1932

Abstract

Congenital prosopagnosia (CP), a life-long impairment in face processing that occurs in the absence of any apparent brain damage, provides a unique model in which to explore the psychological and neural bases of normal face processing. The goal of this review is to offer a theoretical and conceptual framework that may account for the underlying cognitive and neural deficits in CP. This framework may also provide a novel perspective in which to reconcile some conflicting results that permits the expansion of the research in this field in new directions. The crux of this framework lies in linking the known behavioral and neural underpinnings of face processing and their impairments in CP to a model incorporating grid cell–like activity in the entorhinal cortex. Moreover, it stresses the involvement of active, spatial scanning of the environment with eye movements and implicates their critical role in face encoding and recognition. To begin with, we describe the main behavioral and neural characteristics of CP, and then lay down the building blocks of our proposed model, referring to the existing literature supporting this new framework. We then propose testable predictions and conclude with open questions for future research stemming from this model.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-vision-113020-012740
2021-09-15
2024-06-20
Loading full text...

Full text loading...

/deliver/fulltext/vision/7/1/annurev-vision-113020-012740.html?itemId=/content/journals/10.1146/annurev-vision-113020-012740&mimeType=html&fmt=ahah

Literature Cited

  1. Arcaro MJ, Schade PF, Vincent JL, Ponce CR, Livingstone MS. 2017. Seeing faces is necessary for face-domain formation. Nat. Neurosci. 20:1404–12
    [Google Scholar]
  2. Arizpe J, Walsh V, Yovel G, Baker CI. 2017. The categories, frequencies, and stability of idiosyncratic eye-movement patterns to faces. Vis. Res. 141:191–203
    [Google Scholar]
  3. Arizpe JM, Noles DL, Tsao JW, Chan AW. 2019. Eye movement dynamics differ between encoding and recognition of faces. Vision 3:9
    [Google Scholar]
  4. Avidan G, Behrmann M. 2009. Functional MRI reveals compromised neural integrity of the face processing network in congenital prosopagnosia. Curr. Biol. 19:1146–50
    [Google Scholar]
  5. Avidan G, Behrmann M. 2014. Structural and functional impairment of the face processing network in congenital prosopagnosia. Front. Biosci. 1:236–57
    [Google Scholar]
  6. Avidan G, Hasson U, Malach R, Behrmann M. 2005. Detailed exploration of face-related processing in congenital prosopagnosia: 2. Functional neuroimaging findings. J. Cogn. Neurosci. 17:1150–67
    [Google Scholar]
  7. Avidan G, Tanzer M, Behrmann M. 2011. Impaired holistic processing in congenital prosopagnosia. Neuropsychologia 49:2541–52
    [Google Scholar]
  8. Avidan G, Tanzer M, Hadj-Bouziane F, Liu N, Ungerleider LG, Behrmann M. 2014. Selective dissociation between core and extended regions of the face processing network in congenital prosopagnosia. Cereb. Cortex 24:1565–78
    [Google Scholar]
  9. Barton JJ, Corrow SL. 2016. The problem of being bad at faces. Neuropsychologia 89:119–24
    [Google Scholar]
  10. Bate S, Adams A, Bennetts R, Line H. 2019. Developmental prosopagnosia with concurrent topographical difficulties: a case report and virtual reality training program. Neuropsychol. Rehabil. 29:1290–312
    [Google Scholar]
  11. Behrmann M, Avidan G, Gao F, Black S. 2007. Structural imaging reveals anatomical alterations in inferotemporal cortex in congenital prosopagnosia. Cereb. Cortex 17:2354–63
    [Google Scholar]
  12. Behrmann M, Avidan G, Marotta JJ, Kimchi R. 2005. Detailed exploration of face-related processing in congenital prosopagnosia: 1. Behavioral findings. J. Cogn. Neurosci. 17:1130–49
    [Google Scholar]
  13. Behrmann M, Lee AC, Geskin JZ, Graham KS, Barense MD 2016. Temporal lobe contribution to perceptual function: a tale of three patient groups. Neuropsychologia 90:33–45
    [Google Scholar]
  14. Bellmund JLS, Deuker L, Navarro Schröder T, Doeller CF 2016. Grid-cell representations in mental simulation. eLife 5:e17089
    [Google Scholar]
  15. Bicanski A, Burgess N. 2019. A computational model of visual recognition memory via grid cells. Curr. Biol. 29:979–90.e4
    [Google Scholar]
  16. Bobak AK, Parris BA, Gregory NJ, Bennetts RJ, Bate S. 2017. Eye-movement strategies in developmental prosopagnosia and “super” face recognition. Q. J. Exp. Psychol. 70:201–17
    [Google Scholar]
  17. Bottini R, Doeller CF. 2020. Knowledge across reference frames: cognitive maps and image spaces. Trends Cogn. Sci. 24:606–19
    [Google Scholar]
  18. Bowles DC, McKone E, Dawel A, Duchaine B, Palermo R et al. 2009. Diagnosing prosopagnosia: effects of ageing, sex, and participant-stimulus ethnic match on the Cambridge Face Memory Test and Cambridge Face Perception Test. Cogn. Neuropsychol. 26:423–55
    [Google Scholar]
  19. Bussey TJ, Saksida LM. 2002. The organization of visual object representations: a connectionist model of effects of lesions in perirhinal cortex. Eur. J. Neurosci. 15:355–64
    [Google Scholar]
  20. Bussey TJ, Saksida LM, Murray EA. 2003. Impairments in visual discrimination after perirhinal cortex lesions: testing “declarative” versus “perceptual-mnemonic” views of perirhinal cortex function. Eur. J. Neurosci. 17:649–60
    [Google Scholar]
  21. Chang L, Tsao DY. 2017. The code for facial identity in the primate brain. Cell 169:1013–28.e14
    [Google Scholar]
  22. Cohen Kadosh K, Henson RN, Cohen Kadosh R, Johnson MH, Dick F 2011. Task-dependent activation of face-sensitive cortex: an fMRI adaptation study. J. Cogn. Neurosci. 22:903–17
    [Google Scholar]
  23. Collins JA, Olson IR. 2014. Beyond the FFA: the role of the ventral anterior temporal lobes in face processing. Neuropsychologia 61:65–79
    [Google Scholar]
  24. Corrow JC, Corrow SL, Lee E, Pancaroglu R, Burles F et al. 2016. Getting lost: topographic skills in acquired and developmental prosopagnosia. Cortex 76:89–103
    [Google Scholar]
  25. Dalrymple KA, Palermo R. 2016. Guidelines for studying developmental prosopagnosia in adults and children. Wiley Interdiscip. Rev. Cogn. Sci. 7:73–87
    [Google Scholar]
  26. Davies-Thompson J, Andrews TJ. 2012. Intra- and interhemispheric connectivity between face-selective regions in the human brain. J. Neurophysiol. 108:3087–95
    [Google Scholar]
  27. DeGutis J, Cohan S, Nakayama K. 2014. Holistic face training enhances face processing in developmental prosopagnosia. Brain 137:1781–98
    [Google Scholar]
  28. DiCarlo JJ, Cox DD. 2007. Untangling invariant object recognition. Trends Cogn. Sci. 11:333–41
    [Google Scholar]
  29. Duchaine BC, Nakayama K. 2006. Developmental prosopagnosia: a window to content-specific face processing. Curr. Opin. Neurobiol. 16:166–73
    [Google Scholar]
  30. Fairhall SL, Ishai A. 2007. Effective connectivity within the distributed cortical network for face perception. Cereb. Cortex 17:2400–6
    [Google Scholar]
  31. Fisher K, Towler J, Rossion B, Eimer M. 2020. Neural responses in a fast periodic visual stimulation paradigm reveal domain-general visual discrimination deficits in developmental prosopagnosia. Cortex 133:76–102
    [Google Scholar]
  32. Furl N, Garrido L, Dolan RJ, Driver J, Duchaine B. 2011. Fusiform gyrus face selectivity relates to individual differences in facial recognition ability. J. Cogn. Neurosci. 23:1723–40
    [Google Scholar]
  33. Furl N, Hadj-Bouziane F, Liu N, Averbeck BB, Ungerleider LG. 2012. Dynamic and static facial expressions decoded from motion-sensitive areas in the macaque monkey. J. Neurosci. 32:15952–62
    [Google Scholar]
  34. Garrido L, Furl N, Draganski B, Weiskopf N, Stevens J et al. 2009. Voxel-based morphometry reveals reduced grey matter volume in the temporal cortex of developmental prosopagnosics. Brain 132:3443–55
    [Google Scholar]
  35. Gerlach C, Klargaard SK, Petersen A, Starrfelt R. 2017. Delayed processing of global shape information in developmental prosopagnosia. PLOS ONE 12:e0189253
    [Google Scholar]
  36. Gerlach C, Klargaard SK, Starrfelt R. 2016. On the relation between face and object recognition in developmental prosopagnosia: no dissociation but a systematic association. PLOS ONE 11:e0165561
    [Google Scholar]
  37. Gerlach C, Starrfelt R 2021. Patterns of perceptual performance in developmental prosopagnosia: an in-depth case series. Cogn. Neuropsychol 38:27–49
    [Google Scholar]
  38. Geskin J, Behrmann M. 2017. Congenital prosopagnosia without object agnosia? A literature review. Cogn. Neuropsychol. 35:4–54
    [Google Scholar]
  39. Gobbini MI, Haxby JV. 2007. Neural systems for recognition of familiar faces. Neuropsychologia 45:32–41
    [Google Scholar]
  40. Gomez J, Drain A, Jeska B, Natu VS, Barnett M, Grill-Spector K. 2019. Development of population receptive fields in the lateral visual stream improves spatial coding amid stable structural-functional coupling. NeuroImage 188:59–69
    [Google Scholar]
  41. Gomez J, Natu V, Jeska B, Barnett M, Grill-Spector K. 2018. Development differentially sculpts receptive fields across early and high-level human visual cortex. Nat. Commun. 9:788
    [Google Scholar]
  42. Gomez J, Pestilli F, Witthoft N, Golarai G, Liberman A et al. 2015. Functionally defined white matter reveals segregated pathways in human ventral temporal cortex associated with category-specific processing. Neuron 85:216–27
    [Google Scholar]
  43. Grill-Spector K, Weiner KS, Kay K, Gomez J. 2017. The functional neuroanatomy of human face perception. Annu. Rev. Vis. Sci. 3:167–96
    [Google Scholar]
  44. Grimaldi P, Saleem KS, Tsao D. 2016. Anatomical connections of the functionally defined “face patches” in the macaque monkey. Neuron 90:1325–42
    [Google Scholar]
  45. Gschwind M, Pourtois G, Schwartz S, Van De Ville D, Vuilleumier P. 2012. White-matter connectivity between face-responsive regions in the human brain. Cereb. Cortex 22:1564–76
    [Google Scholar]
  46. Hadj-Bouziane F, Liu N, Bell AH, Gothard KM, Luh WM et al. 2012. Amygdala lesions disrupt modulation of functional MRI activity evoked by facial expression in the monkey inferior temporal cortex. PNAS 109:E3640–48
    [Google Scholar]
  47. Hahn CA, O'Toole AJ. 2017. Recognizing approaching walkers: neural decoding of person familiarity in cortical areas responsive to faces, bodies, and biological motion. NeuroImage 146:859–68
    [Google Scholar]
  48. Hasson U, Avidan G, Deouell LY, Bentin S, Malach R. 2003. Face-selective activation in a congenital prosopagnosic subject. J. Cogn. Neurosci. 15:419–31
    [Google Scholar]
  49. Haxby JV, Hoffman EA, Gobbini MI. 2000. The distributed human neural system for face perception. Trends Cogn. Sci. 4:223–33
    [Google Scholar]
  50. Henriksson L, Mur M, Kriegeskorte N. 2015. Faciotopy—a face-feature map with face-like topology in the human occipital face area. Cortex 72:156–67
    [Google Scholar]
  51. Hesse JK, Tsao DY. 2020. The macaque face patch system: a turtle's underbelly for the brain. Nat. Rev. Neurosci. 21:695–716
    [Google Scholar]
  52. Hessels RS. 2020. How does gaze to faces support face-to-face interaction? A review and perspective. Psychon. Bull. Rev. 27:856–81
    [Google Scholar]
  53. Hsiao JH, Cottrell G. 2008. Two fixations suffice in face recognition. Psychol. Sci. 19:998–1006
    [Google Scholar]
  54. Jacobs J, Lee SA. 2016. Spatial cognition: grid cells support imagined navigation. Curr. Biol. 26:R277–79
    [Google Scholar]
  55. Ji S, Yang M, Yu K 2013. 3D convolutional neural networks for human action recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35:221–31
    [Google Scholar]
  56. Jiahui G, Yang H, Duchaine B 2018. Developmental prosopagnosics have widespread selectivity reductions across category-selective visual cortex. PNAS 115:E6418–27
    [Google Scholar]
  57. Joseph JE, Swearingen JE, Clark JD, Benca CE, Collins HR et al. 2012. The changing landscape of functional brain networks for face processing in typical development. NeuroImage 63:1223–36
    [Google Scholar]
  58. Julian JB, Keinath AT, Frazzetta G, Epstein RA. 2018. Human entorhinal cortex represents visual space using a boundary-anchored grid. Nat. Neurosci. 21:191–94
    [Google Scholar]
  59. Kar K, Kubilius J, Schmidt K, Issa EB, DiCarlo JJ. 2019. Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior. Nat. Neurosci. 22:974–83
    [Google Scholar]
  60. Killian NJ, Jutras MJ, Buffalo EA. 2012. A map of visual space in the primate entorhinal cortex. Nature 491:761–64
    [Google Scholar]
  61. Klargaard SK, Starrfelt R, Petersen A, Gerlach C. 2016. Topographic processing in developmental prosopagnosia: preserved perception but impaired memory of scenes. Cogn. Neuropsychol. 33:405–13
    [Google Scholar]
  62. Kriegeskorte N, Formisano E, Sorger B, Goebel R 2007. Individual faces elicit distinct response patterns in human anterior temporal cortex. PNAS 104:20600–5
    [Google Scholar]
  63. Landi SM, Freiwald WA. 2017. Two areas for familiar face recognition in the primate brain. Science 357:591–95
    [Google Scholar]
  64. Lange J, de Lussanet M, Kuhlmann S, Zimmermann A, Lappe M et al. 2009. Impairments of biological motion perception in congenital prosopagnosia. PLOS ONE 4:e7414
    [Google Scholar]
  65. LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
    [Google Scholar]
  66. Lewis M, Purdy S, Ahmad S, Hawkins J 2019. Locations in the neocortex: a theory of sensorimotor object recognition using cortical grid cells. Front. Neural Circuits 13:22
    [Google Scholar]
  67. Loftus GR, Harley EM. 2005. Why is it easier to identify someone close than far away?. Psychon. Bull. Rev. 12:43–65
    [Google Scholar]
  68. Lohse M, Garrido L, Driver J, Dolan RJ, Duchaine BC, Furl N. 2016. Effective connectivity from early visual cortex to posterior occipitotemporal face areas supports face selectivity and predicts developmental prosopagnosia. J. Neurosci. 36:3821–28
    [Google Scholar]
  69. Malaspina M, Albonico A, Toneatto C, Daini R. 2017. What do eye movements tell us about the visual perception of individuals with congenital prosopagnosia?. Neuropsychology 31:546–63
    [Google Scholar]
  70. McKone E. 2009. Holistic processing for faces operates over a wide range of sizes but is strongest at identification rather than conversational distances. Vis. Res. 49:268–83
    [Google Scholar]
  71. Moeller S, Freiwald WA, Tsao DY. 2008. Patches with links: a unified system for processing faces in the macaque temporal lobe. Science 320:1355–59
    [Google Scholar]
  72. Murray EA, Bussey TJ, Saksida LM. 2007. Visual perception and memory: a new view of medial temporal lobe function in primates and rodents. Annu. Rev. Neurosci. 30:99–122
    [Google Scholar]
  73. Nau M, Navarro Schroder T, Bellmund JLS, Doeller CF 2018. Hexadirectional coding of visual space in human entorhinal cortex. Nat. Neurosci. 21:188–90
    [Google Scholar]
  74. Nestor A, Plaut DC, Behrmann M 2011. Unraveling the distributed neural code of facial identity through spatiotemporal pattern analysis. PNAS 108:9998–10003
    [Google Scholar]
  75. Odegard TN, Farris EA, Ring J, McColl R, Black J. 2009. Brain connectivity in non-reading impaired children and children diagnosed with developmental dyslexia. Neuropsychologia 47:1972–77
    [Google Scholar]
  76. O'Neil EB, Barkley VA, Kohler S. 2013. Representational demands modulate involvement of perirhinal cortex in face processing. Hippocampus 23:592–605
    [Google Scholar]
  77. O'Neil EB, Cate AD, Kohler S. 2009. Perirhinal cortex contributes to accuracy in recognition memory and perceptual discriminations. J. Neurosci. 29:8329–34
    [Google Scholar]
  78. O'Neil EB, Hutchison RM, McLean DA, Kohler S. 2014. Resting-state fMRI reveals functional connectivity between face-selective perirhinal cortex and the fusiform face area related to face inversion. NeuroImage 92:349–55
    [Google Scholar]
  79. Pertzov Y, Krill D, Weiss N, Lesinger K, Avidan G. 2020. Rapid forgetting of faces in congenital prosopagnosia. Cortex 129:119–32
    [Google Scholar]
  80. Peterson MF, Zaun I, Hoke H, Jiahui G, Duchaine B, Kanwisher N. 2019. Eye movements and retinotopic tuning in developmental prosopagnosia. J. Vis. 19:97
    [Google Scholar]
  81. Phillips JS, Greenberg AS, Pyles JA, Pathak SK, Behrmann M et al. 2012. Co-analysis of brain structure and function using fMRI and diffusion-weighted imaging. J. Vis. Exp. 69:4125
    [Google Scholar]
  82. Piccardi L, De Luca M, Di Vita A, Palermo L, Tanzilli A et al. 2019. Evidence of taxonomy for developmental topographical disorientation: developmental landmark agnosia case 1. Appl. Neuropsychol. Child 8:187–98
    [Google Scholar]
  83. Pizzamiglio MR, De Luca M, Di Vita A, Palermo L, Tanzilli A et al. 2017. Congenital prosopagnosia in a child: neuropsychological assessment, eye movement recordings and training. Neuropsychol. Rehabil. 27:369–408
    [Google Scholar]
  84. Poltoratski S, Kay K, Finzi D, Grill-Spector K. 2020. Holistic face recognition is an emergent phenomenon of spatial integration in face-selective regions. bioRxiv 338491. https://doi.org/10.1101/2020.10.13.338491
    [Crossref]
  85. Pyles JA, Verstynen TD, Schneider W, Tarr MJ. 2013. Explicating the face perception network with white matter connectivity. PLOS ONE 8:e61611
    [Google Scholar]
  86. Richler JJ, Gauthier I. 2014. A meta-analysis and review of holistic face processing. Psychol. Bull. 140:1281–302
    [Google Scholar]
  87. Rosenthal G, Tanzer M, Simony E, Hasson U, Behrmann M, Avidan G. 2017. Altered topology of neural circuits in congenital prosopagnosia. eLife 6:e25069
    [Google Scholar]
  88. Ross DA, Gauthier I. 2015. Holistic processing in the composite task depends on face size. Vis. Cogn. 23:533–45
    [Google Scholar]
  89. Royer J, Blais C, Charbonneau I, Dery K, Tardif J et al. 2018. Greater reliance on the eye region predicts better face recognition ability. Cognition 181:12–20
    [Google Scholar]
  90. Russell R, Chatterjee G, Nakayama K. 2012. Developmental prosopagnosia and super-recognition: no special role for surface reflectance processing. Neuropsychologia 50:334–40
    [Google Scholar]
  91. Russell R, Duchaine B, Nakayama K. 2009. Super-recognizers: people with extraordinary face recognition ability. Psychon. Bull. Rev. 16:252–57
    [Google Scholar]
  92. Scherf KS, Thomas C, Doyle J, Behrmann M 2014. Emerging structure–function relations in the developing face processing system. Cereb. Cortex 24:2964–80
    [Google Scholar]
  93. Schmalzl L, Palermo R, Green M, Brunsdon R, Coltheart M. 2008. Training of familiar face recognition and visual scan paths for faces in a child with congenital prosopagnosia. Cogn. Neuropsychol. 25:704–29
    [Google Scholar]
  94. Schroff F, Kalenichenko D, Philbin J. 2015. FaceNet: A unified embedding for face recognition and clustering. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)815–23 Piscataway, NJ: IEEE
    [Google Scholar]
  95. Schwarzer G, Huber S, Dummler T. 2005. Gaze behavior in analytical and holistic face processing. Mem. Cognit. 33:344–54
    [Google Scholar]
  96. Schwarzer G, Huber S, Gruter M, Gruter T, Gross C et al. 2007. Gaze behaviour in hereditary prosopagnosia. Psychol. Res. 71:583–90
    [Google Scholar]
  97. Simmons WK, Reddish M, Bellgowan PS, Martin A. 2009. The selectivity and functional connectivity of the anterior temporal lobes. Cereb. Cortex 20:813–25
    [Google Scholar]
  98. Siugzdaite R, Bathelt J, Holmes J, Astle DE. 2020. Transdiagnostic brain mapping in developmental disorders. Curr. Biol. 30:1245–57.e4
    [Google Scholar]
  99. Song S, Garrido L, Nagy Z, Mohammadi S, Steel A et al. 2015. Local but not long-range microstructural differences of the ventral temporal cortex in developmental prosopagnosia. Neuropsychologia 78:195–206
    [Google Scholar]
  100. Steinbrink C, Vogt K, Kastrup A, Muller HP, Juengling FD et al. 2008. The contribution of white and gray matter differences to developmental dyslexia: insights from DTI and VBM at 3.0 T. Neuropsychologia 46:3170–78
    [Google Scholar]
  101. Stollhoff R, Kennerknecht I, Elze T, Jost J. 2011. A computational model of dysfunctional facial encoding in congenital prosopagnosia. Neural Netw 24:652–64
    [Google Scholar]
  102. Tan C, Poggio T. 2016. Neural tuning size in a model of primate visual processing accounts for three key markers of holistic face processing. PLOS ONE 11:e0150980
    [Google Scholar]
  103. Tanzer M, Freud E, Ganel T, Avidan G. 2013. General holistic impairment in congenital prosopagnosia: evidence from Garner's speeded-classification task. Cogn. Neuropsychol. 30:429–45
    [Google Scholar]
  104. Tanzer M, Weinbach N, Mardo E, Henik A, Avidan G. 2016. Phasic alertness enhances processing of face and non-face stimuli in congenital prosopagnosia. Neuropsychologia 89:299–308
    [Google Scholar]
  105. Tardif J, Morin Duchesne X, Cohan S, Royer J, Blais C et al. 2019. Use of face information varies systematically from developmental prosopagnosics to super-recognizers. Psychol. Sci. 30:300–8
    [Google Scholar]
  106. Thomas C, Avidan G, Humphreys K, Jung K, Gao F, Behrmann M. 2009. Reduced structural connectivity in ventral visual cortex in congenital prosopagnosia. Nat. Neurosci. 12:29–31
    [Google Scholar]
  107. Tsao DY, Moeller S, Freiwald WA 2008a. Comparing face patch systems in macaques and humans. PNAS 105:19514–19
    [Google Scholar]
  108. Tsao DY, Schweers N, Moeller S, Freiwald WA. 2008b. Patches of face-selective cortex in the macaque frontal lobe. Nat. Neurosci. 11:877–79
    [Google Scholar]
  109. Verfaillie K, Huysegems S, De Graef P, Van Belle G. 2014. Impaired holistic and analytic face processing in congenital prosopagnosia: evidence from the eye-contingent mask/window paradigm. Vis. Cogn. 22:503–21
    [Google Scholar]
  110. Wang L, Baumgartner F, Kaule FR, Hanke M, Pollmann S. 2019. Individual face- and house-related eye movement patterns distinctively activate FFA and PPA. Nat. Commun. 10:5532
    [Google Scholar]
  111. Weiss N, Mardo E, Avidan G. 2016. Visual expertise for horses in a case of congenital prosopagnosia. Neuropsychologia 83:63–75
    [Google Scholar]
  112. Wilcockson DWT, Burns EJ, Xiao B, Tree JJ, Crawford JR. 2020. Atypically heterogeneous vertical first fixations to faces in a case series of people with developmental prosopagnosia. Vis. Cogn. 28:311–23
    [Google Scholar]
  113. Witthoft N, Poltoratski S, Nguyen M, Golarai G, Liberman A et al. 2016. Reduced spatial integration in the ventral visual cortex underlies face recognition deficits in developmental prosopagnosia. bioRxiv 051102. https://doi.org/10.1101/051102
    [Crossref]
  114. Woolnough O, Rollo PS, Forseth KJ, Kadipasaoglu CM, Ekstrom AD, Tandon N. 2020. Category selectivity for face and scene recognition in human medial parietal cortex. Curr. Biol. 30:2707–15.e3
    [Google Scholar]
  115. Yamins DL, DiCarlo JJ. 2016. Using goal-driven deep learning models to understand sensory cortex. Nat. Neurosci. 19:356–65
    [Google Scholar]
  116. Zhao Y, Zhen Z, Liu X, Song Y, Liu J. 2018. The neural network for face recognition: insights from an fMRI study on developmental prosopagnosia. NeuroImage 169:151–61
    [Google Scholar]
  117. Zhen Z, Fang H, Liu J. 2013. The hierarchical brain network for face recognition. PLOS ONE 8:e59886
    [Google Scholar]
  118. Zoccolan D, Kouh M, Poggio T, DiCarlo JJ. 2007. Trade-off between object selectivity and tolerance in monkey inferotemporal cortex. J. Neurosci. 27:12292–307
    [Google Scholar]
/content/journals/10.1146/annurev-vision-113020-012740
Loading
/content/journals/10.1146/annurev-vision-113020-012740
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error