scholarly journals Computational Modeling of Backwards-Blocking Reasoning in Human Adults

2020 ◽  
Author(s):  
Deon T. Benton ◽  
David H. Rakison
Keyword(s):  
Cognitive Ability ◽  
Causal Reasoning ◽  
Computational Models ◽  
Associative Processes ◽  
Complex Interactions ◽  
The World ◽  
Human Adults ◽  
Screening Off ◽  
Associative Models ◽  
Detector Design

Causal reasoning is a fundamental cognitive ability that enables humans to learn about the complex interactions in the world around them. However, it remains unknown whether causal reasoning is underpinned by a Bayesian mechanism or an associative one. For example, some maintain that a Bayesian mechanism underpins human causal reasoning because it can better account for backward-blocking (BB) and indirect screening-off (IS) findings than certain associative models. However, the evidence is mixed about the extent to which learners engage in both kinds of reasoning. Here, we report an experiment and several computational models that examine to what extent adults engage in BB and IS reasoning using the blicket-detector design. The results revealed that adults’ causal ratings in a backwards-blocking and indirect screening-off condition were consistent with associative rather than a Bayesian computational model. These results are interpreted to mean that adults use associative processes to reason about causal events.

Triggers of Thought: Impressions within Hume’s Theory of Mind

2010 ◽  
Vol 13 (1) ◽  
pp. 105-121
Author(s):  
Anik Waldow
Keyword(s):  
Theory Of Mind ◽  
Associative Processes ◽  
Sensory Inputs ◽  
The World ◽  
Theories Of Meaning ◽  
Conceptual Resources

This essay argues that Humean impressions are triggers of associative processes, which enable us to form stable patterns of thought that co-vary with our experiences of the world. It will thus challenge the importance of the Copy Principle by claiming that it is the regularity with which certain kinds of sensory inputs motivate certain sets of complex ideas that matters for the discrimination of ideas. This reading is conducive to Hume’s account of perception, because it avoids the impoverishment of conceptual resources so typical for empiricist theories of meaning and explains why ideas should be based on impressions, although impressions cannot be known to mirror matters of fact. Dieser Aufsatz argumentiert dafür, dass humesche Eindrücke („impressions“) Auslöser von assoziativen Prozessen sind, welche es uns ermöglichen, stabile Denkmuster zu bilden, die mit unseren Erfahrungen der Welt kovariant sind. Der Aufsatz stellt somit die Wichtigkeit des Kopien-Prinzips in Frage, nämlich dadurch, dass behauptet wird, für die Unterscheidung der Ideen sei die Regelmäßigkeit maßgeblich, mit der gewisse Arten von sensorischen Eingaben gewisse Mengen von komplexen Ideen motivieren. Diese Lesart trägt zu einem Verständnis von Humes Auffassung der Wahrnehmung bei, da sie die Verarmung der begrifflichen Mittel, die für empiristische Theorien der Bedeutung so typisch ist, vermeidet und erklärt, warum Ideen auf Eindrücken basieren sollten, obwohl Eindrücke nicht als Abbildungen von Tatsachen erkannt werden können.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

scholarly journals Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

2021 ◽  
Vol 9 (2) ◽  
pp. 417
Author(s):  
Sherli Koshy-Chenthittayil ◽  
Linda Archambault ◽  
Dhananjai Senthilkumar ◽  
Reinhard Laubenbacher ◽  
Pedro Mendes ◽  
...  
Keyword(s):  
Species Interactions ◽  
Computational Models ◽  
Human Microbiome ◽  
Agent Based Modeling ◽  
Autonomous Agent ◽  
Agent Based Models ◽  
Agent Based ◽  
Complex Interactions ◽  
Mucosal Surfaces ◽  
Living Organisms

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.

Current trends in mathematical modeling of tumor–microenvironment interactions: a survey of tools and applications

2010 ◽  
Vol 235 (4) ◽  
pp. 411-423 ◽  
Author(s):  
Katarzyna A Rejniak ◽  
Lisa J McCawley
Keyword(s):  
Mathematical Modeling ◽  
Protein Interactions ◽  
Computational Models ◽  
Chemical Species ◽  
Tumor Stroma ◽  
Cellular Functions ◽  
Complex Interactions ◽  
Expanding Population

In its simplest description, a tumor is comprised of an expanding population of transformed cells supported by a surrounding microenvironment termed the tumor stroma. The tumor microcroenvironment has a very complex composition, including multiple types of stromal cells, a dense network of various extracellular matrix (ECM) fibers interpenetrated by the interstitial fluid and gradients of several chemical species that either are dissolved in the fluid or are bound to the ECM structure. In order to study experimentally such complex interactions between multiple players, cancer is dissected and considered at different scales of complexity, such as protein interactions, biochemical pathways, cellular functions or whole organism studies. However, the integration of information acquired from these studies into a common description is as difficult as the disease itself. Computational models of cancer can provide cancer researchers with invaluable tools that are capable of integrating the complexity into organizing principles as well as suggesting testable hypotheses. We will focus in this Minireview on mathematical models in which the whole cell is a main modeling unit. We will present a current stage of such cell-focused mathematical modeling incorporating different stromal components and their interactions with growing tumors, and discuss what modeling approaches can be undertaken to complement the in vivo and in vitro experimentation.

scholarly journals The Environment Is Not A System

2018 ◽  
Vol 7 (1) ◽  
pp. 152-165
Author(s):  
Tega Brain
Keyword(s):  
Knowledge Production ◽  
Mass Extinction ◽  
Computational Models ◽  
Rapid Climate Change ◽  
The World ◽  
History Of Ecology ◽  
History Of ◽  
And Control ◽  
Systems View ◽  
Manipulation And Control

This paper considers some of the limitations and possibilities of computational models in the context of environmental inquiry, specifically exploring the modes of knowledge production that it mobilizes. Historic computational attempts to model, simulate and make predictions about environmental assemblages, both emerge from and reinforce a systems view on the world. The word eco-system itself stands as a reminder that the history of ecology is enmeshed with systems theory and presup-poses that species entanglements are operational or functional. More surreptitiously, a systematic view of the environment connotes it as bounded, knowable and made up of components operating in chains of cause and effect. This framing strongly invokes possibilities of manipulation and control and implicitly asks: what should an ecosystem be optimized for? This question is particularly relevant at a time of rapid climate change, mass extinction and, conveniently, an unprecedented surplus of computing.

The Semantic Web and Its Entanglements

2017 ◽  
Vol 22 (1) ◽  
pp. 21-37 ◽  
Author(s):  
Matthew T. Mccarthy
Keyword(s):  
Artificial Intelligence ◽  
Semantic Web ◽  
Linked Data ◽  
Practice Theory ◽  
Knowledge Systems ◽  
Access To Information ◽  
Assemblage Theory ◽  
Complex Interactions ◽  
The World ◽  
The Web

The web of linked data, otherwise known as the semantic web, is a system in which information is structured and interlinked to provide meaningful content to artificial intelligence (AI) algorithms. As the complex interactions between digital personae and these algorithms mediate access to information, it becomes necessary to understand how these classification and knowledge systems are developed. What are the processes by which those systems come to represent the world, and how are the controversies that arise in their creation, overcome? As a global form, the semantic web is an assemblage of many interlinked classification and knowledge systems, which are themselves assemblages. Through the perspectives of global assemblage theory, critical code studies and practice theory, I analyse netnographic data of one such assemblage. Schema.org is but one component of the larger global assemblage of the semantic web, and as such is an emergent articulation of different knowledges, interests and networks of actors. This articulation comes together to tame the profusion of things, seeking stability in representation, but in the process, it faces and produces more instability. Furthermore, this production of instability contributes to the emergence of new assemblages that have similar aims.

scholarly journals The Development of Causal Reasoning

2017 ◽  
Author(s):  
Paul Muentener ◽  
Elizabeth Bonawitz
Keyword(s):  
Young Children ◽  
Causal Reasoning ◽  
Causal Structure ◽  
Statistical Evidence ◽  
Causal Learning ◽  
Causal Relationships ◽  
Older Children ◽  
Very Young Children ◽  
The World

Research on the development of causal reasoning has broadly focused on accomplishing two goals: understanding the origins of causal reasoning, and examining how causal reasoning changes with development. This chapter reviews evidence and theory that aim to fulfill both of these objectives. In the first section, it focuses on the research that explores the possible precedents for recognizing causal events in the world, reviewing evidence for three distinct mechanisms in early causal reasoning: physical launching events, agents and their actions, and covariation information. The second portion of the chapter examines the question of how older children learn about specific causal relationships. It focuses on the role of patterns of statistical evidence in guiding learning about causal structure, suggesting that even very young children leverage strong inductive biases with patterns of data to inform their inferences about causal events, and discussing ways in which children’s spontaneous play supports causal learning.

Sorting Out the Plague

2021 ◽  
pp. 93-111
Author(s):  
Robert N. Wiedenmann ◽  
J. Ray Fisher
Keyword(s):  
Insect Vectors ◽  
Bacterial Dna ◽  
The Third ◽  
Complex Interactions ◽  
Rapid Spread ◽  
The World ◽  
Disease Reservoirs ◽  
The Way

This chapter explores the complex interactions among mammal hosts, insect vectors, bacteria and even amoebae implicated in the movement of the plague around the world. As it shows, trying to find the cause for the three plague pandemics is similar to the way a television detective solves a murder mystery. While the third pandemic established the roles of rats, rat fleas, and bacteria, that explanation has been incorrectly applied to explain the first two pandemics. The chapter shows how bacterial DNA collected from the teeth of 6th-Century plague victims, exhumed 1,400 years later, established greater understanding of the rate and geographic extent of the plague's spread. It goes on to relate how the age-old conclusions that brown rats were disease reservoirs and their fleas were vectors have been reconsidered, assigning rats and fleas specific roles and recognizing that humans and human lice as host and vector are more consistent with the plague’s rapid spread. Using clues from hosts and vectors to solve the mystery requires investigators to be like detectives.

scholarly journals Primary Cognitive Categories Are Determined by Their Invariances

2020 ◽  
Vol 11 ◽  
Author(s):  
Peter Gärdenfors
Keyword(s):  
Computational Models ◽  
External World ◽  
Neural Mechanisms ◽  
Sensory Signals ◽  
The World

The world as we perceive it is structured into objects, actions and places that form parts of events. In this article, my aim is to explain why these categories are cognitively primary. From an empiricist and evolutionary standpoint, it is argued that the reduction of the complexity of sensory signals is based on the brain's capacity to identify various types of invariances that are evolutionarily relevant for the activities of the organism. The first aim of the article is to explain why places, object and actions are primary cognitive categories in our constructions of the external world. It is shown that the invariances that determine these categories have their separate characteristics and that they are, by and large, independent of each other. This separation is supported by what is known about the neural mechanisms. The second aim is to show that the category of events can be analyzed as being constituted of the primary categories. The category of numbers is briefly discussed. Some implications for computational models of the categories are also presented.

scholarly journals Linking flexibility of brain networks to cognitive development in preschool children

2020 ◽  
Author(s):  
Lily Chamakura ◽  
Syed Naser Daimi ◽  
Katsumi Watanabe ◽  
Joydeep Bhattacharya ◽  
Goutam Saha
Keyword(s):  
Preschool Children ◽  
Brain Development ◽  
Cognitive Ability ◽  
Temporal Variability ◽  
Short Term Memory ◽  
Brain Networks ◽  
Brain Network ◽  
Memory And Attention ◽  
Functional Brain Networks ◽  
Human Adults

AbstractRecent studies of functional connectivity networks (FCNs) suggest that the reconfiguration of brain network across time, both at rest and during task, is linked with cognition in human adults. In this study, we tested this prediction, i.e. cognitive ability is associated with a flexible brain network in preschool children of 3-4 years - a critical age, representing a ‘blossoming period’ for brain development. We recorded magnetoen-cephalogram (MEG) data from 88 preschoolers, and assessed their cognitive ability by a battery of cognitive tests. We estimated FCNs obtained from the source reconstructed MEG recordings, and characterized the temporal variability at each node using a novel path-based measure of temporal variability; the latter captures reconfiguration of the node’s interactions to the rest of the network across time. Using connectome predictive modeling, we demonstrated that the temporal variability of fronto-temporal nodes in the dynamic FCN can reliably predict out-of-scanner performance of short-term memory and attention distractability in novel participants. Further, we observed that the network-level temporal variability increased with age, while individual nodes exhibited an inverse relationship between temporal variability and node centrality. These results demonstrate that functional brain networks, and especially their reconfiguration ability, are important to cognition at an early but a critical stage of human brain development.

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