Hierarchical Processing of Face Viewpoint in Human Visual Cortex

Axelrod, Vadim; Yovel, Galit

doi:10.1523/jneurosci.4770-11.2012

Cited by 96 publications

(103 citation statements)

References 68 publications

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“…The hierarchical transformations leading to face-selective cells are paralleled by an increase in spatial integration from cells integrating over a few minutes of arc in V1 to cells at the pinnacle of the hierarchy responding within a large portion of the visual field (VF). Research in homologous areas in the human visual cortex is consistent with single-cell data from the monkey IT cortex [22][23][24][25]. Experimentalists invariably identify the temporal cortex as the site of object representation and recognition [15][16][17][20][21][22][23][24][25].…”

Section: Current View Of Object Representation and Recognitionsupporting

confidence: 58%

Space reconstruction by primary visual cortex activity: a parallel, non-computational mechanism of object representation

Gur

2015

Trends in Neurosciences

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Section: Current View Of Object Representation and Recognitionsupporting

confidence: 58%

Space reconstruction by primary visual cortex activity: a parallel, non-computational mechanism of object representation

Gur

2015

Trends in Neurosciences

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“…In sum, our study validated the notion that fMRI MVPA is a powerful tool for fMRI analysis. fMRI MVPA retrieved information about facial viewpoint with high fidelity, for example, extracting a mirror symmetric representation in AL/AF (Kietzmann et al, 2012; see also Axelrod and Yovel, 2012). However, we also unveiled a key limitation of fMRI MVPA in its failure to retrieve information about face identity in regions where singleunit recordings demonstrated that this information was represented in the underlying neuronal populations.…”

Section: Discussionmentioning

confidence: 53%

Single-Unit Recordings in the Macaque Face Patch System Reveal Limitations of fMRI MVPA

2015

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Multivariate pattern analysis (MVPA) of fMRI data has become an important technique for cognitive neuroscientists in recent years; however, the relationship between fMRI MVPA and the underlying neural population activity remains unexamined. Here, we performed MVPA of fMRI data and single-unit data in the same species, the macaque monkey. Facial recognition in the macaque is subserved by a well characterized system of cortical patches, which provided the test bed for our comparison. We showed that neural population information about face viewpoint was readily accessible with fMRI MVPA from all face patches, in agreement with single-unit data. Information about face identity, although it was very strongly represented in the populations of units of the anterior face patches, could not be retrieved from the same data. The discrepancy was especially striking in patch AL, where neurons encode both the identity and viewpoint of human faces. From an analysis of the characteristics of the neural representations for viewpoint and identity, we conclude that fMRI MVPA cannot decode information contained in the weakly clustered neuronal responses responsible for coding the identity of human faces in the macaque brain. Although further studies are needed to elucidate the relationship between information decodable from fMRI multivoxel patterns versus single-unit populations for other variables in other brain regions, our result has important implications for the interpretation of negative findings in fMRI multivoxel pattern analyses.

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“…Logothetis and Sheinberg (1996) concluded that some neurons are view invariant (firing to their preferred stimulus independent of view angle), some are view selective (firing more for some view angles), and that view invariance is more common for familiar objects than novel objects. It is also known that the neural response to faces becomes increasingly view invariant in higher visual regions (Axelrod & Yovel, 2012). Here, we measured whether the neural response to abstract visual symmetry is view invariant or view selective.…”

Section: Introductionmentioning

confidence: 96%

Conditions for view invariance in the neural response to visual symmetry

2014

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Symmetry detection is slow when patterns are distorted by perspective, perhaps due to a time-consuming normalization process, or because discrimination relies on remaining weaker regularities in the retinal image. Participants viewed symmetrical or random dot patterns, either in a frontoparallel or slanted plane (±50°). One group performed a color discrimination task, while another performed a regularity discrimination task. We measured a symmetry-related eventrelated potential (ERP), beginning around 300 ms. During color discrimination, the ERP was reduced for slanted patterns, indexing only the remaining retinal structure. During regularity discrimination, the same ERP was view invariant, and identical for frontoparallel or slanted presentation. We conclude that normalization occurs rapidly during active symmetry discrimination, while symmetry-sensitive networks respond only to regularity in the retinal image when people are attending to other features.Descriptors: Symmetry, Event-related potentials, Sustained posterior negativity, View invariance, Perspective distortionThe two-dimensional retinal projection of an object changes dramatically as the observer adopts different vantage points. This produces novel inputs to the recognition system, but objects are nevertheless identified reliably and rapidly, and this formidable computational feat occurs unconsciously. Logothetis and Sheinberg (1996) concluded that some neurons are view invariant (firing to their preferred stimulus independent of view angle), some are view selective (firing more for some view angles), and that view invariance is more common for familiar objects than novel objects. It is also known that the neural response to faces becomes increasingly view invariant in higher visual regions (Axelrod & Yovel, 2012). Here, we measured whether the neural response to abstract visual symmetry is view invariant or view selective.Many visual systems are highly sensitive to symmetry, perhaps because it helps to identify objects against a background (Machilsen, Pauwels, & Wagemans, 2009), to achieve shape constancy (Pizlo & Stevenson, 1999), or because it indicates reproductive fitness (Tyler, 1995). Bilateral symmetry perception has been demonstrated in insects (Plowright, Evans, Leung, & Collin, 2011), birds (Møller, 1992), and humans (Julesz, 1971; Mach, 1886 Mach, / 1959. In humans, symmetry perception interacts with other figural cues (Bertamini, 2010;Treder & van der Helm, 2007), while models have been developed that extract symmetry from spatial filters (Dakin & Hess, 1997).Most psychophysical and neuroimaging researchers have used symmetric patterns in the frontoparallel plane, which produce a symmetrical retinal projection (e.g., Bertamini, Friedenberg, & Kubovy, 1997;Jacobsen & Höfel, 2003;Royer, 1981;Sasaki, Vanduffel, Knutsen, Tyler, & Tootell, 2005;Wenderoth, 1994). However, the benefits of symmetry perception presuppose the ability to recognize symmetrical objects from multiple viewpoints: After all, an observer will almost never enco...

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Hierarchical Processing of Face Viewpoint in Human Visual Cortex

Cited by 96 publications

References 68 publications

Space reconstruction by primary visual cortex activity: a parallel, non-computational mechanism of object representation

Space reconstruction by primary visual cortex activity: a parallel, non-computational mechanism of object representation

Single-Unit Recordings in the Macaque Face Patch System Reveal Limitations of fMRI MVPA

Conditions for view invariance in the neural response to visual symmetry

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