Reading in developmental prosopagnosia: Evidence for a dissociation between word and face recognition.

Starrfelt, Randi; Klargaard, Solja K.; Petersen, Anders; Gerlach, Christian

doi:10.1037/neu0000428

Cited by 30 publications

(31 citation statements)

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“…This comparison is particularly interesting as the DPs performed the exact same tests as did the HP group, and in many respects seem to pose a mirror image of the HPs. In the first section below, we present the results for the group comparisons, which for the most part have been reported elsewhere (Gerlach et al, 2017Starrfelt et al, 2018). The dissociations analyses, however, have not been presented previously.…”

Section: Do Low-performers Differ Qualitatively From Others In Face Pmentioning

confidence: 99%

“…The control sample comprised 20 individuals. Note that data from these participants have been reported in previous publications (Gerlach, Klargaard, Petersen, & Starrfelt, 2017;Starrfelt, Klargaard, Petersen, & Gerlach, 2018). They are included here for a direct comparison with the HPs included in the present study.…”

Section: Low Performers (Developmental Prosopagnosics (Dp))mentioning

confidence: 99%

“…RTs were trimmed by excluding RTs from trials deviating more than 2.5 SD for each individual at each word length, to exclude voice key errors. We included this task to examine whether the HPs proficiency would extend to processing of a stimulus category (words) that is usually assumed to be rather independent from face processing ability; also in DP (Burns et al, 2017;Rubino, Corrow, Corrow, Duchaine, & Barton, 2016;Starrfelt et al, 2018).…”

Section: Reading Taskmentioning

confidence: 99%

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The good, the bad, and the average: Characterizing the relationship between face and object processing across the face recognition spectrum

2019

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Face recognition skills vary considerably both in the normal population and in various clinical groups, and understanding the cognitive mechanisms contributing to this variability is important. In the present study, we investigate whether a group of good face recognizers (high performers; HPs) perform qualitatively differently from a control group on tests of face, object and word recognition, and also compare them to a group of developmental prosopagnosics (DPs). Through a series of experiments, we (i) examine whether HPs are better than control subjects in face and object recognition, (ii) investigate if any dissociations 2 among face, object, and word processing tasks can be demonstrated in the HPs, and (iii) compare the performance of the HPs to a group of poor face recognizers namely a group of DPs. Data from this DP group have previously been reported, but the analyses presented here are new. We find that HPs were significantly better than matched control subjects on tests of face and object recognition including a reading task, but they did not show significantly larger inversion effects on typical tests of face processing (the CFMT and the CFPT). There was no evidence of dissociations between face and object processing in the HPs when compared to controls, indicating superior performance across visual domains. In the DP group, however, we found significant dissociations between face and object recognition performance on a group level, indicating that face processing is disproportionally affected. On this basis, we propose that superior face processing in HPs rely on more general cognitive or perceptual processes shared with object processing. Hence, while face processing in DPs seems qualitatively different from the normal population, there is no such difference between average and high performing face recognizers. Thus, what underlies superior face processing in HPs might also underlie their superior performance with other stimulus classes and might be conceived as a general factor in the visual domain, a VG-factor, akin to the G factor in intelligence.

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Section: Do Low-performers Differ Qualitatively From Others In Face Pmentioning

confidence: 99%

Section: Low Performers (Developmental Prosopagnosics (Dp))mentioning

confidence: 99%

Section: Reading Taskmentioning

confidence: 99%

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The good, the bad, and the average: Characterizing the relationship between face and object processing across the face recognition spectrum

2019

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“…The severity of the face recognition disorder in such individuals can be as severe as that noted in individuals with a frank RH VOTC lesion and, like those individuals, These individuals rely on voice and other cues such as hairstyle to support individual face recognition Barton, Albonico, Susilo, Duchaine, & Corrow, 2019;Rosenthal et al, 2017). In contrast with the association of word and face recognition deficits in DD, as reviewed in Shared Representations With Weighting section above, there are now several studies of individuals with CP which have demonstrated a dissociation between face and word recognition (Burns et al, 2017;Rubino, Corrow, Corrow, Duchaine, & Barton, 2016;Starrfelt, Klargaard, Petersen, & Gerlach, 2018).…”

Section: Patients With a Selective Impairment Of Either Face Or Word mentioning

confidence: 99%

Hemispheric Organization for Visual Object Recognition: A Theoretical Account and Empirical Evidence

Behrmann

Plaut

2020

Perception

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Despite the similarity in structure, the hemispheres of the human brain have somewhat different functions. A traditional view of hemispheric organization asserts that there are independent and largely lateralized domain-specific regions in ventral occipitotemporal (VOTC), specialized for the recognition of distinct classes of objects. Here, we offer an alternative account of the organization of the hemispheres, with a specific focus on face and word recognition. This alternative account relies on three computational principles: distributed representations and knowledge, cooperation and competition between representations, and topography and proximity. The crux is that visual recognition results from a network of regions with graded functional specialization that is distributed across both hemispheres. Specifically, the claim is that face recognition, which is acquired relatively early in life, is processed by VOTC regions in both hemispheres. Once literacy is acquired, word recognition, which is co-lateralized with language areas, primarily engages the left VOTC and, consequently, face recognition is primarily, albeit not exclusively, mediated by the right VOTC. We review psychological and neural evidence from a range of studies conducted with normal and brain-damaged adults and children and consider findings which challenge this account. Last, we offer suggestions for future investigations whose findings may further refine this account.

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“…The results above are consistent with intermingling but distinct neural resources underlying the processing of different categories (Plaut & Behrmann, ). For single faces and words, such intermingling has been previously suggested by fMRI (Mei et al, ; Nestor et al, ) and neuropsychological studies (Albonico & Barton, ; Gerlach, Marstrand, Starrfelt, & Gade, ; Sigurdardottir, Ívarsson, Kristinsdóttir, & Kristjánsson, , but see Starrfelt, Klargaard, Petersen, & Gerlach, ). Moreover, prior EEG work has documented the reliance of these two categories on occipitotemporal channels around 170 ms as reflected, for instance, by the importance of the N170 ERP component for faces (Bentin, Allison, Puce, Perez, & McCarthy, ; Ince et al, ; Rossion, Joyce, Cottrell, & Tarr, ), words (Bentin, Mouchetant‐Rostaing, Giard, Echallier, & Pernier, ; Maurer, Zevin, & McCandliss, ), and, more generally, for visual expertise (Tanaka & Curran, ).…”

Section: Discussionmentioning

confidence: 54%

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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Reading in developmental prosopagnosia: Evidence for a dissociation between word and face recognition.

Cited by 30 publications

References 53 publications

The good, the bad, and the average: Characterizing the relationship between face and object processing across the face recognition spectrum

The good, the bad, and the average: Characterizing the relationship between face and object processing across the face recognition spectrum

Hemispheric Organization for Visual Object Recognition: A Theoretical Account and Empirical Evidence

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

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