Rediscovering Symbols: The Role of Category Labels in Similarity Judgment

Yu, Na-Yung; Yamauchi, Takashi; Schumacher, Jay

doi:10.17791/jcs.2008.9.2.89

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…Emotion theorists disagree in the ontological status of emotion: a small number of discrete emotions (Ekman & Cordaro, 2011;Panksepp & Watt, 2011), two dimensions of core affect (valence and arousal), appraisal of goal-related changes in the environment (Moors, Ellsworth, Scherer, & Frijda, 2013), and/or motivated action (e.g., approaching or avoiding) (Elliot, Eder, & Harmon-Jones, 2013;Lang & Bradley, 2010) are said to result in a variety of different emotion experiences. Other theorists (Barrett, 2014;Lindquist, 2013;Russell, 2003) suggest that emotions are constructed dynamically from domain-general systems of categorization and predictive inference (Yamauchi, 2009;Yamauchi & Markman, 2000;Yu, Yamauchi, & Schumacher, 2008).…”

Section: Measuring Emotionsmentioning

confidence: 99%

Reading Emotion From Mouse Cursor Motions: Affective Computing Approach

Yamauchi

Xiao

2017

Cognitive Science

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Affective computing research has advanced emotion recognition systems using facial expressions, voices, gaits, and physiological signals, yet these methods are often impractical. This study integrates mouse cursor motion analysis into affective computing and investigates the idea that movements of the computer cursor can provide information about emotion of the computer user. We extracted 16-26 trajectory features during a choice-reaching task and examined the link between emotion and cursor motions. Participants were induced for positive or negative emotions by music, film clips, or emotional pictures, and they indicated their emotions with questionnaires. Our 10-fold cross-validation analysis shows that statistical models formed from "known" participants (training data) could predict nearly 10%-20% of the variance of positive affect and attentiveness ratings of "unknown" participants, suggesting that cursor movement patterns such as the area under curve and direction change help infer emotions of computer users.

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Section: Measuring Emotionsmentioning

confidence: 99%

Reading Emotion From Mouse Cursor Motions: Affective Computing Approach

Yamauchi

Xiao

2017

Cognitive Science

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The influence of theoretical knowledge on similarity judgment

Sun

Guo-en

2019

Cogn Process

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On the Perception of Probable Things: Neural Substrates of Associative Memory, Imagery, and Perception

Albright

2012

Neuron

147

122

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SUMMARY Perception is influenced both by the immediate pattern of sensory inputs and by memories acquired through prior experiences with the world. Throughout much of its illustrious history, however, study of the cellular basis of perception has focused on neuronal structures and events that underlie the detection and discrimination of sensory stimuli. Relatively little attention has been paid to the means by which memories interact with incoming sensory signals. Building upon recent neurophysiological/behavioral studies of the cortical substrates of visual associative memory, I propose a specific functional process by which stored information about the world supplements sensory inputs to yield neuronal signals that can account for visual perceptual experience. This perspective represents a significant shift in the way we think about the cellular bases of perception.

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Rediscovering Symbols: The Role of Category Labels in Similarity Judgment

Cited by 3 publications

References 5 publications

Reading Emotion From Mouse Cursor Motions: Affective Computing Approach

Reading Emotion From Mouse Cursor Motions: Affective Computing Approach

The influence of theoretical knowledge on similarity judgment

On the Perception of Probable Things: Neural Substrates of Associative Memory, Imagery, and Perception

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