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Monteiro, F., Rodrigues , P., Santos, I. M., Bem-Haja, P., & Rosa, P. J. (2023). FamFac – A Database of Famous Faces for Psychology Experiments. International Journal of Psychological Research, 16(2), 31–41. https://doi.org/10.21500/20112084.6498
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The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
To give up copyright, the authors allow that, International Journal of Psychological Research, distribute the work more broadly, check for the reuse by others and take care of the necessary procedures for the registration and administration of copyright; at the same time, our editorial board represents the interests of the author and allows authors to re-use his work in various forms. In response to the above, authors transfer copyright to the journal, International Journal of Psychological Research. This transfer does not imply other rights which are not those of authorship (for example those that concern about patents). Likewise, preserves the authors rights to use the work integral or partially in lectures, books and courses, as well as make copies for educational purposes. Finally, the authors may use freely the tables and figures in its future work, wherever make explicit reference to the previous publication in International Journal of Psychological Research. The assignment of copyright includes both virtual rights and forms of the article to allow the editorial to disseminate the work in the manner which it deems appropriate.
The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
Abstract
Introduction. High variation in the low-level proprieties of visual stimuli and varying degrees of familiarity with famous faces may have caused a bias in the results of investigations that tried to disentangle the processes involved in familiar and unfamiliar face processing (e.g., temporal differences in the detection of the first event-related potentials specialized in face processing may have been caused by different methods of controlling variance in the low-level proprieties of visual stimuli). Objective. To address these problems, we developed a freely available database of 183 famous faces whose low-level proprieties (brightness, size, resolution) have been homogenized and the level of familiarity established. Method. The brightness of the stimuli was standardized by a custom-developed algorithm. The size and the resolution of the pictures were homogenized in Gimp. The familiarity level of the famous faces was established by a group of 48 Portuguese college students. Results. Our results suggest that the brightness of each image did not differ significantly from the mean brightness value of the stimuli set, confirming the standardizing ability of the algorithm. Forty-one famous faces were classified as highly familiar. Main findings and implications. This study provides two important resources, as both the algorithm and the database are freely available for research purposes. The homogenization of the low-level features and the control of the level of familiarity of the famous faces included in our database should ensure that they do not elicit confounding effects such as the ones verified in past studies.
References
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Bruce, V., Henderson, Z., Greenwood, K., Hancock, P. J., Burton, A. M., & Miller, P. (1999). Verification of face identities from images captured on video. Journal of Experimental Psychology: Applied, 5(4), 339. https://doi.org/10.1037/1076-898X.5.4.339.
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Burton, A. M., Bruce, V., & Hancock, P. J. (1999). From pixels to people: a model of familiar face recognition. Cognitive Science, 23(1), 1–31. https://doi.org/10.1207/s15516709cog2301_1.
Cocker, K. D., Moseley, M. J., Bissenden, J. G., Fielder, A. R. (1994). Visual acuity and pupillary responses to spatial structure in infants. Investigative Ophthalmology & Visual Science. 35, 2620-2625.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Dubois, S., Rossion, B., Schiltz, C., Bodart, J. M., Michel, C., Bruyer, R., & Crommelinck, M. (1999). Effect of familiarity on the processing of human faces. Neuroimage, 9, 278-289. https://doi.org/10.1006/nimg.1998.0409.
Dragoi, V., Sharma, J. & Sur, M. (2000). Adaptation-induced plasticity of orientation tuning in adult visual cortex. Neuron, 28(1), 287–298. https://doi.org/10.1016/S0896-6273(00)00103-3.
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191. https://doi.org/10.3758/B
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Gosling, A., & Eimer, M. (2011). An event-related brain potential study of explicit face recognition. Neuropsychologia, 49(9), 2736–2745. https://doi.org/10.1016/j.neuropsychologia.2011.05.025.
Heap, L. A., Vanwalleghem, G., Thompson, A. W., Favre-Bulle, I. A., & Scott, E. K. (2018). Luminance changes drive directional startle through a thalamic pathway. Neuron, 99(2), 293-301. https://doi.org/10.1016/j.neuron.2018.06.013.
Johnston, R. J., & Edmonds, A. J. (2009). Familiar and unfamiliar face recognition: a review. Memory, 17(5), 577–596. https://doi.org/10.1080/09658210902976969.
Kamitani, Y. & Tong, F. (2006). Decoding seen and attended motion directions from activity in the human Visual Cortex. Current Biology, 16(11), 1096–1102. https://doi.org/10.1016/j.cub.2006.04.003.
Knebel, J. F., Toepel, U., Hudry, J., Le Coutre, J., & Murray, M. M. (2008). Generating controlled image sets in cognitive neuroscience research. Brain Topography, 20(4), 284–289. https://doi.org/10.1007/s10548-008-0046-5.
Lakens, D., Fockenberg, D. A., Lemmens, K. P., Hamm, J., & Miden, C. J. (2013). Brightness differences influence the evaluation of affective pictures. Cognition and Emotion, 27(7), 1225–1246. https://doi.org/10.1080/02699931.2013.781501.
Leibenluft, E., Gobbini, M. I., Harrison, T., & Haxby, J. V. (2004). Mothers’ neural activation in response to pictures of their children and other children. Biological Psychiatry, 56(4), 225–232. https://doi.org/10.1016/j.biopsych.2004.05.017.
Lima, D., Pinto, R., & Albuquerque, P. B. (2021). Recognition and naming test of the Portuguese population for national and international celebrities. Behavior Research Methods, 53(6), 2326-2337. https://doi.org/10.3758/s13428-021-01572-y.
Longmore, C. A., Santos, I. M., Silva, C. F., Hall, A., Faloyin, D., Little, E. (2017). Image dependency in the recognition of newly learnt faces. Quarterly Journal of Experimental Psychology, 70(5), 863-873. https://doi.org/10.1080/17470218.2016.1236825.
Marful, A., Díez-Álamo, A. M., Plaza-Navas, S., & Fernandez, A. (2018). A normative study for photographs of celebrities in Spain. Plos One, 13(5), e0197554. https://doi.org/10.1371/journal.pone.0197554.
McCourt, M. E., & Foxe, J. J. (2003). Brightening prospects for “early” corticol coding of perceived luminance. Journal of Vision, 3(9), 49–56. https://doi.org/10.1167/3.9.424.
Natu, V., & O’Toole, A. J. (2011). The neural processing of familiar and unfamiliar faces: a review and synopsis. British Journal of Psychology, 102(4), 726–747. https://doi.org/10.1111/j.2044-8295.2011.02053.x.
Nessler, D., Mecklinger, A., & Penney, T. B. (2005). Perceptual fluency, semantic familiarity and recognition-related familiarity: an electrophysiological exploration. Cognitive Brain Research, 22(2), 265–288. https://doi.org/10.1016/j.cogbrainres.2004.03.023.
Orquin, J. L., Loose, S. M. (2013). Attention and choice: A review on eye movements in decision making. Acta Psychologica, 144(1), 190-206. https://doi.org/10.1016/j.actpsy.2013.06.003.
Park, S., Konkle, T., & Oliva, A. (2015). Parametric coding of the size and clutter of natural scenes in the human brain. Cerebral Cortex, 25(7), 1792-1805. https://doi.org/10.1093/cercor/bht418.
Prajapati, B., Dunne, M., & Armstrong, R. (2010). Sample size estimation and statistical power analyses. Optometry Today, 16(7), 10-18.
Ramon, M., Caharel, S., & Rossion, B. (2011). The speed of recognition of personally familiar faces. Perception, 40(4), 437–449. https://doi.org/10.1068/p6794.
Schettino, A., Keil, A., Porcu, E., & Müller, M. M. (2016). Shedding light on emotional perception: interaction of brightness and semantic content in extrastriate visual cortex. NeuroImage, 133, 341–353. https://doi.org/10.1016/j.neuroimage.2016.03.020.
Schindler, S., Schettino, A., Pourtois, G. (2018). Electrophysiological correlates of the interplay between low-level visual features and emotional content during word reading. Scientific Reports, 8, 1-13. https://doi.org/10.1038/s41598-018-30701-5.
Stacey, P. C., Walker, S., & Underwood, J. D. (2005). Face processing and familiarity: evidence from eye-movement data. British Journal of Psychology, 96(4), 407–422. https://doi.org/10.1348/000712605X47422.
UNESCO. (2018). The Creative Commons licenses. UNESCO. https://en.unesco.org/open-access/creative-commons-licenses.
Valentine, T., Lewis, M. B., & Hills, P. J. (2016). Face-space: A unifying concept in face recognition research. Quarterly Journal of Experimental Psychology, 69(10), 1996-2019. https://doi.org/10.1080/17470218.2014.990392.
Willenbockel, V., Sadr, J., Fiset, D., Horne, G. O., Gosselin, F., & Tanaka, J. W. (2010). Controlling low-level image properties: The SHINE toolbox. Behavior Research Methods, 42(3), 671–684. https://doi.org/10.3758/BRM.42.3.671.
Bainbridge, W. A., & Oliva, A. (2015). A toolbox and sample object perception data for equalization of natural images. Data in Brief, 5, 846–851. https://doi.org/10.1016/j.dib.2015.10.030.
Bentin, S., & Deouell, L. Y. (2000) Structural encoding and identification in face processing: ERP evidence for separate mechanisms. Cognitive Neuropsychology, 17(1–3), 35–55. https://doi.org/10.1080/026432900380472.
Bizzozero, I., Lucchelli, F., Saetti, M. C., & Spinnler, H. (2007). “Whose face is this?”: Italian norms of naming celebrities. Neurological Sciences, 28(6), 315-322. https://doi.org/10.1007/s10072-007-0845-6.
Brannan, J. R., Solan, H. A., Ficarra, A. P., & Ong, E. (1998). Effect of luminance on visual evoked potential amplitudes in normal and disabled readers. Optometry and Vision Science: Official Publication of the American Academy of Optometry, 75(4), 279-283. https://doi.org/10.1097/00006324-199804000-00025.
Bruce, V., Henderson, Z., Greenwood, K., Hancock, P. J., Burton, A. M., & Miller, P. (1999). Verification of face identities from images captured on video. Journal of Experimental Psychology: Applied, 5(4), 339. https://doi.org/10.1037/1076-898X.5.4.339.
Bruce, V., & Young, A. (1986). Understanding face recognition. British Journal of Psychology, 77(3), 305–327. https://doi.org/10.1111/j.2044-8295.1986.tb02199.x.
Burton, A. M., Bruce, V., & Hancock, P. J. (1999). From pixels to people: a model of familiar face recognition. Cognitive Science, 23(1), 1–31. https://doi.org/10.1207/s15516709cog2301_1.
Cocker, K. D., Moseley, M. J., Bissenden, J. G., Fielder, A. R. (1994). Visual acuity and pupillary responses to spatial structure in infants. Investigative Ophthalmology & Visual Science. 35, 2620-2625.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
Dubois, S., Rossion, B., Schiltz, C., Bodart, J. M., Michel, C., Bruyer, R., & Crommelinck, M. (1999). Effect of familiarity on the processing of human faces. Neuroimage, 9, 278-289. https://doi.org/10.1006/nimg.1998.0409.
Dragoi, V., Sharma, J. & Sur, M. (2000). Adaptation-induced plasticity of orientation tuning in adult visual cortex. Neuron, 28(1), 287–298. https://doi.org/10.1016/S0896-6273(00)00103-3.
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191. https://doi.org/10.3758/B
F03193146.
Fife-Schaw, C. (2006). Levels of measurement In G. M. Breakwell, S. Hammond, C. Fife-Schaw, & J. A. Smith (Eds.), Research Methods in Psychology. (pp. 147-157). Sage Publications.
Gosling, A., & Eimer, M. (2011). An event-related brain potential study of explicit face recognition. Neuropsychologia, 49(9), 2736–2745. https://doi.org/10.1016/j.neuropsychologia.2011.05.025.
Heap, L. A., Vanwalleghem, G., Thompson, A. W., Favre-Bulle, I. A., & Scott, E. K. (2018). Luminance changes drive directional startle through a thalamic pathway. Neuron, 99(2), 293-301. https://doi.org/10.1016/j.neuron.2018.06.013.
Johnston, R. J., & Edmonds, A. J. (2009). Familiar and unfamiliar face recognition: a review. Memory, 17(5), 577–596. https://doi.org/10.1080/09658210902976969.
Kamitani, Y. & Tong, F. (2006). Decoding seen and attended motion directions from activity in the human Visual Cortex. Current Biology, 16(11), 1096–1102. https://doi.org/10.1016/j.cub.2006.04.003.
Knebel, J. F., Toepel, U., Hudry, J., Le Coutre, J., & Murray, M. M. (2008). Generating controlled image sets in cognitive neuroscience research. Brain Topography, 20(4), 284–289. https://doi.org/10.1007/s10548-008-0046-5.
Lakens, D., Fockenberg, D. A., Lemmens, K. P., Hamm, J., & Miden, C. J. (2013). Brightness differences influence the evaluation of affective pictures. Cognition and Emotion, 27(7), 1225–1246. https://doi.org/10.1080/02699931.2013.781501.
Leibenluft, E., Gobbini, M. I., Harrison, T., & Haxby, J. V. (2004). Mothers’ neural activation in response to pictures of their children and other children. Biological Psychiatry, 56(4), 225–232. https://doi.org/10.1016/j.biopsych.2004.05.017.
Lima, D., Pinto, R., & Albuquerque, P. B. (2021). Recognition and naming test of the Portuguese population for national and international celebrities. Behavior Research Methods, 53(6), 2326-2337. https://doi.org/10.3758/s13428-021-01572-y.
Longmore, C. A., Santos, I. M., Silva, C. F., Hall, A., Faloyin, D., Little, E. (2017). Image dependency in the recognition of newly learnt faces. Quarterly Journal of Experimental Psychology, 70(5), 863-873. https://doi.org/10.1080/17470218.2016.1236825.
Marful, A., Díez-Álamo, A. M., Plaza-Navas, S., & Fernandez, A. (2018). A normative study for photographs of celebrities in Spain. Plos One, 13(5), e0197554. https://doi.org/10.1371/journal.pone.0197554.
McCourt, M. E., & Foxe, J. J. (2003). Brightening prospects for “early” corticol coding of perceived luminance. Journal of Vision, 3(9), 49–56. https://doi.org/10.1167/3.9.424.
Natu, V., & O’Toole, A. J. (2011). The neural processing of familiar and unfamiliar faces: a review and synopsis. British Journal of Psychology, 102(4), 726–747. https://doi.org/10.1111/j.2044-8295.2011.02053.x.
Nessler, D., Mecklinger, A., & Penney, T. B. (2005). Perceptual fluency, semantic familiarity and recognition-related familiarity: an electrophysiological exploration. Cognitive Brain Research, 22(2), 265–288. https://doi.org/10.1016/j.cogbrainres.2004.03.023.
Orquin, J. L., Loose, S. M. (2013). Attention and choice: A review on eye movements in decision making. Acta Psychologica, 144(1), 190-206. https://doi.org/10.1016/j.actpsy.2013.06.003.
Park, S., Konkle, T., & Oliva, A. (2015). Parametric coding of the size and clutter of natural scenes in the human brain. Cerebral Cortex, 25(7), 1792-1805. https://doi.org/10.1093/cercor/bht418.
Prajapati, B., Dunne, M., & Armstrong, R. (2010). Sample size estimation and statistical power analyses. Optometry Today, 16(7), 10-18.
Ramon, M., Caharel, S., & Rossion, B. (2011). The speed of recognition of personally familiar faces. Perception, 40(4), 437–449. https://doi.org/10.1068/p6794.
Schettino, A., Keil, A., Porcu, E., & Müller, M. M. (2016). Shedding light on emotional perception: interaction of brightness and semantic content in extrastriate visual cortex. NeuroImage, 133, 341–353. https://doi.org/10.1016/j.neuroimage.2016.03.020.
Schindler, S., Schettino, A., Pourtois, G. (2018). Electrophysiological correlates of the interplay between low-level visual features and emotional content during word reading. Scientific Reports, 8, 1-13. https://doi.org/10.1038/s41598-018-30701-5.
Stacey, P. C., Walker, S., & Underwood, J. D. (2005). Face processing and familiarity: evidence from eye-movement data. British Journal of Psychology, 96(4), 407–422. https://doi.org/10.1348/000712605X47422.
UNESCO. (2018). The Creative Commons licenses. UNESCO. https://en.unesco.org/open-access/creative-commons-licenses.
Valentine, T., Lewis, M. B., & Hills, P. J. (2016). Face-space: A unifying concept in face recognition research. Quarterly Journal of Experimental Psychology, 69(10), 1996-2019. https://doi.org/10.1080/17470218.2014.990392.
Willenbockel, V., Sadr, J., Fiset, D., Horne, G. O., Gosselin, F., & Tanaka, J. W. (2010). Controlling low-level image properties: The SHINE toolbox. Behavior Research Methods, 42(3), 671–684. https://doi.org/10.3758/BRM.42.3.671.
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