Objective
"Our ability to understand causality is at the very core of modern civilization. We see potential antecedents of this understanding in some non-human animals, notably apes and corvids. To date, behaviour thought to be indicative of causal understanding, particularly tool-use, has been mainly described as a phenomenon rather than studied as a mechanism and thus suffers from the lack of an experimentally-tested theoretical framework and deconstructive analysis. This significantly constrains our progress in answering key questions such as: (1) how do humans understand the physical world and solve problems? (2) what other ways of understanding causality and problem solving has evolution produced? (3) what selective pressures lead to the evolution of causal cognition? Each of these questions constitutes an area where there exists enormous potential to advance cognitive science. The overarching aim is to create a coherent, experimentally-tested, theoretical framework of the cognitive mechanisms underlying causal knowledge in corvids and humans, both young and adult. The advantage of our approach is that we will study two types of mind that have very different neural machineries and investigate the similarities and differences in their cognitive processes. We will create a sufficient level of abstraction to develop a deep theory of cognition, something that would not be possible by studying only a single species and its close evolutionary relatives. One of the most exciting aspects is that we will begin to map the ‘universal mind’ (i.e. the cognitive mechanisms that are repeatedly created by convergent evolution) to provide a quantum leap in our understanding of cognition. Finally, by discovering evolved biases in children’s learning and reasoning mechanisms we will pave the way for new teaching methods that boost learning in the classroom by appealing to the way children naturally understand the world."
Fields of science
Call for proposal
ERC-2013-ADG
See other projects for this call
Funding Scheme
ERC-AG - ERC Advanced GrantHost institution
CB2 1TN Cambridge
United Kingdom