Search results for: brain MRI segmentation

Authors: Fatima Mokeddem

Abstract:

The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

Procedia PDF Downloads 140

Authors: Noor Hasmini Abdghani, Nik Kamariah Nikmat, Nor Hayati Ahmad

Abstract:

Rapid growth of the internet technology led to changes in the consumer lifestyles. This involved customer buying behaviour-based internet that create new kind of buying strategy. Hence, it has summoned many of world firms including Malaysia to generate new quality strategy in preparation to face new customer buying lifestyles. Particularly, this study focused on identifying online customer segment of automobile passenger car customers. Secondly, the objective is to understand online customer’s receptiveness towards internet technologies. This study distributed 700 questionnaires whereby 582 were returned representing 83% response rate. The data were analysed using factor and regression analyses. The result from the factor analysis precipitates four online passenger car segmentations in Malaysia, which are: Segment (1)- Automobile Online shopping Preferences, Segment (2)- Automobile Online Brand Comparison, Segment (3)- Automobile Online Information Seeking and Segment (4)- Automobile Offline Shopping Preferences. In understanding the online customer’s receptiveness towards internet, the regression result shows that there is significant relationship between each of four segments of online passenger car customer with attitude towards automobile online shopping. This implies that, for online customers to have receptiveness toward internet technologies, he or she must have preferences toward online shopping or at least prefer to browse any related information online even if the actual purchase is made at the traditional store. With this proposed segmentation strategy, the firms especially the automobile firms will be able to understand their online customer behavior. At least, the proposed segmentation strategy will help the firms to strategize quality management approach for their online customers’ buying decision making.

Keywords: Automobile, Market Segmentation, Online Shopping Attitude, Quality Management Strategy

Procedia PDF Downloads 540

Authors: Karima Merchant

Abstract:

The aim of this study was to analyze the impact of the Writing Eight Exercise, an exercise from the Brain Integration Therapy, with Kindergartners who are struggling with writing tasks in school. With the help of this exercise, children were able to cross the midline, an invisible line running from our brain to our feet, which separates the body’s right from left. Crossing the midline integrates the brain hemispheres, thus encouraging bilateral movement. The study was spread over 15 weeks where the children were required to do the Writing Eight Exercise 4 times a week. The data collection methods included observations, student work samples and feedback from teachers and parents. Based on the results of this study, it can be concluded that the Writing Eight Exercise had a positive impact on students’ approach towards writing tasks, letter formation, and fine motor skills.

Keywords: crossing the midline, fine motor skills, letter formation, writing

Procedia PDF Downloads 461

Authors: Fumihiro Imai, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

Abstract:

It is important to know the growth rate of brain tumors before surgery because it influences treatment planning, including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without the administration of a contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after a clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients, and WHO grade 4 in 2 patients), meningioma WHO grade 1 in 2 patients, and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW signals than that low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

Procedia PDF Downloads 86

Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

Abstract:

The study uses an image analysis technique employing thermal imaging to measure the percentage of areas with various temperatures on a freezing surface. An image segmentation method using threshold values is applied to a sequence of image recording the freezing process. The phenomenon is transient and temperatures vary fast to reach the freezing point and complete the freezing process. Freezing salt water is subjected to the salt rejection that makes the freezing point dynamic and dependent on the salinity at the phase interface. For a specific area of freezing, nucleation starts from one side and end to another side, which causes a dynamic and transient temperature in that area. Thermal cameras are able to reveal a difference in temperature due to their sensitivity to infrared radiance. Using Experimental setup, a video is recorded by a thermal camera to monitor radiance and temperatures during the freezing process. Image processing techniques are applied to all frames to detect and classify temperatures on the surface. Image processing segmentation method is used to find contours with same temperatures on the icing surface. Each segment is obtained using the temperature range appeared in the image and correspond pixel values in the image. Using the contours extracted from image and camera parameters, stratified areas with different temperatures are calculated. To observe temperature contours on the icing surface using the thermal camera, the salt water sample is dropped on a cold surface with the temperature of -20°C. A thermal video is recorded for 2 minutes to observe the temperature field. Examining the results obtained by the method and the experimental observations verifies the accuracy and applicability of the method.

Keywords: ice contour boundary, image processing, image segmentation, salt ice, thermal image

Procedia PDF Downloads 320

Authors: Dur-E- Shahwar

Abstract:

Much attention has been given to ‘bridging the gap’ between neuroscience and educational practice. In order to gain a better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning approach, focusing on boundary-spanning actors, boundary objects, and boundary work. In 26 semi-structured interviews, neuroscientists and education professionals were asked about their perceptions in regard to the gap between science and practice and the role they play in creating, managing, and disrupting this boundary. Neuroscientists and education professionals often hold conflicting views and expectations of both brain-based learning and of each other. This leads us to argue that there are increased prospects for a neuro-scientifically informed learning practice if science and practice work together as equal stakeholders in developing and implementing neuroscience research.

Keywords: language learning, explore, educational practices, mentalist, practice

Procedia PDF Downloads 337

Authors: Hanan F. Aly, Fateheya M. Metwally, Hanaa H. Ahmed

Abstract:

The current study is undertaken to elucidate a possible neuroprotective role of dehydroepiandrosterone (DHEA) against the development of Alzheimer’s disease in experimental rat model. Alzheimer’s disease was produced in young female ovariectomized rats by intraperitoneal administration of AlCl3 (4.2 mg/kg body weight) daily for 12 weeks. Half of these animals also received orally DHEA (250 mg/kg body weight, three times weekly) for 18 weeks. Control groups of animals received either DHAE alone, or no DHEA, or were not ovariectomized. After such treatment the animals were analyzed for oxidative stress biomarkers such as hydrogen peroxide, nitric oxide and malondialdehyde, total antioxidant capacity, reduced glutathione, glutathione peroxidase, glutathione reductase, superoxide dismutase and catalase activities, antiapoptotic marker Bcl-2 and brain derived neurotrophic factor. Also, brain cholinergic markers (acetylcholinesterase and acetylcholine) were determined. The results revealed significant increase in oxidative stress parameters associated with significant decrease in the antioxidant enzyme activities in Al-intoxicated ovariectomized rats. Significant depletion in brain Bcl-2 and brain-derived neurotrophic factor levels were also detected. Moreover, significant elevations in brain acetylcholinesterase activity accompanied with significant reduction in acetylcholine level were recorded. Significant amelioration in all investigated parameters was detected as a result of treatment of Al-intoxicated ovariectomized rats with DHEA. These results were confirmed by histological examination of brain sections. These results clearly indicate a neuroprotective effect of DHEA against Alzheimer’s disease.

Keywords: Alzheimer’s disease, oxidative stress, apoptosis, dehydroepiandrosterone

Procedia PDF Downloads 323

Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

Abstract:

Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides a very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations، Intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review The findings EEG- LORETA about epilepsy.

Keywords: epilepsy, EEG, EEG-LORETA

Procedia PDF Downloads 545

Authors: C. Román, M. Guevara, P. Salas, D. Duclap, J. Houenou, C. Poupon, J. F. Mangin, P. Guevara

Abstract:

Diffusion Magnetic Resonance Imaging (dMRI) allows the non-invasive study of human brain white matter. From diffusion data, it is possible to reconstruct fiber trajectories using tractography algorithms. Our previous work consists in an automatic method for the identification of short association bundles of the superficial white matter (SWM), based on a whole brain inter-subject hierarchical clustering applied to a HARDI database. The method finds representative clusters of similar fibers, belonging to a group of subjects, according to a distance measure between fibers, using a non-linear registration (DTI-TK). The algorithm performs an automatic labeling based on the anatomy, defined by a cortex mesh parcelated with FreeSurfer software. The clustering was applied to two independent groups of 37 subjects. The clusters resulting from both groups were compared using a restrictive threshold of mean distance between each pair of bundles from different groups, in order to keep reproducible connections. In the left hemisphere, 48 reproducible bundles were found, while 43 bundles where found in the right hemisphere. An inter-hemispheric bundle correspondence was then applied. The symmetric horizontal reflection of the right bundles was calculated, in order to obtain the position of them in the left hemisphere. Next, the intersection between similar bundles was calculated. The pairs of bundles with a fiber intersection percentage higher than 50% were considered similar. The similar bundles between both hemispheres were fused and symmetrized. We obtained 30 common bundles between hemispheres. An atlas was created with the resulting bundles and used to segment 78 new subjects from another HARDI database, using a distance threshold between 6-8 mm according to the bundle length. Finally, a laterality index was calculated based on the bundle volume. Seven bundles of the atlas presented right laterality (IP_SP_1i, LO_LO_1i, Op_Tr_0i, PoC_PoC_0i, PoC_PreC_2i, PreC_SM_0i, y RoMF_RoMF_0i) and one presented left laterality (IP_SP_2i), there is no tendency of lateralization according to the brain region. Many factors can affect the results, like tractography artifacts, subject registration, and bundle segmentation. Further studies are necessary in order to establish the influence of these factors and evaluate SWM laterality.

Keywords: dMRI, hierarchical clustering, lateralization index, tractography

Procedia PDF Downloads 331

Authors: Nirupama Dixit, Anyaa Mittal, Neeru Sood

Abstract:

Alzheimer’s disease (AD) is a progressive form of dementia, contributing to up to 70% of cases, mostly observed in elderly but is not restricted to old age. The pathophysiology of the disease is characterized by specific pathological changes in brain. The changes (i.e. accumulation of metal ions in brain, formation of extracellular β-amyloid (Aβ) peptide aggregates and tangle of hyper phosphorylated Tau protein inside neurons) damage the neuronal connections irreversibly. The current issues in improvement of life quality of Alzheimer's patient lies in the fact that the diagnosis is made at a late stage of the disease and the medications do not treat the basic causes of Alzheimer's. The targeted delivery of drug through the blood brain barrier (BBB) poses several limitations via traditional approaches for treatment. To overcome these drug delivery limitation, nanoparticles provide a promising solution. This review focuses on current strategies for efficient targeted drug delivery using nanoparticles and improving the quality of therapy provided to the patient. Nanoparticles can be used to encapsulate drug (which is generally hydrophobic) to ensure its passage to brain; they can be conjugated to metal ion chelators to reduce the metal load in neural tissue thus lowering the harmful effects of oxidative damage; can be conjugated with drug and monoclonal antibodies against BBB endogenous receptors. Finally this review covers how the nanoparticles can play a role in diagnosing the disease.

Keywords: Alzheimer's disease, β-amyloid plaques, blood brain barrier, metal chelators, nanoparticles

Procedia PDF Downloads 490

Authors: Chung-Ming Lo, Kevin Li-Chun Hsieh

Abstract:

The central nervous system in the World Health Organization defines grade 2, 3, 4 gliomas according to the aggressiveness. For brain tumors, using image examination would have a lower risk than biopsy. Besides, it is a challenge to extract relevant tissues from biopsy operation. Observing the whole tumor structure and composition can provide a more objective assessment. This study further proposed a computer-aided diagnosis (CAD) system based on a convolutional neural network to quantitatively evaluate a tumor's malignancy from brain magnetic resonance imaging. A total of 30 grade 2, 43 grade 3, and 57 grade 4 gliomas were collected in the experiment. Transferred parameters from AlexNet were fine-tuned to classify the target brain tumors and achieved an accuracy of 98% and an area under the receiver operating characteristics curve (Az) of 0.99. Without pre-trained features, only 61% of accuracy was obtained. The proposed convolutional neural network can accurately and efficiently classify grade 2, 3, and 4 gliomas. The promising accuracy can provide diagnostic suggestions to radiologists in the clinic.

Keywords: convolutional neural network, computer-aided diagnosis, glioblastoma, magnetic resonance imaging

Procedia PDF Downloads 147

Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum

Abstract:

Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.

Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value

Procedia PDF Downloads 412

Authors: C. Flynn, Q. Yuan, C. Reinhardt

Abstract:

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder affecting broad areas of the cerebral cortex and hippocampus. More than 95% of AD cases are representative of sporadic AD, where both genetic and environmental risk factors play a role. The main pathological features of AD include the widespread deposition of amyloid-beta and neurofibrillary tau tangles in the brain. The earliest brain pathology related to AD has been defined as hyperphosphorylated soluble tau in the noradrenergic locus coeruleus (LC) neurons, characterized by Braak. However, the cause of this pathology and the ultimate progression of AD is not understood. Increasing research points to a connection between the gut microbiota and the brain, and mounting evidence has shown that there is a bidirectional interaction between the two, known as the gut-brain axis. This axis can allow for bidirectional movement of neuroinflammatory cytokines and pathogenic misfolded proteins, as seen in AD. Prebiotics and probiotics have been shown to have a beneficial effect on gut health and can strengthen the gut-barrier as well as the blood-brain barrier, preventing the spread of these pathogens across the gut-brain axis. Our laboratory has recently established a pretangle tau rat model, in which we selectively express pseudo-phosphorylated human tau (htauE14) in the LC neurons of TH-Cre rats. LC htauE14 produced pathological changes in rats resembling those of the preclinical AD pathology (reduced olfactory discrimination and LC degeneration). In this work, we will investigate the effects of pre/probiotic ingestion on AD behavioral deficits, blood inflammation/cytokines, and various brain markers in our experimental rat model of AD. Rats will be infused with an adeno-associated viral vector containing a human tau gene pseudophosphorylated at 14 sites (common in LC pretangles) into 2-3 month TH-Cre rats. Fecal and blood samples will be taken at pre-surgery, and various post-surgery time points. A collection of behavioral tests will be performed, and immunohistochemistry/western blotting techniques will be used to observe various biomarkers. This work aims to elucidate the relationship between gut health and AD progression by strengthening gut-brain relationship and aims to observe the overall effect on tau formation and tau pathology in AD brains.

Keywords: alzheimer’s disease, aging, gut microbiome, neurodegeneration

Procedia PDF Downloads 137

Authors: Lara Ann Türeli, Özlem Bozkurt

Abstract:

There is a biochemical component to listening to music. The type of music listened to can lead to different levels of neurotransmitter and biochemical activity within the brain, resulting in brain stimulation and different moods. Therefore, music plays an important role in neuromarketing and consumer behavior. The quality of a commercial can be measured by the effect the music has on its audience. Thus, understanding how music can affect the brain can provide better marketing strategies for all businesses. The type of music used plays an important role in how a person responds to certain experiences. In the context of marketing and consumer behavior, music can determine whether a person will be intrigued to buy something. Depending on the type of music listened to by an individual; the music may trigger the release of pleasurable neurotransmitters such as dopamine. Dopamine is a neurotransmitter that plays an important role in reward pathways in the brain. When an individual experiences a pleasurable activity, increased levels of dopamine are produced, eventually leading to the formation of new reward pathways. Consequently, the increased dopamine activity within the brain triggered by music can result in new reward pathways along the dopamine pathways in the brain. Selecting pleasurable music for commercials can result in long-term brain stimulation, increasing consumerism. The effect of music on consumerism should be considered not only in commercials but also in the atmosphere it creates within stores. The type of music played in a store can affect consumer behavior and intention. Specifically, the rhythm, pitch, and pace of music can contribute to the mood of the song. The background music in a store can determine the consumer’s emotional presence and consequently affect their intentions. In conclusion, understanding the physiological, psychological, and neurochemical basis of the effect of music on brain stimulation is essential to understand consumer behavior. The role of dopamine in the formation of reward pathways as a result of music directly contributes to consumer behavior and the tendency of a commercial or store to leave a long-term effect on the consumer. The careful consideration of the pitch, pace, and rhythm of a song in the selection of music can not only help companies predict the behavior of a consumer but also determine the behavior of a consumer.

Keywords: sensory processing, neuropsychology, dopamine, neuromarketing

Procedia PDF Downloads 80

Authors: Hooshmand Kalayeh

Abstract:

The human brain consists of reptilian, mammalian, and thinking brain. And mind consists of conscious, subconscious, and unconscious parallel neural-net programs. The primary objective of this paper is to propose a methodology for quantitative analysis of neural-nets associated with these mental activities in the neocortex. The secondary objective of this paper is to suggest a methodology for quantitative analysis of presence; the proposed methodologies can be used as a first-step to measure, monitor, and understand consciousness and presence. This methodology is based on Neural-Networks (NN), number of neuron in each NN associated with consciousness, subconsciouness, and unconsciousness, and number of neurons in neocortex. It is assumed that the number of neurons in each NN is correlated with the associated area and volume. Therefore, online and offline visualization techniques can be used to identify these neural-networks, and online and offline measurement methods can be used to measure areas and volumes associated with these NNs. So, instead of the number of neurons in each NN, the associated area or volume also can be used in the proposed methodology. This quantitative analysis and associated online and offline measurements and visualizations of different Neural-Networks enable us to rewire the connections in our brain for a more balanced living.

Keywords: brain, mind, consciousness, presence, sub-consciousness, unconsciousness, skills, concentrations, attention

Procedia PDF Downloads 314

Authors: Kabil Boukhari

Abstract:

In the context of information retrieval, the selection of the most relevant words is a very important step. In fact, the text cleaning allows keeping only the most representative words for a better use. In this paper, we propose a library for the purpose text preprocessing within an implemented application to facilitate this task. This study has two purposes. The first, is to present the related work of the various steps involved in text preprocessing, presenting the segmentation, stemming and lemmatization algorithms that could be efficient in the rest of study. The second, is to implement a developed tool for text preprocessing in French and English. This library accepts unstructured text as input and provides the preprocessed text as output, based on a set of rules and on a base of stop words for both languages. The proposed library has been made on different corpora and gave an interesting result.

Keywords: text preprocessing, segmentation, knowledge extraction, normalization, text generation, information retrieval

Procedia PDF Downloads 94

Authors: Rafik Djemili, Hocine Bourouba, M. C. Amara Korba

Abstract:

In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods.

Keywords: brain-computer interface, motor imagery, electroencephalogram, linear discriminant analysis, support vector machine

Procedia PDF Downloads 499

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

Abstract:

Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

Procedia PDF Downloads 149

Authors: Qazi Umer Jamil, Abubakr Siddique, Mubeen Ur Rehman, Nida Aziz, Mohsin I. Tiwana

Abstract:

This paper discusses a brain controlled robotic gait trainer for neurorehabilitation of Spinal Cord Injury (SCI) patients. Patients suffering from Spinal Cord Injuries (SCI) become unable to execute motion control of their lower proximities due to degeneration of spinal cord neurons. The presented approach can help SCI patients in neuro-rehabilitation training by directly translating patient motor imagery into walkers motion commands and thus bypassing spinal cord neurons completely. A non-invasive EEG based brain-computer interface is used for capturing patient neural activity. For signal processing and classification, an open source software (OpenVibe) is used. Classifiers categorize the patient motor imagery (MI) into a specific set of commands that are further translated into walker motion commands. The robotic walker also employs fall detection for ensuring safety of patient during gait training and can act as a support for SCI patients. The gait trainer is tested with subjects, and satisfactory results were achieved.

Keywords: brain computer interface (BCI), gait trainer, spinal cord injury (SCI), neurorehabilitation

Procedia PDF Downloads 161

Authors: Magda I. Hassan

Abstract:

This paper aims to investigate the health effects of aspartame on weanling male hamsters. 20 Golden Syrian hamsters drank only water (control) or water with 6, 11, and 18 mg aspartame/kg of body weight per day for 42 days. Food intake, weight gain, glucose blood level, and lipid profile were determined at the end of the experiment. The animals were sacrificed and histopathological examination of organs (liver, brain and heart) was done. Results revealed that animals in Asp.groups consumed significantly larger amount of food than the control (13.4±5.9, 8.6±2.5 and 8.8±3.0 vs 4.2±2.5 g/day, in succession). Hamsters in the control group showed higher total cholesterol and HDL levels than hamsters in aspartame 6, 11, 18 groups (160±19 vs 101±13, 130±22, 141±15 mg/dl & 144±9 vs 120±12, 118±13, 99±17 respectively (P<0•05)). The control group showed a glucose concentration below those of aspartame groups, indicating no effect of aspartame on glucose blood level. While, there were no significant differences in the triglycerides and LDL levels between control group and Asp.groups. Histopathological changes were observed, especially in brain and liver cells. Aspartame increases appetite and weight gain of young hamsters. Therefore, FDA should reconsider the acceptable daily intake (ADI) of aspartame for children.

Keywords: aspartame, brain, food intake, hamsters

Procedia PDF Downloads 285

Authors: Thanooja Naushad, Meena Natarajan, Tushar Vasant Kulkarni

Abstract:

Background: The Lacey Assessment of Preterm Infants (LAPI) is used in clinical practice to identify premature babies at risk of neuromotor impairments, especially cerebral palsy. This study attempted to find the validity of the Lacey assessment of preterm infants to predict neuromotor outcomes of premature babies at 12 months corrected age and to compare its predictive ability with the brain ultrasound. Methods: This prospective cohort study included 89 preterm infants (45 females and 44 males) born below 35 weeks gestation who were admitted to the neonatal intensive care unit of a government hospital in Dubai. Initial assessment was done using the Lacey assessment after the babies reached 33 weeks postmenstrual age. Follow up assessment on neuromotor outcomes was done at 12 months (± 1 week) corrected age using two standardized outcome measures, i.e., infant neurological international battery and Alberta infant motor scale. Brain ultrasound data were collected retrospectively. Data were statistically analyzed, and the diagnostic accuracy of the Lacey assessment of preterm infants (LAPI) was calculated -when used alone and in combination with the brain ultrasound. Results: On comparison with brain ultrasound, the Lacey assessment showed superior specificity (96% vs. 77%), higher positive predictive value (57% vs. 22%), and higher positive likelihood ratio (18 vs. 3) to predict neuromotor outcomes at one year of age. The sensitivity of Lacey assessment was lower than brain ultrasound (66% vs. 83%), whereas specificity was similar (97% vs. 98%). A combination of Lacey assessment and brain ultrasound results showed higher sensitivity (80%), positive (66%), and negative (98%) predictive values, positive likelihood ratio (24), and test accuracy (95%) than Lacey assessment alone in predicting neurological outcomes. The negative predictive value of the Lacey assessment was similar to that of its combination with brain ultrasound (96%). Conclusion: Results of this study suggest that the Lacey assessment of preterm infants can be used as a supplementary assessment tool for premature babies in the neonatal intensive care unit. Due to its high specificity, Lacey assessment can be used to identify those babies at low risk of abnormal neuromotor outcomes at a later age. When used along with the findings of the brain ultrasound, Lacey assessment has better sensitivity to identify preterm babies at particular risk. These findings have applications in identifying premature babies who may benefit from early intervention services.

Keywords: brain ultrasound, lacey assessment of preterm infants, neuromotor outcomes, preterm

Procedia PDF Downloads 138

Authors: Sultan Z. Mahmud, Emily C. Graff, Adil Bashir

Abstract:

Phosphoprotein enriched in astrocytes 15 kDa (PEA-15) is a multifunctional adapter protein which is associated with the regulation of apoptotic cell death. Recently it has been discovered that PEA-15 is crucial in normal neurodevelopment of domestic cats, a gyrencephalic animal model, although the exact function of PEA-15 in neurodevelopment is unknown. This study investigates how PEA-15 affects the blood-brain barrier (BBB) permeability in cat brain, which can cause abnormalities in tissue metabolite and energy supplies. Severe polymicrogyria and microcephaly have been observed in cats with a loss of function PEA-15 mutation, affecting the normal neurodevelopment of the cat. This suggests that the vital role of PEA-15 in neurodevelopment is associated with gyrification. Neurodevelopment is a highly energy demanding process. The mammalian brain depends on glucose as its main energy source. PEA-15 plays a very important role in glucose uptake and utilization by interacting with phospholipase D1 (PLD1). Mitochondria also plays a critical role in bioenergetics and essential to supply adequate energy needed for neurodevelopment. Cerebral blood flow regulates adequate metabolite supply and recent findings also showed that blood plasma contains mitochondria as well. So the BBB can play a very important role in regulating metabolite and energy supply in the brain. In this study the blood-brain permeability in cat brain was measured using MRI magnetization transfer (MT) effect on the perfusion signal. Perfusion is the tissue mass normalized supply of blood to the capillary bed. Perfusion also accommodates the supply of oxygen and other metabolites to the tissue. A fraction of the arterial blood can diffuse to the tissue, which depends on the BBB permeability. This fraction is known as water extraction fraction (EF). MT is a process of saturating the macromolecules, which has an effect on the blood that has been diffused into the tissue while having minimal effect on intravascular blood water that has not been exchanged with the tissue. Measurement of perfusion signal with and without MT enables to estimate the microvascular blood flow, EF and permeability surface area product (PS) in the brain. All the experiments were performed with Siemens 7T Magnetom with 32 channel head coil. Three control cats and three PEA-15 mutant cats were used for the study. Average EF in white and gray matter was 0.9±0.1 and 0.86±0.15 respectively, perfusion in white and gray matter was 85±15 mL/100g/min and 97±20 mL/100g/min respectively, PS in white and gray matter was 201±25 mL/100g/min and 225±35 mL/100g/min respectively for control cats. For PEA-15 mutant cats, average EF in white and gray matter was 0.81±0.15 and 0.77±0.2 respectively, perfusion in white and gray matter was 140±25 mL/100g/min and 165±18 mL/100g/min respectively, PS in white and gray matter was 240±30 mL/100g/min and 259±21 mL/100g/min respectively. This results show that BBB is compromised in PEA-15 mutant cat brain, where EF is decreased and perfusion as well as PS are increased in the mutant cats compared to the control cats. This findings might further explain the function of PEA-15 in neurodevelopment.

Keywords: BBB, cat brain, magnetization transfer, PEA-15

Procedia PDF Downloads 143

Authors: M. Chojak

Abstract:

Recently, more and more scientific disciplines refer to research in the field of neurobiology. Interdisciplinary research procedures are created using modern methods of brain imaging. Neither did the pedagogues start looking for neuronal conditions for various processes. The publications began to show concepts such as ‘neuropedagogy’, ‘neuroeducation’, ‘neurodidactics’, ‘brain-friendly education’. They were and are still used interchangeably. In the offer of training for teachers, the topics of multiple intelligences or educational kinesiology began to be more and more popular. These and other ideas have been actively introduced into the curricula. To our best knowledge, the literature on the subject lacks articles organizing the new nomenclature and indicating the methodological framework for research that would confirm the effectiveness of the above-mentioned innovations. The author of this article tries to find the place for neuropedagogy in the system of sciences, define its subject of research, methodological framework and basic concepts. This is necessary to plan studies that will verify the so-called neuromyths.

Keywords: brain, education, neuropedagogy, research

Procedia PDF Downloads 173

Authors: P. Neeraj, Anurag Sharma, Harsukhpreet Singh

Abstract:

In current years, Brain-Computer Interface (BCI) scheme based on steady-state Visual Evoked Potential (SSVEP) have earned much consideration. This study tries to evolve an SSVEP based BCI scheme that can regulate any gadget mock-up in two unique positions ON and OFF. In this paper, two distinctive gleam frequencies in low-frequency part were utilized to evoke the SSVEPs and were shown on a Liquid Crystal Display (LCD) screen utilizing Lab View. Two stimuli shading, Yellow, and Blue were utilized to prepare the system in SSVEPs. The Electroencephalogram (EEG) signals recorded from the occipital part. Elements of the brain were separated by utilizing discrete wavelet Transform. A prominent system for multilayer system diverse Neural Network Algorithm (NNA), is utilized to characterize SSVEP signals. During training of the network with diverse calculation Regression plot results demonstrated that when Levenberg-Marquardt preparing calculation was utilized the exactness turns out to be 93.9%, which is superior to another training algorithm.

Keywords: brain computer interface, electroencephalography, steady-state visual evoked potential, wavelet transform, neural network

Procedia PDF Downloads 334

Authors: S. Thangapandiyan, S. Miltonprabu

Abstract:

Fl (Fl) exposure engenders neurodegeneration and induces oxidative stress in the brain. The Neuroprotective role of EGCG on oxidative stress-mediated neurotoxicity in Fl intoxicated rat hippocampus has not yet been explored so far. Hence, the present study is focused on witnessing whether EGCG (40mg/kg) supplementation prevents Fl induced oxidative stress in the brain of rats with special emphasis on the hippocampus. Fl (25mg/kg) intoxication for four weeks in rats showed an increase in Fl concentration along with the decrease the AChE, NP, DA, and 5-HT activity in the brain. The oxidative stress markers (ROS, TBARS, NO, and PC) were significantly increased with decreased enzymatic (SOD, CAT, GPx, GR, GST, and G6PD) and non-enzymatic antioxidants (GSH, TSH, and Vit.C) in Fl intoxicated rat hippocampus. Moreover, Fl intoxicated rats exhibited an intrinsic and extrinsic pathway mediated apoptosis in the hippocampus of rats. Fl intoxication significantly increased the DNA damage as evidenced by increased DNA fragmentation. Furthermore, the toxic impact of Fl on hippocampus was also proved by the immunohistochemical, histological, and ultrastructural studies. Pre-administration of EGCG has significantly protected the Fl induced oxidative stress, biochemical changes, cellular apoptotic, and histological alternations in the hippocampus of rats. In conclusion, EGCG supplementation significantly attenuated the Fl induced oxidative stress mediated neurotoxicity via its free radical scavenging and antioxidant activity.

Keywords: brain, hippocampal, NaF, ROS, EGCG

Procedia PDF Downloads 392

Authors: Shweta Dhindhwal

Abstract:

Dopamine is an essential neurotransmitter in the central nervous system of all vertebrates and plays an important role in many processes such as motor function, learning and behavior, and sensory activity. One of the important functions of dopamine is release of pituitary hormones. It is synthesized from the amino acid tyrosine. Two types of dopamine receptors, D1-like and D2-like, have been reported in fish. The dopamine containing neurons are located in the olfactory bulbs, the ventral regions of the pre-optic area and tuberal hypothalamus. Distribution of the dopaminergic system has not been studied in the murrel, Channa punctatus. The present study deals with identification of D2 receptors in the brain of murrel. A phylogenetic tree has been constructed using partial sequence of D2 receptor. Distribution of putative dopaminergic neurons in the brain has been investigated. Also, formalin induced hypertrophy of neurosecretory cells in murrel has been studied.

Keywords: dopamine, fish, pre-optic area, murrel

Procedia PDF Downloads 421

Authors: Chia-Ju Peng, Shih-Jui Chen

Abstract:

This paper proposes a method to discriminate electroencephalogram (EEG) signals between different concentration states using empirical mode decomposition (EMD). Brain-computer interface (BCI), also called brain-machine interface, is a direct communication pathway between the brain and an external device without the inherent pathway such as the peripheral nervous system or skeletal muscles. Attention level is a common index as a control signal of BCI systems. The EEG signals acquired from people paying attention or in relaxation, respectively, are decomposed into a set of intrinsic mode functions (IMF) by EMD. Fast Fourier transform (FFT) analysis is then applied to each IMF to obtain the frequency spectrums. By observing power spectrums of IMFs, the proposed method has the better identification of EEG attention level than the original EEG signals between different concentration states. The band power of IMF3 is the most obvious especially in β wave, which corresponds to fully awake and generally alert. The signal processing method and results of this experiment paves a new way for BCI robotic system using the attention-level control strategy. The integrated signal processing method reveals appropriate information for discrimination of the attention and relaxation, contributing to a more enhanced BCI performance.

Keywords: biomedical engineering, brain computer interface, electroencephalography, rehabilitation

Procedia PDF Downloads 391

Authors: Qingjin Liu, Jinpeng Niu, Kangjia Chen, Jiao Li, Huafu Chen, Wei Liao

Abstract:

Functional connectomics is essential in cognitive science and neuropsychiatry, offering insights into the brain's complex network structures and dynamic interactions. Although neuroimaging has uncovered functional connectivity issues in Major Depressive Disorder (MDD) patients, the dynamic shifts in connectome topology and their link to gene expression are yet to be fully understood. To explore the differences in dynamic connectome topology between MDD patients and healthy individuals, we conducted an extensive analysis of resting-state functional magnetic resonance imaging (fMRI) data from 434 participants (226 MDD patients and 208 controls). We used multilayer network models to evaluate brain module dynamics and examined the association between whole-brain gene expression and dynamic module variability in MDD using publicly available transcriptomic data. Our findings revealed that compared to healthy individuals, MDD patients showed lower global mean values and higher standard deviations, indicating unstable patterns and increased regional differentiation. Notably, MDD patients exhibited more frequent module switching, primarily within the executive control network (ECN), particularly in the left dorsolateral prefrontal cortex and right fronto-insular regions, whereas the default mode network (DMN), including the superior frontal gyrus, temporal lobe, and right medial prefrontal cortex, displayed lower variability. These brain dynamics predicted the severity of depressive symptoms. Analyzing human brain gene expression data, we found that the spatial distribution of MDD-related gene expression correlated with dynamic module differences. Cell type-specific gene analyses identified oligodendrocytes (OPCs) as major contributors to the transcriptional relationships underlying module variability in MDD. To the best of our knowledge, this is the first comprehensive description of altered brain module dynamics in MDD patients linked to depressive symptom severity and changes in whole-brain gene expression profiles.

Keywords: major depressive disorder, module dynamics, magnetic resonance imaging, transcriptomic

Procedia PDF Downloads 25

Authors: Mahdi Akhbardeh

Abstract:

Synchronization of neuronal firing is a hallmark of several neurological diseases. Recently, stimulation techniques have been developed which make it possible to desynchronize oscillatory neuronal activity in a mild and effective way, without suppressing the neurons' firing. As yet, these techniques are being used to establish demand-controlled deep brain stimulation (DBS) techniques for the therapy of movement disorders like severe Parkinson's disease or essential tremor. We here present a first conceptualization suggesting that the nucleus accumbens is a promising target for the standard, that is, permanent high-frequency, DBS in patients with severe and chronic obsessive-compulsive disorder (OCD). In addition, we explain how demand-controlled DBS techniques may be applied to the therapy of OCD in those cases that are refractory to behavioral therapies and pharmacological treatment.

Keywords: stereotactic neurosurgery, deep brain stimulation, obsessive-compulsive disorder, phase resetting

Procedia PDF Downloads 512

Authors: Omar Abdalla, Abdelfatah Ahmed, Ahmed Mustafa, Abdelazem Eldouma

Abstract:

The purpose of this study is evaluating the effect of extremely low frequency magnetic field on Waster rats brain. The number of rats used in this study were 25, which were divided into five groups, each group containing five rats as follows: Group 1: The control group which was not exposed to energized field; Group 2: Rats were exposed to a magnetic field with an intensity of 0.6 mT (2 hours/day); Group 3: Rats were exposed to a magnetic field of 1.2 mT (2 hours/day); Group4: Rats were exposed to a magnetic field of 1.8 mT (2 hours/day); Group 5: Rats were exposed to a magnetic field of 2.4 mT (2 hours/day) and all groups were exposed for seven days, by designing a maze and calculating the time average for arriving to the decoy at special conditions. We found the time average before exposure for the all groups was G2=330 s, G3=172 s, G4=500 s and G5=174 s, respectively. We exposed all groups to ELF-MF and measured the time and we found: G2=465 s, G3=388 s, G4=501 s, and G5=442 s. It was observed that the time average increased directly with field strength. Histological samples of frontal lop of brain for all groups were taken and we found lesion, atrophy, empty vacuoles and disorder choroid plexus at frontal lope of brain. And finally we observed the disorder of choroid plexus in histological results and Alzheimer's symptoms increase when the magnetic field increases.

Keywords: nonionizing radiation, biophysics, magnetic field, shrinkage

Procedia PDF Downloads 545