Our main research interest focuses on causal cognition. Specifically, we are interested in how causal knowledge is acquired, represented and used, mediating human behaviour in various cognitive tasks (e.g., inferring causal knowledge from observations, diagnostic reasoning, or decision making).
Our work in the field has been mainly concerned with the experimental study of the conditions under which different cognitive processes underlie human performance in causal scenarios: from intuitive processes based on the computation of statistical covariation between target events (i.e., associative learning processes) to higher cognitive processes that rely on the use of prior causal knowledge (e.g., domain specific knowledge, structural causal knowledge, etc.).
Recently, we have been interested in a more comprehensive approach to the study of causal cognition, what has led us not only to continue with classical behavioural studies but also to incorporate: 1) a neuroscientific approach (e.g., event-related brain potential studies of error detection); 2) computational modelling using neural networks; 3) the study of causal cognition in professional settings that rely on the use of domain specific causal knowledge (e.g., clinical psychology or aviation).
Our research is being currently supported by Junta de Andalucia (EXCEL-SEJ-0406) and Ministerio de Educación y Ciencia (SEJ2007-63691/PSIC).
Some of the current research lines:
Influence of causal reasoning in human associative learning.
The role of context in interference phenomena.
Implicit measures of human associative learning.
Error computation in causal learning as measured by ERP.
Diagnostic reasoning in clinical settings.
Situation assessment in the aviation domain.