scholarly journals Neurolinguistics: Structure, Function, and Connectivity in the Bilingual Brain

2016 ◽  
Vol 2016 ◽  
pp. 1-22 ◽  
Author(s):  
Becky Wong ◽  
Bin Yin ◽  
Beth O’Brien
Keyword(s):  
Neural Network ◽  
Language Processing ◽  
Developmental Psychology ◽  
Theoretical Models ◽  
Future Research ◽  
Universal Language ◽  
And Function ◽  
The Impact ◽  
The Brain ◽  
Neuroimaging Techniques

Advances in neuroimaging techniques and analytic methods have led to a proliferation of studies investigating the impact of bilingualism on the cognitive and brain systems in humans. Lately, these findings have attracted much interest and debate in the field, leading to a number of recent commentaries and reviews. Here, we contribute to the ongoing discussion by compiling and interpreting the plethora of findings that relate to the structural, functional, and connective changes in the brain that ensue from bilingualism. In doing so, we integrate theoretical models and empirical findings from linguistics, cognitive/developmental psychology, and neuroscience to examine the following issues: (1) whether the language neural network is different for first (dominant) versus second (nondominant) language processing; (2) the effects of bilinguals’ executive functioning on the structure and function of the “universal” language neural network; (3) the differential effects of bilingualism on phonological, lexical-semantic, and syntactic aspects of language processing on the brain; and (4) the effects of age of acquisition and proficiency of the user’s second language in the bilingual brain, and how these have implications for future research in neurolinguistics.

scholarly journals Normative range parenting and the developing brain: a scoping review of the literature

2019 ◽  
Author(s):  
Madeline Farber ◽  
Dylan Gee ◽  
Ahmad R. Hariri
Keyword(s):  
Mental Health ◽  
Brain Development ◽  
Scoping Review ◽  
Developmental Trajectories ◽  
Future Research ◽  
Risk And Resilience ◽  
Abuse And Neglect ◽  
Brain Structure And Function ◽  
And Function ◽  
The Impact

Studies of early adversity such as trauma, abuse, and neglect highlight the critical importance of quality caregiving in brain development and mental health. However, the impact of normative range variability in caregiving on such biobehavioral processes remains poorly understood. Thus, we lack an essential foundation for understanding broader, population-representative developmental mechanisms of risk and resilience. Here, we conduct a scoping review of the extant literature centered on the question, “Is variability in normative range parenting associated with variability in brain structure and function?” After removing duplicates and screening by title, abstract, and full-text, 23 records were included in a qualitative review. The most striking outcome of this review was not only how few studies have explored associations between brain development and normative range parenting, but also how little methodological consistency exists across published studies. In light of these limitations, we propose recommendations for future research on normative range parenting and brain development. In doing so, we hope to facilitate evidence-based research that will help inform policies and practices that yield optimal developmental trajectories and mental health.

Research on capital structure determinants: a review and future directions

2017 ◽  
Vol 13 (2) ◽  
pp. 106-132 ◽  
Author(s):  
Satish Kumar ◽  
Sisira Colombage ◽  
Purnima Rao
Keyword(s):  
Capital Structure ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Secondary Data ◽  
Theoretical Models ◽  
Order Theory ◽  
Organizational Level ◽  
Future Research ◽  
Content Type ◽  
The Impact

Purpose The purpose of this paper is to study the status of studies on capital structure determinants in the past 40 years. This paper highlights the major gaps in the literature on determinants of capital structure and also aims to raise specific questions for future research. Design/methodology/approach The prominence of research is assessed by studying the year of publication and region, level of economic development, firm size, data collection methods, data analysis techniques and theoretical models of capital structure from the selected papers. The review is based on 167 papers published from 1972 to 2013 in various peer-reviewed journals. The relationship of determinants of capital structure is analyzed with the help of meta-analysis. Findings Major findings show an increase of interest in research on determinants of capital structure of the firms located in emerging markets. However, it is observed that these regions are still under-examined which provides more scope for research both empirical and survey-based studies. Majority of research studies are conducted on large-sized firms by using secondary data and regression-based models for the analysis, whereas studies on small-sized firms are very meager. As majority of the research papers are written only at the organizational level, the impact of leverage on various industries is yet to be examined. The review highlights the major determinants of capital structure and their relationship with leverage. It also reveals the dominance of pecking order theory in explaining capital structure of firms theoretically as well as statistically. Originality/value The paper covers a considerable period of time (1972-2013). Among very few review papers on capital structure research, to the best of authors’ knowledge; this is the first review to identify what is missing in the literature on the determinants of capital structure while offering recommendations for future studies. It also synthesize the findings of empirical studies on determinants of capital structure statistically.

An Improved Cross-Domain Sentiment Analysis Based on a Semi-Supervised Convolutional Neural Network

2022 ◽  
pp. 155-170
Author(s):  
Lap-Kei Lee ◽  
Kwok Tai Chui ◽  
Jingjing Wang ◽  
Yin-Chun Fung ◽  
Zhanhui Tan
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Research Work ◽  
Latent Semantic Indexing ◽  
Future Research ◽  
Training Time ◽  
Cross Domain ◽  
Document Frequency

The dependence on Internet in our daily life is ever-growing, which provides opportunity to discover valuable and subjective information using advanced techniques such as natural language processing and artificial intelligence. In this chapter, the research focus is a convolutional neural network for three-class (positive, neutral, and negative) cross-domain sentiment analysis. The model is enhanced in two-fold. First, a similarity label method facilitates the management between the source and target domains to generate more labelled data. Second, term frequency-inverse document frequency (TF-IDF) and latent semantic indexing (LSI) are employed to compute the similarity between source and target domains. Performance evaluation is conducted using three datasets, beauty reviews, toys reviews, and phone reviews. The proposed method enhances the accuracy by 4.3-7.6% and reduces the training time by 50%. The limitations of the research work have been discussed, which serve as the rationales of future research directions.

scholarly journals The impact of language attrition on language teaching: the dynamics of linguistic knowledge retention and maintenance in multilingualism

2019 ◽  
Vol 72 (3) ◽  
pp. 311-330
Author(s):  
Felipe Flores Kupske
Keyword(s):  
Dynamic Model ◽  
Language Processing ◽  
Language Teaching ◽  
Knowledge Retention ◽  
Linguistic Knowledge ◽  
Language Attrition ◽  
Language Retention ◽  
L2 Development ◽  
The Impact ◽  
The Brain

Language attrition has become a vibrant theme as it has implications for theoretical linguistics, including, for example, the organization of linguistic information in the brain and language processing. Insights from this area also have impact on the study of second language (L2) development and can feed the area of language teaching. Once language attrition may be of value for the study of language retention and maintenance, it can contribute to language teaching with long lasting results, more effective planning and syllabus design. In this perspective, as studies exploring L2 attrition are still limited, this article provides a synthesis of research on the area. By drawing from the Dynamic Model of Multilingualism and from the Threshold Hypothesis, it also explores the implications L2 attrition research has for language teaching with a view to establishing more informed language practices and policies.

scholarly journals Analyzing and interpreting neural networks for NLP: A report on the first BlackboxNLP workshop

2019 ◽  
Vol 25 (4) ◽  
pp. 543-557 ◽  
Author(s):  
Afra Alishahi ◽  
Grzegorz Chrupała ◽  
Tal Linzen
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Natural Language Processing ◽  
Language Processing ◽  
Performance Testing ◽  
Network Architectures ◽  
Empirical Methods ◽  
Neural Models ◽  
The Impact ◽  
Systematic Manipulation

AbstractThe Empirical Methods in Natural Language Processing (EMNLP) 2018 workshop BlackboxNLP was dedicated to resources and techniques specifically developed for analyzing and understanding the inner-workings and representations acquired by neural models of language. Approaches included: systematic manipulation of input to neural networks and investigating the impact on their performance, testing whether interpretable knowledge can be decoded from intermediate representations acquired by neural networks, proposing modifications to neural network architectures to make their knowledge state or generated output more explainable, and examining the performance of networks on simplified or formal languages. Here we review a number of representative studies in each category.

scholarly journals Regulatory Roles of Bone in Neurodegenerative Diseases

2020 ◽  
Vol 12 ◽  
Author(s):  
Zhengran Yu ◽  
Zemin Ling ◽  
Lin Lu ◽  
Jin Zhao ◽  
Xiang Chen ◽  
...  
Keyword(s):  
Stem Cells ◽  
Neurodegenerative Diseases ◽  
The Elderly ◽  
Lymphoid Organ ◽  
The Body ◽  
Hematopoietic Stem ◽  
Brain Functions ◽  
And Function ◽  
The Impact ◽  
The Brain

Osteoporosis and neurodegenerative diseases are two kinds of common disorders of the elderly, which often co-occur. Previous studies have shown the skeletal and central nervous systems are closely related to pathophysiology. As the main structural scaffold of the body, the bone is also a reservoir for stem cells, a primary lymphoid organ, and an important endocrine organ. It can interact with the brain through various bone-derived cells, mostly the mesenchymal and hematopoietic stem cells (HSCs). The bone marrow is also a place for generating immune cells, which could greatly influence brain functions. Finally, the proteins secreted by bones (osteokines) also play important roles in the growth and function of the brain. This article reviews the latest research studying the impact of bone-derived cells, bone-controlled immune system, and bone-secreted proteins on the brain, and evaluates how these factors are implicated in the progress of neurodegenerative diseases and their potential use in the diagnosis and treatment of these diseases.

scholarly journals Oxidative stress and genetic markers of suboptimal antioxidant defense in the aging brain: a theoretical review

2014 ◽  
Vol 25 (6) ◽  
Author(s):  
Lauren E. Salminen ◽  
Robert H. Paul
Keyword(s):  
Oxidative Stress ◽  
Antioxidant Defense ◽  
Future Research ◽  
Aging Brain ◽  
Older Individuals ◽  
Glutathione S Transferase ◽  
Antioxidant Defense Enzymes ◽  
Repair Mechanisms ◽  
The Impact ◽  
The Brain

AbstractNormal aging involves a gradual breakdown of physiological processes that leads to a decline in cognitive functions and brain integrity, yet the onset and progression of decline are variable among older individuals. While many biological changes may contribute to this degree of variability, oxidative stress is a key mechanism of the aging process that can cause direct damage to cellular architecture within the brain. Oligodendrocytes are at a high risk for oxidative damage due to their role in myelin maintenance and production and limited repair mechanisms, suggesting that white matter may be particularly vulnerable to oxidative activity. Antioxidant defense enzymes within the brain, such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and glutathione-S-transferase (GST), are crucial for breaking down the harmful end products of oxidative phosphorylation. Previous studies have revealed that allele variations of polymorphisms that encode these antioxidants are associated with abnormalities in SOD, CAT, GPx, and GST activity in the central nervous system. This review will focus on the role of oxidative stress in the aging brain and the impact of decreased antioxidant defense on brain integrity and cognitive function. Directions for future research investigations of antioxidant defense genes will also be discussed.

scholarly journals Multi-Hops Functional Connectivity Improves Individual Prediction of Fusiform Face Activation via a Graph Neural Network

2021 ◽  
Vol 14 ◽  
Author(s):  
Dongya Wu ◽  
Xin Li ◽  
Jun Feng
Keyword(s):  
Neural Network ◽  
Functional Connectivity ◽  
Brain Connectivity ◽  
Face Area ◽  
The Face ◽  
The Individual ◽  
The Right ◽  
And Function ◽  
The Relationship ◽  
The Brain

Brain connectivity plays an important role in determining the brain region’s function. Previous researchers proposed that the brain region’s function is characterized by that region’s input and output connectivity profiles. Following this proposal, numerous studies have investigated the relationship between connectivity and function. However, this proposal only utilizes direct connectivity profiles and thus is deficient in explaining individual differences in the brain region’s function. To overcome this problem, we proposed that a brain region’s function is characterized by that region’s multi-hops connectivity profile. To test this proposal, we used multi-hops functional connectivity to predict the individual face activation of the right fusiform face area (rFFA) via a multi-layer graph neural network and showed that the prediction performance is essentially improved. Results also indicated that the two-layer graph neural network is the best in characterizing rFFA’s face activation and revealed a hierarchical network for the face processing of rFFA.

scholarly journals It may be time to perfect the neuron of artificial neural network

2020 ◽  
Author(s):  
Gang Liu
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Input Data ◽  
Basic Unit ◽  
Future Research ◽  
Brain Neuron ◽  
Artificial Neuron ◽  
The Neural Network ◽  
Artificial Neural ◽  
The Brain

In recent years, artificial neural networks (ANNs) have won numerous contests in pattern recognition, machine learning, and artificial intelligence. The basic unit of an ANN is to mimic neurons in the brain. Neuron in ANNs is expressed as f(wx+b) or f(wx).This structure does not consider the information processing capabilities of dendrites. However, recently, studies shown that dendrites participate in pre-calculation in the brain. Concretely, biological dendrites play a role in the pre-processing to the interaction information of input data. Therefore, it's time to perfect the neuron of the neural network. This paper, add dendrite processing section, presents a novel artificial neuron, according to our previous studies (CR-PNN or Gang transform). The dendrite processing section can be expressed as WA.X. Because I perfected the basic unit of ANNs-neuron, there are so many networks to try, this article gives the basic architecture for reference in future research.

scholarly journals Novel Insight Into the Development and Function of Hypopharyngeal Glands in Honey Bees

2021 ◽  
Vol 11 ◽  
Author(s):  
Saboor Ahmad ◽  
Shahmshad Ahmed Khan ◽  
Khalid Ali Khan ◽  
Jianke Li
Keyword(s):  
Honey Bees ◽  
Future Research ◽  
Factors Affecting ◽  
Hypopharyngeal Glands ◽  
And Function ◽  
First Time ◽  
The Brain ◽  
Insight Into ◽  
Made In

Hypopharyngeal glands (HGs) are the most important organ of hymenopterans which play critical roles for the insect physiology. In honey bees, HGs are paired structures located bilaterally in the head, in front of the brain between compound eyes. Each gland is composed of thousands of secretory units connecting to secretory duct in worker bees. To better understand the recent progress made in understanding the structure and function of these glands, we here review the ontogeny of HGs, and the factors affecting the morphology, physiology, and molecular basis of the functionality of the glands. We also review the morphogenesis of HGs in the pupal and adult stages, and the secretory role of the glands across the ages for the first time. Furthermore, recent transcriptome, proteome, and phosphoproteome analyses have elucidated the potential mechanisms driving the HGs development and functionality. This adds a comprehensive novel knowledge of the development and physiology of HGs in honey bees over time, which may be helpful for future research investigations.

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