The so-called “dark room problem” makes vivd the challenges that purely predictive models face in accounting for motivation. I argue that the problem is a serious one. Proposals for solving the dark room problem via predictive coding architectures are either empirically inadequate or computationally intractable. The Free Energy principle might avoid the problem, but only at the cost of setting itself up as a highly idealized model, which is then literally false to the world. I draw at least one optimistic (...) conclusion, however. Real-world, real-time systems may embody motivational states in a variety of ways consistent with idealized principles like FEP, including ways that are intuitively embodied and extended. This may allow predictive coding theorists to reconcile their account with embodied principles, even if it ultimately undermines loftier ambitions. (shrink)

A common kind of explanation in cognitive neuroscience might be called functiontheoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function constitutes (in the system’s normal environment) the exercise of the cognitive capacity. Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it reveals (...) the causal structure of the mechanism underlying the capacity. If they are right, then a cognitive model that resists a transparent mapping to known neural mechanisms fails to be explanatory. I argue that a functiontheoretic characterization of a cognitive capacity can be genuinely explanatory even absent an account of how the capacity is realized in neural hardware. (shrink)

Saying that psychological states are functional states, the functionalist claims more than that psychological states have functions. Rather, functionalism is the theory that psychological states are defined and constituted by their functions. On this view, what it is to be a psychological state of a certain sort just is and consists entirely of having a certain function. Anything that has that function in a suitable system would therefore be that psychological state. If storing information for later use is the essential (...) function of memory, then anything that has that function counts as a memory. Similarly, one might say that anything that traps or kills mice counts as a mouse trap. (shrink)

Proponents of mechanistic explanation have argued that dynamical models are mere phenomenal models, in that they describe rather than explain the scientific phenomena produced by complex systems. I argue instead that dynamical models can, in fact, be explanatory. Using an example from neuroscientific research on epilepsy, I show that dynamical models can meet the explanatory demands met by mechanistic models, and as such occupy their own unique place within the space of explanatory scientific models.

A common kind of explanation in cognitive neuroscience might be called function-theoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function constitutes the exercise of the cognitive capacity (in the system's normal environment). Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it reveals (...) the causal structure of the mechanism underlying the capacity. If they are right, then a cognitive model that resists a transparent mapping to known neural mechanisms fails to be explanatory. I argue that a function-theoretic characterization of a cognitive capacity can be genuinely explanatory even absent an account of how the capacity is realized in neural hardware. (shrink)

We have some justified beliefs about modal matters. A modal epistemology should explain what’s involved in our having that justification. Given that we’re realists about modality, how should we expect that explanation to go? In the first part of this essay, I suggest an answer to this question based on an analogy with games. Then, I outline a modal epistemology that fits with that answer. According to a theory-based epistemology of modality, you justifiably believe that p if you justifiably believe (...) a theory that says that p and you believe p on the basis of that theory. (shrink)

A common kind of explanation in cognitive neuroscience might be called function-theoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function constitutes (in the system’s normal environment) the exercise of the cognitive capacity. Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it reveals (...) the causal structure of the mechanism underlying the capacity. If they are right, then a cognitive model that resists a transparent mapping to known neural mechanisms fails to be explanatory. I argue that a function-theoretic char-acterization of a cognitive capacity can be genuinely explanatory even absent an account of how the capacity is realized in neural hardware. (shrink)

The thesis is about Multiple Realization. Multiple realization is roughly the idea of a higher level property being multiply realized by different lower level physical properties. Philosophers usually argue that if a property is multiply realized, it is not reducible to its realizers. Mobilized as such, multiple realization plays a central role in what is usually called Non-Reductive Physicalism. Despite its popularity, and beyond the hunches and intuitions that back the concept, seldom do philosophers consider the nature of multiple realization. (...) The central aim of the thesis is to tackle the somewhat overlooked question: “what is multiple realization?” The rationale is that to find out what philosophical tasks multiple realization can accomplish, we have to know what multiple realization is. The thesis proceeds as follow: In chapter 2, I’ll argue for a methodology for the entire project in answering the question. I’ll argue that there are four desiderata we want from any account of multiple realization, namely, Multiplicity, Naturalness, Physical Realization, and Anti-Reductionism. We should look for an account of multiple realization that could respect the four desiderata in a philosophically satisfactory way. In chapter 3, I’ll look at the alleged origin of multiple realization, Jerry Fodor’s. I’ll reconstruct Fodor’s account of multiple realization. I’ll argue that the major bug of Fodor’s account is his failure in respecting Physical Realization. In chapter 4, I’ll examine Jaegwon Kim’s important critique of Fodor. I’ll argue that Kim’s criticism can be reconstructed as an account of multiple realization that intentionally violates Naturalness. In chapter 5, I’ll look at what I call the Causal Power Subset View of multiple realization as suggested by some philosophers around the turn of the 21st century. I’ll reconstruct an account of multiple realization from their works and argue that their account faces difficulties in reconciling Physical and Anti-Reductionism. I’ll further argue that their account nudges us toward a representational reading of Anti-Reductionism, according to which our seeming commitment to the higher level realized property is, in fact, a partial representation of a complex physical state. In chapter 6, I develop the aforementioned suggestion into a fuller picture. I’ll sketch a representational account of multiple realization and elucidate its plausibility. One result of the thesis is that the desiderata motivating a theory of multiple realization are in tight tension. One has to choose among them. My approach is no exception. I choose to give up Anti-Reductionism and Naturalness, but, as a remedy, I attempt to explain and make sense of the motivations and intuitions backing these two desiderata, arriving at a picture that I am comfortable with, after traveling the long journey. (shrink)

Absence of evidence arguments are indispensable to comparative neurobiology. The absence in a given species of a homologous neural architecture strongly correlated with a type of conscious experience in humans should be able to be taken as a prima facie reason for concluding that the species in question does not have the capacity for that conscious experience. Absence of evidence reasoning is, however, widely disparaged for being both logically illicit and unscientific. This paper argues that these concerns are unwarranted. There (...) is no logical barrier to formulating cogent absence of evidence arguments; indeed, accepting such arguments is part of what it is to be committed to falsifiability as a critical aspect of the scientific method. Absence of evidence arguments can always be blocked, however, by assuming that psychological properties are ‘multiply realizable’. While we take multiple realizability to be highly likely at some level of analysis, we argue that it is question-begging to assume that it exists at every level of analysis, and thus it should not automatically be thought to undermine absence of evidence reasoning in the animal consciousness debate. Using the example of pain and focusing on homologies at the level of information processing tasks, we show how, in the science of consciousness, an absence of evidence might well serve as evidence of absence. (shrink)

It is widely assumed that functional and dispositional properties are not identical to their physical base, but that there is some kind of asymmetrical ontological dependence between them. In this regard, a popular idea is that the former are realized by the latter, which, under the non-identity assumption, is generally understood to be a non-causal, constitutive relation. In this paper we examine two of the most widely accepted approaches to realization, the so-called ‘flat view’ and the ‘dimensioned view’, and we (...) analyze their explanatory relevance in the light of a number of examples from the life sciences, paying special attention to developmental phenomena. Our conclusion is that the emphasis placed by modern-day biology on such properties as variability, evolvability, and a whole collection of phenomena like modularity, robustness, and developmental constraint or developmental bias requires the adoption of a much more dynamic perspective than traditional realization frameworks are able to capture. (shrink)