Scene Clutter and Attention Differentially Affect Object Category and Location Representations

Graumann, Monika; Ciuffi, Caterina; Cichy, Radoslaw Martin

doi:10.1167/19.10.171a

Cited by 1 publication

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“…In cluttered scenes, objects may not be fully separated from the background without the formation of some object representation, resulting in a need to represent nonidentity features at higher levels of processing. Supporting this, Graumann et al (2019) reported stronger position representation in higher ventral regions for objects in cluttered than in uncluttered scenes. Thus, scene clutter may account for the discrepancy in neural data between Hong et al (2016) and our study.…”

Section: Discussionmentioning

confidence: 62%

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks

Vaziri-Pashkam

2021

J. Neurosci.

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A visual object is characterized by multiple visual features, including its identity, position and size. Despite the usefulness of identity and nonidentity features in vision and their joint coding throughout the primate ventral visual processing pathway, they have so far been studied relatively independently. Here in both female and male human participants, the coding of identity and nonidentity features was examined together across the human ventral visual pathway. The nonidentity features tested included two Euclidean features (position and size) and two non-Euclidean features (image statistics and spatial frequency (SF) content of an image). Overall, identity representation increased and nonidentity feature representation decreased along the ventral visual pathway, with identity outweighing the non-Euclidean but not the Euclidean features at higher levels of visual processing. In 14 convolutional neural networks (CNNs) pretrained for object categorization with varying architecture, depth, and with/without recurrent processing, nonidentity feature representation showed an initial large increase from early to mid-stage of processing, followed by a decrease at later stages of processing, different from brain responses. Additionally, from lower to higher levels of visual processing, position became more underrepresented and image statistics and SF became more overrepresented compared with identity in CNNs than in the human brain. Similar results were obtained in a CNN trained with stylized images that emphasized shape representations. Overall, by measuring the coding strength of object identity and nonidentity features together, our approach provides a new tool for characterizing feature coding in the human brain and the correspondence between the brain and CNNs.

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Section: Discussionmentioning

confidence: 62%

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks

Vaziri-Pashkam

2021

J. Neurosci.

View full text Add to dashboard Cite

show abstract

Scene Clutter and Attention Differentially Affect Object Category and Location Representations

Cited by 1 publication

References 0 publications

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks

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