Article
Psychology, Multidisciplinary
David Harris Smith, Guido Schillaci
Summary: Creativity is essential in both Humanities and STEM disciplines, but differs in motivations and constraints. Artists and engineers have distinct goals and approaches in their creative endeavors.
FRONTIERS IN PSYCHOLOGY
(2021)
Editorial Material
Computer Science, Artificial Intelligence
Zhong Li, Herwig Unger, Kyandoghere Kyamakya
Summary: This special issue focuses on the explainability of machine learning in methodologies and applications, an urgent question to be addressed, especially in light of the significant success of artificial intelligence applications in diverse fields.
KNOWLEDGE-BASED SYSTEMS
(2023)
Review
Multidisciplinary Sciences
Joel Serey, Luis Quezada, Miguel Alfaro, Guillermo Fuertes, Manuel Vargas, Rodrigo Ternero, Jorge Sabattin, Claudia Duran, Sebastian Gutierrez
Summary: This study evaluates the main challenges, trends, technological approaches, and artificial intelligence methods developed by new researchers and professionals in the field of machine learning through a literature review. The research finds that artificial intelligence methods, such as artificial neural networks, Support Vector Machines, K-means, and Bayesian Methods, exhibit symmetry and are widely used in data management.
Review
Health Care Sciences & Services
Ruopeng An, Jing Shen, Yunyu Xiao
Summary: This scoping review provides an overview of the applications of artificial intelligence (AI) in obesity research, with a focus on machine learning (ML) and deep learning (DL) models applied to tabular, image, and text data. The review identifies the usefulness of AI models in detecting meaningful patterns and relationships related to obesity outcomes. Additionally, it discusses the increasing trend of adopting state-of-the-art DL models for challenging tasks in computer vision and natural language processing.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
History & Philosophy Of Science
Carmelo Cali
Summary: This paper discusses the relationship between phenomenology of perception and synthetic phenomenology. It argues that phenomenology of perception makes a contribution to synthetic phenomenology and explores two attempts at specifying the phenomenal content of artificial agents.
FOUNDATIONS OF SCIENCE
(2023)
Article
Multidisciplinary Sciences
Lenore Blum, Manuel Blum
Summary: This paper examines consciousness from the perspective of theoretical computer science and proposes a Conscious Turing Machine (CTM) model. Influenced by the Turing machine and the global workspace theory, the model considers phenomena associated with consciousness and draws explanations that align with cognitive neuroscience literature.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Review
Neurosciences
Violetta Molokopoy, Amedeo D'Angiulli
Summary: This paper explores the expressivity and tractability of vividness from an interdisciplinary perspective of cognitive sciences, focusing on the discussion around symbolic approach to the concept of vividness and its crucial role in human reasoning psychology.
Review
Chemistry, Multidisciplinary
Julian Kimmig, Stefan Zechel, Ulrich S. Schubert
Summary: The ongoing digitalization is rapidly changing and revolutionizing various aspects of life, including the field of materials science. While there are promising examples showing the potential of digitalization to change research methods for new materials, there are still many issues to be addressed in order to achieve digital-supported material research.
ADVANCED MATERIALS
(2021)
Article
Medical Informatics
Rachel S. Kim, Steven Simon, Brett Powers, Amneet Sandhu, Jose Sanchez, Ryan T. Borne, Alexis Tumolo, Matthew Zipse, J. Jason West, Ryan Aleong, Wendy Tzou, Michael A. Rosenberg
Summary: The study aimed to create an electronic health record-based prediction tool to guide patient referral to specialists for rhythm-control management by comparing different machine learning algorithms. Age was found to be the strongest predictor of a rhythm-control strategy, while more complex models incorporating neural networks provided greater accuracy and reduced inappropriate referrals. The trade-off between prediction accuracy and model interpretability needs to be addressed by healthcare systems seeking to incorporate algorithms for rhythm management in AF patients.
JMIR MEDICAL INFORMATICS
(2021)
Article
Psychology, Multidisciplinary
Shigeru Taguchi, Hayato Saigo
Summary: This paper explores the duality of the now in consciousness and formalizes it using the concepts of monoids and coslice categories in category theory. It helps us understand the differences between ordinary consciousness and meditative consciousness.
FRONTIERS IN PSYCHOLOGY
(2023)
Review
Behavioral Sciences
Megan A. K. Peters
Summary: Perceptual metacognition possesses unique properties that allow for the study of the neural and computational correlates of subjective experience. Metacognition leads to subjective experiences, involves internal representations, utilizes recursive computations, is anchored to observable behavior, and depends on hierarchical computations.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2022)
Article
Psychology, Multidisciplinary
Ulrich Weger, Terje Sparby, Friedrich Edelhaeuser
Summary: The paper proposes a renewed trichotomic distinction based on epistemological considerations about the nature of thinking, applied to the question of the true self. The differentiation between representational and immersive thinking can help illuminate aspects of the (true) self that are elusive to a dualistic perspective, paving the way for an empirical inquiry into the self and discussing implications for the study of psychological phenomena in more general terms.
EUROPEAN PSYCHOLOGIST
(2021)
Article
Computer Science, Interdisciplinary Applications
Steve J. Bickley, Ho Fai Chan, Benno Torgler
Summary: This study examines the diffusion and application of artificial intelligence (AI) in economics using a scientometrics approach. The findings reveal that AI has been utilized and discussed in different subfields of economics, with variations over time, location, and subfield. The quality of institutional affiliation is positively correlated with engagement and focus on AI in economics, while there is a negative correlation between the Human Development Index and the proportion of AI papers based on learning.
Review
Pharmacology & Pharmacy
Nikita Serov, Vladimir Vinogradov
Summary: The technology of drug delivery systems (DDSs) has shown great potential in the field of nanomedicine, but its rational design and high-throughput development are still in their early stages. Integrating data-driven approaches, high throughput experimentation techniques, process automation, AI technology, and machine learning can potentially accelerate the development of efficient nanoformulated drugs and smart materials.
ADVANCED DRUG DELIVERY REVIEWS
(2022)
Article
Biochemistry & Molecular Biology
Alfred Ultsch, Joern Loetsch
Summary: Bayesian inference is widely used in science, but its calculation is not robust in regions of low evidence. Researchers propose a robust extension approach that improves class assignment accuracy for extreme values and weak evidence data.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Letter
Multidisciplinary Sciences
P. Lush, A. K. Seth
NATURE COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Gloria Andrada, Robert W. Clowes, Paul R. Smart
Summary: AI systems are becoming increasingly important in people's lives worldwide, leading to calls for greater transparency. However, there is ambiguity in defining transparency and conflicting demands for it. This paper analyzes the meaning of transparency and proposes a taxonomy to clarify the types of transparency needed from AI systems. It explores the relationship between technological transparency and human agency, and argues for considering all these different notions of transparency in designing ethically adequate AI systems.
Review
Multidisciplinary Sciences
Pedro A. M. Mediano, Fernando E. Rosas, Andrea I. Luppi, Henrik J. Jensen, Anil K. Seth, Adam B. Barrett, Robin L. Carhart-Harris, Daniel Bor
Summary: This article summarizes a recent formal theory of causal emergence based on information decomposition and discusses its application in various scenarios. The formalism quantifies emergence and is amenable to empirical testing.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2022)
Review
Behavioral Sciences
Pedro A. M. Mediano, Fernando E. Rosas, Daniel Bor, Anil K. Seth, Adam B. Barrett
Summary: This article discusses the integrated information theory of consciousness (IIT) and argues that by distinguishing between strong IIT and weak IIT, the appeal and applicability of IIT can be greatly expanded. Strong IIT identifies consciousness with specific properties associated with maximum integrated information, while weak IIT tests pragmatic hypotheses that relate aspects of consciousness to broader measures of information dynamics. The authors review challenges for strong IIT, explain how existing empirical findings can be well explained by weak IIT without committing to strong IIT entirely, and discuss the outlook for both flavors of IIT.
TRENDS IN COGNITIVE SCIENCES
(2022)
Article
Psychology, Multidisciplinary
Maxwell J. D. Ramstead, Anil K. Seth, Casper Hesp, Lars Sandved-Smith, Jonas Mago, Michael Lifshitz, Giuseppe Pagnoni, Ryan Smith, Guillaume Dumas, Antoine Lutz, Karl Friston, Axel Constant
Summary: This paper presents a version of neurophenomenology that utilizes computational modeling techniques based on generative modeling in neuroscience and biology. The approach, known as computational phenomenology, applies methods from computational modeling to create a formal model of descriptions of lived experience in philosophy. The paper provides an overview of the naturalization of phenomenology project, evaluates philosophical objections, and presents their approach in detail.
REVIEW OF PHILOSOPHY AND PSYCHOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Zafeirios Fountas, Anastasia Sylaidi, Kyriacos Nikiforou, Anil K. Seth, Murray Shanahan, Warrick Roseboom
Summary: Human perception and experience of time are influenced by various factors such as attention, memory, and perceptual stimulation. A comprehensive model of human time perception is introduced in this study, showing that cognitive load, scene type, and memory play significant roles in time experience.
NEURAL COMPUTATION
(2022)
Article
Biochemical Research Methods
Maxine T. Sherman, Zafeirios Fountas, Anil K. Seth, Warrick Roseboom
Summary: The subjective experience of time in humans is influenced by the environment, and time estimates are constructed by accumulating salient events. This study demonstrates that it is possible to reconstruct participants' subjective experience of time duration by analyzing salient events in their brain activity. These findings highlight the importance of perceptual processing of a dynamic environment in subjective time perception.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Psychology, Experimental
Zoltan Dienes, Pete Lush, Bence Palfi, Warrick Roseboom, Ryan Scott, Ben Parris, Anil Seth, Max Lovell
Summary: The article first reviews recent research from the laboratory, which interprets hypnotizability as a manifestation of the capacity for phenomenological control, allowing individuals to create subjective experiences in nonhypnotic contexts. It then examines phenomenological control as a metacognitive process, where intentional cognitive and motor actions occur without awareness of specific intentions. This article argues that various laboratory phenomena may be constructed through phenomenological control and presents a new theory of intentional binding to measure the absence of conscious intentions in a hypnotic context. There is no evidence that cold control confers abilities beyond the proposed metacognitive monitoring, and the article explores the negative correlation between mindfulness and cold control as a lack of mindfulness of intentions.
PSYCHOLOGY OF CONSCIOUSNESS-THEORY RESEARCH AND PRACTICE
(2022)
Article
Neurosciences
Hardik Rajpal, Pedro A. M. Mediano, Fernando E. Rosas, Christopher B. Timmermann, Stefan Brugger, Suresh Muthukumaraswamy, Anil K. Seth, Daniel Bor, Robin L. Carhart-Harris, Henrik J. Jensen
Summary: Schizophrenia and psychotomimetic drug states share some similarities in terms of physiological and phenomenological properties, but they also have fundamental differences. By comparing the neural dynamics induced by LSD and ketamine with those associated with schizophrenia, this study found that both conditions exhibit increased neural signal diversity. However, schizophrenia is characterized by an increased transfer of neural entropy from the front to the back of the brain, while the two drugs result in an overall reduction of transfer entropy. Additionally, computational modeling suggests that the drugs reduce the precision of priors, while schizophrenia leads to an increased precision of sensory information. These findings provide new insights into the similarities and differences between schizophrenia and drug-induced states, and may have implications for the study of consciousness and future mental health treatments.
Article
Behavioral Sciences
Lina I. Skora, James J. A. Livermore, Zoltan Dienes, Anil K. Seth, Ryan B. Scott
Summary: The extent to which high-level, complex functions can proceed unconsciously has been a topic of considerable debate. This study focuses on instrumental conditioning and aims to examine the feasibility of instrumental conditioning in the unconscious domain. The results suggest that complex forms of learning may rely on conscious access.
Article
Psychology, Multidisciplinary
David J. Schwartzman, Ales Oblak, Nicolas Rothen, Daniel Bor, Anil K. Seth
Summary: This article investigates the similarities between induced and lifelong visual experiences and finds that training can alter the visual experiences of non-synaesthetes and produce phenomena similar to natural grapheme-colour synaesthesia.
COLLABRA-PSYCHOLOGY
(2023)
Meeting Abstract
Ophthalmology
Peter Lush, Anil K. Seth, Ryan B. Scott, Zoltan Dienes
Article
Psychology, Biological
Jolien C. Francken, Lola Beerendonk, Dylan Molenaar, Johannes J. Fahrenfort, Julian D. Kiverstein, Anil K. Seth, Simon van Gaal
Summary: This academic survey explores the theoretical and methodological foundations, common assumptions, and the current state of consciousness research. The results show that there is considerable discussion and debate among researchers regarding the definition and study of consciousness. The survey also reveals varying opinions on topics such as machine consciousness, the gradual development of consciousness in the animal kingdom, and extensive unconscious processing. Additionally, the survey highlights the most promising theories of consciousness, preferred measures to determine consciousness, and potential neural signatures. These findings provide insight into the current views of researchers in the field and can help prioritize research and theoretical approaches.
NEUROSCIENCE OF CONSCIOUSNESS
(2022)
Article
History & Philosophy Of Science
Paul R. Smart, Gloria Andrada, Robert W. Clowes
Summary: This article challenges the importance of phenomenal transparency in cognitive extension and proposes that transparency is more applicable to situations that support the ascription of cognitive/mental dispositional properties. Transparency is neither necessary nor sufficient for cognitive extension, but it is helpful in understanding the circumstances in which episodes of extended cognizing arise.
Article
Humanities, Multidisciplinary
Robert W. Clowes, Gloria Andrada
Summary: This paper discusses the concept of mental depth and challenges Chater's (2018) argument that the mind is flat. The authors argue that mental depth is not just an illusory confabulation, but can be explained through neural contributions and embodied skills within rich environmental contexts.
Article
Computer Science, Artificial Intelligence
Qianghua Liu, Yu Tian, Tianshu Zhou, Kewei Lyu, Ran Xin, Yong Shang, Ying Liu, Jingjing Ren, Jingsong Li
Summary: This study proposes a few-shot disease diagnosis decision making model based on a model-agnostic meta-learning algorithm (FSDD-MAML). It significantly improves the diagnostic process in primary health care and helps general practitioners diagnose few-shot diseases more accurately.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)
Article
Computer Science, Artificial Intelligence
Balazs Borsos, Corinne G. Allaart, Aart van Halteren
Summary: The study demonstrates the feasibility of predicting functional outcomes for ischemic stroke patients and the usability of multimodal deep learning architectures for this purpose.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)
Article
Computer Science, Artificial Intelligence
Abdelmoniem Helmy, Radwa Nassar, Nagy Ramdan
Summary: This study utilizes machine learning models to detect depression symptoms in Arabic and English texts, and provides manually and automatically annotated tweet corpora. The study also develops an application that can detect tweets with depression symptoms and predict depression trends.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)
