency waves of the cell phone was more at the depths higher than 22 mm of the tissue. In fact, the thermal effect of radiofrequency waves was higher in higher depths.

Keywords: mobile phone, radio frequency waves, brain tissue, temperature

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4687 LGG Architecture for Brain Tumor Segmentation Using Convolutional Neural Network

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

Abstract:

The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

Procedia PDF Downloads 156
4686 Smart Brain Wave Sensor for Paralyzed- a Real Time Implementation

Authors: U.B Mahadevswamy UBM, Siraj Ahmed Siraj

Abstract:

As the title of the paper indicates about brainwaves and its uses for various applications based on their frequencies and different parameters which can be implemented as real time application with the title a smart brain wave sensor system for paralyzed patients. Brain wave sensing is to detect a person's mental status. The purpose of brain wave sensing is to give exact treatment to paralyzed patients. The data or signal is obtained from the brainwaves sensing band. This data are converted as object files using Visual Basics. The processed data is further sent to Arduino which has the human's behavioral aspects like emotions, sensations, feelings, and desires. The proposed device can sense human brainwaves and detect the percentage of paralysis that the person is suffering. The advantage of this paper is to give a real-time smart sensor device for paralyzed patients with paralysis percentage for their exact treatment. Keywords:-Brainwave sensor, BMI, Brain scan, EEG, MCH.

Keywords: Keywords:-Brainwave sensor , BMI, Brain scan, EEG, MCH

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4685 Brain Computer Interface Implementation for Affective Computing Sensing: Classifiers Comparison

Authors: Ramón Aparicio-García, Gustavo Juárez Gracia, Jesús Álvarez Cedillo

Abstract:

A research line of the computer science that involve the study of the Human-Computer Interaction (HCI), which search to recognize and interpret the user intent by the storage and the subsequent analysis of the electrical signals of the brain, for using them in the control of electronic devices. On the other hand, the affective computing research applies the human emotions in the HCI process helping to reduce the user frustration. This paper shows the results obtained during the hardware and software development of a Brain Computer Interface (BCI) capable of recognizing the human emotions through the association of the brain electrical activity patterns. The hardware involves the sensing stage and analogical-digital conversion. The interface software involves algorithms for pre-processing of the signal in time and frequency analysis and the classification of patterns associated with the electrical brain activity. The methods used for the analysis and classification of the signal have been tested separately, by using a database that is accessible to the public, besides to a comparison among classifiers in order to know the best performing.

Keywords: affective computing, interface, brain, intelligent interaction

Procedia PDF Downloads 357
4684 Network Analysis and Sex Prediction based on a full Human Brain Connectome

Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

Abstract:

we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

Procedia PDF Downloads 114
4683 Gut-Microbiota-Brain-Axis, Leaky Gut, Leaky Brain: Pathophysiology of Second Brain Aging and Alzheimer’s Disease- A Neuroscientific Riddle

Authors: Bilal Ahmad

Abstract:

Alzheimer’s disease (AD) is one of the most common neurodegenerative illnesses. However, how Gut-microbiota plays a role in the pathogenesis of AD is not well elucidated. The purpose of this literature review is to summarize and understand the current findings that may elucidate the gut microbiota's role in the development of AD. Methods: A literature review of all the relevant papers known to the author was conducted. Relevant articles, abstracts and research papers were collected from well-accepted web sources like PubMed, PMC, and Google Scholar. Results: Recent studies have shown that Gut-microbiota has an important role in the progression of AD via Gut-Microbiota-Brain Axis. The onset of AD supports the ‘Hygiene Hypothesis’, which shows that AD might begin in the Gut, causing dysbiosis, which interferes with the intestinal barrier by releasing pro-inflammatory cytokines and making its way up to the brain via the blood-brain barrier (BBB). Molecular mechanisms lipopolysaccharides and serotonin kynurenine (tryptophan) pathways have a direct association with inflammation, the immune system, neurodegeneration, and AD. Conclusion: The studies helped to analyze the molecular basis of AD, other neurological conditions like depression, autism, and Parkinson's disease and how they are linked to Gut-microbiota. Further, studies to explore the therapeutic effects of probiotics in AD and cognitive enhancement should be warranted to provide significant clinical and practical value.

Keywords: gut-microbiota, Alzheimer’s disease, second brain aging, lipopolysaccharides, short-chain fatty acids

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4682 Antioxidant Effects of C-Phycocyanin on Oxidized Astrocyte in Brain Injury Using 2D and 3D Neural Nanofiber Tissue Model

Authors: Seung Ju Yeon, Seul Ki Min, Jun Sang Park, Yeo Seon Kwon, Hoo Cheol Lee, Hyun Jung Shim, Il-Doo Kim, Ja Kyeong Lee, Hwa Sung Shin

Abstract:

In brain injury, depleting oxidative stress is the most effective way to reduce the brain infarct size. C-phycocyanin (C-Pc) is a well-known antioxidant protein that has neuroprotective effects obtained from green microalgae. Astrocyte is glial cell that supports the nerve cell such as neuron, which account for a large portion of the brain. In brain injury, such as ischemia and reperfusion, astrocyte has an important rule that overcomes the oxidative stress and protect from brain reactive oxygen species (ROS) injury. However little is known about how C-Pc regulates the anti-oxidants effects of astrocyte. In this study, when the C-Pc was treated in oxidized astrocyte, we confirmed that inflammatory factors Interleukin-6 and Interleukin-3 were increased and antioxidants enzyme, Superoxide dismutase (SOD) and catalase was upregulated, and neurotrophic factors, brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) was alleviated. Also, it was confirmed to reduce infarct size of the brain in ischemia and reperfusion because C-Pc has anti-oxidant effects in middle cerebral artery occlusion (MCAO) animal model. These results show that C-Pc can help astrocytes lead neuroprotective activities in the oxidative stressed environment of the brain. In summary, the C-PC protects astrocytes from oxidative stress and has anti-oxidative, anti-inflammatory, neurotrophic effects under ischemic situations.

Keywords: c-phycocyanin, astrocyte, reactive oxygen species, ischemia and reperfusion, neuroprotective effect

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4681 Effect of Training and Development on Employee Performance in the Banking Industry: A Case Study of Some Selected Banks within Bauchi Metropolis

Authors: Sagir Abubakar

Abstract:

Organization must move along with the employees, because organization should adapt itself to the changing environment. The paper examines the effect of training and development on employee performance. Training and development has an important role in improve the performance, skills and attitude of employee in an organization. Training and development will also help an employee to do his present job or to prepare him for a higher position with increased responsibilities. The paper analyses the employee performance towards training and development conducted in some selected banks within Bauchi metropolis. Review of related literature was done on, training, training objectives, methods and development and its method. A census survey was carried out using staff of GTB and Skye Banks Bauchi branch where a total of 40 questionnaires were administered personally by the researcher and there were 100% responses. Correlation analysis was adopted for the analysis of data collected. The study concludes that 95% of respondents agreed that training and development are vital for both employee and organizations performance. They also suggest that training and development should be made compulsory for all categories of employee in an organization. Training and Development programmes are necessary in any organization for improving the quality of work of the employee.

Keywords: training, development, employee, performance, banks

Procedia PDF Downloads 430
4680 Memory Types in Hemodialysis (HD) Patients; A Study Based on Hemodialysis Duration, Zahedan: South East of Iran

Authors: Behnoush Sabayan, Ali Alidadi, Saeid Ebarhimi, N. M. Bakhshani

Abstract:

Hemodialysis (HD) patients are at a high risk of atherosclerotic and vascular disease; also little information is available for the HD impact on brain structure of these patients. We studied the brain abnormalities in HD patients. The aim of this study was to investigate the effect of long term HD on brain structure of HD patients. Non-contrast MRI was used to evaluate imaging findings. Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% were female. According to study, HD patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had small vessel ischemia than the HD patients who underwent HD for a shorter term, which the median time was 3 to 5 months. Most of the small vessel ischemia was located in pre-ventricular, subcortical and white matter (1.33± .471, 1.23± .420 and 1.39±.490). However, the other brain damages like: central pons abnormality, global brain atrophy, thinning of corpus callosum and frontal lobe atrophy were found (P<0.01). The present study demonstrated that HD patients who were under HD for a longer time had small vessel ischemia and we conclude that this small vessel ischemia might be a causative mechanism of brain atrophy in chronic hemodialysis patients. However, additional researches are needed in this area.

Keywords: Hemodialysis Patients, Duration of Hemodialysis, MRI, Zahedan

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4679 Market-Driven Process of Brain Circulation in Knowledge Services Industry in Sri Lanka

Authors: Panagodage Janaka Sampath Fernando

Abstract:

Brain circulation has become a buzzword in the skilled migration literature. However, promoting brain circulation; returning of skilled migrants is challenging. Success stories in Asia, for instances, Taiwan, and China, are results of rigorous policy interventions of the respective governments. Nonetheless, the same policy mix has failed in other countries making it skeptical to attribute the success of brain circulation to the policy interventions per se. The paper seeks to answer whether the success of brain circulation within the Knowledge Services Industry (KSI) in Sri Lanka is a policy driven or a market driven process. Mixed method approach, which is a combination of case study and survey methods, was employed. Qualitative data derived from ten case studies of returned entrepreneurs whereas quantitative data generated from a self-administered survey of 205 returned skilled migrants (returned skilled employees and entrepreneurs) within KSI. The pull factors have driven the current flow of brain circulation within KSI but to a lesser extent, push factors also have influenced. The founding stone of the industry has been laid by a group of returned entrepreneurs, and the subsequent growth of the industry has attracted returning skilled employees. Sri Lankan government has not actively implemented the reverse brain drain model, however, has played a passive role by creating a peaceful and healthy environment for the industry. Therefore, in contrast to the other stories, brain circulation within KSI has emerged as a market driven process with minimal government interventions. Entrepreneurs play the main role in a market-driven process of brain circulation, and it is free from the inherent limitations of the reverse brain drain model such as discriminating non-migrants and generating a sudden flow of low-skilled migrants. Thus, to experience a successful brain circulation, developing countries should promote returned entrepreneurs by creating opportunities in knowledge-based industries.

Keywords: brain circulation, knowledge services industry, return migration, Sri Lanka

Procedia PDF Downloads 248
4678 Examining Electroencephalographic Activity Differences Between Goalkeepers and Forwards in Professional Football Players

Authors: Ruhollah Basatnia, Ali Reza Aghababa, Mehrdad Anbarian, Sara Akbari, Mohammad Khazaee

Abstract:

Introduction: The investigation of brain activity in sports has become a subject of interest for researchers. Several studies have examined the patterns or differences in brain activity during different sports situations. Previous studies have suggested that the pattern of cortical activity may differ between different football positions, such as goalkeepers and other players. This study aims to investigate the differences in electroencephalographic (EEG) activity between the positions of goalkeeper and forward in professional football players. Methods: Fourteen goalkeepers and twelve forwards, all males between 19-28 years old, participated in the study. EEG activity was recorded while participants were sitting with their eyes closed for 5 minutes. The mean relative power of EEG activity for each frequency band was compared between the two groups using independent samples t-test. Findings: The study found significant differences in the relative power of EEG activity between different frequency bands and electrodes. Notably, significant differences were observed in the mean relative power of EEG activity between the two groups for certain frequency bands and electrodes. These findings suggest that EEG activity can serve as a sensory indicator for cognitive and performance differences between goalkeepers and forwards in football players. Discussion: The results of this study suggest that EEG activity can be used to identify cognitive and performance differences between goalkeepers and forwards in football players. However, further research is needed to establish the relationship between EEG activity and actual performance in the field. Future studies should investigate the potential influence of other factors, such as fatigue and stress, on the EEG activity of football players. Additionally, the use of real-time EEG feedback could be explored as a tool for training and performance optimization in football players. Further research is required to fully understand the potential of EEG activity as a sensory indicator for cognitive and performance differences between football player positions and to explore its potential applications for training and performance optimization in football and other sports.

Keywords: football, brain activity, EEG, goalkeepers, forwards

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4677 Utility of Executive Function Training in Typically Developing Adolescents and Special Populations: A Systematic Review of the Literature

Authors: Emily C. Shepard, Caroline Sweeney, Jessica Grimm, Sophie Jacobs, Lauren Thompson, Lisa L. Weyandt

Abstract:

Adolescence is a critical phase of development in which individuals are prone to more risky behavior while also facing potentially life-changing decisions. The balance of increased behavioral risk and responsibility indicates the importance of executive functioning ability. In recent years, executive function training has emerged as a technique to enhance this cognitive ability. The aim of the present systematic review was to discuss the reported efficacy of executive functioning training techniques among adolescents. After reviewing 3110 articles, a total of 24 articles were identified which examined the role of executive functioning training techniques among adolescents (age 10-19). Articles retrieved demonstrated points of comparison across psychiatric and medical diagnosis, location of training, and stage of adolescence. Typically developing samples, as well as those with attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), conduct disorder, and physical health concerns were found, allowing for the comparison of the efficacy of techniques considering physical and psychological heterogeneity. Among typically developing adolescents, executive functioning training yielded nonsignificant or low effect size improvements in executive functioning, and in some cases executive functioning ability was decreased following the training. In special populations, including those with ADHD, (ASD), conduct disorder, and physical health concerns significant differences and larger effect sizes in executive functioning were seen following treatment, particularly among individuals with ADHD. Future research is needed to identify the long-term efficacy of these treatments, as well as their generalizability to real-world conditions.

Keywords: adolescence, attention-deficit hyperactivity disorder, executive function, executive function training, traumatic brain injury

Procedia PDF Downloads 159
4676 Base Deficit Profiling in Patients with Isolated Blunt Traumatic Brain Injury – Correlation with Severity and Outcomes

Authors: Shahan Waheed, Muhammad Waqas, Asher Feroz

Abstract:

Objectives: To determine the utility of base deficit in traumatic brain injury in assessing the severity and to correlate with the conventional computed tomography scales in grading the severity of head injury. Methodology: Observational cross-sectional study conducted in a tertiary care facility from 1st January 2010 to 31st December 2012. All patients with isolated traumatic brain injury presenting within 24 hours of the injury to the emergency department were included in the study. Initial Glasgow Coma Scale and base deficit values were taken at presentation, the patients were followed during their hospital stay and CT scan brain findings were recorded and graded as per the Rotterdam scale, the findings were cross-checked by a radiologist, Glasgow Outcome Scale was taken on last follow up. Outcomes were dichotomized into favorable and unfavorable outcomes. Continuous variables with normal and non-normal distributions are reported as mean ± SD. Categorical variables are presented as frequencies and percentages. Relationship of the base deficit with GCS, GOS, CT scan brain and length of stay was calculated using Spearman`s correlation. Results: 154 patients were enrolled in the study. Mean age of the patients were 30 years and 137 were males. The severity of brain injuries as per the GCS was 34 moderate and 109 severe respectively. 34 percent of the total has an unfavorable outcome with a mean of 18±14. The correlation was significant at the 0.01 level with GCS on presentation and the base deficit 0.004. The correlation was not significant between the Rotterdam CT scan brain findings, length of stay and the base deficit. Conclusion: The base deficit was found to be a good predictor of severity of brain injury. There was no association of the severity of injuries on the CT scan brain as per the Rotterdam scale and the base deficit. Further studies with large sample size are needed to further evaluate the associations.

Keywords: base deficit, traumatic brain injury, Rotterdam, GCS

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4675 A Review of Brain Implant Device: Current Developments and Applications

Authors: Ardiansyah I. Ryan, Ashsholih K. R., Fathurrohman G. R., Kurniadi M. R., Huda P. A

Abstract:

The burden of brain-related disease is very high. There are a lot of brain-related diseases with limited treatment result and thus raise the burden more. The Parkinson Disease (PD), Mental Health Problem, or Paralysis of extremities treatments had risen concern, as the patients for those diseases usually had a low quality of life and low chance to recover fully. There are also many other brain or related neural diseases with the similar condition, mainly the treatments for those conditions are still limited as our understanding of the brain function is insufficient. Brain Implant Technology had given hope to help in treating this condition. In this paper, we examine the current update of the brain implant technology. Neurotechnology is growing very rapidly worldwide. The United States Food and Drug Administration (FDA) has approved the use of Deep Brain Stimulation (DBS) as a brain implant in humans. As for neural implant both the cochlear implant and retinal implant are approved by FDA too. All of them had shown a promising result. DBS worked by stimulating a specific region in the brain with electricity. This device is planted surgically into a very specific region of the brain. This device consists of 3 main parts: Lead (thin wire inserted into the brain), neurostimulator (pacemaker-like device, planted surgically in the chest) and an external controller (to turn on/off the device by patient/programmer). FDA had approved DBS for the treatment of PD, Pain Management, Epilepsy and Obsessive Compulsive Disorder (OCD). The target treatment of DBS in PD is to reduce the tremor and dystonia symptoms. DBS has been showing the promising result in animal and limited human trial for other conditions such as Alzheimer, Mental Health Problem (Major Depression, Tourette Syndrome), etc. Every surgery has risks of complications, although in DBS the chance is very low. DBS itself had a very satisfying result as long as the subject criteria to be implanted this device based on indication and strictly selection. Other than DBS, there are several brain implant devices that still under development. It was included (not limited to) implant to treat paralysis (In Spinal Cord Injury/Amyotrophic Lateral Sclerosis), enhance brain memory, reduce obesity, treat mental health problem and treat epilepsy. The potential of neurotechnology is unlimited. When brain function and brain implant were fully developed, it may be one of the major breakthroughs in human history like when human find ‘fire’ for the first time. Support from every sector for further research is very needed to develop and unveil the true potential of this technology.

Keywords: brain implant, deep brain stimulation (DBS), deep brain stimulation, Parkinson

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4674 Comparison of Stereotactic Craniotomy for Brain Metastasis, as Compared to Stereotactic Radiosurgery

Authors: Mostafa El Khashab

Abstract:

Our experience with 50 patients with metastatic tumors located in different locations of the brain by a stereotactic-guided craniotomy and total microsurgical resection. Patients ranged in age from 36 to 73 years. There were 28 women and 22 men. Thirty-four patients presented with hemiparesis and 6 with aphasia and the remaining presented with psychological manifestations and memory issues. Gross total resection was accomplished in all cases, with postoperative imaging confirmation of complete removal. Forty patients were subjected to whole brain irradiation. One patient developed a stroke postoperatively and another one had a flap infection. 4 patients developed different postoperative but unrelated morbidities, including pneumonia and DVT. No mortality was encountered. We believe that with the assistance of stereotactic localization, metastases in vital regions of the brain can be removed with very low neurologic morbidity and that, in comparison to other modalities, they fare better regarding their long-term outcome.

Keywords: stereotactic, craniotomy, radiosurgery, patient

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4673 Reconstruction of Visual Stimuli Using Stable Diffusion with Text Conditioning

Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

Abstract:

The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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4672 A Study of the Views of Information Technologies Teachers regarding In-Service Training

Authors: Halit Arslan, Ismail Sahin, Ahmet Oguz Akturk, Ismail Celik

Abstract:

Today, the means of following the developments in the area of science and technology is to keep up with the pace of the advancements in this area. As is in every profession, apart from their personal efforts, the training of teachers in the period after they start their careers is only possible through in-service training. The aim of the present study is to determine the views of Information Technologies (IT) teachers regarding the in-service training courses organized by the Ministry of National Education. In this study, in which quantitative research methods and techniques were employed, the views of 196 IT teachers were collected by using the “Views on In-service Training” questionnaire developed by the authors of the paper. Independent groups t-test was used to determine whether the views of IT teachers regarding in-service training differed depending on gender, age and professional seniority. One-way analysis of variance (ANOVA) was used to investigate whether the views of IT teachers regarding in-service training differed depending on the number of in-service training courses they joined and the type of in-service training course they wanted to take. According to the findings obtained in the study, the views of IT teachers on in-service training did not show a significant difference depending on gender and age, whereas those views differed depending on professional seniority, the number of in-service training courses they joined and the type of in-service training course they wanted to take.

Keywords: in-service training, IT teachers, professional development, personal development

Procedia PDF Downloads 381
4671 EEG Neurofeedback Training – Healing the Wounded Brain

Authors: Jamuna Rajeswaran

Abstract:

In the past two decades, with a population of more than a billion. India is passing through a major socio-demographic and epidemiological transition with consequent changes in health scenario. TBI constitute significant burden on health care resources in India The impact on a person and family can be devastating. Patients with TBI experience persistent cognitive deficits, emotional changes, which contribute to the disruption of life activities. The recovery of TBI would be maximized by appropriate rehabilitation. Neurofeedback is an emerging neuroscience-based clinical application. Sixty patients were recruited for this study after obtaining informed consent. Rivermead Head Injury Follow-up Questionnaire, Rivermead Post Concussion Symptoms Questionnaire and Visual Analog Scale were used to assess the behavioral and symptomotolgy associated with post TBI. Neuropsychological assessment was carried out using NIMHANS neuropsychological battery 2004. The Intervention group received neurofeedback training and the waitlist group did not receive any treatment during this phase. Patients were allocated to intervention and waitlist group at random. There were 30 patients in each group. Patients were given 20 sessions of NFT Patients were trained on the O1 and O2 channels for alpha theta training. Each session was of 40 minutes duration with 5-6 sessions per week. The post-training assessment was carried out for the intervention group after 20 sessions of NFT. The waitlist group underwent assessment after one month. Results showed neurofeedback training is effective in ameliorating deficits in cognitive functions and quality of life in patients with TBI. Improvements were corroborated by the clinical interview with patients and significant others post NFT.

Keywords: assessment, rehabilitation, cognition, EEG neurofeedback

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4670 Interbrain Synchronization and Multilayer Hyper brain Networks when Playing Guitar in Quartet

Authors: Viktor Müller, Ulman Lindenberger

Abstract:

Neurophysiological evidence suggests that the physiological states of the system are characterized by specific network structures and network topology dynamics, demonstrating a robust interplay between network topology and function. It is also evident that interpersonal action coordination or social interaction (e.g., playing music in duets or groups) requires strong intra- and interbrain synchronization resulting in a specific hyper brain network activity across two or more brains to support such coordination or interaction. Such complex hyper brain networks can be described as multiplex or multilayer networks that have a specific multidimensional or multilayer network organization characteristic for superordinate systems and their constituents. The aim of the study was to describe multilayer hyper brain networks and synchronization patterns of guitarists playing guitar in a quartet by using electroencephalography (EEG) hyper scanning (simultaneous EEG recording from multiple brains) and following time-frequency decomposition and multilayer network construction, where within-frequency coupling (WFC) represents communication within different layers, and cross-frequency coupling (CFC) depicts communication between these layers. Results indicate that communication or coupling dynamics, both within and between the layers across the brains of the guitarists, play an essential role in action coordination and are particularly enhanced during periods of high demands on musical coordination. Moreover, multilayer hyper brain network topology and dynamical structure of guitar sounds showed specific guitar-guitar, brain-brain, and guitar-brain causal associations, indicating multilevel dynamics with upward and downward causation, contributing to the superordinate system dynamics and hyper brain functioning. It is concluded that the neuronal dynamics during interpersonal interaction are brain-wide and frequency-specific with the fine-tuned balance between WFC and CFC and can best be described in terms of multilayer multi-brain networks with specific network topology and connectivity strengths. Further sophisticated research is needed to deepen our understanding of these highly interesting and complex phenomena.

Keywords: EEG hyper scanning, intra- and interbrain coupling, multilayer hyper brain networks, social interaction, within- and cross-frequency coupling

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4669 An Overview of Evaluations Using Augmented Reality for Assembly Training Tasks

Authors: S. Werrlich, E. Eichstetter, K. Nitsche, G. Notni

Abstract:

Augmented Reality (AR) is a strong growing research topic in different training domains such as medicine, sports, military, education and industrial use cases like assembly and maintenance tasks. AR claims to improve the efficiency and skill-transfer of training tasks. This paper gives a comprehensive overview of evaluations using AR for assembly and maintenance training tasks published between 1992 and 2017. We search in a structured way in four different online databases and get 862 results. We select 17 relevant articles focusing on evaluating AR-based training applications for assembly and maintenance tasks. This paper also indicates design guidelines which are necessary for creating a successful application for an AR-based training. We also present five scientific limitations in the field of AR-based training for assembly tasks. Finally, we show our approach to solve current research problems using Design Science Research (DSR).

Keywords: assembly, augmented reality, survey, training

Procedia PDF Downloads 248