GATSBY COMPUTATIONAL NEUROSCIENCE UNIT

Causal Learning in Rats

Empirical research with nonhuman primates appears to support the view that causal reasoning is a key cognitive faculty that divides humans from animals. The claim is that animals approximate causal learning using associative processes. We will present a number of recent experiments that cast doubt on this conclusion. Rats made causal inferences in a more basic task which taps into core features of causal reasoning without requiring complex physical knowledge. They derived predictions of the outcomes of interventions after passive observational learning of different kinds of causal models. Additional studies showed that rats are capable of flexibly switching between predictions based on observations and interventions. Moreover, they differentiated between their own acts and external observable causes, which is consistent with the assumption that only interventions but not any kind of external cause are treated as independent external influences in a causal system. Possibly this belief represents a precursor of an implicit belief in free will. In the final part of the presentation we will speculate about the relation between rational models and rats' reasoning and learning. Whereas rats' inferences are consistent with the predictions of causal Bayes nets, learning seems to be better described by a variant of causal-model theory.