Neural correlates of uncertain decision making: ERP evidence from the Iowa Gambling Task

Abstract

In our daily life, it is very common to make decisions in uncertain situations. The Iowa Gambling Task (IGT) has been widely used in laboratory studies because of its good simulation of uncertainty in real life activities. The present study aimed to examine the neural correlates of uncertain decision making with the IGT. Twenty-six university students completed this study. An adapted IGT was administered to them, and the EEG data were recorded. The adapted IGT we used allowed us to analyze the choice evaluation, response selection, and feedback evaluation stages of uncertain decision making within the same paradigm. In the choice evaluation stage, the advantageous decks evoked larger P3 amplitude in the left hemisphere, while the disadvantageous decks evoked larger P3 in the right hemisphere. In the response selection stage, the response of “pass” (the card was not turned over; the participants neither won nor lost money) evoked larger negativity preceding the response compared to that of “play” (the card was turned over; the participant either won or lost money). In the feedback evaluation stage, feedback-related negativity (FRN) was only sensitive to the valence (win/loss) but not the magnitude (large/small) of the outcome, and P3 was sensitive to both the valence and the magnitude of the outcome. These results were consistent with the notion that a positive somatic state was represented in the left hemisphere and a negative somatic state was represented in the right hemisphere. There were also anticipatory ERP effects that guided the participants' responses and provided evidence for the somatic marker hypothesis with more precise timing.

Neural Correlates of Successful and Unsuccessful Strategical Mechanisms Involved in Uncertain Decision-Making

“…In accordance with previous studies our analysis of the P300 for the entire group showed a significant difference in feedback processing [3,23,30,63,64]. We also found a higher positivity for a loss compared to a gain.…”

RL mechanisms of short-term plasticity of auditory cortex

“…This is not a surprising finding, since the modulation of FRN by expected outcome magnitude is still under debate. In some investigations it has been postulated that FRN is not influenced by reward magnitude (Cui et al, 2013;Hajcak et al, 2003Hajcak et al, , 2006Holroyd et al, 2006;Marco-Pallares et al, 2008;Nieuwenhuis et al, 2004;De Pascalis et al, 2010;Yeung and Sanfey, 2004), however, there is also a mounting evidence that FRN encode magnitude in addition to probability and valence (Bellebaum et al, 2010;Kreussel et al, 2012;Toyomaki and Murohashi, 2005). Therefore, our results replicated previous findings of absence of FRN modulation by reward magnitude, which might be explained by relatively low difference in magnitude of potential outcome.…”

Computational EEG modelling of decision making under ambiguity reveals spatio-temporal dynamics of outcome evaluation

“…This is a longer interval than is often used to examine the FRN (Weinberg et al 2014;Cui et al 2013;Fuentemilla et al 2013). However, the regressor which was expressed most strongly in the EEG in the interval more traditionally associated with the FRN (between about 230ms to 300ms after feedback presentation) was the VPP model choice probability, which is consistent with the role in prediction error attributed to the FRN.…”

“…While previous research suggests that the P3 is sensitive to magnitude (Yeung and Sanfey 2004), there have been conflicting findings with regard to the effect of magnitude on the FRN. A recent meta-analysis suggested that the FRN does show a strong main effect of reward magnitude (Sambrook and Goslin 2015), while other studies suggest that the FRN is not associated with magnitude (Yeung and Sanfey 2004;Hajcak et al 2006;Cui et al 2013). …”