Antonia Plerou

Innovative research technologies in the neurosciences have remarkably improved the perception of brain structure and function. The use of several neurofeedback training techniques is broadly used for the memory and cognition augmentation as well as for several learning difficulties and AHDD rehabilitation. Author's objective is to review cognitive enhancement techniques with the use of brain imaging intervention methods as well to evaluate the effects of these methods in the educational process. The efficiency and limitations of neurofeedback training with the use of EEG brain imaging, HEG scanning, namely NIR and PIR method and fMRI scan including rt-fMRI brain scanning technique are also discussed. Moreover, technical and clinical details of several neurofeedback treatment approaches were also taken into consideration.

This paper discusses the industry of science that deals with neural networks. He started to give answers to questions about what are neural networks to make their relationship with the brain and to identify some of the problems can be solved with their help. After a brief introduction to cognitive science reported the differences and similarities between computer and human brain. Prompted by the description of the structure of an artificial neuron compared with biological neural networks and provided the description of the model of artificial neuron. At the end of the work mentioned briefly some of the most important applications of neural networks.

This paper is related to the branch of science that deals with artificial neural networks. It is initiated with a view to answer questions about what neural networks is ,to make correlation with the brain and identify some issues that could be arranged with their help. After a short introduction to cognitive science some differences and similarities comparing computer and human brain are mentioned. While the structure of an artificial neuron was described, a comparison to biological neural networks was made and an artificial neuron model description was also provided. Finally some of the most important applications of neural networks were also mentioned.

The primary research question is the identification of common characteristics and symptoms presented by people with dyscalculia and difficulties in applying algorithmic thinking. Algorithmic thinking is called the ability of comprehension, implementation, evaluation and creation of algorithms. A key point of the search are the features that could be observed in people with problems in algorithmic thinking as well as the analysis and evaluation of difficulties related to mathematical and algorithmic thinking.

Although learning disabilities studies is in advanced stage, research related in algorithmic procedures is limited, since interest in this field is recently displayed. This discourse describes some cognitive and algorithmic principles, which rule the development of a software related to dyscalculia. More specifically,this software design is based on principles related to the diagnostic evaluation of dyscalculia . The proposed software is based on the assumption that dyscalculia is noticed due to a lack of understanding of mathematical concepts and aims at understanding the cerebral reproductions of algorithmic procedures. One of the challenges is the analysis and evaluation the difficulties related to algorithmic mathematical thinking. A key point is maping the features of people with problems in algorithmic thinking.

This work deals with the branch of science that deals with neural networks. It begins providing answers to questions about what neural networks do, their association with the brain and to identify some of the problems which can be solved with their help. After a brief introduction to cognitive science reported the differences and similarities between computer and human brain. On the occasion to describe the structure of an artificial neuron was compared with biological neural networks and provided the description of the model of artificial neuron. At the end of the work there is a short reference to the evolution of neural networks and some of its applications.

This work is about the specific disorder of managing mathematical concepts which is known as dyscalculia. Specifically, a correlation between the terms of dyslexia and dyscalculia is given. Furthermore there is a reference about the link between learning difficulties in language and those relating to mathematical logic. The definition of dyscalculia is also given. An important issue of learning difficulties in mathematics is assessment and diagnosis. While evaluating dyscalculia some symptoms of people that display this specificity are mentioned. Finally factors that are likely responsible for this special disorder are analyzed.

This thesis deals with the branch of science about neural networks. Computer and human brain differences and similarities and a brief historical overview are mentioned. Artificial neurons were compared with biological neural networks and some of the applications of neural networks are briefly mentioned. Also a description of an artificial neuron model and the most common functions used for activation were given. Some examples of network architecture are also given. Afterwards there is a reference in accordance to the algorithms which are used to train networks as well as some examples of learning. Moreover we analyze some well-known network models such as Perceptron, Back Propagation and Kohonen networks and Hopfield. Those models are classified according to their training process. We present the learning efficiency as a neural networks‟ training. Due this method network parameters are prescribed in order to improve network performance. We set the conditions in which the minimum poi...

Over the last few years, one major research direction of information retrieval includes user behaviour prediction. For that reason many models have been proposed aiming at the accurate evaluation of information retrieval systems and the best prediction of web search users' behaviour. In this paper we propose a new evaluation metric for information retrieval systems which employs two relevance factors; a relevance judgement grade and a popularity grade that represents users' vote for a document. We show that this new metric performs better than other evaluation metrics when expressing user behaviour. Moreover, in order to test the performance of our metric on different and scalable ranking algorithms, we develop a pairwise text similarity algorithm using cosine similarity, implemented on the MapReduce model, and then perform experiments on rankings generated by the algorithm.

During the last decades the interest about the research of neurocognitive issues within the frame of brain imaging techniques is considerably high. In this paper authors' approach concerns the research and the evaluation of the so-called cognitive disorders within the frame of memory and algorithmic abilities. The exceptionality of calendrical savant's skills, the influence of memory, calculation and algorithmic abilities were analyzed within the frame of cognitive neuroscience and brain imaging techniques. Future directions in order to enhance the theoretical findings concerning memory disorders - specifically by analyzing the brain activity signal within the use of brain imaging techniques are also discussed.

Huntington's disease as a neurodegenerative disease is characterized by motor and cognitive impairment. The disease is caused by the mutation of the gene that produces the huntingtin protein causing the repetition of trinucleotide CAG. The mutant protein reacts with other proteins inside and out of the cell causing problems to its normal function and cell death. Recent advances in the signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method able of providing spatio-temporal information regarding brain (dys)function. Authors aim to review objectively and quantitatively the neurophysiological basis of the disease in HD patients as compared to normal controls, with the use of brain imaging in general and EEG brain imaging methods.

ABSTRACT The evaluation of basic arithmetic algorithms has been until recently the core of mathematical tests in elementary and secondary education. However, it is necessary that students are able to understand, analyze and improve more complex algorithms in order to support further the study of mathematics and science. In this paper, a number of issues concerning algorithmic thinking are explored. In particular, a case study is proposed in order to compare the efficiency of the traditional algorithmic problem solving in relation to problem solving using interactive virtual environment. The findings suggest that when problem solving using interactive interface is used under conditions the results are more efficient comparing to the traditional way of algorithmic problem solving.

During the last decades, the interest displayed in neurocognitive and brain science research is relatively high. In this chapter, the cognitive neuroscience field approach focuses in the aspect of the way that cognitive functions are produced by neural circuits in the brain. Within this frame, the effects of impairment to the brain and subsequent changes in the thought processes due to changes in neural circuitry resulting from the ensued damage are analyzed and evaluated. All cognitive functions result from the integration of many simple processing mechanisms, distributed throughout the brain. Brain cortex structures, linked with cognitive disorders, are located in several parts like the frontal, the parietal, the temporal, the occipital lobe and more are analyzed and specified. A critical topic of this chapter in the evaluation of brain operations is mapping regions that control cognitive and mathematical concepts functions. Dyscalculia, in this chapter, is described as a specific...

Although studies on learning difficulties are in general in advanced stage, research related to algorithmic thinking difficulties is limited, since interest in this field has been recently expressed. Additionally, young people nowadays are familiarized with the use of computer. Therefore, an interactive computer-based diagnostic screener, referring to dyscalculia and algorithmic thinking difficulties, is proposed. In this paper, a number of issues concerning algorithmic thinking are also explored. In particular, an approach of algorithmic thinking definition is given and difficulties in algorithmic thinking features are studied. People facing algorithmic thinking difficulties have common characteristic therefore it would be crucial to discover the way these features could be identified in order to detect people at risk. Precise and analytical conclusions concerning the efficiency of the proposed screener are to be reached upon completion and review of the overall project phases.

The recent years the interest in neurocognitive and brain science research is relatively increased. In this study the relation of DNA and genetic factors that are interrelated to brain development and cognitive functions is analyzed. Author’s main purpose is to localize and analyze the function of the particular parts of brain which are related to specific cognitive functions. Especially the connection of specific brain cortexes with mathematical perception and mathematical learning difficulties also known as dyscalculia is analyzed and evaluated as well. Future directions in order to evaluate and enhance the theoretical outcomes by visualizing the brain activity within the use of brain imaging techniques are also discussed.

The mathematical study of epidemics is essential for a better perception of their evolution and control potential. The typical deterministic mathematical models do not provide subjective modeling of these phenomena. The application of fuzzy set theory in order to model epidemiological problems and overcome this issue is suggested as an efficient predictive procedure for the epidemiology of infectious diseases. Although this is a recent research field, authors objective is to provide a review of the state of the art of fuzzy logic theory implementation in epidemiology. Findings suggest that fuzzy sets implementation in epidemiology is a really promising field of research and specify the future stages of fuzzy sets application in epidemiology.

Empirical evidence and therapeutic interactions have suggested that individuals with Borderline Personality Disorder (BPD) may demonstrate deficits in neuropsychological cognitive and interpersonal aspects. ‘Borderline Personality Disorder’ term refers to a psychiatric syndrome that is characterized by emotion dysregulation, impulsivity, risk-taking behavior, irritability, feelings of emptiness, self-injury, and fear of abandonment, as well as unstable interpersonal relationships. Many typical symptoms of Borderline Personality Disorder occur within interpersonal contexts, suggesting that BPD is characterized by aberrant social cognition. To assess the empirical evidence and evaluate Borderline Personality Disorder impact under social and emotional cognition effect, Borderline Disorder symptoms and etiology perception are strongly involved. Studies concerning behavioral and neural underpinnings of the disorder, cognitive processes that help people to interact effectively with each o...

Neurofeedback video games respond to electrical brain signals instead to a mouse, joystick, or game controller input. These games embody the concept of improving physiological functioning by rewarding specific healthy body signals with success at playing a video game. In this paper, a threefold framework in reference to attention deficit disorder (ADD) and attention deficit hyperactivity disorder (ADHD) treatment blending with neurofeedback techniques and video game implementation is presented. In particular, the specifications of a neurofeedback-based video game for children dealing with ADHD, in order to enhance attention and concentration skills, are analyzed. Potential boundaries of this cognitive enhancement approach and authors future directions are also discussed.

Eight computer science students, novice programmers, who were in the first semester of their studies, participated in a field study in order to explore potential differences in their brain activity during programming with a visual versus a textual programming language. The students were asked to develop two specific programs in both programming languages (a total of four tasks). Measurements of cerebral activity were performed by the electroencephalography (EEG) imaging method. According to data analysis, it appears that the type of programming language did not affect the students' brain activity.

Although several surveys related to dyscalculia have proceeded so far, research seems to fail till now to develop a clear concept map referring to the features of dyscalculia classified according to age. Dyscalculia can be recognized by some specific features that are noticed through all stages of the individual’s development. In this paper a classification of features is proposed, according to individuals’ age as well as several screening methods, in order to ensure efficiency of the screening procedure. Dyscalculia’s features evaluation during different stages of age is crucial since diagnosis is relevant to the age considering that math’s learning difficulties arising in early ages are likely to be remitted since this status is possible to be temporary. An innovative aspect in this work is the citation and analysis of algorithmic thinking difficulties encountering in older ages under the range of learning difficulties in mathematics and dyscalculia.

Nowadays, Alzheimer's disease (AD) diagnosis is considered to be a crucial and extremely complex process. Nevertheless, psychometric tools, like Mini-Mental State Evaluation (MMSE), are used to address cognitive function assessment and clinical evaluation processes. However, MMSE's sensitivity in the diagnosis of mild cognitive impairment is debatable in terms of education, age, or nationality. Typical psychometric tools with the use of "paper and pencil" methods combined with physiology measurements are proposed in order to enhance validity and effectiveness in the case of Alzheimer's disease cognitive deficits. The objective of this review study is to highlight the effectiveness of brief cognitive tests (BCT) in the case of dementia and Alzheimer's disease screening. Authors' future work will focus on the application of BCT in MCI diagnosis and evaluation.

This poster will present results from an EEG study comparing visual and textual programming, carried out on informatics students. We observe brain rhythms as the subjects complete programming tasks using Python and Scratch. The present study belongs in the domain of Neuroeducation/Educational Neuroscience, which is an attempt to join cognitive science and education in order to create a sound grounding of education. Our goal is to gain a better understanding of different types of programming as one of the parameters that can impact professional involvement in software development, so as to help us formulate educational methodologies in software engineering education.

Copyright: © 2019 Bobori C, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 international License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited. Abstract Amnesia or amnestic syndrome is a memory deficiency caused not only by brain damage, several diseases or psychological trauma, but is also noticed as a temporal condition resulted from sedatives and hypnotic drugs use. A significant number of people are suffering from several types of amnesia. Therefore, it is essential to review amnesia several types, to analyze potential causes of the amnestic syndrome as well as to categorize commonly met symptoms. In this study, the authors’ objective is to focus on the case of anterograde amnesia. Specifically, an evaluation and rehabilitation protocol is suggested aiming to improve the memory deficits that amnestic people are dealing with. The use of n...

Fuzzy logic is an innovative scientific field with several successful applications. Genetic algorithms and fuzzy logic systems fusion provide real-world problems modeling through the development of intelligent and adaptive systems. Moreover, the statistical analysis of the epidemiology of infectious diseases, which combines fuzzy logic aspects, is vital for perceiving their evolution and control potential. Author's objective is initially to provide a review of the efficiency of fuzzy logic applications. The advanced implementation of fuzzy logic theory in epidemiology and the application of fuzzy logic for controlling genetic algorithms within strategies based on the human experience and knowledge known as fuzzy logic controllers (FLCs) are analyzed. Outcomes of this review study show that not only can fuzzy sets be efficiently implemented in epidemiology but also prove the effectiveness of fuzzy genetic algorithms applications, thus suggesting that fuzzy logic applications are ...

Drug addiction is a chronic relapsing disorder and a burden to society and individuals. The toxicity induced by drugs related with addiction may trigger dysfunction and death of cells of the central nervous system. The study of alterations of proteins and biomarkers in buccal cells would be beneficial in understanding drug addiction, as the buccal mucosa is of ectodermal origin such as the central nervous system. METHOD Buccal smears of 35 individuals with addictive disorders (20) or substance use disorders (15) for more than 3 years were collected by the gentle brushing of the inside of the cheeks. Immunocytochemical staining of IL-1β, IL-6, TNF-α, NFKβ, bcl-2, and ucp4 was performed on the epithelial cells, for the study of oxidative stress, toxicity, and inflammation. Papanicolaou staining was also performed for the potential structural disorders. There was a correlation with the clinical profile of each individual. None of the individuals was HIV or Tbc positive. RESULTS Cytomor...

Innovative research technologies in the neurosciences have remarkably improved the perception of brain structure and function. The use of several neurofeedback training techniques is broadly used for the memory and cognition augmentation as well as for several learning difficulties and AHDD rehabilitation. Author's objective is to review cognitive enhancement techniques with the use of brain imaging intervention methods as well to evaluate the effects of these methods in the educational process. The efficiency and limitations of neurofeedback training with the use of EEG brain imaging, HEG scanning, namely NIR and PIR method and fMRI scan including rt-fMRI brain scanning technique are also discussed. Moreover, technical and clinical details of several neurofeedback treatment approaches were also taken into consideration.

Nowadays, mobile devices are considered to be a powerful and portable tool for assisting people dealing with daily life issues. With the advance of mobile technology, the issue of mobile learning has been broadly explored in e-learning research. Several researchers and educators use pedagogical and technical strengths of mobile technology into learning environments. In this paper, an educational mobile-based application is described in order to promote Corfu’s Old town cultural heritage. The proposed educational mobile based application was pilot-tested in forty-five postgraduate students at Ionian University during cultural heritage courses. The students used a mobile-based educational environment in order to augment their heritage cultural perception and knowledge. The case study results suggest an enhanced perception of the educational content as well as a significantly increased acceptance of the education approach within the role of mobile technology in higher education.

Although research on learning difficulties are overall in an advanced stage, studies related to algorithmic thinking difficulties are limited, since interest in this field has been recently raised. In this paper, an interactive evaluation screener enhanced with neurofeedback elements, referring to algorithmic tasks solving evaluation, is proposed. The effect of HCI, color, narration and neurofeedback elements effect was evaluated in the case of algorithmic tasks assessment. Results suggest the enhanced performance in the case of neurofeedback trained group in terms of total correct and optimal algorithmic tasks solution. Furthermore, findings suggest that skills, concerning the way that an algorithm is conceived, designed, applied and evaluated are essentially improved.

Although significant advances have been made in understanding several cognitive states, the algorithmic thinking ability is yet to be analyzed in terms of neuroscience and brain imaging techniques. Studies on the effects of neurofeedback on learning disabilities especially mathematics disorders are limited. The objective of the present study is to evaluate the brain activity and activation differences between neurofeedback trained participants and controls, during the overall EEG analysis during continuous algorithmic tasks performance. A study of 182 children of upper education is proposed to assess the efficacy of two protocols of neurofeedback training as means of algorithmic thinking ability evaluation. Results suggest statistical significant variation in the mean SD values in terms of several brain waves ratios during algorithmic task solving epochs.

Psychological therapies in order to provide cognitive enhancement have gained some momentum the last decades. The goal of this case study was to evaluate the effects of a cognitive enhancement training program on daily living activities, cognition, and depression in a demented elderly participant. A 6-month training program was proposed for the participant, whose overall evaluation results suggest significant deficits impairment but whose response rate to the proposed tasks of the treatment was interestingly high. However, additional research is needed to overall evaluate the efficacy of the proposed method to elderly adults.

“Serious games” refer to games that go beyond pure entertainment and promote learning. They are utilized within a variety of learning environments enabling students to acquire knowledge and skills, while they offer wide benefits. The authors' team measured and analyzed various factors related to the gameplay and educational content when 2D and 3D serious games are introduced in the educational process. The main objective focused on the correlation of the University students' views that were sharing common characteristics, like gender, information and communication technology skills, game playing experience, and specific scientific background with factors that related to the gameplay as well as the learning effectiveness. The results revealed that game-playing experience had a more positive impact in the case of males, while perceived learning effectiveness of 2D was higher compared to the 3D serious game for both genders. Moreover, there are differentiations among females concerning the scientific background, Information and Communication Technology skills and game-playing experience.

During ages, new and innovative learning technologies are often criticized or rejected, while their full acceptance is commonly delayed. As a result, the progress of Smart Learning Environments is noticed nowadays to be delayed, while educator debate about the technology used in classroom effectiveness. Author’s objective is to explore potential factors in order to render modern communication devices such as mobile phones and tablets suitable for learning in schools, taking into consideration possible advantages or disadvantages. In the case that students use mobile devices during learning procedure, a shortage of suitable content as well as adequate integration of educational and edutainment systems employing gamification techniques within the school framework. These factors are considered to be sufficient enough to strengthen and improve learning experience and effectiveness.

Huntington’s disease as a neurodegenerative disease is characterized by motor and cognitive impairment. The disease is caused by the mutation of the gene that produces the huntingtin protein causing the repetition of trinucleotide CAG. The mutant protein reacts with other proteins inside and out of the cell causing problems to its normal function and cell death. Recent advances in the signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method able of providing spatio-temporal information regarding brain (dys)function. Authors aim to review objectively and quantitatively the neurophysiological basis of the disease in HD patients as compared to normal controls, with the use of brain imaging in general and EEG brain imaging methods.

During the last decades the interest about the research of neurocognitive issues within the frame of brain imaging techniques is considerably high. In this paper authors’ approach concerns the research and the evaluation of the so-called cognitive disorders within the frame of memory and algorithmic abilities. The exceptionality of calendrical savant’s skills, the influence of memory, calculation and algorithmic abilities were analyzed within the frame of cognitive neuroscience and brain imaging techniques. Future directions in order to enhance the theoretical findings concerning memory disorders – specifically by analyzing the brain activity signal within the use of brain imaging techniques are also discussed.

The fusion of Artificial Neural Networks and Fuzzy Logic Systems allows researchers to model real
world problems through the development of intelligent and adaptive systems. Artificial Neural networks
are able to adapt and learn by adjusting the interconnections between layers while fuzzy logic inference
systems provide a computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and
fuzzy reasoning. The combined use of those adaptive structures is known as “Neuro-Fuzzy” systems. In
this chapter, the basic elements of both approaches are analyzed while neuro-fuzzy networks learning
algorithms are presented. Here, we combine the use of neuro-fuzzy algorithms with multimedia-based
signals for training. Ultimately this process may be employed for automatic identification of patterns
introduced in medical applications and more specifically for analysis of content produced by brain
imaging processes.

During the last decades, the interest displayed in neurocognitive and brain science research is relatively high. In this chapter, the cognitive neuroscience field approach focuses in the aspect of the way that cognitive functions are produced by neural circuits in the brain. Within this frame, the effects of impairment to the brain and subsequent changes in the thought processes due to changes in neural circuitry resulting from the ensued damage are analyzed and evaluated. All cognitive functions result from the integration of many simple processing mechanisms, distributed throughout the brain. Brain cortex structures, linked with cognitive disorders, are located in several parts like the frontal, the parietal, the temporal,
the occipital lobe and more are analyzed and specified. A critical topic of this chapter in the evaluation of brain operations is mapping regions that control cognitive and mathematical concepts functions.
Dyscalculia, in this chapter, is described as a specific disorder of managing and conceiving mathematical concepts. Dyscalculia could be identified by difficulties in visual perception, in spatial number organization, in basic mathematical operations and in mathematical induction logic. Moreover, people who deal with dyscalculia present problems, in Euclidean and Non-Euclidean Geometry concepts perception, in
Calculus aspects as well as in solving algorithmic problems where the design, the description and the application of algorithmic steps are required. In order to enhance cognitive brain functions perception, the use of EEG brain imaging is proposed measuring cerebral activity and event-related potentials. The procedure described in this chapter is about the comparison and contrasts EEG brain imaging patterns
of healthy volunteers to EEG samples taken of adults considered being at risk of mathematics learning disabilities such as Dyscalculia and algorithmic thinking difficulties. EEG interpretation analysis is to follow where the deviation of a normal and an abnormal range of wave’s frequency are defined. Several visualized
EEG patterns in relevance with specific abnormalities are presented while several neurocognitive generated disorders could be identified with the use of EEG Brain-imaging technique. The electroencephalogram EEG brain imaging procedure, in order to evaluate problems associated with brain function, is to be further analyzed in this chapter as well. The EEG is the depiction of the electrical activity occurring at the surface of the brain. The recorded waveforms reflect the cortical electrical
activity and they are generally classified according to their frequency (Delta, Theta, Beta, Alpha, Beta, and Gamma) amplitude, and shape. EEG Implementation with the use of 10/20 system of the standardized position of scalp electrodes placement for a classical EEG recording is described as well.
The EEG implementation objective is to identify, classify and evaluate those frequencies and regions in the brain that best characterize brain activity associated with mathematical learning disabilities. Mapping the brain with non-invasive techniques based on trigger and sensing/evaluation experimental multimedia methods similar to those used in computer games and applications are expected to provide relevant results in order to enhance and confirm theoretical cognitive aspects. At that point, a cognitive and mathematical perception evaluation is to follow and specifically the assessment of the relation of difficulties in mathematics with particular parts of the human brain. EEG wave data visualization is contacted with the use of Acknowledge an interactive, intuitive program which provides data analysis instantly. At the end of this chapter EEG computational evaluation with the use of pattern recognition methods as well as the intuition of author’s future work in relevance with the use of experimental multimedia technologies to enhance the dynamic recognition and evaluation of user cognitive responses during EEG implementation are noted.

The recent years the interest in neurocognitive and brain science research is relatively increased. In this study the relation of DNA and genetic factors that are interrelated to brain development and cognitive functions is analyzed. Author’s main purpose is to localize and analyze the function of the particular parts of brain which are related to specific cognitive functions. Especially the connection of specific brain cortexes with mathematical perception and mathematical learning difficulties also known as dyscalculia is analyzed and evaluated as well. Future directions in order to evaluate and enhance the theoretical outcomes by visualizing the brain activity within the use of brain imaging techniques are also discussed.