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Concepts and Prototypes01:24

Concepts and Prototypes

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The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
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Stereotype Content Model02:16

Stereotype Content Model

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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Encoding01:19

Encoding

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Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
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Components of Language01:24

Components of Language

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Natural and Artificial Concepts01:24

Natural and Artificial Concepts

473
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
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Modeling and Similitude01:12

Modeling and Similitude

537
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
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Related Experiment Video

Updated: Dec 25, 2025

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

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Constructing Semantic Models From Words, Images, and Emojis.

Armand S Rotaru1, Gabriella Vigliocco1

  • 1Experimental Psychology Department, University College London.

Cognitive Science
|April 3, 2020
PubMed
Summary
This summary is machine-generated.

New multimodal semantic models integrate linguistic, visual, and affective information. Adding affective data improved abstract concept representation, enhancing overall semantic model performance.

Keywords:
ConcretenessDistributional modelsEmotionLanguageMultimodal modelsSimilarity/relatednessVision

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Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
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Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
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Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology

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Area of Science:

  • Cognitive Science
  • Computational Linguistics
  • Neuroscience

Background:

  • Multimodal semantic models combining linguistic and visual data outperform unimodal models.
  • Emotion significantly impacts semantic processing, particularly for abstract concepts.
  • Existing models lack integration of linguistic, visual, and affective information.

Purpose of the Study:

  • To develop and evaluate multimodal semantic models incorporating affective representations.
  • To assess the impact of affective information on semantic similarity judgments.
  • To improve the fit of computational models to human semantic behavior.

Main Methods:

  • Enhanced visual and affective representations from state-of-the-art models.
  • Utilized a neural network for predicting emojis from text to derive affective representations.
  • Assessed model performance by fitting semantic similarity/relatedness judgments.

Main Results:

  • Integrating both visual and affective representations significantly improved model performance.
  • Visual representations enhanced concrete word processing.
  • Affective representations particularly improved abstract word processing.

Conclusions:

  • Multimodal semantic models benefit from the inclusion of affective information.
  • Affective representations are crucial for understanding abstract concepts.
  • Optimized weighting of different data modalities enhances semantic model accuracy.