Tuesday, November 26, 2019

Interpreting Behavior Genetic Models: Complexity, compression, and the gloomy prospect

Interpreting Behavior Genetic Models: Seven Developmental Processes to Understand. Daniel A. Briley et al. Behavior Genetics, March 2019, Volume 49, Issue 2, pp 196–210, November 22 2018. https://link.springer.com/article/10.1007/s10519-018-9939-6

Abstract: Behavior genetic findings figure in debates ranging from urgent public policy matters to perennial questions about the nature of human agency. Despite a common set of methodological tools, behavior genetic studies approach scientific questions with potentially divergent goals. Some studies may be interested in identifying a complete model of how individual differences come to be (e.g., identifying causal pathways among genotypes, environments, and phenotypes across development). Other studies place primary importance on developing models with predictive utility, in which case understanding of underlying causal processes is not necessarily required. Although certainly not mutually exclusive, these two goals often represent tradeoffs in terms of costs and benefits associated with various methodological approaches. In particular, given that most empirical behavior genetic research assumes that variance can be neatly decomposed into independent genetic and environmental components, violations of model assumptions have different consequences for interpretation, depending on the particular goals. Developmental behavior genetic theories postulate complex transactions between genetic variation and environmental experiences over time, meaning assumptions are routinely violated. Here, we consider two primary questions: (1) How might the simultaneous operation of several mechanisms of gene–environment (GE)-interplay affect behavioral genetic model estimates? (2) At what level of GE-interplay does the ‘gloomy prospect’ of unsystematic and non-replicable genetic associations with a phenotype become an unavoidable certainty?

Keywords: Gene–environment interplay Human agency Personality Cognitive ability Developmental genetics

Complexity, compression, and the gloomy prospect

As a field, behavior genetics has produced substantial knowledge concerning replicable patterns of genetic and environmental influences across the lifespan (Plomin et al. 2016). Heritability is substantial (Turkheimer 2000), but each SNP explains a tiny portion of variance (Chabris et al. 2015). There is some evidence of GE-interplay, even if the empirical data to this point have not identified many replicable examples for G × E. Genetic and environmental effects shift across the lifespan as phenotypes become more stable. Although the statistical and interpretational implications of GE-interplay processes are well-known, the magnitude of each process is not well-known. Worse still, the factors that affect behavior genetic estimates all occur potentially simultaneously and continuously across development, and they may even interact with one another in a nonlinear and highly complex fashion. Researchers can increase the reasonableness of their inferences from behavior genetic models by gaining clarity on what is known and unknown concerning processes that influence parameter estimates. Ruling out potential processes can substantially shrink the number of possible interpretations.

Some basic questions remain difficult to address: what processes led to an estimate of 40% heritability? Was it additive and independent genetic effects, rGE reinforcing initial differences associated with genotype, or some form of G × E? Would heritability have been 40% if the sample was 10 years younger? Would heritability actually be 50% if assortative mating was correctly handled? Numerous papers have been written on the interpretive problems of heritability (e.g., Johnson et al. 2011; Keller et al. 2010; Turkheimer 1998). Our point here is not to retread this ground, but instead to point out the number of considerations required. Each of these considerations can be deconstructed in isolation to infer what the impact would be on behavior genetic models. The real world combines them all simultaneously in different quantities for each phenotype.

In the face of such taxing complexity, a framework with which to visualize the impact of different combinations of structural inputs would be useful. A successful model could generate phenotype levels from the ground up, starting with partners producing offspring with synthetic genomes and environments. One goal could be to identify what sets of model parameters can fill in the gaps identified in this review. As noted, there are likely several plausible sets of developmental parameters that could lead to the empirical results found in the literature. It might be the case that several potential models could produce similar observed trends, such as increasing heritability with age. We view this as a useful demonstration of the potential for equifinality in behavior genetic models, a limitation of the models that could be overlooked due to implicit assumptions about the data-generating mechanisms. A simulation approach would force these assumptions to be explicit and would allow them to be contrasted with other plausible assumptions.

In this context, we may think of phenotype development or the task of individual-level prediction as falling along a continuum of complexity. At one end is perfect simplicity: a change in an input leads to a change in the output every time, and researchers are able to make accurate predictions with easily obtainable and cognizable information. At the other end, it may be the case that there is such complexity that a description of development requires the full history of all variables at all points in time; the data stream is incapable of any compression. Under this scenario, the best anyone can do is record what happens. There is no more efficient way to express the observations, and the observations do not support any interesting predictions. Although behavior geneticists widely acknowledge that the phenotypes under study are complex (i.e., not having a single cause or simple set of causes), less consideration has been given to the potential compressibility of the phenotypes across individuals relative to the set of available variables (e.g., Li and Vitányi 1997; Wallace and Freeman 1987). By "compression," we mean the ability to represent some large set of information in a more compact manner (Braddon-Mitchell 2001; Sayood 2005; Wheeler 2016). To what extent can behavior genetics move from thousands of genetic associations toward a cognizable and useful model of development (see Kendler 2008)? This type of question has emerged most clearly in the literature surrounding the "gloomy prospect."

The need to empirically evaluate the gloomy prospect

Under the limitations of empirical data collection, little behavior genetic research exists that explicitly considers the possibility of the gloomy prospect. Plomin and Daniels (1987, p. 8) described the gloomy prospect as a situation in which "the salient environment might be unsystematic, idiosyncratic, or serendipitous events," ultimately minimizing the possibility that much scientific progress can be made. Turkheimer and Gottesman (1996) used a simulation approach to illustrate the gloomy prospect; small shifts in environmental context completely removed all specific phenotype.environment associations. Turkheimer (2000, p. 163) applied the same gloomy outlook to molecular genetic associations in the real world due to the inherent complexity of development and noted that "the underlying complex causal processes would cause the apparent results [of molecular genetic studies] to be small, and to change unpredictably from one experiment to the next."

The gloomy prospect is discouraging from an empirical standpoint as it implies that the upper limit for scientific progress in predicting and explaining future behavior at the individual-level may already have been reached or be reached without substantially more meaningful progress. If phenotype development is driven by genetic effects that manifest differently across environments that are peculiar to a given individual, then identifying the effect that a genetic variant has on development will necessarily also be idiosyncratic. If true, the clinical utility of genetic or environmental information about individuals will be largely worthless, since a plethora of interdependent factors (many of which are inaccessible due to a failure of measurement over development) must be known before reasonable predictions can be made.

Gloominess falls on a continuum, and how gloomy the prospect of giving an informative behavior genetic account depends on the phenotype. For example, it may be that things are a bit gloomier for personality compared to cognitive ability or anthropometric traits (e.g., Cheesman et al. 2017). If there is no GE-interplay and no other potentially biasing factors, then molecular genetic associations will replicate and the prospects for giving an informative account is not gloomy at all. But if, on the other hand, GE-interplay is extremely large and the effects of any genetic variant are entirely dependent on the (potentially random) environmental context, then it is unlikely that any genetic effect will replicate. This situation would be maximally gloomy. However, most phenotypes likely fall somewhere between these extremes.

We suggest that a plausible starting point for identifying the "gloominess" of a phenotype is to investigate the seven developmental processes highlighted in this manuscript. Put differently, a greater understanding of phenotype processes (i.e., how the phenotype influences engagement with the environment), structure (i.e., how phenotypes covary), and development (i.e., how phenotypes respond to engagement with the environment in the context of other relevant phenotypes across the lifespan; see Baumert et al. 2017). Each of these questions can be addressed with behavior genetic methodology. For example, the field has established the genetic and environmental structure of many related phenotypes. We suggest that gains can be made in overcoming the gloomy prospect by better understanding our phenotypes, that is to say, gaining knowledge not only of genetic and environmental structure, but also of the processes that led to such a structure across developmental time. This work toward explanation is directly relevant to researchers interested primarily in prediction as the gloomy prospect may imply some upper limit on prediction. Evaluating simultaneous GE-interplay will be challenging, but such work could provide important insight into the mechanisms of phenotype growth.

Additionally, progress toward identifying the boundaries of the gloomy prospect could be made by drawing more heavily on animal models. Although the strength of animal models is typically seen as exerting control over environmental experiences, an increasing number of studies use designs in which GE-interplay is possible (Bell and Saltz 2017; Freund et al. 2013). For example, social niche construction refers to the tendency of certain organisms to form social groups partially based on genetic differences (i.e., rGE; Saltz and Foley 2011; Saltz and Nuzhdin 2014). This behavioral tendency has also been found to be context dependent (Saltz 2011) and influence development (Saltz 2013, 2014). More generally, animals exhibit repeatable behavioral syndromes (Bell et al. 2009; Sih et al. 2004), similar to human personality, and a host of tools are available to better explain and predict these patterns (Bengston et al. 2018). This work may be better situated to address major unanswered questions in human behavior genetics, such as potential sources of Gene × Environment interaction. Lee et al. (2018) found relatively few leads on why genetic associations with educational attainment might vary across contexts (although, see Tropf et al. 2017 for an analysis with individual-level data), but the animal literature may offer further clues (see Saltz et al. 2018). Of course, evidence from animal models may be difficult to extrapolate to a phenotype like educational attainment, but the ability to track the effect of GE-interplay on development dynamically and consistently across the lifespan is a major advantage of animal models.

From 2014... The ultra‐social animal

The ultra‐social animal. Michael Tomasello. European Journal of Social Psychology, April 10 2014. https://doi.org/10.1002/ejsp.2015

Abstract: In evolutionary perspective, what is most remarkable about human sociality is its many and diverse forms of cooperation. Here, I provide an overview of some recent research, mostly from our laboratory, comparing human children with their nearest living relatives, the great apes, in various tests of collaboration, prosocial behavior, conformity, and group‐mindedness (e.g., following and enforcing social norms). This is done in the context of a hypothetical evolutionary scenario comprising two ordered steps: a first step in which early humans began collaborating with others in unique ways in their everyday foraging and a second step in which modern humans began forming cultural groups. Humans' unique forms of sociality help to explain their unique forms of cognition and morality.

Religious individuals had higher reproductive success (this association was especially pronounced in males); religiousness did not show associations with parental investment

Examining the link between religiousness and fitness in a behavioural ecological framework. Janko Međedović. Journal of Biosocial Science, November 26 2019. https://doi.org/10.1017/S0021932019000774

Abstract: In recent years there have been attempts to explain religiousness from an evolutionary viewpoint. However, empirical data on this topic are still lacking. In the present study, the behavioural ecological theoretical framework was used to explore the relations between religiousness, harsh environment, fitness (reproductive success and parental investment) and fitness-related outcomes (age at first birth, desired number of children and the romantic relationship duration). The data were collected from 461 individuals from a community sample who were near the end of their reproductive phase (54% females, Mage = 51.75; SD = 6.56). Positive links between religiousness, harsh environment, fitness and fitness-related outcomes were expected, with the exception of age at first birth, for which a negative association was hypothesized. Hence, the main assumption of the study was that religiousness has some attributes of fast life-history phenotypes – that it emerges from a harsh environment and enables earlier reproduction. The study findings partially confirmed these hypotheses. Religiousness was positively related to environmental harshness but only on a zero-order level. Religious individuals had higher reproductive success (this association was especially pronounced in males) but religiousness did not show associations with parental investment. Religiousness was positively associated with desired number of children and negatively associated with age at first birth, although the latter association was only marginally significant in the multivariate analyses. Finally, path analysis showed that desired number of children and age at first birth completely mediated the relation between religiousness and reproductive success. The data confirmed the biologically adaptive function of religiousness in contemporary populations and found the mediating processes that facilitate fitness in religious individuals. Furthermore, the findings initiate a more complex view of religiousness in a life-history context which could be fruitful for future research: a proposal labelled as ‘ontogeny-dependent life-history theory of religiousness’.


The behavioural ecological framework enables the analysis of the evolution of any behavioural trait ifthe trait in question is genetically transmitted across generations. This can even be applied to com-plex, socially and culturally influenced traits such as religiousness. However, the trait can be targetedby natural selection only if it is related to evolutionary fitness. Furthermore, one of the fundamentalassumptions of behavioural ecology is that individuals adapt to their local environments. The presentresearch sought to explore the relations between religiousness and fitness, the potential mediators ofthis relation and the environmental conditions that could be involved in it. The study hypothesis wasthat religiousness is biologically adaptive (i.e. it is positively associated with fitness and other fitness-related outcomes, all except age of first reproduction where negative association was assumed) andthat it emerges from harsh environmental conditions. These hypotheses were only partially confirmed. However, the study data provide a broader and more comprehensive view of religiousnessin a behavioural ecological context, confirming its adaptiveness in a biological sense. Furthermore, it reveals some of the mechanisms that religious individuals use to achieve higher reproductive success.Finally, the results are implicative for the future life-history theory of religiousness.

The associations between fitness and fitness-related measures
From the viewpoint of behavioural ecology, it is very important to analyse the relations betweenmeasures connected with fitness. First of all, reproductive success and parental investment werefound to be uncorrelated in the present research. This is not unusual–in fact, a negative correla-tion could be expected since number of children should be negatively related to parental invest-ment in each of them; this is a major evolutionary trade-off called the‘quantity–quality trade-off’(Lawson & Mace,2009). The absence of a negative correlation probably stems from the fact thatthe research was conducted in a low-fertility population, while the magnitude of this trade-off ishigher in populations with elevated mean reproductive success (Rosset al.,2016).
Age at first birth was found to be negatively related to both fitness indicators. This findingconfirms earlier findings of a negative directional selection on the timing of first reproduction:individuals who have their first child earlier in their lifetime have higher overall fitness (Tropfet al.,2015; Sanjaket al.,2018). The desired number of children was positively related to bothfitness measures as well. At first glance, this may sound like a trivial finding, but actually it is veryimportant since it shows unique features of contemporary human evolution: fertility in humans isbased on, but far from completely determined by, intentional motivation and planning (Johnson-Hanks,2008). Furthermore, it is at least partially subject to conscious control via contraceptionand other birth control measures. Finally, the duration of the partner relationship is positively relatedto reproductive success and negatively related to age at first birth: the longer individuals are in aromantic relationship, the earlier they become parents and they have more children. It is importantto note that these links were unchanged when participants’age was controlled in the analysis. Thus,long-term mating is apparently evolutionarily adaptive. This is in line with the theories that assumethat long-term mating is a dominant mating pattern in humans since human offspring need elevatedcare and investment from both parents (Stewart-Williams & Thomas,2013). In sum, the obtaineddata regarding the relations between fitness-related outcomes are quite congruent with previous find-ings and life-histories of contemporary humans.

Behavioural ecology of religiousness
Religious individuals have been shown to desire a higher number of children at the beginning oftheir reproductive phase, and they have their offspring earlier in their lifetime (although this linkwas rather weak in the present research) and have higher total fertility in general (this association was pronounced particularly in males, but it did not reach statistical significance in a subsample of females). However, they did not show elevated parental investment. A positive relation betweenr eligiousness and parental investment was assumed since religiousness is related to a closenesstowards family members and family values in general (Jensen & Jensen,1993). The absence ofthis link may suggest that religious individuals are oriented towards offspring quantity but notnecessarily offspring quality as a way of optimizing fitness.A positive link between religiousness and reproductive success has been empirically obtained inprevious research (Sanderson,2008; Blume,2009; Fieder & Huber,2016). The present study alsofound a positive link between religiousness and the desired number of children. These data are inline with a previous finding that shows positive attitudes of religious individuals towards child-bearing (Hayford & Morgan,2008). Furthermore, major religions often advocate a higher family size (Sanderson,2008). Previous research has also obtained evidence that religious individuals tend to have their first child earlier in their lifetime (Pearce & Davis,2016). This was confirmedin the present study, although the link was relatively weak (i.e. only marginally significant in mul-tivariate analyses). Finally, religiousness may enable high fitness in a somewhat indirect way: byfacilitating longer romantic relationships via commitment to marriage, marital satisfaction and lower risk of divorce (Mahoneyet al., 2002). However, this link was not detected in the present data and this was the only fitness-related outcome that was not associated with religiousness. It isimportant to note that desired number of children and age of first birth completely mediated the link between religiousness and reproductive success. This was not expected due to a fact thatthere could be other mediators of this link; however, this result only highlights the role these twovariables have in elevating the fitness of religious individuals.In sum, the data obtained in the present research are in line with previous results suggesting that religiousness is probably under positive directional selection on fertility. Thus, selection actspositively on the genetic basis of religious attitudes. Note that this does not necessarily mean that higher phenotypic levels of religiousness in the upcoming generations should be necessarilyexpected. Many complex cultural and environmental factors act on the phenotypic developmentof religious attitudes and some of them may be opposed to selection. This is why the frequency of religious commitment has in fact been found to fall in Western populations (Zuckerman,2015).The complexity of the biological and environmental factors that shape religiousness prevents theprediction of its phenotypic levels in future populations.Towards a future life-history theory of religiousnessPrevious findings of negative associations between religiousness, sexual permissiveness andrestricted sexuality together with positive associations with serial monogamy suggest that religiousness is part of a slow life-history trajectory (Gladdenet  al.,2009; Baumard &Chevallier,2015; Schmitt & Fuller,2015). However, this view may be oversimplified. If religiousness emerges from a harsh environment and enables earlier reproduction this would mean that ithas the characteristics of the fast life-history trait as well. These associations were obtained in thepresent research although they were fragile. The positive link between harsh environment andreligiousness was heavily dependent on the participants’ sex and age.  The negative link between religiousness and age at first birth was low in magnitude and marginally significant. However, these associations have been found in previous studies as well, and with more convincing effect sizes (Delamontagne, 2010; Pearce,2010; Soltet al.,2011; Pearce & Davis, 2016). It should be noted that elevated offspring quantity, which is clearly associated with religiousness, is the most important indicator of a fast life-history pathway in the first place. All these data suggest that religiousness indeed has some attributes of a fast life-history trajectory.

The present study was cross-sectional by design, which prevented making conclusions aboutthe causal relations between the measures. However, perhapsa  hypothesi sof religiousness’s involvement in life-history trajectories can be made. The existing data suggest that the life-history characteristics of religiousness are contingent on the stages of ontogeny. In earlier stages of development religiousness delays mating activity (expressed, for example, in negative associations between religiousness and the onset of sexual behaviour: Jones et al.,2005), which means that it has slow life-history attributes. However, in the reproductive stage itself, it is associated with earlier marriage and reproduction, thus acting as a fast life-history phenotype. When family is constituted, religiousness again turns to the slow life-history trait by decreasing sexual permissiveness and pro-moting monogamy. Hence, the life-history characteristics of religiousness are different during theontogeny. This proposition may be labelled as an‘ontogeny-dependent life-history theory of religiousness’. This hypothesis may be tested in future studies using a longitudinal approach.

Although many animals display bodily & behavioural changes consistent with the occurrence of affective states similar to those seen in humans, there is controversy about whether these are accompanied by conscious experiences

Towards a comparative science of emotion: Affect and consciousness in humans and animals. Elizabeth S. Paul et al. Neuroscience & Biobehavioral Reviews, November 26 2019. https://doi.org/10.1016/j.neubiorev.2019.11.014

•    Emotions comprise conscious, behavioural, physiological and cognitive elements.
•    Neural correlates of conscious emotion can be investigated in humans and animals.
•    Contemporary theories of consciousness have differing implications for animals.

Abstract: The componential view of human emotion recognises that affective states comprise conscious, behavioural, physiological, neural and cognitive elements. Although many animals display bodily and behavioural changes consistent with the occurrence of affective states similar to those seen in humans, the question of whether and in which species these are accompanied by conscious experiences remains controversial. Finding scientifically valid methods for investigating markers for the subjective component of affect in both humans and animals is central to developing a comparative understanding of the processes and mechanisms of affect and its evolution and distribution across taxonomic groups, to our understanding of animal welfare, and to the development of animal models of affective disorders. Here, contemporary evidence indicating potential markers of conscious processing in animals is reviewed, with a view to extending this search to include markers of conscious affective processing. We do this by combining animal-focused approaches with investigations of the components of conscious and non-conscious emotional processing in humans, and neuropsychological research into the structure and functions of conscious emotions.

[Full text, charts, references, at the link above]

8. Conclusions

The study of affective consciousness in animals falls squarely at the intersection of two longstanding controversies in psychological science – the relationship between consciousness and emotion and the measurement of nonhuman, and nonverbal, consciousness. Accordingly, the strands of empirical evidence and theoretical argument reviewed here are both richly diverse and hotly contested. But though it is beset by the twin enigmas of conceptualizing emotion and measuring consciousness, the study of animal affective consciousness is nonetheless of major potential importance, both for practical problems in animal welfare and for our efforts to get a clear view of our evolutionary kin, near and distant. We have adopted a componential view of emotions (reviewed in Section 3), in which conscious feelings constitute one component in a complex syndrome of related cognitive, motivational, expressive, and behavioural processes. And we have especially highlighted the implications of NCAC theories for a scientific understanding of how conscious feelings can, and cannot, empirically dissociate from other components of emotion, both within and across species.

In posing questions about conscious affect in animals, much (though not all1) work starts with the human case, where understanding is facilitated by subjects’ emotional reports (as well as the informal introspection the researcher employs in interpreting such reports). The human models are then used to identify candidate criteria for conscious emotion, which can be applied to observations of brain, behaviour, and physiology in different animal species. Research in this program can, in turn, be roughly divided into two classes – a wide-focus approach, which begins with general models of human consciousness (Section 4), and a narrow-focus approach, which sets out from specific models of human emotion (Section 5). The two approaches inform one another, because emotional consciousness is one form of consciousness, and together they can suggest principles for the identification of conscious affect in the absence of subjective report (Sections 6 and 7).

As our review illustrates, wide- and narrow-focus studies alike present a mixed picture of promising developments and enduring controversy. In our view, an especially promising strategy is to explicitly link proposed neurofunctional analyses of consciousness in general with a componential view of emotion in particular. This strategy is generative, suggesting novel potential resolutions to questions about conscious animal affect. Nonetheless, the stubborn persistence of core controversies (what kinds of cognition does consciousness require, and what kinds of emotional response require consciousness?) bars anything like a consensus choice among the candidate resolutions at present.

As an example of this dynamic, consider Fig. 1 and its depiction of the componential view of emotion. Here, five components of emotion (Scherer, 2005a,b) are conceptually distinguished, and the task for emotion researchers is to explain their empirical coordination in emotional responses. Such explanations may refer to hypothesized “coordinating mechanisms” that coherently control the component mechanisms (the solid lines in Fig. 1) and/or to direct links between the component mechanisms themselves (dashed lines). It is important to emphasize, however, that Fig. 1 does not, on its own, constitute a model of emotion. Rather, it supplies a conceptual framework within which empirical questions about emotion can be posed – questions which an adequate model, drawing on both wide- and narrow-focus empirical approaches, must answer. Most importantly: (1) how is the coordination of the different components of an emotional response achieved? And (2) do the various components – including emotional consciousness – play comparable or unequal roles in the process of cross-component coordination?

[Fig. 1. Componential framework for conceptualizing emotion. The five outer boxes depict component processes in emotion, similar to those identified in Scherer (2005a,b). The central box stands for possible central mechanisms (at cortical and/or subcortical levels) which may help to coordinate some or all of the components. Actions of the hypothetical central mechanisms are represented by solid lines, direct interactions between the five component processes by dashed lines.]

Different models of emotion, drawing on different views of the functional role(s) of consciousness, suggest different answers to these two critical questions. As an illustration, Fig. 2 shows how one model of conscious emotion, derived from a subset of the research reviewed here, would resolve these questions. In this model, a GW perspective on affective consciousness is assumed. That is, consciousness – affective and otherwise – is assumed to be linked to thalamocortical broadcasting of selected information for the flexible coordination of cognition and action. If consciousness is inherently linked to this coordination function, it will presumably be essential for some aspects of the coordination of component processes in human emotion. Returning to Fig. 1, this GW-inspired viewpoint would then suggest that the “coordinating mechanisms” are not neatly separable from the “consciousness” component. Rather, the consciousness component constitutes part of the coordinating mechanisms (though further unconscious mechanisms, specific to emotion, may also play a role in coordinating an emotional response). Fig. 2 shows how this neurofunctional model of conscious emotion unpacks and relates the “flat” uninterpreted relations in Fig. 1. In this way, the model offers one possible answer to the critical questions of how the emotion components relate to the coordinating process and to one another (consciousness, unlike the other components, is part of a posited central coordinating mechanism). It suggests, in turn, criteria for affective consciousness in the absence of subjective report (i.e. does the affective response reflect a level of integration and flexibility that requires the operation of the GW?).2

[Fig. 2. A possible neurofunctional interpretation of the componential framework. A GW model of conscious emotion is assumed for illustrative purposes. In this model, consciousness functions to globally integrate modular processors for the flexible control of cognition and action. On this view, consciousness is expected to play a central role in coordinating component processes, at least for those emotions which exhibit high levels of integration (i.e., responsiveness to a wide range of information inputs) and flexibility (i.e., adaptive sensitivity to a wide range of contexts). The model also allows for distinct unconscious coordinating mechanisms that may generate more stereotyped (aspects of) emotional responses.]

The model in Fig. 2 illustrates how a neurofunctional analysis of consciousness can flesh out the componential framework for emotion, implying conditions under which consciousness can(not) dissociate from the other emotion components, and hence providing principled criteria whereby consciousness can be inferred from observation of the other components. To be sure, the neurofunctional analysis of conscious emotion (a GW view) assumed in Fig. 2 is not the only available one, and it is not definitively established by the evidence reviewed here. Alternative (e.g., HOT) neurofunctional analyses may assign the consciousness component in Fig. 1 a more peripheral functional role, implying readier dissociability from other components, and hence requiring more stringent criteria for the identification of conscious feelings. At the other end of the spectrum, some views associate basic forms of consciousness (or sentience) with more elementary nervous system functions, implying that consciousness accompanies even component-responses with minimal complexity or coordination.

Nonetheless, the example illustrates the logic of leading approaches to the study of conscious emotion, highlighting both their promise and their limitations. On the one hand, developing theories of the NCAC suggest substantive interpretations of the componential framework, from which principled criteria for affective consciousness in nonverbal creatures can be derived. On the other hand, the search for NCACs itself remains closely bound up with longstanding controversies in the conceptualization of both consciousness and emotion. It is inseparable from fundamental questions, still not adequately resolved, about when, how, and why conscious experiences can be inferred from behavioural responses when subjective report is unavailable. The merging of a componential view of emotion with a neurofunctional analysis of consciousness thus opens up promising new paths toward a scientific understanding of animal affective consciousness, but also shines a sobering light on the obstacles that lie in their way.

The better-than-average effect in comparative self-evaluation: a comprehensive review and meta-analysis

Zell, E, J E, strickhourser, Sedikides, Constantine and Alicke, Mark D. (2019) The better-than-average effect in comparative self-evaluation: a comprehensive review and meta-analysis. Psychological Bulletin (In Press), Nov 18 2019. https://eprints.soton.ac.uk/id/eprint/435685

Abstract: The better-than-average-effect (BTAE) is the tendency for people to perceive their abilities, attributes, and personality traits as superior compared to their average peer. This article offers a comprehensive review of the BTAE and the first quantitative synthesis of the BTAE literature. We define the effect, differentiate it from related phenomena, and describe relevant methodological approaches, theories, and psychological mechanisms. Next, we present a comprehensive meta-analysis of BTAE studies, including data from 124 published articles, 291 independent samples, and over 950,000 participants. Results indicated that the BTAE is robust across studies (dz = 0.78, CI [0.71, 0.84]), with little evidence of publication bias. Further, moderation tests suggested that the BTAE is larger in the case of personality traits than abilities, positive as opposed to negative dimensions, and in studies that (1) use the direct rather than the indirect method, (2) involve many rather than few dimensions, (3) sample European-Americans rather than East-Asians (especially for individualistic traits), and (4) counterbalance self and average peer judgments. Finally, the BTAE is moderately associated with self-esteem (r = .34) and life satisfaction (r = .33). Discussion highlights theoretical and empirical implications.

The tax-financing of Medicare creates mounting economic costs & increasingly untenable policy constraints, which motivate reforms that shift towards a more basic public benefit that individuals can “top-up” with private spending

Does One Medicare Fit All? The Economics of Uniform Health Insurance Benefits. Mark Shepard, Katherine Baicker, Jonathan S. Skinner. Nov 2019. Forthcoming in Tax Policy and the Economy, Volume 34, Moffitt. 2019. https://www.nber.org/papers/w26472

There is increasing interest in expanding Medicare health insurance coverage in the U.S., but it is not clear whether the current program is the right foundation on which to build. Traditional Medicare covers a uniform set of benefits for all income groups and provides more generous access to providers and new treatments than public programs in other developed countries. We develop an economic framework to assess the efficiency and equity tradeoffs involved with reforming this generous, uniform structure. We argue that three major shifts make a uniform design less efficient today than when Medicare began in 1965. First, rising income inequality makes it more difficult to design a single plan that serves the needs of both higher- and lower-income people. Second, the dramatic expansion of expensive medical technology means that a generous program increasingly crowds out other public programs valued by the poor and middle class. Finally, as medical spending rises, the tax-financing of the system creates mounting economic costs and increasingly untenable policy constraints. These forces motivate reforms that shift towards a more basic public benefit that individuals can “top-up” with private spending. If combined with an increase in other progressive transfers, such a reform could improve efficiency and reduce public spending while benefiting low income populations.