Neuroimaging technology is the most widely used tool to study human cognition. While originally a promising tool for mapping the content of cognitive theories onto the structures of the brain, recently developed tools for the analysis, handling and sharing of data have changed the theoretical landscape of cognitive neuroscience. Even with these advancements philosophical analyses of evidence in neuroimaging remain skeptical of the promise of neuroimaging technology. These views often treat the analysis techniques used to make sense of data produced (...) in a neuroimaging experiment as one, attributing the inferential limitations of analysis pipelines to the technology as a whole. Situated against the neuroscientists own critical assessment of their methods and the limitations of those methods, this skepticism appears based on a misunderstanding of the role data analysis techniques play in neuroimaging research. My project picks up here, examining how data analysis techniques, such as pattern classification analysis, are used to assess the evidential value of neuroimaging data. The project takes the form of three papers. In the first I identify the use of multiple data analysis techniques as an important aspect of the data interpretation process that is overlooked by critics. In the second I develop an account of inferences in neuroimaging research that is sensitive to this use of data analysis techniques, arguing that interpreting neuroimaging data is a process of isolating and explaining a variety of data patterns. In the third I argue that the development and uptake of new techniques for analyzing data must be accompanied by changes in research practices and standards of evidence if they are to promote knowledge generation. My approach to this work is both traditionally philosophical, insofar as it involves reading and analyzing the work of philosophers and neuroscientists, and embedded insofar as most of the research was conducted while engaged in attending lab meetings and participating in the work of those scientists whose work is the object of my research. (shrink)

An explanatory gap ensues when the truths constituting the explanans do not entail the explanandum. Attempts to give a physicalist account of consciousness seem to generate an explanatory gap, which is special in the following psychological sense. In other cases, it is possible to bridge or close the gap by regimenting or eliminating the respective concepts. In the case of consciousness, however, there is a pervasive intuition that the gap remains even when one works out a notion of consciousness that (...) allows the entailment of truths about consciousness from physical premises. The intuition is expressed by the sense that something essential about consciousness is left out from any such conceptual regimentation. This paper defends the view that this intuition is generated by the way our experiences are given to us. Every experience has a component that is not captured by any specification. The gap intuition is due to this ineffable component in experiences. Since conscious experiences are partly ineffable, it seems that no account of consciousness captures conscious experiences entirely and so would develop the intuition that something has been left out. An alternative explanation to the gap intuition is provided by the “phenomenal concepts’ strategy”. According to this strategy, it is the peculiar nature of phenomenal concepts that feeds the intuition. The main problem with such an approach is that phenomenal concepts are more coarse-grained than the experiences themselves and thus their application still does not entail what it is like to have a particular phenomenal experience. (shrink)