Moral Dilemma Judgment Revisited: A Loreta Analysis

J. Behavioral Brain Sciences, Forthcoming

17 Pages Posted: 27 Nov 2013 Last revised: 24 Dec 2013

See all articles by Armando da Rocha

Armando da Rocha

Research on Artificial and Natural Intelligence (RANI)

Fábio Rocha

Research on Artificial and Natural Intelligence (RANI)

Eduardo Massad

University of São Paulo (USP)

Date Written: November 26, 2013

Abstract

Recent neuroscience investigations on moral judgment have provided useful information about how brain processes such complex decision making. All these studies so were fMRI investigations and therefore constrained by the poor resolution of this technique. Recent advances in electroencephalography (EEG) analysis provided by Low Resolution Tomogray (Loreta), Principal Component (PCA), Correlation and Regression Analysis improved EEG spatial resolution and make EEG a very useful technique in decision-making studies. Here, we reinvestigate previously fMRI study of personal (PD) and impersonal (ID) moral dilemma judgment, taking profit of these new EEG analysis improvements. Compared to the previous fMRI results, Loreta and PCA revealed a much greater number of cortical areas involved in dilemma judgment, whose temporal and spatial distribution were different for ID compared to PD. Regression analysis showed that activity at some cortical areas favors action implementation, while activity at some other areas opposes it. All these results are discussed from the utilitarian point of view that proposes adequacy of human action being dependent upon how much pleasure and fear/pain they are associated. Another finding of the present paper is that whenever final temporal details of the decision making process is desired, EEG becomes the tool of choice.

Suggested Citation

da Rocha, Armando and Rocha, Fábio and Massad, Eduardo, Moral Dilemma Judgment Revisited: A Loreta Analysis (November 26, 2013). J. Behavioral Brain Sciences, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2360107 or http://dx.doi.org/10.2139/ssrn.2360107

Armando Da Rocha (Contact Author)

Research on Artificial and Natural Intelligence (RANI) ( email )

Rua Tenente Ary Aps, 172
Jundiai, 13207-110
Brazil

Fábio Rocha

Research on Artificial and Natural Intelligence (RANI) ( email )

Rua Tenente Ary Aps, 172
Jundiai, 13207-110
Brazil

Eduardo Massad

University of São Paulo (USP) ( email )

Brazil

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