Personality

Eysenck, H. J.

doi:10.1016/b978-0-12-718670-2.50011-6

Cited by 89 publications

(40 citation statements)

References 129 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The six traits form three pairs (sociable–shy, confident–anxious, industrious–lazy), corresponding to one of three major dimensions of the Big Five: Extraversion (sociable–shy), Neuroticism (confident–anxious), and Conscientiousness (industrious–lazy). These dimensions also correspond to the three major dimensions in Eysenck’s (1983, 1994) Extraversion, Psychoticism, and Neuroticism (EPN) and in Tellegen’s (1985) model. Manipulating the biases on goals and resources changes the baseline activation of the corresponding nodes.…”

Section: A Neural Network Model Of Personalitymentioning

confidence: 90%

“…Personality measures (e.g., Eysenck, 1983, 1994; Lee & Ashton, 2004; McCrae & Costa, 1999; Tellegen & Waller, 2008; Wiggins, & Trapnell, 1996; Zuckerman, 2002) and the lexical analysis of trait terms (e.g., Digman, 1997; Goldberg, 1981; John & Srivastava, 1999; Peabody & De Raad, 2002; Saucier & Ostendorf, 1999) provide considerable evidence for what is termed the Big Five: Extraversion, Neuroticism, Agreeableness, Conscientiousness, and Openness to Experience, with the strongest evidence for the first four. Researchers (e.g., McCrae & Costa, 1999; Hofstee, de Raad, & Goldberg, 1992; Lee & Ashton, 2004; Monroe, Read, & Miller, 2006) have proposed that each of these broad factors has a number of subcomponents.…”

Section: A Neural Network Model Of Personalitymentioning

confidence: 99%

“…It corresponds to Tellegen, Watson, and Clark’s (1999) Negative Activation factor, which represents the extent to which individuals experience actively negative emotions such as distress or fear (Markon, Krueger, & Watson, 2005; Tellegen, 1985; Watson, Wiese, Vaida, & Tellegen, 1999). The earliest, systematic empirical account of the avoidance system may have been provided by Hans Eysenck’s (1967, 1983, 1994) Neuroticism factor (N), which is characterized by anxiety, depression, guilt, low self-esteem, tension, irrationality, shyness, moodiness, and emotionality.…”

Section: A Neural Network Model Of Personalitymentioning

confidence: 99%

See 2 more Smart Citations

A neural network model of the structure and dynamics of human personality.

Read

Monroe

Brownstein

et al. 2010

Psychological Review

220

178

View full text Add to dashboard Cite

We present a neural network model that aims to bridge the historical gap between dynamic and structural approaches to personality. The model integrates work on the structure of the trait lexicon, the neurobiology of personality, temperament, goal-based models of personality, and an evolutionary analysis of motives. It is organized in terms of two overarching motivational systems, an approach and an avoidance system, as well as a general disinhibition and constraint system. Each overarching motivational system influences more specific motives. Traits are modeled in terms of differences in the sensitivities of the motivational systems, the baseline activation of specific motives, and inhibitory strength. The result is a motive-based neural network model of personality based on research about the structure and neurobiology of human personality. The model provides an account of personality dynamics and person-situation interactions and suggests how dynamic processing approaches and dispositional, structural approaches can be integrated in a common framework.

show abstract

Section: A Neural Network Model Of Personalitymentioning

confidence: 90%

Section: A Neural Network Model Of Personalitymentioning

confidence: 99%

Section: A Neural Network Model Of Personalitymentioning

confidence: 99%

See 1 more Smart Citation

A neural network model of the structure and dynamics of human personality.

Read

Monroe

Brownstein

et al. 2010

Psychological Review

220

178

View full text Add to dashboard Cite

show abstract

“…The Virtual Personalities Model drew upon that earlier work to examine in more detail how personality could be understood in terms of the behavior of structured motivational systems. It draws on diverse literatures, summarized elsewhere (e.g., Read, Brown, Wang, & Miller, in press; Read et al, 2010), including those involving the factor structure of personality measures (e.g., Eysenck, 1983, 1994; Lee & Ashton, 2004; McCrae & Costa, 1999; Tellegen, & Waller, 2008; Wiggins & Trapnell, 1996; Zuckerman, 2005), the lexical analysis of trait language (e.g., Digman, 1997; Goldberg, 1981), temperament and neurobiological bases of personality (e.g., Clark & Watson, 2008; Gray, 1987a, 1987b; Gray & McNaughton, 2000; Pickering & Gray, 1999; Rothbart & Bates, 1998; Zuckerman, 2005), an evolutionary analysis of social tasks (e.g., Bugental, 2000; Fiske, 1992; Kenrick & Trost, 1997), taxonomies of human motives (Chulef, Read, & Walsh, 2001; Talevich, Read, Walsh, Iyer, & Chopra, 2017), and our earlier work (e.g., Miller & Read, 1987, 1991; Read, Jones & Miller, 1990; Read & Miller, 1989) on traits as goal-based structures.…”

Section: The Virtual Personalities Neural Network Modelmentioning

confidence: 99%

The Virtual Personalities Neural Network Model: Neurobiological Underpinnings

Read

Brown

Wang

et al. 2018

Personality Neuroscience

View full text Add to dashboard Cite

The Virtual Personalities Model is a motive-based neural network model that provides both a psychological model and a computational implementation that explicates the dynamics and often large within-person variability in behavior that arises over time. At the same time the same model can produce -- across many virtual personalities – between subject variability in behavior that when factor analyzed yields familiar personality structure (e.g., the Big-5). First, we describe our personality model and its implementation as a neural network model. Second, we focus on detailing the neurobiological underpinnings of this model. Third, we examine the learning mechanisms, and their biological substrates, as ways that the model gets “wired up”, discussing Pavlovian and instrumental conditioning, Pavlovian to instrumental transfer (PIT), and habits. Finally, we describe the dynamics of how initial differences in propensities (e.g., dopamine functioning), wiring differences due to experience, and other factors could operate together to develop and change personality over time, and how this might be empirically examined. Thus, our goal is to contribute to the rising chorus of voices seeking a more precise neurobiologically-based science of the complex dynamics underlying personality.

show abstract

“…Over the past 30 years, a significant number of researchers have examined the cognitive, behavioral, and physiological response scales concerning extroversion [4]. In general, studies approved the Eysenck assumption [13], arguing that introverts are more reactive than extroverts and they have lower thresholds.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Effect of Family Atmosphere, School Atmosphere, and Social Support on Aggressiveness and Addiction Preparedness Among Students: The Mediating Role of Extroversion

2020

View full text Add to dashboard Cite

Background: The increased rates of aggression and drug abuse among students are considered an important health issue. Therefore, the present study aimed to investigate the relationship between the emotional atmosphere of the family, the school climate, perceived social support, aggressive behavior, and preparedness for addiction among students, considering the mediating role of extroversion. Methods: This research used the analytical-correlative method. Also, the statistical population included all high school students in Tehran, during the academic year of 2017-2018. Results: The school environment had a significant direct effect on the preparedness for addiction. Besides, we identified the indirect effect of the school environment on irregular drug addiction. The hypothesized model showed the full effect and the nonsignificant direct effect of perceived social support on aggressive behavior. Moreover, there was a significant indirect effect between perceived social support and aggressive behavior. However, there was no direct or indirect effect between perceived social support and preparedness for addiction and the existence of extroversion’s mediating function. Conclusion: Thus, teachers and school administrators are recommended to discuss the psychological environment of the family, the school atmosphere, and perceived social support.

show abstract

Personality

Cited by 89 publications

References 129 publications

A neural network model of the structure and dynamics of human personality.

A neural network model of the structure and dynamics of human personality.

The Virtual Personalities Neural Network Model: Neurobiological Underpinnings

Modeling the Effect of Family Atmosphere, School Atmosphere, and Social Support on Aggressiveness and Addiction Preparedness Among Students: The Mediating Role of Extroversion

Contact Info

Product

Resources

About