Human visual perception is highly adaptive: It flexibly prioritizes information that is relevant to our current tasks and goals, while it attempts to ignore information that is not, or no longer, relevant. For this to work, the cognitive system must somehow represent what is currently relevant. This representation is often called the attentional template, as it determines what we direct our attention to. Although there is no doubt on its existence, remarkably little is known about its representational nature. For example, does it represent features, combinations of features, or more abstract properties? Is it really visual in nature, as so often assumed, or may other types of knowledge contribute or even take over? And how does this change as a function of learning? The aim of our joint research proposal is to answer the fundamental question of what kind of representation the attentional template is, in terms of function (how it affects our behaviour), physiology (how it is implemented in the brain), and time (how it is affected by selection history). To achieve this, all of the labs involved will focus on the very same research questions, but approach these from their own methodological expertise. A thorough understanding of the representational properties of attentional templates will be a major step on the way towards a neuro-cognitive theory of goal-directed perception and action, and will have important implications for many clinical and professional settings.

Mid-twentieth century philosophy of science was dominated by logical empiricism: a philosophical movement whose focus was on scientific methodology, in particular on developing what could be called the logic of science. One of the leaders of the movement, Rudolf Carnap, proposed to model scientific reasoning in inductive logic: the logic of induction and reasoning with probabilities. It became an influential foundational program that is still alive today. Yet there are still many things unclear about inductive logic, especially in its relation to other parts of Carnap’s philosophy. For instance, how can inductive logic provide constraints on rational belief? How does it relate to the theory of rational decisions? Carnap said that “in logic there are no morals”: we are free to choose our logical frameworks as we wish. Yet his inductive logic is there to tell us exactly what to believe. There appears to be a fundamental tension in Carnap’s work between a normative approach to belief and the freedom we have in choosing a formal framework to describe those beliefs. This leads to further questions about the difference between the theoretical and the practical: between beliefs and decisions. A thorough study of Carnap’s inductive logic can shed light on these questions, not only in Carnap’s work, but also in contemporary debates in philosophy. In order to carry out this study, I will explore Carnap’s unpublished work, the majority of which has not yet been researched. The results of the critical analysis of the system will be then applied to some open questions in formal epistemology, philosophy of logic, and metaphilosophy. We will gain a better understanding of what it means for our beliefs and decisions to be rational, and how philosophy can contribute to creating norms of reasoning.

The ?brain challenge? consists in the identification of psychological processes in brain activations. Combining the perspectives of philosophy, psychology, and different levels of neuroscience, I will address part of this challenge on four levels constituting the four parts of this four-year project: (1) the individual anatomical level of the brain, (2) its individual functional level, (3) the large-scale level of brain networks, and (4) the level of applications in practical contexts. Using methods of conceptual analysis, data analysis, and meta-analysis, I plan to publish eight papers and one book about the brain challenge on each of the four levels. The major questions addressed in these publications are: What is a brain structure? To what extend do brain anatomy and function differ inter- and intra-individually and how does this affect the brain challenge? How can the prevalent inferential model, the reverse inference, be improved by taking this knowledge into account? And what implications does this knowledge have in the wider social and legal context, particularly regarding individual applications of neuroscience?