scholarly journals MCGNet+: An Improved Motor Imagery Classication Based on Cosine Similarity

2021 ◽  
Author(s):  
Yan Li ◽  
Ning Zhong ◽  
David Taniar ◽  
Haolan Zhang
Keyword(s):  
Motor Imagery ◽  
Adjacency Matrix ◽  
Rapid Development ◽  
Classification Problem ◽  
Cosine Similarity ◽  
The Past ◽  
Current State ◽  
Computational Capability ◽  
Graph Neural Networks ◽  
The Brain

Abstract It has been a challenge for solving the motor imagery classification problem in the brain informatics area. Accuracy and efficiency are the major obstacles for motor imagery analysis in the past decades since the computational capability and algorithmic availability cannot satisfy complex brain signal analysis. In recent years, the rapid development of Machine Learning (ML) methods has empowered people to tackle the motor imagery classification problem with more efficient methods. Among various ML methods, the Graph neural networks(GNNs) method has shown its efficiency and accuracy in dealing with inter-related complex networks. The use of GNN provides new possibilities for feature extraction from brain structure connection. In this paper, we proposed a new model called MCGNet+, which improves the performance of our previous model MutualGraphNet. In this latest model, the mutual information of the input columns forms the initial adjacency matrix for the cosine similarity calculation between columns to generate a new adjacency matrix in each iteration. The dynamic adjacency matrix combined with the spatial temporal graph convolution network(ST-GCN) has better performance than the unchanged matrix model. The experimental results indicate that MCGNet+ is robust enough to learn the interpretable features and outperforms the current state-of-the-art methods.

scholarly journals Multifaceted origins of sex differences in the brain

2016 ◽  
Vol 371 (1688) ◽  
pp. 20150106 ◽  
Author(s):  
Margaret M. McCarthy
Keyword(s):  
Sex Differences ◽  
State Of The Art ◽  
Human Subjects ◽  
Special Issue ◽  
Molecular Analyses ◽  
The Past ◽  
Current State ◽  
Biological Variable ◽  
Males And Females ◽  
The Brain

Studies of sex differences in the brain range from reductionistic cell and molecular analyses in animal models to functional imaging in awake human subjects, with many other levels in between. Interpretations and conclusions about the importance of particular differences often vary with differing levels of analyses and can lead to discord and dissent. In the past two decades, the range of neurobiological, psychological and psychiatric endpoints found to differ between males and females has expanded beyond reproduction into every aspect of the healthy and diseased brain, and thereby demands our attention. A greater understanding of all aspects of neural functioning will only be achieved by incorporating sex as a biological variable. The goal of this review is to highlight the current state of the art of the discipline of sex differences research with an emphasis on the brain and to contextualize the articles appearing in the accompanying special issue.

scholarly journals Unsupervised seizure localisation with attention-based graph neural networks

2020 ◽  
Author(s):  
Daniele Grattarola ◽  
Lorenzo Livi ◽  
Cesare Alippi ◽  
Richard Wennberg ◽  
Taufik Valiante
Keyword(s):  
Neural Networks ◽  
Brain Activity ◽  
Functional Networks ◽  
Seizure Onset ◽  
The Past ◽  
Seizure Onset Zone ◽  
Brain States ◽  
Graph Neural Networks ◽  
Intracranial Electroencephalography ◽  
The Brain

Abstract Graph neural networks (GNNs) and the attention mechanism are two of the most significant advances in artificial intelligence methods over the past few years. The former are neural networks able to process graph-structured data, while the latter learns to selectively focus on those parts of the input that are more relevant for the task at hand. In this paper, we propose a methodology for seizure localisation which combines the two approaches. Our method is composed of several blocks. First, we represent brain states in a compact way by computing functional networks from intracranial electroencephalography recordings, using metrics to quantify the coupling between the activity of different brain areas. Then, we train a GNN to correctly distinguish between functional networks associated with interictal and ictal phases. The GNN is equipped with an attention-based layer which automatically learns to identify those regions of the brain (associated with individual electrodes) that are most important for a correct classification. The localisation of these regions is fully unsupervised, meaning that it does not use any prior information regarding the seizure onset zone. We report results both for human patients and for simulators of brain activity. We show that the regions of interest identified by the GNN strongly correlate with the localisation of the seizure onset zone reported by electroencephalographers. We also show that our GNN exhibits uncertainty on those patients for which the clinical localisation was also unsuccessful, highlighting the robustness of the proposed approach.

scholarly journals Analysis of Neuromorphic Computing Systems and its Applications in Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 5309-5312
Author(s):  
Pranava Bhat
Keyword(s):  
Machine Learning ◽  
Human Brain ◽  
Neural Systems ◽  
Neuromorphic Computing ◽  
Computing Systems ◽  
The Past ◽  
Computational Capability ◽  
Biological World ◽  
Areas Of Interest ◽  
The Brain

The domain of engineering has always taken inspiration from the biological world. Understanding the functionalities of the human brain is one of the key areas of interest over time and has caused many advancements in the field of computing systems. The computational capability per unit power per unit volume of the human brain exceeds the current best supercomputers. Mimicking the physics of computations used by the nervous system and the brain can bring a paradigm shift to the computing systems. The concept of bridging computing and neural systems can be termed as neuromorphic computing and it is bringing revolutionary changes in the computing hardware. Neuromorphic computing systems have seen swift progress in the past decades. Many organizations have introduced a variety of designs, implementation methodologies and prototype chips. This paper discusses the parameters that are considered in the advanced neuromorphic computing systems and the tradeoffs between them. There have been attempts made to make computer models of neurons. Advancements in the hardware implementation are fuelling the applications in the field of machine learning. This paper presents the applications of these modern computing systems in Machine Learning.

scholarly journals Genetic Insights into Alzheimer's Disease

2021 ◽  
Vol 16 (1) ◽  
pp. 351-376
Author(s):  
Caitlin S. Latimer ◽  
Katherine L. Lucot ◽  
C. Dirk Keene ◽  
Brenna Cholerton ◽  
Thomas J. Montine
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Genetic Pathways ◽  
Cognitive Domains ◽  
The Past ◽  
Current State ◽  
Autopsy Examination ◽  
The Brain ◽  
Remarkable Progress

Alzheimer's disease (AD) is a pervasive, relentlessly progressive neurodegenerative disorder that includes both hereditary and sporadic forms linked by common underlying neuropathologic changes and neuropsychological manifestations. While a clinical diagnosis is often made on the basis of initial memory dysfunction that progresses to involve multiple cognitive domains, definitive diagnosis requires autopsy examination of the brain to identify amyloid plaques and neurofibrillary degeneration. Over the past 100 years, there has been remarkable progress in our understanding of the underlying pathophysiologic processes, pathologic changes, and clinical phenotypes of AD, largely because genetic pathways that include but expand beyond amyloid processing have been uncovered. This review discusses the current state of understanding of the genetics of AD with a focus on how these advances are both shaping our understanding of the disease and informing novel avenues and approaches for development of potential therapeutic targets.

scholarly journals Effects of Radiofrequency Electromagnetic Radiation on Neurotransmitters in the Brain

2021 ◽  
Vol 9 ◽  
Author(s):  
Cuicui Hu ◽  
Hongyan Zuo ◽  
Yang Li
Keyword(s):  
Electromagnetic Radiation ◽  
Biological Effects ◽  
Rapid Development ◽  
Pollution Source ◽  
Emotional Behavior ◽  
Electronic Information ◽  
The Past ◽  
Important Target ◽  
The Brain ◽  
Radiofrequency Electromagnetic Radiation

With the rapid development of electronic information in the past 30 years, technical achievements based on electromagnetism have been widely used in various fields pertaining to human production and life. Consequently, electromagnetic radiation (EMR) has become a substantial new pollution source in modern civilization. The biological effects of EMR have attracted considerable attention worldwide. The possible interaction of EMR with human organs, especially the brain, is currently where the most attention is focused. Many studies have shown that the nervous system is an important target organ system sensitive to EMR. In recent years, an increasing number of studies have focused on the neurobiological effects of EMR, including the metabolism and transport of neurotransmitters. As messengers of synaptic transmission, neurotransmitters play critical roles in cognitive and emotional behavior. Here, the effects of EMR on the metabolism and receptors of neurotransmitters in the brain are summarized.

Rationale and Design Considerations for a Semantic Mediator in Health Information Systems

1998 ◽  
Vol 37 (04/05) ◽  
pp. 518-526 ◽  
Author(s):  
D. Sauquet ◽  
M.-C. Jaulent ◽  
E. Zapletal ◽  
M. Lavril ◽  
P. Degoulet
Keyword(s):  
Information Systems ◽  
Software Engineering ◽  
Health Information ◽  
Rapid Development ◽  
Heterogeneous Systems ◽  
Health Information Systems ◽  
Semantic Interoperability ◽  
Point Of View ◽  
Current State ◽  
Engineering Environment

AbstractRapid development of community health information networks raises the issue of semantic interoperability between distributed and heterogeneous systems. Indeed, operational health information systems originate from heterogeneous teams of independent developers and have to cooperate in order to exchange data and services. A good cooperation is based on a good understanding of the messages exchanged between the systems. The main issue of semantic interoperability is to ensure that the exchange is not only possible but also meaningful. The main objective of this paper is to analyze semantic interoperability from a software engineering point of view. It describes the principles for the design of a semantic mediator (SM) in the framework of a distributed object manager (DOM). The mediator is itself a component that should allow the exchange of messages independently of languages and platforms. The functional architecture of such a SM is detailed. These principles have been partly applied in the context of the HEllOS object-oriented software engineering environment. The resulting service components are presented with their current state of achievement.

Current state and main directions of preservation and strengthening of health of the working population of Russia

2020 ◽  
pp. 527-532 ◽  
Author(s):  
I. V. Bukhtiyarov
Keyword(s):  
Working Conditions ◽  
Russian Federation ◽  
Production Environment ◽  
Working Population ◽  
Industrial Enterprises ◽  
The Past ◽  
Production Factors ◽  
Current State ◽  
The Russian Federation

The article presents the results of the analysis of health, working conditions and prevalence of adverse production factors, the structure of the detected occupational pathology in the working population of the Russian Federation. The article presents Statistical data on the dynamics of the share of workplaces of industrial enterprises that do not meet hygienic standards, occupational morbidity in 2015-2018 for the main groups of adverse factors of the production environment and the labor process. The indicators of occupational morbidity over the past 6 years in the context of the main types of economic activity, individual subjects of the Russian Federation, classes of working conditions, levels of specialized occupational health care. The role of the research Institute of occupational pathology and occupational pathology centers in solving organizational, methodological and practical tasks for the detection, treatment, rehabilitation and prevention of occupational diseases is shown. The basic directions of activity in the field of preservation and strengthening of health of workers, and also safety at a workplace are defined.

From many to one: Meditation and the plasticity of the predictive mind

2020 ◽  
Author(s):  
Ruben Laukkonen ◽  
Heleen A Slagter
Keyword(s):  
Cognitive Enhancement ◽  
The Self ◽  
Predictive Processing ◽  
Focused Attention ◽  
Conceptual Processing ◽  
Current State ◽  
Contemplative Science ◽  
Open Monitoring ◽  
Living Organisms ◽  
The Brain

How profoundly can humans change their own minds? In this paper we offer a unifying account of meditation under the predictive processing view of living organisms. We start from relatively simple axioms. First, the brain is an organ that serves to predict based on past experience, both phylogenetic and ontogenetic. Second, meditation serves to bring one closer to the here and now by disengaging from anticipatory processes. We propose that practicing meditation therefore gradually reduces predictive processing, in particular counterfactual cognition—the tendency to construct abstract and temporally deep representations—until all conceptual processing falls away. Our Many- to-One account also places three main styles of meditation (focused attention, open monitoring, and non-dual meditation) on a single continuum, where each technique progressively relinquishes increasingly engrained habits of prediction, including the self. This deconstruction can also make the above processes available to introspection, permitting certain insights into one’s mind. Our review suggests that our framework is consistent with the current state of empirical and (neuro)phenomenological evidence in contemplative science, and is ultimately illuminating about the plasticity of the predictive mind. It also serves to highlight that contemplative science can fruitfully go beyond cognitive enhancement, attention, and emotion regulation, to its more traditional goal of removing past conditioning and creating conditions for potentially profound insights. Experimental rigor, neurophenomenology, and no-report paradigms combined with neuroimaging are needed to further our understanding of how different styles of meditation affect predictive processing and the self, and the plasticity of the predictive mind more generally.

Neuro-Clinical Signatures of Language Impairments: A Theoretical Framework for Function-to-structure Mapping in Clinics

2020 ◽  
Vol 20 (9) ◽  
pp. 800-811 ◽  
Author(s):  
Ferath Kherif ◽  
Sandrine Muller
Keyword(s):  
Brain Mapping ◽  
Theoretical Framework ◽  
Brain Regions ◽  
Language Impairments ◽  
Structure Mapping ◽  
Language Functions ◽  
The Past ◽  
Language Recovery ◽  
The Brain ◽  
Bow Tie

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.

Phytochemical and Pharmacological Review on Two Herbs of Baijiangcao: Patrinia scabiosaefolia Fisch. ex Trev. and Patrinia villosa (Thunb.) Juss

2020 ◽  
Vol 17 (5) ◽  
pp. 496-517
Author(s):  
Yangcheng Liu ◽  
Wei Liu ◽  
Jiaqi Wang ◽  
Yang Liu ◽  
Changlan Chen ◽  
...  
Keyword(s):  
Chemical Constituents ◽  
Volatile Components ◽  
Research Papers ◽  
Pharmacological Activities ◽  
Comprehensive Review ◽  
Scientific Databases ◽  
The Past ◽  
Current State ◽  
Patrinia Scabiosaefolia ◽  
Antiviral Activities

Patrinia scabiosaefolia Fisch. Trev. and Patrinia villosa (Thunb.) Juss, are two species of Patrinia recorded in the Chinese Pharmacopoeia with the same Chinese name “Baijiangcao” and similar therapeutic effect in traditional Chinese medicine. The present article is the first comprehensive review on the chemical composition and pharmacological activities of these herbs. In this review, data on chemical constituents and pharmacological profile of the two herbs are provided. This review discusses all the classes of the 223 compounds (phenylpropanoids, flavonoids, terpenes, saponins and volatile components, etc.) detected in the two herbs providing information on the current state of knowledge of the phytochemicals present in them. In the past three years, our research group has isolated and identified about more than 100 ingredients from the two herbs. Therefore, we published a systematic review of our research papers and studies on the two herbs were carried out using resources such as classic books about Chinese herbal medicine and scientific databases including Pubmed, Web of Science, SciFinder, CNKI. etc. The present review discusses the most thoroughly studied pharmacological activities (antioxidant, anti-inflammatory, immunomodulatory, antimicrobial, antitumor and antiviral activities) of the two herbs. This comprehensive review will be informative for scientists searching for new properties of these herbs and will be important and significant for the discovery of bioactive compounds from the two herbs and in complete utilization of Patrinia scabiosaefolia Fisch. ex Trev. and Patrinia villosa (Thunb.) Juss.

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