Computational Models of Anxiety: Nascent Efforts and Future Directions

2019 ◽  
Vol 28 (2) ◽  
pp. 170-176 ◽  
Author(s):  
Paul B. Sharp ◽  
Eran Eldar
Keyword(s):  
Present Article ◽  
Clinical Psychology ◽  
Computational Models ◽  
Future Directions ◽  
Computational Approaches ◽  
Psychological Phenomena ◽  
The Mind

Computational approaches to understanding the algorithms of the mind are just beginning to pervade the field of clinical psychology. In the present article, we seek to explain in simple terms why this approach is indispensable to pursuing explanations of psychological phenomena broadly, and we review nascent efforts to use this lens to understand anxiety. We conclude with future directions that will be required to advance algorithmic accounts of anxiety. Ultimately, the surplus explanatory value of computational models of anxiety, above and beyond existing neurobiological models of anxiety, impugns the naively reductionist claim that neurobiological models are sufficient to explain anxiety.

scholarly journals Mechanistic Science: A New Approach to Comprehensive Psychopathology Research That Relates Psychological and Biological Phenomena

2019 ◽  
Vol 7 (2) ◽  
pp. 196-215 ◽  
Author(s):  
Joel G. Thomas ◽  
Paul B. Sharp
Keyword(s):  
Recent Work ◽  
Present Article ◽  
Computational Models ◽  
Reward Processing ◽  
Personality Pathology ◽  
New Approach ◽  
Psychological Constructs ◽  
Psychological Phenomena ◽  
Biological Phenomena ◽  
Mechanistic Approach

Efforts to understand the causes of psychopathology have remained stifled in part because current practices do not clearly describe how psychological constructs differ from biological phenomena and how to integrate them in unified explanations. The present article extends recent work in philosophy of science by proposing a framework called mechanistic science as a promising way forward. This approach maintains that integrating psychological and biological phenomena involves demonstrating how psychological functions are implemented in biological structures. Successful early attempts to advance mechanistic explanations of psychological phenomena are reviewed, and lessons are derived to show how the framework can be applied to a range of clinical psychological phenomena, including gene by environment findings, computational models of reward processing in schizophrenia, and self-related processes in personality pathology. Pursuing a mechanistic approach can ultimately facilitate more productive and successful collaborations across a range of disciplines.

scholarly journals Mechanistic science: A new approach to comprehensive psychopathology research that relates psychological and biological phenomena

2018 ◽  
Author(s):  
Joel G. Thomas ◽  
Paul B. Sharp
Keyword(s):  
Recent Work ◽  
Present Article ◽  
Computational Models ◽  
Reward Processing ◽  
Personality Pathology ◽  
New Approach ◽  
Psychological Constructs ◽  
Psychological Phenomena ◽  
Biological Phenomena ◽  
Mechanistic Approach

Efforts to understand the causes of psychopathology have remained stifled in part because current practices do not clearly describe how psychological constructs differ from biological phenomena and how to integrate them in unified explanations. The present article extends recent work in philosophy of science by proposing a framework called mechanistic science as a promising way forward. This approach maintains that integrating psychological and biological phenomena involves demonstrating how psychological functions are implemented in biological structures. Successful early attempts to advance mechanistic explanations of psychological phenomena are reviewed, and lessons are derived to show how the framework can be applied to a range of clinical psychological phenomena including gene by environment findings, computational models of reward processing in schizophrenia, and self-related processes in personality pathology. Pursuing a mechanistic approach can ultimately facilitate more productive and successful collaborations across a range of disciplines.

scholarly journals Reconsidering a role for attachment in eating disorder management in the context of paediatric diabetes

2021 ◽  
pp. 135910452098621
Author(s):  
Rosie Oldham-Cooper ◽  
Claire Semple ◽  
Laura L. Wilkinson
Keyword(s):  
Disordered Eating ◽  
Holistic Care ◽  
Stable Set ◽  
Future Directions ◽  
Paediatric Diabetes ◽  
Attachment Orientation ◽  
Mind And Body ◽  
The Mind ◽  
The Relationship

We suggest a reconsideration of the role of ‘attachment orientation’ in the context of eating disorders and paediatric diabetes. Attachment orientation is a psychological construct that describes a relatively stable set of expectations and behaviours an individual relies upon in managing relationships. There is considerable evidence of an association between attachment orientation and the development and maintenance of disordered eating in individuals without diabetes, though evidence is more scant in populations with diabetes. We discuss the underpinning theory and critically examine the existing literature for the relationship between attachment orientation and disordered eating in paediatric diabetes. Finally, we draw on adjacent literatures to highlight potential future directions for research should this area be revisited. Overall, we contextualise our discussion in terms of patient-centred, holistic care that addresses the mind and body (i.e., our discussion of attachment orientation assumes a psycho-biological approach).

scholarly journals Structure Determination of Microtubules and Pili: Past, Present, and Future Directions

2022 ◽  
Vol 8 ◽  
Author(s):  
James A. Garnett ◽  
Joseph Atherton
Keyword(s):  
Ex Vivo ◽  
Structural Heterogeneity ◽  
Resonance Spectroscopy ◽  
Future Directions ◽  
Computational Approaches ◽  
The Past ◽  
Major Shift ◽  
Technical Innovations

Historically proteins that form highly polymeric and filamentous assemblies have been notoriously difficult to study using high resolution structural techniques. This has been due to several factors that include structural heterogeneity, their large molecular mass, and available yields. However, over the past decade we are now seeing a major shift towards atomic resolution insight and the study of more complex heterogenous samples and in situ/ex vivo examination of multi-subunit complexes. Although supported by developments in solid state nuclear magnetic resonance spectroscopy (ssNMR) and computational approaches, this has primarily been due to advances in cryogenic electron microscopy (cryo-EM). The study of eukaryotic microtubules and bacterial pili are good examples, and in this review, we will give an overview of the technical innovations that have enabled this transition and highlight the advancements that have been made for these two systems. Looking to the future we will also describe systems that remain difficult to study and where further technical breakthroughs are required.

scholarly journals Chapter 9 - Theory of Mind and Joint Attention - The Handbook on Socially Interactive Agents

2021 ◽  
Author(s):  
Jairo Pérez-Osorio ◽  
Eva Wiese ◽  
Agnieszka Wykowska
Keyword(s):  
Theory Of Mind ◽  
Joint Attention ◽  
Cognitive Neuroscience ◽  
Computational Models ◽  
Social Cognitive ◽  
Virtual Agents ◽  
Artificial Agents ◽  
Future Directions ◽  
Social Cognitive Neuroscience ◽  
Intelligent Virtual Agents

The present chapter provides an overview from the perspective of social cognitive neuroscience (SCN) regarding theory of mind (ToM) and joint attention (JA) as crucial mechanisms of social cognition and discusses how these mechanisms have been investigated in social interaction with artificial agents. In the final sections, the chapter reviews computational models of ToM and JA in social robots (SRs) and intelligent virtual agents (IVAs) and discusses the current challenges and future directions.

Role of Genetic Interactions in Lung Diseases Detection using Computational Approaches: A Review

2021 ◽  
Vol 01 ◽  
Author(s):  
S Priya ◽  
R Manavalan
Keyword(s):  
Lung Cancer ◽  
Lung Diseases ◽  
Computational Models ◽  
Association Studies ◽  
Genetic Interactions ◽  
Genome Wide Association Studies ◽  
Computational Approaches ◽  
Genome Wide ◽  
Human Disorders ◽  
Brca1 Brca2

: Genome-wide Association Studies (GWAS) give special insight into genetic differences and environmental influences that are part of different human disorders and provide prognostic help to increase the survival of patients. Lung diseases such as lung cancer, asthma, and tuberculosis are detected by analyzing Single Nucleotide Polymorphism (SNP) genetic variations. The key causes of lung-related diseases are genetic factors, environmental and social behaviors. The epistasis effects act as a blueprint for the researchers to observe the genetic variation associated with lung diseases. The manual examination of the enormous genetic interactions is complicated to detect the lungs syndromes for diagnosis of acute respiratory. Due to its importance, several computational approaches have been modeled to infer epistasis effects. This article includes a comprehensive and multifaceted review of all relevant genetic studies published between 2006 and 2020. In this critical review, various computational approaches are extensively discussed in detecting respondent Epistasis effects for various lung diseases such as Asthma, Tuberculosis, lung cancer, and Nicotine drug dependence. The analysis shows that different computational models identified candidate genes such as CHRNA4, CHRNB2, BDNF, TAS2R16, TAS2R38, BRCA1, BRCA2, RAD21, IL4Ra, IL-13 and IL-1β, have important causes for genetic variants linked to pulmonary disease. These computational approaches' strengths and limitations are described. The issues behind the computational methods while identifying the lung diseases through epistasis effects and the parameters used by various researchers for their evaluation are presented.

Call for Pragmatic Computational Psychiatry

2016 ◽  
Author(s):  
Martin P. Paulus ◽  
Crane Huang ◽  
Katia M. Harlé
Keyword(s):  
Risk Prediction ◽  
Psychiatric Patient ◽  
Biological Psychiatry ◽  
Biological Parameters ◽  
Pragmatic Approach ◽  
Future Directions ◽  
Computational Approaches ◽  
Computational Psychiatry ◽  
Intense Research

Biological psychiatry is at an impasse. Despite several decades of intense research, few, if any, biological parameters have contributed to a significant improvement in the life of a psychiatric patient. It is argued that this impasse may be a consequence of an obsessive focus on mechanisms. Alternatively, a risk prediction framework provides a more pragmatic approach, because it aims to develop tests and measures which generate clinically useful information. Computational approaches may have an important role to play here. This chapter presents an example of a risk-prediction framework, which shows that computational approaches provide a significant predictive advantage. Future directions and challenges are highlighted.

Computational Intelligence Approaches to Computational Aesthetics

2019 ◽  
pp. 81-92
Author(s):  
Erandi Lakshika ◽  
Michael Barlow
Keyword(s):  
Computational Methods ◽  
Computational Intelligence ◽  
Computational Models ◽  
Automatic Generation ◽  
Classification Problems ◽  
Future Directions ◽  
Simple Classification ◽  
Computational Aesthetics

Computational aesthetics is an area of research that attempts to develop computational methods that can perform human-like aesthetic judgements. Aesthetic judgements are often subjective, and as such, the development of computational models of aesthetics is highly challenging. This chapter summarizes the advancements in the area of computational aesthetics and how computational intelligence techniques are applied in art and aesthetics ranging from simple classification problems to more advanced problems such as automatic generation of art artefacts, stories, and simulations. The chapter concludes by summarizing major challenges that need to be addressed, and future directions that need to be undertaken in order to make significant advancements in the area of computational aesthetics and its applications.

Logic and Abstraction as Capabilities of the Mind

2010 ◽  
pp. 132-148
Author(s):  
David J. Saab ◽  
Uwe V. Riss
Keyword(s):  
Fundamental Difference ◽  
Logical Thinking ◽  
Human Beings ◽  
Analytic Thinking ◽  
General Role ◽  
Computational Approaches ◽  
Input Processing ◽  
The Mind ◽  
Sensus Communis

In this chapter we will investigate the nature of abstraction in detail, its entwinement with logical thinking, and the general role it plays for the mind. We find that non-logical capabilities are not only important for input processing, but also for output processing.  Human beings jointly use analytic and embodied capacities for thinking and acting, where analytic thinking mirrors reflection and logic, and where abstraction is the form in which embodied thinking is revealed to us. We will follow the philosophical analyses of Heidegger and Polanyi to elaborate the fundamental difference between abstraction and logics and how they come together in the mind.  If computational approaches to mind are to be successful, they must be able to recognize meaningful and salient elements of a context and engage in abstraction. Computational minds must be able to imagine and volitionally blend abstractions as a way of recognizing gestalt contexts.  And it must be able to discern the validity of these blendings in ways that, in humans, arise from a sensus communis.

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