Saturday, January 16, 2021

Through different administrations, liberals are shown more likely than self-identified conservatives to avoid interactions with and exposure to ideological disagreement; liberals are largely ideologically consistent

Ideological Bubbles and Two Types of Conservatives. Deborah J Schildkraut, Jeffrey M Berry, James M Glaser. Public Opinion Quarterly, nfaa027, January 11 2021,

Rolf Degen's take:

Abstract: For several years, and through different administrations, surveys have shown that self-identified liberals are more likely than self-identified conservatives to avoid interactions with and exposure to ideological disagreement. In this study, we demonstrate that this ideological asymmetry in outgroup avoidance can be partially explained by the well-established tendency of self-identified conservatives to hold moderate or liberal policy preferences. Using a nationally representative survey, we show that ideologically consistent conservatives look more like liberals (almost all of whom are ideologically consistent) in their tendency to engage in behaviors that promote ideologically homogeneous social networks. Inconsistent conservatives, on the other hand, are more likely to have ideologically heterogeneous social networks, making them less likely to clash with those on the other side and thus less likely to retreat from engagement, even if they hold conservative identities. This set of findings offers insight into the contours of polarization in contemporary America.

Calado et al. (2020)'s study not only showed that repeated events can be implanted, it raised doubts about the idea that repeated events might be harder to implant than single events

What science tells us about false and repressed memories. Henry Otgaar ORCID Icon,Mark L. Howe & Lawrence Patihis. Memory, Jan 12 2021.

Abstract: What does science tell us about memory phenomena such as false and repressed memories? This issue is highly pressing as incorrect knowledge about these memory phenomena might contribute to egregious effects in the courtroom such as false accusations of abuse. In the current article, we provide a succinct review of the scientific nature of false and repressed memories. We demonstrate that research has shown that about 30% of tested subjects formed false memories of autobiographical experiences. Furthermore, this empirical work has also revealed that such false memories can even be implanted for negative events and events that allegedly occurred repeatedly. Concerning the controversial topic of repressed memories, we show that plausible alternative explanations exist for why people claim to have forgotten traumatic experiences; explanations that do not require special memory mechanisms such as the unconscious blockage of traumatic memories. Finally, we demonstrate that people continue to believe that unconscious repression of traumatic incidents can exist. Disseminating scientifically articulated knowledge on the functioning of memory to contexts such as the courtroom is necessary as to prevent the occurrence of false accusations and miscarriages of justice.

KEYWORDS: Repressionrepressed memoryfalse memorymemorytrauma

The scientific nature of false and repressed memories

The issue of how traumatic experiences are remembered is one of the most contested areas in psychology. An especially controversial aspect of this is the topic of repressed memories. Repressed memory is the idea that traumatic experiences – such as sexual abuse – can be unconsciously blocked for many years such that the individual does not know they were abused, and later recovered in pristine form. The issue of repressed memories has become especially pervasive during the so-called “memory wars”; the ongoing debate between those (often memory scholars) asserting that there is no credible scientific evidence that repressed memories exist and others (often clinicians) claiming that repressed memories do exist. Many scholars have assumed that this debate has been settled, but there is evidence that this debate is far from over (Otgaar et al., 2019).

An important element of the debate concerned situations in which people went to therapy and recovered memories of abuse unknown to them before the therapy started. According to many clinicians, the reason for patients being unaware of an abusive experience was that the memories for that abuse were repressed and that therapy helped recover those memories. However, memory researchers contended that such therapeutic interventions might be inherently suggestive and lead to the creation of false memories of abuse (e.g., Loftus, 1993). Furthermore, another argument was that claims of repressed memories could often be explained by ordinary forgetting (Clancy & McNally, 2005). That is, it is quite normal that people who have experienced a traumatic event will not remember all details of that experience.

Considerable scientific work has been devoted to understanding how false memories are formed and whether repressed memories exist. However, questions have been raised about the ecological validity of false memory research (Blizard & Shaw, 2019). Furthermore, although controversial, the topic of repressed memory continues to be very alive in academic, clinical, and legal circles (for a review, see Otgaar et al., 2019). In the current article, our intention is to set the records straight and provide a brief review of what science tells us about the phenomenon of false and repressed memories. To accomplish this, we will pose several target questions about these phenomena that have frequently been discussed in the literature.

The science behind false memories

We will start with several key points that have frequently been mentioned in the false memory literature. Specifically, we will discuss several issues such as the prevalence of false memory susceptibility and the ecological validity of false memory implantation experiments.

How susceptible are people to forming false memories?

A pertinent issue in false memory studies is individuals’ susceptibility to creating false memories. Importantly, not one answer can be given to this question as different false memory methods have been constructed over the past several decades. For example, false memory production can result from associative processes within the mind (e.g., Deese/Roediger–McDermott false memory task; Deese, 1959; Roediger & McDermott, 1995) or from external suggestions from others (e.g., misinformation paradigm; false memory implantation; Loftus, 2005). For the current article, we will mainly focus on false memories elicited due to suggestions and misinformation because these are often most relevant to the memory wars debate.

One relevant false memory paradigm is the false memory implantation method (e.g., Loftus & Pickrell, 1995). In this method, participants are told to elaborate on events that are suggested to have truly happened to them, where several of the events actually did happen to them, but one event that did not. Using this procedure, researchers have implanted a wide variety of false events, ranging from being lost in shopping mall (Loftus & Pickrell, 1995), to taking a hot air balloon ride (Otgaar et al., 2013; Wade et al., 2002), to being abducted by a UFO (Otgaar et al., 2009), to bumping into a punch bowl at a wedding (Hyman & Billings, 1998). In general, these studies have shown that such suggestions can lead to false autobiographical memories.

When examining the rates at which participants fall prey to these suggestions, studies have found different percentages ranging between 0% (Pezdek et al., 1997) to 70% (Shaw & Porter, 2015; but see also Wade et al., 2018, who found only 30% with different criteria). Wade and colleagues (2002) were one of the first to find that across false memory implantation experiments, the weighted mean percent of false memories was 30%. In a more recent review, Brewin and Andrews (2017) analysed many false memory implantation studies and found full-blown false memories in only 15% of participants. Brewin and Andrews argued that implanting autobiographical false memories is not easy nor common.

An important limitation of Brewin and Andrew’s review was that they collapsed all false memory implantation studies and based on this, calculated a mean percent. False memory implantation studies have used various scoring methods to measure false memory formation and therefore calculating mean percentages is not the most precise estimate of false memory susceptibility. Therefore, Scoboria and colleagues (2017) applied a new coding system to eight previous false memory implantation studies. They found that overall 30.4% of reports were classified as false memories and this percentage increased to 46.1% when the suggestion included self-relevant information, imagination procedures, and was not accompanied by a photo.

Collectively, what research on false memory implantation has shown is that a non-trivial percentage of participants (around 30%) can be swayed into remembering a false autobiographical event. So, in contrast to what is sometimes argued (Brewin & Andrews, 2017), false memory implantation can quite commonly occur when the right conditions are met such as probing guided imagery (see also Nash et al., 2017; Otgaar et al., 2017). Real world therapy scenarios that repeat suggestions over time may yield even higher percentages than experiments that often involve just one or two suggestions.

How ecological valid are false memory implantation studies?

There have been numerous articles in which researchers have debated the ecological validity of false memory experiments (e.g., Ceci et al., 1998; Pezdek & Lam, 2007; Wade et al., 2007). Here we use the classic definition provided by Bronfenbrenner (1977) who stated that “ecological validity refers to the extent to which the environment experienced by the subjects in a scientific investigation has the properties it is supposed or assumed to have by the investigator” (p. 516).

One aim of false memory implantation work is to say something about false memories of traumatic events (e.g., sexual abuse). An important property of false memories of sexual abuse is that these memories often concern emotionally negative events and that such memories sometimes concern repeated events of abuse. Scholars have argued that false memory implantation studies do not meet these criteria. For example, Blizard and Shaw (2019) postulated that false memory researchers have “not been able to implant memories for repeated events, as is often the case with reported childhood sexual abuse” (p. 15). Similarly, Brewin and Andrews (2017) argued that “a challenge for the future will be to demonstrate that it is possible to implant memories of a repeated event” (p. 20).

Concerning the implantation of negative events, research has shown that it is possible to elicit false memories for negative events. For example, Porter and colleagues (1999) succeeded in making people falsely report remembering being bitten by a vicious dog. Also, Shaw and Porter (2015) falsely suggested to participants that they committed a crime (e.g., theft) which led to some apparent false memories. Furthermore, Otgaar et al. (2008) showed that in children, a negative false event (i.e., being accused of copying) was more easily implanted than a neutral false event (i.e., moving to another classroom), a pattern that has been also detected in other false memory paradigms as well (e.g., Bookbinder & Brainerd, 2016). Apart from these examples, researchers have implanted various other negative events in children and adults such as receiving a rectal enema (Otgaar et al., 2010; Pezdek et al., 1999), a finger getting stuck in a mousetrap (Ceci et al., 1994), and being hospitalised (Hyman et al., 1995). Of course, because of obvious ethical reasons, it is not possible to implant events that are even more stressful and negative. However, negative events that have been implanted share certain similarities with sexual abuse such as that the events can be painful (e.g., rectal enema, mousetrap), shameful (e.g., rectal enema), and emotionally arousing (e.g., hospitalisation).

The issue of whether repeated events can be implanted in memory has recently been addressed by Calado and colleagues (2020). In their experiment, they falsely told adult participants that they lost their cuddling toy several times while control participants were told that they only lost it once. Strikingly, they found that repeated false events were as easily inserted in memory as suggesting that the event happened once. So, this study not only showed that repeated events can be implanted, it raised doubts about the idea that repeated events might be harder to implant than single events.

Taken together, although the negative false events used in false memory implantation are still a far stretch from traumatic events that matter in legal cases (such as sexual abuse), an accumulating body of research has shown that the negative events in research do share some properties with the real life events in question. 

How does memory for the public past differ from memory for the personal past?

The good old days and the bad old days: evidence for a valence-based dissociation between personal and public memory. Sushmita Shrikanth &Karl K. Szpunar. Memory, Jan 6 2021.

Abstract: How does memory for the public past differ from memory for the personal past? Across five experiments (N = 457), we found that memories of the personal past were characterised by a positivity bias, whereas memories of the public past were characterised by a negativity bias. This valence-based dissociation emerged regardless of how far back participants recounted the personal and public past, whether or not participants were asked to think about significant events, how much time participants were given to retrieve relevant personal and public memories, and also generalised across various demographic categories, including gender, age, and political affiliation. Along with recent work demonstrating a similar dissociation in the context of future thinking, our findings suggest that personal and public event cognition fundamentally differ in terms of access to emotionally salient events. Direct comparisons between personal and public event memory should represent a fruitful avenue for research on event cognition.

KEYWORDS: Personal memorypublic memorycollective memoryemotion

Check also We are positively biased about our personal future while at the same time being negatively biased about the future of our country

Shrikanth, S., Szpunar, P. M., & Szpunar, K. K. (2018). Staying positive in a dystopian future: A novel dissociation between personal and collective cognition. Journal of Experimental Psychology: General. Apr 2018.

Friday, January 15, 2021

Facial recognition technology: Political orientation was correctly classified in 72% of liberal–conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or 100-item questionnaire (66%)

Facial recognition technology can expose political orientation from naturalistic facial images. Michal Kosinski. Scientific Reports volume 11, Article number: 100 (2021). January 11 2021.

Abstract: Ubiquitous facial recognition technology can expose individuals’ political orientation, as faces of liberals and conservatives consistently differ. A facial recognition algorithm was applied to naturalistic images of 1,085,795 individuals to predict their political orientation by comparing their similarity to faces of liberal and conservative others. Political orientation was correctly classified in 72% of liberal–conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%). Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples. Accuracy remained high (69%) even when controlling for age, gender, and ethnicity. Given the widespread use of facial recognition, our findings have critical implications for the protection of privacy and civil liberties.


An algorithm’s ability to predict our personal attributes from facial images could improve human–technology interactions by enabling machines to identify our age or emotional state and adjust their behavior accordingly. Yet, the same algorithms can accurately predict much more sensitive attributes, such as sexual orientation7, personality20 or, as we show here, political orientation. Moreover, while many other digital footprints are revealing of political orientation and other intimate traits29,30,31,32,33,34, one’s face is particularly difficult to hide in both interpersonal interactions and digital records. Facial images can be easily (and covertly) taken by a law enforcement official or obtained from digital or traditional archives, including social networks, dating platforms, photo-sharing websites, and government databases. They are often easily accessible; Facebook and LinkedIn profile pictures, for instance, are public by default and can be accessed by anyone without a person’s consent or knowledge. Thus, the privacy threats posed by facial recognition technology are, in many ways, unprecedented.

Predictability of political orientation from facial images does not necessarily imply that liberals and conservatives have innately different faces. While facial expression or head pose, facial hair, and eyewear were not particularly strongly linked with political orientation in this study, it is possible that a broader range of higher-quality estimates of those and other transient features could fully account for the predictability of political orientation. Yet, from the privacy protection standpoint, the distinction between innate and transient facial features matters relatively little. Consistently changing one’s facial expressions or head orientation would be challenging, even if one knew exactly which of their transient facial features reveal their political orientation. Moreover, the algorithms would likely quickly learn how to extract relevant information from other features—an arms race that humans are unlikely to win.

Some may doubt whether the accuracies reported here are high enough to cause concern. Yet, our estimates unlikely constitute an upper limit of what is possible. Higher accuracy would likely be enabled by using multiple images per person; using images of a higher resolution; training custom neural networks aimed specifically at political orientation; or including non-facial cues such as hairstyle, clothing, headwear, or image background. Moreover, progress in computer vision and artificial intelligence is unlikely to slow down anytime soon. Finally, even modestly accurate predictions can have tremendous impact when applied to large populations in high-stakes contexts, such as elections. For example, even a crude estimate of an audience’s psychological traits can drastically boost the efficiency of mass persuasion35. We hope that scholars, policymakers, engineers, and citizens will take notice.

This is a clear indication that the global signal from human-induced climate change is now as powerful as the force of nature, said Prof. Taalas

2020 was one of three warmest years on record. World Meteorological Organization Press Release Number 14012021. January 14 2021.

Geneva, Jan 14 2021 - The year 2020 was one of the three warmest on record, and rivalled 2016 for the top spot, according to a consolidation of five leading international datasets by the World Meteorological Organization (WMO). A naturally occurring cooling climate phenomenon, La Niña, put a brake on the heat only at the very end of the year.

All five datasets surveyed by WMO concur that 2011-2020 was the warmest decade on record, in a persistent long-term climate change trend. The warmest six years have all been since 2015, with 2016, 2019 and 2020 being the top three. The differences in average global temperatures among the three warmest years – 2016, 2019 and 2020 – are indistinguishably small.  The average global temperature in 2020 was about 14.9°C,  1.2 (± 0.1) °C above the pre-industrial (1850-1900) level.

“The confirmation by the World Meteorological Organization that 2020 was one of the warmest years on record is yet another stark reminder of the relentless pace of climate change, which is destroying lives and livelihoods across our planet. Today, we are at 1.2 degrees of warming and already witnessing unprecedented weather extremes in every region and on every continent. We are headed for a catastrophic temperature rise of 3 to 5 degrees Celsius this century. Making peace with nature is the defining task of the 21st century. It must be the top priority for everyone, everywhere," said United Nations Secretary-General António Guterres.

“The exceptional heat of 2020 is despite a La Niña event, which has a temporary cooling effect,” said WMO Secretary-General Prof. Petteri Taalas. “It is remarkable that temperatures in 2020 were virtually on a par with 2016, when we saw one of the strongest El Niño warming events on record. This is a clear indication that the global signal from human-induced climate change is now as powerful as the force of nature,” said Prof. Taalas.

“The temperature ranking of individual years represent only a snapshot of a much longer-term trend. Since the 1980s each decade has been warmer than the previous one. Heat-trapping gases in the atmosphere remain at record levels and the long lifetime of carbon dioxide, the most important gas, commits the planet to future warming,” said Prof. Taalas.

The La Niña event which began in late 2020 is expected to continue into early to mid-2021.  La Niña and El Niño effects on average global temperature are typically strongest in the second year of the event, and the extent to which the continued cooling effects of La Niña in 2021 may temporarily diminish the overall long-term warming trend during this coming year remains to be seen.

Sustained heat and wildfires in Siberia and low Arctic sea ice extent, as well as the record-breaking Atlantic hurricane season were among the standout features of 2020.

Temperature is just one of the indicators of climate change. The others are: greenhouse gas concentrations; ocean heat content; ocean pH; global mean sea level; glacial mass; sea ice extent and extreme events.

As in previous years, there were significant socio-economic impacts in 2020. For instance, the United States reported a record 22 billion-dollar disasters in 2020, which was the nation’s fifth warmest year on record.   

International Datasets

WMO uses datasets (based on monthly climatological data from observing sites and ships and buoys in global marine networks) developed and maintained by the United States National Oceanic and Atmospheric Administration (NOAA), NASA’s Goddard Institute for Space Studies (NASA GISS), and the United Kingdom’s Met Office Hadley Centre and the University of East Anglia’s Climatic Research Unit (HadCRUT).

WMO also uses reanalysis datasets from the European Centre for Medium Range Weather Forecasts and its Copernicus Climate Change Service, and the Japan Meteorological Agency (JMA).  Reanalysis combines millions of meteorological and marine observations, including from satellites, with models to produce a complete reanalysis of the atmosphere. The combination of observations with models makes it possible to estimate temperatures at any time and in any place across the globe, even in data-sparse areas such as the polar regions.

NASA and Copernicus Climate Change Service estimate that 2020 is jointly the warmest year on record together with 2016. NOAA and the United Kingdom’s HadCRUT dataset both ranked 2020 as the second warmest behind 2016, with Japanese Meteorological Agency (JMA) Reanalysis ranking 2020 as the third warmest.  The small differences among these datasets are all within the margin of error for calculating the average global temperature according to WMO.

The Met Office and the University of East Anglia recently upgraded their long-running HadCRUT dataset, including better coverage in data-sparse areas such as the rapidly warming Arctic. This provides more accurate estimates of global, hemispheric and regional temperature changes. The previous version, HadCRUT4, showed less warming than other global temperature data sets. HadCRUT5 is now more consistent with these other datasets during recent decades and shows slightly more warming than most of them do over the full period since 1850. 

Future projections

The temperature figures will be incorporated into the final WMO report on the State of the Climate in 2020 which will be issued in March 2021. This includes information on all leading climate indicators and selected climate impacts, and updates a provisional report issued in December 2020.

The Paris Agreement seeks to hold the increase in the global average temperature to well below 2°C above pre-industrial levels while pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels.  At 1.2 °C above the pre-industrial (1850-1900) levels, the global average temperature in 2020 is already approaching the lower limit of temperature increase the Paris Agreement seeks to avert. There is at least a one in five chance of the average global temperature temporarily exceeding 1.5 °C by 2024, according to WMO’s Global Annual to Decadal Climate Update, led by the United Kingdom’s Met Office.

The Met Office annual global temperature forecast for 2021 suggests that next year will once again enter the series of the Earth’s hottest years, despite being influenced by the temporary cooling of La Niña, the effects of which are typically strongest in the second year of the event.

Although some mating strategies among gay people resemble heterosexuals of the same sex, others resemble heterosexuals of the opposite sex, & yet in others, the pattern is different than among either heterosexual men or women

Valentova, Jaroslava V., and Marco Antonio C. Varella. 2021. “Initiation of Non-heterosexual Relationships.” PsyArXiv. January 14. doi:10.31234/

Abstract: Human sexual orientation is an intriguing phenomenon which is still poorly understood and has important evolutionary implications. Evolutionary based studies mostly focus on heterosexual individuals and relationships, probably because non-heterosexuality concerns a minority of the population and decreases individual direct reproductive success. To better understand human nature, it is important to analyse whether the mating psychology of minorities exhibit specific evolved sexual/reproductive strategies. Here we review studies on partner preferences, mate choice, and flirting in non-heterosexual populations, to identify which patterns are similar to or different from heterosexuals. The general pattern supports the notion that sex differences are larger than within sex variation among people of different sexual orientations. However, although some mating strategies among non-heterosexuals resemble heterosexuals of the same sex, others resemble heterosexuals of the opposite sex, and yet in others, the pattern is different than among either heterosexual men or women. We point to limitations of the current state of this research, and we suggest possible future directions in the study of non-heterosexual relationship initiation.

Monkeys Prefer Reality Tee Vee

Bliss-Moreau, Eliza, Anthony Santistevan, and Christopher Machado. 2021. “Monkeys Prefer Reality Television.” PsyArXiv. January 12. doi:10.31234/

Abstract: Decades of research have demonstrated that primates value and benefit from social interactions. Despite this, the extent to which nonhuman primates prefer social stimuli relative to similarly complex nonsocial stimuli has not been documented. In order to quantify macaques’ preference for social information, four adult rhesus monkeys freely selected whether they watched “reality television” (30-second videos of conspecifics; “social videos”) or nature documentaries (30-second videos of nature documentaries; “nonsocial videos”) over approximately 900 trials per monkey. After monkeys learned how to pick either category of video, the group showed a preference for viewing social videos. Monkeys demonstrated an attention-related preference for social information as well. Eye-tracking data revealed longer durations watching the social, as compared to nonsocial videos, without breaking gaze. Psychological properties of viewed videos predicted the choices that monkeys made on subsequent trials. Taken together, these results demonstrate an evolutionary old preference for social versus nonsocial information.

Much of science, including public health research, focuses on means (averages); the purpose of the present paper is to reinforce the idea that variability matters just as well

Variability Matters. Maarten Jan Wensink, Linda Juel Ahrenfeldt and Sören Möller. Int. J. Environ. Res. Public Health 2021, 18(1), 157; December 28 2020.

Abstract: Much of science, including public health research, focuses on means (averages). The purpose of the present paper is to reinforce the idea that variability matters just as well. At the hand of four examples, we highlight four classes of situations where the conclusion drawn on the basis of the mean alone is qualitatively altered when variability is also considered. We suggest that some of the more serendipitous results have their origin in variability.

Keywords: inequality; statistical inference; forecasting; lifespan; socioeconomic status; academic performance

6. Discussion

However witty, the accusation levelled against statisticians in the epigraph of this article is unfair. A statistician would always begin by listing some summary statistics of the data (the river, in this case), including variance, minimum and maximum values, and perhaps some quantiles. A statistician would also have some concern with the consequences of making a wrong decision: if these consequences are grave, such as drowning, a statistician would tolerate a smaller likelihood of a wrong decision than when consequences are trivial. As a result, no statistician would set out to wade confidently through a river based solely on information about its average depth.
Nevertheless, the oversimplistic approach of considering the mean alone, and not the distribution around it, is taken all too often. We have given four examples of situations where we needed to augment the information provided by the mean with information about variability in order to draw more informed conclusions. These examples illustrated four classes of situations: (1) if variability is different between groups, means alone give little insight into the share of people that reach a certain threshold and are hence selected into some group (say, high-achieving mathematicians, first example); (2) failing to account for variability gives wrong predictions of future trends (second example); (3) increasing variability implies that not all in a population capitalize on positive health trends to the same extent (third example); and (4) means without variability do not reveal the potential extent of public health issues (fourth example). A mean alone says little about the proportion of a population that crosses a threshold, while different subgroups of a population may follow different trends. This phenomenon also seems to be evident in spread of infectious diseases, most recently the Coronavirus Disease 2019 (COVID-19), where there is large heterogeneity in disease spreading [28].
There are limits to the amount of information that a single number can contain. From that perspective, it is unsurprising that we found situations where averages alone (single numbers) were insufficient to describe relevant aspects of the situation. This immediately begs the question whether a single number like the variance or standard deviation can contain all the relevant aspects of variability. Of course, if data are described sufficiently well by a two-parameter distribution, such as the normal distribution, two numbers say it all. However, in more complex situations, we may need more. Just like an average may not always suffice, descriptions of variability in a single number may be insufficient as well depending on the question we are trying to answer. We then need to complement this information with more numbers, for example skew, which help determine which part of a population crosses a threshold, or which part of a population experience increases in life expectancy.
Piketty [2] finds the Gini coefficient (a single number between 0 and 1) insufficient to describe economic inequalities and their evolution, and instead resorts to quantiles, such as the proportion of the overall wealth possessed by the poorest half of the population, the upper 10%, the upper 5%, the upper 1%, or indeed the upper 0.1% or even 0.01%. Depending on the kind of inequality and the period that he studies, four or five of such quantiles are deemed sufficient to grasp the main elements of economic inequality and its evolution. In their approach of forecasting statistical moments of the age-at-death distribution, Pascariu et al. [29] found that using seven statistical moments tends to strike a good balance between simplicity and computational tractability. Standard statistical courses often teach the first four moments (mean, variance, skew, kurtosis), all of which can be explained intelligibly with pictures, which becomes increasingly difficult for higher moments. Variability, then, is multidimensional as well.
When an inequality is detected, the level of inequality determines whether intervention is indicated, and how. For example, the insurance element of pension systems implies that some people will accumulate more pension payments than others. Indeed, the guarantee of a monthly income is precisely the point of pension systems, so inequality in the total amount of pension received is not necessarily problematic. An issue may arise when certain subgroups can systematically expect to receive a higher pension payout for every Euro they pay into the pension system. This is a matter of some concern, as pension systems often redistribute from poor to rich. Life expectancy of the rich is higher, while in-payments tend to be proportional to monthly benefits. Thus, for every Euro paid in, the rich and educated can expect to receive much more pension than the poor and uneducated, which raises questions about fairness [30].
In the same vein, consider a simple model where every human consists of the same number of cells that are all equally prone to become malignant due to genetic mutations that all occur at the same rate [31]. In such a model, there are no differences between humans at age 0. Yet the age at which cancer occurs, or indeed whether cancer occurs at all before death by competing causes [32], tends to be greatly distinct. Here we have inequality in consequences without any inequality whatsoever in baseline conditions. Yet, we wish to address them, so we should do so as inequality in the outcome emerges. Notice how chances are even at birth, but we still feel we should mend inequality in the outcome.

Discrimination was positively associated with anxiety and negative affect, operationalized by a common latent factor; anxiety and related disorders are not a result of common genetic liability alone

Discrimination and anxiety: Using multiple polygenic scores to control for genetic liability. Adolfo G. Cuevas, Frank D. Mann, David R. Williams, and Robert F. Krueger. Proceedings of the National Academy of Sciences, January 5, 2021 118 (1) e2017224118;

Significance: Genetic factors can concurrently influence perceptions of threatening and stressful events, like discriminatory experiences, and increase liability for anxiety and negative affect. The question has remained unsettled as to whether genetic susceptibility to anxiety and negative affect confounds the relationship between discrimination exposure and these phenotypes. In a national probability sample of noninstitutionalized, English-speaking respondents (n = 1,146), we found that discrimination was positively associated with anxiety and negative affect, operationalized by a common latent factor, even after accounting for genetic confounds. These findings suggest that discrimination is a risk factor for anxiety and related disorders rather than a result of common genetic liability alone. Reducing exposure to discrimination has the potential to improve mental health at the population level.

Abstract: An established body of research indicates that discrimination is associated with increased symptoms of anxiety and negative affect. However, the association cannot be interpreted unambiguously as an exposure effect because a common set of genetic factors can simultaneously contribute to increased liability for symptoms of anxiety, negative affect, and the perception of discrimination. The present study elucidates the association between discrimination and anxiety/negative affect by implementing strict genetic controls in a large sample of adults. We used data from the biomarker project of the Study of Midlife Development in the United States (MIDUS), a national probability sample of noninstitutionalized, English-speaking respondents aged 25 to 74 y. Participants who consented to provide genetic data were biologically unrelated and of European ancestry as determined by genotype principal components analysis (n = 1,146). A single structural regression model was fit to the data with three measures of discrimination specified to load onto a latent factor and six measures of anxiety and negative affect specified to load onto a second latent factor. After accounting for potential genetic confounds—polygenic scores for anxiety, depression, and neuroticism and the first five genetic principal components—greater discrimination was associated with greater anxiety/negative affect (β = 0.53, SE = 0.04, P < 0.001). Findings suggest that measures of perceived discrimination should be considered environmental risk factors for anxiety/negative affect rather than indices of genetic liability for anxiety, depression, or neuroticism. Clinical interventions and prevention measures should focus on ways to mitigate the impact of discrimination to improve mental health at the population level.

Keywords: discriminationanxietynegative affectinternalizingpolygenic scores

The Serpentine Illusion: A Visual Motion Illusion Induced by Phase-Shifted Line Gratings

The Serpentine Illusion: A Visual Motion Illusion Induced by Phase-Shifted Line Gratings. Junxiang Luo et al. Front. Neurosci., December 7 2020.

In a pattern of horizontal lines containing ± 45° zigzagging phase-shifted strips, vivid illusory motion is perceived when the pattern is translated up or down at a moderate speed. Two forms of illusory motion are seen: [i] a motion “racing” along the diagonal interface between the strips and [ii] lateral (sideways) motion of the strip sections. We found the relative salience of these two illusory motions to be strongly influenced by the vertical spacing and length of the line gratings, and the period length of the zigzag strips. Both illusory motions are abolished when the abutting strips are interleaved, separated by a gap or when a real line is superimposed at the interface. Illusory motion is also severely weakened when equiluminant colored grating lines are used. Illusory motion perception is fully restored at < 20% luminance contrast. Using adaptation, we find that line-ends alone are insufficient for illusory motion perception, and that both physical carrier motion and line orientation are required. We finally test a classical spatiotemporal energy model of V1 cells that exhibit direction tuning changes that are consistent with the direction of illusory motion. Taking this data together, we constructed a new visual illusion and surmise its origin to interactions of spatial and temporal energy of the lines and line-ends preferentially driving the magnocellular pathway.

General Discussion

In this paper, we describe a visual motion illusion, which we have called the Serpentine Illusion. It is elicited by a pattern of phase-shifted grating strips, abutting each other along a zigzagging interface. When the stimulus pattern is moved up or down, the intersections formed by the offset line gratings are seen to move in an undulating snake-like fashion. In addition to this motion along the diagonals, lateral motion of the sections is also seen. The strength of both illusory motions depends on the stimulus parameters. The illusion is luminance-contrast dependent, suggesting that magnocellular pathway signals have a predominant impact on the Serpentine Illusion. Results from selective adaptation show that both line gratings and physical motion are necessary for the full perception of the illusion, and modeling suggests the illusory motion can partly be explained by linear spatiotemporal receptive fields of motion sensitive V1 cells.

Visual Features Contributing to the Serpentine Illusion

We used an adaptation paradigm to test the contributions of orientation and motion mechanisms. We used moving and flashed grating-lines or grating-endpoints, and random dots, to adapt out the orientation, motion and end-stopping signals driven by the illusion inducing pattern. According to Figure 10, it was the moving line gratings that had the largest effect of weakening the perception of the Serpentine Illusion. To further test the contribution of line gratings for inducing the illusory motions, we introduced a pattern in which the line gratings of the original pattern were occluded by zigzag masks of varying thickness (Supplementary Figure 6). We found that illusory motion was abolished in the pattern with only endpoints visible (Supplementary Figure 6A), and only slightly restored when 1/2 or 1/3 of the grating lines were masked (Supplementary Figures 6B,C); illusory motion was weakened even with a very thin occluding mask (Supplementary Figure 6D). These observations suggest that continuous line gratings are crucial for the generation of both diagonal and lateral illusory motions.

Differences and Similarities Between Lateral and Diagonal Motion

Diagonal motion occurs primarily when the local contrast differences driven by the endpoints follow each other at close range (i.e., high density). This is the case when the line gratings are narrowly spaced, when the distance between the end points of a line is long and when the period length of the zigzags is short. This will make a grating strip look like an undulating column. On the other hand, lateral motion is favored by low density chains of end points as found with widely spaced line gratings, short horizontal distances between pairs of end points, and a long period of zigzags; these features favor a percept of horizontally arranged rows of end points moving sideward together. Apart from the parameters tested in Experiment 2, we further varied the angle of the zigzagging abutting interface. When the angle is changed to ± 30°, illusory motion along the diagonals predominates (Supplementary Figure 7A), whereas when the angle is changed to ± 60°, strong lateral motion is perceived (Supplementary Figure 7B). In the former case, the zigzags emphasize the vertical columnar structure, whereas at more acute angles the columns are less salient and the horizontal structure predominates. These parametric conditions for seeing diagonal and lateral illusory motion produce groupings that are consistent with the Gestalt principles of proximity and common fate. Whether these two illusory motion patterns drive the same or different underlying neural mechanisms remains unknown. The fact that either of the motion patterns can be almost eliminated when optimizing for the other condition (Supplementary Figures 24), suggests the neural mechanisms may be dissociable. Future studies will need to systemically explore the neural origins of both illusory motions using theoretical, psychophysical and physiological methods.

Illusory Motions Are Luminance-Contrast Dependent

Motion and color signals were classically thought to be encoded differentially (Ramachandran and Gregory, 1978Zeki, 1978Livingstone and Hubel, 1988). This parallel division receives some support from psychophysical studies in which chromatic gratings without luminance contrast can effectively weaken the ability of a subject to discriminate motion direction/speed (Cavanagh et al., 1984Troscianko and Fahle, 1988Cavanagh and Anstis, 1991Kooi and Devalois, 1992Mullen and Boulton, 1992abHenning and Derrington, 1994). Other studies, however, show that equiluminant color contrast can also provide weak cues for motion perception (Cavanagh and Favreau, 1985Saito et al., 1989Hawken et al., 1994Gegenfurtner and Hawken, 19951996a,bBurr et al., 1998Dougherty et al., 1999Lu et al., 1999Yoshizawa et al., 2000Willis and Anderson, 2002Cropper and Wuerger, 2005Burton and McKeefry, 2007). Cortical areas like MT (Saito et al., 1989Seidemann et al., 1999Thiele et al., 1999Wandell et al., 1999Barberini et al., 2005) and V3A (McKeefry et al., 2010) are able to encode motion signals derived from chromatically defined stimuli. In addition it is well known that area V4 encodes motion information and contains mixed parvocellular and magnocellular inputs (Desimone and Schein, 1987Mountcastle et al., 1987Ferrera and Maunsell, 2005Tolias et al., 2005Mysore et al., 2008An et al., 2012Li et al., 2013Yin et al., 2015Birman and Gardner, 2018). This physiological and anatomical data is consistent with the psychophysical data suggesting physical motion signals are processed through mixed pathways (Willis and Anderson, 2002Takeuchi et al., 2003McKeefry and Burton, 2009). Although the exact balance of interactions across form, color and motion signaling circuits is still a matter of some debate, there is nevertheless psychophysical evidence showing that motion illusions are minimized when presented under chromatic equiluminant conditions (Khang and Essock, 1997Hamburger, 2012).

The original Serpentine Illusion stimulus pattern has high luminance contrast between line gratings and background. When we reduced the contrast to physical equiluminance, illusory motion was greatly weakened (Figure 7). This suggests that luminance contrast is an important factor in generating the Serpentine Illusion, an observation consistent with several other motion illusions, which are found to be luminance-contrast dependent (Hamburger, 2012). Examples include the Pinna-Brelstaff illusion (Pinna and Brelstaff, 2000), the Rotating Snakes illusion (Kitaoka and Ashida, 2003), the Rotating-Tilted-Lines illusion (Gori and Hamburger, 2006), the Boogie-Woogie illusion (Cavanagh and Anstis, 2002), and the Dotted Lines illusion (Ito et al., 2009). This indicates that unlike physical motion, illusory motions in the Serpentine and other motion illusions are largely mediated by the magnocellular pathway. Additionally, previous psychophysical studies found that subjects underestimate the speed of moving gratings with relatively low luminance contrast (Campbell and Maffei, 1981Thompson, 1982Stone and Thompson, 1992Blakemore and Snowden, 1999Johnston et al., 1999Anstis, 2003). Analogously, the saliency of illusory motion can also be controlled through changing the strength of luminance contrast in the physical stimulus (Cavanagh and Anstis, 2002Anstis, 2004Backus and Oruc, 2005Howe et al., 2006Hamburger, 2012). It has been hypothesized that a moderate luminance contrast is the main factor in generating some motion illusions (Foster and Altschuler, 2001Cavanagh and Anstis, 2002Conway et al., 2005Ito et al., 2009Hamburger, 2012). However, for the Serpentine Illusion, only the extreme low luminance contrast (10% in Figure 8) can reduce the strength of the perceptual illusory motions.

The observations in Experiment 2 point toward a role for local contrast differences between the abutting line endings. Each pair of juxtaposed, phase-shifted line ends produces a dark patch that stands out when the stimulus pattern is moved up or down. One possible explanation of the illusory motion seen is due to the larger contrast of the dark patch relative to the grating strips. It is known that high-contrast gratings appear to move faster than low-contrast gratings (Thompson, 1982Stone and Thompson, 1992) and this might explain the faster rate at which the dark patches are seen to be moving relative to the flanking line gratings.

Alternatives to the Energy Model

Without directly recording from the nervous system, theoretical models are one of the best ways to infer neural mechanisms that underlie visual perceptual phenomenon. Here, we used the classical motion energy model (Adelson and Bergen, 1985) to show that primary visual cortex neurons respond with directional biases consistent with perception to the illusory motions in Serpentine Illusion stimuli. The motion energy model is a simplified linear summation model (Baker and Issa, 2005Mante and Carandini, 2005), best at predicting response properties in the earliest motion processing stages (Reid et al., 1987Carandini et al., 1997). Complex cells in primary visual cortex and neurons in downstream visual areas like MT and MST have more non-linear response properties (Emerson et al., 1992Simoncelli and Heeger, 1998Pack et al., 2006), and they contribute significantly to the neural representation and perception of illusory motions (Luo et al., 2019). Future studies should explore compare both linear and non-linear coding components and hierarchical population responses (mirroring the hierarchical spatiotemporal integration of motion information), as these may better predict the cortical responses to Serpentine and other illusory motion patterns.

Similarities and Differences Between Serpentine and Other Visual Illusions

The diagonal illusory motion along the zigzagging contour of the interface is reminiscent of the apparent motion in other two well-known motion illusions: the Boogie-Woogie illusion (Cavanagh and Anstis, 2002) and the dotted lines illusion (Ito et al., 2009). The Boogie-Woogie illusion is constructed by a grid of horizontal and vertical bars made up from alternating dark and bright squares placed on a gray background. When this grid is moved diagonally from the lower left to the upper right, the small squares making up the bars appear to “race” up the verticals and to the right along the horizontals. The authors attribute their illusion to different strengths of the motion signals elicited by the vertical and horizontal bars. Apparent upward motion resulting from the alternating light and dark edges of the squares moving “along” the bar (first-order motion) is said to constitute a more efficient motion signal than the “across” motion by the textured edge of the horizontal bar which therefore would appear to move more slowly and be overtaken by the vertically moving squares. The dotted lines illusion contains obliquely aligned white and black dots on a median gray background. Horizontal movement of the patten produce relative motion along the row of dots. The authors suggest that illusory motion is produced by the stronger luminance contrast between adjacent dots along the length of the line, compared to with the luminance difference between dotted lines and background.

Interestingly, another illusory motion effect can be perceived when the Serpentine Illusion picture is moved horizontally along the abutting line gratings (or by tracking the cursor as it moves leftward or rightward). The tilted zigzag illusory contours appears to swell out- or inward to each other. Such illusory motions are inconsistent with the aperture effect (Nakayama and Silverman, 1988), and appear related to the dotted-line illusion. Despite similarities, the lateral motion is not observed in either Boogie-Woogie illusion or dotted lines illusion. Moreover, the boogie-woogie illusion elicits the strongest motion at low contrast while the Serpentine Illusion becomes invisible at low contrast. Compared with the Boogie-Woogie and dotted lines illusion, the Serpentine Illusion does not contain luminance contrast along line gratings. Nevertheless, we cannot rule out the possibility that these three illusions may share similar underlying coding mechanisms, since luminance contrast is critical for producing illusory motion in all three patterns, and under equiluminant conditions, illusory motion is largely eliminated in all three patterns. Further psychophysical and physiological experiments are therefore needed to reveal the neuronal mechanisms underlying the Serpentine Illusion.