In the current chapter, I examined the relationship between the cerebellum, emotion, and morality with evidence from large-scale neuroimaging data analysis. Although the aforementioned relationship has not been well studied in neuroscience, recent studies have shown that the cerebellum is closely associated with emotional and social processes at the neural level. Also, debates in the field of moral philosophy, psychology, and neuroscience have supported the importance of emotion in moral functioning. Thus, I explored the potentially important but less-studies topic with (...) NeuroSynth, a tool for large-scale brain image analysis, while addressing issues associated with reverse inference. The result from analysis demonstrated that brain regions in the cerebellum, the right Crus I and Crus II in particular, were specifically associated with morality in general. I discussed the potential implications of the finding based on clinical and functional neuroimaging studies of the cerebellum, emotional functioning, and neural networks for diverse psychological processes. (shrink)

This chapter analyses the prospects of using neuroimaging methods, in particular functional magnetic resonance imaging (fMRI), for philosophical purposes. To do so, it will use two case studies from the field of emotion research: Greene et al. (2001) used fMRI to uncover the mental processes underlying moral intuitions, while Lindquist et al. (2012) used fMRI to inform the debate around the nature of a specific mental process, namely, emotion. These studies illustrate two main approaches in cognitive neuroscience: Reverse inference and (...) ontology testing, respectively. With regards to Greene et al.’s study, the use of Neurosynth (Yarkoni 2011) will show that the available formulations of reverse inference, although viable a priori, seem to be of limited use in practice. On the other hand, the discussion of Lindquist et al.’s study will present the so far neglected potential of ontology-testing approaches to inform philosophical questions. (shrink)

Conceptual review as task analysis method Meta-analysis is a crucial research tool in cognitive neuroscience. For meta-analysis to succeed, it is important that studies that are grouped together investigate the same cognitive process and that studies that investigate different cognitive processes are grouped apart. After all, comparing apples and oranges makes no sense. Studies’ comparability depends on the cognitive tasks employed. Yet current meta-analyses, especially when automated (e.g. Neurosynth, BrainMap), select and group studies based on cognitive labels (e.g. ‘working (...) memory’, ‘self-reflection’). Unfortunately, labels are often applied inconsistently to tasks: different tasks may receive the same cognitive label, leading to a comparison of apples and oranges during meta-analysis; and the same task may receive different labels, leading to meta-analyses that fail to include all apples, so to speak. I propose conceptual review as a method for overcoming this problem. A conceptual review analyzes the conceptual implications of task choices made in a cognitive neuroscience subfield. It applies philosophical ways of uncovering and analyzing implicit assumptions to the methodological choices neuroscientists make. I explicate how this works and discuss several ways in which conceptual review would benefit cognitive neuroscience. Conceptual review could be combined with neuro-informatics to improve the quality of automated versions of meta-analysis and thereby provide an important contribution to progress in cognitive neuroscience. (shrink)