Kimberly S. Chiew

Mechanisms of motivation-cognition interaction : challenges and opportunities

Recent years have seen a rejuvenation of interest in studies of motivation–cognition interactions arising from many different areas of psychology and neuroscience. The present issue of Cognitive, Affective, & Behavioral Neuroscience provides a sampling of some of the latest research from a number of these different areas. In this introductory article, we provide an overview of the current state of the field, in terms of key research developments and candidate neural mechanisms receiving focused investigation as potential sources of motivation–cognition interaction. However, our primary goal is conceptual: to highlight the distinct perspectives taken by different research areas, in terms of how motivation is defined, the relevant dimensions and dissociations that are emphasized, and the theoretical questions being targeted. Together, these distinctions present both challenges and opportunities for efforts aiming toward a more unified and cross-disciplinary approach. We identify a set of pressing research questions calling for this sort of cross-disciplinary approach, with the explicit goal of encouraging integrative and collaborative investigations directed toward them.

Positive affect versus reward: emotional and motivational influences on cognitive control

It is becoming increasingly appreciated that affective influences can contribute strongly to goal-oriented cognition and behavior. However, much work is still needed to properly characterize these influences and the mechanisms by which they contribute to cognitive processing. An important question concerns the nature of emotional manipulations (i.e., direct induction of affectively valenced subjective experience) versus motivational manipulations (e.g., delivery of performance-contingent rewards and punishments) and their impact on cognitive control. Empirical evidence suggests that both kinds of manipulations can influence cognitive control in a systematic fashion, but investigations of both have largely been conducted independently of one another. Likewise, some theoretical accounts suggest that emotion and motivation may modulate cognitive control via common neural mechanisms, while others suggest the possibility of dissociable influences. Here, we provide an analysis and synthesis of these various accounts, suggesting potentially fruitful new research directions to test competing hypotheses.

Temporal dynamics of motivation-cognitive control interactions revealed by high-resolution pupillometry.

Motivational manipulations, such as the presence of performance-contingent reward incentives, can have substantial influences on cognitive control. Previous evidence suggests that reward incentives may enhance cognitive performance specifically through increased preparatory, or proactive, control processes. The present study examined reward influences on cognitive control dynamics in the AX-Continuous Performance Task (AX-CPT), using high-resolution pupillometry. In the AX-CPT, contextual cues must be actively maintained over a delay in order to appropriately respond to ambiguous target probes. A key feature of the task is that it permits dissociable characterization of preparatory, proactive control processes (i.e., utilization of context) and reactive control processes (i.e., target-evoked interference resolution). Task performance profiles suggested that reward incentives enhanced proactive control (context utilization). Critically, pupil dilation was also increased on reward incentive trials during context maintenance periods, suggesting trial-specific shifts in proactive control, particularly when context cues indicated the need to overcome the dominant target response bias. Reward incentives had both transient (i.e., trial-by-trial) and sustained (i.e., block-based) effects on pupil dilation, which may reflect distinct underlying processes. The transient pupillary effects were present even when comparing against trials matched in task performance, suggesting a unique motivational influence of reward incentives. These results suggest that pupillometry may be a useful technique for investigating reward motivational signals and their dynamic influence on cognitive control.

Dissociable influences of reward motivation and positive emotion on cognitive control.

It is becoming increasingly appreciated that affective and/or motivational influences contribute strongly to goal-oriented cognition and behavior. An unresolved question is whether emotional manipulations (i.e., direct induction of affectively valenced subjective experience) and motivational manipulations (e.g., delivery of performance-contingent rewards and punishments) have similar or distinct effects on cognitive control. Prior work has suggested that reward motivation can reliably enhance a proactive mode of cognitive control, whereas other evidence is suggestive that positive emotion improves cognitive flexibility, but reduces proactive control. However, a limitation of the prior research is that reward motivation and positive emotion have largely been studied independently. Here, we directly compared the effects of positive emotion and reward motivation on cognitive control with a tightly matched, within-subjects design, using the AX-continuous performance task paradigm, which allows for relative measurement of proactive versus reactive cognitive control. High-resolution pupillometry was employed as a secondary measure of cognitive dynamics during task performance. Robust increases in behavioral and pupillometric indices of proactive control were observed with reward motivation. The effects of positive emotion were much weaker, but if anything, also reflected enhancement of proactive control, a pattern that diverges from some prior findings. These results indicate that reward motivation has robust influences on cognitive control, while also highlighting the complexity and heterogeneity of positive-emotion effects. The findings are discussed in terms of potential neurobiological mechanisms.

Enhancement of cognitive control by approach and avoidance motivational states

Affective variables have been shown to impact working memory and cognitive control. Theoretical arguments suggest that the functional impact of emotion on cognition might be mediated through shifting action dispositions related to changes in motivational orientation. The current study examined the effects of positive and negative affect on performance via direct manipulation of motivational state in tasks with high demands on cognitive control. Experiment 1 examined the effects of monetary reward on task-switching performance, while Experiment 2 examined the effects of both rewards and punishments on working memory, using primary (liquid) reinforcers. In both experiments, dissociable trial-by-trial and contextual (block-related) enhancements of cognitive control during task performance were observed in relationship to motivational incentive value. Performance enhancements were equivalent in the reward and punishment conditions, but were differentially impacted by individual difference measures of trait reward and punishment sensitivity. Together, the results suggest both common and specific mechanisms by which approach and avoidance motivational states influence cognitive control, via activation of reward and punishment processing systems.

Neural Circuitry of Emotional and Cognitive Conflict Revealed through Facial Expressions

Background Neural systems underlying conflict processing have been well studied in the cognitive realm, but the extent to which these overlap with those underlying emotional conflict processing remains unclear. A novel adaptation of the AX Continuous Performance Task (AX-CPT), a stimulus-response incompatibility paradigm, was examined that permits close comparison of emotional and cognitive conflict conditions, through the use of affectively-valenced facial expressions as the response modality. Methodology/Principal Findings Brain activity was monitored with functional magnetic resonance imaging (fMRI) during performance of the emotional AX-CPT. Emotional conflict was manipulated on a trial-by-trial basis, by requiring contextually pre-cued facial expressions to emotional probe stimuli (IAPS images) that were either affectively compatible (low-conflict) or incompatible (high-conflict). The emotion condition was contrasted against a matched cognitive condition that was identical in all respects, except that probe stimuli were emotionally neutral. Components of the brain cognitive control network, including dorsal anterior cingulate cortex (ACC) and lateral prefrontal cortex (PFC), showed conflict-related activation increases in both conditions, but with higher activity during emotion conditions. In contrast, emotion conflict effects were not found in regions associated with affective processing, such as rostral ACC. Conclusions/Significance These activation patterns provide evidence for a domain-general neural system that is active for both emotional and cognitive conflict processing. In line with previous behavioural evidence, greatest activity in these brain regions occurred when both emotional and cognitive influences additively combined to produce increased interference.

A new perspective on human reward research: How consciously and unconsciously perceived reward information influences performance

The question of how human performance can be improved through rewards is a recurrent topic of interest in psychology and neuroscience. Traditional, cognitive approaches to this topic have focused solely on consciously communicated rewards. Recently, a largely neuroscience-inspired perspective has emerged to examine the potential role of conscious awareness of reward information in effective reward pursuit. The present article reviews research employing a newly developed monetary-reward-priming paradigm that allows for a systematic investigation of this perspective. We analyze this research to identify similarities and differences in how consciously and unconsciously perceived rewards impact three distinct aspects relevant to performance: decision making, task preparation, and task execution. We further discuss whether conscious awareness, in modulating the effects of reward information, plays a role similar to its role in modulating the effects of other affective information. Implications of these insights for understanding the role of consciousness in modulating goal-directed behavior more generally are discussed.

Reward favors the prepared: Incentive and task-informative cues interact to enhance attentional control.

The dual mechanisms of control account suggests that cognitive control may be implemented through relatively proactive mechanisms in anticipation of stimulus onset, or through reactive mechanisms, triggered in response to changing stimulus demands. Reward incentives and task-informative cues (signaling the presence/absence of upcoming cognitive demand) have both been found to influence cognitive control in a proactive or preparatory fashion; yet, it is currently unclear whether and how such cue effects interact. We investigated this in 2 experiments using an adapted flanker paradigm, where task-informative and reward incentive cues were orthogonally manipulated on a trial-by-trial basis. In Experiment 1, results indicated that incentives not only speed reaction times, but specifically reduce both interference and facilitation effects when combined with task-informative cues, suggesting enhanced proactive attentional control. Experiment 2 manipulated the timing of incentive cue information, demonstrating that such proactive control effects were only replicated with sufficient time to process the incentive cue (early incentive); when incentive signals were presented close to target onset (late incentive) the primary effect was a speed-accuracy trade-off. Together, results suggest that advance cueing may trigger differing control strategies, and that these strategies may critically depend on both the timing-and the motivational incentive-to use such cues.

Monetary Incentives Improve Performance, Sometimes: Speed and Accuracy Matter, and so Might Preparation

It is intuitive to assume that monetary rewards will improve cognitive performance. However, empirical research has yielded mixed results (Bonner et al., 2000). A new study by Dambacher et al. (2011) seeks to clarify an important factor – payoff schemes – in mediating the relationship between incentives and cognitive performance. Specifically, this paper presents a series of three experiments examining the effect of monetary versus symbolic incentives on performance in the Erikson flanker task (Eriksen and Eriksen, 1974). Fast, accurate performance was rewarded in all payoff schemes, while penalties for errors and slow responses were independently manipulated to examine the effects of emphasizing speed versus accuracy on performance. Dambacher et al. (2011) highlight three main findings in their data: (1) performance improves under monetary incentive more when slow responses are punished than when they are not; (2) improvement is not observed when punishment for errors is emphasized instead; and (3) performance still improves without penalties as long as fast, accurate performance is emphasized with reward. Dambacher et al. (2011) interpret these results as evidence that emphasizing speed optimizes performance, while emphasis of both speed and accuracy (e.g., in Experiment 2) fails to enhance performance because determining an optimal response strategy is more difficult under these competing emphases. Importantly, this finding contributes toward a mechanistic understanding of when monetary incentives improve cognitive performance and when they do not. Here we highlight certain aspects of the present study that warrant follow-up and further investigation. One issue we wish to discuss is the role of deadline manipulations. In all three experiments of the present study, deadlines of varying lengths are used (long, medium, and short). Speed–accuracy tradeoff functions (SATFs) under each of these deadlines revealed speed–accuracy shifts in all conditions across studies, with speed increasing and accuracy decreasing with shorter deadlines. An alternative approach to examining speed–accuracy functions is use of diffusion model analysis (Ratcliff and McKoon, 2008; Ratcliff and Rouder, 1998), which provides quantitative estimation of contributions to decision performance. The diffusion model potentially sheds light on how such contributions change under incentive: i.e., whether incentive changes non-decision factors, such as stimulus encoding and response execution; the decision threshold (merely trading accuracy for speed); or specifically enhancing the quality of accumulated information (drift rate) via increased attentional effort, increasing performance speed while maintaining accuracy. A previous paper from the same group (Hubner and Schlosser, 2010) uses predictions from the diffusion model framework to evaluate flanker performance under incentive. They concluded that performance reflected increased speed while maintaining accuracy, consistent with predictions of increased drift rate as a result of increased attentional effort. However, neither that paper nor the current study include diffusion model analyses of the presented experimental data. Recent work suggests that the diffusion model provides an excellent account of behavioral performance, as well as the effects of attentional manipulations, in the flanker task (White et al., 2011). Thus, utilization of a diffusion model approach might provide a convergent means of verifying claims by Hubner, Dambacher et al. (2011) regarding how and when incentives influence task performance. A potential disadvantage of the multiple deadline design employed by Dambacher et al. (2011) is that it may increase task complexity, without providing clear predictions regarding how incentive-related changes in the flanker effect should vary as a function of deadline length. Such differences were observed in the present study (as well as in Hubner and Schlosser, 2010), but remain relatively unexplained. In particular, in Experiment 3, the flanker effect decreased under incentive at short and medium deadlines, but not under the long deadline. These observations were interpreted as evidence that incentive can enhance selective attention without requiring penalty, but why this enhancement would take place at short and medium deadlines and not at longer deadlines remains unclear. Prior work suggests that incentive-related reductions in the flanker effect are elusive (Seifert et al., 2006). One reason may be that incentives have effects that might impact either non-decision time or drift rate, but that this could interact with the time available for responding. In their prior paper Hubner and Schlosser (2010) suggest that a signature of an incentive-related effect on non-decisional processing would be enhanced performance specifically at short deadlines, but decreasing effects at longer deadlines. Indeed, in Experiment 3, performance was enhanced at short and medium but not long deadlines, which might suggest a non-decisional effect. Emerging data from our laboratory is consistent with the idea that monetary incentives may have mixed effects on cognitive performance and attentional control (Chiew and Braver, 2010). We observed a speed–accuracy shift under reward in a similar flanker paradigm, but only found incentive-related reduction of the flanker effect when participants observed a cue predicting the presence/absence of conflict in the upcoming array first. This is consistent with the idea that incentive may enhance attentional control specifically under conditions in which preparatory processes can be easily engaged (Savine and Braver, 2010). Moreover, preliminary diffusion model analysis of our data suggests that drift rate improved under incentive only in the presence of these preparatory cues, while the speed–accuracy shift under reward in the absence of these cues was associated with a change in both response caution and non-decision time. An additional concern regards the simultaneous presence of rewards and punishments in Experiment 1 and 2 of the present study. Theoretical accounts link reward and punishment with approach and avoidance tendencies, respectively, thought to be dissociable, hemispherically lateralized influences on behavior (Davidson et al., 1990; Gray, 1994) distinctly impacting cognitive processes (Savine et al., 2010). Incentivized cognitive performance under emphasis of speed or accuracy should be carefully examined under reward versus penalty alone to better characterize these distinct motivational influences. We applaud Dambacher et al. (2011) for their initial investigations of how incentives affect task performance and attentional engagement during the flanker task. The extension of their work in the directions specified here should help to clarify the specific factors that determine how, why, and under what conditions incentives enhance cognitive processing and associated control functions.

Reward Anticipation Dynamics during Cognitive Control and Episodic Encoding: Implications for Dopamine

Dopamine (DA) modulatory activity critically supports motivated behavior. This modulation operates at multiple timescales, but the functional roles of these distinct dynamics on cognition are still being characterized. Reward processing has been robustly linked to DA activity; thus, examining behavioral effects of reward anticipation at different timing intervals, corresponding to different putative dopaminergic dynamics, may help in characterizing the functional role of these dynamics. Towards this end, we present two research studies investigating reward motivation effects on cognitive control and episodic memory, converging in their manipulation of rapid vs. multi-second reward anticipation (consistent with timing profiles of phasic vs. ramping DA, respectively) on performance. Under prolonged reward anticipation, both control and memory performances were enhanced, specifically when combined with other experimental factors: task-informative cues (control task) and reward uncertainty (memory task). Given observations of ramping DA under uncertainty (Fiorillo et al., 2003) and arguments that uncertainty may act as a control signal increasing environmental monitoring (Mushtaq et al., 2011), we suggest that task information and reward uncertainty can both serve as “need for control” signals that facilitate learning via enhanced monitoring, and that this activity may be supported by a ramping profile of dopaminergic activity. Observations of rapid (i.e., phasic) reward on control and memory performance can be interpreted in line with prior evidence, but review indicates that contributions of different dopaminergic timescales in these processes are not well-understood. Future experimental work to clarify these dynamics and characterize a cross-domain role for reward motivation and DA in goal-directed behavior is suggested.