The relation between holistic processing as measured by three composite tasks and face processing: A latent variable modeling approach

Ventura, Paulo; Ngan, Vince; Pereira, Alexandre; Cruz, Francisco; Guerreiro, José C.; Rosário, Vivienne; Delgado, João; Faustino, Bruno; Barros, Marta Silene Ferreira; Domingues, Miguel; Wong, Alan C.-N.

doi:10.3758/s13414-022-02543-x

Cited by 4 publications

(1 citation statement)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The construct validity of any measure of HP is difficult to establish without these relationships. Even different versions of the same task can fail to correlate (Wang et al, 2016;Ventura et al, 2022). It is not always clear whether the reasons are substantive (Redick and Lindsey, 2013) and pointing to problems with the construct legitimacy (Stone, 2019) of HP, or are methodological (Draheim et al, 2019) and can eventually be resolved (Feest, 2020).…”

Section: Hp: When Construct Validity Is Not Achievedmentioning

confidence: 99%

Mini review: Individual differences and domain-general mechanisms in object recognition

Gauthier¹,

Cha²,

Chang³

2022

Front. Cognit.

View full text Add to dashboard Cite

Over the past three decades, object recognition moved away from domain-general questions, favoring investigation of putative category-specific mechanisms. But growing interest in individual differences in object recognition is putting the spotlight back on domain-general mechanisms, supporting their existence rather than simply assuming them. We reflect on the relative progress in three areas of visual cognition—visual object recognition, ensemble perception, and holistic processing. The study of visual object recognition abilities, based on latent variable modeling, provides strong evidence for domain-general mechanisms with neural correlates in visual areas and contributions to many real-world visual problems. The study of ensemble perception includes evidence for interesting individual differences but the structure of abilities is unclear, with a need for multivariate investigation. The study of individual differences in holistic processing has been unable to establish the construct validity of its measures. Each of these areas is at a different stage of understanding relevant underlying abilities, each one helping to illustrate different challenges that may be unfamiliar to experimentalists.

show abstract

Section: Hp: When Construct Validity Is Not Achievedmentioning

confidence: 99%

Mini review: Individual differences and domain-general mechanisms in object recognition

Gauthier¹,

Cha²,

Chang³

2022

Front. Cognit.

View full text Add to dashboard Cite

show abstract

Manipulating and measuring variation in deep neural network (DNN) representations of objects

Chow,

Palmeri

2024

Cognition

View full text Add to dashboard Cite

Manipulating and Measuring Variation In Deep Neural Network (DNN) Representations of Objects

Chow,

Palmeri

2023

Preprint

View full text Add to dashboard Cite

The relation between holistic processing as measured by three composite tasks and face processing: A latent variable modeling approach

Cited by 4 publications

References 56 publications

Mini review: Individual differences and domain-general mechanisms in object recognition

Mini review: Individual differences and domain-general mechanisms in object recognition

Manipulating and measuring variation in deep neural network (DNN) representations of objects

Manipulating and Measuring Variation In Deep Neural Network (DNN) Representations of Objects

Contact Info

Product

Resources

About

The relation between holistic processing as measured by three composite tasks and face processing: A latent variable modeling approach

Cited by 4 publications

References 56 publications

Mini review: Individual differences and domain-general mechanisms in object recognition

Mini review: Individual differences and domain-general mechanisms in object recognition

Manipulating and measuring variation in deep neural network (DNN) representations of objects

Manipulating and Measuring Variation In&nbsp;Deep Neural Network (DNN) Representations of Objects

Contact Info

Product

Resources

About

Manipulating and Measuring Variation In Deep Neural Network (DNN) Representations of Objects