scholarly journals Consistent Verbal Labels Promote Odor Category Learning

2020 ◽  
Author(s):  
Norbert Vanek ◽  
Marton Soskuthy ◽  
Asifa Majid
Keyword(s):  
Cognitive Processes ◽  
Category Learning ◽  
Perceptual Experience ◽  
Causal Link ◽  
Learning Curves ◽  
Perceptual Processing ◽  
Steady Increase ◽  
Learning Gains ◽  
Verbal Labels ◽  
Different Types

Recent research shows that speakers of most languages find smells difficult to abstract and name. Can verbal labels enhance the human capacity to learn smell categories? Few studies have examined how verbal labeling might affect non-visual cognitive processes, and thus far very little is known about word-assisted odor category learning. To address these gaps, we tested whether different types of training change learning gains in odor categorization. After four intensive days of training to categorize odors that were co-presented with arbitrary verbal labels, people who learned odor categories with odor-label pairs that were more consistent were significantly more accurate than people with the same perceptual experience but who had odor-label pairs that were less consistent. Both groups’ accuracy scores improved, but the learning curves differed. The context of consistent linguistic cuing supported a steady increase in correct responses from the onset of training. However, inconsistent linguistic cuing delayed the start of approximating to target odor categorization. These results show that associations formed between odors and novel verbal labels facilitate the formation of odor categories. We interpret this as showing a causal link between language and olfactory perceptual processing in supporting categorization.

scholarly journals Creating Something Different: Similarity, Contrast, and Representativeness in Categorization

2019 ◽  
Author(s):  
Joseph L. Austerweil ◽  
Shi Xian Liew ◽  
Nolan Bradley Conaway ◽  
Kenneth J. Kurtz
Keyword(s):  
Cognitive Processes ◽  
Category Learning ◽  
Human Cognition ◽  
Fundamental Importance ◽  
Concept Generation ◽  
Statistical Structure ◽  
Representativeness Heuristic ◽  
New Concepts ◽  
Novel Approaches ◽  
Computational Analyses

The ability to generate new concepts and ideas is among the most fascinating aspects of human cognition, but we do not have a strong understanding of the cognitive processes and representations underlying concept generation. In this paper, we study the generation of new categories using the computational and behavioral toolkit of traditional artificial category learning. Previous work in this domain has focused on how the statistical structure of known categories generalizes to generated categories, overlooking whether (and if so, how) contrast between the known and generated categories is a factor. We report three experiments demonstrating that contrast between what is known and what is created is of fundamental importance for categorization. We propose two novel approaches to modeling category contrast: one focused on exemplar dissimilarity and another on the representativeness heuristic. Our experiments and computational analyses demonstrate that both models capture different aspects of contrast’s role in categorization.

The development of features in object concepts

1998 ◽  
Vol 21 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Philippe G. Schyns ◽  
Robert L. Goldstone ◽  
Jean-Pierre Thibaut
Keyword(s):  
Cognitive Processes ◽  
Category Learning ◽  
Cognitive Process ◽  
Conceptual Development ◽  
Object Categorization ◽  
Constructive Induction ◽  
Fixed Space ◽  
Functional Features ◽  
High Level ◽  
Perceptual Changes

According to one productive and influential approach to cognition, categorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower level perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of features as being fixed by low-level processes, we present a theory in which people create features to subserve the representation and categorization of objects. Two types of category learning should be distinguished. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with the features available. Whether fixed or flexible, learning depends on the featural contrasts and similarities between the new category to be represented and the individual's existing concepts. Fixed feature approaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for categorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features are small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categorizations will not be captured by these primitives. We present evidence of flexible perceptual changes arising from category learning and theoretical arguments for the importance of this flexibility. We describe conditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models of dimensionality reduction.

Unraveling What’s on Our Minds

2018 ◽  
Author(s):  
Claire M. Zedelius ◽  
Jonathan W. Schooler
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Task Performance ◽  
Cognitive Processes ◽  
Positive Mood ◽  
Mind Wandering ◽  
Different Types ◽  
And Behavior

Mind-wandering encompasses a variety of different types of thought, involving various different experiential qualities, emotions, and cognitive processes. Much is lost by simply lumping them together, as is typically done in the literature. The goal of this chapter is to explore the nuances that distinguish different types of mind-wandering. The chapter draws on research on mind-wandering as well as other literatures to gain a better understanding of how these different types of mind-wandering affect cognition and behavior. It specifically discusses the distinct effects of different types of mind-wandering on task performance, working memory, mood, and creativity. Finally, the chapter discusses the idea of deliberate engagement in particular types of mind-wandering as a way to achieve desirable outcomes, such as maintaining a positive mood, enhancing creativity, or aiding decision-making.

Training Skills in Minimally Invasive, Robotic and Open Surgery: Brain Activation as an Opportunity for Learning

2020 ◽  
Vol 61 (1) ◽  
pp. 34-50
Author(s):  
Gloria Pelizzo ◽  
Lucilla Cardinali ◽  
Lilla Bonanno ◽  
Silvia Marino ◽  
Carlo Cavaliere ◽  
...  
Keyword(s):  
Surgical Training ◽  
Open Surgery ◽  
Surgical Techniques ◽  
Learning Curves ◽  
Surgical Instruments ◽  
Open Group ◽  
Control Group ◽  
Steady Increase ◽  
Motor Training ◽  
Starting Point

Introduction: The advantages of the robotic approach in surgery are undisputed. However, during surgical training, how this technique influences the learning curve has not been described. We provide a tentative model for analyzing the learning curves associated with observation and active participation in learning different surgical techniques, using functional imaging. Methods: Forty medical students were enrolled and assigned to 4 groups who underwent training in robotic (ROB), laparoscopic (LAP), or open (OPEN) surgery, and a control group that performed motor training without surgical instruments. Surgical/motor training included six 1-h sessions completed over 6 days of the same week. All subjects underwent functional magnetic resonance imaging (fMRI) scanning sessions, before and after surgical training during. Results: Twenty-three participants completed the study. The 3 surgical groups exhibited different learning curves during training. The main effects of the day of training (p < 0.01) and the group (p < 0.01) as well as a significant interaction of day of training group (p < 0.01) were observed. The performance increased in the first 4 days, reaching a peak at day 4, when all groups were considered together. The OPEN group showed the best performance compared to all other groups (p < 0.04). The OPEN group showed a rapid improvement in performance, which peaked at day 4 and decreased on the last day. Similarly, the LAP group showed a steady increase in the number of exercises they completed, which continued for the entire training period and reached a peak on the last day. However, the participants training in ROB surgery, after a performance initially indistinguishable from that of the LAP group, had a dip in their performance, quickly followed by an improvement and reaching a plateau on day 4. fMRI analysis documented the different involvement of the cortical and subcortical areas based on the type of training. Surgical training modified the activation of some brain regions during both observation and the execution of tasks. Conclusions: Differences in the learning curves of the 3 surgical groups were noted. Functional brain activity represents an interesting starting point to guide training programs.

Learning Systems and their Engineering

2003 ◽  
pp. 164-177 ◽  
Author(s):  
Valentina Plekhanova
Keyword(s):  
Cognitive Processes ◽  
Systems Engineering ◽  
Knowledge Engineering ◽  
Learning Processes ◽  
Learning Systems ◽  
Cognitive Systems ◽  
Project Proposal ◽  
Cognitive Agents ◽  
Different Types ◽  
Future Work

This chapter presents a project proposal that defines future work in engineering the learning processes in cognitive systems. This proposal outlines a number of directions in the fields of systems engineering, machine learning, knowledge engineering and profile theory, that lead to the development of formal methods for the modeling and engineering of learning systems. This chapter describes a framework for formalization and engineering the cognitive processes, which is based on applications of computational methods. The proposed work studies cognitive processes in software development process and considers a cognitive system as a multi-agents system of human-cognitive agents. It is important to note that this framework can be applied to different types of learning systems, and there are various techniques from different theories (e.g., system theory, quantum theory, neural networks) can be used for the description of cognitive systems, which in turn can be represented by different types of cognitive agents.

Estimating Cognitive Complexity and the Need for Cognitive Task Analysis

1994 ◽  
Vol 38 (16) ◽  
pp. 1023-1027 ◽  
Author(s):  
Michael J. DeVries ◽  
Sallie E. Gordon
Keyword(s):  
Cognitive Processes ◽  
Cognitive Complexity ◽  
Task Analysis ◽  
Cognitive Task ◽  
Cognitive Task Analysis ◽  
Types Of Knowledge ◽  
Different Types ◽  
Computer Based ◽  
Multiple Domains ◽  
Specific Project

Because an increasing number of systems are being developed to support complex cognitive functioning, task analysis is commonly being augmented with cognitive task analysis, which identifies cognitive processes, knowledge, and mental models relevant to task performance. Cognitive task analysis tends to be lengthy and time-consuming, so designers frequently ask how they might know if it is actually necessary for a specific project. In this paper, we assume that much of the need for cognitive task analysis depends on the inherent “cognitive complexity” of the task. We present a model of cognitive complexity, and show how it was used to develop a computer-based tool for estimating relative cognitive complexity for a set of tasks. The tool, Cog-C, elicits task and subtask hierarchies, then guides the user in making relatively simple estimates on a number of scales. The tool calculates and displays the relative cognitive complexity scores for each task, along with subscores of cognitive complexity for different types of knowledge. Usability and reliability were evaluated in multiple domains, showing that the tool is relatively easy to use, reliable, and well-accepted.

scholarly journals Genesis and Nature of Moral and Legal Norms. Leon Petrażycki’s Naturalistic Solution

Studia Humana ◽  
2018 ◽  
Vol 7 (3) ◽  
pp. 39-52 ◽  
Author(s):  
Andrzej Dąbrowski
Keyword(s):  
Cognitive Processes ◽  
Fundamental Difference ◽  
Scientific Methodology ◽  
Moral Norms ◽  
Emotional Experiences ◽  
New Classification ◽  
Legal Norms ◽  
Different Types ◽  
Over Time

Abstract The aim of the paper is to examine the nature of moral and legal norms in a broader context: first, taking into account logical and methodological assumptions, second, in the perspective of psychology of emotions and legal policy. The basic subject of the research carried out by Leon Petrażycki was represented by law. Originally, it had a psychological character, not an objective, eternal, and unchanging one. To fully understand the genesis and nature of morality and law, Petrażycki addressed the study of mental phenomena, especially emotional experiences. First, however, he developed appropriate rules of logic and scientific methodology. Then he developed a new classification of mental phenomena, among which the fundamental role is played by bilateral (passive-active) emotions. At some stage, emotions begin to cooperate with cognitive processes, first of all with imaginations. Imaginations of acts, such as theft, betrayal, murder, can cause repulsive emotions, and type imaginations, such as truthfulness, charity, justice can evoke apulsive emotions. On the basis of such associations, judgments are created over time, the content of which becomes a basis for fundamental rules of conduct, that is, for norms. There are two fundamentally different types of norms: moral norms and legal norms. The norms of the first type are imperative and represent the nature of validity (they are obeyed), while the norms of the second type are imperative-attributive and they also always entitle someone to something, i.e. they give someone a right. This division determines a fundamental difference between morality and law.

Cardiac device therapy

2018 ◽  
Author(s):  
Kim Rajappan
Keyword(s):  
Cardiac Resynchronization ◽  
Steady Increase ◽  
Implantable Cardioverter Defibrillators ◽  
Device Therapy ◽  
Cardiac Device ◽  
Cardiac Devices ◽  
Cardiac Resynchronization Therapy Devices ◽  
Number Of Patients ◽  
Different Types ◽  
Cardioverter Defibrillators

The term ‘device therapy’ is used in cardiology to refer to three different types of implantable cardiac-rhythm-management devices: pacemakers, implantable cardioverter defibrillators (also known as ICDs), and cardiac resynchronization therapy devices (also known as CRT devices). There has been a steady increase in the number of patients receiving these cardiac devices; in relation to CRT devices, the increase has been almost exponential.

Synesthesia in the process of phraseologismformation: a new approach

2018 ◽  
Vol 9 (1) ◽  
pp. 85-110
Author(s):  
Irina Zykova
Keyword(s):  
Conceptual Model ◽  
Perceptual Experience ◽  
Cognitive Activity ◽  
Conceptual Foundation ◽  
New Approach ◽  
Language Semantics ◽  
The World ◽  
Different Types ◽  
Deep Stratum ◽  
The Way

Abstract The paper aims to explore how the process of phraseologism-formation is linked with the process of perception as part and parcel of human cognitive activity. Specifically, the research focuses on the role synesthesia plays in the construction of phraseological meaning. We proceed from the claim that the perceptual experience a human gains through multiple sensory channels while cognizing the world is preserved in the language semantics. Therefore, one of the main assumptions of the research is that synesthesia as a result of crossintegration of various perceptual sensations and their (sub)modalities influences the formation of phraseologisms and can be traced in their semantics. To test this assumption, a representative corpus of English and Russian phraseological units (more than 3,000) is analyzed. In the course of the analysis different types of synesthetic transfers that underlie the phraseological meanings in question are established. Special attention is paid to the way in which synesthesia is involved in the construction of the deep stratum of phraseological semantics that consists of the conceptual foundation (i.e., macro-metaphorical conceptual model) and phraseological image. Overall, the study offers further evidence that phraseological meaning is derived from the perceptual experience and from various synesthetic transfers in particular.

Sign in / Sign up

Export Citation Format

Share Document