McGill’s Healthy Brains for Healthy Lives Initiative: Integrating Social Context into Neuroscience Research
By Constance A. Cummings, FPR Project Director
In a recent collection of essays, anthropologist Gisli Palsson suggested we’re on the verge of a “post-disciplinary” era of academic collaboration (Palsson, 2015). Signs were very much in evidence at an inaugural workshop exploring ways to integrate social context in neuroscience research at McGill University on June 6–7, 2017. The workshop was sponsored by “Population Neuroscience and Brain Health,” one of the four core themes within McGill’s new Healthy Brains for Healthy Lives (HBHL) initiative, in collaboration with HBHL’s Social Science Subcommittee. HBHL “aims to leverage neuroinformatics and open science to advance our understanding and treatment of neurological and psychiatric disorders.” The program is unique among large-scale brain-based initiatives[1] in its interdisciplinary emphasis on individual variation/developmental trajectories and, more generally, understanding the brain in context by integrating genetic, epigenetic, neurophysiological, imaging, behavioral, environmental, clinical, and social data.
Moderated by McGill cultural psychiatrist Laurence Kirmayer, chair of the HBHL Social Science Subcommittee, the workshop brought together neuroscientists, social scientists, and health care professionals to share information – theories, tools, datasets, insights – that can help guide the direction of research themes related to the HBHL initiative over the next seven years.
This post summarizes Day One of the workshop, specifically three presentations from philosophy of psychiatric neuroscience (Ian Gold), cultural neuroscience (Shinobu Kitayama), and cultural psychiatry (Roberto Lewis-Fernández), which were followed by a panel that sought to bridge the various perspectives. Several insights emerged regarding how we theorize the brain, how our cultural differences emerge, and how we classify disorder across cultures when development goes awry.
Gold discussed drawbacks to neuroreductionism and the benefits of an overall theory or simulation of brain functioning that encompasses top-down and bottom-up perspectives. Kitayama described several lines of evidence from neuroimaging, neurophysiology, and genetics that relate differences in brain structure and functioning to broad cultural differences in concepts of selfhood, behavior, and practices. The talk also underscored the extent to which this work is rapidly evolving toward greater specificity. Regarding how these differences emerge during development, for example, Kitayama’s discussion of “plasticity alleles” (Belsky et al., 2009; Belsky & Pluess, 2013) suggested a mechanism whereby certain common genetic mutations within a population can amplify environmental influences “for better or worse.” Finally, Lewis-Fernández’s talk covered various, “partial solutions” to the current crisis in psychiatric nosology (DSM-5, RDoC, ICD-11). A main point was that classification systems depend on the “uses, purposes, histories, and constituencies for whom they are designed.” He ended with an appeal to “de-reify mental disorders across all uses.” For Lewis-Fernández, mental disorders are “confluences of dimensions and processes” that require a more interdisciplinary approach.
Neuroeducationism and Context in Neuroscience
The workshop opened with a talk by McGill philosopher Ian Gold. Gold began by describing a “strong” form of neuroreductionism in analytic philosophy and cognitive neuroscience popularized by Patricia Churchland, David Eagleman, and others. The strong form isolates the brain as an object of study. For example, according to Churchland’s seminal work on neurophilosophy, the brain (“that miraculous mound of excitable cells lodged in our skulls”) makes us “what we are” (Churchland, 1986, p. 10). A blurb for cognitive neuroscientist David Eagleman’s PBS series asserts that, “[b]y understanding the human brain, we can come close to understanding humanity” (The Brain with David Eagleman, PBS, 2015).
The Importance of Context
Gold provided some historical context for a corresponding rise in neurocentrism within psychiatry. He described how the effects of drugs such as chlorpromazine and lithium on schizophrenia and bipolar disorder altered psychiatry’s “narrative” (Berrios & Markova, 2015). The mid-century biological turn led to immense efforts to decontextualize mental disorders from lived experience, beginning with the publication of DSM-III in 1980 (Andreasen, 2007), and correlate them with biomarkers (Abi-Dargham & Horga, 2016; Woo, Chang, Lindquist, & Wager, 2017). Ultimately, this form of reductive “physicalism” (Parnas & Gallagher, 2015) assumes that mental disorders, the mind, even consciousness, will be solely explained by neuroscience.[2]
Reductionism takes various forms (Kirmayer & Gold, 2012). On the whole, it is intuitively appealing in its simplicity, but inadequate, Gold said. He made an analogy with earthquakes. Our explanation of earthquakes relies on an understanding of plate tectonics, not atomic physics. Just as our earthquake theory can’t be reduced to the behavior of electrons and retain explanatory adequacy or predictive power (it has to address “objects of a certain size and complexity”), so a theory of mind can’t be reduced to “the interactions of nerve cells” (Crick, 1994, p. 7).[3]
Theorizing the Brain in Context
The next part of Gold’s talk focused on what we can learn from a nonreductionistic way of understanding the brain. He described the work of computational neuroscientist David Marr (1982), who perceived visual perception as an information processing task. Marr’s framework involved three representational stages of increasing complexity, ending in a 3-D representation of objects in their environmental context, and three different levels of description: (1) computational, (2) algorithmic, and (3) implementation. The computational level addresses the question, “what is the problem [in the world] that the system is trying to solve”; the algorithmic and implementation levels can be considered the hardware and software. For our purposes, the point is that incorporating salient features of the environment in a dynamic way – which an informational processing approach attempts to do, either representationally (Marr) or almost wholly mechanistically (e.g., Piccinini, 2016) – is critical for achieving an adequate theory of how the brain functions in context.
But, in regard to process, it’s important to recognize the “tremendous diversity” within neuroscience, Michael Meaney, head of HBHL Population Neuroscience and Brain Health, pointed out in the course of the discussion. (Biologist Allan Tobin, another workshop participant and former head of UCLA’s Brain Research Institute, had similar concerns.) A minority, those with a background in psychology, might appreciate Marr’s top-down or computational approach, Meaney said. Some have even addressed multiscale problems like “emotion” and related philosophical perspectives in their work (LeDoux & Brown, 2017). But the majority of cell biologists and other basic neuroscientists interested in localized brain function don’t think like this, according to Meaney. They are solely focusing on the relationship between “the genetic blueprint and the elaboration of a specific cellular pattern.”
While Gold’s talk set the stage for the rest of the workshop by framing our understanding of “the brain” as physically, socially, and culturally “situated” in a context with which it dynamically interacts, the concerns expressed by Meaney and Tobin identified some conceptual issues any interdisciplinary collaboration with basic neuroscience must address.
Cultural Neuroscience: Culture, Gene, and the Brain (Shinobu Kitayama)
The next presentation, by cultural neuroscientist Shinobu Kitayama, focused on differences in brain structure and function related to culture. The first part of the talk covered behavioral and neural evidence for cultural differences. The second part discussed the influence of environment and plasticity alleles.
Kitayama’s seminal work with Hazel Markus argued for a fundamental psychological difference in individuals living in “Western” and “Eastern” cultures based on an “independent” vs. “interdependent” view of the self (Markus & Kitayama, 1991). The Western self is perceived as “bounded, unique . . . organized into a distinctive whole and set contrastively both against other such wholes and against a social and natural background (Geertz, 1975, p. 48). Easterners view the self as “embedded more deeply in social contexts [in which] relationships are more salient or primary than individual preferences,” Kitayama said.
Brain Plasticity
The cultural neuroscience research program grew from Markus and Kitayama’s core assumption of an independent or interdependent model of the self (and, relatedly, individualistic or collectivistic cultural contexts), coupled with evolving technologies for studying the brain that gave us a better understanding of brain plasticity as a function of experience. Over time, the program has incorporated various methods to examine how culture and biological processes interact and affect thought, feeling, and behavior. These methods include non-invasive measurement of the brain’s electrical activity (EEG), with special focus on event-related “potentials” (ERP) generated in response to a specific stimulus, whose exquisitely time-sensitive components (to the millisecond) are associated with distinct mental operations; functional neuroimaging (fMRI), which computationally identifies the location of brain activity on the basis of blood flow 4–6 seconds after presentation of a stimulus; the measurement of physiological (i.e., neuroendocrine and immune system) responses; and genetics. Research topics have ranged from visual perception, attention, emotion, and social explanation.
Kitayama briefly summarized various studies supporting the dichotomous model of selfhood. For example, several behavioral studies indicate a difference in visual perception and attention (e.g., the “framed-line task”) between European Americans and East Asians. In general, these differences are thought to underlie East Asians’ tendency to perceive the “full context” of a scene, that is, more holistically than Americans, who tend to zero in on specific objects and their attributes rather the contexts in which these objects appear (Kitayama, Duffy, Kawamura, & Larsen, 2003; Ishii, Tsukasaki, & Kitayama, 2011). A 2011 ERP study suggests that an “independent” (but not “interdependent”) self-construal mediates a “spontaneous” tendency, or “dispositional bias,” to “infer a personality trait from another person’s behavior” (Na & Kitayama, 2011), rather than ascribe behavior to situational constraints. An fMRI study suggests that East Asians and Americans differ on attentional control or effort when performing simple visuospatial tasks with different demands (some tasks required making relative/contextual judgments; and others absolute/context-independent judgments; Hedden, Ketay, Aron, Markus, & Gabrieli, 2008). For each group, the culturally non-preferred task (e.g., relative/contextual judgments for Americans) elicits above-threshold activation in prefrontal and parietal regions, both of which are implicated in cognitive control of attention and working memory.
Kitayama’s brief sampling gave the audience a good sense of “robust and systematic” cultural differences in functional aspects of brain with respect to social judgement, attention, emotion, self-evaluation, motivation, and so on, based on a methodologically rich and productive research program. The independent/interdependent model of self-construal has emerged as a reliable “signal.” But it’s important to note that the literature suggests there may be substantial individual differences on independence/interdependence within any given culture based on, for example, interaction with socioeconomic factors or migration and acculturation. The literature also suggests a significant ability among people living in multicultural environments to dynamically shift cultural values of individualism or collectivism in one direction or another in response to priming (see, e.g., Chiao, Harada, Komeda, et al. 2010), which could extend to life outside the laboratory setting.
Environment and Gene x Culture Interactions
In the second half of his talk, Kitayama shifted to how persistent cultural differences might arise via the environment or gene x culture interactions. He described a recent co-authored Science article on the relationship between farming patterns in China and individualistic or collectivistic tendencies (Talhelm et al., 2014). Wheat and rice farming emerged almost ten thousand years ago in northern and southern/eastern parts of China, respectively. Wheat is a resilient crop that could be grown in a variety of climatic zones. Rice farming, which arose in the south and east, is both extremely seasonal and a far more intensive process that requires complex irrigation systems and much higher levels of social coordination.
The Science authors found broad psychological differences among 1162 Han Chinese participants that aligned with a subsistence-type theory – that is, whether they lived in historically rice or wheat farming areas – but not with theories based on modernization or pathogen prevalence. The population-level study used several measures: style of thought (analytic or relational), implicit individualism and loyalty/nepotism. The authors also considered divorce rates and number of successful patents for new inventions as crude markers of individualism. Rice farming putatively created ecological pressure for more interdependency, holistic thinking, and loyalty/nepotism. More broadly, Kitayama suggested that environment – rice versus wheat farming – might at least in part explain the persistence of a variation in styles of thought between collectivistic/Eastern and individualistic/Western cultures.
Regarding gene x culture interactions, Kitayama described how variants of a well-studied gene implicated in reward sensitivity (DRD4) – the alleles modulate dopamine signaling efficiency – may play a role in an individual’s susceptibility to cultural influences, including social norms for ingroup cooperation. In particular, Kitayama discussed recent studies on self-centric motivation. An ERP study in which European American and Asian participants tried to earn points for oneself and a close, same-sex friend suggests that the self-centric preference (vs. a close other) is inhibited in Asians with an interdependent self-construal (Kitayama & Park, 2014). And separately, according to an unpublished whole-brain structural neuroimaging study, adult Japanese carriers of DRD4 variants (the 7- and 2-repeat alleles) exhibited thinner orbitofrontal cortices (OFC) than Japanese noncarriers and Westerners. The OFC is implicated in reward and other value-based behavior, and the suggestion is that the mutations amplify environmental effects. That is, Japanese carriers might be “more cognitively attuned to others and various social events in their surroundings while down-regulating their personal goals” (Kitayama et al., 2017).
Plasticity Alleles and Real-World Implications
Some workshop attendees seemed to feel that cultural neuroscience currently operates within a fairly narrow theoretical framework based on the independence/interdependence model of selfhood and the use of broad categorizations for different groups of people. But concepts such as “plasticity alleles” deeply resonated. And the implications seem to go well beyond identifying different styles of thought. For example, Michael Meaney mentioned a common allelic variant of the brain-derived neurotrophic factor (BDNF) gene (the Met allele of BDNF Val66Met polymorphism), which has been implicated in susceptibility to pain. Another workshop attendee, Laurette Dubé, cited a recent JAMA Pediatrics paper co-authored by Patricia Silveira, Michael Meaney, Dubé, and colleagues, which suggested that carriers of the 7-repeat allele of the DRD4 gene are not more likely to be obese, but rather more susceptible to local environmental conditions (e.g., limited food choices for girls in low SES neighborhoods; see Silveira et al., 2016). The cultural neuroscience piece, especially the structural brain changes Kitayama and colleagues have recently identified, fits in with the work at McGill by widening the lens to consider how evolutionary history as well as environmental context may be interacting with common allelic variations during development.
Culture and Context in Psychiatric Nosology (Roberto Lewis-Fernández)
Next, cultural psychiatrist Roberto Lewis-Fernández, who has been involved in both DSM-5 and still-ongoing ICD-11 revisions, discussed the uses and limits of descriptive nosologies. The main problem is that the classification systems, which are based on signs and symptoms, are “increasingly considered invalid.” He discussed the “solutions” offered by the DSM (American Psychiatric Association; APA), ICD (World Health Organization; WHO), and RDoC (National Institute of Mental Health; NIMH) and made suggestions for a more “integrative” psychiatry. He also referred attendees to the journal Psychological Science in the Public Interest, which reviews related issues.
The Crisis in Psychiatric Nosology
According to Lewis-Fernández, the “crisis” relates primarily to our lack in understanding the neural circuitry of mental disorders and their different manifestations across cultures (“the true or authentic ways in which people in particular settings express their distress”). The DSMs (starting with the operationalization of diagnostic criteria in DSM-III; APA, 1980) are to a certain extent a reliable, but not valid, means of classifying psychiatric illness for its multiple uses.
The problem is that the “signs and symptoms” of DSM psychiatric categories are somewhat arbitrarily arranged, according to Lewis-Fernández. Also, given the absence of well-understood etiologies, the signs and symptoms are reifying or “constitutive” in the sense that the criteria have come – through the manuals’ various uses – to “define the disorder” rather than provide “fallible indices” (Kendler, 2017), a Hacking-esque looping effect. To summarize, Lewis-Fernández said that “diagnoses do not represent discrete diseases.” They constitute “labels or more complex maps,” a focus on which “ignores the dimensional nature of psychopathology, obscures variations, minimizes pathogenic social structures, [and] hinders the discovery of illness mechanisms.” The result in limited therapeutic efficacy.ab
Lewis-Fernández reminded us that the ICD and DSM manuals evolved from the need to categorize various causes of death, which led to attempts to classify morbidity. By the time of ICD-8 (1967) and DSM-II (1968), efforts had “harmonized” in the sense of outlining a hierarchical progression from neurosis to psychosis. But the two systems diverged again when DSM-III aimed to increase reliability by operationalizing criteria and DSM-5 decreased emphasis on strict diagnostic hierarchies by recognizing significant comorbidities. Furthermore, as an instrument of the WHO (rather than an American professional association with a substantially different/economic appetite for volume sales, as Allan Tobin pointed out), the ICD serves broader interests and in general tends to incorporate more context. Lewis-Fernández also felt that the way it’s structured avoids a certain amount of “diagnostic creep” (medicalization of social predicaments) and the DSM’s “pseudo-precision.”
NIMH’s RDoC framework for research (2009– ) has been promoted as a long-term solution to the DSM’s lack of validity, with a primary focus on neural circuitry, from which the various psychiatric classifications could arise (and these may cluster quite differently). It identifies five broad domains of psychological functioning that cut across diagnostic categories: negative valence systems, positive valence systems, cognitive systems, social processes, and arousal and regulatory systems; and eight levels of analysis: genes, molecules, cells, circuits, physiology, behavior, self-report, and experimental paradigms. (This is vastly different from how a cultural psychologist would organize the levels of analysis, workshop attendee Andrew Ryder remarked. He would put “behavior” and “self-report” in the middle, and interpersonal relationships, governmental structures, and so forth, on the right.)
Under the then-leadership of Thomas Insel, a behavioral neuroscientist, the RDoC framework appears to represent a certain amount of what Lewis-Fernández described as “thinking inside the box,” which attempted to balance animal and human research interests (Kirmayer and Crafa considered it “impoverished and conceptually flawed”; see Kirmayer & Crafa, 2014). But a recent redesign now incorporates two “additional aspects” to its units of analysis: neurodevelopmental trajectories and interactions with “environment,” albeit narrowly conceptualized on the NIH web page as external stressors, such as “early child abuse.”
The problem with RDoC is the emphasis on neural circuitry and more broadly “discovery science” to understand “how the brain works,” according to Lewis-Fernández, although there was some debate between Michael Meaney and Laurence Kirmayer on the NIMH’s original intentions and motivations (e.g., the absence of “observable, objective predictive indices,” such as changes in an EKG in the context of chest pain (Kendler, 2017). Nonetheless, Lewis-Fernández felt the focus on neural circuitry runs the “high risk” of the kind of reductionism Ian Gold described earlier in the day, such that “every component or level of experience of human suffering could be reduced to brain function.”
In the final part of his talk, Lewis-Fernández described the problem of capturing multiple causes and interactions in any meaningful classification system. Both ICD and DSM have included limited information on biological etiology and DSM-5 has expanded its treatment of culture and gender. Critical issues include the classification of psychiatric disorders as dimensional or categorical (or both, on analogy with light as particle and wave) and the identification of “thresholds.” DSM-5, for example, no longer includes subtypes of schizophrenia and also established symptom domains (such as reality distortion) that cut across psychotic disorders, but it lists a prodromal “attenuated psychosis syndrome” as a “condition for further study.” The DSM, unlike the ICD also “backed away” from clinical significance criteria, such as level of distress or impairment.
A bulleted list in his last slide described future directions: “addressing both transdiagnostic and disorder-specific elements of psychopathology; fully integrating environment and development into RDoC; identifying the best dimensions and cutpoints; developing behavioral and biological measures for clinical use; overcoming implementation barriers; and de-reifying mental disorders across all uses.” According to Lewis-Fernández, we have moved from a “descriptive” psychiatry based on phenomenology to a more “mechanistic” psychiatry based on underlying neurobiology, but the hope is for a more integrative approach that incorporates both biology and environmental and sociocultural contexts.
Thinking Through Context in Neuroscience and Psychiatry (Panel – Ian Gold, Laurence Kirmayer, Shinobu Kitayama, Roberto Lewis-Fernández, Michael Meaney, Patrick McGivern, Allan Tobin)
The purpose of “Population Neuroscience and Brain Health” is to use different kinds of data to understand how the brain functions, which necessarily involves how it interacts with the social world. To advance the discussion, Kirmayer posed two questions to the panel: How can we conceptualize and measure social context? And how can we foster interdisciplinarity?
Levels of Explanation
Gold referred to the “situatedness” movement in cognitive science, which requires understanding mental life as a phenomenon that emerges from the dynamic interaction of brain, mind, body, and environment in a non-representational way (i.e., one that does not involve the need for structured mental representations, such as symbols). Gold felt that little of this framework (the embedded, enactive, extended mind) has been exploited in neuroscience. One suggestion for HBHL would be to think of “the situated brain” as a possible theme, particularly since McGill excels in research on the social environment. Gold also felt the hottest topics in the social and cultural neurosciences, in particular, “cry out for interdisciplinarity,” in such a way that that the social world is not merely taken as a given.
Philosopher of science Patrick McGivern thought that the problems described in psychiatry neuroscience are similar to the kinds of “multi-scale problems” that physics addresses. In this view, levels don’t necessarily align with different disciplines, and no level takes precedence over the others. Knowledge accrues from the different ways in which “explanations and models at different scales interact and support each other, as well as provide context for each other.” Referring to Gold’s example, “you could ask, why is it that tectonic plates are stable forms of matter, and to understand that you would need to look at quantum effects.” A possible question when addressing the “all-encompassing box” depicting environment in the RDoC framework becomes, “how might context appear in our research?”
According to Shinobu Kitayama, cultural neuroscience emerged from efforts to address similar questions. Ten years ago, researchers at Michigan began by positing a simplified scenario based on the identification of two broad cultural groups, but the field has evolved in its understanding of how context can be internalized at even non-cognitive levels of neural processing or expanded to include evolutionary history. Cues to environmental context can also be found at the level of biology. For example, biomarkers may track subjective experiences better than subjective reports (based on midlife studies in the US and Japan; MIDUS and MIDJA). Kitayama noted how certain traits, such as neuroticism or conscientiousness, can have positive or negative consequences for health, depending on culture.
Michael Meaney emphasized the HBHL’s unique emphasis on the individual brains and developmental trajectories, rather than assuming that there are normal and abnormal brains. Each brain “adapts to the early environment and performs and deals with the problems that emerge from the context in which development occurs.” Most of the genomics work does not take environment into account, and yet environment can have significant effects. For example, in certain contexts, IQ is highly heritable, in other, less advantageous contexts IQ heritability is severely limited. Environment has to be stratified. Further, the peak age of onset of most psychiatric disorders is around puberty, putting more emphasis on the need to understand how development goes awry, including in the early family environment or the in utero environment.
Roberto Lewis-Fernández discussed DSM-5’s inclusion of the Cultural Formulation Interview, which attempts “to get a sense of context, as well as a person’s interpretation of that context.” This is relevant for future research in psychiatry since many of the problem sets clinicians encounter are “fundamentally contextual” (Kirmayer). Lewis-Fernández and Kitayama’s approaches tell us two very different things, Kirmayer noted, which are based on how problems are articulated in context versus how the world is experienced at levels that may not be available for conscious reflection.
As the discussion wound down, Allan Tobin urged the group to look for ways to engage and challenge one another. In his experience, the drive toward inter-disciplinarity or multi-disciplinarity comes from what is fun for scientists and/or in response to external pressures from society to solve a problem. In either case, workshops can lead to the creation of networks composed of highly engaged researchers and people who have experienced the conditions that are being studied. This seems especially relevant. As Lewis-Fernández argued, it’s critical to address a person’s “context of meaning” in the case of mental illness in order to assist with their flourishing.
[1]E.g., the Human Brain Project (EU), the BRAIN Initiative (US).
[2] In philosophy, reduction of a higher level (a mental state such as depression) to a lower level (neurobiology), is achieved via “bridge laws” linking the two theories. The “levels” argument, attributed to philosopher Jerry Fodor, is as follows.
- The mind is nothing over and above the functioning brain.
- The science of the brain is neuroscience.
- So a theory of the mind must be a neuroscientific theory.
[3] The full quote is, “The scientific belief is that our minds – the behavior of our brains – can be explained by the interactions of nerve cells (and other cells and the molecules associated with them)” (Crick, 1994, p. 7).
REFERENCES
Abi-Dargham, A., & Horga, G. (2016). The search for imaging biomarkers in psychiatric disorders. Nature Medicine, 22, 1248–1255.
Andreasen, N. C. (2007). DSM and the death of phenomenology in America: An example of unintended consequences. Schizophrenia Bulletin, 33(1), 108–112. doi:http://dx.doi.org/10.1093/schbul/sbl054
Belsky, J., Jonassaint, C., Pluess, M., Stanton, M., Brummmett, B., & Williams, R. (2009). Vulnerability genes or plasticity genes. Molecular Psychiatry, 1–9.
Belsky, J., & Pluess, M. (2013). Beyond risk, resilience, and dysregulation: Phenotypic plasticity and human development. Developmental Psychopathology, 25, 1243–1261.
Berrios, G. E., & Markova, I. S. (2015). Toward a new epistemology of psychiatry. In L. J. Kirmayer, R. Lemelson, & C. A. Cummings (Eds.), Re-visioning psychiatry: Cultural phenomenology, critical neuroscience, and global mental health. New York, NY: Cambridge University Press.
Bombay, A. (2015). A call to end mental health disparaities for Indigenous people. Lancet Psychiatry, 2, 861–862. doi:http://dx.doi.org/10.1016/S2215-0366(15)00352-1
Boylan, J. M., Tsenkova, V. K., Miyamoto, Y., & Ryff, C. D. (2017). Psychological resources and glucoregulation in Japanse adults: Findings from MIDJA. Health Psychology, 36(5), 449–457.
Churchland, P. (1986). Neurophilosophy: Toward a unified science of the mind-brain. Cambridge, MA: MIT Press.
Crick, F. (1994). The astonishing hypothesis: The scientific search for the soul. New York, NY: Scribner.
Doucerain, M. M., Segalowitz, N., & Ryder, A. G. (2017). Acculturation measurement: From simple proxies to sophisticated toolkit. In S. Schwartz & J. Unger (Eds.), Oxford handbook of acculturation and health. Oxford, UK: Oxford University Press.
Hedden, T., Ketay, S., Aron, A., Markus, H. R., & Gabrieli, J. D. E. (2008). Cultural influences on neural substrates of attentional control. Psychological Science, 19(1), 12–17.
Kirmayer, L. J., & Gold, I. (2012). Critical neuroscience and the limits of reductionism. In S. Choudhury & J. Slaby (Eds.), Critical neuroscience: A handbook of the social and cultural contexts of neuroscience (pp. 307–330). Oxford, UK: Wiley-Blackwell.
Kitayama, S., & Park, J. (2014). Error-related brain activity reveals self-centric motivation: Culture matters. Journal of Experimental Psychology: General, 143(1), 62–70. doi:http://dx.doi.org/10.1037/a0031696
Kitayama, S., Yanagisawa, K., Ito, A., Ueda, R., Uchida, Y., & Abe, N. (2017). Reduced orbitofrontal cortical volume is associated with interdependent self-construal. PNAS, 114(30), 7969–7974. doi:10.1038/nrn.2016.56
Krieger, N. (2014). Discrimination and health inequities. International Journal of Health Services, 44(4), 643–710.
Kwan, M.-P. (Ed.) (2014). Geographies of health, disease, and well-being: Recent advances in theories and method. New York, NY: Routledge.
Lederbogen, F., & al., e. (2011). City living and urban upbringing affect neural social stress processing in humans. Nature, 474, 498–501. doi:10.1038/nature10190
LeDoux, J. E., & Brown, R. (2017). A higher-order theory of emotional consciousness. PNAS. doi:http://www.pnas.org/content/114/10/E2016.full.pdf
Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98, 224–253.
Na, J., & Kitayama, S. (2011). Spontaneous Trait Inference Is Culture-Specific: Behavioral and Neural Evidence. Psychological Science, 22(8), 1025–1032. doi:10.1177/0956797611414727
Palsson, G. (2015). Nature, culture, and society: Anthropological perspectives on life. London, UK: Cambridge University Press.
Parnas, J., & Gallagher, S. (2015). Phenomenology and the interpretation of pspychopathological experience. In L. J. Kirmayer, R. Lemelson, & C. A. Cummings (Eds.), Re-visioning psychiatry: Cultural phenomenology, critical neuroscience, and global mental health. New York, NY: Cambridge University Press.
Pedersen, C. B., & Mortensen, P. B. (2001). Evidence of a dose-response relationship between urbanicity during upbringing and schizophrenia risk. Archives of General Psychiatry, 58(11), 1039–1046.
Piccinini, G. (2016). Physical computation: A mechanistic account. New York, NY: Oxford University Press.
Sampson, L., Dasgupta, K., & Ross, N. A. (2014). The association between socio-demographic marginalization and plasma glucose levels at diagnosis of gestational diabetes. Diabetic Medicine. doi:{Kirmayer, forthcoming #39}
Talhelm, T., Zhang, X., Oishi, S., Shimin, C., Duan, D., Lan, X., & Kitayama, S. (2014). Large-scale psychological differences within China explained by rice versus wheat agriculture. Science, 344(6184), 603–608. doi:10.1126/science.1246850
Teicher, M. H., Samson, J. A., Anderson, C. M., & Ohashi, K. (2016). The effects of childhood maltreatment on brain structure, function and connectivity. Nature Reviews Neuroscience, 17, 652–666. doi:http://dx.doi.org/10.1038/nrn.2016.111
Vinkhuyzen, A. A. E., Eyles, D. W., Burne, T. H. J., Blanken, L. M. E., Kruithof, C. J., Verhulst, F., . . . McGrath, J. J. (2016). Gestational vitamin D deficiency and autism-related traits: The Generation R Study. Molecular Psychiatry.
Wasfi, R. A., Dasgupta, K., Orpana, H., & Ross, N. A. (2016). Neighborhood walkability and body mass index trajectories: Lognitudinal study of Canadians. American Journal of Public Health, 106(5), 934–940. doi:10.2105/AJPH.2016.303096
Woo, C.-W., Chang, L. J., Lindquist, M. A., & Wager, T. D. (2017). Building better biomarkers: Brain models in translational neuroimaging. Nature Neuroscience, 20(3), 365–377. doi:10.1038/nn.4478
