Search results for: computational brain

Authors: Muhsin Kizhisseri, Jorg Schluter, Saleh Gharie

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Atherosclerosis is the main reason of stroke, which is one of the deadliest diseases in the world. The carotid artery in the brain is the prominent location for atherosclerotic progression, which hinders the blood flow into the brain. The inclusion of computational fluid dynamics (CFD) into the diagnosis cycle to understand the hemodynamics of the patient-specific carotid artery can give insights into stroke prediction. Realistic outlet boundary conditions are an inevitable part of the numerical simulations, which is one of the major factors in determining the accuracy of the CFD results. The Windkessel model-based outlet boundary conditions can give more realistic characteristics of the distal vascular branches of the carotid artery, such as the resistance to the blood flow and compliance of the distal arterial walls. This study aims to find the most influential distal branches of the carotid artery by using the Windkessel model parameters in the outlet boundary conditions. The parametric study approach to Windkessel model parameters can include the geometrical features of the distal branches, such as radius and length. The incorporation of the variations of the geometrical features of the major distal branches such as the middle cerebral artery, anterior cerebral artery, and ophthalmic artery through the Windkessel model can aid in identifying the most influential distal branch in the carotid artery. The results from this study can help physicians and stroke neurologists to have a more detailed and accurate judgment of the patient's condition.

Keywords: stroke, carotid artery, computational fluid dynamics, patient-specific, Windkessel model, distal vascular branches

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Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

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Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.

Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language

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Authors: Hyuk-Hoon Kim, Young Gi Min

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Background: In carbon monoxide (CO) intoxication, the pathophysiology of delayed neurological sequelae (DNS) is very complex and remains poorly understood. And predicting whether patients who exhibit resolved acute symptoms have escaped or will experience DNS represents a very important clinical issue. Brain magnetic resonance (MR) imaging has been conducted to assess the severity of brain damage as an objective method to predict prognosis. And co-ingestion of a second poison in patients with intentional CO poisoning occurs in almost one-half of patients. Among patients with co-ingestions, 66% ingested ethanol. We assessed the effects of ethanol on neurologic sequelae prevalence in acute CO intoxication by means of abnormal lesion in brain MR. Method: This study was conducted retrospectively by collecting data for patients who visited an emergency medical center during a period of 5 years. The enrollment criteria were diagnosis of acute CO poisoning and the measurement of the serum ethanol level and history of taking a brain MR during admission period. Official readout data by radiologist are used to decide whether abnormal lesion is existed or not. The enrolled patients were divided into two groups: patients with abnormal lesion and without abnormal lesion in Brain MR. A standardized extraction using medical record was performed; Mann Whitney U test and logistic regression analysis were performed. Result: A total of 112 patients were enrolled, and 68 patients presented abnormal brain lesion on MR. The abnormal brain lesion group had lower serum ethanol level (mean, 20.14 vs 46.71 mg/dL) (p-value<0.001). In addition, univariate logistic regression analysis showed the serum ethanol level (OR, 0.99; 95% CI, 0.98 -1.00) was independently associated with the development of abnormal lesion in brain MR. Conclusion: Ethanol could have neuroprotective effect in acute CO intoxication by sedative effect in stressful situation and mitigative effect in neuro-inflammatory reaction.

Keywords: carbon monoxide, delayed neuropsychological sequelae, ethanol, intoxication, magnetic resonance

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Authors: Savaş Karpuz, Sami Küçükşen

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The aim of this study is to investigate the effectiveness of neurological rehabilitation in patients with traumatic brain injury. Participants were 45 consecutive adults with traumatic brain injury who were received the neurologic rehabilitation. Sociodemographic characteristics of the patients, the cause of the injury, the duration of the coma and posttraumatic amnesia, the length of stay in the other inpatient clinics before rehabilitation, the time between injury and admission to the rehabilitation clinic, and the length of stay in the rehabilitation clinic were recorded. The differences in functional status between admission and discharge were determined with Disability Rating Scale (DRS), Functional Independence Measure (FIM), and Functional Ambulation Scale (FAS) and levels of cognitive functioning determined with Ranchos Los Amigos Scale (RLAS). According to admission time, there was a significant improvement identified in functional status of patients who had been given the intensive in-hospital cognitive rehabilitation program. At discharge time, the statistically significant differences were obtained in DRS, FIM, FAS and RLAS scores according to admission time. Better improvement in functional status was detected in patients with lower scores in DRS, and higher scores FIM and RLAS scores at the entry time. The neurologic rehabilitation significantly affects the recovery of functional status after traumatic brain injury.

Keywords: traumatic brain injury, rehabilitation, functional status, neurological

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Authors: Fengjuan Wang, Azilawati Jamaludin

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Developmental Dyscalculia (DD) is defined as a particular learning difficulty with continuous challenges in learning requisite math skills that cannot be explained by intellectual disability or educational deprivation. Recent studies have increasingly recognized that DD is a heterogeneous, instead of monolithic, learning disorder with not only cognitive and behavioral deficits but so too neural dysfunction. In recent years, neuroimaging studies employed group comparison to explore the neural underpinnings of DD, which contradicted the heterogenous nature of DD and may obfuscate critical individual differences. This research aimed to investigate the neural heterogeneity of DD using case studies with functional near-infrared spectroscopy (fNIRS). A total of 54 aged 6-7 years old of children participated in this study, comprising two comprehensive cognitive assessments, an 8-minute resting state, and an 8-minute one-digit addition task. Nine children met the criteria of DD and scored at or below 85 (i.e., the 16th percentile) on the Mathematics or Math Fluency subtest of the Wechsler Individual Achievement Test, Third Edition (WIAT-III) (both subtest scores were 90 and below). The remaining 45 children formed the typically developing (TD) group. Resting-state data and brain activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), and intraparietal sulcus (IPS) were collected for comparison between each case and the TD group. Graph theory was used to analyze the brain network under the resting state. This theory represents the brain network as a set of nodes--brain regions—and edges—pairwise interactions across areas to reveal the architectural organizations of the nervous network. Next, a single-case methodology developed by Crawford et al. in 2010 was used to compare each case’s brain network indicators and brain activation against 45 TD children’s average data. Results showed that three out of the nine DD children displayed significant deviation from TD children’s brain indicators. Case 1 had inefficient nodal network properties. Case 2 showed inefficient brain network properties and weaker activation in the IFG and IPS areas. Case 3 displayed inefficient brain network properties with no differences in activation patterns. As a rise above, the present study was able to distill differences in architectural organizations and brain activation of DD vis-à-vis TD children using fNIRS and single-case methodology. Although DD is regarded as a heterogeneous learning difficulty, it is noted that all three cases showed lower nodal efficiency in the brain network, which may be one of the neural sources of DD. Importantly, although the current “brain norm” established for the 45 children is tentative, the results from this study provide insights not only for future work in “developmental brain norm” with reliable brain indicators but so too the viability of single-case methodology, which could be used to detect differential brain indicators of DD children for early detection and interventions.

Keywords: brain activation, brain network, case study, developmental dyscalculia, functional near-infrared spectroscopy, graph theory, neural heterogeneity

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Authors: Ozgu Hafizoglu

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Analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with attributional, deep structural, casual relations that are essential to learning, to innovation in artificial worlds, and to discovery in science. Cognitive Model of Analogy (CMA) leads and creates information pattern transfer within and between domains and disciplines in science. This paper demonstrates the Cognitive Model of Analogy (CMA) as an evolutionary approach to scientific research. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions. In this paper, the model of analogical reasoning is created based on brain cells, their fractal, and operational forms within the system itself. Visualization techniques are used to show correspondences. Distinct phases of the problem-solving processes are divided thusly: encoding, mapping, inference, and response. The system is revealed relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain cells: glial cells, axons, axon terminals, and neurons, relative to matching conditions of analogical reasoning and relational information. It’s found that encoding, mapping, inference, and response processes in four-term analogical reasoning are corresponding with the fractal and operational forms of brain cells: glial, axons, and neurons.

Keywords: analogy, analogical reasoning, cognitive model, brain and glials

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Authors: Hanna Poikonen, Petri Toiviainen, Mari Tervaniemi

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Event-related potentials (ERPs) evoked by simple tones in the brain have been extensively studied. However, in reality the music surrounding us is spectrally and temporally complex and dynamic. Thus, the research using natural sounds is crucial in understanding the operation of the brain in its natural environment. Music is an excellent example of natural stimulation, which, in various forms, has always been an essential part of different cultures. In addition to sensory responses, music elicits vast cognitive and emotional processes in the brain. When compared to laymen, professional musicians have stronger ERP responses in processing individual musical features in simple tone sequences, such as changes in pitch, timbre and harmony. Here we show that the ERP responses evoked by rapid changes in individual musical features are more intense in musicians than in laymen, also while listening to long excerpts of the composition Carmen. Interestingly, for professional dancers, the amplitudes of the cognitive P300 response are weaker than for musicians but still stronger than for laymen. Also, the cognitive P300 latencies of musicians are significantly shorter whereas the latencies of laymen are significantly longer. In contrast, sensory N100 do not differ in amplitude or latency between musicians and laymen. These results, acquired from a novel ERP methodology for natural music, suggest that we can take the leap of studying the brain with long pieces of natural music also with the ERP method of electroencephalography (EEG), as has already been made with functional magnetic resonance (fMRI), as these two brain imaging devices complement each other.

Keywords: electroencephalography, expertise, musical features, real-life music

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Authors: Tapas Karmaker

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Centuries ago, we came to know about ‘Golden Ratio’ also known as Golden Angle. The idea of this research is based on this theme. Researcher perceives ‘The Golden Ratio’ in terms of harmony, meaning that every single item in the universe follows a harmonic behavior. In case of human being, brain responses easily and quickly to this harmony to help memorization. In this theory, harmony means a link. This study has been carried out on a segment of school students and a segment of common people for a period of three years from 2003 to 2006. The research in this respect intended to determine the impact of harmony in the brain of these people. It has been found that students and common people can increase their memorization capacity as much as 70 times more by applying this method. This method works faster and better between age of 8 and 30 years. This result was achieved through tests to assess memorizing capacity by using tools like words, rhymes, texts, math and drawings. The research concludes that this harmonic method can be applied for improving the capacity of learning languages, for the better quality of lifestyle, or any other terms of life as well as in professional activity.

Keywords: language, education, golden brain, learning, teaching

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Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

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Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: T. O. Ikpesu, I. Tongo, A. Ariyo

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This study was conducted to assess the effects of an organophosphate pesticide glyphosate formulation on neurological enzymes in the brain, liver and serum of juvenile Clarias gariepinus, and also to examine the antidotal prospect of Garcinia kola seeds extract. The fish divided into five groups were exposed to different treatments of glyphosate formulation and Garcinia kola seeds extract. Acetyl cholinesterase activities in the brain, liver and serum of the fish were estimated in the experimental and control fishes on day -7, 14, 21 and of 28 by spectrophotometrical methods. The enzyme was significantly (p < 0.05) inhibited in glyphosate formulation test. The inhibition percentages of AChE ranged for the brain, liver and serum between 40.7–59.4%, 50-57% and 27.5–51.3%, respectively. The aberrated parameters were recovered in G. kola seeds extract treated aquaria, and was dose and time dependent. The present study demonstrated that in vivo glyphosate formulation exposure caused AChE inhibition in the brain, liver and the serum. The brain tissue, however, might be suggested as a good indicator tissue for aquatic pollutants exposure in the fish and G. kola seeds extract has shown to be a good remedy for neurology restoration in a noxious circumstance. The findings has shown that xenobiotics could be eliminated from aquatic organisms, especially fish, and could be put into practice in areas at risk of pollutants. This approach can reduce the risks of biomagnification of poison in sea food. Hence, formulation of this plant extracts into capsule should be encouraged and supported.

Keywords: glyphosate, Clarias gariepinus, brain, Garcinia kola, acetyl cholinesterase, enzymes

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Amedeo D'Angiulli, Kylie Schibli

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Traditionally, children’s brain development research has emphasized the limitative aspects of disability and impairment, electing as an explanatory model the classical clinical notions of brain lesion or functional deficit. In contrast, Positive Educational Neuroscience (PEN) is a new approach that emphasizes strengths and human flourishing related to the brain by exploring how learning practices have the potential to enhance neurocognitive flexibility through neuroplastic overcompensation. This mini-review provides an overview of PEN and shows how it links to the concept of neurocognitive flexibility. We provide examples of how the present concept of neurocognitive flexibility can be applied to special education by exploring examples of neuroplasticity in the learning domain, including: (1) learning to draw in congenitally totally blind children, and (2) music training in children from disadvantaged neighborhoods. PEN encourages educators to focus on children’s strengths by recognizing the brain’s capacity for positive change and to incorporate activities that support children’s individual development.

Keywords: neurocognitive development, positive educational neuroscience, sociocultural approach, special education

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Authors: Mannan Malik Muhammad Naeem, Jeong Myung Yung

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Functional near infrared spectroscopy (fNIRS) has a favorable position in non-invasive brain imaging techniques. The concentration change of oxygenated hemoglobin and de-oxygenated hemoglobin during particular cognitive activity is the basis for this neuro-imaging modality. Two wavelengths of near-infrared light can be used with modified Beer-Lambert law to explain the indirect status of neuronal activity inside brain. The temporal resolution of fNIRS is very good for real-time brain computer-interface applications. The portability, low cost and an acceptable temporal resolution of fNIRS put it on a better position in neuro-imaging modalities. In this study, an optimization model for impulse response function has been used to estimate/predict initial dip using fNIRS data. In addition, the activity strength parameter related to motor based cognitive task has been analyzed. We found an initial dip that remains around 200-300 millisecond and better localize neural activity.

Keywords: fNIRS, brain-computer interface, optimization algorithm, adaptive signal processing

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Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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Authors: Simeon Mayala, Ida Herdlevær, Jonas Bull Haugsøen, Shamundeeswari Anandan, Sonia Gavasso, Morten Brun

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In this paper, we propose a minimum spanning tree-based method for segmenting brain tumors. The proposed method performs interactive segmentation based on the minimum spanning tree without tuning parameters. The steps involve preprocessing, making a graph, constructing a minimum spanning tree, and a newly implemented way of interactively segmenting the region of interest. In the preprocessing step, a Gaussian filter is applied to 2D images to remove the noise. Then, the pixel neighbor graph is weighted by intensity differences and the corresponding minimum spanning tree is constructed. The image is loaded in an interactive window for segmenting the tumor. The region of interest and the background are selected by clicking to split the minimum spanning tree into two trees. One of these trees represents the region of interest and the other represents the background. Finally, the segmentation given by the two trees is visualized. The proposed method was tested by segmenting two different 2D brain T1-weighted magnetic resonance image data sets. The comparison between our results and the standard gold segmentation confirmed the validity of the minimum spanning tree approach. The proposed method is simple to implement and the results indicate that it is accurate and efficient.

Keywords: brain tumor, brain tumor segmentation, minimum spanning tree, segmentation, image processing

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Authors: Shelly Sharma, Pooja Chadha

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Humans are exposed to pesticides and insecticides either directly or indirectly. Exposure to these pesticides may lead to acute toxicity to mammals and non-target organisms. Chlorpyrifos (CPF) is a broad spectrum organophosphate pesticide widely used in various countries of the world. The aim of the present study was to assess the toxicity associated with chlorpyrifos exposure and possible mitigating effect of cow urine against genotoxic and toxic effects in rat brain induced by chlorpyrifos. For this purpose LD50 was determined and rats were orally administered with 1/8th of LD50 (19mg/kg b.wt). Brain samples were taken after 24hrs, 48hrs and 72hrs of treatment. A significant increase in the % tail DNA was observed along with the increase in MDA levels of brain tissues in chlorpyrifos treated groups as compared to control. Cow urine treated groups show decrease in DNA damage and MDA levels as compared to CPF treated group. The study indicates that cow urine has ameliorative potential against neurotoxicity and genotoxicity induced by CPF. Cow urine is considered rich in vitamin A, E and volatile fatty acids which provide antioxidant potential to it. Thus, it can be used as a genoprotective agent.

Keywords: comet assay, brain, cow urine, genotoxicity, toxicity

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Authors: Zahra F. Al-Khateeb, Shenel Shekerzade, Hasna Boumenar, Siân M. Henson, Jordi L. Tremoleda, A. T. Michael-Titus

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Traumatic brain injury (TBI) is the leading cause of disability and death in young adults and also increases the risk ofneurodegeneration. The mechanisms linking moderate to severe TBI to neurodegeneration are not known. It has been proposed that cellular senescence inductionpost-injury could amplify neuroinflammation and induce long-term changes. The impact of these processes after injury to an immature brain has not been characterised yet. We carried out a controlled cortical impact injury (CCI) in juvenile 1 month-old male CD1 mice. Animals were anesthetised and received a unilateral CCI injury. The sham group received anaesthesia and had a craniotomy. A naïve group had no intervention. The brain tissue was analysed at 5 days and 35 days post-injury using immunohistochemistry and markers for microglia, astrocytes, and senescence. Compared tonaïve animals, injured mice showed an increased microglial and astrocytic reaction early post-injury, as reflected in Iba1 and GFAP markers, respectively; the GFAP increase persisted in the later phase. The senescence analysis showed a significant increase inγH2AX-53BP1 nuclear foci, 8-oxoguanine, p19ARF, p16INK4a, and p53 expression in naïve vs. sham groups and naïve vs. CCI groups, at 5 dpi. At 35 days, the difference was no longer statistically significant in all markers. The injury induced a decrease p21 expression vs. the naïve group, at 35 dpi. These results indicate the induction of a complex senescence response after immature brain injury. Some changes occur early and may reflect the activation/proliferation of non-neuronal cells post-injury that had been hindered, whereas changes such as p21 downregulation may reflect a delayed response and pro-repair processes.

Keywords: cellular senescence, traumatic brain injury, brain injury, controlled cortical impact

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Authors: Harry G. Segal

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The idea of the “self” has been essential ever since the early modern period in western culture, especially since the development of psychotherapy, but advances in neuroscience and cognitive theory challenge traditional notions of the self. More specifically, neuroanatomists have found no location of “the self” in the brain; instead, consciousness has been posited to be a rapid combination of perception, memory, anticipation of future events, and judgment. In this paper, a theoretical model is presented to address these neuroanatomical findings and to revise the historical understanding of “selfhood” in the practice of psychotherapy.

Keywords: the self, psychotherapy, the self and the brain

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Authors: Faris Tarlochan, Siva Mahesh Tangutooru

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Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies, each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 µm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral Geniculate Nucleus, visual cortex, finite element, glaucoma, neuroprostheses

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Authors: Yung-Chih Kuo, I-Hsuan Lee

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Solid lipid nanoparticles (SLNs) conjugated with aprotinin (Apr) and melanotransferrin antibody (Anti-MTf) were used to carry doxorubicin (Dox) across the blood–brain barrier (BBB) for glioblastoma multiforme (GBM) chemotherapy. Dox-entrapped SLNs with grafted Apr and Anti-MTf (Apr-Anti-MTf-Dox-SLNs) were applied to a cultured monolayer comprising human brain-microvascular endothelial cells (HBMECs) with regulation of human astrocyte (HAs) and to a proliferated colony of U87MG cells. Based on the average particle diameter, zeta potential, entrapping efficiency of Dox, and grafting efficiency of Apr and Anti-MTf, we found that 40% (w/w) 1,2-dipalmitoyl-sn-glycero-3-phosphocholine in lipids were appropriate for fabricating Apr-Anti-MTf-Dox-SLNs. In addition, Apr-Anti-MTf-Dox-SLNs could prevent Dox from fast dissolution and did not induce a serious cytotoxicity to HBMECs and HAs when compared with free Dox. Moreover, the treatments with Apr-Anti-MTf-Dox-SLNs enhanced the ability of Dox to infuse the BBB and to inhibit the growth of GBM. The current Apr-Anti-MTf-Dox-SLNs can be a promising pharmacotherapeutic preparation to penetrate the BBB for malignant brain tumor treatment.

Keywords: solid lipid nanoparticle, glioblastoma multiforme, blood–brain barrier, doxorubicin

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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

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It is important to know 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 administration of 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 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 grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in 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

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Authors: Asmaa Tahiri, Mouktafi Amine

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A substantial number of traditional medical research has been put forward to managing and treating mental disorders. At the present time, to our best knowledge, it is believed that fundamental understanding of the underlying causes of the majority psychological disorders needs to be explored further to inform early diagnosis, managing symptoms and treatment. The emerging field of evolutionary psychology is a promising prospect to address the origin of mental disorders, potentially leading to more effective treatments. Schizophrenia as a topical mental disorder has been linked to the evolutionary adaptation of the human brain represented in the brain connectivity and asymmetry directly linked to humans higher brain cognition in contrast to other primates being our direct living representation of the structure and connectivity of our earliest common African ancestors. As proposed in the evolutionary psychology scientific literature the pathophysiology of schizophrenia is expressed and directly linked to altered connectivity between the Hippocampal Formation (HF) and Dorsolateral Prefrontal Cortex (DLPFC). This research paper presents the results of the use of tractography analysis using multiple open access Diffusion Weighted Imaging (DWI) datasets of healthy subjects, schizophrenia-affected subjects and primates to illustrate the relevance of the aforementioned brain regions connectivity and the underlying evolutionary changes in the human brain. Deterministic fiber tracking and streamline analysis were used to generate connectivity matrices from the DWI datasets overlaid to compute distances and highlight disconnectivity patterns in conjunction with other fiber tracking metrics; Fractional Anisotropy (FA), Mean Diffusivity (MD) and Radial Diffusivity (RD).

Keywords: tractography, evolutionary psychology, schizophrenia, brain connectivity

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Authors: Karima Merchant

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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

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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

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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

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

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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

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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

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Authors: Nirupama Dixit, Anyaa Mittal, Neeru Sood

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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

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