scholarly journals NeuMapper: A scalable computational framework for multiscale exploration of the brain’s dynamical organization

2022 ◽  
pp. 1-154
Author(s):  
Caleb Geniesse ◽  
Samir Chowdhury ◽  
Manish Saggar
Keyword(s):  
Data Analysis ◽  
Dimensionality Reduction ◽  
Topological Data Analysis ◽  
Computational Framework ◽  
Individual Level ◽  
Computational Costs ◽  
Neuroimaging Data ◽  
The Individual ◽  
And Behavior ◽  
Human Neuroimaging

Abstract For better translational outcomes researchers and clinicians alike demand novel tools to distil complex neuroimaging data into simple yet behaviorally relevant representations at the single-participant level. Recently, the Mapper approach from topological data analysis (TDA) has been successfully applied on noninvasive human neuroimaging data to characterize the entire dynamical landscape of whole-brain configurations at the individual level without requiring any spatiotemporal averaging at the outset. Despite promising results, initial applications of Mapper to neuroimaging data were constrained by (1) the need for dimensionality reduction, and (2) lack of a biologically grounded heuristic for efficiently exploring the vast parameter space. Here, we present a novel computational framework for Mapper—designed specifically for neuroimaging data—that removes limitations and reduces computational costs associated with dimensionality reduction and parameter exploration. We also introduce new meta-analytic approaches to better anchor Mapper-generated representations to neuroanatomy and behavior. Our new NeuMapper framework was developed and validated using multiple fMRI datasets where participants engaged in continuous multitask experiments that mimic “ongoing” cognition. Looking forward, we hope our framework could help researchers push the boundaries of psychiatric neuroimaging towards generating insights at the single-participant level while scaling across consortium-size datasets.

scholarly journals PARTICIPATIVE MANAGEMENT AS A TOOL TO ENSURE STRATEGIC DEVELOPMENT OF ENTERPRISES

2021 ◽  
Author(s):  
Viktoriia Kyfyak ◽  
Olena Herenda
Keyword(s):  
Managerial Behavior ◽  
Management Decisions ◽  
Strategic Development ◽  
Individual Level ◽  
Healthy Environment ◽  
Advantages And Disadvantages ◽  
Positive Side ◽  
Company Policy ◽  
The Individual ◽  
And Behavior

The main focus of this article is on the correlation between employee involvement in management decisions and the growth of both the organization and employees in all areas. The types of managerial behavior are analyzed, within which the main styles are identified, such as: authoritarian and democratic, as well as the advantages and disadvantages of each of them, their impact on the workforce and behavior. The article reflects the need to involve employees in order to improve performance and a sense of responsibility, and lists not only the positive side of this implementation, but also possible negative changes. Effective communication and involvement of staff in management decisions create a basis for ensuring the effective functioning of the enterprise. Involvement of employees, in this article, is not seen as a goal or tool, as is practiced in many organizations, but as a philosophy of management and leadership on how best in a healthy environment to realize their abilities, grow, improve and succeed in each unit and organization in general. The article discusses the main forms of participatory management: informal and short-term participation of personnel in management decisions, consultative involvement of employees, attraction of employees to ownership, involvement of employees in control and improvement of processes, involvement of personnel in decisions about company policy, participation in the organization's income, participation in profits of the organization, participation in the management of the organization. A distinctive feature of this method from many systems of remuneration for labor activity is that the latter are built on the recognition of the contribution of an employee of a given organization at the individual level. Participatory governance is based on the recognition of interests all personnel being reciprocal. This leads to the fact that there is an integration of these interests, and workers become more interested in the results of their work. Involving employees in the decision-making process not only reduces outsourcing, which saves money, time and offers the company long-term reliable assistance from employees who have knowledge of all the processes and deep needs of the corporation.

scholarly journals Mood State and Behavior Predictions in Social Media through Unstructured Data Analysis

2019 ◽  
pp. 1-9
Author(s):  
Gurpreet Singh Bawa ◽  
Suresh Kumar Sharma ◽  
Kanchan K. Jain
Keyword(s):  
Social Media ◽  
Data Analysis ◽  
Personality Trait ◽  
Mood State ◽  
Dirichlet Distribution ◽  
Probability Model ◽  
Unstructured Data ◽  
Latent Features ◽  
The Individual ◽  
And Behavior

For mood State and Behavior Predictions in Social Media through Unstructured Data Analysis, a new model, Behavior Dirichlet Probability Model (BDPM), which can capture the Behavior and Mood of user on Social media is proposed using Dirichlet distribution. There is a colossal amount of data being generated regularly on social media in the form of text from various channels by individuals in the form of posts, tweets, status, comments, blogs, reviews etc. Most of it belongs to some conversation where real-world individuals discuss, analyze, comment, exchange information. Deriving personality traits from textual data can be useful in observing the underlying attributes of the author’s personality which might explain a lot about their behavior, traits etc. These insights of the individual can be utilized to obtain a clear picture of their personality and accordingly a variety of services, utilities would follow automatically. Using Dirichlet probability distribution, the aim is to estimate the probability of each personality trait (or mood state) for an author and then model the latent features in the text which are not captured by the BDPM. As a result, the study can be helpful in prediction of mood state/personality trait as well as capturing the significance of the latent features apart from the ones present in the taxonomies, which will help in making an improved mood state or personality prediction.

The Development of Pro-Environmentalism in Context

2020 ◽  
pp. 418-439
Author(s):  
M. Kyle Matsuba ◽  
Tobias Krettenauer ◽  
Michael W. Pratt
Keyword(s):  
Identity Formation ◽  
Cultural Context ◽  
Environmental Issues ◽  
Industrialized Countries ◽  
Moral Issues ◽  
Individual Level ◽  
Societal Changes ◽  
The Individual ◽  
Moral Attitudes ◽  
And Behavior

Global warming has become an existential concern for our own and the planet’s future. As developmental psychologists, the authors are interested in pro-environmental behavior at the individual level, believing that the societal changes needed to address this issue require changes at the individual level. In this chapter, the authors frame environmental issues as moral issues to the extent that how people think about, react to, and interact in the environment reflect moral values such as caring. Consequently, the authors explore how people’s moral attitudes, thinking, emotions, and behavior around environmental issues form and change over the course of development. They also investigate how developing experiences with the natural environment can influence its importance to the self and in identity formation. Finally, the authors consider that cultural context matters; that attitudes and behaviors toward the environment and how they develop depend on the culture in which we are raised and that what we currently know about the development of environmentalism in not likely to extend much beyond mainstream cultures in Western, industrialized countries.

Students’ Awareness and Embracement of Soft Skills by Learning and Practicing Teamwork

10.28945/4650 ◽  
2020 ◽  
Vol 19 ◽  
pp. 185-201
Author(s):  
Noa Ragonis ◽  
Orit Hazzan ◽  
Gadi Har-Shai
Keyword(s):  
Data Analysis ◽  
Software Engineering ◽  
Computer Science ◽  
Engineering Students ◽  
Soft Skills ◽  
Project Based Learning ◽  
Future Research ◽  
University Graduates ◽  
Individual Level ◽  
The Individual

Aim/Purpose: This paper presents a study about changes in computer science and software engineering students’ perceptions of their soft skills during their progress through the Computer Science Soft Skills course. Background: Soft skills are often associated with a person’s social, emotional and cognitive capabilities. Soft skills are increasingly sought out and are well recognized by employers alongside standard qualifications. Therefore, high importance is attributed to soft skills in computer science and software engineering education. Methodology: Content analysis was applied to interpret, categorize and code statements from students’ course assignment answers. Data analysis was performed gradually at the three main stages of the course and by the two students’ study populations. Contribution: The paper highlights the variety of (a) soft skills that can be learnt in one course, both on the individual level and on the team level and (b) assignments that can be given to students to increase their awareness and motivation to practice and learn soft skills. Findings: Data analysis revealed the following: (a) five individual soft skills categories, with 95 skills, and five team-related soft skills categories, with 52 skills (in total, the students mentioned 147 soft skills); (b) course assignments and particularly team-based activities elicited student awareness of their individual soft skills, both as strengths and weaknesses; (c) students developed their reflection skills, particularly with respect to team-related soft skills; and (d) significant differences exist between the two groups of students in several categories. Recommendations for Practitioners: It is important to provide undergraduate students with opportunities to integrate soft skills during their training. Establishing a meaningful learning process, such as project-based learning, enables students to apply and develop soft skills when accompanied by reflective thought processes. Recommendation for Researchers: A similar course can be taught and be accompanied by similar analysis of students’ learning outcomes, to examine the influence of local culture on the characteristics of soft skills. Impact on Society: Increased awareness of soft skills in scientists and engineers’ undergraduate education. University graduates who will strengthen their variety of soft skills in their academic training process and will be more meaningful employees in the workplace and in society. Future Research: Our future research aims (a) to explore additional innovative ways to increase students’ learning processes, awareness and practices in relation to soft skills and (b) to research how students’ soft skills are developed during the entire undergraduate studies both on the individual level and the team level.

Breaking the frame: frame disputes of war and peace

2017 ◽  
Vol 61 (3) ◽  
pp. 317-332 ◽  
Author(s):  
Chiara Ruffa ◽  
Ralph Sundberg
Keyword(s):  
Social Movements ◽  
War And Peace ◽  
Negative Effects ◽  
Individual Level ◽  
Organizational Frames ◽  
Policy Relevance ◽  
The Individual ◽  
And Behavior ◽  
The Military ◽  
Frame Disputes

Frames guide the way in which organizations and individuals interpret their surrounding contexts and shape avenues for thought, action, and behavior. This paper tests the individual-level effects of experiencing ‘frame disputes’: the state of holding individual-level frames that are at odds with dominant organizational frames. We hypothesize that on the individual level a frame dispute will be associated with negative effects on outcomes important for an organization’s functioning. The hypothesis is tested using a survey of a battalion of Italian soldiers. Our results demonstrate that, on average, soldiers who experienced frame disputes in that they perceived their mission differently from the dominant organizational frame displayed significantly lower levels of perceived cohesion, performance, and legitimacy. Frame disputes are likely to be widespread phenomena among organizations and social movements, and understanding their effects has theoretical, empirical, and policy relevance beyond the military case under study.

scholarly journals Geometric Data Analysis (GDA) - an alternative approach to the analyses of gender differences

2017 ◽  
pp. 32-46
Author(s):  
Claus D. Hansen
Keyword(s):  
Gender Differences ◽  
Data Analysis ◽  
Quantitative Methods ◽  
Individual Level ◽  
Geometric Data ◽  
The North ◽  
Geometric Data Analysis ◽  
And Gender ◽  
The Individual ◽  
Job Attribute Preferences

The aim of this paper is threefold: First, the criticism of quantitative methods raised by feminist and gender researchers is reiterated and illustrated using gender differences in job attribute preferences as an example. Second, the paper compares this ‘standard quantitative methods’ approach to Geometric Data Analysis (GDA), an approach that e.g. makes use of principal components analysis. I argue that GDA breaks with many of the problematic features of traditional statistics by being multi-dimensional (as opposed to one-dimensional), having a statistical model formulated at the individual level (as opposed to treating individuals as mere ‘residuals’) and visualising the results (as opposed to just presenting the results exclusively in numbers). Third, the empirical analyses from the first part of the paper are then used as an example and analysed again, thereby introducing the basic concepts and principles which comprise GDA. Data used in the paper stem from the study Youth on the margin where a sample of young men and women from the North Denmark Region were asked to fill out a battery of job attribute preferences among other things. This is an important topic because such preferences are widely thought to be closely related to the continuing segregation of the Danish labour market.

scholarly journals Social learning for understanding planning practices at the individual level

2021 ◽  
Vol 5 (S1) ◽  
pp. 284-292
Author(s):  
Bahrudin Bahrudin ◽  
Mahyudin Ritonga ◽  
Andino Maseleno ◽  
Miftachul Huda ◽  
Mohd. Hairy Ibrahim
Keyword(s):  
Social Learning ◽  
Government Policy ◽  
Learning Program ◽  
Individual Level ◽  
Legal Sanction ◽  
The People ◽  
Natural Protection ◽  
The Government ◽  
The Individual ◽  
And Behavior

Learning is a process of getting the knowledge to achieve better change. So people who learn need a process of guidance and direction to change their attitude and behavior to become independent human. In fact, most of people learn through selective observation and remember the behavior of other people in their environment. As has been done by the people who implement social learning program, the people have traditionally had local wisdom in protecting nature from generation to generation. This regulation has come a long way after the enactment of the government policy on natural protection of forest. As in the case of destroying forest, they will be subject to customary legal sanction in the form of fine which must be paid by someone as a form of apology.

scholarly journals Attitudinal Ambivalence

Psychology ◽  
2019 ◽  
Author(s):  
Nicoletta Cavazza ◽  
Vincent Pillaud ◽  
Fabrizio Butera
Keyword(s):  
Interpersonal Relationships ◽  
Individual Level ◽  
Attitudinal Ambivalence ◽  
The Individual ◽  
And Behavior ◽  
Attitudes And Behavior ◽  
The Impact ◽  
The Relationship ◽  
Moderating Role

Research on attitudinal ambivalence started in the early 1970s, forty years after the first wave of research on attitudes. Ambivalent attitudes consist of both positive and negative evaluations of the same object. Early approaches proposed different measurement methods, and ambivalence can now be measured either directly (referred to as “felt ambivalence”) or indirectly (referred to as “potential ambivalence”). Because of its duality, ambivalence has been studied in comparison with univalent attitudes—which consist of either positive or negative evaluations of an object—to uncover their specific features, antecedents, and consequences. Relevant research has focused on identifying the prevalence of ambivalent attitudes, and on whether they could stem from particular personality traits or situations. Researchers have found that ambivalent attitudes seem to be widespread and can be held for a long period of time. Their relationship with behaviors has also been widely studied. At the individual level, ambivalence increases response latency when a choice has to be made, extends information processing, can affect attitude stability, and can even lead to discomfort. At the behavioral level, studies have highlighted the moderating role of attitudinal ambivalence on the relationship between attitudes and behavior. A different field of research focuses on its strength to question whether ambivalence leads to more resistance or susceptibility to persuasion and influence. It appears that ambivalent attitudes are pliable and, depending on the context, can either help individuals to be more adaptive or prevent them from arriving at a satisfying conclusion. The role of ambivalent attitudes in interpersonal relationships and self-presentation also highlight some benefits in holding an ambivalent attitude. This article opens by reviewing general overviews to provide a detailed picture of the current state of research. It then presents early approaches to attitudinal ambivalence, and reviews studies that highlight the moderating role of attitudinal ambivalence on the relationship between attitudes and behavior, as well as studies that question whether ambivalence might lead to more resistance or susceptibility to persuasion and influence. The article then focuses on the impact of ambivalence at the individual level. Antecedents of attitudinal ambivalence will be reviewed, as well as its consequences on the individual. The article concludes by presenting research questioning its functions as well as some applied work.

scholarly journals Topological Data Analysis of C. elegans Locomotion and Behavior

2021 ◽  
Vol 4 ◽  
Author(s):  
Ashleigh Thomas ◽  
Kathleen Bates ◽  
Alex Elchesen ◽  
Iryna Hartsock ◽  
Hang Lu ◽  
...  
Keyword(s):  
Data Analysis ◽  
Persistent Homology ◽  
Model Organism ◽  
Topological Data Analysis ◽  
Trade Off ◽  
High Throughput Data ◽  
C Elegans ◽  
Novel Technique ◽  
And Behavior ◽  
Topological Data

We apply topological data analysis to the behavior of C. elegans, a widely studied model organism in biology. In particular, we use topology to produce a quantitative summary of complex behavior which may be applied to high-throughput data. Our methods allow us to distinguish and classify videos from various environmental conditions and we analyze the trade-off between accuracy and interpretability. Furthermore, we present a novel technique for visualizing the outputs of our analysis in terms of the input. Specifically, we use representative cycles of persistent homology to produce synthetic videos of stereotypical behaviors.

scholarly journals Generating dynamical neuroimaging spatiotemporal representations (DyNeuSR) using topological data analysis

2019 ◽  
Vol 3 (3) ◽  
pp. 763-778 ◽  
Author(s):  
Caleb Geniesse ◽  
Olaf Sporns ◽  
Giovanni Petri ◽  
Manish Saggar
Keyword(s):  
Data Analysis ◽  
Mental Disorders ◽  
Open Source ◽  
Topological Data Analysis ◽  
High Dimensional ◽  
Graphical Representations ◽  
Neuroimaging Data ◽  
Open Datasets ◽  
Topological Data

In this article, we present an open source neuroinformatics platform for exploring, analyzing, and validating distilled graphical representations of high-dimensional neuroimaging data extracted using topological data analysis (TDA). TDA techniques like Mapper have been recently applied to examine the brain’s dynamical organization during ongoing cognition without averaging data in space, in time, or across participants at the outset. Such TDA-based approaches mark an important deviation from standard neuroimaging analyses by distilling complex high-dimensional neuroimaging data into simple—yet neurophysiologically valid and behaviorally relevant—representations that can be interactively explored at the single-participant level. To facilitate wider use of such techniques within neuroimaging and general neuroscience communities, our work provides several tools for visualizing, interacting with, and grounding TDA-generated graphical representations in neurophysiology. Through Python-based Jupyter notebooks and open datasets, we provide a platform to assess and visualize different intermittent stages of Mapper and examine the influence of Mapper parameters on the generated representations. We hope this platform could enable researchers and clinicians alike to explore topological representations of neuroimaging data and generate biological insights underlying complex mental disorders.

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