The Relationship Between the Benton Face Recognition Test and Electrophysiological Unfamiliar Face Individuation Response as Revealed by Fast Periodic Stimulation
Restricted accessResearch articleFirst published online February, 2020
The Relationship Between the Benton Face Recognition Test and Electrophysiological Unfamiliar Face Individuation Response as Revealed by Fast Periodic Stimulation
A recent approach to implicitly study face recognition skills has been the fast periodic visual stimulation (FPVS) coupled with electroencephalography (EEG). Its relationship with explicit behavioral measures of face individuation remains largely undocumented. We evaluated the relationship of the FPVS–EEG measure of individuation and performance at a computer version of the Benton Face Recognition Test. High-density EEG was recorded in 32 participants presented with an unfamiliar face at a rate of 6 Hz (F) for 60 s. Every five faces, new identities were inserted. The resulting 1.2 Hz (F/5) EEG response and its harmonics objectively indexed rapid individuation of unfamiliar faces. The robust individuation response, observed over occipitotemporal sites, was significantly correlated with speed, but not accuracy rate of the computer version of the Benton Face Recognition Test. This effect was driven by a few individuals who were particularly slow at the behavioral test and also showed the lowest face individuation response. These results highlight the importance of considering the time taken to recognize a face, as a complementary to accuracy rate variable, providing valuable information about one’s recognition skills. Overall, these observations strengthen the diagnostic value of FPVS–EEG as an objective and rapid flag for specific difficulties at individual face recognition in the human population.
Alonso-PrietoE.Van BelleG.Liu-ShuangJ.NorciaA. M.RossionB. (2013).
The 6 Hz fundamental stimulation frequency rate for individual face discrimination in the right occipito-temporal cortex. Neuropsychologia,
51, 2863–2875. doi:10.1016/j.neuropsychologia.2013.08.018
2.
BellA. J.SejnowskiT. J. (1995).
An information-maximization approach to blind separation and blind deconvolution. Neural Computation,
7, 1129–1159. doi:10.1162/neco.1995.7.6.1129
3.
BentonA. L.Van AllenM. W. (1968).
Impairment in facial recognition in patients with cerebral disease. Cortex,
4, 344–358. doi:10.1016/S0010-9452(68)80018-8
4.
BindemannM.FyshM.CrossK.WattsR. (2016).
Matching faces against the clock. i-Perception,
7(5), 1–18, 2041669516672219.
5.
Bowles, D. C., McKone, E., Dawel, A., Duchaine, B., Palermo, R., Schmalzl, L., Rivolta, D., Wilson, C. E. & Yovel, G. (2009). Diagnosing prosopagnosia: Effects of ageing, sex, and participant–stimulus ethnic match on the Cambridge Face Memory Test and Cambridge Face Perception Test. Cognitive Neuropsychology, 26(5), 423–455.
6.
BruceV.HendersonZ.GreenwoodK.HancockP. J.BurtonA. M.MillerP. (1999).
Verification of face identities from images captured on video. Journal of Experimental Psychology: Applied,
5, 339. doi:10.1037/1076-898X.5.4.339
7.
BruceV.HendersonZ.NewmanC.BurtonA. M. (2001).
Matching identities of familiar and unfamiliar faces caught on CCTV images. Journal of Experimental Psychology: Applied,
7, 207–218. doi:10.1037/1076-898X.7.3.207
8.
BusignyT.RossionB. (2010).
Acquired prosopagnosia abolishes the face inversion effect. Cortex,
46, 965–981. doi:10.1016/j.cortex.2009.07.004
9.
DuchaineB.NakayamaK. (2006).
The Cambridge Face Memory Test: Results for neurologically intact individuals and an investigation of its validity using inverted face stimuli and prosopagnosic participants. Neuropsychologia,
44, 576–585. doi:10.1016/j.neuropsychologia.2005.07.001
10.
DzhelyovaM.JacquesC.DormalG.MichelC.SchiltzC.RossionB. (2019).
High test-retest reliability of a neural index of rapid automatic discrimination of unfamiliar individual faces. Visual Cognition,
27, 127–141. doi:10.1080/13506285.2019.1616639
11.
DzhelyovaM.RossionB. (2014a).
Supra-additive contribution of shape and surface information to individual face discrimination as revealed by fast periodic visual stimulation. Journal of Vision,
14, 15. doi:10.1167/14.14.15
12.
DzhelyovaM.RossionB. (2014b).
The effect of parametric stimulus size variation on individual face discrimination indexed by fast periodic visual stimulation. BMC Neuroscience,
15, 87. doi:10.1186/1471-2202-15-87
13.
EstudilloA.BindemannM. (2014).
Generalization across view in face memory and face matching. i-Perception,
5, 589–601. doi:10.1068/i0669
14.
FyshM. C.BindemannM. (2017).
Effects of time pressure and time passage on face-matching accuracy. Royal Society Open Science,
4, 170249.
15.
HerzmannG.DanthiirV.SchachtA.SommerW.WilhelmO. (2008).
Toward a comprehensive test battery for face cognition: Assessment of the tasks. Behavior Research Methods,
40, 840–857. doi:10.3758/BRM.40.3.840
16.
HillsP. J.LewisM. B. (2018).
The development of face expertise: Evidence for a qualitative change in processing. Cognitive Development,
48, 1–18. doi:10.1016/j.cogdev.2018.05.003
17.
JonasJ.BrissartH.HossuG.Colnat-CoulboisS.VignalJ. P.RossionB.MaillardL. (2018).
A face identity hallucination (palinopsia) generated by intracerebral stimulation of the face-selective right lateral fusiform cortex. Cortex,
99, 296–310. doi:10.1016/j.cortex.2017.11.022
18.
LaguesseR.DormalG.BiervoyeA.KuefnerD.RossionB. (2012).
Extensive visual training in adulthood significantly reduces the face inversion effect. Journal of Vision,
12, 1–13. doi:10.1167/12.10.14
19.
Liu-ShuangJ.NorciaA. M.RossionB. (2014).
An objective index of individual face discrimination in the right occipito-temporal cortex by means of fast periodic oddball stimulation. Neuropsychologia,
52, 57–72. doi:10.1016/j.neuropsychologia.2013.10.022
20.
Liu-ShuangJ.TorfsK.RossionB. (2016).
An objective electrophysiological marker of face individualisation impairment in acquired prosopagnosia with fast periodic visual stimulation. Neuropsychologia,
83, 100–113. doi:10.1016/j.neuropsychologia.2015.08.023
21.
MakeigS.BellA. J.JungT. P.SejnowskiT. J. (1996). Independent component analysis of electroencephalographic data. In TouretzkyD.MozerM.HasselmoM. (Eds.), Advances in neural information processing systems (pp. 145–151).
Cambridge, MA:
MIT Press.
22.
Megreya, A. M., & Burton, A. M. (2006). Unfamiliar faces are not faces: Evidence from a matching task. Memory & cognition, 34(4), 865–876. doi:10.3758/BF03193433
23.
ReganD. (1989). Human brain electrophysiology: Evoked potentials and evoked magnetic fields in science and medicine.
New York, NY:
Elsevier.
24.
RetterT. L.JiangF.WebsterM. A.RossionB. (2019). All-or-none visual categorization in the human brain. bioRxiv, doi: 10.1101/658625
25.
RossionB. (2018).
Prosopdysgnosia? What could it tell us about the neural organization of face and object recognition?Cognitive Neuropsychology,
35, 98–101. doi:10.1080/02643294.2017.1414778
26.
RossionB.BoremanseA. (2011).
Robust sensitivity to facial identity in the right human occipito-temporal cortex as revealed by steady-state visual-evoked potentials. Journal of Vision,
11(2): 16, 1–21. doi:10.1167/11.2.16
27.
RossionB.MichelC. (2018).
Normative accuracy and response time data for the computerized Benton Facial Recognition Test (BFRT-c). Behavior Research Methods,
50, 2442–2460. doi:10.3758/s13428-018-1023-x
28.
RossionB.PrietoE. A.BoremanseA.KuefnerD.Van BelleG. (2012).
A steady-state visual evoked potential approach to individual face perception: Effect of inversion, contrast-reversal and temporal dynamics. NeuroImage,
63, 1585–1600. doi:10.1016/j.neuroimage.2012.08.033
29.
Rossion, B., & Taubert, J. (2019). What can we learn about human individual face recognition from experimental studies in monkeys? Vision Research, 157, 142–158. doi:10.1016/j.visres.2018.03.012
30.
SergentJ. (1984).
An investigation into component and configural processes underlying face perception. British Journal of Psychology,
75, 221–242. doi:10.1111/j.2044-8295.1984.tb01895.x
31.
SheehanM. J.NachmanM. W. (2014).
Morphological and population genomic evidence that human faces have evolved to signal individual identity. Nature Communications,
5, 4800. doi:10.1038/ncomms5800
32.
StacchiL.Liu-ShuangJ.RamonM.CaldaraR. (2019).
Reliability of individual differences in neural face identity discrimination. NeuroImage,
189, 468–475. doi:10.1016/j.neuroimage.2019.01.023
33.
ThigpenN. N.KappenmanE. S.KeilA. (2017).
Assessing the internal consistency of the event‐related potential: An example analysis. Psychophysiology,
54, 123–138.
34.
VettoriS.DzhelyovaM.Van der DonckS.JacquesC.SteyaertJ.RossionB.BoetsB. (2019).
Reduced neural sensitivity to rapid individual face discrimination in autism spectrum disorder. NeuroImage: Clinical,
21, 101613. doi:10.1016/j.nicl.2018.101613
35.
Wilhelm, O., Herzmann, G., Kunina, O., Danthiir, V., Schacht, A., & Sommer, W. (2010). Individual differences in perceiving and recognizing faces—One element of social cognition. Journal of personality and social psychology, 99(3), 530. doi: 10.1037/a0019972
36.
WilmerJ. B.GermineL.ChabrisC. F.ChatterjeeG.WilliamsM.LokenE., . . . DuchaineB. (2010).
Human face recognition ability is specific and highly heritable. Proceedings of the National Academy of Sciences,
107, 5238–5241. doi:10.1073/pnas.0913053107
37.
XuB.Liu-ShuangJ.RossionB.TanakaJ. (2017).
Individual differences in face identity processing with fast periodic visual stimulation. Journal of Cognitive Neuroscience,
29, 1368–1377. doi:10.1162/jocn_a_01126
