scholarly journals Apophatic science: how computational modeling can explain consciousness

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Will Bridewell ◽  
Alistair M C Isaac
Keyword(s):  
Computational Modeling ◽  
Computer Science ◽  
Cognitive Science ◽  
Computational Models ◽  
New Method ◽  
Future Research ◽  
Negative Data ◽  
Lingua Franca ◽  
Cognitive Sciences ◽  
Unique Challenge

Abstract This study introduces a novel methodology for consciousness science. Consciousness as we understand it pretheoretically is inherently subjective, yet the data available to science are irreducibly intersubjective. This poses a unique challenge for attempts to investigate consciousness empirically. We meet this challenge by combining two insights. First, we emphasize the role that computational models play in integrating results relevant to consciousness from across the cognitive sciences. This move echoes Alan Newell’s call that the language and concepts of computer science serve as a lingua franca for integrative cognitive science. Second, our central contribution is a new method for validating computational models that treats them as providing negative data on consciousness: data about what consciousness is not. This method is designed to support a quantitative science of consciousness while avoiding metaphysical commitments. We discuss how this methodology applies to current and future research and address questions that others have raised.

Spazi di parole: metafore e rappresentazioni semantiche

PARADIGMI ◽  
2009 ◽  
pp. 83-100
Author(s):  
Alessandro Lenci
Keyword(s):  
Cognitive Science ◽  
Semantic Similarity ◽  
Computational Linguistics ◽  
Computational Models ◽  
Dimensional Space ◽  
High Dimensional ◽  
Semantic Representations ◽  
Topological Relations ◽  
Cognitive Sciences ◽  
Context Sensitive

- The aim of this paper is to analyse the analogy of the lexicon with a space defined by words, which is common to a number of computational models of meaning in cognitive science. This can be regarded as a case of constitutive scientific metaphor in the sense of Boyd (1979) and is grounded in the so-called Distributional Hypothesis, stating that the semantic similarity between two words is a function of the similarity of the linguistic contexts in which they typically co-occur. The meaning of words is represented in terms of their topological relations in a high-dimensional space, defined by their combinatorial behaviour in texts. A key consequence of adopting the metaphor of word spaces is that semantic representations are modelled as highly context-sensitive entities. Moreover, word space models promise to open interesting perspectives for the study of metaphorical uses in language, as well as of lexical dynamics in general. Keywords: Cognitive sciences, Computational linguistics, Distributional models of the lexicon, Metaphor, Semantics, Word spaces.

scholarly journals How Do Living Systems Create Meaning?

Philosophies ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 36
Author(s):  
Chris Fields ◽  
Michael Levin
Keyword(s):  
Computer Science ◽  
Cognitive Science ◽  
Living Systems ◽  
Temporal Scales ◽  
Cognitive Sciences

Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.

scholarly journals Toward a Computational Neuropsychology of Cognitive Flexibility

2020 ◽  
Vol 10 (12) ◽  
pp. 1000
Author(s):  
Alexander Steinke ◽  
Bruno Kopp
Keyword(s):  
Computational Modeling ◽  
Cognitive Flexibility ◽  
Computational Models ◽  
Neurological Diseases ◽  
Wisconsin Card Sorting Test ◽  
Future Research ◽  
Card Sorting ◽  
Stimulus Response ◽  
Cognitive Inflexibility ◽  
Sorting Test

Cognitive inflexibility is a well-documented, yet non-specific corollary of many neurological diseases. Computational modeling of covert cognitive processes supporting cognitive flexibility may provide progress toward nosologically specific aspects of cognitive inflexibility. We review computational models of the Wisconsin Card Sorting Test (WCST), which represents a gold standard for the clinical assessment of cognitive flexibility. A parallel reinforcement-learning (RL) model provides the best conceptualization of individual trial-by-trial WCST responses among all models considered. Clinical applications of the parallel RL model suggest that patients with Parkinson’s disease (PD) and patients with amyotrophic lateral sclerosis (ALS) share a non-specific covert cognitive symptom: bradyphrenia. Impaired stimulus-response learning appears to occur specifically in patients with PD, whereas haphazard responding seems to occur specifically in patients with ALS. Computational modeling hence possesses the potential to reveal nosologically specific profiles of covert cognitive symptoms, which remain undetectable by traditionally applied behavioral methods. The present review exemplifies how computational neuropsychology may advance the assessment of cognitive flexibility. We discuss implications for neuropsychological assessment and directions for future research.

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review

2020 ◽  
Vol 27 (5) ◽  
pp. 385-391
Author(s):  
Lin Zhong ◽  
Zhong Ming ◽  
Guobo Xie ◽  
Chunlong Fan ◽  
Xue Piao
Keyword(s):  
Supervised Learning ◽  
Protein Interactions ◽  
Computational Models ◽  
Prediction Models ◽  
Chromatin Modification ◽  
Computational Prediction ◽  
Human Diseases ◽  
Future Research ◽  
Non Coding Rna ◽  
Long Non Coding Rna

: In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well as many other processes. Surprisingly, lncRNA has an inseparable relationship with human diseases such as cancer. Therefore, only by knowing more about the function of lncRNA can we better solve the problems of human diseases. However, lncRNAs need to bind to proteins to perform their biomedical functions. So we can reveal the lncRNA function by studying the relationship between lncRNA and protein. But due to the limitations of traditional experiments, researchers often use computational prediction models to predict lncRNA protein interactions. In this review, we summarize several computational models of the lncRNA protein interactions prediction base on semi-supervised learning during the past two years, and introduce their advantages and shortcomings briefly. Finally, the future research directions of lncRNA protein interaction prediction are pointed out.

Research work in the Applied Cognitive Modelling Lab

Impact ◽  
2020 ◽  
Vol 2020 (7) ◽  
pp. 9-11
Author(s):  
Junya Morita
Keyword(s):  
Mental Illness ◽  
Language Development ◽  
Cognitive Science ◽  
Graphic Design ◽  
Computational Models ◽  
Research Work ◽  
Theoretical Studies ◽  
Cognitive Modelling ◽  
Web Navigation ◽  
Fundamental Values

Dr Junya Morita is based at the Applied Cognitive Modelling Laboratory (ACML) within the Department of Behavior Informatics at Shizuoka University in Japan. His team is conducting investigations that use computational models in an effort to improve our understanding of human minds and their inner workings. There are currently two directions of study underway at ACML. The first is concerned with theoretical studies of cognitive modelling, where the team try to construct models that explain human minds as computational and algorithmic levels. The second direction of study is the application of computational cognitive models. Morita and his team believe that there are fundamental values within the basic endeavours of cognitive science and are working to prove these values exist and are valid. Current topics of application include education, driving, entertainment, graphic design, language development, web navigation and mental illness.

Computing Possible Futures

2019 ◽  
Author(s):  
William B. Rouse
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computational Modeling ◽  
Mental Model ◽  
Data Analytics ◽  
Computational Models ◽  
Senior Managers ◽  
Interactive Visualizations ◽  
Use Of Models ◽  
Better Than

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.

scholarly journals Legal Concepts as Mental Representations

2021 ◽  
Author(s):  
Marek Jakubiec
Keyword(s):  
Cognitive Science ◽  
Mental Representations ◽  
Legal Philosophy ◽  
Current Debate ◽  
Cognitive Tools ◽  
Cognitive Sciences ◽  
Cognitive Aspect ◽  
Fundamental Level ◽  
Legal Concepts ◽  
Mental Constructs

AbstractAlthough much ink has been spilled on different aspects of legal concepts, the approach based on the developments of cognitive science is a still neglected area of study. The “mental” and cognitive aspect of these concepts, i.e., their features as mental constructs and cognitive tools, especially in the light of the developments of the cognitive sciences, is discussed quite rarely. The argument made by this paper is that legal concepts are best understood as mental representations. The piece explains what mental representations are and why this view matters. The explanation of legal concepts, understood as mental representations is one of (at least) three levels of explanation within legal philosophy, but—as will be argued—it is the most fundamental level. This paper analyzes the consequences of such understanding of concepts used in the field of legal philosophy. Special emphasis is put on the current debate on the analogical or amodal nature of concepts.

scholarly journals Sonority projection effect in French: A signal detection theory approach

2021 ◽  
pp. 1-12
Author(s):  
Anahita Basirat ◽  
Cédric Patin ◽  
Jérémie Jozefowiez
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Computational Models ◽  
Native Speakers ◽  
Detection Theory ◽  
Future Research ◽  
Theory Approach ◽  
Point Scale ◽  
Projection Effect ◽  
Measure Sensitivity

Abstract Focusing on the Sonority Sequencing Principle (SSP), we investigated the extent to which adult native speakers of French are sensitive to sonority-related constraints compared to lexical attestedness. In a non-word acceptability task, participants were asked to rate the acceptability of three types of non-words using a 6-point scale: non-words with attested sonority rising onset, non-words with unattested sonority rising onset, and non-words with unattested sonority falling onset. Data analysis was done using the signal detection theory approach to measure sensitivity of participants to lexical attestedness and to phonological well-formedness (i.e., respecting or violating the SSP). The results showed that speakers distinguished well-formed and ill-formed forms even when lexical attestedness was controlled for. This is consistent with previous findings on sonority projection effects. Participants were more sensitive to lexical attestedness than phonological well-formedness. Future research using computational models should investigate mechanisms that could account for these findings, namely whether a similar result would be obtained without including any assumption about the SSP in these models.

Historical Cognition and Cognitive Sciences: New in Russian Historiography

Istoriya ◽  
2021 ◽  
Vol 12 (8 (106)) ◽  
pp. 0
Author(s):  
Lidia Sofronova
Keyword(s):  
Cognitive Science ◽  
Natural Science ◽  
Interdisciplinary Research ◽  
Recent Literature ◽  
Natural Sciences ◽  
Cognitive Sciences ◽  
Analytical Review ◽  
Science Disciplines

The article presents an analytical review of the recent literature on cognitive history, especially the Russian collective monograph “Cognitive Sciences and Historical Cognition”, published in 2020. It traces the patterns typical for interdisciplinary research not only within the humanitarian disciplines, but also at the “borders” between the humanities and the “natural sciences”. The article highlights the paradoxical and productive nature of the “mutual interventions” of cognitive science and the humanities, which contribute to overcoming “atomism” both within the humanities and at the “frontier” between them and the natural science disciplines.

The 7E Model of the Human Mind: Articulating a Plastic Self for the Cognitive Science of Religion

2019 ◽  
Vol 19 (5) ◽  
pp. 450-476
Author(s):  
Flavio A. Geisshuesler
Keyword(s):  
Cognitive Science ◽  
Human Mind ◽  
Religious Studies ◽  
The Self ◽  
Cognitive Science Of Religion ◽  
Cognitive Sciences ◽  
Religious Mind ◽  
Science Of Religion ◽  
Concrete Model

AbstractThis article proposes a 7E model of the human mind, which was developed within the cognitive paradigm in religious studies and its primary expression, the Cognitive Science of Religion (CSR). This study draws on the philosophically most sophisticated currents in the cognitive sciences, which have come to define the human mind through a 4E model as embodied, embedded, enactive, and extended. Introducing Catherine Malabou’s concept of “plasticity,” the study not only confirms the insight of the 4E model of the self as a decentered system, but it also recommends two further traits of the self that have been overlooked in the cognitive sciences, namely the negativity of plasticity and the tension between giving and receiving form. Finally, the article matures these philosophical insights to develop a concrete model of the religious mind, equipping it with three further Es, namely emotional, evolved, and exoconscious.

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