psychology experiments database

Psychological Experiments Online

Psychological Experiments Online is a multimedia collection that synthesizes the most important psychological experiments of the 20th and 21st centuries, fostering deeper levels of understanding for students and scholars alike. These experiments have far-reaching impacts on fields as diverse as sociology, business, advertising, economics, political science, law, ethics, and the arts.

Featured Experiments

Behavioral Study of Obedience

Milgram is most famous for his controversial Obedience Study, performed at Yale University in 1961. He was inspired to perform this study by the defense commonly used at the WWII Nuremburg War Criminals Trials, that the Nazi officers and guards implementing the Holocaust had just been “following orders.” Milgram’s Behavioral Study of Obedience tested the extent to which random American civilians could be convinced to inflict pain upon their fellow citizens when ordered to do so by a perceived authority figure. The results of this study horrified the psychological community, the general public, and the study participants themselves once the true nature of the study was explained. This study was one of the driving forces behind the creation of Institutional Review Boards (IRBs) to review proposed scientific experiments using human subjects, and approve or veto their implementation.

Robbers Cave Experiment

The Robbers Cave Experiment was named after its location, as it took place at a boys summer camp in Robbers Cave State Park, Oklahoma. Sherif identified 22 psychologically-normal, white, middle-class, eleven- and twelve-year-old boys from Connecticut to take part in the experiment. The boys were divided into two groups and Sherif studied how conflict and prejudice were first fostered and then reduced. Sherif concluded that groups have their own biases, prejudices, and culture. The Robbers Cave experiment was most helpful in showing that superordinate goals for both groups can help resolve issues and create peace.

Visual Cliff Experiment

In 1960, following their work with sensory-perception in rats, Gibson and Walk hypothesized that depth perception is inherent knowledge as opposed to a learned process. Their experiment consisted of placing an infant on the visual-cliff apparatus: simply described as a table whose edge has been extended by a piece of solidly fixed Plexiglas. The parent or caregiver would call out to the child from across the Plexiglas. If the child was reluctant to cross the Plexiglas, or “cliff”, to go to its parents, the experimenters assumed that the child was able to perceive depth. The study was published that same year in Scientific American and has come to be one of psychology’s most well-known experiments.

Stanford Prison Experiment

The Stanford Prison Experiment was scheduled to run for two weeks, with the intent of studying situational influences on human behavior. The experiment was shut down after just six days due to how extreme those influences turned out to be. The experiment was conducted from August 14 to August 20, 1971, funded by the US Office of Naval Research, and showed that the random assignment of “prisoner” and “guard” to 24 male college students made a major impact on their psychology and behavior, fostering depression among the prisoners and sadism among the guards.

Psychology Experiments Database

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PsyToolkit is a one-stop website. Get your questionnaire/experiment running quickly without hassle.

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PsyToolkit is the only free website offering running programmable online psychological experiments and surveys.

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You can run complex psychological surveys, and use from more than 100 surveys in the survey library .

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• Odum Institute Dataverse The Odum Institute provides services for researchers in managing, archiving and preserving social science data. The Institute houses one of the oldest and largest catalogs of machine readable data in the United States. Data sets are searchable and browsable.
• Data Archiving and Networked Services The collection includes datasets from the Humanities, e.g. History and Archaeology, Social sciences, and Geospatial sciences, primarily with a European focus. DANS is an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW) and the Netherlands Organisation for Scientific Research (NWO).
• Child Care and Early Education Research Connections Research Connections offers public access to child care and early education research data, some of which have never before been publicly available. Researchers can download analysis-ready data directly to their desktop or analyze selected data online free of charge. Data training workshops and an archive for research projects serve the entire field.
• Neuroscience Information Framework The Neuroscience Information Framework is a dynamic inventory of Web-based neuroscience resources: data, materials, and tools accessible via any computer connected to the Internet. Access datasets via the NIF Navigator at the right side of the page.
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Produced by the Buros Center for Testing at the University of Nebraska, this resource is essential for evaluating contemporary testing instruments. Designed for novices and professionals alike, it contains full-text reviews for test products in psychology, education, business and leadership. In addition, it provides a bibliography to English and Spanish-language tests.

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This database is an authoritative source of structured information about tests of interest to a variety of fields. Produced by the American Psychological Association, it provides access to thousands of actual test instruments, most of which are available for immediate download and use in teaching and research.

Produced by the Leibniz Institute for Psychology, this database provides comprehensive bibliographic references from research and applied fields in psychology from the German-speaking countries. 

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• APA PsycArticles Full-text coverage from scholarly journals published by the American Psychological Association (APA) and allied organizations. Coverage spans 1894 to present.
• APA PsycInfo Scholarly articles and books in psychology and related disciplines such as medicine, psychiatry, education, social work, law, criminology, social science, and organizational behavior.
• CINAHL Ultimate the definitive resource for nursing and allied health research, providing full text for more than 900 journals. It covers more than 50 nursing specialties and includes quick lessons, evidence-based care sheets, CEU modules and research instruments

• Health & Psychosocial Instruments (HAPI) Provides information on measurement instruments (i.e., questionnaires, interview schedules, checklists, index measures, coding schemes/ manuals, rating scales, projective techniques, vignettes/scenarios, tests) in the fields of health, psychosocial sciences, and organizational behavior. Use of this resource is limited to one (1) simultaneous user. If you are unable to access it, please try again later.
• Psychological Experiments Online Psychological Experiments Online pairs audio and video recordings of quintessential experiments in psychology with thousands of pages of primary-source documents. It's packed with exclusive and hard-to-find materials, including notes from experiment participants, journal articles, books, field notes, and final reports in topics from obedience to authority and conformity to operant conditioning. If you have trouble accessing this resource, please use your browser's "private window" function
• Psychology & Behavioral Sciences Collection Psychology & Behavioral Sciences Collection is a comprehensive database covering information concerning topics in emotional and behavioral characteristics, psychiatry & psychology, mental processes, anthropology, and observational & experimental methods.
• Sage Research Methods Guides users through every step of the research process with resources including books, instructional videos and more on topics such as qualitative and quantitative research, choosing a statistical method, data visualization, and project planning.
• ScienceDirect Science Direct is a leading full-text scientific database offering journal articles and book chapters from more than 3,900 peer-reviewed journals and more than 11,000 books. There are currently more than 9.5 million articles/chapters on subjects in the Health & Life Sciences, Physical Sciences, and Social & Behavioral Sciences.
• SCOPUS Scopus is the largest abstract and citation database of peer-reviewed literature: scientific journals, books and conference proceedings. It delivers a comprehensive overview of the world's research output in the fields of science, technology, medicine, social sciences, and arts and humanities.

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Experimental psychology, the journal for experimental research in psychology.

• ISSN L: 1618-3169
• ISSN Print: 1618-3169
• ISSN Online: 2190-5142

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As its name implies, Experimental Psychology publishes innovative, original, high-quality experimental research in psychology.

Why is Experimental Psychology a quality journal?

• Professional outlet for cutting-edge experimental research in psychology since 50 years
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To get more detailed information, read the Editorial by Andreas B. Eder and Christian Frings.

What makes Experimental Psychology special?

• Now a founding participant journal in the Peer Community In Registered Reports
• Open to all disciplines of experimental research in psychology
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Open Access for UK authors publishing in APA PsycArticles Hogrefe is participating in the open access publishing pilot for the APA PsycArticles database in 2023-26 – this includes eligible articles accepted in Experimental Psychology. Learn more

Announcing a New Submission Category: Replication Reports The Editors are proud to announce a new article category, which gives you as authors the opportunity to present results of studies conducted as either exact or conceptual replications of already published research. For more information, please click here .

Announcing the Peer Community in Registered Reports Experimental Psychology is proud to be a founding participant journal in the recently launched Peer Community in Registered Reports (PCI-RR). After a preprint is posted on a server and submitted for review at PCI, it follows the usual rounds of reviews and revisions. Once authors have their Registered Report recommended by PCI-RR, they have the option to publish their article in a growing list of “PCI-RR-friendly” journals that have committed to accepting PCI-RR recommendations without further peer review – one of them is Experimental Psychology. Click here for more information.

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Article highlights

Recent Editorial

Message From Your New Editor Raymond M. Klein Experimental Psychology, Vol. 68, No. 4, pp. 173-174

Editor’s Picks

(A)symmetries in Memory and Directed Forgetting of Political Stimuli Andrew Franks, Hajime Otani, and Gavin T. Roupe Experimental Psychology, Vol. 70, No. 2, pp. 68-80

Probing the Dual-Route Model of the SNARC Effect by Orthogonalizing Processing Speed and Depth Daniele Didino, Matthias Brandtner, Maria Glaser, and André Knops Experimental Psychology, Vol. 70, No. 1, pp. 1–13

Raymond Klein

Editor-in-chief

Department of Psychology and Neuroscience

Faculty of Science

Dalhousie University

1355 Oxford St.

Editorial assistant

Swasti Arora Department of Psychology and Neuroscience Faculty of Science Dalhousie University 1355 Oxford St. Halifax, Nova Scotia B3H 4R2 Canada Send email

Associate editors

Ullrich Ecker School of Psychological Science University of Western Australia Perth 6009 Australia Send email Associate Professor at the University of Western Australia. His main interests lie in episodic memory, working memory, feature binding, memory updating, as well as the processing of misinformation and its effects on memory and reasoning. He uses mainly behavioural experimentation, augmented by neuroimaging methods (event-related potentials, fMRI) and computational modelling.

Gesa Hartwigsen Lise Meitner Research Group Cognition and Plasticity Max Planck Institute for Human Cognitive and Brain Sciences Stephanstraße 1a 04103 Leipzig Germany Send email Lise Meitner Research Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig (Germany). Her main interest is the potential for adaptive systems plasticity in neural networks for cognitive functions, with a focus on the healthy and lesioned language network. Her group combines neurostimulation and neuroimaging techniques to probe interactions between domain-specific and domain-general networks.

Manuel Perea University of València Av. Blasco Ibáñez, 21 46010 Valencia Spain Send email Professor of Psychology at the University of Valencia (Spain). His main fields of interest are psychology of language, lexical-semantic memory, and cognitive neuroscience.

James R. Schmidt Université de Bourgogne LEAD-CNRS UMR 5022 Pole AAFE 11 Esplanade Erasme 21000 Dijon France Send email Full Professor at the Université de Bourgogne, working in the Laboratoire d'Etude de l'Apprentissage et du Développement (LEAD; Laboratory for Research on Learning and Development). His main research interests are implicit learning, music learning, cognitive control, and neural networks.

Alexander Schütz University of Marburg Department of Psychology Gutenbergstr. 18 35032 Marburg Germany Send email Professor of Experimental Psychology at the University of Marburg (Germany). His main research interests are visual perception, eye movements and their interaction in active perception.

Editorial board

The expertise of the international editorial board covers a broad range of subject areas. All papers submitted to the journal are subject to full peer-review by members of the board and external reviewers. Hartmut Blank, University of Portsmouth, UK (memory (misinformation and social influence), hindsight bias and meta-analysis) Arndt Bröder, University of Mannheim, Germany (memory and metamemory, judgment and decision making) Roberto Dell'Acqua, Università degli Studi di Padova, Italy (visual attention, visual working memory, attentional blink) Edgar Erdfelder, Universität Mannheim, Germany (episodic memory, judgment/reasoning, cognitive modeling, design/power analysis) Christian Frings, University of Würzburg, Germany (action control, perception-action Integration, inhibition (negative priming), multisensory perception) Morris Goldsmith, University of Haifa, Israel (object-based attention, memory accuracy, and metamemory-metacognition) Dirk Kerzel, Université de Genève, Switzerland (visual search, visual working memory, and motion perception) Andrea Kiesel, University of Freiburg, Germany (cognitive control, multitasking, cognitive-motor interference) Iring Koch, RWTH Aachen, Germany (attention & cognitive control (task switching specifically), bilingualism, sequence learning) Joachim I. Krueger, Brown University, RI, USA (social cognition, JDM, free will) Dominique Lamy, Tel Aviv University, Israel (visual search, visual attention, conscious vs. unconscious visual perception)

Stephen Lindsay, University of Victoria, Canada (memory, eyewitness memory, response bias) Ben Newell, University of New South Wales, Australia (judgment, decision making, choice) Klaus Oberauer, Universität Zürich, Switzerland (working memory, executive functions, episodic memory) Michel Regenwetter, University of Illinois at Urbana-Champaign, IL, USA (order-constrained Inference, decision making, probabilistic choice) Rainer Reisenzein, Universität Greifswald, Germany (emotion, surprise, motivation, temporal order) Jeffrey N. Rouder, University of Missouri, MO, USA (methods (Bayesian in particular), individual differences, attention) David Shanks, University College London, UK (learning, memory, and unconscious processes)

Christoph Stahl, University of Cologne, Germany (evaluative conditioning, implicit/unconscious learning, false memory)

Sarah Teige-Mocigemba, University of Marburg, Germany (social cognition, implicit measures, priming)

Sebastien Tremblay, Université Laval, Canada (cognitive limitations, human performance, problem solving, decision making) Christian Unkelbach, Universität zu Köln, Germany (social cognition, person perception, evaluative learning & conditioning, sport psychology) Eva Walther, Universität Trier, Germany (evaluative learning, conditioning, contingency memory) Peter A. White, Cardiff University, UK (causal judgment, causal perception, temporal aspects of perception)

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Psychology 159 (Yancey)

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FamFac - A Database of Famous Faces for Psychology Experiments

Famfac - una base de datos de caras famosas para experimentos de psicología, fábio monteiro.

1 Center for Research in Neuropsychology and Cognitive Behavioral Intervention (CINEICC), Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal., Universidade de Coimbra, University of Coimbra, Coimbra , Portugal

2 William James Center for Research, Department of Education and Psychology, University of Aveiro, Aveiro, Portugal., Universidade de Aveiro, University of Aveiro, Aveiro , Portugal

Paulo Rodrigues

3 Sport, Health & Exercise Research Unit (SHERU), Department of Psychology and Education, University of Beira Interior, Covilhã, Portugal., Universidade da Beira Interior, University of Beira Interior, Covilhã , Portugal

Isabel M. Santos

Pedro bem-haja.

4 CINTESIS@RISE, Department of Education and Psychology, University of Aveiro, Aveiro, Portugal., Universidade de Aveiro, University of Aveiro, Aveiro , Portugal

Pedro J. Rosa

5 Digital Human-Environment Interaction Lab (HEI-Lab), Lusófona University, Lisbon, Portugal., Lusófona University, Lisbon , Portugal

Associated Data

The database presented in this study is openly available at https://osf.io/x3vsy/ . The algorithm that we developed to homogenize the brightness of experimental stimuli can be found and downloaded from https://github.com/PauloJFSFRodrigues/lowlevel-features .

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).

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.

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.

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.

Introducción.

La existencia de una gran variación en las propiedades de bajo nivel de estímulos visuales y la ocurrencia de diversos grados de familiaridad con rostros famosos pueden haber causado un sesgo en los resultados de las investigaciones que intentaron desentrañar los procesos involucrados en el procesamiento de rostros familiares y desconocidos (por ejemplo, las diferencias temporales en la detección de los primeros potenciales relacionados con eventos especializados en el procesamiento de rostros puede ser explicada por diferentes métodos para controlar la variación en las propiedades de bajo nivel de los estímulos visuales).

Para mitigar estos problemas, desarrollamos una base de datos de 183 caras famosas, disponible gratuitamente, cuyas propiedades de bajo nivel (brillo, tamaño, resolución) fueron homogeneizados y el nivel de familiaridad medido.

Método.

El brillo de los estímulos fue estandarizado por un algoritmo personalizado. El tamaño y la resolución de las imágenes fueran homogeneizadas en Gimp. El nivel de familiaridad de los rostros famosos fue medido por un grupo de 48 estudiantes universitarios portugueses.

Resultados.

Nuestros resultados sugirieron que el brillo de cada imagen no difiere significativamente del valor de brillo medio del conjunto de estímulos. Cuarenta y un rostros famosos fueron clasificados como altamente familiares. Principales implicaciones. Este estudio proporciona dos recursos importantes, ya que tanto el algoritmo como la base de datos están disponibles gratuitamente para fines de investigación. Los procedimientos de homogeneización deben garantizar que los estímulos incluidos en la base de datos no provoquen efectos de confusión como los verificados en estudios anteriores.

1. Introduction

People tend to view the ability to recognize and identify an individual face as a straightforward process. However, face recognition is a complex phenomenon. Several models have been developed to explain the mechanisms behind face recognition. For instance, the interactive activation and competition model ( Burton et al., 1999 ) and the sequential model of face recognition ( Bruce & Young, 1986 ) suggest that to successfully recognize a familiar face, one has to perceptually process the face, encode its visual proprieties, and create an integrated representation of its configural/holistic characteristics. Then, this integrated representation has to be matched with traces of visual features and semantic/episodic information stored in long-term memory. On the other hand, the Face-Space theory states that faces are represented on a multidimensional space and that each dimension of this space corresponds to a different face feature (face shape, hair color, and length). According to this theory, each known face is represented by a unique point in space. The precise location of a face is determined by the value that each of its features receives in the scale of each dimension. The perceptual difference between two faces is determined by the distance between their locations in space ( Valentine et al., 2016 ).

Past investigations that studied the mechanisms that underlie face recognition suggested that different processes are involved in familiar and unfamiliar face recognition 1 ( Stacey et al., 2005 ). For instance, familiar faces are recognized more quickly and accurately than unfamiliar faces ( Ramon et al., 2011 ; Stacey et al., 2005). Additionally, recognizing a familiar face activates a set of brain regions -that store semantic, episodic, and emotional information about a specific familiar person- that are not engaged in unfamiliar face processing ( Johnstone & Edmonds, 2009 ; Natu & O’Toole, 2011 ). On the contrary, unfamiliar face recognition is achieved by visually processing early structural representations ( Bruce & Young, 1986 ). Familiar and unfamiliar face recognition are also susceptible to different detrimental factors unfamiliar face recognition is impaired by poor lighting conditions, and changes in pose, expression, context, and viewpoint. However, these variables do not have a significant detrimental effect on familiar face recognition ( Longmore et al., 2017 ; Natu & O’Toole, 2011 ).

This suggests that unfamiliar face processing is more reliant on pictorial information, which becomes less important as faces become more familiar. Additionally, it has been suggested that the internal features of the face (eyes, nose, mouth) are more relevant than external features (hair, ears, face contour) in familiar face recognition ( Johnstone & Edmonds, 2009 ). No particular advantage has been attributed to external or internal features in unfamiliar face recognition (even though a few studies suggested that external features are more important to unfamiliar face recognition) ( Bruce et al., 1999 ).

Several face categories -famous faces ( Gosling & Eimer, 2011 ; Nessler et al., 2005 ), personally familiar faces ( Leibenluft et al., 2004 ), and experimentally learned faces ( Dubois et al., 1999 )- have been used to assess differences in familiar and unfamiliar face processing. The use of famous faces to assess this phenomenon has the advantage of providing rich pictorial, semantic, and episodic information to participants that may facilitate the activation of semantic memory traces during face recognition. Additionally, the continued exposure to famous faces, through media, allows for robust recognition across viewpoints, lighting conditions, and poses ( Natu & O’Toole, 2011 ). However, Ramon et al. (2011) argue that famous faces may bias the results of familiar face processing experiments for at least two reasons: (1) there may be a wide range of exposure to each famous face across participants, and (2) the images of famous faces used in these experiments are often ‘iconic’ pictures of celebrities, which can lead to image-based recognition instead of familiar face recognition (e.g., the participants may recognize the picture without being familiar with the famous face). Image-based recognition relies on different mechanisms than familiar face recognition. Thus, to avoid such a confounding effect, investigations that use famous faces to assess differences in familiar and unfamiliar face processing should select famous faces that are highly familiar to all participants and should not select iconic pictures that can be recognized based on other pictorial features instead of the famous face. Additionally, these investigations must take into account that the level of familiarity of each famous face is constrained by geographic and socio-cultural variables: (1) a highly familiar famous face in the UK is not necessarily universally recognized in France; (2) a face universally recognized in a sample of elderly adults may not be recognized by all participants in a sample of teenagers ( Lima et al., 2021 ). The need to consider the influence of variables, such as the nationality of the participants, led to the development of several databases of famous faces in recent years. For instance, Bizzozero et al. (2007) developed a famous face database and collected normative data for the Italian population. Lima et al. (2021) and Marful et al. (2018) conducted similar endeavors for the Portuguese and Spanish population, respectively. These studies followed extremely rigorous norms and procedures, which ensure that their stimuli can be used to study the underpinnings of familiar face recognition with reduced bias in samples with similar characteristics to theirs. However, these studies did not control the low-level proprieties of their images.

The existence of a high degree of variance in the low-level proprieties (brightness, contrast, movement) of the stimuli used to evaluate differences between familiar and unfamiliar face processing may also bias the results of investigations that seek to disentangle the mechanisms that underpin these two phenomena ( Andrews et al., 2015 ; Bainbridge & Oliva, 2015 ; McCourt & Foxe, 2003 ). For instance, some authors ( Knebel et al., 2008 ; Willenbockel et al., 2010 ) suggested that temporal differences in the detection of the first event-related potentials (ERP) associated with face processing may be caused by different methods of controlling variance in the lowlevel proprieties of experimental stimuli. Additionally, this variance causes an increase in the latency of neuronal responses in the primary visual cortex ( Brannan et al., 1998 ), and in the preliminary phases of thalamic processing ( Heap et al., 2018 ). On the contrary, controlling brightness and contrast histograms, which can be achieved by equating the means and standard deviations of brightness and contrast distributions and by matching the number of pixels at each brightness and contrast level, reduces the variation in neuronal responses in the primary visual cortex ( Bainbridge & Oliva, 2015 ; Willenbockel et al., 2010 ). For instance, Park et al. (2015) used fMRI (functional magnetic resonance imaging) to assess the impact of varying several properties of visual stimuli on several regions along the occipitaltemporal cortex. They found that the response of V1, an early visual area, is significantly smaller if the spectral energy of the stimuli is equated, and their brightness histograms present a skew value of 0. Additionally, salient low-level features may also cause a confounding effect in pupillometry -high spatial frequencies are associated with a smaller pupil size ( Cocker et al., 1994 )- and oculometry studies -stimuli with salient low-level features receive more fixations- ( Orquin & Loose, 2013 ). Thus, investigations that seek to evaluate high-level cognitive functions, such as familiar and unfamiliar face recognition, must ensure that the variance in the low-level proprieties of their experimental stimuli is homogenized between and within experimental conditions. This will ensure that detected effects are explained by high-level properties of the stimuli, and not by possible confounding effects modulated by an elevated degree of variance in their low-level proprieties ( Knebel et al., 2008 ; Lakens et al., 2013 ; Willenbockel et al., 2010).

In this article, we present a database comprising famous faces, whose variance in the low-level proprieties (brightness, size, resolution) was homogenized. Additionally, the familiarity of the famous faces was assessed by a sample of Portuguese college students. The database is available at https://osf.io/x3vsy/ . The complete set of images can be freely downloaded, transformed, and used for research purposes.

2.1 Participants

The sample of this study consisted of 48 unpaid volunteers who attended the first year of the undergraduate course in Psychology at a university in Portugal. The minimum sample size needed to get reliable familiarity scores was based on previous studies that evaluated the same phenomenon ( Gosling & Eimer, 2011 ; Nessler et al., 2005 ). Our study was advertised through word of mouth. The sample was collected by convenience the participants were directly recruited at the campus of the University. Each participant signed an informed consent form prior to the data collection session. All participants (41 females, 7 males; aged: 17-30 years; mean age: 19.02 years) were of Portuguese nationality and had normal or corrected-to-normal vision. This study was approved by the Ethics and Deontology Committee of the University of Aveiro (N ◦ 40-CED/2019, approved on January 22nd, 2020).

2.2 Stimuli

The database consists of 183 famous faces. These images were selected and downloaded from the Wikimedia Commons website. Every selected image was licensed under a Creative Commons License, which enables the free distribution of copyrighted work ( UNESCO, 2018 ). The selected famous faces were considered to be widely known by the general Portuguese public. The database includes Portuguese and foreign actors/actresses, musicians, athletes, TV personalities, politicians, scientists, etc. Each image was converted to greyscale, resized (397 397 pixels), and rotated (to ensure that the nasal bone presented a 0 ◦ degree angle with the horizontal axis of the image) in GIMP (v2.10). The images were converted to Portable Network Graphics (PNG). Their resolution was also homogenized (every image presents a 96dpi 96dpi resolution). An oval mask was applied to every image to hide the maximal amount possible of external features of each face (hair, ears, face contour), without hiding any of its internal features (eyes, nose, mouth). Additionally, the brightness of the images was homogenized by a custom-algorithm developed in Matlab. To achieve this, our algorithm estimated the brightness of each image (sum of the grey value of each pixel of the image divided by the number of pixels of the image) and the mean brightness of the entire set of images. Then, the brightness of each image was subtracted from the mean brightness of the entire set. This difference was then applied to the grey value of each pixel of the respective images. This ensured that the brightness of each image did not differ significantly from the mean brightness of the entire set. Some examples of the final versions of the famous faces are presented in Figure 1 . Our algorithm can be freely used for research purposes and downloaded at https://github.com/PauloJFSFRodrigues/lowlevel-features . The algorithm can be applied to other sets of images to homogenize their brightness values. A detailed description of the features of the algorithm will be presented in another article.

2.3 Procedure

A cross-sectional design was used to assess the familiarity level of the famous faces included in the FamFac database. Data collection procedures took place at the university. A single group of 48 participants evaluated the familiarity level of all of the famous faces included in the FamFac database in a single session. The participants completed a task programmed on E-Prime (v2.0) to assess the familiarity level of the famous faces. Each participant completed the task individually on a PC. At the beginning of the session, the investigators presented verbal instructions on how to complete the task. The task did not contain any practice trials. Throughout the task, each famous face included in the FamFac database was sequentially presented to the participants in random order. In each trial, a famous face was displayed at the center of the screen and a textbox was presented below the famous face. The participants were asked to type some personal information in the textbox if they were able to identify the famous face (e.g., name, or other unique piece of information about the person). We considered that a famous face was correctly identified if the personal information provided by the participants corresponded to the famous face that was depicted (correct responses received a score of 1). Otherwise, the response received a score of 0.

2.4 Data Preparation and Statistical Analyses

2.4.1 familiarity scores.

The familiarity score of every famous face was calculated by multiplying the proportion of correct responses by 100. In other words, to compute the familiarity score of each face we divided the number of correct responses provided by all participants by the total number of participants (48) and multiplied the resulting score by 100. Thus, the familiarity score of the famous faces could range from 0 to 100. We used the same cutoff points employed by Gosling and Eimer (2011) and Nessler et al. (2005) to classify a face as highly familiar. These authors deemed a face as highly familiar if it received a mean familiarity score above 75 on the scales that they used in their studies.

2.4.1 Power Analysis

The number of stimuli (famous faces) needed to carry the inferential analyses was calculated based on a priori power analyses computed with G*Power (version 3.1.9.7; Faul et al., 2007 ). An a priori power analysis was computed for each inferential statistical test that we conducted (a one-sample t -test, a Mann-Whitney U test, an independent samples t -test, a Kruskal-Wallis H test, and a between-subjects one-way ANOVA). As no previous study has assessed the same relationships that we evaluated in this investigation, we used a medium effect size ( d = .5 for tests in which two means were compared, and f = .25 for analyses in which the means of 3 groups are compared) and an alpha value of .05 to compute each power analysis ( Prajapati et al., 2010 ). The highest result of the power analyses (obtained for the between-subjects one-way ANOVA) suggested that a total sample of 159 famous faces was required to achieve a statistical power of .80.

2.4.3 Statistical Analysis

The data collected in this experiment was prepared and analyzed in Microsoft Excel 2016 and IBM SPSS (v28). A one-sample t -test was employed to evaluate if the brightness of each image did not differ significantly from the mean brightness of the entire set.

As mentioned previously, we applied an oval mask to each famous face to remove the maximal amount possible of external features without hiding its internal features. However, the amount of external features that we were able to remove varied from face to face due to several factors (e.g., viewpoint, face size). One of the factors that contributed the most to these differences was the variability in the hairstyles of the famous faces included in the database. For example, we were able to completely remove the hair of some celebrities with short hair, but we had to keep some hair in the case of celebrities who wore bangs. To evaluate if the amount of hair depicted in each picture had a significant impact on the familiarity scores of the famous faces, we split the database into three categories: faces without hair (65 images), faces in which a small amount of hair was kept -e.g., pictures in which we were unable to remove the widow’s peak, a V-shaped point in the hairline in the center of the forehead- (88 images), and faces in which a great amount of hair was kept -e.g., famous faces with bangs- (30 images). A between-subjects one-way ANOVA and a Kruskal-Wallis H test were computed to evaluate if the amount of hair depicted in the pictures had a significant effect in the familiarity scores of the famous faces. Three Kolmogorov-Smirnov tests and a Levene’s test were computed to evaluate if the three groups of images presented normal distributions, and to check if the variance in these three categories was approximately equal. The result of the latter test suggested that the variances of the three groups were not homogenous, F (2 , 180) = 3.50, p = .03. The results of the Kolmogorov-Smirnov tests suggested that the group of images in which a small amount of hair was kept, D (88) = .07, p = .20, and the images in which a great amount of hair was kept, D (30) = .13, p = .20, presented an approximately normal distribution. However, the famous faces that did not presented any hair did not present a normal distribution, D (65) = .11, p = 0.05. As both assumptions of normality and homoscedasticity were not met, we followed the recommendation of Fife-Schaw (2006) and computed a between-subjects one-way ANOVA (parametric test) and a Kruskal-Wallis H test (non-parametric test) to evaluate if the amount of hair depicted in the pictures had a significant effect in the familiarity scores of the famous faces. As both these tests supported similar conclusions, we choose to present the results of the parametric test, because this test is more robust, which decreases the probability of making a Type-I error.

Additionally, we wanted to ascertain if the participants were more familiarized with Portuguese/national famous faces or foreign/international famous faces. Thus, a Mann-Whitney U test and an independent-samples t-test were carried to assess the effect of type of nationality on the familiarity scores of the famous faces. Considering that the subset of Portuguese/national famous faces and the subset of international famous faces presented unequal sizes ( N Portuguese famous faces = 17 vs. N International famous faces = 166), a Levene’s test was carried out to evaluate if the variance in the familiarity scores of the two subsets was approximately equal. The result of this test suggested that the variance in the familiarity scores of both subsets was approximately equal, F (1 , 181)= 1.82, p = .18. Two Kolmogorov-Smirnov tests were carried to evaluate if the familiarity scores of the subset of Portuguese/national famous faces and the subset of international famous faces presented a normal distribution. The familiarity scores of the subset of Portuguese/national famous faces presented a normal distribution, D (17) = .13, p = .20. However, the same was not verified for the familiarity scores of the international famous faces, D (166) = .08, p = .02. As the assumption of normality was not met, we took the recommendation of Fife-Schaw (2006) into account once again and performed an independent samples t-test (parametric test) and a Mann-Whitney U test (non-parametric test). As both tests yielded similar results, we decided to present the results of the parametric test.

Effect sizes were estimated with Cohen’s d . The benchmarks suggested by Cohen (1988) were used to interpret the magnitude of these effects: small effect ( d = .2), medium effect ( d = .5), and large effect ( d = .8).

The brightness of each image was successfully homogenized by the algorithm developed on Matlab. Our results suggested that the brightness of each image did not differ significantly from the mean brightness of the entire stimuli set ( M = 154.08, 95% CI [-.06, 0.06]), t (182) < .001, p > .99, d < .001, which indicates a small effect size. The brightness values of the stimuli are presented in the supplementary materials (see Table S1). An xlxs file with this data can be downloaded at https://osf.io/x3vsy/ .

As previously mentioned, we used the cutoff point employed by Gosling and Eimer (2011) and Nessler et al. (2005) ) to classify a face as highly familiar. Taking these metrics into account, 41 out of the 183 famous faces were highly familiar to our participants. The familiarity scores of the 183 famous faces are displayed in Table 1 . This information can also be downloaded at https://osf.io/x3vsy/ in xlxs format.

The results of the between-subjects one-way ANOVA suggested that the amount of hair depicted in each image of the FamFac did not have a significant effect in the familiarity scores of the famous faces, F (2 , 180) = .25, p = .78, η 2 < .01. The results of the post-hoc tests revealed that the familiarity scores of the images without hair ( M = 47.88, 95% CI [41.22, 54.54]) did not differ significantly from the familiarity scores of the images in which a small amount of hair was kept ( M = 50.42, 95% CI [45.11, 55.72]), or the images in which a great amount of hair was kept ( M = 51.46, 95% CI [39.58, 63.35]) (all p > .05).

Additionally, the result of the independent-samples ttest, t (181) = 1.81, p = .07, d = .46, suggested that the familiarity scores of Portuguese/national famous faces ( M = 60.83, 95% CI [48.57, 73.10]), and the familiarity scores of international famous faces ( M = 48.55; 95% CI [44.43, 52.66]), did not differ significantly, although there was a tendency for Portuguese famous faces to have a higher familiarity score than international famous faces.

4. Discussion

The results of previous studies suggested that processing familiar and unfamiliar faces elicits different behavioral and electrophysiological responses ( Bentin & Deouell, 2000 ; Gosling & Eimer, 2011 ; Ramon et al., 2011 ; Stacey et al., 2005 ). However, the results of electrophysiological and eye-tracking studies that seek to assess the different mechanisms involved in familiar and unfamiliar face processing may be confounded by several exogenous variables that exert a significant influence on the way that pictorial and structural codes of familiar and unfamiliar faces are processed and retrieved, such as the existence of significant variation in the low-level proprieties of the stimuli -e.g., brightness, contrast- ( Knebel et al., 2008 ; Willenbockel et al., 2010 ); or the existence of varying degrees of familiarity with the faces presented to the participants ( Ramon et al., 2011 ). Thus, investigations interested in disentangling the processes involved in familiar and unfamiliar face processing must ensure that each face presented to the participants is universally recognized, and that variation in the low-level proprieties of the stimuli is kept to a minimum. With these objectives in mind, we developed a database comprising 183 images of famous faces originally licensed under a Creative Commons License, whose low-level proprieties (brightness, size, resolution) were homogenized. The complete set of images is available at https://osf.io/x3vsy/ and can be freely downloaded, transformed, and used for research purposes.

We developed an algorithm in Matlab to automatically equate the brightness of the images included in the FamFac. The algorithm successfully homogenized the brightness of the set of stimuli -the brightness of each image did not differ significantly from the mean brightness of the entire set. Some studies suggested that some ERP components (e.g., P1 and N1) are sensitive to variations in the physical properties of stimuli, such as brightness ( Schettino et al., 2016 ; Schindler et al., 2018 ). This effect is minimized when the variation between the low-level features of the stimuli is controlled for ( Schettino et al., 2016 ). Considering that the brightness of each image included in the FamFac database was homogenized, it is possible to suggest that these stimuli should not elicit such confounding electrophysiological modulations. The algorithm used to equate the brightness of the images can be freely downloaded from https://github.com/PauloJFSFRodrigues/lowlevel-features . This code can be used to homogenize the brightness of other images sets.

As previously stated, investigations that use famous faces to study familiar face processing should ensure that the selected famous faces are highly familiar to all participants ( Ramon et al., 2011 ). For instance, to guarantee that the famous faces that were going to be included in their main experiment were highly familiar, Gosling and Eimer (2011) asked eight participants to name and state the profession of a large pool of 129 famous persons. The famous faces that were included in their main experiment were those that were explicitly identified by at least six participants, which can be translated into a familiarity score of 75 on the scale that was used in our study. The same cutoff point was used by Nessler et al. (2005) ; these authors included a famous face in the set of stimuli that was used in their main experiment if its mean rating was higher than 3 (their familiarity scale ranged from 1 to 4). Taking these metrics into account, 41 out of the 183 famous faces included in the FamFac database were considered highly familiar by our sample. Our results also suggested that the familiarity scores of Portuguese/national famous faces and foreigner famous faces did not differ significantly, although approaching statistical significance ( p = .07). Additionally, the subset of Portuguese/national famous faces consisted only of 17 stimuli. Thus, these results must be treated with caution. Ramon et al. (2011) suggested that varying degrees of familiarity with a given famous face between participants may lead to some additional variability in electrophysiological and ocular correlates elicited by this said famous face. Our results suggest that, in the case of the Portuguese population, there may be some advantage in using national famous faces to evaluate the mechanisms involved in familiar face processing, given that this subset presented higher familiarity scores than the subset comprising foreign faces. However, this difference did not achieve statistical significance.

For the sake of clarity, we will now discuss some of the limitations of this study. First of all, we would like to highlight that the number of famous faces with a familiarity score above 75 is relatively limited. We believe that this was due to the difficulty in finding a substantial set of high-quality images whose copyright license enabled us to freely use and transform them. For the same reason, the images included in the database have a low resolution (96dpi 96dpi). The oval mask that was superimposed on the faces to control for external and background features may also have harmed the familiarity scores of the famous faces. Nevertheless, we decided to keep the oval masks due to the high variability of the original images. We believe that keeping the original images without applying the oval mask would have introduced some bias in the familiarity scores because the participants could use the external features of the faces or other pictorial elements of the images to help them recognize the famous face, which could lead to image-based recognition instead of identity-based recognition. This was particularly true for our category of stimuli -famous faces- as some external features, such as hairstyles, could have been associated with the celebrity depicted. However, in the future, it would be interesting to evaluate if the familiarity scores would improve if the famous faces were presented without the oval masks. Importantly, the familiarity scores of this set of stimuli were assessed with a Portuguese sample. Thus, investigations that want to assess familiar face recognition with samples with different nationalities should evaluate the familiarity scores of the faces included in this database for these samples. Additionally, we recommend that investigations that intend to use this database to assess face recognition with Portuguese samples should choose their set of stimuli from the 41 famous faces that received a familiarity score higher than 75. The algorithm that we developed on Matlab successfully controlled the brightness of the images. However, several other low-level features (e.g., image complexity, movement, orientation, contrast) can cast a similar confounding effect in investigations that use electrophysiological or eye-tracking methods to evaluate high-level cognitive functions ( Bainbridge & Oliva, 2015 ; Dragoi et al., 2000 ; Kamitani & Tong, 2006 ). Nonetheless, due to constrained nature of the present stimuli set (faces with ovals hiding all external and background features), we believe that those effects are limited in this set. Still, future studies with similar aims using stimuli with less constrained characteristics should ensure that the low-level features previously mentioned are also homogenized between their stimuli. The development of algorithms like the one we developed to control the brightness of visual stimuli could facilitate this procedure.

5. Conclusions

We believe that the materials made freely available for research purposes within this study (a famous face dataset anda brightness homogenizing algorithm) are particularly useful resources for studies of face processing, but can also be used in other studies which use visual stimuli and may need to control for low-level features. Furthermore, the original images wecollectedwere licensed under a Creative Commons License. Thus, any authors that wish to use this database can use the available stimuli, and transform them to fit the specific needs of their investigations.

10. Data Availability Statement

1 Unfamiliar face recognition refers to the process of recognizing a previously unknown face. For example, when that face is presented among a set of face stimuli and later must be recognized among new distractor faces; or when participants need to decide whether two photographs of unknown faces display the same person or two different people (Johnstone & Edmonds, 2009).

6. Support Files: The following supporting information can be downloaded at: https://osf.io/x3vsy/ , Table S1.

7. Author Contributions: Conceptualization, I.M.S., P.B-H., P.R., P.J.R.; methodology, I.M.S., P.B-H., P.R., P.J.R., and F.M.; software, P.R., and F.M.; formal analysis, F.M., P.B., and P.B-H.; investigation, F.M., and P.R.; data curation, F.M., P.R., and P.B-H.; writingoriginal draft preparation, F.M.; writingreview and editing, F.M., I.M.S., P.B-H, P.R., and P.J.R.; visualization, F.M., and P.R; supervision, I.M.S., and P.R.; project administration, I.M.S.; funding acquisition, I.M.S., and P.R.. All authors have read and agreed to the published version of the manuscript.

8. Funding: This work was supported by national funds through FCT Fundação para a Ciência e Tecnologia, I.P., with the project PTDC/PSI-GER/31082/2017.

9. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics and Deontology Committee of the University of Aveiro (N ◦ 40CED/2019, approved on January 22nd, 2020).

Conflict of interests: The authors have declared that there is no conflict of interest.

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• Optical illusions
• Python tutorials
• Stimulus sets
• Gabor generator

There are many sets of pictures and videos available that have been rated and standardized in various ways. These can be immensely useful as stimuli in psychological experiments.

Tips for creators

Presentation software, fractals and natural scenes, amsterdam library of object images (aloi), bank of standardized stimuli (boss), bonin et al.'s set of 299 pictures, cipr still images, dartmouth database of children’s faces, ecological alternative to snodgrass and vanderwart, geneva affective picture database (gaped), graspable objects and matched non-objects, hatfield image test, international affective pictures system (iaps), l-eft: leuven embedded figures test, migo et al.'s photos with similarity information, multipic: a standardized set of 750 drawings with multilingual norms, natural scenes collection (nature/ campus scenes), nencki affective picture system (naps), nishimoto et al.'s set of 360 pictures, normative ratings for flanker stimuli, novel object and unusual name database (noun), a pool of pairs of related objects (poporo), psychological image collection at stirling (pics), revised snodgrass and vanderwart object pictorial set, segmentation evaluation database, snodgrass and vanderwart object pictorial set, things: object concepts and naturalistic object images, ub kinface database, upenn natural image database, what do saliency models predict, bacs: the brussels artificial characters set, faces and motion exeter database (famed), umla-runge et al.'s action video clips, miscellaneous.

If you have created a stimulus set yourself, here are a few tips:

• Choose a license for distributing your work. As you can see in the list below, many creators do not specify a license. Unlicensed work is non-free by default, which is problematic for usage and sharing. For a useful guide, see http://creativecommons.org/choose/ .
• Upload your work to an easily accessible location. Do not upload your stimuli as supplementary information on a (paywalled) publisher's website. A good site for uploading academic material is FigShare .

If you are looking for software to present stimuli, take a look at OpenSesame , a free and graphical experiment builder.

Picture sets

Description : A collection of fractals and natural images with visual-search targets (a small F or H) embedded in them. The fractals are original. The natural images are adapted from the UPenn natural image database . For each image, a pupillary luminance map and saliency map is available (see paper for details).

License : Creative Commons Attribution

Link : https://github.com/smathot/materials_for_P0010.5

Reference : Mathôt, S., Siebold, A., Donk, M., & Vitu, F. (2015). Large pupils predict goal-driven eye movements. Journal of Experimental Psychology: General , 144 (3), 513-521. doi:10.1037/a0039168

Description : An extensive set of photos of small objects. The viewing angles and lighting conditions (illumination angle and color) have been systematically varied for each object. Stereo images ("3D") are also inluded.

License : ?

Link : http://staff.science.uva.nl/~aloi/

Reference : Geusebroek, J. M., Burghouts, G. J., & Smeulders, A. W. M. (2005). The Amsterdam library of object images. International Journal of Computer Vision , 61 (1), 103–112.

Description : A large set of full color photos of various objects. Highly recommended.

License : Creative Commons Attribution-ShareAlike

Link : http://sites.google.com/site/mathieubrodeur/Home/boss

Reference 1 : Brodeur, M. B., Dionne-Dostie, E., Montreuil, T., & Lepage, M. (2010). The bank of standardized stimuli (BOSS), a new set of 480 normative photos of objects to be used as visual stimuli in cognitive research. PloS ONE , 5 (5), e10773

Reference 2 : O'Sullivan, M., Lepage, M., Bouras, M., Montreuil, T., Brodeur, M. B. (2012). North-American norms for name disagreement: Pictorial stimuli naming discrepancies. PLoS ONE , 7 (10), e47802.

Reference 3 : Brodeur, M. B., Kehayia, E., Dion-Lessard, G., Chauret, M., Montreuil, T., Dionne-Dostie, E., & Lepage, M. (2012). The bank of standardized stimuli (BOSS): comparison between French and English norms. Behavior Research Methods .

Description : A set of 299 black-and-white line drawings, with various normative ratings, such as name agreement (in French) and naming latency.

Link : http://leadserv.u-bourgogne.fr/bases/pictures/

Reference : Bonin, P., Peereman, R., Malardier, N., Méot, A., & Chalard, M. (2003). A new set of 299 pictures for psycholinguistic studies: French norms for name agreement, image agreement, conceptual familiarity, visual complexity, image variability, age of acquisition, and naming latencies. Behavior Research Methods, Instruments, & Computers , 35 (1), 158-167.

Description : A collection of images. Just images, no additional information is provided.

Link : http://www.cipr.rpi.edu/resource/stills/

Reference : ?

Description : Contains images of 40 male and 40 female models between the ages of 6 and 16. Models are photographed on a black background and are wearing black bibs and black hats to cover hair and ears. They are photographed from 5 different camera angles and pose 8 different facial expressions. Models were rated by independent raters and are ranked for the overall believability of their poses.

License : Dartmouth College (custom license)

Link : http://www.faceblind.org/social_perception/K_Dalrymple/DDCF.html

Reference : Dalrymple, K.A., Gomez, J., & Duchaine, B. (2013). The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set. PLoS ONE , 8 (11), e79131. doi:10.1371/journal.pone.0079131

A template based on this set is included with OpenSesame .

Description : A set of 360 colour photographs of objects, animals, and scenes. Various normative ratings are available.

Link : http://dx.plos.org/10.1371/journal.pone.0037527 (see Supporting information for download links)

Reference : Moreno-Martínez, F. J., & Montoro, P. R. (2012). An ecological alternative to Snodgrass & Vanderwart: 360 high quality colour images with norms for seven psycholinguistic variables. PLoS One , 7 (5), e37528

Description : Mostly scenes with a strong valence.

License : Creative Commons Attribution-NonCommercial-ShareAlike

Link : http://www.affective-sciences.org/researchmaterial

Reference : Dan-Glauser, E. S., & Scherer, K. R. (2011). The Geneva affective picture database (GAPED): a new 730-picture database focusing on valence and normative significance. Behavior Research Methods . doi:10.3758/s13428-011-0064-1

Description : A set of graspable objects and non-objects. Each non-object is matched to a real object in terms of texture, using a texture-synthesis algorithm, and shape.

License : Mixed license, see download page for details

Link : https://bitbucket.org/lvanderlinden/materials-004-jov

Reference : van der Linden, L., Mathôt, S., Vitu, F. (2015). The role of object affordances and center of gravity in eye movements towards isolated daily-life objects. Journal of Vision . 15 (5), 1-18. doi:10.1167/15.5.8

Description : A set of high-quality colour photographs, chosen to span a wide range of categories and naming difficulties.

License : Described as 'free from copyright', but you do need to apply via an online form.

Link : http://testbed.herts.ac.uk/HIT/hit_apply.asp

Reference : Adlington, R. L., Laws, K. R., & Gale, T. M. (2009). The HatField image test: A new picture test and norms for experimental and clinical use. Journal of Clinical and Experimental Neuropsychology , 31 (6), 731-75.

Description : A collection of pictures that have been rated on valence, arousal and dominance. Unfortunately, you can't download these pictures directly, but you have to put in a request (see the link below). They are freely available for non-profit research, though.

Link : http://csea.phhp.ufl.edu/media.html

Reference : Lang, P.J., Bradley, M.M., & Cuthbert, B.N. (2008). International affective picture system (IAPS): Affective ratings of pictures and instruction manual. Technical Report A-8 . University of Florida, Gainseville, FL

Description : Multiple images, with different views, emotions, and disguises, of over 200 individuals of many different races.

Link : http://wiki.cnbc.cmu.edu/Face_Place

Reference : Righi, G., Peissig, J. J., & Tarr, M. J. (2012). Recognizing disguised faces. Visual Cognition , 20 (2), 143-169. doi:10.1080/13506285.2012.654624

Description : FaceSrub comprises a total of 107,818 face images of male and female 530 celebrities, with about 200 images per person. The images were retrieved from the Internet and are taken under real-world situations (uncontrolled conditions). Name and gender annotations of the faces are included.

License : Creative Commons NonCommercial-NoDerivs

Link : http://vintage.winklerbros.net/facescrub.html

Reference : Ng, H.W., & Winkler, S. (2014). A data-driven approach to cleaning large face datasets. Proc. IEEE International Conference on Image Processing (ICIP) . Retrieved from http://vintage.winklerbros.net/Publications/icip2014a.pdf

Description : A set of line shapes in isolation, and embedded in a context of other lines.

Link 1 : https://doi.org/10.6084/m9.figshare.3807885

Link 2 : https://doi.org/10.6084/m9.figshare.3807894

Reference : de-Wit, L., Huygelier, H., Hallen, R. V. der, Chamberlain, R., & Wagemans, J. (2017). Developing the Leuven Embedded Figures Test (L-EFT): testing the stimulus features that influence embedding. PeerJ , 5 , e2862. doi:10.7717/peerj.2862

Description : A collection of gray-scale photos, with similarity ratings for pairs of objects within a set (for example, the similarity between pairs of different pens). The idea is very nice, but unfortunately the quality of the photos is fairly low. Also, the stimuli are paywalled together with the paper.

Link : http://link.springer.com/article/10.3758/s13428-012-0255-4/fulltext.html

Reference : Migo, E. M., Montaldi, D., & Mayes, A. R. (2013). A visual object stimulus database with standardized similarity information. Behavior Research Methods , 45 (2), 344–354. doi:10.3758/s13428-012-0255-4

Description : The Multilingual Picture (MultiPic) databank is the result of an international collaborative project intended to provide the scientific community with a set of publicly available 750 drawings from common concrete concepts created by the same author, standardized for name agreement and visual complexity in several languages.

Link : http://www.bcbl.eu/databases/multipic/

Reference : Duñabeitia, J.A., Crepaldi, D., Meyer, A.S., New, B., Pliatsikas, C., Smolka, E., & Brysbaert, M. (2017). MultiPic: A standardized set of 750 drawings with norms for six European languages. Quarterly Journal of Experimental Psychology . doi:10.1080/17470218.2017.1310261

Description : Natural images of nature scenes containing no man-made objects or people (nature scene collection) and university campus scenes containing cars, building, and people (campus scene collection).

Link : http://www.cps.utexas.edu/natural_scenes/

Reference (for the campus scene collection) : Burge, J., & Geisler, W. S. (2011). Optimal defocus estimation in individual natural images. Proceedings of the National Academy of Sciences , 108 (40), 16849–16854.

Reference (for the natural scene collection) : Geisler, W. S., & Perry, J. S. (2011). Statistics for optimal point prediction in natural images. Journal of Vision.

Description : A large set of photos with normative ratings of valence, arousal, and approach avoidance. The stimuli are not directly downloadable, but available upon request.

License : A custom license that permits academic use.

Link : http://naps.nencki.gov.pl/

Reference : Marchewka, A., Zurawski, L., Jednoróg, K., & Grabowska, A. (2013). The Nencki Affective Picture System (NAPS): Introduction to a novel, standardized, wide-range, high-quality, realistic picture database. Behavior Research Methods . doi:10.3758/s13428-013-0379-1

Description : A collection of 360 black-and-white line drawings, with various norms for Japanese.

Link : http://www.springerlink.com/content/5v773074154063rt/13428_2011_Article_176_ESM.html

Reference : Nishimoto, T., Ueda, T., Miyawaki, K., Une, Y., & Takahashi, M. (2012). The role of imagery-related properties in picture naming: A newly standardized set of 360 pictures for Japanese. Behavior Research Methods .

Description : A set of shapes, symbols, letters, false fonts, and digits with various normative ratings.

Link : http://dx.doi.org/10.6084/m9.figshare.977864

Reference : Chanceaux, M., Mathôt, S., & Grainger, J. (2014). Effects of number, complexity, and familiarity of flankers on crowded letter identification. Journal of Vision , 14 (6), 7. doi:10.1167/14.6.7

Description : Database of images of novel, unusual objects for experimental research. The database includes 64 primary stimuli and a collection of 10 novel categories, each including three exemplars.

License : Creative Commons Attribution NonCommercial

Link : http://michaelhout.com/?page_id=759

Reference : Horst, J. S., & Hout, M. C. (in press). The Novel Object and Unusual Name (NOUN) Database: A collection of novel images for use in experimental research. Behavior Research Methods .

Description : A collection of pairs of objects with norms for semantic relatedness. Validated using both behavioural measures and EEG.

Link : http://www.oszillab.net/downloads.php

Reference : Kovalenko, L.Y., Chaumon, M., & Busch, N.A. (2012). A pool of pairs of related objects (POPORO) for investigating visual semantic integration: Behavioral and electrophysiological validation. Brain Topography . doi:10.1007/s10548-011-0216-8

Description : A diverse collection of stimuli, including faces, objects and textures. Some ratings for the faces are also available.

Link : http://pics.psych.stir.ac.uk/

Reference : The makers request that you simply cite the link above.

Description : Full color line drawings, derived from the original Snodgrass & Vanderwart set.

Link : http://wiki.cnbc.cmu.edu/Objects (Unofficial)

Reference : Rossion, B., & Pourtois, G. (2004). Revisiting Snodgrass and Vanderwart’s object pictorial set: The role of surface detail in basic-level object recognition. Perception , 33 (2), 217-236.

Description : A large database of grayscale photos of one or two objects collected from various sources. The primary goal of this database is to test image-segmentation algorithms.

License : Varies per photo.

Link : http://www.wisdom.weizmann.ac.il/~vision/Seg_Evaluation_DB

Description : A classic set of black and white line drawings. Apparently there are some licensing issues and, despite the fact that this is a widely known set of pictures, it seems hard to get a hold of them. I would recommend using the revised set by Rossion & Pourtois instead.

Reference : Snodgrass, J. G., & Vanderwart, M. (1980). A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity. Journal of Experimental Psychology: Human Learning & Memory , 6 (2), 174-215. doi:10.1037/0278-7393.6.2.174

Description : THINGS is a large dataset of 1,854 object concepts and 26,000+ naturalistic object images, compiled through a web search.

License : See https://osf.io/92yhv/

Link : https://osf.io/jum2f/

Reference : Hebart, M. N., Dickter, A.H., Kidder, A., Kwok, W. Y., Corriveau, A., et al. (2019). THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images. PLOS ONE , 14 (10), e0223792. https://doi.org/10.1371/journal.pone.0223792

Description : A large set of photos of people with information about kinship (e.g., the person in photo X is the father of the person in photo Y).

License : Free for academic use

Link : http://www.cse.buffalo.edu/~yunfu/research/Kinface/Kinface.htm

Reference : Xia, S., Shao, M., & Fu, Y. (2011). Kinship verification through transfer learning. International Joint Conferences on Artificial Intelligence , 2539-2544.

Reference : Umla-Runge, K., Zimmer, H. D., Fu, X., & Wang, L. (2012). An action video clip database rated for familiarity in China and Germany. Behavior Research Methods .

Description : A collection of photos of the Okavango Delta of Botswana, a savanna habitat where humans (and their eyes) presumably evolved. It's a bit quirky, perhaps, but I like the concept.

License : Creative Commons Attribution-NonCommercial

Link : http://tofu.psych.upenn.edu/~upennidb/

Reference : Tkačik, G., Garrigan, P., Ratliff, C., Milčinski, G., Klein, J. M., Seyfarth, L. H., Sterling, P., et al. (2011). Natural images from the birthplace of the human eye. PLoS ONE , 6 (6), e20409. doi:10.1371/journal.pone.0020409

Desription : A set of images that includes subjective saliency ratings.

Link : https://labs.psych.ucsb.edu/eckstein/miguel/research_pages/saliencydata.html

Reference : Koehler, K., Guo, F., Zhang, S., & Eckstein, M. P. (2014). What do saliency models predict? Journal of Vision , 14 (3), 14, 1-27. doi:10.1167/14.3.14

False fonts

Description : Three false fonts that are matched in various ways to real Latin characters. Available in .otf format.

License : Unspecified but free to download

Link : https://osf.io/dj8qm/

Reference : Vidal, C., Content, A., & Chetail, F. (2017). BACS: The Brussels Artificial Character Sets for studies in cognitive psychology and neuroscience. Behavior Research Methods . doi:10.3758/s13428-016-0844-8

Description : A set of videos of 32 speaking male actors. Different viewpoints, headgear, and facial expressions are included.

License : Restrictive, but free for academic use.

Link : http://www.chrislongmore.co.uk/famed/index.html

Description : 784 videos of actions with familiarity ratings for Eastern and Western cultures.

Link : http://www.springerlink.com/content/b32254382l261350/13428_2012_Article_189_ESM.html

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Videos at the Library

The U-M Library has a large collection of video materials both in physical and streaming formats.

• The  Askwith Media Library  is your campus source for movies and TV shows.
• All video content is searchable in the Library Catalog Search .
• Streaming video databases include thematic or publisher/distributor based collections of videos and may be browsed or searched independently.

Searching for Video Content in Library Catalog Search

Searching for videos in the Library Catalog Search by using the Filters on the left-hand column to limit the Format to Visual Material.

• Run your search
• You may need to click "Show all ... Format Filters." if you do not see Visual Material listed
• If Visual Material is not listed, then no videos match your search
• Visual Materials include both hard copy and streaming video formats

Streaming Video Databases

A complete list of streaming video databases is available from the Askwith Media Library.

Instructors: Consult the guide from the Askwith Media Library on  Library Digital Films Service - Streaming video for instructors

• PsycTHERAPY ***To access: after entering PsycNET using above link, click on Browse (in the blue menu bar) and then Psychotherapy Demonstration Videos - PsycTHERAPY*** PsycTHERAPY is a database of streaming psychotherapy demonstrations produced by the American Psychological Association. The videos feature some of North America's leading therapists demonstrating the approaches for which they are known in unscripted, spontaneous sessions with participants who have agreed to have their demonstration sessions taped for educational purposes.
• Psychological Experiments Online This link opens in a new window Provides video and documents relating to many important experiments in social, development, and cognitive psychology. This collection includes 50 streaming videos with corresponding searchable transcripts, as well as links to YouTube videos on related topics. It also includes more than 500 books and documents, including original manuscripts and letters relating to many classic experiments. Access limited to current UM students, faculty and staff.
• Counseling and Therapy in Video An online video collection for the study of social work, psychotherapy, psychology, and psychiatric counseling. Contains nearly 1000 hours of video in many formats including lectures, actual therapy sessions, reenactments, documentaries, and more. Covers a variety of treatment modalities and approaches. more... less... Access limited to current UM students, faculty and staff.
• Kanopy Streaming Video - Psychology Kanopy Streaming offers a variety of documentary and feature films from an array of producers and distributors. Includes popular documentaries, psychotherapy videos, psychological trauma training videos, influential psychologists, symptom media collection, mental health and counseling, and more.
• Filmakers Library Online This link opens in a new window Over 1000 documentary films on topics such as health, history, education, gender studies and psychology. Films include searchable transcripts and the ability to save clips and playlists to your user account. Access limited to current UM students, faculty and staff.
• PBS Video Collection This link opens in a new window Online collection of several hundred videos from the Public Broadcasting Service on a variety of topics. Features films from the series Frontline, American Experience, NOVA, Great Performances, America in Primetime, American Masters, e2, and Odyssey. Access limited to current UM students, faculty and staff.
• Clips for Class A collection of videos on all areas of psychology, collected by Cengage Learning's Psychology group. It is intended for use in connection with psychology courses.

Featured: Psychological Experiments Online!

The Psychological Experiments Online collection includes 50 streaming videos with corresponding searchable transcripts, as well as links to YouTube videos on related topics.  It also includes more than 500 books and documents, including original manuscripts and letters relating to many classic experiments.

Experimental (Empirical) Research Articles

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How Can I Find Experimental (Empirical) Articles?

Many of the recommended databases in this research guide contain scholarly experimental articles (also known as empirical articles or research studies or primary research). Search in databases like: 

• APA PsycInfo ​
• ScienceDirect

Because those databases are rich in scholarly experimental articles, any well-structured search that you enter will retrieve experimental/empirical articles. These searches, for example, will retrieve many experimental/empirical articles:

• caffeine AND "reaction time"
• aging AND ("cognitive function" OR "cognitive ability")
• "child development" AND play

Experimental (Empirical) Articles: How Will I Know One When I See One?

Scholarly experimental articles  to conduct and publish an experiment, an author or team of authors designs an experiment, gathers data, then analyzes the data and discusses the results of the experiment. a published experiment or research study will therefore  look  very different from other types of articles (newspaper stories, magazine articles, essays, etc.) found in our library databases..

In fact, newspapers, magazines, and websites written by journalists report on psychology research all the time, summarizing published experiments in non-technical language for the general public. Although that kind of article can be interesting to read (and can even lead you to look up the original experiment published by the researchers themselves),  to write a research paper about a psychology topic, you should, generally, use experimental articles written by researchers. The following guidelines will help you recognize an experimental article, written by the researchers themselves and published in a scholarly journal.

Structure of a Experimental Article Typically, an experimental article has the following sections:

• The author summarizes her article
• The author discusses the general background of her research topic; often, she will present a literature review, that is, summarize what other experts have written on this particular research topic
• The author describes the experiment she designed and conducted
• The author presents the data she gathered during her experiment
• The author offers ideas about the importance and implications of her research findings, and speculates on future directions that similar research might take
• The author gives a References list of sources she used in her paper

Look for articles structured in that way--they will be experimental/empirical articles. ​

Also, experimental/empirical articles are written in very formal, technical language (even the titles of the articles sound complicated!) and will usually contain numerical data presented in tables. 

As noted above, when you search in a database like APA PsycInfo, it's really easy to find experimental/empirical articles, once you know what you're looking for. Just in case, though, here is a shortcut that might help:

First, do your keyword search, for example:

In the results screen, on the left-hand side, scroll down until you see "Methodology." You can use that menu to refine your search by limiting the articles to empirical studies only:

You can learn learn more about searching in APA PsycInfo, including advanced search limiters like methodology, age group, etc.,  from this APA guide . 

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AQA ALEVEL PSYCHOLOGY - Social Influence: Zimbardo’s (1973) Stanford Prison Experiment

Subject: Psychology

Age range: 16+

Resource type: Unit of work

Last updated

4 September 2024

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This is a complete set of notes for Zimbardo’s Stanford Prison Experiment in AQA Alevel Psychology in the subtopic of social influence. This includes his aim, procedure, findings, conclusion and evaluation points. I hope this helps you with your revision. If you have any questions please message me or leave a reviews. Thank you

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Links to data sets and repositories

A wealth of shared data are available for use in psychological science research. These data span a wide variety of topics. Below are examples of electronically available behavioral and social science data.

• Census Data is an introductory link to the many tables that are available.
• Consumer Behavior Data : Requires registration. "The Surveys of Consumers are conducted by the Survey Research Center, under the direction of Richard T. Curtin, at the University of Michigan. Founded in 1946 by George Katona, the surveys have long stressed the important influence of consumer spending and saving decisions in determining the course of the national economy. The Surveys of Consumers have proven to be an accurate indicator of the future course of the national economy."
• Health and Retirement Study A longitudinal study of health, retirement, and aging. User registration required.
• Human Mortality Database provides detailed mortality and population data to researchers, students, journalists, policy analysts, and others interested in the history of human longevity.
• International Math and Science Study (TIMMS) This Boston College-sponsored site includes the TIMSS 1999 International Database among other data. Additionally, guidebooks (.pdf) are available to download.
• National Archive of Computerized Data on Aging (NACDA) NACDA is funded by the National Institute on Aging and was founded to advance research on aging by helping researchers access under-exploited a broad range.
• Inter-university Consortium for Political and Social Research (ICPSR)
• National Election Studies These are databases primarily related to election activity from 1948 through the present. Simple registration is required.
• National Institute on Alcohol Abuse and Alcoholism Alcohol Use and Consumption Tables A large number of html and text files on alcohol use and consumption.
• National Longitudinal Study of Adolescent Health at the University of North Carolina, Chapel Hill.
• Panel Study of Income Dynamics (PSID) is a longitudinal survey of a representative sample of US individuals and the families in which they reside.
• Wisconsin Longitudinal Study (WLS) is a long-term study of a random sample of 10,317 men and women who graduated from Wisconsin high schools in 1957. Survey data were collected from the original respondents or their parents in 1957, 1964, 1975, and 1992 and from a selected sibling in 1977 and 1994. The National Institute on Aging is supporting a new wave of interviews with graduates, siblings, spouses and widows during 2003-2004.

Data repositories

• Harvard-MIT Data Center  manages technology platforms for the Institute for Quantitative Social Science (IQSS).
• Institute for Social Research (ISR) at the University of Michigan Data available from the five centers of ISR, including Center for Political Studies Inter-university Consortium for Political and Social Research, Population Studies Center, Research Center for Group Dynamics, and Survey Research Center.
• National Center for Educational Statistics (NCES)  is the primary federal entity for collecting and analyzing data related to education.
• National Heart, Lung and Blood Institute (NHLBI) Links to data from various epidemiology studies and clinical trials. Access requires application and IRB approval.

Epidemiology studies include:

• Framingham Heart Study-Cohort
• Framingham Heart Study-Offspring
• Honolulu Heart Program (HHP)
• Atherosclerosis Risk in Communities Study (ARIC)
• Coronary Artery Risk Development in Young Adults (CARDIA)
• Cardiovascular Health Study (CHS)
• National Longitudinal Mortality Study (NLMS)
• Puerto Rico Heart Health Program (PRHHP)

Clinical trials include:

• Asymptomatic Cardiac Ischemia Pilot (ACIP)
• Intermittent Positive Pressure Breathing
• Post Coronary Artery Bypass Graft Study (CABG)
• The Thrombolysis in Myocardial InfarTction Study (TIMI II)
• The Lung Health Study (LHS)

General information

• America’s Data Hub
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Federal statistical agencies with data

• National Center for Science and Engineering Statistics (NCSES)
• National Center for Education Statistics (NCES)
• Census data
• National Center for Health Statistics (NCHS)
• National Longitudinal Surveys (NLS)

More data from the federal statistical system

• Agency for Healthcare Research and Quality (AHRQ) specifically the Medical Expenditure Panel Survey (MEPS) surveys
• Substance Abuse and Mental Health Services Administration (SAMHSA) National Survey of Drug Use and Health (NSDUH)
• Health Resources and Services Administration (HRSA) National Center for Health Workforce Analysis

Related information

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