Electrophysiological signatures associated with the identification of statistical regularities in a sequence of events

• Grant number: 22/00699-3
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Effective date (Start): April 01, 2022
• Effective date (End): March 31, 2025
• Field of knowledge: Engineering - Biomedical Engineering - Bioengineering
• Principal Investigator: Florencia Graciela Leonardi
• Grantee: Paulo Roberto Cabral Passos
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat, AP.CEPID

Abstract

The aim of this project is to tackle the conjecture that the brain computes probabilities and makes inferences about sequences of events. The study of this conjecture in the last decades is motivated by evidences that regularities in a sequence of stimulus shape perception and motor behavior. This, in turn, raises the interest about how the brain deals with the unpredictability inherent to nature. To approach this conjecture, it is proposed an experiment with The Goalkeeper Game (NeuroMat/FAPESP) which will be used as a way of presenting a sequence of stochastic events during a prediction task. In The Goalkeeper Game, the subject that participates in the experiment assumes the role of a goalkeeper in a sequence of penalty kicks. In each penalty kick, the goalkeeper should choose which of three locations, left, center or right, the goalkeeper should jump to defend. The sequence of kicks of the penalty taker, that should be predicted by the goalkeeper, corresponds to a stochastic chain with memory of variable length and is not influence by the choices of the goalkeeper. By recording the electroencephalographic activity (EEG) of the subject during the experiment, we intend to investigate how the segments of brain activity recorded before each prediction are modulated by the stochastic chain and by the results of previous choices of the subject, that means, successes and failures of prediction. Based on the gathered information, we intend to describe how these EEG signals are modulated according to the context of the sequence and the results of previous predictions of the subject. With that knowledge it is possible to retrieve the structure of the sequence presented to the subject from the sequence of EEG segments.