Online research in philosophy

Blair argues that fluid cognition is dissociable from general intelligence. We suggest that a more complete understanding of this dissociation requires development of specific process models of the mechanisms underlying fluid cognition. Recent evidence indicates that relational integration and inhibitory control, both dependent on prefrontal cortex, are key component processes in tasks that require fluid cognition. (Published Online April 5 2006).

This paper discusses various problems of explanations by mechanisms. Two positions are distinguished: the narrow position claims that only explanations by mechanisms are acceptable. It is argued that this position leads to an infinite regress because the discovery of a mechanism must entail the search for other mechanisms etc. Another paradoxical consequence of this postulate is that every successful explanation by mechanisms is unsatisfactory because it generates new ``black box'' explanations. The second – liberal – position that is advanced in this paper regards, besides explanations by mechanisms, also the discovery of bivariate correlations as a first step of an explanation by mechanisms as meaningful. It is further argued that there is no contradiction between causal analysis and the explanation by mechanisms. Instead, explanations by mechanisms always presuppose the analysis of causal structures (but not vice versa). The final point is that an explanation by mechanisms is not inconsistent with the Hempel-Oppenheim scheme of explanation.

A recent movement in the social sciences and philosophy of the social sciences focuses on mechanisms as a central analytical unit. Starting from a pluralist perspective on the aims of the social sciences, I argue that there are a number of important aims to which knowledge about mechanisms—whatever their virtues relative to other aims—contributes very little at best and that investigating mechanisms is therefore a methodological strategy with fairly limited applicability. Key Words: social science • mechanisms • explanation • critical realism • methodology.

Although a reactive framework has long been dominant in cognitive science and neuroscience, an alternative framework emphasizing dynamics and endogenous activity has recently gained prominence. We review some of the evidence for endogenous activity and consider the implications not only for understanding cognition but also for accounts of explanation offered by philosophers of science. Our recent characterization of dynamic mechanistic explanation emphasizes the coordination of accounts of mechanisms that identify parts and operations with computational models of their activity. These can, and should, be extended to incorporate attention to mechanisms that are not only active, but endogenously active.

Mechanisms have become much-discussed, yet there is still no consensus on how to characterise them. In this paper, we start with something everyone is agreed on – that mechanisms explain – and investigate what constraints this imposes on our metaphysics of mechanisms. We examine two widely shared premises about how to understand mechanistic explanation: (1) that mechanistic explanation offers a welcome alternative to traditional laws-based explanation and (2) that there are two senses of mechanistic explanation that we call ‘epistemic explanation’ and ‘physical explanation’. We argue that mechanistic explanation requires that mechanisms are both real and local. We then go on to argue that real, local mechanisms require a broadly active metaphysics for mechanisms, such as a capacities metaphysics.

Simulation theory accounts of mind-reading propose that the observer generates a mental state that matches the state of the target and then uses this state as the basis for an attribution of a similar state to the target. The key proposal is thus that mechanisms that are primarily used online, when a person experiences a kind of mental state, are then co-opted to run Simulations of similar states in another person. Here I consider the neuroscientific evidence for this view. I argue that there is substantial evidence for co-opted mechanisms, leading from one individual’s mental state to a matching state in an observer, but there is no evidence that the output of these co-opted mechanisms serve as the basis for mental state attributions. There is also substantial evidence for attribution mechanisms that serve as the basis for mental state attributions, but there is no evidence that these mechanisms receive their input from co-opted mechanisms.

As much as assumptions about mechanisms and mechanistic explanation have deeply affected psychology, they have received disproportionately little analysis in philosophy. After a historical survey of the influences of mechanistic approaches to explanation of psychological phenomena, we specify the nature of mechanisms and mechanistic explanation. Contrary to some treatments of mechanistic explanation, we maintain that explanation is an epistemic activity that involves representing and reasoning about mechanisms. We discuss the manner in which mechanistic approaches serve to bridge levels rather than reduce them, as well as the different ways in which mechanisms are discovered. Finally, we offer a more detailed example of an important psychological phenomenon for which mechanistic explanation has provided the main source of scientific understanding.

Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction with their styles of modeling. In particular, mental operations often are conceptualized as comparable to the processes employed in classical symbolic AI or neural network models. These models, in turn, have been interpreted by some as themselves intelligent systems since they employ the same type of operations as does the mind. For this paper, what is significant about these approaches to modeling is that they are constructed specifically to account for behavior and are evaluated by how well they do so—not by independent evidence that they describe actual operations in mental mechanisms.

The project of referring to localized cognitive operations in the brain has a long history and many impressive successes. It is a core element in the practice of giving mechanistic explanations of mental abilities. But it has also been challenged by prominent critics. One of the critics’ claims is that brain regions are not specialized for specific cognitive operations and any science that refers to them is misguided. Most recently this claim has been advanced by theorists promoting a dynamical-systems perspective on cognition. There are, however, two ways to view the dynamical-systems perspective. The first is as a competitor to the mechanist perspective, rejecting altogether the conception of the brain as a mechanism or set of mechanisms underlying mental phenomena and thereby rejecting any reference to localized cognitive operations. The second is as a corrective to an overly simplistic conception of a mechanism and as complementary to a more adequate understanding of how mechanisms function. In this chapter I defend the later perspective. On this perspective, the traditional project of referring to localized mental operations in the brain is still important, but both the cognitive operations and brain regions in which they are localized must be conceived in the context of a dynamically active system.

The paper deals with two central issues in the philosophy of neuroscience and psychiatry, namely those of the nature and the major kinds and types of psychopathological mechanisms. Contrary to a widespread view, I argue that mechanisms are not kinds of systems but kinds of processes unfolding in systems or between systems. More precisely, I argue that psychopathological mechanisms are sets of actions and interactions between brain-systems or circuits as well as between the latter and other systems in one's body and external environment, both physical and social, involved in human psychopathology. According to the kinds of properties of the interacting systems or their component-parts, psychopathological mechanisms may be physical, chemical, biological, psychological, social, or, typically, mixed ones. Furthermore, I focus on two main kinds of psychopathological mechanisms involved in the causation of mental disorders, namely the pathogenetic and pathophysiological ones, stressing the importance of their careful distinction for the integrative understanding of otherwise disparate and apparently incommensurable psychiatric research findings. I illustrate my analysis with an example drawn from contemporary research on the mechanisms of acute psychosis. Finally, I stress the relevance of psychopathological mechanisms to a more scientifi cally-grounded classifi cation of mental disorders.