Neuroessentialism: Theoretical and Clinical Considerations

Reductionism in Psychiatry

The reductionist view in psychiatry is not new. Emil Kraepelin argued for some version of it at the beginning of the 20th century (Bentall, 2006). For instance, Kraepelin argued that many psychological disorders, such as schizophrenia, “are best understood as biological diseases” (Bentall, 2006, p. 222) and that psychological disorders “are the result of heredity, chemical imbalances, and metabolic irregularities” (Zachar, 2000, p. 33). Many psychiatrists have followed his lead (Müller, Fletcher, & Steinberg, 2006). Yet Kraepelin’s influence and esteem varied over the 20th century, during which alternative psychological and social explanations of psychological disorders were suggested (Ghaemi, 2013). However, the rise of neuroscience, especially new brain imaging techniques, has put reductive conceptualizations of psychological disorders back in the spotlight. Gruen (1998) argued, “Brain structures, genes, and neurotransmitters have been seen as directly determining depression . . . [u]nderstanding neural circuity is being equated with understanding the experience of fear and depression” (p. 85). Gold and Stoljar (1999) elaborated on this sort of conceptualization:

Many scientists and philosophers adhere to the metaphysical view sometimes known as materialism. Roughly, materialism holds that psychological events, states, and processes are nothing more than events, states, and processes of the brain. Given these two views, and treating neuroscience by definition as the science of the brain, it seems inevitable that the neuron doctrine is true: if the mind is the brain, and if neuroscience is the science of the brain, then it is practically a fact of logic that neuroscience is the science of the mind, and that it alone will explain what can be explained about the mind. (p. 810)

Over the past two decades, commitments to reductionism contributed to a significant increase in brain disease conceptualization of psychological disorders in neuroscientific and psychiatric research (Choudhury & Slaby, 2011). This significant increase has contributed to neuroscience’s status of “poster child” for medical sciences (Racine, 2015). In the same way that behaviorism attempted to ground psychology in the methodology of the natural sciences, neuroessentialistic viewpoints attempt to ground psychological experience and disorders in the methodology of neuroscience.

Yet, despite widespread neuroessentialistic conceptualization of psychological disorders, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) preserved a place for the psychological in psychological disorders. In the DSM-5, symptoms and client self-reports are still primary in diagnosis. The reason for this is that, according to the DSM-5, “there are no laboratory tests, x-rays, or other biological markers for any mental disorder’ there is no physiological specificity to any mental disorder’ there is no genetic specificity to any mental disorder” (Ross, 2013, p. 195). However, in an attempt to identify biomarkers of psychological disorders, the National Institute of Mental Health recently launched the Research Domain Criteria (RDoC). The justification for the RDoC is that the DSM-5 needs to be replaced with a new research program and classification scheme that provides better opportunities for identifying biomarkers. According to the former director of the National Institute of Mental Health, the focus on biomarkers is needed because

unlike our definitions of ischemic heart disease, lymphoma, or AIDS, the DSM diagnoses are based on a consensus about clusters of clinical symptoms, not any objective laboratory measure. In the rest of medicine, this would be equivalent to creating diagnostic systems based on the nature of chest pain or the quality of fever. Indeed, symptom-based diagnosis, once common in other areas of medicine, has been largely replaced in the past half century as we have understood that symptoms alone rarely indicate the best choice of treatment. (Insel, 2013, para. 2)

Proponents of the RDoC argue that symptoms may be clinically useful but relying on them alone is “primitive” medicine (Insel, 2014, p. 397). Instead, the RDoC conceptualizes psychological disorders as

(1) mental disorders are presumed to be disorders of brain circuits. (2) Tools of neuroscience, including neuroimaging . . . can be used to identify dysfunctions of neural circuits. (3) Data from genetics research and clinical neuroscience will yield biosignatures that will augment . . . clinical intervention. (Walter, 2013, p. 4)

Insel (2013) claimed, “RDoC is nothing less than a plan to transform clinical practice by bringing a new generation of research to inform how we diagnose and treat mental disorders” (para. 7). The RDoC has accepted as its working hypothesis that the cause of psychological disorders are disordered brain circuits and the proper approach to diagnosis and treatment is to identify what those circuits are and how to modify them for the best treatment outcomes. In other words, proponents of the RDoC claim that “all mental processes take place in brain tissue, therefore mental disorders must be brain disorders” (Wakefield, 2014, p. 39).

Stigma

A neuroessentialistic approach to psychological disorders is also motivated by the desire to reduce stigma (Corrigan et al., 2000). There is widespread stigma associated with psychological disorders, and this stigma is likely responsible for many negative consequences, such as increased distress and individuals failing to seek treatment for psychological challenges (Bharadwaj, Pai, & Suziedelyte, 2015).

An important component of stigma attached to psychological disorders is related to the attributions attached to psychological disorders. Attributions refer to the etiology and meanings associated with psychological disorders. For example, Corrigan (2000) explained, “Moral models yield attributions that mental illness is onset controllable and persons with mental illness are to blame for their symptoms. Biological models are more consistent with attributions that mental illness is uncontrollable at onset” (p. 53). It follows that one of the appealing features of a neuroessentialistic model of psychological disorders is that it might diminish the blame an individual with a psychological disorder may attribute to himself or herself as well as potentially diminishing the blame others may apply to him or her (Haslam, 2011). The biological approach is hypothesized to accomplish this by positing that the individual is not responsible for the development of his or her psychological disorder. Instead, his or her biology is responsible (Corrigan et al., 2000).

This approach to psychological disorders is prominent. For example, Michelle Obama (2015) recently stated,

When it comes to mental health conditions, we often treat them differently from other diseases like cancer, diabetes or asthma. And that makes no sense. Whether an illness affects your heart, your leg or your brain, it’s still an illness, and there should be no distinction. . . . So there should be absolutely no stigma around mental health. None. Zero.

The First Lady’s remarks suggest that she believes that once the public understands that psychological disorders are not the result of a “lack of moral backbone” or being “weak willed” but are brain diseases that are outside of an individual’s control, the public will be more understanding and less accusatory (Corrigan & Watson, 2004).

The importance of the disease model in combatting stigma is likely most prominent in addiction treatment. An article by Leshner (1997) titled “Addiction Is a Brain Disease, and It Matters” was deeply influential in academic and treatment circles and the perspective that addiction is a chronic brain disease “is now the dominant view of addiction in the field” despite the powerful philosophic, neuroscientific, psychosocial, and epidemiological objections to this perspective (Satel & Lilienfeld, 2013, p. 50; see also Graham, 2013; Heyman, 2009; Levy, 2013).

Many would welcome a reduction in the stigma surrounding psychological disorders. However, a substantial body of research has contradicted the belief that explaining psychological disorders as biological diseases reduces stigma (Kvaale, Haslam, & Gottdiener, 2013; Schomerus, Matschinger, & Angermeyer, 2014; Speerforck, Schomerus, Pruess, & Angermeyer, 2014). For example, Speerforck et al. (2014) conducted a survey that included 3,642 participants. This study found that attributing depression to both a “chemical imbalance of the brain” and to a “brain disease” was significantly correlated with increased stigmatizing attitudes (p. 226). This is a puzzling finding in light of the attribution theory discussed above. That is, if it is the case that depression is caused by a chemical imbalance or a brain disease, then the hypothesis posited in Corrigan (2000) and implied in Michelle Obama (2015) appears to be contradicted. That hypothesis was that a biological model of psychological disorder would diminish blame, which, in turn, would diminish stigma.

Schomerus et al. (2014), which also found an increase in stigmatizing attitudes toward depressed individuals whose depression was attributed to a biological cause, suggested that the increase in stigma is a result of stigma encompassing more than attributions of responsibility and blame. Meaning, the lack of responsibility an individual might have for his or her psychological disorder when explained from a biological perspective can be “outweighed by the adverse effects mediated by perceived differentness and dangerousness, respectively” (p. 311).

Importantly, an increase in stigmatizing attitudes based on biological explanations of psychological disorders is not uniform. Biological explanations that emphasize, for example, a “brain disease” cause of psychological disorders such as alcohol abuse have been found to be associated with less stigmatizing attitudes (Speerforck et al., 2014, p. 226). Nevertheless, whether or not psychological disorders are best understood in neuroessentialistic terms, the belief that neuroessentialistic conceptualizations will reduce stigma for many psychological disorders is at odds with a substantial body of evidence.

Market for Medicine

Pharmaceutical drug use for a variety of psychological disorders has sharply increased over the past several decades (Whitaker, 2011). To illustrate this rise, consider the rising use of antidepressants. According to estimates from Pincus et al. (1998), from 1985 to 1994, the “proportion of psychiatric visits for depression that included a prescription of a psychopharmacological agent increased from 53.5% to 70.9%” (p. 528). A similar increasing trend in the use of antidepressants was discussed in Olfson and Marcus (2009), which identified that

between 1996 and 2005, the overall annual rate of antidepressant treatment among persons 6 years and older increased from 5.84 to 10.12 per 100 persons. This corresponds to a national increase from 13.3 million persons in 1996 to 27 million persons in 2005. (p. 850)

Antidepressant medications approved by the Food and Drug Administration are “blockbuster drugs,” with about 10% of Americans over the age of 12 taking at least one (Kirsch, 2010; Pratt, Brody, & Gu, 2011). Among women, the prevalence is higher. For example, almost one in four women (22%) within the ages of 40 and 59 take antidepressant medication (Pratt et al., 2011).

There are numerous plausible explanations for this significant rise in the use of antidepressants. First, millions of individuals experience significant distress in their lives, which may be related to depression. Most want to reduce or eliminate this distress, especially if this can be achieved quickly and easily via medication. Medications are a quick, cheap, and convenient option. Second, there is evidence that the significant increase in direct-to-consumer (DTC) advertising for antidepressants is related to rising prescription rates (Park & Grow, 2008). Such advertisements portray depression as a biological medical condition that can successfully be treated with medicine (Lacasse & Leo, 2005; Leo & Lacasse, 2008).

Park and Grow (2008) reviewed the literature on the effects of DTC advertising of antidepressants and suggested that at least two factors of DTC advertising are plausibly linked to increased antidepressant use: (1) an increased perceived prevalence of depression, which leads to higher perceived risk, and (2) brand promotion. These two factors work together by suggesting to a large pool of potential consumers that they are at a higher risk for depression than they previously believed; that experiences they may often have—such as feeling tired, disinterest, sadness, or having trouble concentrating or sleeping—could be caused by depression; and that there are medications that effectively treat depression. Deacon (2013) pointed out that it is presently common for patients to request antidepressant medication from their mental health care providers, largely because of DTC advertising. The result of these factors is increased use of antidepressants. As such, it is not entirely surprising that psychiatric medication sales are worth tens of billions of dollars annually—$70 billion in 2010 (Hyman, 2012).

Philosophic Considerations

Much of the philosophic criticism of neuroessentialism is rooted in debates within the philosophy of science and the philosophy of mind (Fuchs, 2011; Horst, 2012; Vintiadis, 2014). Some of these debates include questions such as the following: What is the relationship between reductionism and the special sciences, such as the relationship between physics on the one hand and chemistry, biology, and psychology on the other? What counts as a scientific explanation? Are the concepts used in neuroscience coherent? These questions are reviewed in turn.

Recall the passage from Gold and Stoljar (1999). This passage pointed out that many scientists rely on a reductionist, materialistic ontology. Thus, from this perspective, it is almost a matter of definition that psychological disorders are really brain disorders. Something like this appears to be what the proponents of the RDoC have in mind. However, Graham (2013) challenged the concern raised by Gold and Stoljar (1999) when he wrote,

We should remind ourselves that, despite the unpopularity of dualism in mental health science, a distinction between mental and non-mental somatic or physical disorders is widely accepted within medicine. . . . Does it imply that the mental is something non-physical? No, it does not. . . . The world in which we live in is a hierarchically layered or multi-leveled world. . . . Physics describes the most basic or general level, chemistry a level above that, and biology, psychology, and sociology each describe successively higher and more abstract and specialized levels. . . . We persons are special or distinct in our detailed multi-level complexity. . . . So to be us ultimately is to be physically based or realized. This does not mean, however, that each and every activity, state, aspect or component of us can be exhaustively or completely described in lower level physical scientific terms. (p. 87)

Graham (2013) is presenting two related but distinct arguments. Graham’s first argument is that special sciences, such as chemistry, biology, psychiatry, and clinical psychology, should not worry about ontological concerns related to reduction if they can produce reliable, predictive, and useful information. For example, a cognitive theory of depression that hypothesizes that depression is often caused by particular types of beliefs can, at the same time, assume that beliefs are, in a complete theory of physics, nothing but subatomic particles arranged in a particular way—from quarks to molecules, to neurons, to a brain. However, since contemporary physics is not currently at this level of sophistication, scientists can make do with “cruder” cognitive theories until physics reaches an appropriate level of sophistication. In Graham’s view, this is acceptable as long as the cognitive theories are proficient at reliably producing predictive, useful information.

Graham’s (2013) second argument is that it is plausible that higher level phenomena, such as subjective experience and psychological disorders, may never be reducible to lower level scientific terms. Thus, to understand depression, it is important to consider someone’s brain, beliefs, and social context. For instance, the stock market crash of 2008 has been found to increase feelings of depression and use of antidepressants (McInerney, Mellor, & Nicholas, 2013). The explanation for these increases is unlikely to be a spontaneous, unpredictable spike in brain diseases. Instead, it is likely explained by individuals whose life circumstances have taken a turn for the worse via decreased wealth, unemployment, and other difficulties (McInerney et al., 2013).

Another illustration of Graham’s (2013) argument can be found in Alva Noë (2009): Imagine a group of scientists examining a dollar bill with the greatest technology available. The dollar bill’s subatomic structure has been carefully mapped with the best physics. Yet even the most comprehensive physics is not able to identify the market value of the dollar within the subatomic structure of the paper. Of course, the value of a dollar does not exist within the dollar but emerges in the context of a larger system. In other words, certain features of the world require an appeal to more abstract concepts in order to be explained, and this is true even if these more abstract concepts do not contradict those physical explanations. That is, physicists studying a dollar will not find particles that defy the laws of physics, but they also will not find the dollar’s market value.

Another philosophical consideration centers on what counts as an explanation. Recall that neuroessentialism explains psychological disorders as disordered brains. However, Dretske (2004) suggested that different levels of explanation are involved in science and are required for a comprehensive account of psychological phenomena. To illustrate this, he presented an example focused on a flower that changes color from red to white during the spring season. What explains the color change? One explanation will have to do with the chemical and biological structure of the flower and the color pigments that are caused by that structure. Yet an evolutionary biologist may not be content with that explanation. The evolutionary biologist might point out, for example, that in the spring, a type of beetle migrates into the flower’s habitat, searching for flowers to consume. For one reason or another, this beetle is only attracted to red flowers, which the beetle then consumes. From an evolutionary perspective, the flower’s color change is explained as random adaptation that has been selected because of its survival value. That is, when spring—and the beetles—come, the flower changes from red to white and, since the beetles are only attracted to red flowers, this color change protects the flower from the beetles’ hungry attention.

What is apparent is that the explanation of the flower’s color change varies based on the level of explanation. The explanation from an evolutionary biologist is much different, though not contradictory, from the explanation offered by molecular biologists or botanists. The explanation is different because the evolutionary biologist is focused on the system the flower is a part of (as well as the forces of evolution), while the molecular biologist is focused on the specific chemical and biological processes that make up the flower and are involved with its changing color. A similar line of thinking could apply to psychological disorders. For instance, an individual experiencing depression has a brain that functions in this way or that. It is possible that sometime in the future neuroscientists can reliably identify particular forms of brain function or structure that are reliably correlated with depression. But even then this would not be an exhaustive explanation of depression for the same reason that the flower’s molecular structure is not an exhaustive explanation of color change. In fact, the evolutionary value of depressive symptoms have been discussed at length by numerous researchers and clinicians (Moore & Fresco, 2012; Sloman, Price, Gilbert, & Gardner, 2004; Watkins & Teasdale, 2004; Wolpert, 2008).

A third philosophic criticism of neuroessentialism is that numerous neuroscientists have made conceptual mistakes that exaggerate the explanatory power of neuroscience. The neuroscientist-philosopher duo of Bennett and Hacker identified a pattern of neuroscientists asserting that the brain perceives, thinks, guesses, knows, and so on and that these functions are explained by the brain’s neural activity (Bennett, Dennett, Hacker, & Searle, 2009). These neuroscientists appear to believe that comprehensive identification of neural activity can replace psychological explanations. Bennett and Hacker agreed that maturing neurosceince will be able to identify a continually greater amount of the neural underpinnings of perceiving, thinking, and so on via inductive correlation between neural activity and psychological phenomenon. However, they argued that this process cannot replace psychological explanations because an explanation of a human being’s perceiving, acting, or thinking cannot be accomplished by focusing on the brain alone. Why?

Bennett and Hacker argued that focusing solely on the brain to explain, for example, thinking, is committing the mereological fallacy in which an attribute of a whole entity is mistakenly applied to a part (Bennett et al., 2009). To demonstrate this, consider how neuroscientists identify neural correlates. First, they must identify psychological concepts, such as thinking, believing, intending, and so on. Only after these concepts have been identified are neuroscientists in a position to examine the neural underpinnings involved in these psychological processes. So, for example, if a neuroscientist was identifying the neural activity associated with thoughts, such as “it’s hopeless,” he or she cannot include only the brain in his or her study. The neuroscientist must also rely on the report of the human being who possesses the thought. That is, to correlate the thought that it is hopeless with neural activity, the neuroscientist starts with the psychological phenomenon and then looks for neural manifestation. Subjective experience guides neural mapping, and the neural map is not the same thing as the subjective territory. This is why Bennet and Hacker argued that agreement on “what counts as a manifestation of consciousness is a precondition for scientific investigations into the neural conditions for being conscious. Otherwise one could not even identify what one wants to investigate” (Bennett et al., 2009, p. 136).

Humanistic Considerations

Humanistic psychologists have long argued against reductionist perspectives in psychology. Rogers (1967) was troubled by the methodology of many psychologists’ of his time. He wrote,

One of the great mistakes in the behavioral sciences today . . . is that since our science must deal in observables . . . we have assumed that the pattern we sense must also have to do with observables. (p. 45)

The trouble with this way of thinking is that the object being studied—human experience and behavior—is reduced to the observable manifestations being measured. But a human being is not only his behavior—especially not only behavior in experimental settings. Human beings also possess “internal, ineffable, subjective, and invisible” aspects that, despite their lack of observability, powerfully influence human experience and behavior (Rogers, 1967, p. 45).

Frankl, another preeminent thinker from a humanistic perspective, argued against reductionist thinking in psychology for decades (Frankl, 1978, 1980; Längle & Sykes, 2006). For example, Frankl (1980) argued that “the human quality of a human being is disregarded and neglected, for example, by those psychologists who adhere to either the machine model or the rat model” (p. 15). In Frankl’s view, the problem with these models is that they attempt comprehensive explanations of human beings from a limited perspective, whether that perspective is biological, psychoanalytic, behaviorist, or any other. These limited perspectives are poorly equipped to integrate the human capabilities of self-detachment and self-transcendence. These capabilities allow human beings to be aware of themselves and their surroundings and to make free choices about their attitudes. Without integrating these capabilities, reductionist perspectives (machine model or rat model) describe only particular dimensions of human beings that will not be comprehensive or even most important.

Yet Frankl (1980) appeared to believe that such models, though often presented in a manner that exaggerated their explanatory power, had a place in psychology and psychiatry. He recalled that he was once asked in an interview “whether I as a professor of neurology and psychiatry would not concede that man is subject to conditions and determinants” (p. 16). His reply was that he knew very well many of the conditions and determinants of human beings but that he also knew very well their ability to detach and transcend from those conditions. Due to his belief in the ability of human beings to detach and transcend their situation, he suggested a dimensional ontology, which integrates multiple perspectives of human beings in a way that recognizes conditions, determinates, and detachment and transcendence. He illustrated this dimensional ontology by pointing out that a cylinder, when viewed exclusively from the top or the bottom, looks like a two dimensional circle. Reductionists, Frankl argued, take the circle to be all there is because it is all their perspective enables them to observe. Yet only by incorporating other perspectives is a comprehensive understanding of the cylinder possible. The same is true of human beings—a point that is apropos considering the problem of fragmentation involved in the biopsychosocial model (Cabaniss et al., 2015; Ghaemi, 2010).

Following this line of thinking, Frankl (1978) suggested that depression cannot be understood as a one-size-fits-all phenomena. Instead, Frankl proposed that depression could be understood as endogenic, psychogenic, sociogenic, and/or noogenic. Frankl was willing to entertain the possibility that some forms of psychological disorder had their etiological origins in heredity and biochemistry, while others were rooted in other factors, such as difficult life circumstances and/or underlying unresolved beliefs of life’s meaninglessness. Regardless of etiology, Frankl claimed that assisting clients to find meaning in the struggles of their lives can largely diminish their suffering even if it cannot eliminate their troublesome circumstances. This is why Frankl wrote that it is often “overlooked or forgotten that if a person has found the meaning sought for, he is prepared to suffer, to offer sacrifices, even, if need be, to give his life for the sake of it” (p. 20).

Subsequent humanistic psychologists were also strong critics of deterministic thinking (Giorgi, 2005; Ryback, 2006; Smith, 1978). For example, Smith (1978) argued that humanistic psychologists were not opposed to science but to a science that focused solely on the “positivistic dogmas” (p. 31). A humanistic science, in contrast to a narrow reductionistic view, would consider not only objectively observable biomarkers and behavior but also comprehensive human embeddedness, subjectivity, meaning, agency, and self-reports. Garrison (2001) summarized this when he pointed out that humanistic psychologists emphasized the centrality of human capacities and values, such as “ethics, truth, beauty, wholeness, spontaneity, and creativity” and that attempting to comprehensively understand human experience without reference to these concepts is impossible (p. 93).

The impact that humanistic objections had on reductionist methodology is difficult to overstate. For example, consider the steep decline of behaviorism. Not only did humanistic considerations influence many psychologists to incorporate methodologies and information outside of the behaviorist prescriptions but even prominent behaviorists were affected. For example, when psychologists with behaviorist backgrounds, like Bandura, embraced a more holistic view of human beings that incorporated participant self-reports into their experiments, this incorporation yielded predictive information over and beyond the information that could be obtained by strict behaviorist methodology (Bandura, 1982; Bandura & Adams, 1977). In fact, Bandura (1996), though an empirically oriented psychologist, argued that a human being is not a “sack of potatoes” that can be understood through purely mechanistic forces (p. 324). Rather, human beings are agents who participate in creative, constructive purposes and their awareness of themselves, their situations, and their beliefs makes a difference in their lives.

In sum, humanistic concerns about reductionism have made a significant impact on the psychological debate (DeRobertis, 2013). In fact, humanistic concerns have made an important impact on neuroscientific thinking, which will be discussed further on (DeRobertis, 2015).

Neuroscientific Considerations

Neuroscientists have also challenged neuroessentialism. Beauregard (2012) pointed out that “mainstream neuroscientists—scientists like myself, who study the brain and how it works—operate from the view that electrical impulses in the brain account for all of our thought patterns and mental experiences” (p. 3). This is, more or less, the neuroessentialistic perspective. However, Beauregard argued that evidence from a variety of directions—such as the power of placebo, hypnosis, and neurofeedback—“show us very different models of what is real and what is possible than materialist science permits. They also give us tools with which we can explore the nature of the relationship between our minds . . . and our brains” (p. 15).

The writings of many other neuroscientists support Beauregard’s (2012) view that numerous neuroscientists are suggesting conceptions of the mind that are at odds with neuroessentialism. For instance, Slaby and Gallagher (2014) argued that neuroessentialistic conceptions of the mind are at odds with evidence that shows the importance of the environment for mental processes. Extended conceptions of the mind, sometimes called embodied cognition or situated cognition, are attracting the interest of numerous neuroscientists. This view of the mind

includes neural processes as [a] necessary but not sufficient component. This not only moves us beyond the . . . idea that cognition is something that happens in . . . “in the head,” but also towards a more enactive and intersubjective conception of mind. (p. 34).

In their view, understanding phenomenological experience requires paying attention to neural processes as well as environmental structures and processes. These environmental structures and processes “couple”—form a reciprocal causal relationship—with phenomenological awareness and enable higher levels of cognitive performances.

A common, though simple, example of the extended mind in action is counting on one’s fingers. In this case, the cognitive process of arithmetic, with its neural underpinnings, is coupled with an environmental place holder (the fingers), and the interaction between the cognitive/neural process and the fingers enables more efficient arithmetic. A more complicated example would be the process of writing an academic paper, in which thoughts mingle with notes, word processers, academic journals, Google scholar, and so on (Clark, 2001). In both cases, the brain, the environment, and the mind are involved in dynamic, iterated loops in which each element is an important contributor to phenomenological experience and the neural processes involved in that experience. Wilson (2002) described this as off-loading cognitive work onto the environment. “The advantage is that by doing actual physical manipulation, rather than computing a solution in our heads, we save cognitive work” (p. 629).

Clark (2013) described another example of the way in which contemporary neuroscience is integrating extended conceptions of mind. After discussing a variety of bottom-up neural processes and top-down cognitive processes that influence those neural processes, Clark concretized this discussion by referencing ongoing work in mobile robotics. The outstanding feature of much contemporary work here is that the information processing involved in mobile robotics—which is thought to contain important parallels to the neural processing of human perception, behavior, and cognition—relies on the environment as an indispensable tool in guiding the learning process. Robotics research, Clark wrote, “already demonstrates a variety of concrete ways in which perception and behavior productively interact via loops through action and the environment: loops that may now be considered as affording extra-neural opportunities for the minimization of prediction error” (p. 14). In other words, the researchers who are interested in developing robots that are able to navigate their environment or perform particular tasks within that environment generally do not attempt to code an all-inclusive set of instructions. Instead, they provide programming that emphasizes heuristics that are rooted in robot-environment interactions. The robots behavior evolves as it behaves in the environment, evaluates the results of that behavior in the context of the environmental inputs, then behaves again, and so on. This dynamic loop between environment and behavior has been successful in creating robots that are able to learn and effectively complete numerous tasks (Clark, 2013).

Another neuroscientist, Noë (2009), suggested that the concept of an extended mind is, in fact, a logical result of neuroscientific methodology. A fundamental unit of neuroscience is the neuron (though there are many types of neurons) and its function. However, quite some time ago neuroscientists recognized that individual neurons acting alone will not provide explanations. Thus, neuroscientists study neurons as dynamic clusters that behave in particular ways over time. Given the expansion from studying single neurons to clusters, Noë wondered,

But why stop there? It isn’t as though brain function is transparent when we look to the dynamics of large-scale assemblies of cells. . . . Just as the fact that we cannot understand phenomena of consciousness in terms of the individual cell leads us to consider the causal powers of populations of cells, so the limits of what we can understand in terms of populations lead us to expand our conception and think of neural systems as elements of a larger system that includes the rest of the animal’s body and also its situation in and interaction with the environment. (p. 48)

Other neuroscientists have argued that neuroscientific research should abandon neuroessentialistic perspectives for reasons similar to the above. For instance, Dehaene (2014) described his neuroscientific training in the 1980s, in which the “C word” (consciousness) was not permitted during lab meetings and was very rare in neuroscience publications. He argued that it was widely believed that the concept consciousness added nothing to scientific explanation and neuroscience would be better off abandoning it. However, Dehaene believed that many aspects of current and future neuroscience do not banish consciousness. New trends in neuroscience have incorporated a “key ingredient to the new science of consciousness: taking subjective reports seriously” (p. 11). In fact, Dehaene argued that in the same way that behaviorism has been largely abandoned in favor of approaches that allow for the importance and explanatory power of consciousness, neuroscientific approaches to consciousness that have neglected subjectivity and self-reports may be neglected in the future.

Finally, some neuroscientists appear to agree with Graham’s (2013) argument regarding the appropriate levels of explanation. That is, some neuroscientists have argued that neuroscience has an important place in the investigation of psychology but that this place is within a particular domain. For instance, Carandini (2015) pointed out that a long-standing general rule in science is that scientists should operate at an appropriate level of description when using theories, forming hypotheses, and conducting experiments. This means, for example, that when biologists think about, write about, and conduct experiments, they do not attempt to reduce their area of study to subatomic particles. In fact, they do not attempt to reduce their area of study to subatomic particles even if they agree that, in principle, biology can be reduced to chemistry and chemistry to physics. In other words,

In physics . . . the equations for particle interactions become impossible to solve or even simulate once a system exceeds ten particles. So, to describe what a decent-sized piece of matter does, solid-state physicists developed remarkably successful theories operating at mesoscopic levels. (p. 179)

Similarly, clinical psychologists have developed successful theories that operate at the psychological level, even if clinical psychologists agree that, in principle, psychology can be reduced to biology.

Deacon and Baird (2009)

Deacon and Baird (2009) recruited 90 college students and had them complete one of two possible questionnaires. The participants were randomly divided into two equal-sized groups, and each was given one of the questionnaires. Each questionnaire included three sections. In both questionnaires, the first section included demographic information and mental health history. The mental health history included questions aimed at determining whether or not the participant believed depression is primarily caused by biological or psychosocial factors. Also, in both questionnaires, the second section asked the respondents to imagine that they felt depressed, sought professional help because of feeling depressed, and received a diagnosis of major depression. Here the two questionnaires diverged. In the first version, a biological explanation was given before a biopsychosocial explanation. In the second version, this order was reversed. The biological explanation of depression contained information “adopted from the National Alliance on Mental Illness” website, which detailed the view that depression is caused by a chemical imbalance (p. 421). The biopsychosocial explanation of depression offered an alternative account of depression that emphasized that a wide variety of biological, psychological, and environmental influences were contributing causes of depression.

The third section of each questionnaire asked respondents questions about prognosis, stigma, and treatment. Questions in the prognosis portion included items such as, “To what extent would you feel able to effectively control the depression on your own?” and “To what extent would you expect your depression to be a chronic problem that persists for years?” Questions in the treatment portion included items such as, “How effective would you expect medication to be in treating your depression?” “How effective would you expect psychotherapy to be in treating your depression?” and “To what extent would you believe that making changes in your attitudes and lifestyle would improve your depression?” (Deacon & Baird, 2009, p. 422).

Deacon and Baird (2009) found statistically significant differences between the etiology of depression and stigma, prognosis, and treatment. Individuals who endorsed a biopsychosocial explanation of depression had a more positive prognosis and higher perceived efficacy of psychotherapy. Individuals who endorsed the biological explanation of depression had a more pessimistic prognosis and higher perceived efficacy of medication. The authors concluded that “compared to a biopsychosocial explanation, the chemical imbalance explanation . . . led to decreased personal and moral responsibility for depression, a worse expected prognosis, and the perception that psychosocial interventions are largely ineffective” (p. 429).

Lebowitz, Ahn, and Nolen-Hoeksema (2013)

Lebowitz et al. (2013) conducted three studies. In the first two studies, participants (N1 = 108 and N2 = 40) were recruited online and then assessed for depression with a Beck Depression Inventory-II (BDI-II). Participants who obtained a score of at least 16 on the BDI-II rated their level of agreement with 10 causes of their depressive symptoms, including biochemical and genetic explanations of their symptoms (7-point Likert-type scale from very unlikely to very likely). These participants were then instructed to answer questions about their expected duration of symptoms. The authors conducted a linear regression and found that “the more people with depressive symptoms attribute those symptoms to genetic and biochemical causes, the longer they tend to expect their symptoms to last” (p. 521).

The third study was the same as the first two but included participants who did not obtain a score of 16 or above on the BDI-II and the inclusion of an additional portion. In this added portion, the participants were randomly assigned to one of three conditions: Malleable, Biological-Illness, and Control. In the malleable condition, participants watched a 6-minute video that “provided a basic primer on epigenetics,” which emphasized that environmental factors can modify the biology of mood (Lebowitz et al., 2013, p. 522). For example, the video detailed that exercise and sunlight alter brain chemistry in a way that alleviates the symptoms of depression. In the biological-illness condition, participants watched a different 6-minute video that provided information about depression that was similar to accounts portrayed in the scientific and popular literature. This information highlighted that depression often runs in families and that research has shown that there are differences between the brains of depressed and nondepressed individuals. The control condition participants did not view a video. Then, the participants were asked to rate their expectations of prognosis, personal agency in relationship to mood, and outlook for the future.

Regression analyses found that “biochemical/genetic attribution scores were a significant predictor of longer expected symptoms duration and lower perceived odds of recovery” (Lebowitz et al., 2013, p. 523). Importantly, Lebowitz et al. (2013) also found that the malleability condition was effective in reducing prognostic pessimism as well as in increasing optimistic thinking and personal agency in relationship to mood. The authors concluded that “given the increasing prevalence of biomedical conceptualizations of depression, the notion that depressed individuals who hold such beliefs might be more vulnerable to pessimism about the course of their disorder is alarming” (p. 525).

Read, Cartwright, Gibson, Sheils, and Haslam (2014)

Read et al. (2014) conducted a study in which 1,829 individuals, who had all been prescribed antidepressants in the past 5 years and were at least 18 years old, answered an online questionnaire. The questionnaire had 47 items and included yes-no, Likert-type scale, and open-ended formats. The questionnaire inquired into a number of different areas associated with antidepressants, prescriptions, pharmaceutical companies, and beliefs about the causes of depression. The authors stated that the key question of their study was, “There are many theories, and lots of debate, about what causes problems like depression. Please indicate the extent to which you think the following factors are causes of depression in general” (p. 237). This question was followed by 17 items, gathered from the scientific literature, that listed biological, psychological, and social causes. Participants were instructed to answer each of these items on a 5-point Likert-type scale from strongly disagree to strongly agree.

A number of different relationships were identified between causal beliefs about depression and use of antidepressants, interaction with the prescriber, perceived efficacy of antidepressants, and other factors. Importantly, Read et al. (2014) “replicated the many previous findings” that “bio-genetic beliefs” about depression were associated with greater prognostic pessimism (p. 240). This finding was based on a regression analysis of causal beliefs and the item from the questionnaire read, “People cannot get better by themselves even if they try” (p. 240). The authors concluded that their study “replicated the many previous findings that bio-genetic beliefs are associated with prognostic pessimism” (p. 240).

Kemp, Lickel, and Deacon (2014)

Kemp et al. (2014) conducted a study of 73 participants who reported presently or previously experiencing a depressive episode assessed via an online screening item. Participants were randomized into two groups: the chemical imbalance condition (N = 37) and the control condition (N = 36).

The participants in both conditions were individually administered the credible but fake “Rapid Depression Test” (RDT), which was described to the participants as a test that “would allow participants to determine whether or not their depressive episode(s) were caused by a chemical imbalance in the brain” (Kemp et al., 2014, p. 48). This test included an “experimenter” (an undergraduate research assistant) wearing a lab coat swabbing the inside of each participants’ cheek and then placing the swab in a container. The experimenter then explained to each participant that he was leaving the room to conduct the lab analysis on the swab. After 10 minutes, the experimenter returned with the results of the RDT and explained them to the participant.

In the chemical imbalance condition, the experimenter explained to the participant that the RDT indicated that his or her depressive episode was “caused by an imbalance in the neurotransmitter serotonin” (Kemp et al., 2014, p. 48). Each participant was then shown a bar graph illustrating normal levels of neurotransmitters with the exception of serotonin, which was far below the indicated normative range. In the control condition, the procedure was identical except that the experimenter explained that the test results indicated that all each person’s neurotransmitter levels were within the normative range.

After being presented with the results, each participant completed five assessments: Causal Attributions for Depression Scale, Perceptions of Depression Scale, Negative Mood Regulation Scale, and the Credibility and Expectancy Questionnaire. These scales were meant to collectively measure themes such as the participants’ understanding of the causes of their depression, perception of stigma, prognostic pessimism, and expected mood regulation.

After the experiment was conducted, the participants were debriefed. The debriefing included an explanation that the RDT is not a valid test and the administration of the Deception Credibility Questionnaire. The Deception Credibility Questionnaire is designed to measure “the credibility of the manipulation” (Kemp et al., 2014, p. 50).

Between-group comparisons found that there was a significant difference in prognostic pessimism and mood regulation expectancies with the chemical imbalance condition having greater prognostic pessimism and lower mood regulation expectancies. A repeated-measures ANOVA found that “participants in the chemical imbalance condition rated pharmacotherapy as more credible than psychotherapy” (Kemp et al., 2014, p. 50). Those in the chemical imbalance condition also believed that pharmacotherapy would be more effective than psychotherapy. Kemp et al. (2014) concluded that

chemical imbalance test feedback increased prognostic pessimism, lowered negative mood regulation expectancies, and led participants to view pharmacotherapy as more credible and effective than psychotherapy . . . the present findings suggest that providing individuals with a chemical imbalance causal explanation for their depressive symptoms . . . activates a host of negative beliefs with the potential to worse the course of depression and attenuate response to treatment, particularly psychotherapy. (p. 50)

Schroder, Dawood, Yalch, Donnellan, and Moser (2014)

Schroder et al. (2014) conducted two studies that were designed to measure the relationship between participants’ implicit theories of emotions, such as anxiety and depression, and three domains: psychological symptoms, emotion regulation, and treatment choice.

Following previous research, Schroder et al. (2014) described two types of implicit theories: entity theory and incremental theory. Entity theory holds that “abilities and traits” are “relatively set-in-stone and unable to change” and those that hold entity theory “typically attribute their capacities to genetic and biological causes” (p. 121). On the other hand, incremental theory holds that “self-attributes are responsive to improvement and growth with learning and effort” and that these attributes can be modified by “motivation and effort” (p. 121).

In the first study, Schroder et al. (2014) attempted to measure “how implicit theories” of anxiety, intelligence, and emotion related to a number of different outcome measures, including depression, emotion regulation, and “hypothetical treatment preferences” (p. 124). Participants (N = 388) were assessed with three implicit theory measures: the implicit theories of intelligence, implicit theories of emotion, and implicit theories of anxiety. These protocols are designed to measure a participant’s views on the ability to control and change intelligence and emotion. Participants were also assessed with a number of other instruments such as the Penn State Worry Questionnaire, the Mood and Anxiety Symptom Questionnaire, the BDI-II, the Emotion Regulation Questionnaire, and an item measuring hypothetical treatment choice.

Schroder et al. (2014) found that the implicit theory of emotion scale “significantly predicted many of the” mental health symptoms assessed, such as depression (p. 127). Furthermore, the incremental theory of emotion scale was “uniquely associated with more cognitive reappraisal” suggesting that individuals who endorse incremental theory more than entity theory are more likely to participate in attempts to reframe their emotional experience. This is important because reframing emotional experience is often an effective strategy for reducing negative psychological symptoms. Finally, the authors found that participants whose implicit theories of emotions were “indicative of more of an entity theory” were significantly more likely to choose medication instead of psychotherapy as a hypothetical treatment choice, which suggests that these participants expect medication to be more beneficial (p. 129).

Similar to the first study, the second study (N = 298) found that incremental theories of emotion were “negatively related to symptoms of anxiety, depression . . . and positively related to cognitive reappraisal” (Schroder et al. 2014, p. 130).

Schroder et al. (2014) concluded that “cultivation of incremental theories of . . . emotion may be most beneficial in terms of mental health and functioning” (p. 134) and that “changing implicit theories more toward incremental beliefs may lead to reductions in symptoms” (p. 135). In other words, believing that one’s emotional state is fixed via genetic or biological causes is related to less cognitive reappraisal and worse mental health symptoms.

Lebowitz and Ahn (2014)

Lebowitz and Ahn (2014) conducted three studies that focused on clinicians instead of patients. In the first two studies (N1 = 132 and N2 = 105), mental health clinicians were given vignettes that described patients with mental disorders. The first study described patients with schizophrenia and social phobia. The second study described patients with major depression and obsessive compulsive disorder. Each disorder was described in two separate passages. One passage described the disorder from a genetic and neurobiological perspective. The other passage described the disorder from a psychosocial perspective. Each mental health clinician was given a total of four vignettes in which both of the disorders were described from both of the perspectives mentioned above. After reading each of the vignettes, how the clinicians “felt about the fictitious patients” was measured by having them view 18 adjectives and then rate “how much each one described their feelings toward the patient described” (p. 17787). This method is “well-validated” and “extensively used in empathy research” (p. 17787).

In addition to measuring empathy, the clinicians also rated how much improvement they expected each of the patients to make via medication or psychotherapy as well as the “clinical utility” of each descriptive passage. The data indicated that biological explanations resulted in significantly less clinician empathy than the psychosocial explanation in both studies. Furthermore, in both studies, biological explanations were evaluated as less clinically useful for each disorder except schizophrenia and, also in both studies, clinicians rated psychotherapy as significantly less effective than medication when a biological explanation was given versus when a psychosocial explanation was given.

In the third study (n = 106), participants were given both biological and psychosocial explanations of psychological disorders but one form of explanation was dominant. They believed this would “more closely mirror the real world, in which biological conceptualizations of psychopathology may gradually come to predominate psychosocial explanations without totally eliminating them” (Lebowitz & Ahn, 2014, p. 17788). Similar to the first two studies, descriptive passages in which biological explanations dominated resulted in significantly less clinician empathy than passages in which psychosocial explanations and biologically dominant explanations led to “significantly higher ratings of medication effectiveness and significantly lower ratings of psychotherapy effectiveness” (Lebowitz & Ahn, 2014, p. 17788). The Lebowitz and Ahn (2014) concluded by stating that the data suggest that “biological explanations of mental illness can have clinically relevant negative consequences among mental health clinicians,” especially decreasing clinician empathy and increasing clinician expectancy that patients could benefit from psychotherapy (p. 17788`).