Neurodireito: diferenças entre penas aplicadas a criminosos por estudantes de direito e por estudantes leigos em contextos de manipulação do nojo

Abstract

Legal decisions are not entirely rational and are influenced by emotions, heuristics, biases and other extra-legal circumstances. Empirical studies of these influences are important in order to properly deal with them. To this aim, it is essential that studies of these decisions be interdisciplinary, with a prominent emphasis on the role of psychology and neuroscience in support of legal disciplines through a new approach called “neurolaw”. Particularly noteworthy in the United States of America there are studies with functional magnetic resonance imaging, which have sought to map the neural circuits involved in third-party punishment, which include the steps of: attribution of responsibility, harm assessment and penalty quantification. Furthermore, the process of evaluating the aggressor's intention - which is part of the so-called “theory of mind” - is still decisive. These studies found greater or lesser activation of several different brain structures in each of these stages, such as the dorsolateral prefrontal cortex, the amygdala, and the temporoparietal junction. However, researches of penalty quantification stage, which investigated these circuits, were made with lay people, that is, people without formal knowledge in law. Our experiments about disgust and punishment, although did not find correlation nor causality relationship between both, showed, in another hand, that lay students punishes differently from advanced law students. Law techniques knowledge of judges, law professionals and law students may recruit different neural circuitry from that observed among lay people. Therefore, we propose to researchers, that will investigate neural circuits involved in law decision, to consider recruit not only lay people, but also people with law knowledge among their volunteers and we also propose that more researches be done on these fields, aiming to allow Bayesian statistics analysis.