Natural products represent one of the most important reservoirs of structural and chemical diversity for the generation of leads in the drug development process. A growing number of researchers have shown interest in the development of drugs based on Chinese herbs. In this review, the use and potential of omic technologies as powerful tools in the modernization of traditional Chinese medicine are discussed. The analytical combination from each omic approach is crucial for understanding the working mechanisms of cells, tissues, organs, and organisms as well as the mechanisms of disease. Gradually, omic approaches have been introduced in every stage of the drug development process to generate high-quality Chinese medicine-based drugs. Finally, the future picture of the use of omic technologies is a promising tool and arena for further improvement in the modernization of traditional Chinese medicine. Since ancient times, plants have been an essential element for the prevention and treatment of a wide variety of diseases. Historically, natural products represent one of the most important reservoirs of structural and chemical diversity for the generation of leads in the drug development process , 2. The In the past years, the use of herbal preparations has gained attention in European and Asian countries. Only in Europe, about 100 million people make use of traditional and complementary medicine. Furthermore, the increasing popularity of traditional and alternative medicine is observed in Africa, Asia, Australia, and North America –7. In acTraditional Chinese Medicine (TCM) is a medical system for the prevention and treatment of diseases that focuses on the patient rather than the disease when compared to the Western medicine. The main principle by which TCM works is the use of herbs for the restoration of the yin-yang imbalance that results in disease . DespiteNovel advanced technologies are needed to improve separation methods, quality control, standardization techniques, screening, the study of the mechanism of action of individual compounds, and clinical validation assays. In this sense, the application of omic technologies in TCM research is a promising approach to assist in the modernization of TCM and to address the complex challenges encountered in TCM research. Therefore, the aim of this review is to give a general overview of the use of omic technologies as promising and powerful tools in TCM research.The rapidly evolving technology has led to the development of research tools to assist a more comprehensive study of biological systems. In TCM, researchers have gradually introduced the most recent technological advances trying to overcome the most common bottlenecks in TCM research. By analyzing the emergence and evolution of the current technologies, their potential application in TCM research can be better understood.A significant breakthrough in technological advances was the completion of the Human Genome Project which is considered one of the greatest scientific achievements of the past century . The genDespite the significant contribution of genomic studies, the need to bridge the sequence information for the identification of potential therapeutic targets with the physiology and pathology of an organism using novel sophisticated approaches became a clear and pivotal task . One wayThe postgenomic era was a pivotal stage for the emergence of “omic” studies in biological research representing the beginning of the systems biology era. Data generated by omic studies are described as the wholeness of living systems that result in useful information after the application of bioinformatic analyses . The orgThe analytical combination of information from each omic approach is crucial for understanding the working mechanisms of cells, tissues, organs, and organisms as well as the mechanisms of disease , 15. VisGenes and gene products act as a complex interconnected network in synchrony with a wide variety molecular system pathways rather than acting independently. Since the establishment of omics approaches, omic technologies have been applied in different areas of biotechnology, drug discovery, and biomedical research including TCM. However, a close analysis of the omic research published in the past ten years shows that the use of omic technologies in TCM has not been fully explored . TherefoAnother omic approach at DNA level is epigenomics. Epigenetic studies focus on the reversible heritable modifications in gene expression that do not involve any change in the DNA sequence , 17. As Metagenomic studies involve the analysis of a collection of genes from the environment that are related to the host physiology . This apThe study of the alterations in gene expression upon exposure to chemicals to identify potential genetic toxicants and monitor their cellular mechanisms is the main focus of toxicogenomics , 19. ToxPharmacogenomics aims to identify and analyze genes involved in the response to drugs to assess interindividual variability and susceptibility to adverse drug reactions , 22. PhaHerbogenomics, also referred as botanogenomics, is a novel concept that makes use of genomic and proteomic comparative analysis for the study of the biological effect of herbs . This coTranscriptomics comprises the study of the complete set of messenger RNA under specific conditions in any given cell; it is also known as the study of transcripts , 25. By The above-mentioned omic approaches have contributed to the understanding of biological processes for the evaluation and validation of TCM. Another promising technology developed that has strongly emerged as a powerful tool for the assessment of physiological events is proteomics. Since the introduction of the term proteomics for the first time 20 years ago, proteomic technologies have rapidly evolved and being integrated into several stages in the pharmaceutical research and development . ProteomThe downstream complexity of mechanisms that lead to a specific biological effect is not directly related to the number of genes. Instead, other gene expression mechanisms such as posttranslational modifications and alternative splicing play an important role in protein variation. It has been estimated that about 35% of human genes undergo alternative splicing which means that the traditional one gene one protein hypothesis should be adjusted to a one gene-many protein model , 25. As Phosphorylation is considerably the most commonly found posttranslational modification in proteins accounting for about 17,500 phosphorylated gene products in humans . PhosphoSimilarly, as phosphoproteomics, glycoproteomics comprises the study of proteins with another important posttranslational modification in cell processes, namely, glycosylation. Glycosylation of proteins occurs in about 25% of the human proteins and nearly 4,500 proteins have being detected to undergo glycosylation . HoweverAnother omic approach that focuses on the proteome is toxicoproteomics which is used to evaluate the effect of the exposure to toxic agents in cells and tissues at qualitative and quantitative level. The proteome profiling upon xenobiotic exposure allows prediction of toxic responses to herbal components .Chemoproteomics applies function-based proteomics to study the protein structure and their interaction with chemicals. The proteins subjected to chemoproteomic studies require carefully optimized conditions to conserve protein structure, posttranslational modifications, and even interactions with regulatory proteins , 31. CheImmunomics focus on the regulatory mechanisms of the immune system on pathogens from antigen recognition to the immune response caused by the antigens presented to the immune machinery of the host , 32. AltAs mentioned above, the use of multiple omic approaches allows a broader and more detailed understanding of biological phenomena from different points of view. The complexity and a large amount of data generated by each individual omic approach have led to the emergence of a new omic tool to combine, analyze, and interpret multiomic data. The result of the analytical combination of the enormous amount of data generated by different omic approaches is called integrome and it is the main focus on interactomics . InteracMetabolomic studies include the qualitative and quantitative analysis of a large number of metabolites and their dynamics in a given biological system , 35. TheThe metabolic state of an individual is influenced by environmental, genetic, and gut microbiome factors. Comparative studies of the metabolic profiles before and after drug exposure provide valuable information about the treatment outcome and the effect of drugs on metabolism. Pharmacometabolomics is currently applied in pharmacology, drug discovery, and development and personalized therapy . In rece Ricinus communis . Long-term treatment with ricin was shown to induce perturbations in multiple metabolic pathways including amino-acid metabolism and oxidative stress which partly explains the observed nephrotoxicity [ Tripterygium wilfordii) and discovered changes in ß-oxidation pathway [The omic discipline that combines metabolomics and toxicology in comparative analyses of endogenous metabolite profiles in a normal state and during and after drug treatment is toxicometabolomics . Since stoxicity . Further pathway . TogetheLipids play essential roles in biological processes from energy reservoirs and structural cellular components to elements in cell-signaling pathways . StudiesThe phytochemome comprises the group of compounds present in plants such as alkaloids, polyphenols, terpenes, sulfides, thiols, plant peptides, and their metabolites. Phytochemomics focuses on the intracellular and extracellular study at different molecular levels, the chemical structure, and mechanism of action of the phytochemome . PhytochThe focus of chinmedomics is to investigate the biological action, synergistic effect, and metabolic profile of Chinese formulae. Chinmedomics has shown great potential when studying TCM since it introduces the holistic concept of TCM combined with the most sophisticated analytical tools , 48.The technologically driven advances in chinmedomics have been used to address the efficacy and safety concerns in TCM research , 49. To Metallomics is defined as the comprehensive quantitative and qualitative analysis of an entire set of metals and metalloid species within a cell, tissue, or the whole organisms . Since iCrucial physiological processes such as cellular signaling, metabolism, enzymatic activity, and transmembrane transport involve the action of ions . The ionThe phenotype is the whole set of physical and biochemical characteristics of a living organism as a result of interaction with genetic and environmental factors , 54. In Phenome is the whole set of expressed traits in a defined population associated with the influence of genetic of environmental factors , 55. PheThe study of the phenotype at a cellular level for the understanding of molecular disease networks is the focus of cytomics. In order to gain more understanding of the molecular processes at a cellular level, the human cytome project was conceived . HoweverAs discussed above, the diversity of omic approaches provides a wide variety of technological tools that are applied to TCM research. In addition, the potential applications of some omic technologies in TCM research should be further explored. In Omic technologies can be applied to the study of a wide variety of diseases as shown in A critical concern in TCM research is to ensure quality, safety, and efficacy to meet the quality standard requirements . In the In TCM, the diversity and number of components responsible for the biological activity make the analytical procedure a challenging task. However, emerging technologies and improved methods have contributed to facilitating the quality control of TCMs. Some of the technologies applied in the characterization of metabolites for quality control include NMR-based metabolic fingerprinting, capillary electrophoresis, HPLC, gas chromatography, HPLC-PDA-ESI/MS, HPLC-DAD-ESI/MS, GC/MS, GCxGC-qMS, TOF/MS, GCxGC-TOF/MS, MALDI-TOF/MS, HLPC/UV, TLC, ultra-TLC, UPLC, UPLC-Q/TOF-MS, IT-TOF-MS, capillary zone electrophoresis (CZE), capillary electrochromatography (CEC), pressurized CEC, micellar electrokinetic chromatography, turbulent flow chromatography (TFC), and HPLC/ESI/MS , 99–101.The metabolite characterization is not only useful for assessment of efficacy and safety by determination of the compounds responsible for the biological activity or side effects, but also it is essential for the standardization during the manufacturing process. Differences in quantity and quality of compounds in TCMs can be due to factors such as the plant of the plant used, storage conditions, agricultural practices , extraction, and preparation methods , 35. ThoAlthough important technological advances for the analysis of TCMs have been developed and applied, some challenges are still of significant concern. Frequently, some of the components responsible for the therapeutic or toxic effect in TCM have not been fully characterized which hampers the analytical process , 108. AnIn conclusion, the use of omic technologies has enormously contributed to improving the cost effectiveness, sensitivity, and reliability of analytical methods in the quality control process of TCM. Several analytical techniques are being introduced in quality control of herbal preparations at all stages of the production process. The need to have one optimized analytical procedure for one specific herbal preparation slows down the development of analytical protocols for TCM when compared to the analytical procedures of Western medicine. More extensive and oriented work is needed to overcome the issues encountered and to adopt the newest technological advances in TCM research. However, the introduction of existing technologies and the fast development of emerging omic tools provide a wide variety of analytical platforms and promising future to assist in the quality control of TCM.The study of therapeutic targets in TCM is a complex and challenging task. It requires the use of multiple methodologies combined to construct disease maps from different perspectives since the effect of TCMs is the final result of the effect on multiple targets. From the genomic point of view, about 30–40 thousand genes encode a larger number of proteins that represent potential drug targets for human diseases . In thisAs mentioned above, genomic technologies were the first methods to be applied in target discovery in combination with transcriptomics. Microarray analysis and mRNA expression profiles used to compare the normal state, disease related genes, or gene expression under treatment conditions have shown promising results for target validation. However, the gene expression profiles might not be directly correlated with the late functional biological state . TherefoThe use of proteomic and metabolomic approaches applied to TCM research has increased since 2006. On the other hand, genomics and transcriptomics have not been widely used in TCM research when compared to proteomics and metabolomics as shown in observations made until 2012. Therefore, there is a clear need to explore genomic and transcriptomic technologies applied to TCM research .Proteomic studies have contributed to the identification of potential drug targets not only by comparing the proteome profiles but also by using protein-drug or protein-protein interaction information . In vitrA close analysis of the methods used in proteomics for the study of the mechanism of disease has highlighted the pros and cons of such methods. For instance, a limitation being pointed out is the use of gel-based proteomics. Gel-based separation techniques can lead to partial peptide recovery from the gel which requires the use of several extraction steps to increase the peptide yield. However, the multistep methodologies are time-consuming compared to gel-free proteomic techniques. It has also been observed that the resolution of 1D gel systems is not good enough to analyze complex biological samples . FurtherProteomic studies can be combined with virtual screening technologies to predict binding profiles of the TCM components with potential target proteins and to build protein-protein interaction maps to track the signaling pathways involved in the biological effects. Furthermore, the combined data from comparative proteomics, protein-drug, and protein-protein interaction provide useful information to support the process for candidate drug targets . ImportaThe study of posttranslational modifications (PTMs) in proteomics has enormously contributed to the understanding of molecular mechanisms in biological systems particularly for the identification of potential drug targets. The study of PTMs in biological systems is a challenging task due to the high diversity of PTMs. About 300 different types of PTMs have been identified using the most sophisticated analytical technologies . New anaNowadays, proteomics technologies comprise a wide variety of high-throughput methods to study complex systems. A large amount of proteomic data generated can be analyzed using open source or commercial bioinformatics. Nevertheless, new bioanalytical approaches need to be developed to manage the enormous amount of proteomic data to improve the handling, analysis, and visualization of proteome information . In TCM The comparison of the abnormalities in the metabolome to the normal stage provides an insight into the pathways affected at several disease stages, and it is known as comparative metabolomics . For insE. This approach involves the use of parallel alternating scans to generate ion information using low collision energy or to generate a full scan mass fragment, precursor ion, and neutral ion information by high collision energy. The information obtained by MSE has been shown to provide similar data to the data obtained by conventional MS/MS analysis. However, UPLC-MSE technology has the advantage of allowing the characterization of unknown biomarkers in an untargeted context [E was used to study the metabonomic profile of chronic kidney disease induced by adenine excess and the protective effects of the TCM Poria cocos [ Poria cocos [Furthermore, metabolomic studies have been shown to be helpful in the detection of response-to-treatment biomarkers which can be used for the development of new drugs . Metabol context . For exaia cocos . This meia cocos . In otheia cocos , 121. Ania cocos . An examia cocos . The metia cocos .In high-throughput settings, metabolomics technologies are used not only for the identification of biomarkers but also for understanding the progression and the metabolome variation in the different disease stages which contributed to a better understanding of the pathology picture . In addiMethods such as NMR-based metabolite profiling, HPLC, GC-MS, GCxGC-TOF-MS, MALDI-TOF-MS, and CE-MS are metabolomic tools that can be used for the simultaneous analysis of 1000 compounds. Such technologies have shown to be fast, efficient, and sensitive for the detection of low abundance metabolites. In terms of bioinformatics analysis, great efforts are being made to improve the current tools in order to integrate the omic information and generate more reliable and complete bioinformatics tools. An example of such improved bioinformatic options is the Integrated Interactome System which comprises genes, proteins, metabolites, and drugs data . TogetheMetabolomics profiling can assist in the identification of early biomarkers of disease which is beneficial to detect early pathological stages . Early dChinese formulations comprise a combination of several herbs. The active compounds in the formulations can act on specific targets and the biological activity is the result of combined effects. The final pharmacological action of the active compounds can be mutual accentuation, mutual enhancement, mutual suppression, mutual antagonism, or mutual incompatibility . In ordeThere is an overlap in the methodologies for identification of disease mechanisms, biomarkers, drug targets, and the study of the mechanism of action of TCMs. Some of the technologies mentioned in the previous section are also used in the study of the molecular mechanisms in TCMs. Therefore, the most recent advances in omic technologies that have being applied in TCM research including some practical examples and technologies that need further exploration will be discussed.Genomic approaches to the study of the mechanism of action of TCMs have been applied in the past years. A clear example of the use of recent sophisticated genomic technologies is the biclustering analysis of gene expression profiles using DNA microarray technology to identify gene expression variation. The data generated in the DNA microarray analysis is used to identify biologically relevant clusters for gene expression profiles resulting from chemical treatment to construct connectivity map (cMap) profiles. Consequently, the cMAP profiles are processed by biclustering analysis using a factor analysis for bicluster acquisition method. The data generated by the above-mentioned tools combining gene expression data, statistics, and bioinformatics contributed to the elucidation of the mechanism of action of TCMs and have shown potential for the analysis of complex herbal formulae .A combination of technologies such as isoelectric focusing, SDS-PAGE, in-gel digestion, MALDI-TOF-MS, and real-time PCR have contributed to the identification of proteins involved in the mechanism of action of curcumin in in vitro models. Additionally, information about the signaling pathway in which the differential proteins act can provide with information about the function and signaling pathway involved in the mechanism of action . In anotAnother detailed study of the use of proteomics to determine the mechanism of action of TCMs was carried out by Lao et al., 2014. In this review, the authors summarize a number of studies based on proteomics in TCM research carried out in the past 10 years. In this review, it can be observed that proteomic technologies are being applied in the study of a wide variety of disorders in in vitro, in vivo, and in silico studies . ProteomWhen studying the mechanism of action of TCMs, the use of transcriptomic technologies applied to TCM is powerful tools due to the high sensitivity, accuracy, specificity, reproducibility, and high-throughput approach . In addiAn example of the use of transcriptomics in the study of the mechanism of action of TCMs is the study carried out by Liu et al., 2013. In this study, differential microarray gene expression analysis in an in vitro platform combined with pharmacological studies for validation purposes to elucidate the mechanism of action of the TCM studied. The data generated were analyzed using the software ArrayTrack, CLUSTER, and TREEVIEW. The approach used improved the understanding of the mechanism of action and the potential use of the TCM in cancer treatment . AdditioThe use of metabolomics technologies provides a deeper insight into the metabolic changes accompanied by TCM treatment which enables biomarker identification and elucidation of mode-of-action. Danqi Tongmai tablet was shown to have a protective effect against acute myocardial infarction. Comparison of metabolomic profile of Danqi Tongmai tablet treated and untreated rats were subjected to pathway analysis to identify the pathways modified in Danqi Tongmai tablet treated rats. Briefly, the knowledge from Kyoto Encyclopedia of Genes and Genomes (KEGG) was utilized to identify deregulated pathways. A more detailed statistical test of pathway enrichment and comparison of pathway topology were conducted in MetaboAnalyst . The stuAlthough omic technologies have being applied in the study of the molecular mechanism by which TCMs exhibit their biological effects, more exploration is needed to take full advantage of the wide range of technologies currently available.Omic technologies have shown enormous potential in the modernization of TCM. Gradually, omic approaches have being introduced in every stage of the development process to generate high-quality TCMs. The complexity of TCM in terms of composition and multitarget effects has being addressed by omic approaches. However, further study and optimization of the current methodologies are needed to successfully overcome the most common bottlenecks in TCM research. The high chemical and pharmacological diversity found in TMCs requires the development of a suitable set of omic technologies established in a strategic manner and adapted to every specific compound, a group of compounds, or TCM extracts. Because each plant, formulae, extract, or group of compounds has different physicochemical nature and contains different active and toxic compounds as well as analytical and active biomarkers, each case requires specific analytical approaches and methodologies that cannot be applied to another plant, formulae, extract, or group of compounds. The wide variety of technologies available needs to be further explored and the feasibility of any particular omic technology or the combination of multiomic approaches needs to be studied in detail. Therefore, validation of the strategic omic approaches applied is needed to support their introduction in guidelines and to allow the development of standard operation procedures to facilitate reproducibility, harmonization, and standardization of the protocols used in the development of TCMs. Emerging novel and sophisticated omic technologies will require a continuous study and application in TCM research. Finally, the future picture of the use of omic technologies is a promising tool and arena for further improvement in the modernization of TCM.


Intracellular Mg‐ATP changes in concentration can be sensed by CNNM proteins and may regulate their function(s). Although the exact role between ATP production and Mg2+ concentrations is unknown, an interesting hypothesis is that CNNM proteins function as indirect sensors of intracellular Mg2+ concentrations.A common feature of CNNM proteins is the presence of intracellular cystathionine β‐synthase (CBS) domains  ratio.As a result, several groups have examined the potential Mg2+ probes, resulting in a large pile of conflicting data. First, using the Mg2+‐sensitive fluorescent Magnesium Green indicator, the group of Miki showed that overexpression of CNNM4 or CNNM2 decreased cellular Mg2+ concentrations , which is a known inhibitor of TRPM7 . Moreover, the discrepancy between the different models shows that CNNM2 function is largely dependent on other proteins present in the cell. This is suggestive of a regulating function rather than a transport function. Given that the CNNM2‐dependent 25Mg2+ uptake could be blocked by 2‐APB, TRPM7, a channel involved in Mg2+ homeostasis, is an interesting candidate for regulation by CNNM2  CNNM proteins do not comply with the consensual topological attributes of a typical Mg2+ transporter, i.e. abundant transmembrane domains and a cation pore formed by membrane‐spanning domains; (ii) conflicting functional data of CNNM‐mediated Mg2+ extrusion between different cellular models indicate that the Mg2+ extrusion function of CNNM proteins depends on the Mg2+ channels/transporters specifically expressed by each cellular model; and (iii) CNNM2‐mediated Mg2+ extrusion in epithelial cells is not dependent on Na+ in a series of experiments. Altogether, this shows that CNNM proteins are not Na+/Mg2+ exchangers. Future research should focus on the identification of the protein partners of CNNMs to elucidate the CNNM‐dependent regulation of Mg2+ transport.Hence, the following evidence supports that CNNM proteins are not Najphysiol@physoc.org. Comments will be moderated and accepted comments will be published online only as ‘supporting information’ to the original debate articles once discussion has closed.Readers are invited to give their views on this and the accompanying CrossTalk articles in this issue by submitting a brief (250 word) comment. Comments may be submitted up to 6 weeks after publication of the article, at which point the discussion will close and the CrossTalk authors will be invited to submit a ‘LastWord’. Please email your comment, including a title and a declaration of interest, to None declared.Both authors have approved the final version of the manuscript and agree to be accountable for all aspects of the work. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed.This work was financially supported by grants from the Netherlands Organization for Scientific Research (NWO VENI 016.186.012) and the Dutch Kidney Foundation (Kolff 14OKG17).


Tableware size may influence how much food and non-alcoholic drink is consumed. Preliminary evidence of the impact of glass size on purchasing of alcoholic drinks shows an increase in wine sales of almost 10% when the same portion of wine is served in a larger glass. The primary aim of the current study is to test if micro-drinking behaviours act as a mechanism that could underlie this effect, through an increase in drinking rate, sip duration and/or number of sips from a larger glass.In a between-subjects experimental design, 166 young women were randomised to drink a 175 ml portion of wine from either a smaller (250 ml) or larger (370 ml) wine glass. Primary outcomes were three micro-drinking behaviours, assessed observationally using video recordings: drinking rate, sip number and sip duration. Other possible mechanisms examined were satisfaction with the perceived amount of wine served and pleasure of the drinking experience, assessed using self-report measures.Wine drunk from the larger, compared with the smaller glass, was consumed more slowly and with shorter sip duration, counter to the hypothesised direction of effect. No differences were observed in any of the other outcome measures.These findings provide no support for the hypothesised mechanisms by which serving wine in larger wine glasses increases consumption. While micro-drinking behaviours may still prove to be a mechanism explaining consumption from different glass sizes, cross-validation of these results in a more naturalistic setting is needed. Excessive alcohol consumption is estimated to be the fifth leading cause of death and disability . Price, A recent Cochrane review has shown that the size of tableware influences consumption of food and non-alcoholic beverages, with larger sizes leading to greater consumption . HoweverThe mechanisms underlying increased alcohol consumption have rarely been studied. Most evidence for mechanisms underpinning consumption behaviour comes from literature on food, and to a lesser extent, non-alcoholic beverage consumption. Eating rate, bite size, chewing rate, number of sips and sip size have shown to be mechanisms which contribute to the volume of food and non-alcoholic beverage intake –11. To oWine served in larger glasses is likely to be perceived as less in quantity than a similar amount served in a smaller glass . Such diOther mechanisms may mediate micro-drinking behaviours or independently affect consumption of alcohol when served in different sized glasses. These include, first, satisfaction with the quantity of the wine served, and second, the pleasure associated with the drinking experience.Satisfaction with the quantity of the wine may operate through the “unit bias heuristic” . The uniThe glasses that are used can influence the pleasure of drinking alcohol . This maThe same portion of wine served in a larger compared with a smaller glass is consumed more rapidly (Hypothesis 1). We will also explore whether any difference in speed of consumption could be a result of i) a greater number of sips and ii) longer sip duration.Serving a fixed portion of wine in a larger compared with a smaller glass lowers satisfaction with the amount (Hypothesis 2).Wine served in a larger glass leads to a more pleasurable drinking experience (Hypothesis 3).Preliminary evidence from a field study suggests that wine sales may be greater when wine is served in a larger glass . The curSince the research underpinning Hypotheses 2 and 3 is scant and indirect, the current study should be considered exploratory. By examining relatively broad mechanisms in this study, we may highlight those dimensions where further exploration could be most beneficial. For instance, if larger glasses lead to greater pleasure when drinking, this could be the result of glass size altering the smell or taste of the wine. Similarly, larger glass sizes may differentially impact the physical ability to take a larger sip. If so, this is likely to be reflected in micro-drinking behaviour variables such as drinking rate or sip duration.Finally, we will examine whether micro-drinking behaviours, as well as satisfaction with the amount and the pleasure of the drinking experience, are associated with the desire to drink more. Desire to drink more will serve as a proxy for assessing further consumption. Perceived intoxication will serve as a proxy for the perceived amount of wine consumed from a larger and a smaller glass. For instance, if participants who drink from a smaller glass perceive that it contains a greater amount of wine than those who drink from a larger glass, they might also perceive having a greater level of intoxication.The study used a between-subjects design, with participants randomised to one of two groups to receive 175 ml of wine served in one of two wine glass sizes: (a) smaller (250 ml), (b) larger (370 ml).M = 22.93; SD = 3.52, range 18–42) who drank red wine, were at least 18 years of age, were not currently pregnant or taking any medication that interacts with alcohol, and who had not consumed alcohol in the 12 h prior to the study. The study included only women to minimise gender differences in average sip duration [Participants comprised of 166 female students , with a researcher pressing a button when the wine touched participants’ lips – indicating sip initiation, and pressing the button again when the wine left participants’ lips – indicating sip end. A second coder, blind to the study hypotheses, independently coded 20% of the videos selected at random to assess coding reliability (presented in the Results section). Variables derived from the video recordings included total time taken to consume the wine, number of sips, and average sip duration.This was assessed in two parts: firstly, by exploring perceptions of the amount of wine served, and secondly, examining participants’ satisfaction with the perceived amount of wine.Two questions, rated on a seven-point rating scale ranging from 1 (Much less) to 7 (Much more) asked: “How does the amount of wine in the glass you just drank compare to a typical glass of wine you would drink at home?” and “How does the amount of wine in the glass you just drank compare to a typical glass of wine you would drink at a pub or restaurant?”. The baseline of the typical wine portions participants consumed was established by the following question: “What size would your typical glass in a pub or restaurant be?”. Participants could answer by indicating small (=1), medium (=2), or large (=3).Five attributes of the given amount of wine  were each rated using seven-point scales, ranging from 1 (Strongly agree) to 7 (Strongly disagree). The latter three attributes were reverse-coded prior to the analysis. A composite score (‘Satisfaction’) combining these attributes was formed (Cronbach’s α = 0.71).The pleasure of the drinking experience was assessed by rating the experience of drinking the wine on five attributes using seven-point rating scales: Pleasurable, Enjoyable, Disagreeable, Unpleasant, Distasteful. The latter three dimensions were reverse-coded prior to the analysis. A composite score was developed to reflect this variable (Cronbach’s α = 0.95).Desire to drink more was assessed by indicating agreement on a seven point scale ranging from 1 (Strongly agree) to 7 (Strongly disagree) for the following statements: “I wish I had another glass of wine right now”, “I don’t want any more wine right now”, “If I were offered another glass of wine right now, I would drink it”, “If I were in a pub or bar, I would buy another glass of wine right now”, “ If I had the chance, I would not have any more wine right now”. Appropriate items were reverse-coded prior to the analysis. Scale reliability assessed by Cronbach’s α was 0.78.Perceived intoxication was assessed with a single item: “I feel drunk at the moment”. Participants responded by indicating agreement with the statement on a scale ranging from 1 (Strongly agree) to 7 (Strongly disagree).The Alcohol Use Disorders Identification Test (AUDIT ), a 10-iThe Alcohol Urge Questionnaire (AUQ ), an 8-iThe nature of the study was disguised by administering a computerised version of the Trail Making Test as a filler task . The TraParticipants were recruited from the University of Cambridge and from Anglia Ruskin University via mailing lists, poster advertisements and word-of-mouth. They received £10 payment for participation. Participants completed the sessions individually in a quiet laboratory between 12:00 and 21:00 h during weekdays. To avoid participants’ consumption being influenced by awareness of the study hypotheses, the study was presented to them as investigating the effects of limited amounts of alcohol on cognitive performance. After giving consent, eligibility to participate in the study was confirmed by a breathalyser check, to ensure that participants had refrained from consuming alcohol in the preceding 12 h. Participants then completed the AUDIT and AUQ measures. Participants were randomised to either the smaller (250 ml) or larger (370 ml) wine glass condition using a computer generated randomisation schedule with the constraint of having an equal number of participants per group. A portion of 175 ml Cuvée des Vignons Beaujolais red wine  was measured out by filling a 175 ml pub thimble to the brim, and then poured into the wine glass allocated by randomisation, immediately prior to each experimental session. Wine bottles were secured with a vacuum-pump to minimise oxidation of the wine between experimental sessions. When participants had completed the baseline measures, the experimenter switched on the hidden camera from a remote laptop, and returned to the lab with a glass of red wine. Participants were told to drink the wine at their own pace while watching a nature documentary . The experimenter then left the room and returned when the participants had indicated by ringing a bell that they had finished their glass of wine. If participants did not finish drinking the wine after 30 min, the experimenter returned to ask if everything was alright. If participants were still drinking, the experimenter left and returned to end the session either when the participant indicated that they had the wine finished or after an additional 15 min, whichever was sooner. After the drinking session, participants were given the questionnaires to complete, followed by the filler task. Finally, participants were asked what they thought the aim of the study was. Participants were blind to the study aims and were fully debriefed about the purpose of the study via email at the end of the study, i.e., when the last participant had completed the study.Preliminary analyses included examining differences between groups between-group mean differences for effects of glass size on outcome variables using non-parametric bootstraps in R: (i) Total drinking time (ii) Satisfaction, and (iii) Pleasure, and (iv) Desire to drink more, as well as other aspects of drinking behaviour that may contribute to drinking time, i.e.: a. number of sips and b. sip duration. We also tested between-group mean differences for effects of glass size on perceived intoxication as a proxy for how much people believe they had consumed. Regression analyses were conducted to test for “proof of concept”; namely that desire to drink more is predicted by the measures listed in (i) to (iii) above.Sensitivity analyses were conducted by removing any participants who had not drunk all the wine they had been served or who indicated they were aware of the study aims.Descriptive statistics including age, AUQ and AUDIT scores per randomised group are presented in Table Descriptive statistics regarding the primary variables are presented in Table p < .05, with participants drinking more slowly when wine was served in a larger glass.Micro-drinking behaviours were analysed by means of non-parametric bootstrap analysis  = .128, p > .05.The percentage of participants randomised to the larger glass condition that would typically order a small, medium, or large portion of wine was 30.1%, 53.0%, and 16.19%, respectively. Similarly, the percentage of participants randomised to the smaller glass condition that typically take a small, medium or large portion of wine was 27.7%, 55.4%, and 16.9%, respectively. The patterns of participants’ typical wine portion sizes in a pub or restaurant did not differ between groups, χp < .05. There were also no differences between the two groups with regards to perceptions of the amount of wine served as assessed by non-parametric bootstrap , both ps < .05. These results provide no support for Hypothesis 2.Differences in satisfaction with the perceived amount were not significant when analysed by non-parametric bootstrap , Non-parametric bootstrap , showed no differences in pleasure, providing no support for the hypothesis that drinking from a larger glass elicits a more pleasurable drinking experience.Classic and robust multivariate regression estimates  = .99, p < .001, (32) = .93, p < .001, for number of sips and sip duration, respectively. This indicated a high level of inter-rater reliability.The ratings of the two independent raters were positively correlated - single measures intra-class correlation for total time was (32) = .99, N = 12) was conducted and similar results were obtained. Finally, comparison of the between-group location parameters of the distribution of the outcomes of interest by means of Wilcoxon’s tests lead to the same conclusions.Three participants did not finish their wine. The quantities remaining were small and consisted of 3 ml, 6 ml, and 20 ml, respectively. We considered the total time measures of participants with left-over wine as right-censored and compared parameters of gamma regression parameter estimates (models not reported here) and obtained similar results. An additional sensitivity check for participants who correctly guessed the aims of the study  as a postulated mechanism for increased consumption of wine when served in a larger glass . Other pThere are two sets of possible explanations for the absence of any support for the study hypotheses concerning the mechanisms by which larger glasses increase consumption in a bar. The first set concerns the ecological validity of the laboratory setting for understanding an effect observed in a bar. Consumption of alcohol is influenced by context, with several studies showing that the amount of alcohol consumed in lab settings is generally lower than that consumed in a bar –28. CertA second set of possible explanations for the study’s null findings is that the investigated mechanisms do not relate to alcohol consumption. However, this is inconsistent with our finding that overall drinking rate and pleasure of drinking experience predict the desire to drink further. This supports the ‘proof of concept’ hypothesis and suggests that the measures used in this study can be useful for investigating alcohol consumption behaviour in future research.This study is, to our knowledge, the first to investigate the influence of micro-drinking behaviours on wine consumption. While much research has focused on food and portion size, this study investigates the relatively neglected area of alcohol consumption behaviour and the environmental cues such as glass design that can influence it. The use of experimental methods provides the first objective exploration of factors that could be driving increased alcohol consumption from larger glasses.The limitations of the study include the lack of a consumption-based outcome. While desire to drink more provides a proxy for consumption, a true consumption variable would offer stronger evidence of the mechanisms examined in the current study. A further limitation is that although the laboratory setting allowed for a high degree of control, it may not reflect drinking behaviour in more natural settings, as discussed above. Finally, the study sample differs between the current study and the field study in which the glass size effect was observed . We examThe current study provides a first step towards understanding the mechanisms by which glass size impacts on alcohol consumption. Future studies will need to ascertain the role of contextual factors that may interact with environmental cues which contribute to alcohol consumption. This can be accomplished by either conducting a field experiment in a bar setting or an experiment in a laboratory setting with added contextual richness  to determine the external validity of the present results. Together, this could be used to optimise glass design to reduce alcohol consumption at a large scale..Examining how a fixed volume wine is consumed from different sized wine glasses in a laboratory setting provided no evidence to support the three study hypotheses. Cross-validation of the present results in a field setting or a bar lab is needed, to exclude the explanations that the present results are an artefact of a laboratory context or inherent to the demographic characteristics of the study sample. Thus, micro-drinking behaviours may still be a promising candidate for a mechanism that can explain consumption from different sized wine glasses, if explored in a naturalistic and ecologically valid setting. Elucidating the mechanisms that underlie modifiable environmental cues remains an important goal for developing interventions that have the potential to inform policies that aim to reduce alcohol consumption at population level


Unlike mirror self-recognition, recognizing one's own image in delayed video footage may indicate the presence of a concept of self that extends across time and space. While humans typically show this ability around 4 years of age, it is unknown whether this capacity is found in non-human animals. In this study, chimpanzees performed a modified version of the mark test to investigate whether chimpanzees could remove stickers placed on the face and head while watching live and delayed video images. The results showed that three of five chimpanzees consistently removed the mark in delayed-viewing conditions, while they removed the stickers much less frequently in control video conditions which lacked a link to their current state. These findings suggest that chimpanzees, like human children at the age of 4 years and more, can comprehend temporal dissociation in their concept of self. HumanFrom a phylogenetic perspective, chimpanzees and other great apes have been shown to exhibit self-recognition in mirror studies –17, and The aim of this study was to explore the reactions of chimpanzees to their delayed self-image. We tested five chimpanzees in experimental sessions beginning with the placement of 10 stickers on the head or face of a fully awake chimpanzee. Following a 2 min observation period during which no image was shown on the monitor, one of eight types of video was then presented on the monitor for 2 min. These included: a live self-video; a 1 s delayed self-video; a 2 s delayed self-video; a 4 s delayed self-video; a distant past video (more than one week old) showing the subject with stickers on the face and head; a distant past video (more than one week old) of the subject with no stickers on the face or head; a video of a human with stickers on the face and head; and a video of a human with no stickers on the face or head. Each chimpanzee watched five repeats of each of the eight conditions.2.2.1.Pan troglodytes) participated in this study. All subjects lived in a group together at the Great Ape Research Institute, Hayashibara Biomedical Laboratories, Inc., Japan, in an enriched environment consisting of a 7400 m2 outdoor enclosure and several indoor areas [Five chimpanzees  had all looked at mirrors and reflective surfaces and made self-directed gestures, such as opening the mouth and looking into it. The other two individuals (Zamba and Misaki) were never observed using mirrors or reflective surfaces in this way prior to the current test.2 in area and 5 m tall, was used for these sessions. The pretest was conducted to confirm whether chimpanzees could recognize their own mirror image. Loi and Zamba both entered the experimental room by themselves. Tsubaki was accompanied by her dependent infant. Mizuki and Misaki were not related, but had a close bond and came together to the experimental room. This pair also gave birth to their baby during the course of the experiment, who subsequently accompanied them. Familiar experimenters (S.H. and K.F.) stayed in the same room with the chimpanzees during testing. Additional staff were occasionally in the room, typically to take care of the infants who were not being tested.Before the delayed video testing, one pretest session involving mirror exposure and three pretest sessions involving live video exposure were conducted. An experimental room that was hexagonal in cross-section, 7.6 mThe pretest session involved three main steps. In step 1, four circular stickers (silver and 8 mm in diameter) were placed on areas directly visible to the chimpanzee (i.e. one sticker per arm and leg). Responses were then observed for about 30 s. In step 2, 10 circular stickers were placed on the chimpanzee's face and head. Based on the close and long-term relationships between the chimpanzees and the researchers, the five chimpanzees accepted placement of stickers without apparent distress. In contrast with many previous studies using the mark test . We alsoThree pretest sessions involving live video exposure were conducted. The aim of this pretest was to habituate the chimpanzees to the presence of a monitor and to provide experimenters with an opportunity to practise the delayed video testing procedures described below. In addition, these video images were used for the sessions of the delayed test for conditions 5 and 6 (see below). A video camera was placed at the top of the 19-inch monitor that presented the live video footage, and filmed an area from slightly below the chin to slightly above the top of the head. This camera was one of the two cameras used to record all testing sessions. The image on the monitor was flipped from the normal orientation, to ensure that the left–right correspondence was the same as that of a mirror image. The three-step procedure for this video pretest was the same as the pretest involving the mirror, except that the chimpanzee's image was displayed on a monitor rather than a mirror. An experimenter gave a small piece of food in the same manner as in the mirror exposure test. The experimenter stayed outside of the range covered by the video camera but their hand become visible on the monitor when food was given to the chimpanzee.2.3.The test was conducted in the same indoor experimental room, and familiar experimenters (S.H. and K.F.) stayed in the same room with the chimpanzees during testing . In stepIn step 2, one of the following eight videos (conditions 1–8) was presented for 2 min: a live video (condition 1), a 1 s delayed video (condition 2), a 2 s delayed video (condition 3), a 4 s delayed video (condition 4), a video of the subject that was filmed more than one week prior in which stickers had been placed on the face and head of the subject (condition 5), a video of the subject that was filmed more than one week prior, in which no stickers were present on the face and head (condition 6), a video of a human who had stickers placed on the face and head (condition 7) or a video of a human with no stickers (condition 8). In steps 1 and 2, an experimenter gave a small piece of food about every 20 s to ensure that the chimpanzee remained in a relaxed state to enable recording of their behaviour, regardless of the chimpanzee's behaviour during the test.For the live video condition, the image filmed by the camera placed at the top of the monitor (described above) was presented on the monitor. The image on the monitor was flipped from the normal orientation to ensure that the image shown was the same as that of a mirror image. The 1 s, 2 s and 4 s delayed conditions were created using a special device  that was plugged into the same video camera. For conditions 5 and 6 in which the delay exceeded 1 week, we edited video scenes recorded during the prior testing and/or pretest involving live video exposure. For condition 5, we edited the video to include only images of the chimpanzee in which (i) there were more than three stickers on their face and head, and (ii) no self-directed behaviour was evident to ensure there was no coincidental matching of the subject's current self-directed behaviour to that of the pre-recorded video. For condition 6, we edited the video to ensure that there were no stickers nor any self-directed behaviour. For the human videos, we recorded a person with whom the subjects were familiar but who was not present during testing. In both human videos, the models engaged in slight, natural movements so that the video was not a still image, but no self-directed behaviour occurred. The only difference between the two human videos was the presence (condition 7) or absence (condition 8) of 10 stickers located upon the head and face.Each session contained two conditions, each starting from step 1. We conducted 20 sessions for each of the five chimpanzees; thus, there were 40 conditions and five repeats of each of the eight conditions. The order of conditions was counterbalanced. The sessions were separated by at least one week, with an average of one month to avoid habituation and maintain the subjects' interest. The entire test (20 sessions) was carried out across 2 years and 2 months.2.4.The following behaviours were coded from the video recordings: (1) removal of stickers, (2) self-directed behaviour toward the head or face (i.e. the subject touching the face or head with their hand), (3) contingency checking behaviour, such as opening the mouth and shaking the hands and (4) looking at the monitor. Notably, (i) the removal of stickers is not mutually exclusive with self-directed behaviour, and the former requires the latter and (ii) the coding of whether a subject was watching the monitor overlaps with other coded behaviours. Specifically, the coding included: ‘removal of the sticker while watching the monitor’, ‘removal of the sticker while not watching the monitor’, ‘self-directed behaviour while watching the monitor’, ‘self-directed behaviour while not watching the monitor’, plus contingency checking behaviour.The number of stickers on a subject's face and head at the start of the test (i.e. when the monitor was switched on) varied, as some of the 10 stickers originally placed were removed by subjects' groping behaviour. Therefore, we calculated the proportion of the number of stickers that were removed during the test by dividing the number of stickers removed during the test by the number of stickers at the start of the test, and compared these proportions across experimental conditions. We continued recording each subject's behaviour for 2 min after the start of the test, but the chimpanzees occasionally removed all of the stickers before the 2 min had elapsed. In such cases, we considered the time until the subject removed the last sticker as the test period, and calculated the proportion of the duration of a particular behaviour (e.g. self-directed behaviour while watching the monitor) by dividing the duration of that behaviour by this adjusted test period.κ for the above-mentioned four mutually exclusive coding categories was 0.813 (p < 0.001). The statistical tests were non-parametric as we could not assume normality in the dataset. Data from each individual was treated separately because there were individual differences in responses.A rater who was unaware of the experimental conditions and hypotheses coded all of the video recordings. A second rater coded 20% of the sessions to measure inter-rater reliability. Cohen's 3.3.1.Three chimpanzees  removed all of the stickers while watching mirror and live video images during the pretests. The remaining two individuals (Zamba and Misaki) did not remove any stickers placed on their face and head during the mirror and live video exposure pretests, but they removed all of the stickers placed on the visible parts of the body such as the arms and legs.3.2.p = 0.36). However, there were statistically significant differences in the proportion of stickers removed while watching the monitor across the eight conditions  and the proportion of time spent engaging in self-directed behaviour while watching the monitor across the eight conditions  on the group level , the proportion of stickers removed while watching the monitor  and the proportion of time spent engaging in self-directed behaviour while watching the monitor .Three of five chimpanzees  consistently engaged in self-directed behaviours, exhibiting hand/finger actions directed to their own face and head, and removing the stickers while watching the image on the monitor in the live, 1 s, 2 s and 4 s delay conditions . The responses of these three individuals were significantly different across the eight conditions according to the following three measures: the proportion of stickers removed , whereas the corresponding proportions of self-directed behaviour were significantly lower in conditions 5–8 .Conditions 5–8 were used to rule out the possibility that the self-directed behaviour we observed while chimpanzees watched the monitor would emerge when viewing any stimuli on the monitor (condition 8), mere appearance of stickers in the image shown on the monitor (condition 7), a self-image video with no stickers (condition 6), or a self-image video without relevance to their current state (condition 5). The proportion of time spent on self-directed behaviour while watching the monitor was not different between the live and briefly delayed conditions . The other two chimpanzees, Loi and Tsubaki, did not exhibit contingency checking behaviour, but did engage in several self-directed behaviours while watching the videos for conditions 5–8.p > 0.1 for all of the individuals). Moreover, the three chimpanzees who exhibited evidence of recognition while watching delayed videos each removed one or more stickers during the first presentations .To test for the possible effects of learning during the course of the experiment, we examined responses across sessions. The result showed no statistically significant increases or decreases in the three measures as a function of session in (i) the proportion of stickers removed, (ii) the proportion of time spent engaging in self-directed behaviour while watching the monitor, and (iii) the proportion of stickers removed while watching the monitor  did not identify any trends in recognition. The three chimpanzees exhibited evidence of recognition while watching delayed videos during the first presentations, indicating that the chimpanzees were able to recognize their self-image in the delayed video conditions from the beginning of the experiments.We have thus far discussed the positive results from three of five chimpanzees. The other two chimpanzees exhibited almost no self-directed behaviour or removal of stickers placed on the head and face . ImportaWhile the interpretation of these negative results remains unclear, individual variation in the capacity for self-recognition is possible and motivational factors may also play a role. However, the two chimpanzees easily removed the visible stickers that were placed on their arms and legs. Therefore, the fact that these two individuals did not remove the stickers that were placed on non-visible parts of their face cannot be ascribed to simple lack of motivation to remove the stickers. There may be individual variations in the depth of the level of self-recognition in chimpanzees. Alternatively, subtle differences in the rearing environment may have led to the varied performance in this task. A cross-country study of human children found cultural differences in their mirror self-recognition . Thus, tResearchers have reported similarities in various types of higher cognitive functioning between chimpanzees and humans, such as memory, tool-use and symbolic representation . The preThere may be criticism against our study, as our method was different from the classic mark test and the subject chimpanzees knew that the stickers were being placed. A future direction of study would be to use the classic mark test paradigm, which requires surreptitious placement of a marker/sticker, to investigate delayed self-recognition in non-human animals. However, this approach would face the following two challenges: first, it would be difficult to secure a sufficiently large number of subjects. Surreptitious placement of a marker/sticker is ideally accomplished as a single trial, as has been seen in studies with human children that used between-subject comparisons to test live versus delayed self-recognition –7. To coet al. [Furthermore, if such a study relied on using dye that cannot be removed easily as a marker , chimpaet al. , we consAnother future direction of study would be to extend the duration of the delay to match that of most of the human studies ,5,7,9. A


From the perspective of video media, measuring speed biases may help to optimize video reproduction speed and validate “natural” video compression techniques based on sub-threshold temporal squeezing.We live almost literally immersed in an artificial visual world, especially motion pictures. In this exploratory study, we asked whether the best speed for reproducing a video is its original, shooting speed. By using adjustment and double staircase methods, we examined speed biases in viewing real-life video clips in three experiments, and assessed their robustness by manipulating visual and auditory factors. With the tested stimuli , speed underestimation was the rule rather than the exception, although it depended largely on clip content, ranging on average from 2% (ego-motion) to 32% . Manipulating display size or adding arbitrary soundtracks did not modify these speed biases. Estimated speed was not correlated with estimated duration of these same video clips. These results indicate that the sense of speed for real-life video clips can be systematically biased, independently of the impression of elapsed time. Measuring subjective visual  Motion pictures—videos—are becoming pervasive in our everyday life. Yet, videos might easily fool us. For example, we recently showed that observers fail to notice large speed manipulations when viewing a soccer match video clip . One reason could be that, subjectively, the scene is not “filling time” sufficiently. Indeed, according to an influential model based on the idea that temporal cognition depends on the accumulation of event ticks, perceived time is dilated when a visual stimulus “fills” it more densely, for example because of a higher speed or higher temporal frequency Brown, . Thus, iTo address these three issues, we assessed the subjectively estimated “natural” speed of short video clips depicting various real-life scenes. This was achieved by measuring the point of subjective equality . To mimic real-life viewing conditions, no stimulus standard was provided for comparison, so that observers had to rely entirely on their internal expectations. In Bayesian terms, this amounts to emphasizing the role of priors in perceptual decisions  volunteered for the experiments. They had normal or corrected-to-normal vision, and were naïve as to the purpose of the experiment. This study was carried out in accordance with the recommendations of San Raffaele Ethical Committee. The protocol was approved by the San Raffaele Ethical Committee. All subjects gave written informed consent in accordance with the Declaration of Helsinki.1, except for the video clip in the first-person perspective (ego-motion). Temporal calibration was performed by recording a visual stimulus flashing at 1 Hz for 60 s. The recorded flash frequency turned out to be 0.999 Hz, which corresponds to an error of 0.1%.We used four short video clips , displaying physical motion, human motion—first-person and third-person perspectives—and mixed human-physical motion. Three videos were shot in-house with a smartphone in HD format , and one video was obtained, with permission, from a web collection of naturalistic landscapes, again in HD formatVideo clips represented rather uniform scenes and were displayed on a black background. C1 (jumping man—only human motion) is a frontal shot of a young man jumping in front of a building wall. C2  shows the same man dribbling a soccer ball in front of the same wall. C3  is a wide shot of an undertow of the sea, with the seashore in the front, surrounded by a few rocks, and the sea in the background. C4 (ego-motion) is a first-person perspective of a walk in a crowded street. The original video clips are available on request from the corresponding author.different frames are displayed. The frame rate cannot be higher than the refresh rate, but the refresh rate can be higher than the frame rate. In order to reproduce the video clips at a variable speed, participants changed the actual frame rate by means of two keyboard keys (speed increase and decrease). Given the 60 Hz refresh rate and the 30 Hz video original frame rate, reproducing a video at its original speed means displaying the same frame twice in two subsequent refresh cycles (2:1 ratio). Doubling the original video speed means displaying a video frame every refresh cycle (1:1 ratio), while halving it means displaying one video frame for four refresh cycles (4:1 ratio). Intermediate speeds are achieved by implementing appropriate ratios between the frame rate and the refresh rate. This solution for a variable speed video reproduction avoids two visual artifacts, namely, video tearing, which would result from the crude disabling of the V-synch signal, and unnatural motion, which could result from frame resampling/interpolation. In the debriefing, observers did not report motion irregularities, and videos appeared smooth. Programs were written in Matlab using the Psychophysics Toolbox extensions, and were run under Windows 7 on an Intel-based PC with on-board graphics. In this experiment videos were muted.Video clips were displayed on a 21″ LCD monitor at a 60 Hz refresh rate and a viewing distance of about 60 cm. We distinguish between refresh rate, i.e., the frequency at which the visual display visual buffer is updated, and frame rate, i.e., the frequency at which In this and our previous study . Their task was to adjust the speed by means of two keyboard keys (in 0.1% steps) in order to reach the speed that they reputed to be the original shooting speed, at which time they could skip to the next trial. Each video clip lasted 30 s, and this was also the maximum time available for speed adjustment, after which the program passed automatically to the next trial. Observers were never shown the videos at the original speed as the standard for comparison, and were instructed to be as natural as possible in trying to re-establish the original video speed, as if they were trying to fix the reproduction speed of their old, non-calibrated videotape player. A few familiarization trials with similar video clips preceded the beginning of the experimental session.The same participants were also tested for their ability to reproduce the duration of video clip pieces by means of a prospective interval reproduction task Grondin, , which wIn this experiment we tested four video clips , three clip sizes , and two repetitions (blocked), for a total of 24 trials for each participant. All factors were within-subject, and their presentation order was randomized within each block.α < 0.05, while in pairwise comparisons we used α < 0.01 to reduce multiple comparison effects. Effect size was assessed through partial eta square (η2), while associations were tested with Pearson’s r or Spearman’s rho according to their measurement scales. For the duration reproduction task, linear fitting of perceived vs. objective durations was performed through robust linear least-squares method.For the statistical analyses, we used both means and medians as estimators of central tendency, together with 95% bootstrap confidence intervals (method: bias corrected and accelerated percentile with 1000 runs). Normality assumption was checked with the Shapiro-Wilk test, and outliers were detected with the Grubbs test. Repeated-measures ANOVAs were used, applying the Greenhouse correction whenever necessary, in which case the degrees of freedom were non-integer. Null-hypothesis was rejected at For technical problems, three participants were excluded from the analyses, as their recordings were corrupted. Thus, in the following we report data from 12 participants. Four outlier values  were replaced by mean values.F = 5.680, p = 0.003, η2 = 0.341).As an initial step, we considered the adjustment history for all participants in all trials Figure . The plo−1). Figure F = 7.009, p = 0.013, η2 = 0.389). Pairwise contrasts showed only one non-significant comparison, namely, C2 vs. C4. Despite the non-significant interactions, to further examine whether speed judgments are indeed insensitive to display size, we ran four separate ANOVAs, one for each video clip data. Again, no statistically significant effects of display size were found, except for an interaction display size × repetition with C4  = 5.305, p = 0.018, η2 = 0.325).The final value of the adjusted speed reached at the end of the trial is the PSE, expressed as a frame rate value, which we took as a measure of speed judgment  by 9%, 3%, 25% and 4% for C1, C2, C3 and C4, respectively Figure , and ther = −0.010, p = 0.866). By contrast, we found a significant trial-wise correlation between total adjustment behavior, computed as the sum of instantaneous IFI changes produced in each trial, and speed estimation , which suggests that the more observers adjust, the more they underestimate video speed, regardless of the initial speed.We checked for a possible correlation between the randomly assigned initial video clip speed and the final observer’s estimation, but the two variables were not correlated at the trial-wise level (t(11) = −7.869, p < 0.001). At variance with PSE in the speed estimation task, it did not depend on the video clip type (F(333) = 2.410, p = 0.085, η2 = 0.180). Indeed, slope was not correlated with PSE, either subject-wise , subject-and-clip-wise , or subject-and-clip-and-size-wise . The intercept, which could reflect very short-range temporal processing, and was on average negative across subjects although not significantly different from zero  = −10.950, p < 0.001), was also uncorrelated with PSE .Figure p = 0.024, N = 12). However, the sample size was small and most subjects’ age was comprised between 20 and 30, thus we cautiously suggest that this result remains to be confirmed with a participants’ sample better tailored to studying age effects.Finally, we found a positive significant correlation between PSE and subject age , and smaller errors were found with human motion , ego-motion , and mixed human-and-physical motion .As for display size, we failed to find significant effects on PSE, either globally or with single ANOVAs. This suggests that, as far as speed is concerned, it makes no difference watching a movie on a computer monitor (the largest display size used in this experiment) or on a mobile phone . Clearly, it is possible that stronger manipulations turn out to be effective in modifying video speed judgments, such as immersive display viewing.As for the duration reproduction task, we did not find evidence that duration estimation is related to speed estimation. First, at variance with speed estimation, temporal estimation did not depend on clip type. Second, no correlation was found between the performances in the two tasks, regardless of whether we considered the level of subject, subject-and-clip, or subject-and-clip-and-size level. Note that the lack of significant effects of repetition in the speed estimation task makes the presence of carry-over effects due to the fixed task sequence unlikely.tempo variations of a metronome beating; tempo variations of a musical piece; musical pieces and white noise allegedly capable of evoking different arousal states), and in one case, volume manipulation, could modify the PSE for video speed.It is possible that the tendency toward speed underestimation found in Experiment 1 depended on the fact that the video clips were muted. Indeed, as anticipated, acoustic stimuli can modulate temporal processing and have a tight relation to movement  volunteered for the experiments. They had normal or corrected-to-normal vision. This study was carried out in accordance with the recommendations of San Raffaele Ethical Committee. The protocol was approved by the San Raffaele Ethical Committee. All subjects gave written informed consent in accordance with the Declaration of Helsinki.Stimuli and tasks were the same as in Experiment 1, except that the maximal trial duration was extended to 60 s to provide a more comfortable response temporal window (video playback was in looping mode) and that, to reduce the overall duration of the experiment, the video clip with human motion (C1) was dropped (C1 was in fact similar to C2 in terms of both content and PSE). Another difference with Experiment 1 was that at the end of each trial participants provided a confidence rating on a 1–9 scale at the end of each trial. This was a type 2 judgment, that is, a judgment of the participant’s own decision performance , which were generated with the “TempoPerfect” Software (NCH Software). In session 2 we used a Bach piece , with five speed levels . Audio speed manipulations included pitch-compensation. Finally, because pure temporal manipulations may be less effective than music salience , plus an additional white noise stimulus. In this session we manipulated also the soundtrack volume (two levels). The three stimuli were equalized to yield the same mean sound amplitude at each volume level (45 and 61 dB on average). In all sessions auditory stimuli were reproduced on headphones. Sound levels were measured with the “Science Journal” app for smartphones, placing the microphone close to the headphones loudspeaker. Before starting the experiment, participants were given a short familiarization session.This experiment had three experimental sessions, characterized by different soundtracks. In session 1 we used a sequence of metronome beats, with five different tempo), for a total of 15 trials for each participant. In session 2 we tested the same three video clips and five auditory conditions , for a total of 15 trials for each participant. In session three we tested the same three video clips, with three auditory conditions (two pieces plus white noise) and two volume levels, for a total of 18 trials for each participant. In all sessions the design involved only within-subject factors, and their presentation order was randomized. Each session lasted about 20 min. The three sessions were run in either the same or different days, according to the participants’ convenience. Participants took part in either one (N = 6), two (N = 8) or three (N = 7) experimental sessions, and, where possible, session order was counterbalanced across subjects so that each session had 15 subjects.In session 1, we tested three video clips , and five auditory conditions , suggesting that using 60 s as maximal trial duration was an over-prudent measure, and that the 30-s trial duration used in Experiment 1 was appropriate. In the following, we report the main results from the three sessions in sequential order.F = 9.465, p = 0.004, η2 = 0.403), with speed increments of 6%, 20% and 0% for C2, C3, C4, respectively  PSEs were significantly above the objective video clip frame rate, in two subjects (13%) they were significantly smaller, and in four subjects (27%) confidence intervals included the 30-fps reference value (data not shown).As in Experiment 1, we found the video clip type to be the only factor capable to significantly affect PSE , and a significant trial-wise correlation between total adjustment behavior and PSE .We found a modest but significant trial-wise correlation between the initial video clip speed and PSE .The pattern of confidence ratings indicated good compliance with the task, with mean values across video clips and soundtracks ranging between 4.3 and 9. The main effect of video clip, but not of soundtrack, was statistically significant . ANOVA revealed only a significant main effect of video clip  = 7.421, p = 0.015, η2 = 0.346). All pairwise contrasts with the three clips were statistically significant. We found no statistically significant effects of soundtrack by running a separate ANOVA for each video clip data. Speed increments were 5%, 18% and −1% for C2, C3, C4, respectively .No significant trial-wise correlations emerged .Mean confidence ratings ranged between 4.6 and 9. The main effect of video clip, but not of soundtrack, was statistically significant  = 7.777, p = 0.012, η2 = 0.357), and no other significant effects. All pairwise contrasts with the three clips were statistically significant. Also ANOVAs on individual video clip data failed to show significant effects. Speed increments were 6%, 18% and −1% for C2, C3, C4, respectively , rather than a soundtrack with different r = 0.147, p = 0.015) and not with the initial video clip speed .PSE was significantly correlated with total adjustment behavior (p = 0.018), but not that of soundtrack (p = 0.340).Mean confidence ratings ranged between 5.8 and 8.8. Again, the main effect of video clip was statistically significant , and strengthens the notion that systematic, stimulus-specific errors in estimating video speed reflect rather robust biases in visual cognition. Clearly, as also noted for display size, it is always possible that stronger or different auditory manipulations turn out to be effective in modifying video speed judgments .We also found that the estimated video speed was not totally independent of the adjustment procedure, because PSE was sometimes correlated with either the initial video speed and/or observers’ adjustment behavior. This observation motivated Experiment 3.In this experiment we aimed at replicating the speed estimation errors found in Experiments 1 and 2, but using another psychophysical method, namely, the double staircase method. Indeed, actively adjusting the video speed over time is not equivalent to making a pure perceptual judgment. In relying on the experimenter’s rather than the subject’s control, the staircase method provides a more perceptually-oriented measurement procedure  volunteered for the experiments. They had normal or corrected-to-normal vision, and were N = 10), and each group was presented the C2 video clip and either the C3a or the C3b video clip .Stimuli were prepared by randomly selecting 3 s-long portions of the two video clips used in Experiments 1 and 2 (C2 and C3). These two video clips were associated to large and small speed estimation errors, respectively, thus spanning a relatively wide perceptual range. We actually tested two versions of the stimulus that determined the highest error (C3), which allowed us to verify whether such a large speed estimation error could be due to some peculiarity of that particular video clip. The first version, called C3a, was the same that we already used in the previous experiments. The second version, called C3b, depicted the same general visual subject (water waves), but was shot with the same camera used to record video clips C1, C2 and C4 . Participants were divided in two groups (The staircase procedure involved two series (one for C2 and the other for C3) of double (increasing and decreasing) staircases randomly interleaved, with maximum 40 trials each , targeting 50% PSE (1 up − 1 down steps), and with 16 reversals as stopping rule. The entire procedure lasted about 15 min. This experiment was conducted with the same equipment used in Experiment 2.For each observer, PSE for each video clip was computed in two ways, respectively as the geometric mean of the last 11 responses over the two staircases, or as the video clip speed corresponding to half of the psychometric function (0.5). The psychometric function was computed through logistic fit of individual observers’ responses . Because PSE was practically identical when computed with the two methods, in the results we report only the PSE derived from the psychometric function This also made it possible to measure the just noticeable difference (JND), that is, the smallest discriminable speed difference as indexed by the semi-interquartile range of the psychometric function. PSE is expressed as percent departure from the original video clip frame rate and PSE as percentage of the original video clip frame rate, although for the statistical analyses the raw values were used.t-test for independent-samples (2-tailed) assessed PSE difference between C3a and C3b.The experiment was structured as a 2 × 2 design, with one within-subject (video clip) and one between-subject (group) factor. The statistical analyses were the same used in Experiment 1, except that a mixed-factors ANOVA was used. Moreover, Student’s N = 40) was reached 17 times, and the staircase procedure stopped on average after 33 trials .Observers’ responses converged rather regularly to a final plateau level. The maximum number of trials  = 55.171, p < 0.001, η2 = 0.754) and neither the main effect of group nor the interaction clip × group were significant  = 1.819, p = 0.194, η2 = 0.092, and F = 4.202, p = 0.055, η2 = 0.189, respectively), thus suggesting that PSE was essentially modulated by the general type of visual content rather than on specific stimulus features. Indeed, despite a tendency toward larger speed underestimation with C3a than with C3b, a pairwise comparison did not reveal a significant PSE difference between these two video clips (t(18) = 1.714, p = 0.104).PSE was significantly higher than 30 fps with all visual stimuli, as attested by confidence intervals, indicating a general tendency toward speed underestimation, especially for the C3 video clips Figure . The maiF = 12.435, p = 0.002, η2 = 0.409; main effect of group, F = 0.014, p = 0.908, η2 = 0.001; interaction clip × group, F = 0.273, p = 0.608, η2 = 0.015), and PSE and JND were positively correlated .A similar pattern of results was found for JND  made it unlikely for observers to be influenced by spurious cues related to trial sequence. Indeed, in that condition it is almost impossible for an observer to keep track of the history of each individual staircase sequence, thus excluding that a speed underestimation bias could have been introduced by converging to the speed mid-point counting the individual staircase steps. As a cons, to prevent the experimental session from lasting too long, speed judgments were based on rather short video clip pieces (3 s), thus losing large part of the visual context.tempo, by measuring the perceived “right” speed of real-life scenes presented as video clips. We ran three experiments in which methods and experimental conditions were varied. The results indicate that observers tended to judge video clips to be too slow , with a content-specific PSE pattern that survived across experiments  or auditory  factors.Speed underestimation was not an artifact. Temporal calibration was accurate, thus we can exclude temporal artifacts in video recordings. Also, the experiments were conducted on different computers, graphic cards and monitors, thus we can exclude temporal artifacts in video reproduction hardware. Furthermore, speed underestimation was found with two different psychophysical methods, adjustment and staircase, thus we can exclude a methodological artifact .Therefore, speed underestimation with real-life videos seems to be a genuine, replicable phenomenon, robust to experimental manipulations of display size and soundtrack. Clearly, this conclusion cannot be generalized, as PSE depended strongly on video content. It is entirely possible that certain stimuli are associated to null PSEs or even to speed overestimation , the sensitivity of the human visual system to sampled motion suggests a relationship between frame rate and speed perception (Watson and Ahumada, Converging evidence from multiple experiments in this study suggests that video speed biases are a genuine and replicable phenomenon, and robust to simple visual and auditory manipulations. Speed underestimation was the most common pattern that we have found, although at present this claim cannot be generalized. Importantly, when viewing real-life video clips speed biases may be the rule rather than the exception. This finding may be exploited to develop a simple assessment tool to monitor the subjective flow of reality, and may have far-reaching implications for the world of video media and perceptual technologies.FR acquired and analyzed the data, and contributed to writing the article. EM acquired the data. CS analyzed the data and wrote the article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.