Reward Reduces Conflict by Enhancing Attentional Control and Biasing Visual Cortical Processing

Abstract

How does motivation interact with cognitive control during challenging behavioral conditions? Here, we investigated the interactions between motivation and cognition during a response conflict task and tested a specific model of the effect of reward on cognitive processing. Behaviorally, participants exhibited reduced conflict during the reward vs. no-reward condition. Brain imaging results revealed that a group of subcortical and fronto-parietal regions was robustly influenced by reward at cue processing and, importantly, that cue-related responses in fronto-parietal attentional regions were predictive of reduced conflict-related signals in the medial prefrontal cortex (PFC)/anterior cingulate cortex during the upcoming target phase. Path analysis revealed that the relationship between cue responses in the right intraparietal sulcus (IPS) and interference-related responses in the medial PFC during the subsequent target phase was mediated via signals in the left fusiform gyrus, which we linked to distractor-related processing. Finally, reward increased functional connectivity between the right IPS and both bilateral putamen and bilateral nucleus accumbens during the cue phase, a relationship that covaried with across-individual sensitivity to reward in the case of the right nucleus accumbens. Taken together, our findings are consistent with a model in which motivationally salient cues are employed to upregulate top-down control processes that bias the selection of visual information, thereby leading to more efficient stimulus processing during conflict conditions.

RETRACTED ARTICLE: Local and global effects of motivation on cognitive control

“…With regard to the trial-bytrial enhancements of cognitive control associated with the incentive cue effect, the most likely neural locus is the frontoparietal brain control network, which includes lateral prefrontal cortex (PFC), anterior cingulate cortex, and posterior parietal cortex. In a number of neuroimaging studies showing incentive-related modulation of cognition, activation in all of these regions has been found to be reliably enhanced by motivational value (Beck, Locke, Savine, Jimura, & Braver, 2010;Locke & Braver, 2008;Padmala & Pessoa, 2011;Pessoa & Engelmann, 2010;Pochon et al, 2002;Taylor et al, 2004). More specifically, in a prior neuroimaging study using this incentive task-switching paradigm, we found that left lateral PFC was the most likely site of motivational and cognitive control integration .…”

A new window to understanding individual differences in reward sensitivity from attentional networks

“…Nonetheless, these results were not replicated using an alternative meta-analytic method (see Liu et al 2011). Such scarce evidence contrasts with the psychophysiological studies showing enhanced P300 when processing reward cues and outcomes (Parvaz et al 2012;van Lankveld and Smulders 2008;Yeung and Sanfey 2004), and with functional connectivity studies showing increased coupling between the parietal and striatal areas in the presence of reward cues (Padmala and Pessoa 2011). Furthermore, fMRI studies using attentional paradigms have revealed the greater involvement of the fronto-parietal areas when processing rewarding stimuli that compete with other stimuli (Small et al 2005;Locke and Braver 2008;Mohanty et al 2008;Engelmann et al 2009;Ivanov et al 2011).…”

“…A second interesting point of this research lies in the study of individual differences in reward sensitivity. While studies using rewardrelated tasks have shown modulation of reward sensitivity in the brain areas associated with the reward system (Beaver et al 2006;Carter et al 2009;Hahn et al 2009;Barrós-Loscertales et al 2010;Costumero et al 2013), studies focused on the interactions between motivation and cognitive control have demonstrated modulatory effects of reward sensitivity on the activity and connectivity of the parietal and frontal areas (Locke and Braver 2008;Engelmann et al 2009;Padmala and Pessoa 2011).…”

Binding by Random Bursts: A Computational Model of Cognitive Control

“…Furthermore, with stronger control there are less errors, faster RTs, and smaller congruency effects. This occurs both proactively (e.g., because the reward at stake is higher or because the upcoming task is difficult; Janssens, De Loof, Pourtois, & Verguts, 2016;Vassena et al, 2014;Padmala & Pessoa, 2011) and reactively (e.g., in response to current trial processing difficulty or after an error or incongruent trial; Gratton, Coles, & Donchin, 1992).…”