Relations between Disciplines

Insofar as cognitive science presents itself as interdisciplinary, it is important to consider how disciplines can integrate. Much of the philosophical discussion of interdisciplinary relations has focused on the question of reduction and the particular model of reduction advanced by philosophers in the mid-twentieth century.

Using this model, philosophers have debated whether the theories of one cognitive discipline, psychology, reduce to those of another, neuroscience (Fodor 1974, Churchland 1986). On the theory reduction model (Nagel 1961), theories are construed as linguistic statements, ideally organized in an axiomatic form, and reduction involves the derivation of the theories of the reduced science from those of the reducing science. One of the requirements of a valid reduction is that common vocabulary is used in the premises and the conclusion. Since this is typically not the case in the relation between neuroscience and psychology, additional premises are required, bridge principles that relate the vocabulary of one discipline to that of the other. Much of the controversy over the reducibility of psychology to neuroscience has turned on the issue of whether appropriate bridge principles can be generated. Fodor (1974) argues that bridge principles are not possible since the concepts used in neuroscience group phenomena in very different ways than those employed in psychology. One version of the argument appeals to the claim that psychological states can be realized in very different types of brains, in which very different states realize the same psychological predicates (Putnam 1967; a claim questioned by Bechtel and Mundale 1999).

The theory reduction account fails, in many ways, to characterize the interactions between disciplines that are characteristic of cognitive science, such as between psychology, AI, linguistics, and philosophy.

Although theories are sometimes the point of engagement, many of the engagements go beyond theories, and involve the utilization of techniques of inquiry from different disciplines and the combining of explanatory approaches (e.g., computational modeling from AI in psychology). Finally, it even fails to capture the sort of relations one actually finds between psychology and neuroscience that are characterized as reductionist, since the focus is seldom on deriving one body of theory from another, but rather on working out a mechanism responsible for a phenomenon. Insofar as a mechanism involves both an account of the parts and what they do, and an account of the organization in the whole mechanism and how it confronts its environment, a mechanistic account is inherently an interlevel account to which research on both lower and higher levels contributes.

Lindley Darden and Nancy Maull (1977) introduced the notion of an interfield theory as an alternative account of how theories can relate the results of inquiries in different fields. On this account, the product of interactions between fields or disciplines is not the logical derivation of the theories of one field from those of another, but the integration of information procured in multiple fields to address a common problem. Interfield theories typically develop when investigators in different fields possess different tools which each provide part of the information needed to address the phenomenon of interest. The quest to draw and coordinate resources from contributing disciplines to explain phenomena of shared interest is characteristic of cognitive science. For example, while linguists have focused on developing grammars that account for the productive features of languages, psychologists have been concerned with the mental representations and psychological processes involved in language production and comprehension (Abrahamsen 1987). Different tools are needed and employed to formulate and test grammars than to propose and evaluate psychological mechanisms.

In addition, AI researchers contribute to trying to understand language by developing computational models, while neuroscience researchers offer evidence of the brain processes employed and the operations each can perform.

From the 1950s until the 1980s, neuroscience played only a marginal role in cognitive science. Neuroscientists were actively involved in the early interdisciplinary discussions that prefigured cognitive science, but their primary investigatory tools at the time, such as recording from single neurons, could not be employed on human subjects engaged in cognitive tasks. But beginning in the 1980s and especially through the 1990s, new non-invasive neural imaging techniques that could measure brain activity (using blood flow as a proxy) provided an avenue for linking psychological studies of behavior with information about brain activity. This research is often characterized as cognitive neuroscience and differentiated from cognitive science proper, but increasingly these tools are being invoked in cognitive science itself.

Much of cognitive science has focused on cognitive operations detached from affect (reflecting a long differentiation in philosophy between reason and emotion). Recent research in various cognitive science disciplines has challenged this segregation. For example, evidence has amassed that effective moral reasoning requires a proper integration of emotion and reason (Damasio 1995). Similarly, pathological conditions such as autism appear to involve deficits in both reasoning and emotion. A brief exploration of this research illustrates some of the most exciting interdisciplinary engagements in contemporary cognitive science.

Autism is a developmental disorder characterized by impairments in social interaction and communication, as well as repetitive and stereotyped patterns of behavior (think of the preoccupation with The People’s Court displayed by Dustin Hoffman's character in the 1988 movie Rain Man). While first under the purview of developmental psychology, autism has become the focus of study for a number of disciplines (see Volkmar, Paul, Klin, and Cohen 2005).

One issue has been to characterize more precisely autism's symptoms, particularly its social deficits. Developmental psychologists and neuropsychologists work to construct improved behavioral measures to capture the spectrum of deficits found in people with autism. Given more precise descriptions of the behavioral phenomena, researchers offer theories of the cognitive operations impaired in people with autism. Some propose that autism involves deficits in “executive functions” (skills such as planning, inhibition, and cognitive flexibility); others point to problems of “weak central coherence” (the general ability to integrate pieces of information into coherent or meaningful wholes). One of the most prominent theories explains autism's social deficits in terms of an impaired “theory of mind”: that autistic individuals cannot conceive of people's mental states, and thus cannot use this information to guide their social interactions.

While behavioral experiments are used to investigate the predictions of these explanatory proposals, researchers have increasingly turned to neuroscience to determine how the brains of autistic people differ (anatomically, functionally, developmentally) from those of unimpaired people and people with other psychological disorders. A popular neurobiological theory claims autism involves a dysfunctioning “mirror neuron system” (Williams, Whiten, Suddendorf, and Perrett 2001). Mirror neurons, which were first discovered in primates, fire both when an agent acts and when they observe other agents' actions. An analogous neural system has been found in humans in the pars opercularis of the inferior frontal gyrus, and is proposed to account for, among other things, our understanding of people's intentions, emotions, and other mental states. For example, Mirella Dapretto et al. (2006) argue that we normally understand the emotional significance of people's facial expressions because the mirror neuron system, in concert with the limbic system, causes this emotion to be “mirrored” in us; in this way we “feel” and accordingly understand the perceived person's emotion. Based on an fMRI study showing little activity in the mirror neuron systems of autistic children when imitating or perceiving emotional facial expressions, Dapretto et al. suggest they do not experience the emotions of perceived others in the way unimpaired people do. This proposal thus explains autism's deficits in social understanding and interaction in terms of the inability to automatically experience the emotions and other mental states of social interactants.

As autism research shows, explanations in cognitive science proceed using tools from a variety of disciplines. These tools are brought to characterize the parts, operations, and organization of the cognitive mechanisms underlying our mental abilities.

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Source: Allhoff F.. Philosophies of the Sciences: A Guide. N.-Y.: Wiley-Blackwell,2010. — 386 p.. 2010

Relations between Disciplines

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