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.
School of Medicine, University of São Paulo and LIM01-HCFMUSP, Rua Teodoro Sampaio 115, São Paulo, CEP 5405-000, SP, Brazil.
Brain Res. 2010 Sep 10;1351:198-211. doi: 10.1016/j.brainres.2010.06.046. Epub 2010 Jun 26.
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.
在实际环境中影响决策的变量是不可控的,而且在许多情况下甚至是实验者都不知道的。在这种情况下,实验者必须尽可能接近实际决策(选举日)的时刻来研究决策意图(投票)。在这里,我们研究了与巴西枪支管制公投前一周宣布的投票意图相关的大脑活动,该公投旨在禁止枪支交易。国会中出现了两个联盟,分别为赞成(禁止枪支交易)和反对(允许枪支交易)投票进行宣传。由于需要在很短的时间(5 天)内研究相当数量(此处为 32 名)的选民,因此时间限制使得 EEG 成为记录与投票决策相关的大脑活动的首选工具。最近的 fMRI 和 EEG 研究表明,决策是由于特定神经元网络的参与而产生的。在这项工作中,应用了一种特殊的 EEG 技术来研究投票决策网络的拓扑结构,并将其与标准 ERP 程序的结果进行了比较。结果表明,投票决策涉及负责计算禁止或允许枪支交易决策的收益和风险的网络,并且这些网络的拓扑结构对投票(即 YES/NO)敏感。