Neurodynamics of an election.
Variables influencing decision-making in real settings, as in the case of voting decisions, are uncontrollable and in many times even unknown to the experimenter. In this case, the experimenter has to study the intention to decide (vote) as close as possible in time to the moment of the real decision (election day). Here, we investigated the brain activity associated with the voting intention declared 1 week before the election day of the Brazilian Firearms Control Referendum about prohibiting the commerce of firearms. Two alliances arose in the Congress to run the campaigns for YES (for the prohibition of firearm commerce) and NO (against the prohibition of firearm commerce) voting. Time constraints imposed by the necessity of studying a reasonable number (here, 32) of voters during a very short time (5 days) made the EEG the tool of choice for recording the brain activity associated with voting decision. Recent fMRI and EEG studies have shown decision-making as a process due to the enrollment of defined neuronal networks. In this work, a special EEG technique is applied to study the topology of the voting decision-making networks and is compared to the results of standard ERP procedures. The results show that voting decision-making enrolled networks in charge of calculating the benefits and risks of the decision of prohibiting or allowing firearm commerce and that the topology of such networks was vote- (i.e., YES/NO-) sensitive.
da Rocha
Armando Freitas
AF
RANI-Research on Natural and Artificial Intelligence, Rua Tenente Ary Aps, 172 Jundiaí, CEP 13207-110, Brazil; School of Medicine, University of São Paulo and LIM01-HCFMUSP, Rua Teodoro Sampaio 115, São Paulo, CEP 5405-000, SP, Brazil. Electronic address: armando@enscer.com.br.
Rocha
Fábio Theoto
FT
RANI-Research on Natural and Artificial Intelligence, Rua Tenente Ary Aps, 172 Jundiaí, CEP 13207-110, Brazil; School of Medicine, University of São Paulo and LIM01-HCFMUSP, Rua Teodoro Sampaio 115, São Paulo, CEP 5405-000, SP, Brazil. Electronic address: fabio@enscer.com.br.
Burattini
Marcelo Nascimento
MN
School of Medicine, University of São Paulo and LIM01-HCFMUSP, Rua Teodoro Sampaio 115, São Paulo, CEP 5405-000, SP, Brazil. Electronic address: mnburatti@usp.br.
Massad
Eduardo
E
School of Medicine, University of São Paulo and LIM01-HCFMUSP, Rua Teodoro Sampaio 115, São Paulo, CEP 5405-000, SP, Brazil. Electronic address: edmassad@usp.br.
D000328:Adult; D003657:Decision Making / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000502:physiology*; D011057:Politics; D013997:Time Factors