Neural processing of reward magnitude under varying attentional demands

Department of Neurology and Centre for Advanced Imaging, Otto-von-Guericke-University, Leipziger Str. 44, 39120 Magdeburg, Germany.
Brain research (Impact Factor: 2.84). 02/2011; 1383:218-29. DOI: 10.1016/j.brainres.2011.01.095
Source: PubMed


Central to the organization of behavior is the ability to represent the magnitude of a prospective reward and the costs related to obtaining it. Therein, reward-related neural activations are discounted in dependence of the effort required to resolve a given task. Varying attentional demands of the task might however affect reward-related neural activations. Here we employed fMRI to investigate the neural representation of expected values during a monetary incentive delay task with varying attentional demands. Following a cue, indicating at the same time the difficulty (hard/easy) and the reward magnitude (high/low) of the upcoming trial, subjects performed an attention task and subsequently received feedback about their monetary reward. Consistent with previous results, activity in anterior-cingulate, insular/orbitofrontal and mesolimbic regions co-varied with the anticipated reward-magnitude, but also with the attentional requirements of the task. These activations occurred contingent on action-execution and resembled the response time pattern of the subjects. In contrast, cue-related activations, signaling the forthcoming task-requirements, were only observed within attentional control structures. These results suggest that anticipated reward-magnitude and task-related attentional demands are concurrently processed in partially overlapping neural networks of anterior-cingulate, insular/orbitofrontal, and mesolimbic regions.

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Available from: Christian Michael Stoppel, Jul 25, 2014
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    • "Based on this model a measure for the duration of the implementation of response inhibition can be derived, the so-called stop-signal response time (SSRT), which has been shown to be prolonged in several neuropsychiatric disorders such as attention-deficit hyperactivity disorder, obsessive-compulsivity disorder and schizophrenia (Bekker et al., 2005c; Chamberlain et al., 2006; Lijffijt et al., 2005; Lipszyc and Schachar, 2010). While different cognitive functions, including cognitive control, are usually studied in settings devoid of explicit extrinsic motivation, it has been shown that reward prospect can have beneficial effects on a range of cognitive functions like working memory (Beck et al., 2010; Gilbert and Fiez, 2004), memory formation (Adcock et al., 2006), and attention (Krebs et al., 2009; Padmala and Pessoa, 2011; Schevernels et al., 2014; Stoppel et al., 2011). In these studies, motivation is usually implemented using a cue indicating that a reward can be obtained if the upcoming task is performed correctly (monetary incentive delay task; NeuroImage 121 (2015) 115–125 Abbreviations: CSDs, current source densities; EEG, electroencephalography; ERP, event-related potential; fMRI, functional magnetic resonance imaging; MEG, magnetoencephalography ; rANOVA, repeated-measures analysis of variance; RT, reaction time; SN, selection negativity; SSRT, stop-signal reaction time; SST, successful stop trial; UST, unsuccessful stop trial. "
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    ABSTRACT: Reward availability is known to facilitate various cognitive operations, which is usually studied in cue-based paradigms that allow for enhanced preparation in reward-related trials. However, recent research using tasks that signal reward availability via task-relevant stimuli suggests that reward can also rapidly promote performance independent of global strategic preparation. Notably, this effect was also observed in a reward-related stop-signal task, in which behavioral measures of inhibition speed were found to be shorter in trials signaling reward. Corresponding fMRI results implied that this effect relies on boosted reactive control as indicated by increased activity in the 'inhibition-related network' in the reward-related condition. Here, we used EEG to better characterize transient modulations of attentional processes likely preceding this ultimate implementation of response inhibition. Importantly, such modulations would probably reflect enhanced proactive control in the form of more top-down attention to reward-related features. Counter to the notion that behavioral benefits would rely purely on reactive control, we found increased stop-evoked attentional processing (larger N1 component) on reward-related trials. This effect was accompanied by enhanced frontal P3 amplitudes reflecting successful stopping, and earlier and larger ERP differences between successful and failed stop trials in the reward-related condition. Finally, more global proactive control processes in the form of a reward context modulation of reward-unrelated trials did not have an effect on stopping performance but did influence attentional processing of go stimuli. Together, these results suggest that proactive and reactive processes can interact to bring about stimulus-specific reward benefits when the task precludes differential global preparation. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 07/2015; DOI:10.1016/j.neuroimage.2015.07.023 · 6.36 Impact Factor
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    • "Un ejemplo de ello es el estudio de Tomporowski y Tinsley (1996), en el que utilizando una tarea de atención sostenida, observaron que cuando los participantes eran reforzados económicamente por su participación conseguían mantener la atención, mientras que cuando no se les recompensaba la atención sostenida disminuía significativamente. Los resultados funcionales obtenidos han mostrado que la red neuronal involucrada en la interacción entre el control cognitivo y la motivación apetitiva incluye áreas (1) frontales como el córtex prefrontal medio o el giro frontal inferior, (2) parietales como el sulco intraparietal o ínsula, y (3) estriatales como el nucleo accumbens, o el putamen (Padmala y Pessoa, 2011; Stoppel y cols., 2011; Padmala y Pessoa, 2010; Savine y Braver, 2010; Beck y cols., 2010; Pochon y cols., 2002; Rogers y cols., 2004). De igual modo, los apuntan a la dopamina como principal neurotransmisor involucrado en esta interacción (Engelmann y cols., 2009; Zink y cols., 2004; Pessoa y Engelmann, 2010; Ávila y cols., 2012). "

    01/2015; DOI:10.6035/AgoraSalut.2015.1.1
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    • "Recent evidence suggests that facing an upcoming effortful task also induces increased ACC and striatum involvement. This might reflect a motivational effect towards task performance, comparable to the incentive given by a monetary reward [23]–[25]. In terms of energy expenditure, this would be translated to the invigoration of the optimal behavior, which in turn is required to obtain a reward. "
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    ABSTRACT: Anticipating a potential benefit and how difficult it will be to obtain it are valuable skills in a constantly changing environment. In the human brain, the anticipation of reward is encoded by the Anterior Cingulate Cortex (ACC) and Striatum. Naturally, potential rewards have an incentive quality, resulting in a motivational effect improving performance. Recently it has been proposed that an upcoming task requiring effort induces a similar anticipation mechanism as reward, relying on the same cortico-limbic network. However, this overlapping anticipatory activity for reward and effort has only been investigated in a perceptual task. Whether this generalizes to high-level cognitive tasks remains to be investigated. To this end, an fMRI experiment was designed to investigate anticipation of reward and effort in cognitive tasks. A mental arithmetic task was implemented, manipulating effort (difficulty), reward, and delay in reward delivery to control for temporal confounds. The goal was to test for the motivational effect induced by the expectation of bigger reward and higher effort. The results showed that the activation elicited by an upcoming difficult task overlapped with higher reward prospect in the ACC and in the striatum, thus highlighting a pivotal role of this circuit in sustaining motivated behavior.
    PLoS ONE 03/2014; 9(3):e91008. DOI:10.1371/journal.pone.0091008 · 3.23 Impact Factor
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