The pragmatic use of metaphor in empirical psychology

Abstract

Metaphors of mind and their elaboration into models serve a crucial explanatory role in psychology. In this article, an attempt is made to describe how biology and engineering provide the predominant metaphors for contemporary psychology. A contrast between the discursive and descriptive functions of metaphor use in theory construction serves as a platform for deliberation upon the pragmatic consequences of models derived therefrom. The conclusion contains reflections upon the possibility of an integrative interdisciplinary psychology.

Keywords

explanation metaphors of mind philosophy of psychology pragmatism psychology

Introduction

Empirical psychology has two modes of explanation: hypothetico-deductive and analogical. While much has been written about its status as a science that employs the former mode (Bechtel, 2008; Fodor, 1998; Thagard, 2012), in this article I consider the latter. Since empirical psychology is part of the human sciences, metaphor use is necessary to supplement the descriptive explanations and methodologies of the scientific method. My goal is to address the purpose, constraints, and goals of analogical explanation in empirical psychology from the vantage point of pragmatism.

In securing agreement between analogical domains, successful metaphor use reveals structural integrity in nature that is not simply parsimonious. The analogical connections drawn between fields engender discovery, hypothesis formation, and novel interpretation of data. Indeed, choosing between theories is often a matter of selecting a more or less fruitful metaphor (Hoffman, Cochran, and Nead, 1990). Root metaphors generate research by serving as starting points, limiting factors, anchors, and conduits for creative intellectual exploration. One of the generative functions of metaphor is providing a connection between a hunch, or pre-analytic detection of similarity, and a new theory (Kearns, 1987). ‘It is pictures rather than propositions, metaphors rather than statements that determine most of our philosophical convictions’ (Rorty, 1979: 12). Some even argue the central problem of science is making a connection between metaphor (as model or theory) and experimental results (Brown, 2003). Metaphors also serve as heuristic frameworks to ease communication between scientists and the public (Fischer, 2014). Their use in contemporary psychology enables interactive coupling between model, theory, and observation towards data interpretation and communication.

By serving as a bridge between the abstract and the concrete, metaphors provide a sense of scope and emphasis (Danziger, 1990). In science, models are representational entities wherein fit to the natural phenomenon is partial and imperfect. Adoption of a given model for a particular field of data is thus generally determined by its instrumental – that is, pragmatic – benefits (Giere, 1999, 2006). Those benefits are enabling explanation through broadening the associational field, engendering creative abduction, and providing direction for empirical study. One pragmatic element of successful metaphor use is the opportunity to spin off a theoretical model that allows the scientist to refer to phenomena not fully determined by empirical conditions (Harré, 2004). The abstract nature of analogy is thus a reliable epistemic strategy to handle hidden or unknown entities.

This article provides an assessment of contemporary metaphors of mind as pragmatic paradigms for empirical exploration.¹ The various metaphors currently in use draw from biology and engineering and thus have diverging epistemological consequences. In the discussion section, I consider broader issues in our use of descriptive and discursive explanation.

What is and what is not a metaphor

A necessary feature of metaphor is that a structural correspondence is created whereby a comparison of terms that each have their own associational fields enriches the semantic field of the phenomenon in question (Black, 1962, 1977). The topic or tenor (i.e. principal subject) is conceived in the context of a vehicle (or modifying term) against a ground that serves as the semantic basis of the metaphor (Hoffman, Cochran, and Nead, 1990; Richards, 1965). A successful metaphor reverberates through the network of entailments, thus serving as a stimulating guide to disambiguate new discoveries (Boyd, 1979; Lakoff and Johnson, 2003). For example, the topic of memory has often been portrayed in the vehicle of a container. The associational semantic field of container allows for the entailments of space and storage in folk notions (i.e. ‘I can’t remember but it is somewhere in there’; ‘I had it, but now it is lost’), as well as technical notions like encoding.

Towards progressive conceptual change in theory construction, metaphor is moulded into a framework or a model to provide structure for analytical descriptions and entailments (Thagard, 1992). The elaboration of the generative impetus of metaphor use leads to theory-constitutive practices like the proposal of models (Kearns, 1987). For example, creating a structural correspondence between memory and space/container coincides with the cognitive scientific notion of sets of memory banks, for short-term memory, working memory, long-term memory, and procedural memories (Kandel and Pittenger, 1999). Through creative abduction, metaphor as model fits the phenomenon under investigation into a pattern that generates ampliative inferences. One can ask about localization of the different memory banks in the brain, or about how they relate to each other; researchers have studied how a memory ‘moves’ from short-term loops to long-term ‘storage’, or how, during the process of learning, a skill becomes stored in procedural memory (Baddeley, 2007). Conceptual change enabled thereby includes the collapse of a part of a kind-hierarchy, branch jumping leading to broad recategorization, and hierarchical tree redefinition (Magnani, 2002). For example, when memory theorists distinguished between declarative and non-declarative memories, the latter served as a way to recategorize learning actions, skills, and motor routines as forms of memory under the new hierarchical tree of ‘procedural memory’ (Squire, 2004).

As a model, metaphor enables the identification of relationships between interconnected elements in a system (Bowdle and Gentner, 2005). A model consists of the coupling of one organization of data with another mode of organization (Pribram, 1990). In the psychological sciences, these structures usually represent functional elements of the brain in some schematic abstraction, like the neural coding and storage of objects, properties, relations, behaviours, and processes (MacLeod and Nersessian, 2013). Descriptions of ‘remembering’ as activations of the associational cortex, or of the hippocampus as the site of memory consolidation, illustrate this point (Squire, Stark, and Clark, 2004). Metaphors as models provide a simple frame with which one may ask and interpret how and why a system behaves across a range of settings, and thus offer predictive accounts for behaviour through an exposition of structural elements (Clement, 2013). This is the basis, for instance, of studies of dissociation in patients with lesions, such as patient H. M., who had extensive damage in the hippocampus, which was used as a way to chart memory deficits and functional brain localization (Squire, 2009).

To change metaphors, then, entails a shift in conjectural templates, such as looking at the phenomenon differently, reordering relationships, comparing events, and discarding or imagining further epistemic manipulations (Magnani, 2002). Sometimes the metaphor provides a new set of theoretical terms and images that is not present in the data itself; in such cases of catachresis, it fills a lexical gap and serves an epistemic role in reframing and even creating a way to view the phenomenon (Barrett, 2011). For example, neuropsychologist Giulio Tononi (2012) uses the term ‘phi’, which is also used in quantum mechanics to specify wave functions, to stand for how information is integrated in the brain. Implicit in this catachresis is the claim that consciousness is a specifiable physical magnitude that is analogous to, or even identical with, information integration. In contrast, new terms are often coined to denote heretofore unknown phenomena in physics. The general practice there is to employ nonsense terms that do not have other connotations so as to avoid analogical interpretation.

The study of metaphor and its use in psychology reached its zenith between the mid-1980s and early 2000s. Classic texts in the field include Bradie (1999); Brown (2003); Draaisma (2000); Gentner and Grudin (1985); Kearns (1987); Lakoff and Johnson (2003); Leary (1990); Montuschi (2000); Ruse (2005). Currently, consideration of metaphor use is a focus in the fields of embodied cognition (e.g. Asma and Gabriel, 2019; Barsalou, 2009; Fincher-Kiefer, 2019; Gentner, Loewenstein, and Thompson, 2003; Gibbs, 2006), phenomenal consciousness (Fischer and Curtis, 2019; Klein, 2021), and reasoning and mental models (Boroditsky, 2000; Thibodeau and Boroditsky, 2011). Some popular models in psychology are derived from metaphors; for example, global workspace theory (GWT) drew on an analogy between the attentional properties of neuronal processing and the workspace of a globally broadcast screen at a sporting event (Baars, 1988). In GWT, the attendees are likened to unconscious neurons; the camera of attention (or consciousness) is turned to them when what they are ‘processing’ is so important that it should be globally broadcast to all neurons.

On the other hand, some theories are inaccurately described as metaphors. This occurs, for instance, when dualistic language is used to describe the mind; dualism is not a metaphor per se (McGinn, 1989; Ryle, 1949). Some argue that metaphor cannot be applied to the problem of phenomenal consciousness without becoming tautological (Klein, 2021). While analogical reasoning and figurative description is widespread in the sciences, it is important to grasp what is not metaphor, namely literal description. One example is non-reductionist mechanistic explanation, in which we delineate parts and their functioning, such as in manuals of operation or blueprints of man-made machines (Craver, 2005). Another is the theoretical entities used in behaviourism (Flanagan, 1984). With the rise of empirical tools such as neuroimaging and microscopy, it is worth considering whether a literal description of the brain and body is possible and how that would affect the pragmatic use of metaphor in psychology.

In the first section of the article, I explore how philosophical pragmatism motivates theory-constitutive metaphor use. In the next section, I offer a brief illustrative history of metaphors of mind, followed by an exploration of prevalent metaphors in contemporary theory. The third section focuses on metaphors in contemporary psychology, and the concluding sections contrast the pragmatics of modes of explanation entailed thereby.

Pragmatism

Analogical explanation in scientific thought is continuous with the role that metaphor plays in everyday practical thought, wherein we create ‘as if’ scenarios to navigate the world (Vaihinger, 2009[1911]). Metaphors of mind are similarly fictions in search of practical corroboration; we justify an assumption by seeing what comes of it (Freud, quoted in Leary, 1990). Appiah (2017: 3; emphasis in original) summarizes Vaihinger: ‘Very often we can reasonably proceed as if what we know to be false is true because it is useful for some purpose to do so.’ Vaihinger's ‘as if’ philosophy is of a piece with C. S. Pierce’s (1878) notion that belief in a useful fiction is a habit that enables action, that is to say, beliefs about the world compose rules for action (James, 1972[1907]: 286–302).

In line with this pragmatic relation between belief and useful fiction, the broad practical purpose of metaphor is to aid us in moving appropriately through practical or theoretical empirical investigation of the world. In this context, truth simply refers to efficacy, that is, the quality of ideas that allows them to be assimilated, validated, corroborated, and verified (James, 1972[1907]). ‘A metaphor works when it satisfies a purpose, namely, understanding an aspect of the concept’ (Lakoff and Johnson, 2003: 97). If it leads to successful wayfinding, a description is an effective explanation.

The pragmatic function of metaphor in empirical psychology may therefore be to help settle intransigent empirical or rational disputes through tracing practical consequences. A metaphor that is pragmatically true will lead to a model that points researchers in an empirically worthwhile direction. For James (1972[1907]), what a scientist seeks in philosophy is intellectual abstraction that maintains a positive connection to the empirical world. Accordingly, one purpose of the psychological sciences is to achieve such an understanding of human behaviour that enables, among other things, predictions about future behaviour and reliable frameworks to understand intentional thought (Kagan, 2017). Pragmatism is an epistemology of wayfinding: the construction of models based on metaphors is a self-conscious extension of the cognitive capacity to map our environment (Giere, 1999). Indeed, metaphors do not need to be veridical to lead to interesting or empirically fruitful findings; their usefulness is in creating space for rational and empirical exploration. Metaphor use in empiricism is a process of showing similarities and dissimilarities in phenomena and bringing into relief the theorist's assumptions therein (Hoffman, Cochran, and Nead, 1990).

Metaphor plays an ontological role insofar as it offers a fundamental redescription that frames our dispositions towards a hidden entity. Indeed, metaphor partially creates what it purports to reveal; it structures how we see what we don’t know (Berggren, 1963). Analogy is a practical strategy of disambiguation to conceive of unknown domains. We use it in situations when we are confused; when learning a new language, for example, we make analogies to languages and gestures or sounds that we understand. Thus, metaphors of mind occupy a unique position between evidence and trust: we collect enough evidence through an analogical structure that we grow to trust it as a guide for prediction and collecting further evidence. Children are said to use such practical systems as they explore and learn about their environment (Gopnik, 1996). A given metaphor is not necessarily present in the observed phenomenon; it is rather a tool of analysis that is in the eye of the scientist-beholder, trusted insofar as it generates insight. Subsequently, the metaphor requires trust from the scientific or lay community. It serves an epistemological function that enables direction and structure, while at the same time not necessarily being empirically demonstrable. For example, portrayal of the connectivity of the brain in a connectome is a way of understanding its complexity within the analogy of binding (connectere; Guenther, 2015).

Metaphors that reify unreal properties or that focus on artefactual phenomena or relations are not pragmatic; they do not aid empirical wayfinding. For example, to say that the mind is like a radio, that consciousness is being beamed in our heads, while falsifiable, has so far not proven a useful avenue of research. Adopting metaphors in inappropriate circumstances runs the risk of occluding elements of the phenomenon and disregarding properties that are inconsistent with the metaphor (Lakoff and Johnson, 2003). The computer metaphor adopted in cognitive science, for example, occluded the importance of the body (Chemero, 2011). Furthermore, while a scientist employs an explicit surface-level metaphor in their thinking, a deeper, more implicit metaphor may also be in use throughout their oeuvre (Leary, 1990). Freud, for example, could explain dreams at the manifest level through linguistic contrivances and associations, while returning to the hydraulic and topographical models of the mind to draw deeper inferences (Freud, 1963[1915]).

Presently, no single metaphor of mind can serve a theory-constitutive function (Kearns, 1987). The last 150 years of experimental psychology presents us with a diffusion of data generated by competing laboratories, each seeking its own reliable metaphors to interpret empirical findings.

A brief history of metaphors of mind

The essential function of metaphor in a pragmatic approach to theory construction in empirical psychology is to help us say what we mean in a way in which the partiality of our understanding becomes illuminated (Harré, 2004). We conceptualize what is unclear in terms of what is more clearly structured (Lakoff and Johnson, 2003). The function of metaphor is thus not only to reorganize our conceptions but also to express commonly held but imperfectly articulated feelings (Gergen, 1990) so as to encourage reflection upon substitution, comparison, and interaction among associational fields (Black, 1962).

In some cases, metaphor may serve to convey a sense of complexity without specifying precise mappings or relations between the topic and vehicle domains (Bowdle and Gentner, 2005; Gentner, 1983). Unpacking and specifying complexity is an important function of the explanatory metaphor, which should clarify the phenomenon without necessarily reducing it. This complexity must then be worked out through empirical research framed by the questions suggested by imposing the model upon the phenomenon.

Psychological theory in the 18th century devolved on metaphors of mind-as-entity characterized by the qualities of tangibility and passivity, with a simplicity of structure (Kearns, 1987). For example, John Locke’s (2004[1689]) simple, tangible, and passive tabula rasa was impressible. The frame of mind-as-entity enabled thinkers to activate the entailments of associated ideas from physics, biology, and geology (Kearns, 1987). The early 19th century added a concern to preserve spirituality and the power of the will through moral psychology, such as the notion of ‘mental hygiene’, popularized in Isaac Ray's book from 1863. Kearns (1987), for instance, describes how mentally ill people were thought to have immutable souls but diseased, immoral bodies that needed to be reshaped by new customs.

In the late 19th century, there was a shift to an emphasis on mind-as-living-being, wherein ‘mindscapes’, ‘sentient webs’, and other generative metaphors for mind-as-substance predominated. For example, John Stuart Mill made the analogy of mental chemistry and mental mechanics so as to disambiguate how simple principles like reflex arcs and laws of association could lead to complex mental phenomena (Kearns, 1987). George Henry Lewes portrayed the mind as a web of sentient neural tremors grouped into sensations (ibid.: 129). Victorian physiologists sought to avoid the mind/body problem by naturalizing the mind while not losing the spiritual thread, portraying the mind as an entity that ‘receive[s] nerve-force and generates mind-force’ (ibid.: 98). Nerve ganglia at this time were interpreted as an analogy for ‘sentient webs’ that exerted immaterial principles (Jacyna, 1981). The notion of the ‘mindscape’ can be seen here as a way to spatialize the mind while still allowing for the dynamics of Descartes’ res cogitans. For thinkers like Alexander Bain, this allowed one to reject the passive receptacle theory of the British empiricists and appropriate nascent physiological accounts of biological activity (Robinson, 1976).

In the early part of the 20th century, animate and spatial metaphors dominated, while in the latter half of the century, systems metaphors were in ascendance (see review and tables in Gentner and Grudin, 1985). Other dominant metaphors of mind include the ‘sensorium’ or ‘presence room’ and the aforementioned ‘blank slate’ of the British empiricists (Locke, 2004[1689]), which formed the basis for later behaviourist and associationist traditions (Barrett, 2012; Skinner, 1951; Watson, 2007[1924]), as well as the universal Turing machine of the artificial intelligence and cognitive science communities (Gardner, 1985; Herken, 1995).²

In the 20th century, the dominant paradigms in empirical psychology were behaviourism and cognitive science. Behaviourism enabled empirical precision of great subtlety, best suited to non-human animal experiments, while cognitive science supported systematic modelling of internal information states, best suited to computers and some rational skills. Each approach thus described a different domain of mental function (Gabriel, 2012). Behaviourism sought a literal language that eschewed intentionality and metaphor to describe the mind; it remains at the core of the animal neurosciences as a flexible and reliable system for training and manipulating stimuli and responses (Barrett, 2012). Cognitive science and its computational metaphor, on the other hand, systematized mind into units such as ‘modules’ as information-processing units (on the history of ‘information’, see Garson, 2015), especially in the parallel distributed processing models of connectionism (Fodor, 1983; Gardner, 1985). And yet, cognitive science did not make sufficient strides concerning global elements of the mind like affect and subjectivity (Klein, 2017; Metzinger, 2002).

A crucial question is whether the shifting of metaphors reflects cultural context or advances in scientific naturalism. Kurt Danziger (1990) claims the reciprocal confirmation of symbolic structures at different levels of discourse implies a type of hall of mirrors, wherein the root metaphor of an era is formed from a taken-for-granted collective representation. The sociocultural embeddedness of psychological theory is apparent, for example, in shifts in our portrayals of memory (Draaisma, 2000). Such shifts between passive, Platonic, and cognitive dynamics in the representation of memory dramatize how theories reflect culture and objects encountered when searching for images to conceive of hidden processes of the mind (Douglas, 1977). Consider that spatial metaphors of the mind in the 18th and early 19th centuries indicated a step away from Cartesian dualism. In this step, mental life was secularized for the purposes of scientific investigation insofar as cause and effect were localized in a physical space, res extensa. Systems metaphors, like ‘switchboards’ or ‘sentient webs’, then arose as a way of creating sets of spatialized mental units that enabled the imputation of relations therein and thus more elaborate landscapes of cause and effect networks. This approach was amenable to a computational metaphor that instantiated relations of cause and effect units into distributed networks of digital logic gates. These units could be investigated through modelling, as well as serve to explain cognitive dissociations reported in the burgeoning neurosciences. The computer metaphor has proven particularly powerful because it links meaningful aspects of the mind to meaningless physical processes (Draaisma, 2000). One interpretation of why metaphors wax and wane in popularity is that the field at a given time may simply designate the most complex objects then known as the metaphor of mind, adopting in the early 20th century, for example, the ‘photograph’ for our spatial imagistic metaphors and the ‘switchboard’ as a metaphor for neural function (Jaynes, 2000[1976]).

The current range of metaphors used in empirical psychology are demonstrable hybrids built upon the negative evolution of the metaphors highlighted above (Koch, 1999). We turn now to contemporary metaphors of mind that integrate elements of associationist, behaviourist, and computational models.

Contemporary metaphors

As metaphors are essentially filters on our perception (Draaisma, 2000), contemporary models derived therefrom condition scientists’ decisions to explore, verify, and corroborate elements of the mind. In the last two decades, an international community of empirical psychologists has focused on a particular set of fruitful models (Araujo, 2017). In this section, I focus on major metaphors in contemporary experimental psychology and the models that employ them.³ These metaphors resemble those of 20th-century schools of experimental psychology, as they include both native structures and elements that can be modified by experience. With an eye to their pragmatic consequences, I describe the interaction between associational fields that each metaphor allows and the novel discoveries made possible by these forms of selective perception.

The tenor of the mind in contemporary experimental psychology draws upon two major vehicles, biology and engineering. The following associational fields are thus brought to bear on the study of the mind: evolution, developmental processes, emergence, the body, and machine learning. Biology and engineering are modes of scientific naturalism, and it is largely through them that contemporary psychology employs epistemology adapted from the natural sciences. Through structural correspondence, concepts from these vehicles notably render the tenor of the mind more tractable to mechanistic description.

The unifying theories of the historical science biology are cell theory, evolution theory, genes, and homeostasis (Ruse, 2005; Tibell and Harms, 2017). Placing psychology in correspondence with biology allows the entailment of principles like probability, ecology, and a broader range of spatial and temporal scales. This naturalist ontology allows for more sophisticated consideration of the transformations between genotype and phenotype, or innate systems and their developmental trajectory, such as the epigenetics of how environment modifies genes expression (Carey, 2012). Furthermore, the relation between environment and DNA serves as an associational field for how developmental pathways emerge from an organism's interactive lifeway (Kaufman, 1993). Such formulations open up further questions concerning the evolution of development (Carroll, 2005) and consideration of the functional telos of the mind in an evolutionary context (Nagel, 2012).

The key principles of engineering are testability, maintenance, integrity, external integration, ethics, and management (Hurst, 1999). Taking a formal, design stance allows psychologists to consider the adaptive functions of the mind, creative solutions to problems faced by the organism, and the modes in which these solutions can be delivered. For example, evolutionary psychology employs the method of ‘reverse engineering’ our behaviours to discover their function in the environment of evolutionary adaptednesss (Tooby and Cosmides, 1990). Other integral ideas include assessment of structure, strength, and cost, which take into account stress and strain upon materials. For example, Pessoa (2013) and other researchers emphasize how attention is a limited resource that depends upon an organism's motivation and the cognitive load it is under. Compression of lability as an effect of environmental feedback demonstrated in the limits of materials has come to serve as a crucial associative principle for neural dynamics (Colombetti, 2017)

I now describe some important contemporary models so as to illustrate how these metaphors have served pragmatic ends in theoretical and empirical work. Affective science characterizes the mind as evolutionarily nested rational and passional functional neural layers, as in, for example, the hot/cold cognition model and the affective neuroscience and basic emotions theories (see Boyd, 2017; Damasio, 2018; Davidson, Scherer, and Goldsmith, 2003; Ekman, 1999; Kahneman, 2013; Marcus, 2009; Panksepp, Biven, and Siegel, 2012). By using the vehicle of evolution, the affective sciences enlist the epistemological context of biology rather than the formalisms of computationalism. These models trade on the complex relationship between categories of faculty psychology, viz. emotional versus cognitive forces, to argue the mind is best understood as an integral part of an organism engaged in navigating the world through both innate and learned motivational urges. The affective sciences employ the associational fields of neurochemistry and evolution. Through these interactions it postulates a language of drives, competition, feedback loops, inhibition, and homeostasis. As in other fields that employ the developmental metaphor of evolution, an emphasis is placed on fitting the human mind into the same category as other natural phenomena, including animal minds. All the tools of evolutionary biology, such as identifying homologies, thus become available. Sophisticated concepts from neuroscience concerning areas largely ignored by cognitive neuroscience, since they cannot be imaged (for example, the brain stem), and the volumetric nature of neurotransmission, enrich empirical psychologists’ investigation of mental phenomena (Panksepp, 1998). Bringing evolution to bear on the mind – as in the model of evolutionary psychology and the affective sciences, makes available the associational fields of developmental processes and findings from ethology and evolutionary biology (de Waal, 2001).

While early cognitive neuroscience conducted a quasi-phrenological search for centres (e.g. the memory centre, the language centre, etc.; Uttal, 2011), contemporary neuroscience emphasizes the distributed nature of networks for storage and function (see Pribram, 1990). These metaphors of connectedness and complexity dovetail with engineering metaphors being brought to bear on systems neuroscience (Guenther, 2015).

Embodied, embedded, extended, and enactive (or 4E) models emerged as a critique of passive, mentalist, representational models and sought to portray the mind as emerging through a relationship between body and world. This approach, which includes ecological psychology and forms of machine learning of robots that locomote, characterizes the mind as a spatialized physical system and thus emphasizes real-time active integration of perceptual and motor processes (see Chemero, 2011; Gibson, 2014[1979]; Hutto and Myin, 2013; Manzotti, 2019; Varela, Thompson, and Rosch, 1991). 4E models reconceptualize the mind rhetorically and functionally as a brain-body unit moving through an environment composed of artefacts of the mind (Wilson, 2002). This approach emphasizes a biological metaphor of systems that includes the holistic integration between the organism and its environment (Laland et al., 2015). The mind is said to have been built out into the world, since the objects we created store aspects of the mind, like the built environment and technological gadgets (Barrett and Rendall, 2010). 4E approaches to cognition offer a biologically situated return to the spatialized, physical metaphors of the 19th century. The emphasis on the body as a system relating to its ecological niche seeks to put flesh back on the bones of the rarefied computer metaphors of the cognitive sciences. It also purports to avoid dualism by adopting a neutral monist language to describe the organism in its environment. This anti-representationalism draws from the vehicle of images rather than that of propositions. For example, ecological psychologists describe how we adjudge moving objects based on optic flow on the retina rather than resorting to internal representations of movement in the brain (Loomis and Beall, 1998).

Models that emphasize dynamic mechanics in neural systems hearken back to the metaphor of mind as machine, portraying it as a sophisticated set of mechanisms that produce determinate regularities (Chemero and Silberstein, 2008). Contemporary dynamic and heuristic models of the mind, through associational fields in engineering, emphasize constraints upon computation. Some theorists emphasize the role of temporal and non-linear factors (see Colombetti, 2017; Cosmelli, Lachaux, and Thompson, 2007; Eliasmith and Anderson, 2003; Van Gelder, 1995), while others dwell upon the active, autonomous, and adaptive qualities of the biological mind (see Bechtel, 2008; Bechtel and Richardson, 2010) or the limited resource capacities of neural systems as energy resources (Pessoa, 2013). Likewise, bounded rationality is founded on the notion that the mind is a logical machine under time and resource constraints that require adaptive heuristic shortcuts, including predictive and Bayesian processing (Barsalou, 2009; Gigerenzer, 2015; Oaksford and Chater, 1994; Serre et al., 2007; Simon, 1982). Refinements of these models continue; for example, the coding metaphor of neural communication and storage has been criticized as not sufficiently taking into account the causal structure of the brain and the informational requirements of cognition (Brette, 2019).

Dynamic mechanics and bounded rationality models locate weaknesses in previous computational metaphors and instead offer concepts drawn from engineering and information theory. In bounded rationality, the optimal logic of computers is contrasted with human rationality to reveal that heuristic mechanisms such as imitation, tallying, and tit-for-tat are necessary to account for human capacities (Gigerenzer, 2010). These models seek the qualifications of ecological validity and parsimony as a reaction against the overly theoretical nature of strong artificial intelligence. Bounded rationality seeks to avoid the Panglossian adaptationism of evolutionary psychology and optimal observer models used in psychophysics by taking into account the limitations of biological minds relative to computer models. Specifically, time, attention, speed, and bandwidth are cited as limitations of the mind. This anchors analysis of the mind in the design project of engineering. Dynamic mechanics similarly adds the variables of time and energetics as a reaction to the insufficient formulation of temporal dynamics in cognitive modelling. The notion of limits and constraints in materials is drawn from the associational fields of engineering and machine learning. For example, towards broader explanations of the organization of learning, Gallistel (1990) describes dead reckoning in insects through the variables of time, gravity, and basic sensation.

Many of the models that draw from these predominant metaphors can be related to each other. For example, by virtue of rejecting a disembodied and passive notion of the mind, 4E may be melded to a dynamic (e.g. Chemero, 2011; Colombetti, 2017) or affective approach (Carruthers, 2008; Gabriel, 2021; Proust, 2015). Eventually, models that employ biological metaphors (e.g. affective sciences, enactivism) could converge. The mechanistic nature of the dynamic model is easily applied to biological entities (Bechtel and Abrahamsen, 2010; Craver, 2005).

Pragmatic analysis of contemporary metaphors

Similar to the shift Aristotle enacted by repositioning the soul as a set of capacities rather than Platonic categories, a pragmatic approach must suggest an empirically limited phenomenon, a set of verifiable causal units, and ultimately make possible new, useful knowledge. Ultimately, the metaphor adopted by researchers matters for pragmatic testability and thus bears upon the very viability of the human sciences project as such (Rose, 2006). When the metaphor is suitable to the explanatory task, meaningful empirical work is generated. Inappropriate metaphors endanger the feasibility of studying the mind by reifying illusory concepts or limiting the horizons of explanation (Klein, 2017; Uttal, 2011).

A researcher's decision between models and their metaphors will depend upon whether the metaphor achieves precision, plausibility, and a set of interesting and powerful consequences for a systematic understanding of the explanandum (Gentner and Grudin, 1985). When alternative theories are equally compatible, humans tend to choose a theory based on temperament, or extra-theoretical considerations like elegance or economy (James, 1972[1907]: 83). The metaphors and the respective models discussed above have been fruitful in generating empirical programmes; they are each plausible in a naturalist ontology that seeks a systematic understanding of the mind.

The method by which the precision of each metaphor will be cashed out varies (Asay, 2018). Dynamic neural models employ the methodological tool of decomposition into structural and functional aspects, as well as complex computational modelling (Bechtel and Abrahamsen, 2010; Bechtel and Richardson, 1992), whereas 4E models complicate the constitution of mind by emphasizing body/world loops that are constitutive of knowledge and information transfer. We must choose the appropriate metaphor for the phenomenon at hand by explicitly weighing the experimental and pragmatic consequences of our choice.

The rise of biology and engineering metaphors is a consequence of great theoretical advances in the 20th and early 21st centuries in genetics, cell theory, evolution, and the material sciences. This knowledge was almost instantly applied to the technology that shapes the sociocultural landscape we inhabit. The modern pipeline between public and private research laboratories in the natural sciences and applied fabrication in the private sector has been effective. In response, psychologists, who were previously considered natural philosophers, have gone to great lengths to be considered as behavioural scientists engaged in perceptual sciences (Smith, 1997). Adopting metaphors and methods from biology and engineering is a continuation of these efforts. Engineering continues the mechanistic metaphor of matter to which psychology adhered in its behaviourist and cognitive science paradigms, though drawing from biology may entail a hasty commitment to scientific naturalism (Klein, 2021).

Contemporary experimental psychology has developed sophisticated tools beyond reaction time and rudimentary psychophysics to image the brain. Some insights include the creation of psychoactive medication, like benzodiazepines, developed in partnerships between clinicians and neuropharmacologists. Reverse-engineering the brain by starting with the function, say face recognition, and then working backwards to try to build a process that may accomplish the function allows for functional analysis that may eventuate in effective therapeutic measures in cognitive behavioural therapy.

Drawbacks of descriptive models

We may also enquire into the drawbacks of employing these descriptive and functional metaphors. Whereas discursive approaches to the mind like humanism and psychoanalysis allowed for agentic discourse, descriptive metaphors like biology and engineering tend to emphasize the mechanistic aspects of the mind (Chemero and Silberstein, 2008; Rieff, 1979). When a metaphor is discursive, the actor maintains agency and can exercise control or self-regulation – even if it is only rhetorical – over the mind (Bandura, 1991; Cervone, 2004), whereas a mechanistic metaphor as a description of mental processes generally does not leave space for the agentic control of the phenomenological subject. Discursive models allow for the efficacy of introspection (Lo Dico, 2018); this is because the conscious act of introspection is a linguistic dialogical process that, as in symbolic interactionism, contributes to the process of self-making (Hermans, 2001; Mead, 1934). By way of illustration, Sigmund Freud's hydraulic metaphor of unconscious energy served as a way to engage in discursive analysis regarding the power of repressed memories upon our behaviours, whereas his later topographic model was as a descriptive mechanical spatial metaphor of how memories interact with each other vis-à-vis their position in a mental space (Freud, 1963[1915]).

We can expect that descriptive explanation will tend to reductionism, most likely in the form of formal mechanistic models. Discursive explanation of the human mind, on the other hand, situates it in the broader context of history and culture. 4E models seek an integrative, ecologically valid description of perceptual and motor processes that is ultimately to be couched in biological terms of the organism in its environmental niche. Dynamic systems models are descriptive levels of function and structure supporting emergent formal causes modelled as control variables ultimately couched in mechanistic engineering metaphors (Chemero and Silberstein, 2008; Craver, 2005). There may be ways to locate agency or human values in this frame, since mechanistic explanation leaves room for higher-level theories (Bechtel, 2008; Craver and Bechtel, 2007).

We can expect bounded rationality models to describe the building blocks of practical reason as satisficing information-processing algorithms, as seen in the implementation of ‘nudge’ infrastructures in economic situations (Gigerenzer, 2010). The descriptive, computational metaphor of bounded rationality suggests we are endowed with an adaptive toolbox that frames the world in domain-specific heuristics that guide searches, stop searches, and make decisions (Gigerenzer and Todd, 1999). These non-optimal heuristics are matched to particular environments; they demonstrate the boundedness of rationality to its environmental niche and capacity limitations, including time, and computationally cheap, fast, frugal resources (Todd, 2001). This metaphor leans on a notion of the mind as an imperfect adaptive mechanism, which allows us to draw from the language of process, optimality, and other terms from engineering (Bechtel and Abrahamsen, 2010). While Gigerenzer (2010) makes room for social heuristics in moral behaviour, the framing of behaviour in the field as evolutionarily adapted traits conflicts with our agentic notions of self-mastery and the possibility of self-betterment and efficiency through wilful transformation of character.

Models derived from biological metaphors always connect the mind to other phenomena in nature. From such models we can expect a naturalist epistemology wherein the mind is understood as a material phenomenon, similar to the mind-as-entity metaphor of the Victorian physiologists but with far more detail and less emphasis on spiritual aspects. As an example of a biological metaphor, neo-Darwinism and evolutionary psychology use the model of adaptation to theorize the function and structural origin of the mind. Early versions of this approach, like Freud's drive theory and the selfish gene theory (Dawkins, 1989), had the consequence of denying the dignity of man insofar as agency was portrayed as being in the service of impersonal biological drives. In fact, both psychoanalytic and psychiatric theories minimize the role of intention, the former by locating it in the unconscious and the latter by reducing it to neurochemistry (Luhrmann, 2000).

Discursive models

Adopting a discursive or descriptive approach to the mind has pragmatic consequences for an individual's sense of meaning and for ethical considerations (Gould, 1997). Indeed, the way we experience and act in the world can be structured by the metaphors we adopt (Lakoff and Johnson, 2003). For example, one's conception of social hierarchy, of top-down or bottom-up economic forces, has immediate social and political utility (Hoffman, 1979). On this front, cognitive science has been criticized for being too individualistic by focusing all its explanations on the mental processes of the individual (Putnam, 1975); in doing so, it fails to take into account discursive cultural factors that convey the complexity of lived experience and the efficacy of shared symbols. Taking these macroscopic cultural factors into account requires the discursive exercise, common in the human sciences and humanities, of considering how ideas, institutions, and social encounters sculpt the mind.

While it is primarily the responsibility of psychology to cultivate its discursive practices, which already thrive in clinical practice as well as in sectors of social and personality psychology, the humanities must maintain their ability to protect difference by continuing to communicate a diverse international pool of topics and scholars. To maintain discursive and agentic situatedness, the reflexivity of the human sciences must be brought to bear on an interdisciplinary psychology. Even though the neuro-disciplines will lose the veneer of being wholly ‘scientific’, it is worthwhile for psychology to cultivate knowledge of other disciplines in order to generate more common ground for discussion, mutual learning, and possibilities for investigation. As it stands, neuro-disciplinarians hold a coveted position: they take the biological and engineering metaphors to mean that they are tracing the biology of human nature and that with the help of computer scientists/engineers they will be able to develop technologies for the sake of efficiency and eventually to create intelligent life. In fact, their adherence to such hopes indicates a lack of contextual understanding of the history of the human sciences and, moreover, an impoverished notion of the ‘human’ (Vidal and Ortega, 2017).

The role of humanist discursive models of the mind in relation to biological and engineering metaphors in psychology is thus to enable consideration of broader contextual stories. To take one example, Barbara Maria Stafford’s (1999) work on analogical thinking suggests that a path to understanding consciousness is available to us in the concept of analogy. Such an approach examines how comprehension is an active, imaginative form of grasping sense data via making connections, just like in the shadow boxes of Joseph Cornell, or cabinets of curiosities that allow our associative faculties to generate bonds between the inside world of thought and the outside world of objects. This non-reductionist approach creates space for phenomenology and the creative labour of perceiving and thinking about the world in symbols. This metaphorical frame of thought as an analogical process is pragmatic as a generator of discourse concerning the relation between the arts, imagination, and analogical thinking (Asma and Gabriel, 2019); it provides a lens through which the history of art objects is simultaneously a discourse on imagination. This model could easily inform empirical work on visual pattern recognition. Stafford's work cannot be used to make predictions, but it does offer an example of a rich interpretative context in the humanities through which researchers can identify relationships between abstract principles of analogy and concrete examples of historical art objects.

In considering further how we portray knowledge, whether in a set of formulas or schematics, a flowchart of mechanical models, or a well-illustrated academic monograph, we can see that the communication of findings is aided by metaphors that are legible and easily displayed. In addition to the traditional purpose of models to enable balance, symmetry, and order, the syntax of a new language of visual models allows insight into the nature of interconnectedness, multiplicity, and the decentred nature of the contemporary search for knowledge (Lima, 2013). Ultimately, a pragmatic assessment of metaphors of mind helps us to determine whether or not the fictions we use adhere to the broader goals of the human sciences.

Discussion

Consideration of the role of metaphor in scientific practices generates engagement with ontological and epistemological issues that are at the marrow of our desire to capture the world in thought. At base, metaphor provides a communicable order of things (Foucault, 1966). Due to the range of phenomena and the diverse uses of knowledge, metaphors can be descriptive or explanatory, illustrative or constitutive, informative or evaluative, revealing or masking, and enriching or deforming (Leary, 1990: 364). In this section, metaphors of mind are assessed with regard to their metaphysical consequences.

The transcendental realist position is that metaphors explain regularities and dispositional attributes at various levels of macroscopic and microscopic order that are beyond empirical experience (Bhaskar, 1975). The revelation of hidden structural elements in nature thus allows an extension of the reach of scientific understanding. In the service of grasping aspects of the natural world that exist but are beyond our empirical ken, metaphor reorders the semantic field by generating new intensional contents (Harré, 2004: 124). This is generally a boon for gaining a theoretical understanding of nature, but it could blinker our view of the phenomenon by focusing our attention on one aspect rather than another. For example, classifying phenomena via a tree metaphor orders evidence very differently than the family resemblance model, thus obscuring the subtleties of the latter frame (Lima, 2014). Metaphors can be abused when this tool for tentative description becomes a tool of presumptuous prescription (Leary, 1990). By shifting how we individuate the elements of nature that we believe we are studying, metaphor use can lead to unwarranted reification and confusion about the structure and delineation of natural kinds (Greenberg, 2013; Khalidi, 2013). For example, the rise of brain imaging technologies transformed our notions of causation, reifying the esoteric techniques and the interpretative palette of localization (Uttal, 2011).

Our choice of models is important for the experimental programmes we pursue. The way in which we pivot between models reflects shifting paradigms relative to social and cultural context (Jasanoff, 2004; Kuhn, 2012). The paradigm shift to the cognitive sciences in the late 20th century, for example, reflected changes in the accepted foundations of the mind from associationist network to computer, areas of interest from reward learning to linguistics and visual search, and modes of investigation from reinforcement schedules to the modelling of thought as an algorithm. At each step, we are in danger of reifying theoretical or methodological entities due to overextending the metaphor. Paradigms based on new metaphors function as ‘theory plus’ additional methodology, instruments, and metaphysical suppositions (Scheffler, 1967; Shapiro, 1985). For example, the cognitive revolution was a theory that the mind functioned like a computer (i.e. strong and weak AI) plus the methodology of modelling; instruments for tracking reaction time, eye gaze, and so on; and the metaphysical assumption of scientific naturalism. This is exemplified in the work of David Marr (1975) and a range of paradigms from Fodor’s (1983) modularity of mind to the modelling of object perception with optimal observers.

Alternatively, a paradigm may just be an exemplary solution to an earlier problem faced in the field (Giere, 1999), in which case the truth of a paradigm is its pragmatic success as a verificationist, or empirically adequate, process for investigating an earlier problematic (Van Fraassen, 1980). This approach reflects a strong pragmatism wherein we are no longer connecting scientific endeavour with the philosophical notion of truth as correspondence with reality, but rather binding experimentation to our tools, models, and metaphorical frames (Rorty, 1979).

The method by which we investigate a given phenomenon, be it via recording reaction times or measuring cortisol levels, is motivated by the ontological frame of the underlying causal story of the behaviour. A given scientific theory is a family of models ranging from small-scale to macroscopic causal stories. Shifts in scientific terminology indicate increasing specificity while also reflecting a greater sense of authority for certain schools within the intellectual community. The metaphor in ascent at any given time devours the research resources in the field (Bloor, 1976). Each generation of scientists receives an education within a given set of metaphorical frames that have a buzz in that era; to a large extent, this determines what these individuals find worth studying. The success of a generation of scientists depends upon securing useful, illustrative, informative, revealing, verifiable metaphorical frames for empirical work and then demonstrating how the adopted metaphor enables progress in picking out ontologically real and verifiable elements of nature. In this way, methodology is the practical instantiation of the link between pragmatism and metaphor. By employing metaphors drawn from biology and engineering, contemporary psychology is pragmatically wedded to their methodological apparatus.

While scientific knowledge is relevant to our medical and biological investigations of the natural world, as a human science psychology additionally bears upon ethical and existential questions and thus must take into account notions of responsibility and meaning. If psychology is the study of human nature, then what kind of explanatory model of ourselves do we need? What makes a particular metaphor more apt is how aesthetic, moral, practical, and intellectual rationality is brought to bear on the truthfulness of a metaphor (Leary, 1990). To bring in a further Nietzschean consideration, scientists and laypersons, within reasonable boundaries, will tend to conceive of the nature of the mind and reality according to what they want the truth to be. Beliefs are mired in affective needs (Asma and Gabriel, 2019; James, 1972[1907]). There's a human weakness to letting belief ride on emotional factors such as ‘lively conception’ and ‘instinctive liking’ (James, 1956[1897]). Ultimately, the most pragmatic approach to metaphors as forms of explanation is that we need an understanding of the world sufficient to our needs (Lakoff and Johnson, 2003). To understand the motivation to explain, I conclude with a discussion of metaphors of mind in popular culture and the ethical function of explanation.

Explanation

In its pragmatic aspect, scientific explanation refers to evidence unto facts in the form of cause and effect processes, classification systems, laws, data, observations of empirical tests, and so on. That is, a model explains by pointing to concatenated evidence in the service of systematic understanding. This accumulated image of the phenomenon can thereafter be harnessed towards technological innovation or simply more veridical ways of perceiving the world. The purpose of explanation in the sciences is thus to discover facts and subsequently to elaborate upon this evidence through technology like machines, and pharmaceutical drugs, towards making life easier or more pleasurable through alleviating or simplifying tasks and problems. The explanatory metaphor in the psychological sciences is itself ultimately a tool for appraising the mind and our position in the world (Heyes, 2018; Sterelny, 2014). In this way, it supplements and guides hypothetico-deductive modes of explanation.

Turning to the models summarized above, we can enlist perspectival realism to contextualize how a scientist must do their best to explain phenomena given (a) the limitations of their perspective, and (b) how much of a theory is underdetermined by the evidence (Giere, 2006). Whereas a reductionist functional approach has more esoteric, technological applications, an holistic, discursive approach lends itself more readily to practical use in lay psychology. If we were to attempt to satisfice our practical needs with a model, we ought to turn to discursive metaphors like those of the humanities and their interdisciplinary models, the affective sciences, bounded rationality, and, in a non-scientific frame, faith. On the other hand, if our goal is to provide a totalizing explanatory model, the mechanistic frames of dynamic mechanics plus some evolutionary theory offer useful metaphors and models. But there is a trap lying in wait for scientists who achieve success with a particular methodology: they begin to pose only problems that are likely to be solved with the metaphor at hand, thus obscuring both the phenomena and the explanatory efficacy of science (Lewontin, 2000). Some argue that this is precisely the corner into which the psychological sciences have painted themselves by adopting a materialist, mechanistic metaphor to explain the inherently subjective phenomenon of the mind (Klein, 2014, 2017).

The public is increasingly informed about the brain as the assumed epicentre of thought, though many of the details are liable to distortion. We live in a culture where discourse about the causal supremacy of the brain abounds (Frazzetto and Anker, 2009; Smith, 2019), even though the claim is marginally connected to actual empirical advances (Vidal and Ortega, 2017). General findings from experimental psychology filter into the broader intellectual world at a steady rate, though no hegemonic metaphor of mind spans popular and technical uses of psychology. It seems most likely that an explanatory and causal pluralism will be our best bet in the long run (Chemero and Silberstein, 2008).

Interdisciplinary psychology

How we unpack the nature of the mind and the role of culture seems to require not only successful experiments and contextualized brain imaging but also scholarly interaction with systems of knowledge both within (i.e. anthropology, sociology, humanities, etc.) and outside (i.e. biology, genetics, engineering, etc.) the human sciences. Ideally, the metaphors of mind with which we move forward will neither obfuscate human dignity nor reify technological methods. It is the responsibility of the psychological sciences to seek out and eventually deliver the metaphor(s) that encapsulate the function, context, and purpose of the mind. In this context, a discursive, biological model with space for descriptive localized reduction may be the most pragmatic metaphor of mind.

Ideally, an interdisciplinary psychology that followed this path of mixed metaphors for descriptive and discursive needs would allow for creative uses of psychology in the arts and the contextual factors provided by the historical sciences. Additionally, it would maintain roots in anthropology to secure a story of sources: for example, what use does psychology play in a given locale and in what terms? How do the methods employed speak to other elements of the culture and its unique historical approach to reality?

Similar to how we traced conceptual evolution through the use of metaphor, psychology can be seen as a historical anthropology of the soul of the century; a tracing of subtle forces. According to Smith (2019: 15), the task of the history of the human sciences vis-à-vis an interdisciplinary psychology is to develop relations between different purposes and forms of understanding and encompass the reflexive links between knowledge and practice. A given age's ways of conceiving of the mind are a blueprint of the desires and cosmologies now entombed. Through this study of the pragmatic uses of metaphor, we can consider psychology not as a cumulative positivist project but rather as a palimpsest of past paradigms plus the methodologies and pathologies of the present. In other words, ‘historical knowledge contributes narrative, and the understanding of narrative is fundamental to the notion of being human; human self-knowledge and action are mutually constitutive, or, belief changes a person and what a person does changes belief’ (ibid.: 17).

Recent work in psychology, for example, questions accepted metaphors and models through the use of cross-cultural data (Henrich, Heine, and Norenzayan, 2010; Muthukrishna, Henrich, and Slingerland, 2021). The biggest challenge to transforming what we expect from psychology is that practitioners are unlikely to give up the fruitful high ground of technological and epistemological eminence. Nevertheless, psychologists and philosophers would benefit greatly from adding reflexive human sciences and anthropological methods to their knowledge practices, not only because they would be more capacious interlocutors and collaborators but because the lack of context for the uses of psychology obscures the significance and meaning of its findings. This article has been a way to get at these issues because metaphors of mind employed in a given period are ineluctably drawn from the available localized knowledge practices. It is time empirical psychology included historical context and anthropology so that in addition to descriptive principles of mechanism, psychologists could discursively approach phenomena as part of our broader cultural projects.

Footnotes

Declaration of conflicting interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Rami Gabriel

Notes

Author biography

Rami Gabriel received his doctorate in cognitive and perceptual sciences in 2007 under Dr Stanley B. Klein for a dissertation on prosopagnosia and the relation between emotion and cognition. His main research interests are the philosophy of psychology, affective neuroscience, consciousness studies, self, and identity. Recent publications include Why I Buy: Self, Taste, and Consumer Society in America (Intellect Press, 2013) and (with S. T. Asma) The Emotional Mind: Affective Roots of Culture and Cognition (Harvard University Press, 2019). His upcoming book, A Suspicious Science: The Uses of Psychology, will be published by Oxford University Press in 2022.

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