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Recognizing Facial Slivers

Gilad-Gutnick, Sharon and Harmatz, Elia Samuel and Tsourides, Kleovoulos and Yovel, Galit and Sinha, Pawan (2018) Recognizing Facial Slivers. Journal of Cognitive Neuroscience, 30 (7). pp. 951-962. ISSN 0898-929X.

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We report here an unexpectedly robust ability of healthy human participants (n = 40) to recognize extremely distorted needle-like facial images, challenging the well-entrenched notion that veridical spatial configuration is necessary for extracting facial identity. In face identification tasks of parametrically compressed internal and external features, we found that the sum of performances on each cue falls significantly short of performance on full faces, despite the equal visual information available from both measures (with full faces essentially being a superposition of internal and external features). We hypothesize that this large deficit stems from the use of positional information about how the internal features are positioned relative to the external features. To test this, we systematically changed the relations between internal and external features and found preferential encoding of vertical but not horizontal spatial relationships in facial representations (n = 20). Finally, we employ magnetoencephalography imaging (n = 20) to demonstrate a close mapping between the behavioral psychometric curve and the amplitude of the M250 face familiarity, but not M170 face-sensitive evoked response field component, providing evidence that the M250 can be modulated by faces that are perceptually identifiable, irrespective of extreme distortions to the face's veridical configuration. We theorize that the tolerance to compressive distortions has evolved from the need to recognize faces across varying viewpoints. Our findings help clarify the important, but poorly defined, concept of facial configuration and also enable an association between behavioral performance and previously reported neural correlates of face perception.

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Additional Information:© 2018 Massachusetts Institute of Technology. Posted Online April 18, 2018. We thank Drs. Richard Held, Ming Meng, Sidney Diamond, Benjamin Balas, and Amos Gutnick for their helpful comments on this work. This work was supported by NEI (NIH) R01 EY020517 Scholar Award from James McDonnell Foundation to P. S. S. G., P. Y., and P. S. designed the study, S. G., K. T. and S. H. collected data, S. G. and K. T. analyzed data, and S. G., K. T., G. Y., and P. S. wrote the manuscript.
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NIHR01 EY020517
James McDonnell FoundationUNSPECIFIED
Issue or Number:7
Record Number:CaltechAUTHORS:20180503-161153177
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:86218
Deposited By: Tony Diaz
Deposited On:03 May 2018 23:52
Last Modified:29 Jul 2020 22:28

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