Вестник Челябинского государственного университета.
2018. № 3 (413). Экономические науки. Вып. 60. С. 124—132.
УДК 316
ББК 60.524
THE HUMAN BRAIN AND DEMOCRACY — LESSONS FROM SOCIAL NEUROSCIENCE IN A FAST-CHANGING WORLD
Gernot Ernst
Vestre Viken hospital trust and Psychological institute, University of Oslo, Oslo, Norway
In neuroscience, a broad spectrum of investigation methods are applied on all levels, beginning with molecular biological approaches in cells cultures, sophisticated animal experiments, different modern technical approaches, namely different imaging methods up to computational models. In the last decades, neuroscientific methods have been increasingly used to investigate social research questions, leading to a new subfield of neuroscience, coined "social neuroscience", and recently, political neuroscience was introduced. One application of social psychology and social neuroscience regards the question if there are psychological and neuroscientific correlates to the political distinction between left-wing and right-wing. Quite consistent evidence for personality differences between liberals and conservatives has been presented, and also, first evidence for structural differences between liberal and conservative brains. The social world is probably changing faster than ever before in the history of humanity. Although fundamental structures of human exploitation are principally the same, both biological and social factors with a potentially deep influence on the plastic brain have changed. In this article, a preliminary comprehensive and integrated model is introduced. It consists of five main brain modules involved in social cognition, and includes "biological" factors like sleep, movement, palatine food and (medical) drugs and social factors like media use, social safety and impulsivity. Media structures, social structures and habit changes may lead to a shift to right-wing opinions and anti-democratic attitudes. The described neurobiological effects might have significant influences on the individual level whether to support left- or right wing politics.
Keywords: social neuroscience, political neuroscience, social brain, social cognition, internet, social networks.
Introduction
The history of democracy is now longer than 2500 years when in Athens in the 6th century BC eventually democratic structures were established. The Athenian democracy is still the longest existing democratic system in history, surviving in a hostile environment about 500 years. The next steps towards more radical democratic systems happened first during the French revolution. Other attempts such as the Roman Republic were mostly timocracies where only the wealthy members of society were included. In other words, in most of the human history, the governmental form was not democratic. Beginning with Plato and Aristoteles, scholars have debated the foundations and conditions for democracies, and several theories have been established (Schmidt, 2000). It is not the intention of this article to discuss these theories further.
In nature, no species has developed a somehow democratic system. This sounds trivial — how could animals who lack, e.g. self-consciousness or social intelligence develop a complex political system. Besides that, issues of self-consciousness and social cognition are debated and several species probably have a limited self-consciousness, including ceph-alopods (Mather, 2008), dolphins, elephants and of course primates (Boly et al., 2013) or at least some forms of empathy (Frans B.M. De Waal, 2014;
F.B.M. de Waal & Preston, 2017) and social communication (Briefer, 2018). Several animal groups show highly organized cooperation (e.g., ants, bees, but also monkeys), but there is no clear evolutionary direction towards more sociality.
The brain is a central element in any social organization, an undisputed fact. From an evolutionary perspective, the brain is a demanding organ. It needs 20 % of the blood perfusion generated by cardiac output and up to 50 % of the body energy in specific situations. It seems convincing that an organ needing such a high amount of energy needs to have high survival advantages for the species. The main difference between rodents in general and higher primates — apes, monkeys, and the humans is based on a developed neocortex, mainly the prefrontal cortex. According to Passingham and Wise (Passingham & Wise, 2012), a leading reason for the development of the latter comes from new foraging methods. Primates made an evolutionary step forward by a better visual system and several new mechanisms to learn how to find and forage food, which gave them advantages to other animals. Several of these brain mechanisms are also involved in social interactions.
Although the evolution went on from monkeys to apes, at a time 30 to 23 million years ago, not many differences existed between them. First at the end of
this period, monkeys started to dominate the environment, especially the core and the more verdant areas of the trees (Turner, 2015). Several reasons have been proposed, such as monkeys were able to eat unripe fruits, in difference to apes (Turner, 2015). This contributed probably to the still existent social higher social organization of monkeys compared to apes. In fact, one of the closest relative to humans, the Orang Utan is rather a solitary animal. The larger apes, than, had to rely on the higher areas and were not able to organize and protect themselves in groups to the same extent. The rather narrow niche was probably involved in the increasing intelligence of apes. Acting more individually, the prefrontal cortex developed probably as a response to the challenge to decide between different salient goals (should I take the bigger fruit high above me, which is more dangerous to approach; or instead take the smaller fruit nearby?) (Passingham & Wise, 2012). They developed greater dexterity in arms and hands, again associated with increased connectivity in the inferior parietal lobe, where the parietal (haptic, touch), temporal (auditory) and occipital (visual) cortices form an association complex (Turner, 2015), a property lacking in monkeys. Comparative sociology between different species of monkeys and apes indicates that apes are less social as monkeys (but might still act socially under specific conditions, probably even in the form of "wars" in Chimpanzees). The only substantial ties in ape communities are between mothers and their off-springs, although some (weak) ties exist between siblings (Turner, 2015). Biological sociologists conducted cladistic analysis, based on the assumption, that those traits that all members of the related species process are likely to be the traits of the last common ancestor (A. Maryanski, 1992, 1994; A.R. Maryanski, 1987; Turner, 2015). A line of scientific arguments explains the sociality of humans because of increased subcortical structures associated with emotions. Usually, the difference between humans and apes is related to the increased prefrontal cortex, it turned out, however, that also the limbic structure of the brain are even corrected for weight much bigger compared to our nearest ancestors (Plut-chik, 1980; Turner, 2015).
The crucial question is — which parts of the human brain make us democratic or even socialist. Beyond the possibilities — are there also limitations indicated by the limited capability of the human brain? An even more crucial question is — how does our social and democratic brain behave in a fast-changing world.
This article aims to introduce social and political neuroscience regarding democratic and socialistic behavior. I will then briefly describe some principles
and structures of the brain involved in social cognition. Afterward, I will try to give some preliminary answers on the human possibilities and limitations in political attitude and behavior and finally discuss a framework of fast-changing social and biological conditions which might have significant consequences in our modern world.
Social Neuroscience and the social brain
Neuroscience is the science of the nervous system, including the brain. In neuroscience, a broad spectrum of investigation methods are applied on all levels, beginning with molecular biological approaches in cells cultures, sophisticated animal experiments, different modern technical approaches, namely different imaging methods up to computational models (Agarwal & Port, 2018; Glickstein, 2014; Kandel & Mack, 2013). The adult human brain is estimated to contain 86±8 billion neurons, with a roughly equal number (85 ± 10 billion) of non-neuronal cells (Azevedo et al., 2009). Each neuron has in average 100 connections mostly to other neurons, only 1 % of the connections in the brain are incoming or outgoing nerve fibers. This means that the brain is probably the most complex structure existing.
Fig. 1. The human brain in its anatomic location.
By Patrick J. Lynch, medical illustrator, licensed under theCreativeCommons Attribution2.5 License 2006
A crucial property of the brain is its plasticity. In stimutotdbrainereae^euronipradncencw comiect tions tAoOher neuvone nvoorivhOeeatliee sileel con-nections.Thisis in aacCmrasneaOle. Sprcifictrain-inn leadingromesse ronnertConrincrtAserlhoelly the volume of this part of the brain, which can be
demonstrated with structural imaging methods (Al-tenmuller & Furuya, 2016; Bezzola, Merillat, Gaser, & Jancke, 2011). On the other hand, not used brain regions are diminishing, and connections are reduced. These processes happen all the time, leading to a universal neuroscientific rule: use it or lose it (Kolb & Gibb, 2014). This is of particular importance in the social world where the use of cognition involves brain regions and changed activity either increases or decreases the volume, as demonstrated in taxi drivers having a much more prominent hippocampus, a brain region involved in orientation (Maguire et al., 2000).
In the last decades, neuroscientific methods have been increasingly used to investigate social research questions, leading to a new subfield of neuroscience, coined "social neuroscience" by Cacioppo (Cacioppo, 1994) and recently, political neuroscience was introduced (Jost, Nam, Amodio, & Van Bavel, 2014). The term social brain was introduced already earlier by Brothers (Brothers,l 990)andconsists of networks which are interconnected and work in cooperation.
1) The social perception network which serves ac-cnratt percep°on and mte^retation of cocia° tinnals,incSudiwg the perception of emotional changeo tn faces.tt consistsof thetusifarmf-rfs,sooerinrtemparalsulfur,andthelattral occipital cortex.
2t The emetion .rocetsingneftswrk inaolve9 in exw pewience, ewpressionr recognition, sn9 lasl not lwnsttocirlloarnigg . Itconsisls of tteamnwdpi ta, ventral ond orOital prefrontal cortex, insula, somatosensory cortices and other subcortical
structures like the striatum and the thalamus.
3) The self-regulation network, involved in processing internal emotional states and its effects on behavior. Key regions are the lateral prefrontal cortex (especially the dorsolateral part and the anterior cingulate cortex).
4) A network involved in mental state attribution, also called "Theory of Mind", which is involved in understanding and reasoning about one's mental state and the state of others. Involved in this is the superior temporal cortex, the temporoparietal junction, the medial prefrontal cortex, precuneus and the temporal poles (Frith & Frith, 2006; Hari, Henriks-son, Malinen, & Parkkonen, 2015; Kennedy & Adolphs, 2012; Stanley & Adolphs, 2013).
The case of the liberal (left-wing) and the conservative brain
One applicationofsocialpsychologi and social neuroscience regards the question if there are psychological and neuroscientific correlates to the political olistioction between teft-wmg an0 riglrt-wing. I will give in the following a short overview.
T heodor W Adomyaod nisinsfftutefor social re-tearcOwcconeotpPeeael iesiscieotlsPs interested in the psychology of conservatism. Under the im-prossionoffoacisa^tieey chnductcd eorly studies, ObyonO otOer lrodfhg to initieie an emigration process aircs1yinl032 whentheyconciudedthat the arising fascism inGoionaey was ineeiobleat this point. He famously coined the notion of the "authoritarian
Lateral view
«
/3)' . '
[ dIPFC ) u
LSMJ
Social Perception Emotion & Motivation Behavioral Adaptations Social Atribution
Fig. 2. Brain areas that participate in social processing. EBA: extra-striate body area, FFA: fusiform face area, FFA, AMY: amygdala, AI: anterior insula, ACC:anteriorcingulate cortex,OFC: orbitofrontalcortex, VS: ventralAtrirtum, HTHhopatroiomos (HOH),aiPFCt daroclctAralprefaootaloorCox, mPFC: medial prefrontal cortex, vPMC: ventral premotor cortex , STS: superior temporal sulcus (STS),
PCC: posterior cingulate cortex , PC: precuneus (PC), TPJ: temporoparietal junction (TPJ) (Biilnlœ APtoitio, HhlVC.OCrimageis licensed uodec tAe Creative CommoneAttributinn 3.0 Unported
personality" and constructed the F-scale meant to be capable of identifying personalities in danger to succumb to fascistic ideologies (Adorno, 1950/1995). At this time their approach was based on a progressive and comprehensive interpretation of Marxism and Freud's psychoanalytical approach.
Although both his scientific evidence has been questioned and his scientific approach has been criticized (Shils, 1954), since then social psychologists have been interested in the conservative personality. Adornos cooperator Frenkel-Brunswik coined the theory of ambiguity intolerance based on a psycho-dynamic approach. The F-scale was followed by the "C-scale" of Wilson and Patterson (Wilson & Patterson, 1968) combining nonpolitical items (ideas about horoscopes, Jazz music, etc.) and political items (e.g. death penalty, legalized abortion etc.). Altemeyer (Altemeyer, 1981) introduced his famous RWA-scale and shaped research in these areas more than two decades. More recently, Mondak used extensively modern personality research questionnaires (the Big Five) to describe properties of the conservative and left personality (Mondak, 2010; Mondak, Hibbing, Canache, Seligson, & Anderson, 2010) and Hibbing, beyond others studied associations between biological factors and political attitude and behavior (Hibbing, Smith, & Alford, 2013; Hibbing, Smith, Peterson, & Feher, 2014).
Social dominance theory states that human societies strive to minimize group conflict by developing belief systems justifying the hegemony of some groups over others (Sidanius & Pratto, 1999; Malle, Stallworth, Sidanius, & Pratto, 1994; Pratto, 1999). In this theory, legitimizing myths are used as devices to explain and to maintain the societal status quo such as 'paternalistic myths' (the need of groups to lead and take care of other groups not capable to do this), 'reciprocal myths' (idea of a symbiotic relationship between upper and lower class to the best of both groups) or 'sacred myths' (explaining differences by eternal laws, gods and so on). A scale has been developed [social dominance orientation, SDO (Malle et al., 1994)] which in reality might be composed of two subscales, the desire for group-based dominance and opposition to equality (Jost & Thompson, 2000).
Jost (Jost, Glaser, Kruglanski, & Sulloway, 2003) [2003] tries to integrate all these theoretical approaches. He argues that a "number of different epis-temic motives (dogmatism-intolerance of ambiguity; cognitive complexity; closed-mindedness; uncertainty avoidance; needs for order, structure, and closure), existential motives (self-esteem, terror management, fear, threat, anger, and pessimism), and ideological motives (self-interest, group dominance, and system justification) are all related to the expression of polit-
ical conservatism" [Jost 2003. P. 351]. However, all motives, he concludes, might origin in psychological attempts to manage uncertainty and fear.
In a recent review, Hibbing and colleagues summarize recent research findings. They mention the same circuits and phenomena, but the quoted studies differentiated between left wing and right wing attitudes and tried to find differences. One line of investigation is looking at personality traits and political orientation. Central findings are that individuals on the left are more likely to show empathy and openness to new experiences, to base their moral judgment on individualizing concerns like to harm avoidance and fairness and to support ideas like stimulation and autonomy. Those on the right report more often to value conscience and politeness, to prefer purity, authority and in-group/out-group distinctions and liking security, conformity and tradition (Hibbing et al., 2014).
Kanai and colleagues conducted a study where participants grouped themselves on a Likert Scale between "very liberal" to "very conservative" and were tested by structural MRI. The main result was an increased anterior cingulate cortex in left-wing participants and conservative participants an increased right amygdala. The authors themselves associated increased anterior cingula with increased tolerance to uncertainty because individuals with normal anterior cingulate have a lower capacity to tolerate uncertainty and conflicts. Conservative participants with a larger amygdala might be more sensitive to fears, and they might be more inclined to integrate conservative views in their belief system (Kanai, Feilden, Firth, & Rees, 2011). Consistent with the findings of structural differences by Kanai, significantly greater activation was observed in the right amygdala for Republicans and in the left posterior insula (near the temporal-parietal junction) in Democrats when making winning risky versus winning safe decisions (Schreiber et al., 2013).
Summarized, quite consistent evidence for statistical personality differences between liberals and conservatives has been presented, and, perhaps not surprisingly, first evidence for statistical differences between liberal and conservative brains. It is a collective, not an individual observation. You will find conservatives open to new experiences, but the majority is not as open as liberals. You will find fearful liberals, but the majority is not frightened as much as conservatives. We are not able to put an individual in an MR scanner and tell her afterward which political opinion she has. But we can probably put 50 members of a conservative and 50 members of a liberal party in the scanner and the blinded scientist will later be able to predict, which of the groups has a liberal or conservative attitude.
Mental abilities for democratic and socialist behavior
Any democratic and socialist behavior is based on fundamental human abilities. In political debates and struggles, we need to understand that also our opponents are humans using their form of logic (Lakoff, 2002). We need for this a sound mentalizing system (Van Overwalle & Baetens, 2009). We need to understand our and other's emotions (Bernhardt & Singer, 2012; Decety, 2012; Panksepp & Panksepp, 2013). We need an entire balance between rational reflection and emotional appreciation (Petty & Brinol, 2015). We need to cooperate and be able to maintain a balance between egoism and altruism (Herrmann, Thoni, & Gachter, 2008; Rand & Nowak, 2013; Rilling et al., 2002; Sakaiya et al., 2013).
A world in rapid change
The social world is probably changing faster than ever before in the history of humanity. Although fundamental structures of human exploitation are principally the same, both biological and social factors with a potentially deep influence on the plastic brain have changed. A brief review of some factors makes this point clearer. The duration of sleep is alarmingly decreasing in the Western world. Within 20 years the mean sleep duration decreased from about 8 hours to 6.5 hours. The Center for Disease Control in Atlanta, usually more focused on epidemics like Ebola is worried about a sleep deprivation epidemic. Sleep duration is not trivial. It has been associated with severe cardiac diseases, diabetes, but also profound changes in decreased executive function, memory disturbances and attention problems [Regestein 2004, Sternberg 2013, Krieg 2001]. Many individuals train and use their body less. People who do not engage in physical activity are two times more likely to exhibit symptoms of depression and anxiety compared with those who regularly practice physical activity and a higher prevalence of symptoms for anxiety (9.8 %) and depression (10.9 %) was observed among those claiming to not practice regular physical activity (De Mello et al., 2013). Obesity is increasing significantly both in industrialized and non-industrialized countries (Saklayen, 2018). This epidemy is not appearing by chance. Evidence from Germany, Finland, and the United Kingdom shows a link between financial distress and obesity. Regardless of their income or wealth, people who experience periods of financial hardship are at increased risk of obesity, and the increase is higher for more severe and recurrent hardship (Conklin et al., 2013; Laaksonen, Sarlio-Lahteenkorva, & Lahelma, 2004; Munster, Ru-ger, Ochsmann, Letzel, & Toschke, 2009). Obesity is associated with an underactive prefrontal cortex
(Volkow et al., 2009) which again has consequences for social behavior and development of addiction (Moorman, 2018). Misuse of sedative drugs is increasing (Williams, 2017), having probably profound effects on social behavior (Perkins et al., 2013). The same regards the misuse of opioids in the US (Olsen, 2016), while we learn increasingly about the effects of opioids on social cognition (Loseth, Ellingsen, & Leknes, 2014). Adolescents use several hours a day smartphones, which has caused beyond others lower self-esteem, a dramatic change (Twenge, Martin, & Campbell, 2018). Use of social media is associated with increased loneliness (Burke, Marlow, & Lento, 2010), loneliness leads to increased use of social media (Clayton, Osborne, Miller, & Oberle, 2013).
Putting together the mentioned and other factors my research aims to develop a comprehensive and integrated model which I present here. It consists of five main brain modules mentioned before: the amygdala, mentalizing, empathy and action/perception networks together with modules involved in rational processing, all essential for the social and political brain. On the right side "biological" factors like sleep, movement, palatine food and (medical) drugs are included. On the right side social factors like media use (internet, television, and reading), social meeting places, (perceived) social safety and impul-sivity are introduced. Arrows show associations and probable causes. For each of the arrows, evidence (at least in a certain degree) has been presented. Several vicious circles can be identified, both within patterns with not surprising interactions like sleep-food-obesity-movement, but also more far-reaching and somehow not as natural interactions (like movement, anxiety and the use of antidepressive drugs and drug use in adolescence and impulsiveness). Changes in the brain have effects on attitude and behavior again, beginning with sleep, food intake, and movement, but also in changed and increased consumption of media and social behavior.
Consequences and conclusions
When we recall probable psychological and neu-robiological differences between liberals and conservatives, media structures, social structures and habit changes may lead to a shift to right-wing opinions and anti-democratic attitudes. In particular, scaring information, pictures, fast-changing social structures activate amygdala-circuits, classically associated with right-wing thinking. At the same time overstimulation turns down anterior cingulate structures classically associated with left-wing thinking. These effects might explain partially recent political developments. In a world where rich people are becoming more prosperous, poverty increases and social safety
Fig. 3. A simplified model of effects and interaction of differentsocialandbiological factorsonthesocialbrain
is challenged a rational choice might be to support scribed neurobiological effects might have significant left-wing movements going for increased social se- influences on the individual level whether to support curity and equality, but the opposite happens. The de- left- or rightwingpolitics.
Information about the author
Gernot Ernst — MD, Associate Professor. Vestre Viken hospital trust and Psychological institute, University of Oslo, Oslo, Norway.
Bulletin of Chelyabinsk State University.
2018. No. 3 (413). Economic Sciences. Iss. 60. Рp. 124—132.
References
1. Adorno T.W. (1950/1995). Studien zum autoritären Charakter. Frankfurt a.M.: Suhrkamp Verlag.
2. Agarwal N., Port J.D. (2018). Neuroimaging: Anatomy Meets Function Neuroimaging.
3. Altemeyer B. (1981). Right-wing authoritarianism. Winnipeg: University of Manitoba Press.
4. Altenmuller E., Furuya S. (2016). Brain Plasticity and the Concept of Metaplasticity in Skilled Musicians. Adv Exp Med Biol, 957, 197—208. doi: 10.1007/978-3-319-47313-0_11.
5. Azevedo F.A., Carvalho L.R., Grinberg L.T., Farfel J.M., Ferretti R.E., Leite R.E., Herculano-Houzel S. (2009). Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J Comp Neurol, 513 (5), 532—541. doi:10.1002/cne.21974.
6. Bernhardt B.C., Singer T. (2012). The neural basis of empathy. Annu Rev Neurosci, 35, 1—23. doi:10.1146/annurev-neuro-062111-150536.
7. Bezzola L., Merillat S., Gaser C., Jancke L. (2011). Training-induced neural plasticity in golf novices. J Neurosci, 31 (35), 12444—12448. doi:10.1523/jneurosci.1996-11.2011.
8. Billeke P. & Aboitiz F. (2013). Social cognition in schizophrenia: from social stimuli processing to social engagement. Front Psychiatry, 4, 4. doi:10.3389/fpsyt.2013.00004.
9. Boly M., Seth A.K., Wilke M., Ingmundson P., Baars B., Laureys S. Tsuchiya N. (2013). Consciousness in humans and non-human animals: recent advances and future directions. Front Psychol, 4, 625. doi:10.3389/ fpsyg.2013.00625.
10. Briefer E.F. (2018). Vocal contagion of emotions in non-human animals. Proc Biol Sci, 285 (1873). doi:10.1098/rspb.2017.2783.
11. Brothers L. (1990). The social brain: a project for integrating primate behavior and neurophysiology in a new domain. Concepts in Neuroscience, 1, 27—51.
12. Burke M., Marlow C., Lento T. (2010). Social network activity and social well-being (pp. 1909—1912).
13. Cacioppo J.T. (1994). Social neuroscience: autonomic, neuroendocrine, and immune responses to stress. Psychophysiology, 31 (2), 113—128.
14. Clayton R.B., Osborne R.E., Miller B.K., Oberle C.D. (2013). Loneliness, anxiousness, and substance use as predictors of Facebook use. Computers in Human Behavior, 29 (3), 687—693. doi: 10.1016/j. chb.2012.12.002.
15. Conklin A.I., Forouhi N.G., Suhrcke M., Surtees P., Wareham N.J., Monsivais P. (2013). Socioeconomic status, financial hardship and measured obesity in older adults: a cross-sectional study of the EPIC-Norfolk cohort. BMC Public Health, 13, 1039. doi:10.1186/1471-2458-13-1039.
16. De Mello M.T., Lemos Vde.A., Antunes H.K., Bittencourt L., Santos-Silva R., Tufik S. (2013). Relationship between physical activity and depression and anxiety symptoms: a population study. J Affect Disord, 149 (1-3), 241—246. doi:10.1016/j.jad.2013.01.035.
17. De Waal F.B.M. (2014). Empathy in Primates and Other Mammals. In J. Decety (ed.). Empathy. From Bench to Bedisde (pp. 87—106). Cambridge, Massachusetts: MIT Press.
18. de Waal F.B.M., Preston S.D. (2017). Mammalian empathy: behavioural manifestations and neural basis. Nat Rev Neurosci, 18 (8), 498—509. doi:10.1038/nrn.2017.72.
19. Decety J. (2012). Empathy: from bench to bedside. Cambridge Mass: MIT Press.
20. Frith C D., Frith U. (2006). The neural basis of mentalizing. Neuron, 50 (4), 531—534. doi:10.1016/j. neuron.2006.05.001.
21. Glickstein M. (2014). Neuroscience: a historical introduction. Cambridge, Mass: MIT Press.
22. Hari R., Henriksson L., Malinen S., Parkkonen L. (2015). Centrality of Social Interaction in Human Brain Function. Neuron, 88 (1), 181—193. doi:10.1016/j.neuron.2015.09.022.
23. Herrmann, B., Thoni C., Gachter S. (2008). Antisocial punishment across societies. Science, 319 (5868), 1362—1367. doi: 10.1126/science.1153808.
24. Hibbing J.R., Smith K.B., Alford J.R. (2013). Predisposed. Liberals, conservatives and the biology of political differences: Roudtledge.
25. Hibbing J.R., Smith K.B., Peterson J.C., Feher B. (2014). The deeper sources of political conflict: evidence from the psychological, cognitive, and neuro-sciences. Trends Cogn Sci, 18 (3), 111—113. doi:10.1016/j. tics.2013.12.010.
26. Jost J.T., Glaser J., Kruglanski A.W., Sulloway F.J. (2003). Political conservatism as motivated social cognition. Psychological Bulletin, 129 (3), 339—375. doi:10.1037/0033-2909.129.3.339.
27. Jost J.T., Nam H.H., Amodio D.M., Van Bavel J.J. (2014). Political Neuroscience: The Beginning of a Beautiful Friendship. Political Psychology, 35, 3—42. doi:10.1111/pops.12162.
28. Jost J.T., Thompson E.P. (2000). Group-Based Dominance and Opposition to Equality as Independent Predictors of Self-Esteem, Ethnocentrism, and Social Policy Attitudes among African Americans and European Americans. Journal of Experimental Social Psychology, 36 (3), 209—232. doi:10.1006/jesp.1999.1403.
29. Kanai R., Feilden T., Firth C., Rees G. (2011). Political orientations are correlated with brain structure in young adults. Curr Biol, 21 (8), 677—680. doi:10.1016/j.cub.2011.03.017.
30. Kandel E.R., Mack S. (2013). Principles of neural science (5th ed.). New York: McGraw-Hill Medical.
31. Kennedy D.P., Adolphs R. (2012). The social brain in psychiatric and neurological disorders. Trends Cogn Sci, 16 (11), 559—572. doi:10.1016/j.tics.2012.09.006.
32. Kolb B., Gibb R. (2014). Searching for the principles of brain plasticity and behavior. Cortex, 58, 251—260. doi:10.1016/j.cortex.2013.11.012.
33. Laaksonen M., Sarlio-Lahteenkorva S., Lahelma E. (2004). Multiple dimensions of socioeconomic position and obesity among employees: The Helsinki Health Study. Obes Res, 12 (11), 1851—1858. doi:10.1038/ oby.2004.230.
34. Lakoff G. (2002). Moral politics: how liberals and conservatives think (2nd ed.). Chicago: University of Chicago Press.
35. Loseth G.E., Ellingsen D.M., Leknes S. (2014). State-dependent mu-opioid modulation of social motivation. Front Behav Neurosci, 8, 430. doi:10.3389/fnbeh.2014.00430.
36. Maguire E.A., Gadian D.G., Johnsrude I.S., Good C.D., Ashburner J., Frackowiak R.S., Frith C.D. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proc Natl Acad Sci USA, 97 (8), 4398—4403. doi:10.1073/pnas.070039597.
37. Malle B.F., Stallworth L.M., Sidanius J., Pratto F. (1994). Social Dominance Orientation: A Personality Variable Predicting Social and Political Attitudes (vol. 67).
38. Maryanski A. (1992). The last ancestor: an ecology-network model on the origins of human sociality. Advances in Human Ecology, 2, 1—32.
39. Maryanski A. (1994). The Pursuit of Human Nature in Sociobiology and Evolutionary Sociology. Sociological Perspectives, 37 (3), 375—389. doi:10.2307/1389502.
40. Maryanski A.R. (1987). African ape social structure: Is there strength in weak ties? Social Networks, 9 (3), 191—215. doi: 10.1016/0378-8733 (87)90020-7.
41. Mather J.A. (2008). Cephalopod consciousness: behavioural evidence. Conscious Cogn, 17 (1), 37—48. doi:10.1016/j.concog.2006.11.006.
42. Mondak J.J. (2010). Personality and the Foundations of Political Behavior. Cambridge: Cambridge University Press.
43. Mondak J.J., Hibbing M.V., Canache D., Seligson M.A., Anderson M.R. (2010). Personality and Civic Engagement: An Integrative Framework for the Study of Trait Effects on Political Behavior. American Political Science Review, 104 (01), 85—110. doi: 10.1017/s0003055409990359.
44. Moorman D.E. (2018). The role of the orbitofrontal cortex in alcohol use, abuse, and dependence. Prog Neuropsychopharmacol Biol Psychiatry. doi:10.1016/j.pnpbp.2018.01.010.
45. Munster E., Ruger H., Ochsmann E., Letzel S., Toschke A.M. (2009). Over-indebtedness as a marker of socioeconomic status and its association with obesity: a cross-sectional study. BMC Public Health, 9, 286. doi:10.1186/1471-2458-9-286.
46. Olsen Y. (2016). The CDC Guideline on Opioid Prescribing: Rising to the Challenge. JAMA, 315 (15), 1577—1579. doi: 10.1001/jama.2016.1910
47. Panksepp J., Panksepp J.B. (2013). Toward a cross-species understanding of empathy. Trends Neurosci, 36 (8), 489—496. doi: 10.1016/j.tins.2013.04.009.
48. Passingham R.E., Wise S.P. (2012). The Neurobiology of the prefrontal cortex : anatomy, evolution, and the origin of insight. Oxford: Oxford university press.
49. Perkins A.M., Leonard A.M., Weaver K., Dalton J.A., Mehta M.A., Kumari V., Gauthier I. (2013). A Dose of Ruthlessness: Interpersonal Moral Judgment Is Hardened by the Anti-Anxiety Drug Lorazepam. Journal of Experimental Psychology: General, 142 (3), 612—620. doi:10.1037/a0030256.
50. Petty R.E., Brinol P. (2015). Emotion and persuasion: cognitive and meta-cognitive processes impact attitudes. Cogn Emot, 29 (1), 1—26. doi:10.1080/02699931.2014.967183.
51. Plutchik R. (1980). Emotion: a psychoevolutionary synthesis. New York: Harper & Row.
52. Pratto F. (1999). The Puzzle of Continuing Group Inequality: Piecing Together Psychological, Social, and Cultural Forces in Social Dominance Theory. Advances in Experimental Social Psychology, 31 (C), 191—263. doi: 10.1016/S0065-2601 (08)60274-9.
53. Rand D.G., Nowak M.A. (2013). Human cooperation. Trends Cogn Sci, 17 (8), 413—425. doi:10.1016/j. tics.2013.06.003.
54. Rilling J., Gutman D., Zeh T., Pagnoni G., Berns G., Kilts C. (2002). A neural basis for social cooperation. Neuron, 35 (2), 395—405.
55. Sakaiya S., Shiraito Y., Kato J., Ide H., Okada K., Takano K., Kansaku K. (2013). Neural correlate of human reciprocity in social interactions. Front Neurosci, 7, 239. doi:10.3389/fnins.2013.00239.
56. Saklayen M.G. (2018). The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep, 20 (2), 12. doi: 10.1007/s11906-018-0812-z.
57. Schmidt M.G. (2000). Demokratietheorien : eine Einführung (3., überarb. und erw. Aufl. ed. Vol. 1887). Opladen: Leske + Budrich.
58. Schreiber, D., Fonzo, G., Simmons, A. N., Dawes, C. T., Flagan, T., Fowler J.H., Paulus M.P. (2013). Red brain, blue brain: evaluative processes differ in Democrats and Republicans. PLoS One, 8 (2), e52970. doi:10.1371/journal.pone.0052970.
59. Shils E.A. (1954). Authoritarianism: "Right" and "left." In R. Christie & M. Jahoda (eds.), Studies in the scope and method of The authoritarian personality (pp. 24—49). Glencoe, Ill: Free Press.
60. Sidanius J., Pratto F. (1999). Social dominance : an intergroup theory of social hierarchy and oppression. Cambridge: Cambridge University Press.
61. Stanley D.A., Adolphs R. (2013). Toward a neural basis for social behavior. Neuron, 80 (3), 816—826. doi:10.1016/j.neuron.2013.10.038.
62. Turner J.H. (2015). The Neurology of Human Nature: Implications for the Sociological Analysis of Health and Well-Being. In R.K. Schutt, L.J. Seidman, M.S. Keshavan (eds.), Social Neuroscienc (pp. 41—87). Cambridge: Harvard University Press.
63. Twenge J.M., Martin G.N., Campbell W.K. (2018). Decreases in Psychological Well-Being Among American Adolescents After 2012 and Links to Screen Time During the Rise of Smartphone Technology. Emotion. doi: 10.1037/emo0000403.
64. Van Overwalle F., Baetens K. (2009). Understanding others' actions and goals by mirror and mental-izing systems: a meta-analysis. Neuroimage, 48 (3), 564—584. doi:10.1016/j.neuroimage.2009.06.009.
65. Volkow N.D., Wang G.J., Telang F., Fowler J.S., Goldstein R.Z., Alia-Klein N., Pradhan K. (2009). Inverse association between BMI and prefrontal metabolic activity in healthy adults. Obesity (Silver Spring), 17 (1), 60—65. doi: 10.1038/oby.2008.469.
66. Williams A. (2017). Prozac Nation Is Now the United States of Xanax. Style.
67. Wilson G.D., Patterson J.R. (1968). A new measure of conservatism. Br J Soc Clin Psychol, 7 (4), 264—269.