Independence of viewpoint and identity in face ensemble processing

Sama, Marco A; Nestor, Adrian; Cant, Jonathan S.

doi:10.1167/19.5.2

Cited by 9 publications

(10 citation statements)

References 68 publications

(92 reference statements)

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“…Reports of single orientation under high interference were significantly below chance, indicating that participants were more likely to select the mean value as the target, compared with the correct single item value. This is strong evidence of global interference, and is consistent with previous results showing the influence of the ensemble mean on single-item processing (Brady & Alvarez, 2011 ; Sama et al, 2019 ). Together, these results appear to demonstrate reciprocal interference between global and local processing in ensemble perception.…”

Section: Discussionsupporting

confidence: 92%

“…Elucidating the underlying cognitive mechanisms of this process has received increased attention in recent years, shifting the focus from “what” is extracted to “how” it is extracted. This research has revealed that ensemble processing mechanisms operate independently from traditional single-item processing (Cant, Sun, & Xu, 2015 ; Im & Halberda, 2013 ) as well as across higher- and lower-level stimulus domains (Haberman, Brady, & Alvarez, 2015 ; Sama, Nestor, & Cant, 2019 ). Furthermore, ensemble perception appears to require minimal levels of attention (Chong & Treisman, 2005 ; Ji, Rossi, & Pourtois, 2018 ; Khayat & Hochstein, 2018 ; Peng, Kuang, & Hu, 2019 ; Utochkin & Tiurina, 2014 ; but see Jackson-Nielsen, Cohen, & Pitts, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

“…Second, what is the relationship between the processing of global summary statistics and the details of local items? Studies show that single-item reports tend to be biased to the ensemble mean (Brady & Alvarez, 2011 ; de Fockert & Wolfenstein, 2009 ; Maule, Witzel, & Franklin, 2014 ; Sama et al, 2019 ). The reverse may also occur, wherein focused attention on single items biases reports of the ensemble mean (de Fockert & Marchant, 2008 ), either through primacy and recency effects during serial presentation (Hubert-Wallander & Boynton, 2015 ), or if certain single items are intrinsically valuable (Dodgson & Raymond, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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Global and local interference effects in ensemble encoding are best explained by interactions between summary representations of the mean and the range

Sama

Srikanthan

Nestor

et al. 2021

Atten Percept Psychophys

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Through ensemble encoding, the visual system compresses redundant statistical properties from multiple items into a single summary metric (e.g., average size). Numerous studies have shown that global summary information is extracted quickly, does not require access to single-item representations, and often interferes with reports of single items from the set. Yet a thorough understanding of ensemble processing would benefit from a more extensive investigation at the local level. Thus, the purpose of this study was to provide a more critical inspection of global-local processing in ensemble perception. Taking inspiration from Navon (Cognitive Psychology, 9(3), 353-383, 1977), we employed a novel paradigm that independently manipulates the degree of interference at the global (mean) or local (single item) level of the ensemble. Initial results were consistent with reciprocal interference between global and local ensemble processing. However, further testing revealed that local interference effects were better explained by interference from another summary statistic, the range of the set. Furthermore, participants were unable to disambiguate single items from the ensemble display from other items that were within the ensemble range but, critically, were not actually present in the ensemble. Thus, it appears that local item values are likely inferred based on their relationship to higher-order summary statistics such as the range and the mean. These results conflict with claims that local information is captured alongside global information in summary representations. In such studies, successful identification of set members was not compared with misidentification of items within the range, but which were nevertheless not presented within the set.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Global and local interference effects in ensemble encoding are best explained by interactions between summary representations of the mean and the range

Sama

Srikanthan

Nestor

et al. 2021

Atten Percept Psychophys

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“…Regarding ensembles, while extensive behavioral work has documented our ability to extract summary representations from groups of faces (de Fockert & Wolfenstein, ; Haberman, Brady, & Alvarez, ; Neumann, Schweinberger, & Burton, ; Sama, Nestor, & Cant, ; Yamanashi Leib et al, ), little is known about their neural underpinnings. Interestingly, recent fMRI work (Im et al, ) found that face ensembles exhibit marked reliance on dorsal stream areas along with a right hemispheric advantage.…”

Section: Discussionmentioning

confidence: 99%

A multivariate investigation of visual word, face, and ensemble processing: Perspectives from EEG‐based decoding and feature selection

et al. 2019

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Dan Nemrodov and Shouyu Ling are contributed equally to this work.The University of Toronto has filed a U.S. patent application that includes portions of the method for feature selection described here. Adrian Nestor and Dan Nemrodov are co-inventors on this patent. AbstractRecent investigations have focused on the spatiotemporal dynamics of visual recognition by appealing to pattern analysis of EEG signals. While this work has established the ability to decode identity-level information (such as the identity of a face or of a word) from neural signals, much less is known about the precise nature of the signals that support such feats, their robustness across visual categories, or their consistency across human participants. Here, we address these questions through the use of EEG-based decoding and multivariate feature selection as applied to three visual categories: words, faces and face ensembles (i.e., crowds of faces). Specifically, we use recursive feature elimination to estimate the diagnosticity of time and frequencybased EEG features for identity-level decoding across three datasets targeting each of the three categories. We then relate feature diagnosticity across categories and across participants while, also, aiming to increase decoding performance and reliability. Our investigation shows that word and face processing are similar in their reliance on spatiotemporal information provided by occipitotemporal channels. In contrast, ensemble processing appears to also rely on central channels and exhibits a similar profile with word processing in the frequency domain. Further, we find that feature diagnosticity is stable across participants and is even capable of supporting cross-participant feature selection, as demonstrated by systematic boosts in decoding accuracy and feature reduction. Thus, our investigation sheds new light on the nature and the structure of the information underlying identity-level visual processing as well as on its generality across categories and participants.

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“…Since the spatial organization of items in an ensemble display is typically random, these displays lack drastic size-contrast cues and the structured organization of elements seen in typical visual illusions (e.g., the Ebbinghaus illusion). Yet ensemble displays still impart a strong perceptual bias, in that the perception of a feature value of a single item from the set is routinely pulled toward the average value of the set (Brady and Alvarez, 2011;Sama et al, 2019). Does this bias toward the ensemble average influence grasping?…”

Section: Introductionmentioning

confidence: 99%

Grasping of Real-World Objects Is Not Biased by Ensemble Perception

et al. 2021

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The visual system is known to extract summary representations of visually similar objects which bias the perception of individual objects toward the ensemble average. Although vision plays a large role in guiding action, less is known about whether ensemble representation is informative for action. Motor behavior is tuned to the veridical dimensions of objects and generally considered resistant to perceptual biases. However, when the relevant grasp dimension is not available or is unconstrained, ensemble perception may be informative to behavior by providing gist information about surrounding objects. In the present study, we examined if summary representations of a surrounding ensemble display influenced grip aperture and orientation when participants reached-to-grasp a central circular target which had an explicit size but importantly no explicit orientation that the visuomotor system could selectively attend to. Maximum grip aperture and grip orientation were not biased by ensemble statistics during grasping, although participants were able to perceive and provide manual estimations of the average size and orientation of the ensemble display. Support vector machine classification of ensemble statistics achieved above-chance classification accuracy when trained on kinematic and electromyography data of the perceptual but not grasping conditions, supporting our univariate findings. These results suggest that even along unconstrained grasping dimensions, visually-guided behaviors toward real-world objects are not biased by ensemble processing.

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Independence of viewpoint and identity in face ensemble processing

Cited by 9 publications

References 68 publications

Global and local interference effects in ensemble encoding are best explained by interactions between summary representations of the mean and the range

Global and local interference effects in ensemble encoding are best explained by interactions between summary representations of the mean and the range

A multivariate investigation of visual word, face, and ensemble processing: Perspectives from EEG‐based decoding and feature selection

Grasping of Real-World Objects Is Not Biased by Ensemble Perception

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