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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.

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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

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Department of Psychology and Neuroscience

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1355 Oxford St.

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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)

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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Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

Writing the Experimental Report: Overview, Introductions, and Literature Reviews

Welcome to the Purdue OWL

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Experimental reports (also known as "lab reports") are reports of empirical research conducted by their authors. You should think of an experimental report as a "story" of your research in which you lead your readers through your experiment. As you are telling this story, you are crafting an argument about both the validity and reliability of your research, what your results mean, and how they fit into other previous work.

These next two sections provide an overview of the experimental report in APA format. Always check with your instructor, advisor, or journal editor for specific formatting guidelines.

General-specific-general format

Experimental reports follow a general to specific to general pattern. Your report will start off broadly in your introduction and discussion of the literature; the report narrows as it leads up to your specific hypotheses, methods, and results. Your discussion transitions from talking about your specific results to more general ramifications, future work, and trends relating to your research.

Experimental reports in APA format have a title page. Title page formatting is as follows:

• A running head and page number in the upper right corner (right aligned)
• A definition of running head in IN ALL CAPS below the running head (left aligned)
• Vertically and horizontally centered paper title, followed by author and affiliation

Please see our sample APA title page .

Crafting your story

Before you begin to write, carefully consider your purpose in writing: what is it that you discovered, would like to share, or would like to argue? You can see report writing as crafting a story about your research and your findings. Consider the following.

• What is the story you would like to tell?
• What literature best speaks to that story?
• How do your results tell the story?
• How can you discuss the story in broad terms?

During each section of your paper, you should be focusing on your story. Consider how each sentence, each paragraph, and each section contributes to your overall purpose in writing. Here is a description of one student's process.

Briel is writing an experimental report on her results from her experimental psychology lab class. She was interested in looking at the role gender plays in persuading individuals to take financial risks. After her data analysis, she finds that men are more easily persuaded by women to take financial risks and that men are generally willing to take more financial risks.

When Briel begins to write, she focuses her introduction on financial risk taking and gender, focusing on male behaviors. She then presents relevant literature on financial risk taking and gender that help illuminate her own study, but also help demonstrate the need for her own work. Her introduction ends with a study overview that directly leads from the literature review. Because she has already broadly introduced her study through her introduction and literature review, her readers can anticipate where she is going when she gets to her study overview. Her methods and results continue that story. Finally, her discussion concludes that story, discussing her findings, implications of her work, and the need for more research in the area of gender and financial risk taking.

The abstract gives a concise summary of the contents of the report.

• Abstracts should be brief (about 100 words)
• Abstracts should be self-contained and provide a complete picture of what the study is about
• Abstracts should be organized just like your experimental report—introduction, literature review, methods, results and discussion
• Abstracts should be written last during your drafting stage

Introduction

The introduction in an experimental article should follow a general to specific pattern, where you first introduce the problem generally and then provide a short overview of your own study. The introduction includes three parts: opening statements, literature review, and study overview.

Opening statements: Define the problem broadly in plain English and then lead into the literature review (this is the "general" part of the introduction). Your opening statements should already be setting the stage for the story you are going to tell.

Literature review: Discusses literature (previous studies) relevant to your current study in a concise manner. Keep your story in mind as you organize your lit review and as you choose what literature to include. The following are tips when writing your literature review.

• You should discuss studies that are directly related to your problem at hand and that logically lead to your own hypotheses.
• You do not need to provide a complete historical overview nor provide literature that is peripheral to your own study.
• Studies should be presented based on themes or concepts relevant to your research, not in a chronological format.
• You should also consider what gap in the literature your own research fills. What hasn't been examined? What does your work do that others have not?

Study overview: The literature review should lead directly into the last section of the introduction—your study overview. Your short overview should provide your hypotheses and briefly describe your method. The study overview functions as a transition to your methods section.

You should always give good, descriptive names to your hypotheses that you use consistently throughout your study. When you number hypotheses, readers must go back to your introduction to find them, which makes your piece more difficult to read. Using descriptive names reminds readers what your hypotheses were and allows for better overall flow.

In our example above, Briel had three different hypotheses based on previous literature. Her first hypothesis, the "masculine risk-taking hypothesis" was that men would be more willing to take financial risks overall. She clearly named her hypothesis in the study overview, and then referred back to it in her results and discussion sections.

Thais and Sanford (2000) recommend the following organization for introductions.

• Provide an introduction to your topic
• Provide a very concise overview of the literature
• State your hypotheses and how they connect to the literature
• Provide an overview of the methods for investigation used in your research

Bem (2006) provides the following rules of thumb for writing introductions.

• Write in plain English
• Take the time and space to introduce readers to your problem step-by-step; do not plunge them into the middle of the problem without an introduction
• Use examples to illustrate difficult or unfamiliar theories or concepts. The more complicated the concept or theory, the more important it is to have clear examples
• Open with a discussion about people and their behavior, not about psychologists and their research

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• Beauty sleep:...

Beauty sleep: experimental study on the perceived health and attractiveness of sleep deprived people

• Related content
• Peer review
• John Axelsson , researcher 1 2 ,
• Tina Sundelin , research assistant and MSc student 2 ,
• Michael Ingre , statistician and PhD student 3 ,
• Eus J W Van Someren , researcher 4 ,
• Andreas Olsson , researcher 2 ,
• Mats Lekander , researcher 1 3
• 1 Osher Center for Integrative Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
• 2 Division for Psychology, Department of Clinical Neuroscience, Karolinska Institutet
• 3 Stress Research Institute, Stockholm University, Stockholm
• 4 Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, and VU Medical Center, Amsterdam, Netherlands
• Correspondence to: J Axelsson john.axelsson{at}ki.se
• Accepted 22 October 2010

Objective To investigate whether sleep deprived people are perceived as less healthy, less attractive, and more tired than after a normal night’s sleep.

Design Experimental study.

Setting Sleep laboratory in Stockholm, Sweden.

Participants 23 healthy, sleep deprived adults (age 18-31) who were photographed and 65 untrained observers (age 18-61) who rated the photographs.

Intervention Participants were photographed after a normal night’s sleep (eight hours) and after sleep deprivation (31 hours of wakefulness after a night of reduced sleep). The photographs were presented in a randomised order and rated by untrained observers.

Main outcome measure Difference in observer ratings of perceived health, attractiveness, and tiredness between sleep deprived and well rested participants using a visual analogue scale (100 mm).

Results Sleep deprived people were rated as less healthy (visual analogue scale scores, mean 63 (SE 2) v 68 (SE 2), P<0.001), more tired (53 (SE 3) v 44 (SE 3), P<0.001), and less attractive (38 (SE 2) v 40 (SE 2), P<0.001) than after a normal night’s sleep. The decrease in rated health was associated with ratings of increased tiredness and decreased attractiveness.

Conclusion Our findings show that sleep deprived people appear less healthy, less attractive, and more tired compared with when they are well rested. This suggests that humans are sensitive to sleep related facial cues, with potential implications for social and clinical judgments and behaviour. Studies are warranted for understanding how these effects may affect clinical decision making and can add knowledge with direct implications in a medical context.

Introduction

The recognition [of the case] depends in great measure on the accurate and rapid appreciation of small points in which the diseased differs from the healthy state Joseph Bell (1837-1911)

Good clinical judgment is an important skill in medical practice. This is well illustrated in the quote by Joseph Bell, 1 who demonstrated impressive observational and deductive skills. Bell was one of Sir Arthur Conan Doyle’s teachers and served as a model for the fictitious detective Sherlock Holmes. 2 Generally, human judgment involves complex processes, whereby ingrained, often less consciously deliberated responses from perceptual cues are mixed with semantic calculations to affect decision making. 3 Thus all social interactions, including diagnosis in clinical practice, are influenced by reflexive as well as reflective processes in human cognition and communication.

Sleep is an essential homeostatic process with well established effects on an individual’s physiological, cognitive, and behavioural functionality 4 5 6 7 and long term health, 8 but with only anecdotal support of a role in social perception, such as that underlying judgments of attractiveness and health. As illustrated by the common expression “beauty sleep,” an individual’s sleep history may play an integral part in the perception and judgments of his or her attractiveness and health. To date, the concept of beauty sleep has lacked scientific support, but the biological importance of sleep may have favoured a sensitivity to perceive sleep related cues in others. It seems warranted to explore such sensitivity, as sleep disorders and disturbed sleep are increasingly common in today’s 24 hour society and often coexist with some of the most common health problems, such as hypertension 9 10 and inflammatory conditions. 11

To describe the relation between sleep deprivation and perceived health and attractiveness we asked untrained observers to rate the faces of people who had been photographed after a normal night’s sleep and after a night of sleep deprivation. We chose facial photographs as the human face is the primary source of information in social communication. 12 A perceiver’s response to facial cues, signalling the bearer’s emotional state, intentions, and potential mate value, serves to guide actions in social contexts and may ultimately promote survival. 13 14 15 We hypothesised that untrained observers would perceive sleep deprived people as more tired, less healthy, and less attractive compared with after a normal night’s sleep.

Using an experimental design we photographed the faces of 23 adults (mean age 23, range 18-31 years, 11 women) between 14.00 and 15.00 under two conditions in a balanced design: after a normal night’s sleep (at least eight hours of sleep between 23.00-07.00 and seven hours of wakefulness) and after sleep deprivation (sleep 02.00-07.00 and 31 hours of wakefulness). We advertised for participants at four universities in the Stockholm area. Twenty of 44 potentially eligible people were excluded. Reasons for exclusion were reported sleep disturbances, abnormal sleep requirements (for example, sleep need out of the 7-9 hour range), health problems, or availability on study days (the main reason). We also excluded smokers and those who had consumed alcohol within two days of the protocol. One woman failed to participate in both conditions. Overall, we enrolled 12 women and 12 men.

The participants slept in their own homes. Sleep times were confirmed with sleep diaries and text messages. The sleep diaries (Karolinska sleep diary) included information on sleep latency, quality, duration, and sleepiness. Participants sent a text message to the research assistant by mobile phone (SMS) at bedtime and when they got up on the night before sleep deprivation. They had been instructed not to nap. During the normal sleep condition the participants’ mean duration of sleep, estimated from sleep diaries, was 8.45 (SE 0.20) hours. The sleep deprivation condition started with a restriction of sleep to five hours in bed; the participants sent text messages (SMS) when they went to sleep and when they woke up. The mean duration of sleep during this night, estimated from sleep diaries and text messages, was 5.06 (SE 0.04) hours. For the following night of total sleep deprivation, the participants were monitored in the sleep laboratory at all times. Thus, for the sleep deprivation condition, participants came to the laboratory at 22.00 (after 15 hours of wakefulness) to be monitored, and stayed awake for a further 16 hours. We therefore did not observe the participants during the first 15 hours of wakefulness, when they had had a slightly restricted sleep, but had good control over the last 16 hours of wakefulness when sleepiness increased in magnitude. For the sleep condition, participants came to the laboratory at 12.00 (after five hours of wakefulness). They were kept indoors two hours before being photographed to avoid the effects of exposure to sunlight and the weather. We had a series of five or six photographs (resolution 3872×2592 pixels) taken in a well lit room, with a constant white balance (×900l; colour temperature 4200 K, Nikon D80; Nikon, Tokyo). The white balance was differently set during the two days of the study and affected seven photographs (four taken during sleep deprivation and three during a normal night’s sleep). Removing these participants from the analyses did not affect the results. The distance from camera to head was fixed, as was the focal length, within 14 mm (between 44 and 58 mm). To ensure a fixed surface area of each face on the photograph, the focal length was adapted to the head size of each participant.

For the photo shoot, participants wore no makeup, had their hair loose (combed backwards if long), underwent similar cleaning or shaving procedures for both conditions, and were instructed to “sit with a straight back and look straight into the camera with a neutral, relaxed facial expression.” Although the photographer was not blinded to the sleep conditions, she followed a highly standardised procedure during each photo shoot, including minimal interaction with the participants. A blinded rater chose the most typical photograph from each series of photographs. This process resulted in 46 photographs; two (one from each sleep condition) of each of the 23 participants. This part of the study took place between June and September 2007.

In October 2007 the photographs were presented at a fixed interval of six seconds in a randomised order to 65 observers (mainly students at the Karolinska Institute, mean age 30 (range 18-61) years, 40 women), who were unaware of the conditions of the study. They rated the faces for attractiveness (very unattractive to very attractive), health (very sick to very healthy), and tiredness (not at all tired to very tired) on a 100 mm visual analogue scale. After every 23 photographs a brief intermission was allowed, including a working memory task lasting 23 seconds to prevent the faces being memorised. To ensure that the observers were not primed to tiredness when rating health and attractiveness they rated the photographs for attractiveness and health in the first two sessions and tiredness in the last. To avoid the influence of possible order effects we presented the photographs in a balanced order between conditions for each session.

Statistical analyses

Data were analysed using multilevel mixed effects linear regression, with two crossed independent random effects accounting for random variation between observers and participants using the xtmixed procedure in Stata 9.2. We present the effect of condition as a percentage of change from the baseline condition as the reference using the absolute value in millimetres (rated on the visual analogue scale). No data were missing in the analyses.

Sixty five observers rated each of the 46 photographs for attractiveness, health, and tiredness: 138 ratings by each observer and 2990 ratings for each of the three factors rated. When sleep deprived, people were rated as less healthy (visual analogue scale scores, mean 63 (SE 2) v 68 (SE 2)), more tired (53 (SE 3) v 44 (SE 3)), and less attractive (38 (SE 2) v 40 (SE 2); P<0.001 for all) than after a normal night’s sleep (table 1 ⇓ ). Compared with the normal sleep condition, perceptions of health and attractiveness in the sleep deprived condition decreased on average by 6% and 4% and tiredness increased by 19%.

 Multilevel mixed effects regression on effect of how sleep deprived people are perceived with respect to attractiveness, health, and tiredness

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A 10 mm increase in tiredness was associated with a −3.0 mm change in health, a 10 mm increase in health increased attractiveness by 2.4 mm, and a 10 mm increase in tiredness reduced attractiveness by 1.2 mm (table 2 ⇓ ). These findings were also presented as correlation, suggesting that faces with perceived attractiveness are positively associated with perceived health (r=0.42, fig 1 ⇓ ) and negatively with perceived tiredness (r=−0.28, fig 1). In addition, the average decrease (for each face) in attractiveness as a result of deprived sleep was associated with changes in tiredness (−0.53, n=23, P=0.03) and in health (0.50, n=23, P=0.01). Moreover, a strong negative association was found between the respective perceptions of tiredness and health (r=−0.54, fig 1). Figure 2 ⇓ shows an example of observer rated faces.

 Associations between health, tiredness, and attractiveness

Fig 1  Relations between health, tiredness, and attractiveness of 46 photographs (two each of 23 participants) rated by 65 observers on 100 mm visual analogue scales, with variation between observers removed using empirical Bayes’ estimates

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Fig 2  Participant after a normal night’s sleep (left) and after sleep deprivation (right). Faces were presented in a counterbalanced order

To evaluate the mediation effects of sleep loss on attractiveness and health, tiredness was added to the models presented in table 1 following recommendations. 16 The effect of sleep loss was significantly mediated by tiredness on both health (P<0.001) and attractiveness (P<0.001). When tiredness was added to the model (table 1) with an estimated coefficient of −2.9 (SE 0.1; P<0.001) the independent effect of sleep loss on health decreased from −4.2 to −1.8 (SE 0.5; P<0.001). The effect of sleep loss on attractiveness decreased from −1.6 (table 1) to −0.62 (SE 0.4; P=0.133), with tiredness estimated at −1.1 (SE 0.1; P<0.001). The same approach applied to the model of attractiveness and health (table 2), with a decrease in the association from 2.4 to 2.1 (SE 0.1; P<0.001) with tiredness estimated at −0.56 (SE 0.1; P<0.001).

Sleep deprived people are perceived as less attractive, less healthy, and more tired compared with when they are well rested. Apparent tiredness was strongly related to looking less healthy and less attractive, which was also supported by the mediating analyses, indicating that a large part of the found effects and relations on appearing healthy and attractive were mediated by looking tired. The fact that untrained observers detected the effects of sleep loss in others not only provides evidence for a perceptual ability not previously subjected to experimental control, but also supports the notion that sleep history gives rise to socially relevant signals that provide information about the bearer. The adaptiveness of an ability to detect sleep related facial cues resonates well with other research, showing that small deviations from the average sleep duration in the long term are associated with an increased risk of health problems and with a decreased longevity. 8 17 Indeed, even a few hours of sleep deprivation inflict an array of physiological changes, including neural, endocrinological, immunological, and cellular functioning, that if sustained are relevant for long term health. 7 18 19 20 Here, we show that such physiological changes are paralleled by detectable facial changes.

These results are related to photographs taken in an artificial setting and presented to the observers for only six seconds. It is likely that the effects reported here would be larger in real life person to person situations, when overt behaviour and interactions add further information. Blink interval and blink duration are known to be indicators of sleepiness, 21 and trained observers are able to evaluate reliably the drowsiness of drivers by watching their videotaped faces. 22 In addition, a few of the people were perceived as healthier, less tired, and more attractive during the sleep deprived condition. It remains to be evaluated in follow-up research whether this is due to random error noise in judgments, or associated with specific characteristics of observers or the sleep deprived people they judge. Nevertheless, we believe that the present findings can be generalised to a wide variety of settings, but further studies will have to investigate the impact on clinical studies and other social situations.

Importantly, our findings suggest a prominent role of sleep history in several domains of interpersonal perception and judgment, in which sleep history has previously not been considered of importance, such as in clinical judgment. In addition, because attractiveness motivates sexual behaviour, collaboration, and superior treatment, 13 sleep loss may have consequences in other social contexts. For example, it has been proposed that facial cues perceived as attractive are signals of good health and that this recognition has been selected evolutionarily to guide choice of mate and successful transmission of genes. 13 The fact that good sleep supports a healthy look and poor sleep the reverse may be of particular relevance in the medical setting, where health estimates are an essential part. It is possible that people with sleep disturbances, clinical or otherwise, would be judged as more unhealthy, whereas those who have had an unusually good night’s sleep may be perceived as rather healthy. Compared with the sleep deprivation used in the present investigation, further studies are needed to investigate the effects of less drastic acute reductions of sleep as well as long term clinical effects.

Conclusions

People are capable of detecting sleep loss related facial cues, and these cues modify judgments of another’s health and attractiveness. These conclusions agree well with existing models describing a link between sleep and good health, 18 23 as well as a link between attractiveness and health. 13 Future studies should focus on the relevance of these facial cues in clinical settings. These could investigate whether clinicians are better than the average population at detecting sleep or health related facial cues, and whether patients with a clinical diagnosis exhibit more tiredness and are less healthy looking than healthy people. Perhaps the more successful doctors are those who pick up on these details and act accordingly.

Taken together, our results provide important insights into judgments about health and attractiveness that are reminiscent of the anecdotal wisdom harboured in Bell’s words, and in the colloquial notion of “beauty sleep.”

What is already known on this topic

Short or disturbed sleep and fatigue constitute major risk factors for health and safety

Complaints of short or disturbed sleep are common among patients seeking healthcare

The human face is the main source of information for social signalling

What this study adds

The facial cues of sleep deprived people are sufficient for others to judge them as more tired, less healthy, and less attractive, lending the first scientific support to the concept of “beauty sleep”

By affecting doctors’ general perception of health, the sleep history of a patient may affect clinical decisions and diagnostic precision

Cite this as: BMJ 2010;341:c6614

We thank B Karshikoff for support with data acquisition and M Ingvar for comments on an earlier draft of the manuscript, both without compensation and working at the Department for Clinical Neuroscience, Karolinska Institutet, Sweden.

Contributors: JA designed the data collection, supervised and monitored data collection, wrote the statistical analysis plan, carried out the statistical analyses, obtained funding, drafted and revised the manuscript, and is guarantor. TS designed and carried out the data collection, cleaned the data, drafted, revised the manuscript, and had final approval of the manuscript. JA and TS contributed equally to the work. MI wrote the statistical analysis plan, carried out the statistical analyses, drafted the manuscript, and critically revised the manuscript. EJWVS provided statistical advice, advised on data handling, and critically revised the manuscript. AO provided advice on the methods and critically revised the manuscript. ML provided administrative support, drafted the manuscript, and critically revised the manuscript. All authors approved the final version of the manuscript.

Funding: This study was funded by the Swedish Society for Medical Research, Rut and Arvid Wolff’s Memory Fund, and the Osher Center for Integrative Medicine.

Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any company for the submitted work; no financial relationships with any companies that might have an interest in the submitted work in the previous 3 years; no other relationships or activities that could appear to have influenced the submitted work.

Ethical approval: This study was approved by the Karolinska Institutet’s ethical committee. Participants were compensated for their participation.

Participant consent: Participant’s consent obtained.

Data sharing: Statistical code and dataset of ratings are available from the corresponding author at john.axelsson{at}ki.se .

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode .

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Experimental Research on Dreaming: State of the Art and Neuropsychoanalytic Perspectives

Perrine m. ruby.

1 INSERM U1028, Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Lyon, France

2 CNRS UMR5292, Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Lyon, France

3 University Lyon 1, Lyon, France

Dreaming is still a mystery of human cognition, although it has been studied experimentally for more than a century. Experimental psychology first investigated dream content and frequency. The neuroscientific approach to dreaming arose at the end of the 1950s and soon proposed a physiological substrate of dreaming: rapid eye movement sleep. Fifty years later, this hypothesis was challenged because it could not explain all of the characteristics of dream reports. Therefore, the neurophysiological correlates of dreaming are still unclear, and many questions remain unresolved. Do the representations that constitute the dream emerge randomly from the brain, or do they surface according to certain parameters? Is the organization of the dream’s representations chaotic or is it determined by rules? Does dreaming have a meaning? What is/are the function(s) of dreaming? Psychoanalysis provides hypotheses to address these questions. Until now, these hypotheses have received minimal attention in cognitive neuroscience, but the recent development of neuropsychoanalysis brings new hopes of interaction between the two fields. Considering the psychoanalytical perspective in cognitive neuroscience would provide new directions and leads for dream research and would help to achieve a comprehensive understanding of dreaming. Notably, several subjective issues at the core of the psychoanalytic approach, such as the concept of personal meaning, the concept of unconscious episodic memory and the subject’s history, are not addressed or considered in cognitive neuroscience. This paper argues that the focus on singularity and personal meaning in psychoanalysis is needed to successfully address these issues in cognitive neuroscience and to progress in the understanding of dreaming and the psyche.

The word “dream” is commonly used to express an unattainable ideal or a very deep and strong desire:

I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their skin, but by the content of their character. Martin Luther King

In dream reports, however, one often notices banal situations, strange scenes, or even frightening events. Why is there such a contrast between the popular meaning of the word “dream” and the content of dream reports? Why are some dream scenes so bizarre? Are dreams built from images that arise randomly from the sleeping brain? Or is the emergence and organization of dream images controlled by currently unknown parameters? Does dreaming have a function?

Answering these questions is not easy because dreaming is elusive. We still do not know when it happens during the night, how long it lasts, whether we can recall its entire content, or how to control it. For more than a century, such limited understanding of dreaming has seriously hampered experimental investigations. Nonetheless, scientific research has managed to produce considerable information about the phenomenology and physiology of dreaming and has improved our understanding of this fascinating phenomenon.

Experimental Research on Dreaming

Dreaming and experimental psychology, dream content.

Dreaming was first investigated on an experimental level in the nineteenth century. Calkins ( 1893 ) published the first statistical results about dreaming and argued that some aspects of dream content could be quantified. Later, questionnaires and automatic analysis of the lexical content of dream reports allowed psychologists to show that dream content has some precise phenomenological characteristics. According to psychological studies (Hall and Van de Castle, 1966 ; Schwartz, 1999 ), visual imagery occurs more frequently in dreams than imagery of other senses (audition, olfaction, touch, and taste); the dream drama is mostly lived by the dreamer from a first-person perspective; some elements of real-life events previously experienced by the dreamer often contribute to the scene of the dream; most often, the dream sequence is not within the dreamer’s voluntary control (i.e., the dreamer may be convinced during the dream that the dream’s story is really happening); temporal and spatial incoherencies can occur in the dream story; the dream report is often full of people interacting with each other (e.g., discussions, fights, pursuit, sexuality); and finally, the dream report often contains strong emotions.

Substantial variability of content exists, however, among the same individual’s dreams and among the dreams of different individuals. Further, psychological studies have shown that many internal and external parameters can influence dream content. For example, males report more aggression and violence in their dreams than do females (Nielsen et al., 2003 ; Schredl et al., 2004 ). External stimulation perceived by the dreamer can be incorporated into dreams (Koulack, 1969 ; Saint-Denys, 1867; Hoelscher et al., 1981 ), as illustrated by the famous Dali painting Dream Caused by the Flight of a Bee around a Pomegranate a Second before Awakening . The current concerns of the subject may also be found in the content of his/her dreams (Schwartz, 1999 ; Domhoff and Schneider, 2008 ), and many aspects of the subject’s daily life were found to influence dream content, including news events (Bulkeley and Kahan, 2008 ), musical practice (Uga et al., 2006 ), religious beliefs (Domhoff and Schneider, 2008 ), chronic pain (Raymond et al., 2002 ), mood (Cartwright et al., 1998a ), or a violent living environment (Valli et al., 2005 ). By contrast, congenital or acquired malformations do not seem to significantly influence dream content (Voss et al., 2010 ; Saurat et al., 2011 ).

Based on these results, two opposing hypotheses were formulated: the continuity hypothesis (Schredl and Hofmann, 2003 ) and the discontinuity hypothesis (Rechtschaffen, 1978 ; Kahn et al., 1997 ; Stickgold et al., 2001 ). The former relies on results showing that the themes of an individual’s thoughts during waking life and dreaming are similar; the latter focuses on the fundamentally different structures of thoughts during waking life and dreaming. Voss et al. ( 2010 ) stressed in their recent paper that these hypotheses represent oversimplified approaches to dream analysis and argued that waking and dreaming thoughts were related but structurally independent; in other words, she argued in favor of merging the continuity and discontinuity hypotheses.

Dream report frequency

Dream report frequency (DRF) can vary within subjects and varies substantially among subjects. In a study of 900 German subjects with a large age range from various socioprofessional categories, the mean DRF was approximately 1 dream report per week (Schredl, 2008 ). This result shows that the dream experience is common and familiar to everyone. Psychological studies have demonstrated that many parameters covary with DRF and may thus influence it.

Sleep parameters

First, DRF varies according to the sleep stage preceding awakening (e.g., Dement and Kleitman, 1957b ; Nielsen, 2000 , for a review). More dream reports are obtained after an awakening during rapid eye movement (REM) sleep than after an awakening during non-REM (NREM) sleep. These results inspired the REM sleep hypothesis of dreaming (see the section Dreaming and Neuroscience). Second, DRF increases with the number of awakenings during sleep, according to retrospective self-evaluations of awakenings (Cory and Ormiston, 1975 ; Schredl et al., 2003 ). Such studies showed that the more the subjects tended to awaken during sleep, the higher their DRF. These results support the hypothesis of Koulack and Goodenough ( 1976 ), which proposes that nocturnal awakenings facilitate the encoding of the dream in memory and thus facilitate dream recall upon awakening. However, this hypothesis has not been tested by measuring awakenings with polysomnographic recordings in healthy subjects with various DRFs. Finally, DRF varies according to the method of awakening. Abrupt awakenings lead to more dream reports than gradual awakenings (Shapiro et al., 1963 , 1965 ; Goodenough et al., 1965 ).

Physiological and environmental parameters

Dream report frequency deceases with age (e.g., Schredl, 2008 ) and tends to be slightly higher among females than males (e.g., Schredl, 2008 ; Schredl and Reinhard, 2008 ). Remarkably, Schredl’s ( 2008 ) results revealed that DRF also varied according to the size of the subject’s place of residence.

Psychological parameters

First, increased professional stress or interpersonal stress resulted in an increase in DRF (for a review, see Schredl, 1999 ). Second, an interest in dreams or a positive attitude toward dreams clearly covaries with DRF (Hill et al., 1997 ; Schredl, 1999 ; Schredl et al., 2003 ). The greater an individual’s interest in dreams, the higher his/her DRF. Third, several cognitive abilities have been found to covary with DRF. Contradictory results have been reported for the correlation between DRF and memory abilities (short-term, long-term, visual, verbal, implicit, and explicit; significant positive correlation: Cory and Ormiston, 1975 ; Belicki et al., 1978 ; Butler and Watson, 1985 ; Schredl et al., 1995 ; Solms, 1997 ; no significant correlation: Cohen, 1971 ; Belicki et al., 1978 ; Schredl et al., 1995 , 1997 , 2003 ; Solms, 1997 ) and the correlation between DRF and visual imagery ( significant positive correlation : Hiscock and Cohen, 1973 ; Richardson, 1979 ; Okada et al., 2000 ; no significant correlation : Hill et al., 1997 ; Okada et al., 2000 ). However, several studies have consistently shown that DRF is positively correlated with creativity (Fitch and Armitage, 1989 ; Schredl, 1999 ; Schredl et al., 2003 ) and intelligence scales (multiple-choice vocabulary test, Schonbar, 1959 ; Shipley Intelligence Scale, Connor and Boblitt, 1970 ). Finally, many authors have reported a correlation between DRF and personality traits. Subjects with a high DRF are more likely to have a personality with thinner boundaries (Hartmann described people with thin boundaries as being open, trustworthy, vulnerable, and sensitive; Hartmann, 1989 ; Hartmann et al., 1991 ; Schredl et al., 2003 ), to be more anxious (Schonbar, 1959 ; Tart, 1962 ), to have a higher level of absorption (the absorption scale measures the capacity to become absorptively involved in imaginative and esthetic experiences; Hill et al., 1997 ; Schredl, 1999 ; Schredl et al., 2003 ), to be more open to experience (Hill et al., 1997 ; Schredl et al., 2003 ), and to be less alexithymic (alexithymia is a personality variable that incorporates difficulty identifying and describing feelings, difficulty distinguishing between feelings and the physical sensation of emotional arousal, limited imaginative processes, and an externally oriented cognitive style; De Gennaro et al., 2003 ; Nielsen et al., 2011 ) compared to subjects with a low dream recall frequency. However, those results have not always been reproducible (e.g., Schredl, 2002 for openness to experience; Cory and Ormiston, 1975 ; Hill et al., 1997 for anxiety; Nielsen et al., 1997 for alexithymia) and, according to the recent review by Blagrove and Pace-Schott ( 2010 ), it is difficult to draw conclusions about a possible link between personality traits and DRF.

In conclusion, numerous parameters have been identified that covary with DRF. Schredl stressed in many of his papers that the studied parameters usually explain only a small percentage of the total variance (e.g., Schredl, 2008 ). Thus, the DRF variation profile suggests that the production, encoding and recall of dreams are influenced by numerous parameters that probably interact with each other.

Dreaming and neuroscience

The neuroscientific approach to dreaming arose at the end of the 1950s with the discovery of REM during human sleep by the American physiologist Nathaniel Kleitman and his team (Aserinsky and Kleitman, 1953 ; Dement and Kleitman, 1957a ). During these sleep episodes with saccades, the researchers noticed a decrease in voltage and an increase in frequency in the EEG, accompanied by an increase in cardiac frequency variability and a decrease in body movements. They concluded that these physiological modifications indicate a particular sleep stage, which they called REM sleep. A few years later, the French team led by neurobiologist Michel Jouvet discovered that the lack of movement during REM sleep in cats was due to a general muscular atonia, controlled notably by the locus coeruleus α in the brainstem (Jouvet and Michel, 1959 ; Berger, 1961 later showed that muscular atonia during REM sleep also occurs in humans). Interestingly, the inability to move during REM sleep indicates deep sleep and paradoxically, the fast EEG activity of REM sleep resembles EEG activity in wakefulness. Jouvet concluded that this particular physiological state is associated with a “third state” of the brain (in addition to the brain states associated with wakefulness and NREM sleep) which he called “paradoxical sleep” instead of “REM sleep” (Jouvet et al., 1959 ; Jouvet, 1992 ). Several years later, Fisher et al. ( 1965 ) discovered another physiological characteristic of REM sleep: the penile erection.

During the same period, the American team noticed that a subject awakened during REM sleep very often reported a dream (80% of awakenings in REM sleep vs. 6% of awakenings in NREM sleep are followed by a dream report, according to Dement and Kleitman, 1957b ). Researchers concluded that dreaming occurs during REM sleep. The eye movements of REM sleep would allow the dreamer to scan the imaginary scene of the dream (the scanning hypothesis); the cerebral cortex activation revealed by the rapid EEG would allow intense cognitive activity, creating the complex stories of a dream; and the lack of muscle tone would prevent the dreamer from acting out his dreams. From that time on, researchers investigated REM sleep to obtain answers about dreaming.

In the 1990s, researchers used functional neuroimaging techniques such as positron emission tomography (PET) to investigate brain activity during REM sleep in humans. This new approach enabled researchers to demonstrate that the functional organization of the brain during REM sleep is different from the functional organization of the brain during wakefulness (Maquet et al., 1996 ; Braun et al., 1998 ). In comparison to wakefulness, brain activity during REM sleep is decreased in some brain regions (e.g., in the dorsolateral prefrontal cortex; Braun et al., 1998 ) and increased in other regions (e.g., in the occipital and temporal cortex, the hippocampus and parahippocampus, the anterior cingulate, the precentral and postcentral gyri, the superior parietal cortex, and the pons; Braun et al., 1998 ; Maquet et al., 2000 ). Looking more generally for brain activity correlating with REM sleep (the vigilance states considered included wakefulness, slow-wave sleep, and REM sleep), Maquet et al. ( 1996 ) found negative correlations in the precuneus, posterior cingulate cortex, temporoparietal junction, and dorsolateral prefrontal cortex and positive correlations in the amygdala, anterior cingulate, postcentral gyrus, thalamus, and pons (see Schwartz and Maquet, 2002 ; Maquet et al., 2005 ; Nir and Tononi, 2010 for reviews). Based on these results, researchers argued that the particular functional organization of the brain during REM sleep could explain the phenomenological characteristics of dream reports (Hobson and Pace-Schott, 2002 ; Schwartz and Maquet, 2002 ; Maquet et al., 2005 ; Nir and Tononi, 2010 ). They considered that brain activity increases and decreases during REM sleep could be interpreted on the basis of what we know about brain activity during wakefulness. In this context, the increased occipital cortex activity during REM sleep could explain the visual component of dream reports because neuroimaging results during wakefulness showed that visual imagery with the eyes closed activates the occipital cortex (Kosslyn and Thompson, 2003 ). The decreased activity in the temporoparietal junction during REM sleep may explain why dreams are mainly experienced in the egocentric coordinates of the first-person; indeed, during wakefulness, activity in the temporoparietal junction was reported to be greater for allocentric vs. egocentric representation (e.g., Ruby and Decety, 2001 ; Zacks et al., 2003 ) and for third- vs. first-person perspective (e.g., Ruby and Decety, 2003 , 2004 ). The increased activity in the hippocampus during REM sleep could explain why dreams are often composed of known images or characters, as the hippocampus is known to be associated with the encoding and retrieval of lived events during wakefulness (e.g., Piolino et al., 2009 ). The decreased activity in the lateral prefrontal cortex during REM sleep could explain why dream stories lack consistency, why the dreamer’s perception of time is altered, why the dream story is beyond the control of the dreamer and why the dreamer is convinced that the dream story is really happening. Indeed, during wakefulness, the lateral prefrontal cortex is involved in executive function, cognitive control, and working memory (Petrides, 2005 ; Koechlin and Hyafil, 2007 ). The increased activity in the medial prefrontal cortex during REM sleep could explain the attribution of thoughts, beliefs, and emotions to the characters in the dream because, during wakefulness, the medial prefrontal cortex is known to participate in mind reading (Ruby et al., 2007 , 2009 ; Legrand and Ruby, 2009 ). The increased activity in the motor cortex (precentral gyrus) during REM sleep could explain the movements of the characters’ bodies in the dream because, during wakefulness, motor imagery, and the imagination of someone’s action from the third-person perspective involve the precentral gyrus (Decety et al., 1994 ; Ruby and Decety, 2001 ). Finally, the amygdala’s activity during REM sleep could explain why emotions, especially fear, are often mentioned in dream reports; indeed, the amygdala is involved in the processing of emotional stimuli during wakefulness (Adolphs, 2008 ).

In conclusion, results from experimental psychology and neuroscience allow us to better understand the phenomenology of dreaming and the cerebral correlates of some characteristics of dream reports. Still, what do they tell us about the role of dreaming? What are the current hypotheses about dream function(s)?

Hypotheses about dream function(s)

No function.

At the end of the twentieth century, the neurologist Alan Hobson, who was profoundly anti-psychoanalysis, proposed a theory that deprived dreaming of any function. Hobson argued that dreaming is an epiphenomenon of REM sleep: “Because dreams are so difficult to remember, it seems unlikely that attention to their content could afford much in the way of high-priority survival value. Indeed, it might instead be assumed that dreaming is an epiphenomenon of REM sleep whose cognitive content is so ambiguous as to invite misleading or even erroneous interpretation” (Hobson et al., 1998 ).

Psychological individualism

In contrast, other teams, like Michel Jouvet’s, believed that dreaming serves a vital function. In 1979, Jouvet’s team blocked muscular atonia during REM sleep in a cat by damaging the locus coeruleus α in its brainstem. This lesion resulted in the appearance of movements during REM sleep. Movies from the Jouvet lab show sleeping cats performing complex motor actions (with altered control and coordination) resembling those of wakefulness, such as fur licking, growling, chasing prey, mastication, and fighting. From these videos, the authors concluded that the cat was acting out its dream, and they called this non-physiological state “oneiric behavior” (Sastre and Jouvet, 1979 ). These results led Jouvet to propose that dreaming plays a role in reinforcing a species’ typical behavior. Later in his career, Jouvet moved toward a hypothesis focusing on the role of dreaming in the individual dimension. He speculated that dreams (note that, for Jouvet, dreams and paradoxical sleep were equivalent) could be involved in psychological individualism and in the stability of the dreamer’s personality (Jouvet, 1991 , 1992 , 1998 ). According to Jouvet, “the brain is the sole organ of homeotherms that do not undergo cell division. We thus have to explain how certain aspects of psychological heredity (found in homozygote twins raised in different surroundings) may persist for a whole life (psychological individuation). A definitive genetic programming during development (by neurogenesis) is unlikely due to the plasticity of the nervous system. That is why we have to consider the possibility of an iterative genetic programming. The internal mechanisms (synchronous) of paradoxical sleep (SP) are particularly adapted to such programming. This would activate an endogenous system of stimulation that would stimulate and stabilize receptors genetically programmed by DNA in some neuronal circuits. The excitation of these neurons during SP leads to oniric behaviors that could be experimentally revealed – the lists of these behaviors are specific to each individual and indirect data suggest a genetic component of this programming. Amongst the mechanisms allowing the iterative programming of SP, sleep is particularly important. Security – and hence the inhibition of the arousal system – is a sine qua non-condition for genetic programming to take place. In that sense, sleep could very well be the guardian of dreaming” (Jouvet, 1991 ). In other words, Jouvet’s hypothesis is that paradoxical sleep restores neuronal circuitry that was modified during the day to preserve the expression of the genetic program that codes for psychological characteristics. This process would ensure the stability of personality across time.

The threat simulation theory

The Finnish psychologist Antti Revonsuo recently proposed a hypothesis called threat simulation theory, which explains the fearful characteristics of dream content (Revonsuo, 2000 ; Valli and Revonsuo, 2009 ). According to this theory, dreams serve as virtual training places to improve threat avoidance or threat fighting ability. The theory postulates that such nocturnal training makes the dreamer more efficient at resolving threatening situations during wakefulness.

Emotional regulation

Cartwright et al. ( 1998a , b ) defended the idea that dreaming is involved in emotional regulation. Her team showed that, in healthy subjects, the depression level before sleep was significantly correlated with affect in the first REM report. Her team also observed that low scorers on the depression scale displayed a flat distribution of positive and negative affect in dreams, whereas those with a depressed mood before sleep showed a pattern of decreasing negative and increasing positive affect in dreams reported from successive REM periods (Cartwright et al., 1998a ). These results led Cartwright’s team to suggest that dreaming may actively moderate mood overnight in normal subjects. The team strengthened this hypothesis by showing that among subjects who were depressed because of a divorce, those who reported more negative dreams at the beginning of sleep and fewer at the night’s end were more likely to be in remission 1 year later than subjects who had fewer negative dreams at the beginning of sleep and more at the end of the night (Cartwright et al., 1998b ). The researchers concluded that negative dreams early in the night may reflect a within-sleep mood regulation process, whereas those that occur later may indicate a failure in the completion of this process.

Memory consolidation

Finally, a current mainstream hypothesis in cognitive neuroscience credits sleep and dreaming with a role in memory consolidation (for a recent review, see Diekelmann and Born, 2010 ). Numerous studies have shown that brain activity during training is replayed during post-training sleep (e.g., using a serial reaction time task Maquet et al., 2000 , demonstrated replay during REM sleep; using a maze exploration task Peigneux et al., 2004 , demonstrated replay during slow-wave sleep). Decreased performance during the post-training day in sleep-deprived subjects further suggested that the replay of brain activity at night contributes to memory consolidation (e.g., Maquet et al., 2003 ). Only recently, however, have experimental results in humans argued in favor of a role of dreaming per se in memory consolidation. In one study, subjects were trained on a virtual navigation task before taking a nap. Post-nap tests showed that subjects who dreamed about the task performed better than subjects who did not dream (note that only 4 out of 50 subjects dreamed about the task in this study; Wamsley et al., 2010 ). Using a different approach, Nielsen and colleagues provided additional arguments supporting a link between dreams and memory (Nielsen et al., 2004 ; Nielsen and Stenstrom, 2005 ). This team demonstrated that dreams preferably incorporate events that the dreamer lived the day before and events that the dreamer lived 7 days before the dream (U shaped curve). Animal studies have shown that after associative learning, the excitability of hippocampal cells increases (which leads to an increase in neuronal plasticity) and then returns to baseline 7 days after training (Thompson et al., 1996 ). The similarity between the delay of episodic event incorporation into dreams and the delay of post-training cellular plasticity in the hippocampus led the Canadian team to suggest a link between dreaming and episodic memory consolidation.

In summary, the preceding section describes the current state of the art on dreaming, its phenomenology and cerebral correlates and hypotheses about its functions. Some substantial advances have been made, but much remains to be understood.

Unresolved Issues

The link between oneiric behaviors and dream reports.

A piece of evidence in favor of a strong link between REM sleep and dreaming is the oneiric behavior (the appearance of complex motor behaviors when motor inhibition is suppressed during REM sleep) discovered by Sastre and Jouvet ( 1979 ) in cats and reproduced by Sanford et al. ( 2001 ) in rats. Researchers interpreted these results as the animal acting out its dream. However, as animals do not talk, the link between oneiric behavior and dream recall cannot be tested experimentally. This limitation seriously hampers our understanding of dreaming. In humans, complex motor behaviors (e.g., talking, grabbing, and manipulating imaginary objects, walking, and running) can also occur during REM sleep in a pathological context. This syndrome is called REM sleep behavior disorder (RBD). It can be caused by substance withdrawal (e.g., alcohol, Nitrazepam) or intoxication (e.g., caffeine, tricyclic antidepressants) or by various diseases (e.g., Parkinson’s and Alzheimer’s diseases, pontine neoplasms). According to physicians experts on this syndrome, some patients report dreams that are consistent with their behaviors in REM sleep (Mahowald and Schenck, 2000 ). According to the literature, however, such matches seem to be loose and not systematic. Only one study has tested whether observers can link dream content to sleep behaviors in RBD (Valli et al., 2011 ). In this study, each video recording of motor manifestations was combined with four dream reports, and seven judges had to match the video clip with the correctly reported dream content. The authors found that reported dream content can be linked to motor behaviors at a level better than chance. However, only 39.5% of video-dream pairs were correctly identified. Note, however, that because the authors obtained only movements and not behavioral episodes for many RBD patients, the link between videos and dream reports was unfairly difficult to make.

It is important to note that motor behavior during sleep can happen outside of REM sleep. Sleepwalking and sleep terrors, which occur during NREM sleep, are usually not considered dream enactments. However, we know that dreams can happen during NREM sleep, and many patients report dreamlike mentation after awakening from sleepwalking or sleep terrors (71%, according to Oudiette et al., 2009 ). In addition, Oudiette et al. ( 2009 ) reported that the dreamlike mentation can correspond with the sleep behavior in NREM sleep. Consequently, the authors concluded that sleepwalking may represent an acting out of corresponding dreamlike mentation.

Recent research suggests that any kind of motor behavior during sleep can be considered an oneiric behavior. One of the challenges for future research is to test the strength of the link between these oneiric behaviors and dream reports in a controlled and systematic way.

Neurophysiological correlates of dreaming

Despite the numerous neuroimaging studies of sleep in humans, the neurophysiological correlates of dreaming remain unclear.

Indeed, dreaming can happen during NREM sleep, and although NREM brain activity differs substantially from REM sleep brain activity (Maquet et al., 2000 ; Buchsbaum et al., 2001 ), some NREM dreams are phenomenologically indistinguishable from REM dreams (Hobson, 1988 ; Cavallero et al., 1992 ; Cicogna et al., 1998 ; Wittmann et al., 2004 ). This phenomenon is difficult to understand given what we currently know about the sleeping brain and about dreaming. One explanation may rely on the possibility that brain activity during sleep is not as stable as we think.

Brain activity during REM sleep in humans is considered to be well understood (Hobson and Pace-Schott, 2002 ; Schwartz and Maquet, 2002 ; Nir and Tononi, 2010 ), but several results question this notion. First, contrary to the common belief that dorsolateral prefrontal cortex activity decreases during REM sleep, several studies have reported increased activity in the dorsolateral prefrontal cortex during REM sleep (Hong et al., 1995 , 2009 ; Nofzinger et al., 1997 ; Kubota et al., 2011 ). Second, brain activity during REM sleep is heterogeneous. The mean regional cerebral blood flow during 1 min of REM sleep (e.g., as reported in Maquet et al., 1996 ) and the regional cerebral blood flow associated with the rapid eye movements of REM sleep (Hong et al., 2009 ; Miyauchi et al., 2009 ) highlight different brain regions. Finally, few congruencies have been noted in the results of studies investigating brain activity during REM sleep (Hong et al., 1995 , 2009 ; Maquet et al., 1996 , 2000 ; Braun et al., 1997 , 1998 ; Nofzinger et al., 1997 ; Peigneux et al., 2001 ; Wehrle et al., 2005 ; Miyauchi et al., 2009 ; Kubota et al., 2011 ), even between studies using the same technique and the same contrasts (e.g., Braun et al., 1998 ; Maquet et al., 2000 ), or between studies investigating the same REM event (e.g., brain activity associated with rapid eyes movements, as in Peigneux et al., 2001 ; Wehrle et al., 2005 ; Hong et al., 2009 ; Miyauchi et al., 2009 ). Furthermore, few brain regions are consistently reported across the majority of the studies. This inconsistency suggests great intra- and intersubject variability in brain activity during REM sleep in humans. A challenge for future research will be to find out whether the variability in brain activity during REM sleep can be explained by the variability in dream content.

Because dream reports can be collected after awakenings from any sleep stage, one may hypothesize that the brain activity that subserves dreaming (if such brain activity is reproducible across dreams) is quite constant throughout the night and can be observed during all sleep stages. Some results have supported this hypothesis and encouraged further attention in this direction. Buchsbaum et al. ( 2001 ), for example, reported that metabolism in the primary visual areas and certain parts of the lateral temporal cortex does not fluctuate much across REM and slow-wave sleep. Similarly, Nielsen’s team found that dream recall (vs. no dream recall) was associated with decreased alpha (8–12 Hz) power in the EEG preceding awakening, regardless of the sleep stage (Stage 2 or REM sleep; Esposito et al., 2004 ). Interestingly, some authors have suggested that decreased power in the alpha band during wakefulness reflects search and retrieval processes in long-term memory (for a review, see Klimesch, 1999 ).

Processes of selection and organization of dream representations

Nielsen’s team found that episodic events from the 1, 7, and 8 days before a dream were more often incorporated into the dream than were events from 2 or 6 days before the dream (Nielsen et al., 2004 ; results reproduced by Blagrove et al., 2011 ). This result tells us that internal processes control and shape dream content and thus help us to constrain and shape hypotheses about the function and biological basis of dreaming.

At the end of the nineteenth century, Saint-Denys (1867) showed that a sensory stimulus (e.g., the scent of lavender) presented to a sleeping subject without his or her knowledge could induce the incorporation of an event associated with the stimulus (e.g., holidays spent near a lavender field) into the dream, regardless of the delay between the dream and the association stimulus/events (lavender scent/holidays). The author demonstrated that the external world can influence dream content in a direct or indirect way.

Finally, it appears that both external and internal parameters can shape or govern dream content. Nonetheless, few of these parameters are known, and some regularities in the phenomenology of dreams suggest that more influencing parameters remain to be discovered. For example, some individuals experience recurring themes, characters, or places in their dreams. In line with this observation, Michael Schredl’s team showed that the content and style of a person’s life strongly influence dream content (Schredl and Hofmann, 2003 ). However, the rule(s) governing which lived events are incorporated into dreams remain unknown. Do the representations constituting the dream emerge randomly from the brain, or do they surface according to certain parameters? Similarly, is the organization of the dream’s representations chaotic, or is it determined by rules? Does dreaming have a meaning? What is/are the function(s) of dreaming?

Dreaming, Psychoanalysis, and Neuropsychoanalysis

Psychoanalysis, which was developed by the neurologist Sigmund Freud in the beginning of the twentieth century, proposes answers to the questions raised above. Indeed, his theory of the human mind comprises hypotheses about the rules of selection and organization of the representations that constitute dreams.

At the beginning of the twentieth century, Freud presented the concept of the unconscious. He proposed that a part of our mind is made up of thoughts, desires, emotions, and knowledge that we are not aware of, but that nevertheless profoundly influence and guide our behaviors. In his books (e.g., Freud, 1900, 1920 ), Freud proposes that the unconscious mind comes out in slips and dreams. Its expression, however, is coded within dreams (the work of dream), and unconscious thoughts are distorted before they emerge in the conscious mind of the sleeping subject (manifest content of the dream). As a consequence, the dreamer is not disturbed by repressed and unacceptable thoughts (latent content of the dream) and can continue sleeping (this is the reason why Freud considered dreams the guardians of sleep). Hence, according to Freud, decoding dreams’ latent content provides an access to the unconscious mind.

In Freud’s theory of the mind, unconscious thoughts and feelings may cause the patient to experience life difficulties and/or maladjustment, and free unconscious thoughts can help the patient gain insight into his/her situation. As a consequence, Freud developed techniques to decode dreams and provide a way for an analyst to look inside the words and unconscious images of the patient, and to free them through patient insight. One of these techniques is called free association, and is regarded as an essential part of the psychoanalytic therapy process. In order for an analyst to get to the latent content of a dream, he requires the patient to discuss the dream’s manifest content and encourage free association about the dream. Free association is the principle that the patient is to say anything and everything that comes to mind. This includes decensoring his/her own speech so that he/she truly expresses everything. Over time, the therapist or analyst will draw associations between the many trains of uncensored speech the patient shares during each session. This can lead to patient insight into their unconscious thoughts or repressed memories, and the accomplishment of their ultimate goal of “freedom from the oppression of the unconscious” (Trull, 2005 ).

Hence, Freud considered that dreams, as well as slips, have a meaning and can be interpreted, so that one is justified in inferring from them the presence of restrained or repressed intentions (Freud, 1900, 1920 ). Note that, in Freud’s theory of the mind, the words “meaning” and “intention” are closely linked: “Let us agree once more on what we understand by the ‘meaning’ of a psychic process. A psychic process is nothing more than the purpose which it serves and the position which it holds in a psychic sequence. We can also substitute the word ‘purpose’ or ‘intention’ for ‘meaning’ in most of our investigations” (Freud, 1920 ).

In other words, according to Freud, decoding dreams with the free association method provides an access to what makes each of us so special, uncorvering the forces that guide one’s behavior. It gives access to an unknown dimension of ourselves that is fundamental in understanding who we are. It provides access to personal meaning.

This hypothesis, attributing significant importance and meaning to dreams, has rarely been considered by neuroscientists who often consider Freud’s work and theory unscientific.

However, this situation may change as the relationship between psychoanalysis and neuroscience evolves. The starting point was the creation of the International Society for Neuropsychoanalysis in 2000. It was founded by neuropsychologist and psychoanalyst Mark Solms with the intention to promote interactions and collaborations between psychoanalysis and neuroscience. The challenge was serious, as illustrated by neuroscientist Alan Hobson’s aggressiveness in the famous dream debate (Alan Hobson vs. Mark Solms) entitled “Should Freud’s dream theory be abandoned?” held in Tucson, Arizona, in 2006 during the Towards a Science of Consciousness meeting (scientific arguments can be found in Solms, 2000 and Hobson et al., 2000 ). Alan Hobson tried to convince the assembly that Freud was 100% wrong and that Freud’s dream theory was misguided and misleading and should be abandoned. He aimed to demonstrate that Freud’s dream theory is incompatible with what we know about how the brain works. He added that Freud’s dream theory was not scientific because it was not testable or falsifiable. Finally, he presented his model of dreaming, the activation-synthesis hypothesis (Hobson and McCarley, 1977 ; Hobson et al., 2000 ): “The Activation-Synthesis model of dream construction proposed that the phasic signals arising in the pontine brainstem during REM sleep and impinging upon the cortex and limbic forebrain led directly to the visual and motor hallucinations, emotion, and distinctively bizarre cognition that characterize dream mentation. In doing so, these chaotically generated signals arising from the brain stem acted as a physiological Rorschach test, initiating a process of image and narrative synthesis involving associative and language regions of the brain and resulting in the construction of the dream scenarios.” In contrast, Mark Solms demonstrated that what is currently known about the dreaming brain is at least broadly consistent with Freud’s dream theory. He argued that it is generally accepted that brain stem activation is necessary, but not sufficient, to explain the particular characteristics of dream consciousness. What does explain the particular characteristics of dream consciousness, according to Solms, are the following features of brain activity during REM sleep (Braun et al., 1997 ): the activation of core forebrain emotion and instinctual drive mechanisms, i.e., the limbic and paralimbic brain areas (the anterior cingulate, insula, hippocampus, parahippocampal gyrus, and temporal pole), and of the posterior perceptual system (the fusiform gyrus, superior, inferior and middle temporal gyrus, and angular gyrus) and the deactivation of executive dorsolateral frontal control mechanisms (the dorsolateral prefrontal cortex). He further argued that his lesion studies (Solms, 1997 ) are congruent with neuroimaging results because they showed that a total cessation of dreaming results from lesions in the medial part of the frontal lobe and in the temporoparietal junction (whereas no cessation of dreaming was observed for core brainstem lesions or for dorsolateral prefrontal lesions). Finally he emphasized that the activation of motivational mechanisms (such as drives and basic emotions) and of posterior perceptual system associated with deactivation of the executive control (i.e., reality oriented regulatory mechanism) during REM sleep, is broadly consistent with Freud’s dream theory which claims that our instinctual drive states (notably appetitive and libidinal drive system) are relatively disinhibited during sleep. Note that experimental results demonstrating the existence of unconscious representations that guide behavior (e.g., Shevrin and Fritzler, 1968 ; Bunce et al., 1999 ; Arminjon, 2011 , for a review) could also have been cited in support of Freud’s dream theory. This debate was a success for Mark Solms and neuropsychoanalysis. Indeed, at the end of the debate, approximately 100 people voted “no” (i.e., “Freud’s dream theory should not be abandoned”), approximately 50 people voted “yes” and 50 voted “I don’t know”.

Solms’ ( 1997 , 2000 ) approach to dreaming and his experimental results fundamentally challenged our current understanding of dreaming. He proposes that dreaming and REM sleep are controlled by different brain mechanisms. According to Solms, REM sleep is controlled by cholinergic brain stem mechanisms, whereas dreaming is mediated by forebrain mechanisms that are probably dopaminergic. This implies that dreaming can be activated by a variety of NREM triggers. Several experimental results support this hypothesis.

First, behavioral studies have demonstrated that the link between REM sleep and dream reports is lax. Subjects awakened during NREM sleep can recall dreams at a high rate (Foulkes, 1962 : 74% of awakenings in NREM sleep were followed by dream reports; Cavallero et al., 1992 : 64%; Wittmann et al., 2004 : 60%); dreams can be recalled after a nap consisting only of NREM sleep (Salzarulo, 1971 ; Palagini et al., 2004 ); and some individuals never recall dreams, even when awakened from REM sleep (Pagel, 2003 ). In addition, in healthy subjects with a normal dream recall frequency (around 1 dream recall per week, Schredl, 2008 ), dream recall after an awakening during REM sleep is not systematic: 5–30% of awakenings in REM sleep are not followed by a dream recall, according to the literature (e.g., Dement and Kleitman, 1957a , b ; Foulkes, 1962 ; Hobson, 1988 ). Finally, 5–10% of NREM dreams cannot be distinguished from REM dreams based on their content (Hobson, 1988 ; Cavallero et al., 1992 ; Cicogna et al., 1998 ; Wittmann et al., 2004 ).

Second, as Solms ( 2000 ) argued, the amount of dream recall can be modulated by dopamine agonists (Scharf et al., 1978 ; Nausieda et al., 1982 ) without concomitant modification of the duration and frequency of REM sleep (Hartmann et al., 1980 ). Dream recall can be suppressed by focal brain lesions (at the temporo-parieto-occipital junction and ventromedial prefrontal cortex; Solms, 1997 , 2000 ). These lesions do not have any appreciable effects on REM frequency, duration, or density (Kerr et al., 1978 ; Michel and Sieroff, 1981 ). Finally, some clinical studies suggest that a dream can be triggered by nocturnal seizures in NREM sleep, i.e., by focal brain stimulation. Some cases of recurring nightmares caused by epileptiform activity in the temporal lobe have indeed been reported (Solms, 2000 ).

Conclusion: Collaboration between Neuroscience and Psychoanalysis Would Benefit Dream Research

Considering the issues that remain unresolved (e.g., neurophysiologic variability, parameter(s) influencing the emergence of representations in dreams, the meaning of dreams), a psychoanalytic perspective would certainly benefit dream research by providing new directions/leads and helping to reach a comprehensive understanding of dreaming.

On the one hand, psychological research has demonstrated that dream content is influenced by one’s personal life, especially personal concerns (Schwartz, 1999 ; Schwartz and Maquet, 2002 ; Schredl and Hofmann, 2003 ), and some neuroscientists have hypothesized that dreaming is involved in psychological individualism. Thus, both psychology and neuroscience have provided results and hypotheses that validate the possibility that dreaming has something to do with personal and meaningful issues. On the other hand, Freud argued that the unconscious, which guides behaviors and desires, express itself during dreams. The two disciplines’ (cognitive neuroscience and psychoanalysis) convergence on dreaming thus seems obvious; however, very little collaboration has occurred to date.

Note that some experimental studies in psychology have considered the psychoanalytic perspective. For example, Greenberg et al. ( 1992 ) attempted “a research-based reconsideration of the psychoanalytical theory of dreaming.” They evaluated the presence of problems (defined as an expression of negative feeling or any situation evoking such feeling or requiring some change or adaptation) during dreaming and pre- and post-sleep wakefulness in two subjects. They showed that problems occurred very frequently in the manifest dream content and that these problems were nearly systematically related to the problems noted during pre-sleep wakefulness. In addition, they observed that effective dreams (i.e., dreams that presented some solution to the individuals’ problems) were followed by a waking state in which the impact of the problems was diminished, whereas ineffective dreams were followed by the persistence of the problems. This study thus confirmed that personal concerns influence dream content. In addition it provided new results suggesting that dreaming may have some psychological problem-solving function (this result recalls the neuroscientific findings that sleep has a cognitive problem-solving function associated with brain reorganization; e.g., Wagner et al., 2004 ; Darsaud et al., 2011 ). Greenberg et al.’s ( 1992 ) study managed to quantify personal issues and clearly broadened the cognitive neuroscience perspective on dreaming. To proceed further, approaches integrating psychoanalysis and neuroscience must now be developed. Several subjective issues at the core of the psychoanalytic approach, such as the concept of personal meaning, the concept of unconscious episodic memory and the subject’s history, are not addressed or considered in cognitive neuroscience. This limitation hampers the understanding of psychological and neurophysiological functioning in humans. These issues must be addressed, and the expertise of psychoanalysts in singularity and personal meaning is needed to do so in neuroscience and to further the understanding of dreaming and of the psyche.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Experimental Psychology Research Paper Topics

This page provides a comprehensive list of experimental psychology research paper topics , tailored specifically for students aiming to explore and understand the intricacies of human psychological processes through empirical research. Experimental psychology serves as a cornerstone of psychological science, employing rigorous scientific methods to investigate and interpret the vast complexities of human behavior and mental functions. Through carefully designed experiments, researchers can isolate variables and establish causal relationships, paving the way for advancements in our understanding of perception, cognition, emotion, and other psychological phenomena. By delving into these topics, students will gain valuable insights into the experimental designs, methodologies, and ethical considerations that define this vibrant field. This resource is designed to inspire and facilitate impactful research endeavors, equipping students with the knowledge to contribute significantly to the expansion and refinement of psychological science.

100 Experimental Psychology Research Paper Topics

Experimental psychology stands as a pivotal branch of psychology that applies scientific methods to investigate and unravel the mechanisms behind human thought and behavior. This field allows researchers to design experiments that precisely manipulate variables to observe their effects on subjects, thereby providing clear, causal links between psychological phenomena. The selection of the right experimental psychology research paper topics is not merely academic—it is foundational to advancing our understanding of human psychology. By choosing insightful and challenging topics, students can push the boundaries of what is known and contribute valuable new insights to the scientific community.

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• The effects of color on mood and perception.
• Sensory deprivation and its impact on cognitive functions.
• The role of attention in perceptual processing.
• Multisensory integration and its effects on human perception.
• Perceptual illusions and what they reveal about the human brain.
• The influence of aging on sensory acuity.
• Cross-cultural differences in sensory perceptions.
• The impact of technology on visual and auditory perception.
• Neuropsychological insights into taste and smell.
• The perception of pain: mechanisms and modifiers.
• The impact of sleep on memory consolidation.
• Neuroplasticity and memory: how experiences rewire the brain.
• The effects of stress on memory retrieval.
• Comparative analysis of short-term and long-term memory.
• The role of repetition and spacing in learning effectiveness.
• Memory enhancement techniques: cognitive and pharmacological approaches.
• The reliability of eyewitness memory in different environments.
• Age-related differences in learning capacity and memory retention.
• The use of virtual reality in memory recall experiments.
• False memories: their creation and implications.
• Cognitive biases that influence decision making.
• The role of emotion in rational decision-making processes.
• The impact of cognitive overload on decision quality.
• Differences in decision making between genders.
• The effect of social influence on decision-making accuracy.
• Decision fatigue: causes and consequences.
• The use of heuristics in complex decision-making.
• Neurological underpinnings of spontaneous versus planned decisions.
• The role of intuition in cognitive processing.
• The impact of aging on decision-making abilities.
• The physiological basis of emotional responses.
• Emotional regulation and its effects on mental health.
• The impact of culture on emotional expression and recognition.
• The role of emotions in moral judgment.
• Emotional contagion in groups and crowds.
• The effects of music and art on emotional states.
• Gender differences in emotional processing.
• The relationship between emotional responses and psychopathologies.
• The development of emotional intelligence over the lifespan.
• Measuring emotions: methodologies and technologies.
• The influence of group dynamics on individual behavior.
• Conformity and obedience: experiments and explanations.
• The effects of social exclusion on psychological health.
• The role of social media in shaping public opinions.
• Stereotypes and prejudice: their formation and impacts.
• Altruism and prosocial behavior in controlled experiments.
• The psychology of persuasion and its mechanisms.
• Social loafing vs. social facilitation in work and sports.
• The impact of first impressions on subsequent interactions.
• Leadership styles and their psychological effects on group performance.
• The stages of cognitive development in children.
• The impact of parental styles on child behavior.
• Adolescence: risk factors and psychological resilience.
• Developmental disorders: early detection and intervention strategies.
• The role of play in social and cognitive development.
• Aging and cognitive decline: preventive strategies.
• Lifespan psychology: changes in aspirations and motivations.
• The effects of early educational interventions on developmental outcomes.
• The influence of genetics vs. environment in developmental trajectories.
• Social development and peer influences during childhood and adolescence.
• Brain injuries and their impact on personality and behavior.
• Neurological bases of addiction and substance abuse.
• The effects of neurological diseases on family dynamics.
• Cognitive rehabilitation techniques for stroke survivors.
• The relationship between brain structure and cognitive functions.
• Neuroethics: the implications of brain research.
• The use of neuroimaging to study thought processes.
• The impact of diet and physical health on neurological health.
• Sleep disorders and their psychological effects.
• The role of mirror neurons in empathy and learning.
• Conditioning and learning: classical and operant approaches.
• The effects of reinforcement schedules on behavior modification.
• Behavioral theories in marketing and consumer behavior.
• Animal models in behavioral research: ethics and insights.
• The use of behavior therapy techniques for psychological disorders.
• The psychology of habits: formation, maintenance, and change.
• The role of behavioral factors in obesity and other health issues.
• Behavioral genetics: separating nature from nurture.
• The impact of environmental factors on behavior.
• Behavioral adaptations to climate change and environmental stresses.
• Language acquisition in children and adults.
• The cognitive processes involved in reading and writing.
• The relationship between language and thought.
• Language disorders: dyslexia, aphasia, and others.
• The impact of bilingualism on cognitive development.
• Speech perception and processing mechanisms.
• The neuroanatomy of language production and comprehension.
• Social interactions and language use.
• The evolution of language: theories and evidence.
• Artificial intelligence and natural language processing.
• The psychological impact of chronic illness on individuals and families.
• The effectiveness of psychological interventions in physical health care.
• Stress and its effects on physical health.
• The role of psychology in pain management.
• Behavioral risk factors for heart disease and other illnesses.
• The impact of patient-practitioner communication on health outcomes.
• Psychological aspects of reproductive health.
• The role of motivation in health behavior change.
• Health disparities: the impact of socioeconomic status and race.
• Psychoneuroimmunology: the link between mental states and immune response.

The breadth and depth of experimental psychology research paper topics provide a robust platform for students to explore and contribute to various facets of psychological science. These topics not only allow students to apply scientific methodologies to real-world psychological issues but also offer opportunities to innovate and enhance the understanding of human behavior. Students are encouraged to delve deeply into these experimental psychology research paper topics, as doing so will enable them to produce significant scholarly work that has the potential to influence theoretical frameworks and practical applications in psychology.

The Range of Experimental Psychology Research Paper Topics

Research Methods in Experimental Psychology

One of the core components of experimental psychology is its focus on methodological rigor and precision. The common research methodologies used in experimental psychology include controlled experiments, observational studies, and case studies, each serving different but complementary purposes. In controlled experiments, variables are manipulated in a controlled environment to observe causation and effect, making it possible to draw conclusions about how different factors influence psychological outcomes.

The importance of experimental design, controls, and variables cannot be overstated in this context. Good experimental design ensures that the results are attributable solely to the manipulated variables, not to external factors. Controls help isolate the effects of interest by holding constant other potential influences, thereby increasing the validity of the experiment. A discussion of these elements highlights their role in minimizing biases and errors, thus enhancing the reliability and applicability of the research findings.

Analyzing case studies of successful experimental setups further illustrates these points. For instance, classic experiments in social psychology, such as the Stanford prison experiment or Milgram’s obedience study, though controversial, have provided deep insights into human social behavior and conformity. These case studies not only show effective experimental design but also underscore the ethical considerations and psychological impacts associated with experimental psychology.

Innovative Areas in Experimental Research

Experimental psychology continually evolves as new technologies and theoretical approaches emerge. Cutting-edge research areas within this field include neuropsychology, cognitive robotics, and virtual reality applications, each pushing the boundaries of traditional experimental methods. These innovations allow for more precise measurements and the simulation of complex psychological processes in controlled environments.

Emerging technologies like eye-tracking devices, EEG, and fMRI have revolutionized the way experiments are conducted in experimental psychology. These tools offer unprecedented views into the neural underpinnings of cognition and behavior, allowing for more detailed and accurate predictions about how these processes operate under various conditions. Additionally, the integration of experimental psychology with fields like genetics, neuroscience, and information technology facilitates interdisciplinary research that enriches our understanding of cognitive and behavioral sciences.

Ethical Considerations in Experimental Research

Ethical considerations form a significant pillar of research in experimental psychology. Because experimental methods often involve manipulating variables to observe effects on real participants, ethical guidelines are crucial to ensure the safety and well-being of subjects. Discussions on ethical issues in experimental psychology include considerations about informed consent, deception, and the potential psychological harm that could arise from participation in studies.

Exploring the guidelines and regulations that govern experimental research helps safeguard the interests of participants and maintain public trust in psychological research. For example, the APA’s ethical guidelines mandate that experiments involving humans or animals must adhere to strict ethical standards to minimize harm and discomfort. Case studies highlighting ethical dilemmas in past research, such as the ethical controversies surrounding the aforementioned Stanford prison experiment, serve as important learning tools for current and future psychologists to understand and navigate the complex ethical landscape of experimental research.

Reflecting on the breadth of experimental psychology research paper topics offers a window into the discipline’s vast potential to influence myriad aspects of modern life, from education and health to technology and beyond. The insights gained from rigorous experimental research provide a foundation for practical applications that improve psychological interventions, educational programs, and therapeutic practices, enhancing the quality of life across various settings. As experimental psychology continues to evolve, the fusion of innovative research methods, ethical consideration, and interdisciplinary collaboration holds the promise to further advance psychological science and its applications, ensuring its relevance and impact well into the future.

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Experimental (Empirical) Research Articles

• Library vs. Google
• Background Reading
• Keyword Searching
• Evaluating Sources
• Please Note: Searching PsycInfo
• Citing Sources
• Need more help?

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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Experimental Method In Psychology

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

The experimental method involves the manipulation of variables to establish cause-and-effect relationships. The key features are controlled methods and the random allocation of participants into controlled and experimental groups .

What is an Experiment?

An experiment is an investigation in which a hypothesis is scientifically tested. An independent variable (the cause) is manipulated in an experiment, and the dependent variable (the effect) is measured; any extraneous variables are controlled.

An advantage is that experiments should be objective. The researcher’s views and opinions should not affect a study’s results. This is good as it makes the data more valid  and less biased.

There are three types of experiments you need to know:

1. Lab Experiment

A laboratory experiment in psychology is a research method in which the experimenter manipulates one or more independent variables and measures the effects on the dependent variable under controlled conditions.

A laboratory experiment is conducted under highly controlled conditions (not necessarily a laboratory) where accurate measurements are possible.

The researcher uses a standardized procedure to determine where the experiment will take place, at what time, with which participants, and in what circumstances.

Participants are randomly allocated to each independent variable group.

Examples are Milgram’s experiment on obedience and  Loftus and Palmer’s car crash study .

• Strength : It is easier to replicate (i.e., copy) a laboratory experiment. This is because a standardized procedure is used.
• Strength : They allow for precise control of extraneous and independent variables. This allows a cause-and-effect relationship to be established.
• Limitation : The artificiality of the setting may produce unnatural behavior that does not reflect real life, i.e., low ecological validity. This means it would not be possible to generalize the findings to a real-life setting.
• Limitation : Demand characteristics or experimenter effects may bias the results and become confounding variables .

2. Field Experiment

A field experiment is a research method in psychology that takes place in a natural, real-world setting. It is similar to a laboratory experiment in that the experimenter manipulates one or more independent variables and measures the effects on the dependent variable.

However, in a field experiment, the participants are unaware they are being studied, and the experimenter has less control over the extraneous variables .

Field experiments are often used to study social phenomena, such as altruism, obedience, and persuasion. They are also used to test the effectiveness of interventions in real-world settings, such as educational programs and public health campaigns.

An example is Holfing’s hospital study on obedience .

• Strength : behavior in a field experiment is more likely to reflect real life because of its natural setting, i.e., higher ecological validity than a lab experiment.
• Strength : Demand characteristics are less likely to affect the results, as participants may not know they are being studied. This occurs when the study is covert.
• Limitation : There is less control over extraneous variables that might bias the results. This makes it difficult for another researcher to replicate the study in exactly the same way.

3. Natural Experiment

A natural experiment in psychology is a research method in which the experimenter observes the effects of a naturally occurring event or situation on the dependent variable without manipulating any variables.

Natural experiments are conducted in the day (i.e., real life) environment of the participants, but here, the experimenter has no control over the independent variable as it occurs naturally in real life.

Natural experiments are often used to study psychological phenomena that would be difficult or unethical to study in a laboratory setting, such as the effects of natural disasters, policy changes, or social movements.

For example, Hodges and Tizard’s attachment research (1989) compared the long-term development of children who have been adopted, fostered, or returned to their mothers with a control group of children who had spent all their lives in their biological families.

Here is a fictional example of a natural experiment in psychology:

Researchers might compare academic achievement rates among students born before and after a major policy change that increased funding for education.

In this case, the independent variable is the timing of the policy change, and the dependent variable is academic achievement. The researchers would not be able to manipulate the independent variable, but they could observe its effects on the dependent variable.

• Strength : behavior in a natural experiment is more likely to reflect real life because of its natural setting, i.e., very high ecological validity.
• Strength : Demand characteristics are less likely to affect the results, as participants may not know they are being studied.
• Strength : It can be used in situations in which it would be ethically unacceptable to manipulate the independent variable, e.g., researching stress .
• Limitation : They may be more expensive and time-consuming than lab experiments.
• Limitation : There is no control over extraneous variables that might bias the results. This makes it difficult for another researcher to replicate the study in exactly the same way.

Key Terminology

Ecological validity.

The degree to which an investigation represents real-life experiences.

Experimenter effects

These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.

Demand characteristics

The clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).

Independent variable (IV)

The variable the experimenter manipulates (i.e., changes) is assumed to have a direct effect on the dependent variable.

Dependent variable (DV)

Variable the experimenter measures. This is the outcome (i.e., the result) of a study.

Extraneous variables (EV)

All variables which are not independent variables but could affect the results (DV) of the experiment. EVs should be controlled where possible.

Confounding variables

Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.

Random Allocation

Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition.

The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.

Order effects

Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:

(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;

(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.

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This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

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Study suggests five-second break can diffuse an argument between coupled partners

by Bob Yirka , Phys.org

A trio of psychologists at The University of St Andrews, in Scotland, has found that taking a five-second break before things escalate can reduce the chances of a full-blown argument occurring. For their paper, published in the journal Communications Psychology , Annah McCurry, Robert May and David Donaldson, conducted emotional experiments with volunteer couples.

Prior research has suggested that if couples in intimate relationships take a time -out when feeling frustration or anger building toward their partner, they may be able to diffuse the situation. The research team wanted to know how much of a break is needed to achieve such a result, so they designed and carried out emotional and stress experiments with 81 volunteer couples in their lab.

The experiments consisted of asking the couples to play an interactive game with one another that was designed to lead to conflict. Part of the game involved allowing one participant to blast a loud, unpleasant noise at their partner. Each of the couples was asked to play thirty rounds of the game, and they were interrupted and forced to take a time out at different times and for different durations. Each of the couples was also filmed with a 360-degree camera fitted with a microphone while they played.

The researchers used what they describe as advanced machine learning software to help them analyze the results of the gameplay between the couples. Voice levels and facial expressions were used to determine frustration and anger levels.

The analysis showed that forcing a couple to take a time-out as short as five seconds during the moments when frustration was building but before an outburst occurred, was as effective as a 10 to 15 second time out—a finding the team suggests, indicates that the break itself serves to diffuse the situation, thus its duration was not nearly as important as the fact that it took place.

The research team concludes by suggesting that their findings indicate that couples have a simple and easy-to-use tool at their disposal, one that does not require anything but the desire and will to use it when a potential argument begins to arise.

Journal information: Communications Psychology

© 2024 Science X Network

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Nutritional and psychosocial intervention to improve the self-concept of body image and increase the self-esteem of overweight and obese individuals: a quasi-experimental study.

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González-Fernández, E.; Xandri-Martínez, R.; Gómez-Díaz, M.; Navas-López, J. Nutritional and Psychosocial Intervention to Improve the Self-Concept of Body Image and Increase the Self-Esteem of Overweight and Obese Individuals: A Quasi-Experimental Study. Nutrients 2024 , 16 , 2708. https://doi.org/10.3390/nu16162708

González-Fernández E, Xandri-Martínez R, Gómez-Díaz M, Navas-López J. Nutritional and Psychosocial Intervention to Improve the Self-Concept of Body Image and Increase the Self-Esteem of Overweight and Obese Individuals: A Quasi-Experimental Study. Nutrients . 2024; 16(16):2708. https://doi.org/10.3390/nu16162708

González-Fernández, Elvira, Raquel Xandri-Martínez, Magdalena Gómez-Díaz, and Julia Navas-López. 2024. "Nutritional and Psychosocial Intervention to Improve the Self-Concept of Body Image and Increase the Self-Esteem of Overweight and Obese Individuals: A Quasi-Experimental Study" Nutrients 16, no. 16: 2708. https://doi.org/10.3390/nu16162708

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