Start Submission Become a Reviewer

Reading: Motivated Cognition: Effects of Reward, Emotion, and Other Motivational Factors Across a Var...

Download

A- A+
Alt. Display

Perspective/Opinion

Motivated Cognition: Effects of Reward, Emotion, and Other Motivational Factors Across a Variety of Cognitive Domains

Author:

Christopher R. Madan

School of Psychology, University of Nottingham, Nottingham, GB
X close

Abstract

A growing body of literature has demonstrated that motivation influences cognitive processing. The breadth of these effects is extensive and span influences of reward, emotion, and other motivational processes across all cognitive domains. As examples, this scope includes studies of emotional memory, value-based attentional capture, emotion effects on semantic processing, reward-related biases in decision making, and the role of approach/avoidance motivation on cognitive scope. Additionally, other less common forms of motivation–cognition interactions, such as self-referential and motoric processing can also be considered instances of motivated cognition. Here I outline some of the evidence indicating the generality and pervasiveness of these motivation influences on cognition, and introduce the associated ‘research nexus’ at Collabra: Psychology.

Subject: Psychology
How to Cite: Madan, C. R. (2017). Motivated Cognition: Effects of Reward, Emotion, and Other Motivational Factors Across a Variety of Cognitive Domains. Collabra: Psychology, 3(1), 24. DOI: http://doi.org/10.1525/collabra.111
1284
Views
287
Downloads
2
Citations
Altmetric
  Published on 19 Oct 2017
 Accepted on 29 Sep 2017            Submitted on 08 Sep 2017

Considering the scope of motivated cognition

Generally, motivation can be defined as goal-oriented behavior, often with the goal of maximizing pleasure and minimizing pain (Berridge, 2004; Hassin et al., 2009; Hughes & Zaki, 2015; Madan, 2013; see Kleinginna Jr. & Kleinginna, 1981, for an overview of different researchers’ definitions). As topics within the scope of of ‘motivated cognition’ often are considered more directly, I will first briefly describe a facet of this research area as an example. It is well known that emotion can influence how we attend to the world around us, such as in studies of the weapon-focus effect (Fawcett et al., 2013; Loftus et al., 1987; Steblay, 1992) and flash-bulb memories (Bohn & Berntsen, 2007; Brown & Kulik, 1977; Hirst et al., 2009). These findings lay the foundation for theories such as the attentional narrowing hypothesis (Easterbrook, 1959) and arousal-biased competition hypothesis (Mather & Sutherland, 2011) (though there is also evidence of a role of distinctiveness; Dewhurst & Parry, 2000; Pickel, 1998; Talmi & Moscovitch, 2004). However, a broader view would be to consider emotion-cognition interactions as segment of a more extensive literature on goal-oriented behavior and motivation, a domain-general perspective on the influences of motivational factors on cognition. For instance, rewards have been shown to similarly bias attention allocation, even when using considerably different experimental procedures (Anderson, 2013, 2016a; Awh et al., 2012). This broader view is in-line with recent perspectives on the influence of motivation on cognition (Botvinick & Braver, 2015; Braver et al., 2014; Chiew & Braver, 2011; Cunningham & Brosch, 2012; Gable & Harmon-Jones, 2010; Harmon-Jones et al., 2012a, b; Hughes & Zaki, 2015; Madan, 2013; Murty & Dickerson, 2017; Northoff & Hayes, 2011).

Emotion and reward

Considered broadly, emotion and reward processing bare many commonalities in their influence on cognition. For instance, both can preferentially capture attention (Aarts et al., 2008; Anderson, 2005, 2013, 2016a; Arnell et al., 2007; Bocanegra & Zeelenberg, 2009; MacKay et al., 2004; Raymond & O’Brien, 2009; Strange et al., 2003) and lead to impairments in processing of peripheral information information (Anderson, 2013; Anderson & Yantis, 2013; Bucker & Theeuwes, 2017; Dolcos et al., 2011; Kensinger et al., 2007; Talmi, 2013). Moreover, even when allowing for sufficient allocation of attention, both emotion and reward can impair memory for intentionally encoded contextual information (Madan et al., 2012a, 2017a, 2012b; Zimmerman & Kelley, 2010). Emotional arousal is often thought to be the principle dimension (as opposed to valence) (Bradley et al., 2001; Christianson, 1992; Mather & Sutherland, 2011; Talmi, 2013), and there is increasing evidence that ‘salience,’ an analogous dimension, is important to reward processing (Castel et al., 2016; Kahneman et al., 1993; Litt et al., 2011; Ludvig et al., 2014; Madan et al., 2014; Madan & Spetch, 2012; Tsetsos et al., 2012; Wispinski et al., 2017; Zeigenfuse et al., 2014). Providing more mechanistic similarities between emotion and reward, both have been shown to relate to autonomic function (e.g., pupil dilation and heart rate) (Abercrombie et al., 2008; Ariel & Castel, 2014; Bijleveld et al., 2009; Bradley et al., 2001, 2008; Buchanan et al., 2006; Fowles et al., 1982; Hochman & Yechiam, 2011; Manohar et al., 2017). Additionally, there are age-related differences in both emotion and reward processing, where older adults are more biased towards positively valenced and gain experiences, than negative/loss experiences (Barber et al., 2016; Carstensen & Mikels, 2005; Castel et al., 2016; Mikels & Reed, 2009; Mikels et al., 2016; Pachur et al., 2017; Samanez Larkin et al., 2007). This parallel may be somewhat exaggerated, however, as emotion and reward are sometimes experimentally operationalized similarly, and thus would produce similar effects in behavior. Specifically, both emotion and reward are often studied using shocks (Bauch et al., 2014; Bisby & Burgess, 2014; Dunsmoor et al., 2015; Jensen et al., 2007; Murty et al., 2012, 2011; Pessoa, 2009; Phelps & LeDoux, 2005; Redondo et al., 2014; Schmidt et al., 2015; Wang et al., 2013; Weiner & Walker, 1966), food (Beaver et al., 2006; de Water et al., 2017; Isen & Geva, 1987; LaBar et al., 2001; Polanía et al., 2015; Talmi et al., 2013; Wadlinger & Isaacowitz, 2006), emotional face pictures (Bradley et al., 1997; Lin et al., 2012; Tsukiura & Cabeza, 2008; Vrijsen et al., 2013; Vuilleumier & Schwartz, 2001; Woud et al., 2013), or erotic/sexual pictures (Attard-Johnson & Bindemann, 2017; Bradley et al., 2001; Ferrey et al., 2012; Hamann et al., 2004; Iigaya et al., 2016; Most et al., 2007; Sescousse et al., 2013a, 2010). As such, it would be expected that both emotion and reward demonstrate similar effects on cognition, as they can be studied using nearly identical experimental designs.

Despite these similarities between how emotion- and reward- processing are studied, there are also a variety of differences. Providing evidence of distinct roles of emotion and reward, when varied within the same experiment, the two factors can produce additive effects (Shigemune et al., 2010) or have otherwise been shown to separably influence behavior (Bennion et al., 2016; Bowen & Spaniol, 2017; Chiew & Braver, 2014; Isen et al., 1988; Mather & Schoeke, 2011; Otto et al., 2016). Emotion is often studied using stimuli that are inherently emotional–words, pictures, sounds, or videos that themselves semantically connote emotional content (Kensinger et al., 2007; MacKay et al., 2004; Madan et al., 2012a, 2017c; Shafer et al., 2012; Shigemune et al., 2010; Strange et al., 2003). In contrast, reward is often implemented as an instructional cue or feedback outcome (Adcock et al., 2006; Castel et al., 2002; Mason et al., 2017; Murayama & Kitagami, 2014; Murty et al., 2012; Pessiglione et al., 2007; Shigemune et al., 2010; Shohamy & Adcock, 2010; Spaniol et al., 2013). Though this dissociation is often true, there are exceptions—such as emotion studies where emotionally neutral stimuli are associated with emotional responses through a similar training task (Mather & Knight, 2008), emotional stimuli are presented just prior to the stimuli of interest (Qiao-Tasserit et al., 2017; Xie & Zhang, 2016, 2017), or with emotional stimuli are used as a feedback signal (Finn & Roediger, 2011). Similarly, in reward studies, items can be ‘trained’ to have a reward value before the task-of-interest (Anderson, 2013; Madan et al., 2012b; Madan & Spetch, 2012; Raymond & O’Brien, 2009), While a comparison of instructed vs. learned rewards has not been studied directly, there is a parallel with the literature on decisions from uncertainty. Specifically, studies have found differences in people’s risk preferences when decisions are made based on explicitly described odds and outcomes (‘decisions from description’), relative to those based on learned experiences (‘decisions from experience’) (Barron & Erev, 2003; Camilleri & Newell, 2011; Hertwig & Erev, 2009; Jessup et al., 2008; Ludvig et al., 2014; Ludvig & Spetch, 2011; Madan et al., 2017b; Mata et al., 2011; Yoon et al., 2017) (also see Braem et al., 2017).

A particularly interesting consideration when comparing the motivational characteristics of emotion and reward processing is the role of valence—emotional experiences can be either positive or negative (i.e., pleasant or unpleasant), rewards can be either gains or losses (though these could be gains and losses relative to expectations, based on either the average outcome or prior experiences). Within their respective literatures, when only one valence is included, it is often the case that only negatively valenced emotional effects are studied, whereas only gain reward outcomes are included. Given the growing literatures demonstrating valence effects in both emotion (Bowen et al., in press; Fredrickson & Branigan, 2005; Gasper & Clore, 2002; Kensinger & Corkin, 2004; Taylor, 1991; Xie & Zhang, 2016) and reward (Jensen et al., 2007; Kahneman & Tversky, 1984; Lejarraga & Hertwig, 2016; Litt et al., 2011; Ludvig et al., 2014; Samanez Larkin et al., 2007) effects on cognition, it is important to be aware of this limitation when only one valence is included in an experimental design. Motivation more generally can also be valenced, as a continuum of approach vs. avoidance motivation (Braver et al., 2014; Gable & Harmon-Jones, 2010; Kaplan et al., 2012; Murty et al., 2011; Vrijsen et al., 2013; Woud et al., 2013). Critically, this valence dimension of motivation does not directly map onto the valence of emotions or rewards. For instance, both anger and determination can be considered an approach motivation, while fear corresponds with avoidance (Carver & Harmon-Jones, 2009; Harmon-Jones et al., 2011, 2013).

Within the domain of rewards, there are a multitude of forms that a reward can take. Monetary rewards are the most common type of incentive; the use of shocks, and thus the avoidance of punishment, is also used often. However, it is important to consider that other rewards may yield different effects on cognition. Rather than examining these different rewards in isolation, a subset of studies have taken the approach of comparing their effects, or putting them in conflict. For instance, some studies have examined the motivational effects of monetary reward alongside another reward-related stimuli type, such as an appetitive juice reinforcer (Beck et al., 2010; Krug & Braver, 2014; Yee et al., 2016) or pain induction (Delgado et al., 2011; Murty et al., 2011; Read & Loewenstein, 1999; Talmi et al., 2009; Vlaev et al., 2014, 2009; Zhou & Gao, 2008). Other studies use what could be broadly considered a social reward, such as smiling face (Lin et al., 2012), indicator of social status (Izuma et al., 2008; Zink et al., 2008), or erotic pictures (Iigaya et al., 2016; Sescousse et al., 2013a, b). Additionally, some studies have investigated the motivational role of monetary feedback relative to verbal praise (e.g., “Very well done!”, “Great job!”) (Albrecht et al., 2014; Deci, 1971, 1972; Williams & DeSteno, 2008) though comparisons between reward categories have also been studied (Gross et al., 2014; Roper & Vecera, 2016; Rosati & Hare, 2016).

Other motivational factors

The extent of motivation on cognition is not constrained to emotion and reward. From the current perspective, other factors that lead to selective prioritization of cognitive processes also include the influences of motoric and self-referential processing.

While it is clear that emotion- and reward-related information are preferentially processed and modulate cognitive processes, it is likely less obvious that this may also be true for motor movements. It can be argued that the entire purpose of the brain is to produce movement–the ‘motor chauvinist’ view (Wolpert et al., 2001), a particularly strong perspective within the scope of embodied cognition. While this is an extreme stance, there is evidence that motor processes–such as enacted actions, gestures, and exercise–are beneficial to cognitive processes (Madan & Singhal, 2012b, c). Here motoric processing can be viewed as a type of goal-oriented behavior and in alignment with an approach motivation. A number of more subtle manipulations have demonstrated that cognitive processes can cue motor representations and influence motor movements, and that motor representations can modulate performance in cognitive tasks. For instance, in a simple task involving reaching for blocks and picking them up, grasping kinematics are influenced by text printed on the blocks, such as ‘long’ or ‘short’, as well as by words representing relative large or small objects (e.g., ‘apple’ or ‘grape’) (Gentilucci et al., 2000; Gentilucci & Gangitano, 1998; Glover et al., 2004). In the opposite direction, motor congruency of objects and pictures of objects, such as the side of a handle can influence response time and other measures in cognitive tasks (Brouillet et al., 2015; Buccino et al., 2009; Chum et al., 2007; Handy et al., 2003; Marino et al., 2014; Oakes & Onyper, 2017; Tucker & Ellis, 1998). Even more broadly, words and pictures representing objects varying in functionality can influence attention, semantic processing, and memory (Hauk et al., 2004; Madan et al., 2016; Madan & Singhal, 2012a; Montefinese et al., 2013; Pulvermüller, 2005; Shebani & Pulvermüller, 2013; Tousignant & Pexman, 2012; Witt et al., 2010). These effects are particularly interesting given debates regarding the role of evoked motor functionality information in response to pictures and words, as opposed to physical objects (Skiba & Snow, 2016; Snow et al., 2011, 2014; Squires et al., 2016; Wilson & Golonka, 2013). Taken together, functional objects can also capture attention, interfere with concurrent processes, and elicit approach motivation responses in ways that share commonalities with emotion and reward processes.

Self-referential processing can also be considered subset of motivated cognition. Unlike emotion-, reward-, and motor-processing, which are properties of the stimuli or how they are attended to, self-relevance is a property of the stimuli’s congruence with the participant. Often self relevance is studied using words that relate to the participant, such as personality trait adjectives (e.g., ‘curious’, ‘stingy’) (Fujiwara et al., 2008; Gutchess et al., 2007; Rogers et al., 1977; Symons & Johnson, 1997; Wentura et al., 2000) or autobiographical words (e.g., hometown, high school) (Gray et al., 2004; Yamawaki et al., in press). In other studies, self relevance is experimentally assigned, such as using sentences that refer to either ‘you’ or another person (Fields & Kuperberg, 2012) or by assigning the ownership of presented objects to the participant or ‘other’ (Cunningham et al., 2008; DeScioli et al., 2015; Truong et al., 2016, 2017). (See Northoff et al., 2006, for a review.) In some ways these two approaches align with the distinction outlined with emotion and reward studies, where the property can either be congruence between self and the stimuli (personality trait adjectives) or implemented as part of the task instructions (assigned ownership). Similar to both emotion and reward, self-referential stimuli can also elicit attentional capture (Alexopoulos et al., 2012; Arnell et al., 1999; Bargh, 1982; Tacikowski & Nowicka, 2010). This is particularly well exemplified by the ‘cocktail party effect,’ where people are able to focus on a particular conversation amidst a variety of concurrent sounds, but can readily and automatically attend to a different conversation if their name is mentioned (Conway et al., 2001; Moray, 1959; Wood & Cowan, 1995). Nonetheless, prior work has demonstrated that the effects of self-referential processing can be dissociated from reward (Northoff & Hayes, 2011) and emotion (Fields & Kuperberg, 2012, 2016; Grilli et al., in press; Kensinger & Gutchess, 2016) processes. In some studies, social cues have been used analogously to rewards, such as trial feedback (Anderson, 2016b, 2017) or in association with other stimuli, such as faces, as a signal for importance (Hargis & Castel, in press). More broadly, it has been shown that people exhibit a bias to pay more attention to pictures of their enemies and incidentally remembered more information about their enemies (Li et al., in press). Along this social dimension, people have also been found to have an ‘own-race bias,’ where people remembered faces of individuals of the same racial background better than those of another race (DeLozier & Rhodes, 2015). To some degree, cultural differences in attention and memory may also be influenced by collective self-referential effects, where cultural background leads to inter-individual differences in how contextual information is prioritized and attended to (Lin & Han, 2009; Masuda & Nisbett, 2001; Millar et al., 2013). In sum, studies of self-referential processing have demonstrated that we have a bias towards stimuli that correspond to ownership or our identity. The design of these self-referential studies share many commonalities with emotion and reward, in operationalization and in their observed influence on cognitive processing, providing additional support for a domain-general view of motivation-cognition interactions and goal-oriented behavior.

Importantly, the factors discussed thus far are not intended to be an exhaustive list of motivational factors known to influence cognitive processes. Beyond motoric and self-referential processing, numerous other distinct factors can also be construed as being instances of motivated cognition. For instance, people have also been shown to be able to prioritize memory for words representing allergens and medication side-effects that were instructed to be more severe (Friedman et al., 2015; Middlebrooks et al., 2016), similar to prior prioritization studies that used reward values (Castel et al., 2002). It has also been shown in a number of studies that words processed with their survival relevance in-mind are remembered better than in the context of several other instructions (Kang et al., 2008; Nairne & Pandeirada, 2008; Nairne et al., 2008, 2007; Soderstrom & McCabe, 2011; Weinstein et al., 2008). Food stimuli, briefly discussed as being used in both studies of emotion and reward, have also been studied in their own right as a means of probing motivational processes, particularly with interest in time-varying differences in motivation through satiation (Radel & Clément-Guillotin, 2012; Skrynka & Vincent, 2017; Wagner et al., 2012) and other measures of physiological homeostasis (Padulo et al., 2017; Tiedemann et al., 2017).

Conclusion

In sum, it is clear that motivation can guide cognition. These motivational factors–including, but not limited to, emotion and reward processes—modulate behavior across a variety of cognitive domains, often resulting in the prioritized processing of some stimuli. Nonetheless, many of the nuances of these motivation-cognition interactions have yet to be sufficiently understood. One general question is the specificity of these different motivational factors in modulating cognition. For instance, how much of what is known about the effects of emotion on memory can be considered domain-general characteristics of motivational salience and valence, rather than domain-specific effects of emotion? Along these lines, it is clear that emotion and reward, among other factors, necessitate unique research approaches (Gershman & Daw, 2017; Mattek et al., 2017; Panksepp et al., 2017; Schultz, 2015), but it is an open question where the boundaries lie between these different facets of motivation. More broadly, while the position of this perspective paper is that these factors can be summarized as ‘motivational factors’ despite a variety of differences–this is far from conclusive. It is well-established that there are different mechanisms and brain structures associated with these factors, but there nonetheless is a substantiative number of commonalities between them as well. My hope is that this perspective article will provide a new lens evaluate existing research and help to inspire further research to better understand how these constructs relate to each other.

Associated with this Perspective article is a new ‘research nexus’ at Collabra: Psychology, focused on fostering future research into motivated cognition. Briefly, a research nexus is similar to a special issue/collection in a journal, but in addition to invited authors and articles, the nexus will remain open for submissions, in order to create a growing collection of articles around the topic. In this newly launched research nexus, we welcome research into any individual motivational factor and their influence on cognition, as well as studies that compare or otherwise investigate the interactions between different motivational factors. While the perspective outlined here is suggestive that nearly all of cognition is motivated, manuscripts submitted to this research nexus must explicitly discuss how their research question and findings inform our understanding of the influence of motivation on cognition. Studies comparing different motivational factors are of particular interest, as this work is ultimately necessary to address open questions regarding the overlap or diversity in how different factors influence cognition.

Acknowledgements

I would like to thank Ryan Daley, Elizabeth, Kensinger, John Ksander, and Debbie Yee for feedback on an earlier draft of the manuscript.

Competing Interests

Christopher Madan is an Editor at Collabra: Psychology. He was not involved in the peer review of the article.

References

  1. Aarts, H., Custers, R. and Marien, H. (2008). Preparing and motivating behavior outside of awareness. Science 319: 1639–1639, DOI: https://doi.org/10.1126/science.1150432 

  2. Abercrombie, H. C., Chambers, A. S., Greischar, L. and Monticelli, R. M. (2008). Orienting, emotion, and memory: phasic and tonic variation in heart rate predicts memory for emotional pictures in men. Neurobiology of Learning and Memory 90: 644–650, DOI: https://doi.org/10.1016/j.nlm.2008.08.001 

  3. Adcock, R. A., Thangavel, A., Whitfield-Gabrieli, S., Knutson, B. and Gabrieli, J. D. (2006). Reward-motivated learning: Mesolimbic activation precedes memory formation. Neuron 50: 507–517, DOI: https://doi.org/10.1016/j.neuron.2006.03.036 

  4. Albrecht, K., Abeler, J., Weber, B. and Falk, A. (2014). The brain correlates of the effects of monetary and verbal rewards on intrinsic motivation. Frontiers in Neuroscience 8: 303.DOI: https://doi.org/10.3389/fnins.2014.00303 

  5. Alexopoulos, T., Muller, D., Ric, F. and Marendaz, C. (2012). I, me, mine: Automatic attentional capture by self-related stimuli. European Journal of Social Psychology 42: 770–779, DOI: https://doi.org/10.1002/ejsp.1882 

  6. Anderson, A. K. (2005). Affective influences on the attentional dynamics supporting awareness. Journal of Experimental Psychology: General 134: 258–281, DOI: https://doi.org/10.1037/0096-3445.134.2.258 

  7. Anderson, B. A. (2013). A value-driven mechanism of attentional selection. Journal of Vision 13: 7–7, DOI: https://doi.org/10.1167/13.3.7 

  8. Anderson, B. A. (2016a). The attention habit: how reward learning shapes attentional selection. Annals of the New York Academy of Sciences 1369: 24–39, DOI: https://doi.org/10.1111/nyas.12957 

  9. Anderson, B. A. (2016b). Social reward shapes attentional biases. Cognitive Neuroscience 7: 30–36, DOI: https://doi.org/10.1080/17588928.2015.1047823 

  10. Anderson, B. A. (2017). Counterintuitive effects of negative social feedback on attention. Cognition and Emotion 31: 590–597, DOI: https://doi.org/10.1080/02699931.2015.1122576 

  11. Anderson, B. A. and Yantis, S. (2013). Persistence of value-driven attentional capture. Journal of Experimental Psychology: Human Perception and Performance 39: 6–9, DOI: https://doi.org/10.1037/a0030860 

  12. Ariel, R. and Castel, A. D. (2014). Eyes wide open: enhanced pupil dilation when selectively studying important information. Experimental Brain Research 232: 337–344, DOI: https://doi.org/10.1007/s00221-013-3744-5 

  13. Arnell, K. M., Killman, K. V. and Fijavz, D. (2007). Blinded by emotion: Target misses follow attention capture by arousing distractors in RSVP. Emotion 7: 465–477, DOI: https://doi.org/10.1037/1528-3542.7.3.465 

  14. Arnell, K. M., Shapiro, K. L. and Sorensen, R. E. (1999). Reduced repetition blindness for one’s own name. Visual Cognition 6: 609–635, DOI: https://doi.org/10.1080/135062899394876 

  15. Attard-Johnson, J. and Bindemann, M. (2017). Sex-specific but not sexually explicit: pupillary responses to dressed and naked adults. Royal Society Open Science 4: 160963.DOI: https://doi.org/10.1098/rsos.160963 

  16. Awh, E., Belopolsky, A. V. and Theeuwes, J. (2012). Top–down versus bottom–up attentional control: a failed theoretical dichotomy. Trends in Cognitive Sciences 16: 437–443, DOI: https://doi.org/10.1016/j.tics.2012.06.010 

  17. Barber, S. J., Opitz, P. C., Martins, B., Sakaki, M. and Mather, M. (2016). Thinking about a limited future enhances the positivity of younger and older adults’ recall: Support for socioemotional selectivity theory. Memory & Cognition 44: 869–882, DOI: https://doi.org/10.3758/s13421-016-0612-0 

  18. Bargh, J. A. (1982). Attention and automaticity in the processing of self-relevant information. Journal of Personality and Social Psychology 43: 425–436, DOI: https://doi.org/10.1037/0022-3514.43.3.425 

  19. Barron, G. and Erev, I. (2003). Small feedback-based decisions and their limited correspondence to description-based decisions. Journal of Behavioral Decision Making 16: 215–233, DOI: https://doi.org/10.1002/bdm.443 

  20. Bauch, E. M., Rausch, V. H. and Bunzeck, N. (2014). Pain anticipation recruits the mesolimbic system and differentially modulates subsequent recognition memory. Human Brain Mapping 35: 4594–4606, DOI: https://doi.org/10.1002/hbm.22497 

  21. Beaver, J. D., Lawrence, A. D., van Ditzhuijzen, J., Davis, M. H., Woods, A. and Calder, A. J. (2006). Individual differences in reward drive predict neural responses to images of food. Journal of Neuroscience 26: 5160–5166, DOI: https://doi.org/10.1523/JNEUROSCI.0350-06.2006 

  22. Beck, S. M., Locke, H. S., Savine, A. C., Jimura, K. and Braver, T. S. (2010). Primary and secondary rewards differentially modulate neural activity dynamics during working memory. PLoS ONE 5: e9251.DOI: https://doi.org/10.1371/journal.pone.0009251 

  23. Bennion, K. A., Payne, J. D. and Kensinger, E. A. (2016). The impact of napping on memory for future-relevant stimuli: Prioritization among multiple salience cues. Behavioral Neuroscience 130: 281–289, DOI: https://doi.org/10.1037/bne0000142 

  24. Berridge, K. C. (2004). Motivation concepts in behavioral neuroscience. Physiology & Behavior 81: 179–209, DOI: https://doi.org/10.1016/j.physbeh.2004.02.004 

  25. Bijleveld, E., Custers, R. and Aarts, H. (2009). The unconscious eye opener. Psychological Science 20: 1313–1315, DOI: https://doi.org/10.1111/j.1467-9280.2009.02443.x 

  26. Bisby, J. A. and Burgess, N. (2014). Negative affect impairs associative memory but not item memory. Learning & Memory 21: 760–766, DOI: https://doi.org/10.1101/lm.032409.113 

  27. Bocanegra, B. R. and Zeelenberg, R. (2009). Dissociating emotion-induced blindness and hypervision. Emotion 9: 865–873, DOI: https://doi.org/10.1037/a0017749 

  28. Bohn, A. and Berntsen, D. (2007). Pleasantness bias in flashbulb memories: Positive and negative flashbulb memories of the fall of the berlin wall among east and west germans. Memory & Cognition 35: 565–577, DOI: https://doi.org/10.3758/BF03193295 

  29. Botvinick, M. and Braver, T. (2015). Motivation and cognitive control: From behavior to neural mechanism. Annual Review of Psychology 66: 83–113, DOI: https://doi.org/10.1146/annurev-psych-010814-015044 

  30. Bowen, H. J., Kark, S. M. and Kensinger, E. A. (). NEVER forget: negative emotional valence enhances recapitulation. Psychonomic Bulletin & Review, DOI: https://doi.org/10.3758/s13423-017-1313-9 (in press). 

  31. Bowen, H. J. and Spaniol, J. (2017). Effects of emotion and motivation on memory dissociate in the context of losses. Learning and Motivation 58: 77–87, DOI: https://doi.org/10.1016/j.lmot.2017.05.003 

  32. Bradley, B. P., Mogg, K., Millar, N., Bonham-Carter, C., Fergusson, E., Jenkins, J. and Parr, M. (1997). Attentional biases for emotional faces. Cognition & Emotion 11: 25–42, DOI: https://doi.org/10.1080/026999397380014 

  33. Bradley, M. M., Codispoti, M., Cuthbert, B. N. and Lang, P. J. (2001). Emotion and motivation i: Defensive and appetitive reactions in picture processing. Emotion 1: 276–298, DOI: https://doi.org/10.1037/1528-3542.1.3.276 

  34. Bradley, M. M., Miccoli, L., Escrig, M. A. and Lang, P. J. (2008). The pupil as a measure of emotional arousal and autonomic activation. Psychophysiology 45: 602–607, DOI: https://doi.org/10.1111/j.1469-8986.2008.00654.x 

  35. Braem, S., Houwer, J. D., Demanet, J., Yuen, K. S., Kalisch, R. and Brass, M. (2017). Pattern analyses reveal separate experience based fear memories in the human right amygdala. The Journal of Neuroscience 37: 8116–8130, DOI: https://doi.org/10.1523/JNEUROSCI.0908-17.2017 

  36. Braver, T. S., Krug, M. K., Chiew, K. S., Kool, W., Westbrook, J. A., Clement, N. J., Adcock, R. A., Barch, D. M., Botvinick, M. M., Carver, C. S., Cools, R., Custers, R., Dickinson, A., Dweck, C. S., Fishbach, A., Gollwitzer, P. M., Hess, T. M., Isaacowitz, D. M., Mather, M., Murayama, K., Pessoa, L., Samanez-Larkin, G. R. and Somerville, L. H. (2014). Mechanisms of motivation–cognition interaction: challenges and opportunities. Cognitive, Affective, & Behavioral Neuroscience 14: 443–472, DOI: https://doi.org/10.3758/s13415-014-0300-0 

  37. Brouillet, D., Brouillet, T., Milhau, A., Heurley, L., Vagnot, C. and Brunel, L. (2015). Word-to-picture recognition is a function of motor components mappings at the stage of retrieval. International Journal of Psychology 51: 397–402, DOI: https://doi.org/10.1002/ijop.12210 

  38. Brown, R. and Kulik, J. (1977). Flashbulb memories. Cognition 5: 73–99, DOI: https://doi.org/10.1016/0010-0277(77)90018-X 

  39. Buccino, G., Sato, M., Cattaneo, L., Rodà, F. and Riggio, L. (2009). Broken affordances, broken objects: A TMS study. Neuropsychologia 47: 3074–3078, DOI: https://doi.org/10.1016/j.neuropsychologia.2009.07.003 

  40. Buchanan, T. W., Etzel, J. A., Adolphs, R. and Tranel, D. (2006). The influence of autonomic arousal and semantic relatedness on memory for emotional words. International Journal of Psychophysiology 61: 26–33, DOI: https://doi.org/10.1016/j.ijpsycho.2005.10.022 

  41. Bucker, B. and Theeuwes, J. (2017). Pavlovian reward learning underlies value driven attentional capture. Attention, Perception, & Psychophysics 79: 415–428, DOI: https://doi.org/10.3758/s13414-016-1241-1 

  42. Camilleri, A. R. and Newell, B. R. (2011). When and why rare events are underweighted: A direct comparison of the sampling, partial feedback, full feedback and description choice paradigms. Psychonomic Bulletin & Review 18: 377–384, DOI: https://doi.org/10.3758/s13423-010-0040-2 

  43. Carstensen, L. L. and Mikels, J. A. (2005). At the intersection of emotion and cognition. Current Directions in Psychological Science 14: 117–121, DOI: https://doi.org/10.1111/j.0963-7214.2005.00348.x 

  44. Carver, C. S. and Harmon-Jones, E. (2009). Anger is an approach-related affect: Evidence and implications. Psychological Bulletin 135: 183–204, DOI: https://doi.org/10.1037/a0013965 

  45. Castel, A. D., Benjamin, A. S., Craik, F. I. M. and Watkins, M. J. (2002). The effects of aging on selectivity and control in short-term recall. Memory & Cognition 30: 1078–1085, DOI: https://doi.org/10.3758/BF03194325 

  46. Castel, A. D., Friedman, M. C., McGillivray, S., Flores, C. C., Murayama, K., Kerr, T. and Drolet, A. (2016). I owe you: age-related similarities and differences in associative memory for gains and losses. Aging, Neuropsychology, and Cognition 23: 549–565, DOI: https://doi.org/10.1080/13825585.2015.1130214 

  47. Chiew, K. S. and Braver, T. S. (2011). Positive affect versus reward: Emotional and motivational influences on cognitive control. Frontiers in Psychology 2: 279.DOI: https://doi.org/10.3389/fpsyg.2011.00279 

  48. Chiew, K. S. and Braver, T. S. (2014). Dissociable influences of reward motivation and positive emotion on cognitive control. Cognitive, Affective, & Behavioral Neuroscience 14: 509–529, DOI: https://doi.org/10.3758/s13415-014-0280-0 

  49. Christianson, S.-Å. (1992). Emotional stress and eyewitness memory: A critical review. Psychological Bulletin 112: 284–309, DOI: https://doi.org/10.1037/0033-2909.112.2.284 

  50. Chum, M., Bekkering, H., Dodd, M. D. and Pratt, J. (2007). Motor and visual codes interact to facilitate visuospatial memory performance. Psychonomic Bulletin & Review 14: 1189–1193, DOI: https://doi.org/10.3758/BF03193111 

  51. Conway, A. R. A., Cowan, N. and Bunting, M. F. (2001). The cocktail party phenomenon revisited: The importance of working memory capacity. Psychonomic Bulletin & Review 8: 331–335, DOI: https://doi.org/10.3758/BF03196169 

  52. Cunningham, S. J., Turk, D. J., Macdonald, L. M. and Macrae, C. N. (2008). Yours or mine? ownership and memory. Consciousness and Cognition 17: 312–318, DOI: https://doi.org/10.1016/j.concog.2007.04.003 

  53. Cunningham, W. A. and Brosch, T. (2012). Motivational salience: Amygdala tuning from traits, needs, values, and goals. Current Directions in Psychological Science 21: 54–59, DOI: https://doi.org/10.1177/0963721411430832 

  54. Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of Personality and Social Psychology 18: 105–115, DOI: https://doi.org/10.1037/h0030644 

  55. Deci, E. L. (1972). The effects of contingent and noncontingent rewards and controls on intrinsic motivation. Organizational Behavior and Human Performance 8: 217–229, DOI: https://doi.org/10.1016/0030-5073(72)90047-5 

  56. Delgado, M. R., Jou, R. L. and Phelps, E. A. (2011). Neural systems underlying aversive conditioning in humans with primary and secondary reinforcers. Frontiers in Neuroscience 5: 71.DOI: https://doi.org/10.3389/fnins.2011.00071 

  57. DeLozier, S. and Rhodes, M. G. (2015). The impact of value-directed remembering on the own-race bias. Acta Psychologica 154: 62–68, DOI: https://doi.org/10.1016/j.actpsy.2014.11.009 

  58. DeScioli, P., Rosa, N. M. and Gutchess, A. H. (2015). A memory advantage for property. Evolutionary Psychology 13: 411–423, DOI: https://doi.org/10.1177/147470491501300205 

  59. de Water, E., Mies, G. W., Figner, B., Yoncheva, Y., van den Bos, W., Castellanos, F. X., Cillessen, A. H. N. and Scheres, A. (2017). Neural mechanisms of individual differences in temporal discounting of monetary and primary rewards in adolescents. NeuroImage 153: 198–210, DOI: https://doi.org/10.1016/j.neuroimage.2017.04.013 

  60. Dewhurst, S. A. and Parry, L. A. (2000). Emotionality, distinctiveness, and recollective experience. European Journal of Cognitive Psychology 12: 541–551, DOI: https://doi.org/10.1080/095414400750050222 

  61. Dolcos, F., Iordan, A. D. and Dolcos, S. (2011). Neural correlates of emotion–cognition interactions: A review of evidence from brain imaging investigations. Journal of Cognitive Psychology 23: 669–694, DOI: https://doi.org/10.1080/20445911.2011.594433 

  62. Dunsmoor, J. E., Murty, V. P., Davachi, L. and Phelps, E. A. (2015). Emotional learning selectively and retroactively strengthens memories for related events. Nature 520: 345–348, DOI: https://doi.org/10.1038/nature14106 

  63. Easterbrook, J. A. (1959). The effect of emotion on cue utilization and the organization of behavior. Psychological Review 66: 183–201, DOI: https://doi.org/10.1037/h0047707 

  64. Fawcett, J. M., Russell, E. J., Peace, K. A. and Christie, J. (2013). Of guns and geese: a meta-analytic review of the ‘weapon focus’ literature. Psychology, Crime & Law 19: 35–66, DOI: https://doi.org/10.1080/1068316X.2011.599325 

  65. Ferrey, A. E., Frischen, A. and Fenske, M. J. (2012). Hot or not: Response inhibition reduces the hedonic value and motivational incentive of sexual stimuli. Frontiers in Psychology 3: 575.DOI: https://doi.org/10.3389/fpsyg.2012.00575 

  66. Fields, E. C. and Kuperberg, G. R. (2012). It’s all about you: An ERP study of emotion and self-relevance in discourse. NeuroImage 62: 562–574, DOI: https://doi.org/10.1016/j.neuroimage.2012.05.003 

  67. Fields, E. C. and Kuperberg, G. R. (2016). Dynamic effects of self-relevance and task on the neural processing of emotional words in context. Frontiers in Psychology 6: 2003.DOI: https://doi.org/10.3389/fpsyg.2015.02003 

  68. Finn, B. and Roediger, H. L. (2011). Enhancing retention through reconsolidation. Psychological Science 22: 781–786, DOI: https://doi.org/10.1177/0956797611407932 

  69. Fowles, D. C., Fisher, A. E. and Tranel, D. T. (1982). The heart beats to reward: The effect of monetary incentive on heart rate. Psychophysiology 19: 506–513, DOI: https://doi.org/10.1111/j.1469-8986.1982.tb02577.x 

  70. Fredrickson, B. L. and Branigan, C. (2005). Positive emotions broaden the scope of attention and thought-action repertoires. Cognition & Emotion 19: 313–332, DOI: https://doi.org/10.1080/02699930441000238 

  71. Friedman, M. C., McGillivray, S., Murayama, K. and Castel, A. D. (2015). Memory for medication side effects in younger and older adults: The role of subjective and objective importance. Memory & Cognition 43: 206–215, DOI: https://doi.org/10.3758/s13421-014-0476-0 

  72. Fujiwara, E., Levine, B. and Anderson, A. K. (2008). Intact implicit and reduced explicit memory for negative self-related information in repressive coping. Cognitive, Affective, & Behavioral Neuroscience 8: 254–263, DOI: https://doi.org/10.3758/CABN.8.3.254 

  73. Gable, P. and Harmon-Jones, E. (2010). The motivational dimensional model of affect: Implications for breadth of attention, memory, and cognitive categorisation. Cognition & Emotion 24: 322–337, DOI: https://doi.org/10.1080/02699930903378305 

  74. Gasper, K. and Clore, G. L. (2002). Attending to the big picture: Mood and global versus local processing of visual information. Psychological Science 13: 34–40, DOI: https://doi.org/10.1111/1467-9280.00406 

  75. Gentilucci, M., Benuzzi, F., Bertolani, L., Daprati, E. and Gangitano, M. (2000). Language and motor control. Experimental Brain Research 133: 468–490, DOI: https://doi.org/10.1007/s002210000431 

  76. Gentilucci, M. and Gangitano, M. (1998). Influence of automatic word reading on motor control. European Journal of Neuroscience 10: 752–756, DOI: https://doi.org/10.1046/j.1460-9568.1998.00060.x 

  77. Gershman, S. J. and Daw, N. D. (2017). Reinforcement learning and episodic memory in humans and animals: An integrative framework. Annual Review of Psychology 68: 101–128, DOI: https://doi.org/10.1146/annurev-psych-122414-033625 

  78. Glover, S., Rosenbaum, D. A., Graham, J. and Dixon, P. (2004). Grasping the meaning of words. Experimental Brain Research 154: 103–108, DOI: https://doi.org/10.1007/s00221-003-1659-2 

  79. Gray, H. M., Ambady, N., Lowenthal, W. T. and Deldin, P. (2004). P300 as an index of attention to self-relevant stimuli. Journal of Experimental Social Psychology 40: 216–224, DOI: https://doi.org/10.1016/S0022-1031(03)00092-1 

  80. Grilli, M. D., Woolverton, C. B., Crawford, M. and Glisky, E. L. (). Self-reference and emotional memory effects in older adults at increased genetic risk of alzheimer’s disease. Aging, Neuropsychology, and Cognition, DOI: https://doi.org/10.1080/13825585.2016.1275508 (in press). 

  81. Gross, J., Woelbert, E., Zimmermann, J., Okamoto-Barth, S., Riedl, A. and Goebel, R. (2014). Value signals in the prefrontal cortex predict individual preferences across reward categories. Journal of Neuroscience 34: 7580–7586, DOI: https://doi.org/10.1523/JNEUROSCI.5082-13.2014 

  82. Gutchess, A. H., Kensinger, E. A., Yoon, C. and Schacter, D. L. (2007). Ageing and the self-reference effect in memory. Memory 15: 822–837, DOI: https://doi.org/10.1080/09658210701701394 

  83. Hamann, S., Herman, R. A., Nolan, C. L. and Wallen, K. (2004). Men and women differ in amygdala response to visual sexual stimuli. Nature Neuroscience 7: 411–416, DOI: https://doi.org/10.1038/nn1208 

  84. Handy, T. C., Grafton, S. T., Shroff, N. M., Ketay, S. and Gazzaniga, M. S. (2003). Graspable objects grab attention when the potential for action is recognized. Nature Neuroscience 6: 421–427, DOI: https://doi.org/10.1038/nn1031 

  85. Hargis, M. B. and Castel, A. D. (). Younger and older adults’ associative memory for social information: The role of information importance. Psychology and Aging 32: 325–330, DOI: https://doi.org/10.1037/pag0000171 (in press). 

  86. Harmon-Jones, C., Schmeichel, B. J., Mennitt, E. and Harmon-Jones, E. (2011). The expression of determination: Similarities between anger and approach-related positive affect. Journal of Personality and Social Psychology 100: 172–181, DOI: https://doi.org/10.1037/a0020966 

  87. Harmon-Jones, E., Gable, P. A. and Price, T. F. (2012a). The influence of affective states varying in motivational intensity on cognitive scope. Frontiers in Integrative Neuroscience 6DOI: https://doi.org/10.3389/fnint.2012.00073 

  88. Harmon-Jones, E., Gable, P. A. and Price, T. F. (2012b). The influence of affective states on cognitive broadening/narrowing: Considering the importance of motivational intensity. Social and Personality Psychology Compass 6: 314–327, DOI: https://doi.org/10.1111/j.1751-9004.2012.00432.x 

  89. Harmon-Jones, E., Gable, P. A. and Price, T. F. (2013). Does negative affect always narrow and positive affect always broaden the mind? considering the influence of motivational intensity on cognitive scope. Current Directions in Psychological Science 22: 301–307, DOI: https://doi.org/10.1177/0963721413481353 

  90. Hassin, R. R., Aarts, H., Eitam, B., Custers, R. and Kleiman, T. (2009). Non-conscious goal pursuit and the effortful control of behavior In: Oxford handbook of human action. New York: Oxford University Press, pp. 549–566.  

  91. Hauk, O., Johnsrude, I. and Pulvermüller, F. (2004). Somatotopic representation of action words in human motor and premotor cortex. Neuron 41: 301–307, DOI: https://doi.org/10.1016/S0896-6273(03)00838-9 

  92. Hertwig, R. and Erev, I. (2009). The description–experience gap in risky choice. Trends in Cognitive Sciences 13: 517–523, DOI: https://doi.org/10.1016/j.tics.2009.09.004 

  93. Hirst, W., Phelps, E. A., Buckner, R. L., Budson, A. E., Cuc, A., Gabrieli, J. D. E., Johnson, M. K., Lustig, C., Lyle, K. B., Mather, M., Meksin, R., Mitchell, K. J., Ochsner, K. N., Schacter, D. L., Simons, J. S. and Vaidya, C. J. (2009). Long-term memory for the terrorist attack of september 11: Flashbulb memories, event memories, and the factors that influence their retention. Journal of Experimental Psychology: General 138: 161–176, DOI: https://doi.org/10.1037/a0015527 

  94. Hochman, G. and Yechiam, E. (2011). Loss aversion in the eye and in the heart: The autonomic nervous system’s responses to losses. Journal of Behavioral Decision Making 24: 140–156, DOI: https://doi.org/10.1002/bdm.692 

  95. Hughes, B. L. and Zaki, J. (2015). The neuroscience of motivated cognition. Trends in Cognitive Sciences 19: 62–64, DOI: https://doi.org/10.1016/j.tics.2014.12.006 

  96. Iigaya, K., Story, G. W., Kurth-Nelson, Z., Dolan, R. J. and Dayan, P. (2016). The modulation of savouring by prediction error and its effects on choice. eLife 5: e13747.DOI: https://doi.org/10.7554/eLife.13747 

  97. Isen, A. M. and Geva, N. (1987). The influence of positive affect on acceptable level of risk: The person with a large canoe has a large worry. Organizational Behavior and Human Decision Processes 39: 145–154, DOI: https://doi.org/10.1016/0749-5978(87)90034-3 

  98. Isen, A. M., Nygren, T. E. and Ashby, F. G. (1988). Influence of positive affect on the subjective utility of gains and losses: It is just not worth the risk. Journal of Personality and Social Psychology 55: 710–717, DOI: https://doi.org/10.1037/0022-3514.55.5.710 

  99. Izuma, K., Saito, D. N. and Sadato, N. (2008). Processing of social and monetary rewards in the human striatum. Neuron 58: 284–294, DOI: https://doi.org/10.1016/j.neuron.2008.03.020 

  100. Jensen, J., Smith, A. J., Willeit, M., Crawley, A. P., Mikulis, D. J., Vitcu, I. and Kapur, S. (2007). Separate brain regions code for salience vs. valence during reward prediction in humans. Human Brain Mapping 28: 294–302, DOI: https://doi.org/10.1002/hbm.20274 

  101. Jessup, R. K., Bishara, A. J. and Busemeyer, J. R. (2008). Feedback produces divergence from prospect theory in descriptive choice. Psychological Science 19: 1015–1022, DOI: https://doi.org/10.1111/j.1467-9280.2008.02193.x 

  102. Kahneman, D., Fredrickson, B. L., Schreiber, C. A. and Redelmeier, D. A. (1993). When more pain is preferred to less: Adding a better end. Psychological Science 4: 401–405, DOI: https://doi.org/10.1111/j.1467-9280.1993.tb00589.x 

  103. Kahneman, D. and Tversky, A. (1984). Choices, values, and frames. American Psychologist 39: 341–350, DOI: https://doi.org/10.1037/0003-066X.39.4.341 

  104. Kang, S. H. K., McDermott, K. B. and Cohen, S. M. (2008). The mnemonic advantage of processing fitness-relevant information. Memory & Cognition 36: 1151–1156, DOI: https://doi.org/10.3758/MC.36.6.1151 

  105. Kaplan, R. L., Damme, I. V. and Levine, L. J. (2012). Motivation matters: Differing effects of pre-goal and post-goal emotions on attention and memory. Frontiers in Psychology 3DOI: https://doi.org/10.3389/fpsyg.2012.00404 

  106. Kensinger, E. A. and Corkin, S. (2004). Two routes to emotional memory: Distinct neural processes for valence and arousal. Proceedings of the National Academy of Sciences 101: 3310–3315, DOI: https://doi.org/10.1073/pnas.0306408101 

  107. Kensinger, E. A., Garoff-Eaton, R. J. and Schacter, D. L. (2007). Effects of emotion on memory specificity: Memory trade-offs elicited by negative visually arousing stimuli. Journal of Memory and Language 56: 575–591, DOI: https://doi.org/10.1016/j.jml.2006.05.004 

  108. Kensinger, E. A. and Gutchess, A. H. (2016). Cognitive aging in a social and affective context: Advances over the past 50 years. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 72: 61–70, DOI: https://doi.org/10.1093/geronb/gbw056 

  109. Kleinginna, P. R. Jr. and Kleinginna, A. M. (1981). A categorized list of motivation definitions, with a suggestion for a consensual definition. Motivation and Emotion 5: 263–291, DOI: https://doi.org/10.1007/BF00993889 

  110. Krug, M. K. and Braver, T. S. (2014). Motivation and cognitive control: Going beyond monetary incentives In: The Psychological Science of Money. Springer, pp. 137–162, DOI: https://doi.org/10.1007/978-1-4939-0959-9_7 

  111. LaBar, K. S., Gitelman, D. R., Parrish, T. B., Kim, Y.-H., Nobre, A. C. and Mesulam, M.-M. (2001). Hunger selectively modulates corticolimbic activation to food stimuli in humans. Behavioral Neuroscience 115: 493–500, DOI: https://doi.org/10.1037/0735-7044.115.2.493 

  112. Lejarraga, T. and Hertwig, R. (2016). How the threat of losses makes people explore more than the promise of gains. Psychonomic Bulletin & Review 24: 708–720, DOI: https://doi.org/10.3758/s13423-016-1158-7 

  113. Li, L. M. W., Masuda, T. and Lee, H. (). Low relational mobility leads to greater motivation to understand enemies but not friends and acquaintances. British Journal of Social Psychology, DOI: https://doi.org/10.1111/bjso.12216 (in press). 

  114. Lin, A., Adolphs, R. and Rangel, A. (2012). Social and monetary reward learning engage overlapping neural substrates. Social Cognitive and Affective Neuroscience 7: 274–281, DOI: https://doi.org/10.1093/scan/nsr006 

  115. Lin, Z. and Han, S. (2009). Self-construal priming modulates the scope of visual attention. Quarterly Journal of Experimental Psychology 62: 802–813, DOI: https://doi.org/10.1080/17470210802271650 

  116. Litt, A., Plassmann, H., Shiv, B. and Rangel, A. (2011). Dissociating valuation and saliency signals during decision-making. Cerebral Cortex 21: 95–102, DOI: https://doi.org/10.1093/cercor/bhq065 

  117. Loftus, E. F., Loftus, G. R. and Messo, J. (1987). Some facts about “weapon focus”. Law and Human Behavior 11: 55–62, DOI: https://doi.org/10.1007/BF01044839 

  118. Ludvig, E. A., Madan, C. R. and Spetch, M. L. (2014). Extreme outcomes sway risky decisions from experience. Journal of Behavioral Decision Making 27: 146–156, DOI: https://doi.org/10.1002/bdm.1792 

  119. Ludvig, E. A. and Spetch, M. L. (2011). Of black swans and tossed coins: Is the description-experience gap in risky choice limited to rare events?. PLoS ONE 6: e20262.DOI: https://doi.org/10.1371/journal.pone.0020262 

  120. MacKay, D. G., Shafto, M., Taylor, J. K., Marian, D. E., Abrams, L. and Dyer, J. R. (2004). Relations between emotion, memory, and attention: Evidence from taboo stroop, lexical decision, and immediate memory tasks. Memory & Cognition 32: 474–488, DOI: https://doi.org/10.3758/BF03195840 

  121. Madan, C. R. (2013). Toward a common theory for learning from reward, affect, and motivation: the SIMON framework. Frontiers in Systems Neuroscience 7DOI: https://doi.org/10.3389/fnsys.2013.00059 

  122. Madan, C. R., Caplan, J. B., Lau, C. S. and Fujiwara, E. (2012a). Emotional arousal does not enhance association-memory. Journal of Memory and Language 66: 695–716, DOI: https://doi.org/10.1016/j.jml.2012.04.001 

  123. Madan, C. R., Chen, Y. Y. and Singhal, A. (2016). ERPs differentially reflect automatic and deliberate processing of the functional manipulability of objects. Frontiers in Human Neuroscience 10DOI: https://doi.org/10.3389/fnhum.2016.00360 

  124. Madan, C. R., Fujiwara, E., Caplan, J. B. and Sommer, T. (2017a). Emotional arousal impairs association-memory: Roles of amygdala and hippocampus. NeuroImage 156: 14–28, DOI: https://doi.org/10.1016/j.neuroimage.2017.04.065 

  125. Madan, C. R., Fujiwara, E., Gerson, B. C. and Caplan, J. B. (2012b). High reward makes items easier to remember, but harder to bind to a new temporal context. Frontiers in Integrative Neuroscience 6DOI: https://doi.org/10.3389/fnint.2012.00061 

  126. Madan, C. R., Ludvig, E. A. and Spetch, M. L. (2014). Remembering the best and worst of times: Memories for extreme outcomes bias risky decisions. Psychonomic Bulletin & Review 21: 629–636, DOI: https://doi.org/10.3758/s13423-013-0542-9 

  127. Madan, C. R., Ludvig, E. A. and Spetch, M. L. (2017b). The role of memory in distinguishing risky decisions from experience and description. Quarterly Journal of Experimental Psychology 70: 2048–2059, DOI: https://doi.org/10.1080/17470218.2016.1220608 

  128. Madan, C. R., Shafer, A. T., Chan, M. and Singhal, A. (2017c). Shock and awe: Distinct effects of taboo words on lexical decision and free recall. Quarterly Journal of Experimental Psychology 70: 793–810, DOI: https://doi.org/10.1080/17470218.2016.1167925 

  129. Madan, C. R. and Singhal, A. (2012a). Encoding the world around us: Motor-related processing influences verbal memory. Consciousness and Cognition 21: 1563–1570, DOI: https://doi.org/10.1016/j.concog.2012.07.006 

  130. Madan, C. R. and Singhal, A. (2012b). Motor imagery and higher-level cognition: four hurdles before research can sprint forward. Cognitive Processing 13: 211–229, DOI: https://doi.org/10.1007/s10339-012-0438-z 

  131. Madan, C. R. and Singhal, A. (2012c). Using actions to enhance memory: effects of enactment, gestures, and exercise on human memory. Frontiers in Psychology 3DOI: https://doi.org/10.3389/fpsyg.2012.00507 

  132. Madan, C. R. and Spetch, M. L. (2012). Is the enhancement of memory due to reward driven by value or salience?. Acta Psychologica 139: 343–349, DOI: https://doi.org/10.1016/j.actpsy.2011.12.010 

  133. Manohar, S. G., Finzi, R. D., Drew, D. and Husain, M. (2017). Distinct motivational effects of contingent and noncontingent rewards. Psychological Science 28: 1016–1026, DOI: https://doi.org/10.1177/0956797617693326 

  134. Marino, B. F. M., Sirianni, M., Volta, R. D., Magliocco, F., Silipo, F., Quattrone, A. and Buccino, G. (2014). Viewing photos and reading nouns of natural graspable objects similarly modulate motor responses. Frontiers in Human Neuroscience, : 8.DOI: https://doi.org/10.3389/fnhum.2014.00968 

  135. Mason, A., Farrell, S., Howard-Jones, P. and Ludwig, C. J. (2017). The role of reward and reward uncertainty in episodic memory. Journal of Memory and Language 96: 62–77, DOI: https://doi.org/10.1016/j.jml.2017.05.003 

  136. Masuda, T. and Nisbett, R. E. (2001). Attending holistically versus analytically: Comparing the context sensitivity of Japanese and americans. Journal of Personality and Social Psychology 81: 922–934, DOI: https://doi.org/10.1037/0022-3514.81.5.922 

  137. Mata, R., Josef, A. K., Samanez-Larkin, G. R. and Hertwig, R. (2011). Age differences in risky choice: a meta-analysis. Annals of the New York Academy of Sciences 1235: 18–29, DOI: https://doi.org/10.1111/j.1749-6632.2011.06200.x 

  138. Mather, M. and Knight, M. (2008). The emotional harbinger effect: Poor context memory for cues that previously predicted something arousing. Emotion 8: 850–860, DOI: https://doi.org/10.1037/a0014087 

  139. Mather, M. and Schoeke, A. (2011). Positive outcomes enhance incidental learning for both younger and older adults. Frontiers in Neuroscience 5DOI: https://doi.org/10.3389/fnins.2011.00129 

  140. Mather, M. and Sutherland, M. R. (2011). Arousal-biased competition in perception and memory. Perspectives on Psychological Science 6: 114–133, DOI: https://doi.org/10.1177/1745691611400234 

  141. Mattek, A. M., Wolford, G. L. and Whalen, P. J. (2017). A mathematical model captures the structure of subjective affect. Perspectives on Psychological Science 12: 508–526, DOI: https://doi.org/10.1177/1745691616685863 

  142. Middlebrooks, C. D., McGillivray, S., Murayama, K. and Castel, A. D. (2016). Memory for allergies and health foods: How younger and older adults strategically remember critical health information. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 71: 389–399, DOI: https://doi.org/10.1093/geronb/gbv032 

  143. Mikels, J. A. and Reed, A. E. (2009). Monetary losses do not loom large in later life: Age differences in the framing effect. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 64B: 457–460, DOI: https://doi.org/10.1093/geronb/gbp043 

  144. Mikels, J. A., Shuster, M. M., Thai, S. T., Smith-Ray, R., Waugh, C. E., Roth, K., Keilly, A. and Stine-Morrow, E. A. L. (2016). Messages that matter: Age differences in affective responses to framed health messages. Psychology and Aging 31: 409–414, DOI: https://doi.org/10.1037/pag0000040 

  145. Millar, P. R., Serbun, S. J., Vadalia, A. and Gutchess, A. H. (2013). Cross-cultural differences in memory specificity. Culture and Brain 1: 138–157, DOI: https://doi.org/10.1007/s40167-013-0011-3 

  146. Montefinese, M., Ambrosini, E., Fairfield, B. and Mammarella, N. (2013). The ‘subjective’ pupil old/new effect: Is the truth plain to see?. International Journal of Psychophysiology 89: 48–56, DOI: https://doi.org/10.1016/j.ijpsycho.2013.05.001 

  147. Moray, N. (1959). Attention in dichotic listening: Affective cues and the influence of instructions. Quarterly Journal of Experimental Psychology 11: 56–60, DOI: https://doi.org/10.1080/17470215908416289 

  148. Most, S. B., Smith, S. D., Cooter, A. B., Levy, B. N. and Zald, D. H. (2007). The naked truth: Positive, arousing distractors impair rapid target perception. Cognition & Emotion 21: 964–981, DOI: https://doi.org/10.1080/02699930600959340 

  149. Murayama, K. and Kitagami, S. (2014). Consolidation power of extrinsic rewards: Reward cues enhance long-term memory for irrelevant past events. Journal of Experimental Psychology: General 143: 15–20, DOI: https://doi.org/10.1037/a0031992 

  150. Murty, V. P. and Dickerson, K. C. (2017). Motivational influences on memory In: Advances in Motivation and Achievement. Emerald Group Publishing Limited, pp. 203–227.  

  151. Murty, V. P., LaBar, K. S. and Adcock, R. A. (2012). Threat of punishment motivates memory encoding via amygdala, not midbrain, interactions with the medial temporal lobe. Journal of Neuroscience 32: 8969–8976, DOI: https://doi.org/10.1523/JNEUROSCI.0094-12.2012 

  152. Murty, V. P., LaBar, K. S., Hamilton, D. A. and Adcock, R. A. (2011). Is all motivation good for learning? dissociable influences of approach and avoidance motivation in declarative memory. Learning & Memory 18: 712–717, DOI: https://doi.org/10.1101/lm.023549.111 

  153. Nairne, J. S. and Pandeirada, J. N. S. (2008). Adaptive memory: Is survival processing special?. Journal of Memory and Language 59: 377–385, DOI: https://doi.org/10.1016/j.jml.2008.06.001 

  154. Nairne, J. S., Pandeirada, J. N. S. and Thompson, S. R. (2008). Adaptive memory: The comparative value of survival processing. Psychological Science 19: 176–180, DOI: https://doi.org/10.1111/j.1467-9280.2008.02064.x 

  155. Nairne, J. S., Thompson, S. R. and Pandeirada, J. N. S. (2007). Adaptive memory: Survival processing enhances retention. Journal of Experimental Psychology: Learning, Memory, and Cognition 33: 263–273, DOI: https://doi.org/10.1037/0278-7393.33.2.263 

  156. Northoff, G. and Hayes, D. J. (2011). Is our self nothing but reward?. Biological Psychiatry 69: 1019–1025, DOI: https://doi.org/10.1016/j.biopsych.2010.12.014 

  157. Northoff, G., Heinzel, A., de Greck, M., Bermpohl, F., Dobrowolny, H. and Panksepp, J. (2006). Self-referential processing in our brain: A meta-analysis of imaging studies on the self. NeuroImage 31: 440–457, DOI: https://doi.org/10.1016/j.neuroimage.2005.12.002 

  158. Oakes, M. A. and Onyper, S. V. (2017). The movement-induced self-reference effect: enhancing memorability through movement toward the self. Cognitive Processing, DOI: https://doi.org/10.1007/s10339-017-0810-0 

  159. Otto, A. R., Fleming, S. M. and Glimcher, P. W. (2016). Unexpected but incidental positive outcomes predict real-world gambling. Psychological Science 27: 299–311, DOI: https://doi.org/10.1177/0956797615618366 

  160. Pachur, T., Mata, R. and Hertwig, R. (2017). Who dares, who errs? disentangling cognitive and motivational roots of age differences in decisions under risk. Psychological Science 28: 504–518, DOI: https://doi.org/10.1177/0956797616687729 

  161. Padulo, C., Carlucci, L., Manippa, V., Marzoli, D., Saggino, A., Tommasi, L., Puglisi-Allegra, S. and Brancucci, A. (2017). Valence, familiarity and arousal of different foods in relation to age, sex and weight. Food Quality and Preference 57: 104–113, DOI: https://doi.org/10.1016/j.foodqual.2016.12.010 

  162. Panksepp, J., Lane, R. D., Solms, M. and Smith, R. (2017). Reconciling cognitive and affective neuroscience perspectives on the brain basis of emotional experience. Neuroscience & Biobehavioral Reviews 76: 187–215, DOI: https://doi.org/10.1016/j.neubiorev.2016.09.010 

  163. Pessiglione, M., Schmidt, L., Draganski, B., Kalisch, R., Lau, H., Dolan, R. J. and Frith, C. D. (2007). How the brain translates money into force: A neuroimaging study of subliminal motivation. Science 316: 904–906, DOI: https://doi.org/10.1126/science.1140459 

  164. Pessoa, L. (2009). How do emotion and motivation direct executive control?. Trends in Cognitive Sciences 13: 160–166, DOI: https://doi.org/10.1016/j.tics.2009.01.006 

  165. Phelps, E. A. and LeDoux, J. E. (2005). Contributions of the amygdala to emotion processing: From animal models to human behavior. Neuron 48: 175–187, DOI: https://doi.org/10.1016/j.neuron.2005.09.025 

  166. Pickel, K. L. (1998). Unusualness and threat as possible causes of “weapon focus”. Memory 6: 277–295, DOI: https://doi.org/10.1080/741942361 

  167. Polanía, R., Moisa, M., Opitz, A., Grueschow, M. and Ruff, C. C. (2015). The precision of value-based choices depends causally on fronto-parietal phase coupling. Nature Communications 6: 8090.DOI: https://doi.org/10.1038/ncomms9090 

  168. Pulvermüller, F. (2005). Opinion: Brain mechanisms linking language and action. Nature Reviews Neuroscience 6: 576–582, DOI: https://doi.org/10.1038/nrn1706 

  169. Qiao-Tasserit, E., Garcia Quesada, M., Antico, L., Bavelier, D., Vuilleumier, P. and Pichon, S. (2017). Transient emotional events and individual affective traits affect emotion recognition in a perceptual decision-making task. PLOS ONE 12: e0171375.DOI: https://doi.org/10.1371/journal.pone.0171375 

  170. Radel, R. and Clément-Guillotin, C. (2012). Evidence of motivational influences in early visual perception. Psychological Science 23: 232–234, DOI: https://doi.org/10.1177/0956797611427920 

  171. Raymond, J. E. and O’Brien, J. L. (2009). Selective visual attention and motivation. Psychological Science 20: 981–988, DOI: https://doi.org/10.1111/j.1467-9280.2009.02391.x 

  172. Read, D. and Loewenstein, G. (1999). Enduring pain for money: decisions based on the perception and memory of pain. Journal of Behavioral Decision Making 12: 1–17, DOI: https://doi.org/10.1002/(sici)1099-0771(199903)12:1¡1::aid-bdm310¿3.0.co;2-v 

  173. Redondo, R. L., Kim, J., Arons, A. L., Ramirez, S., Liu, X. and Tonegawa, S. (2014). Bidirectional switch of the valence associated with a hippocampal contextual memory engram. Nature 513: 426–430, DOI: https://doi.org/10.1038/nature13725 

  174. Rogers, T. B., Kuiper, N. A. and Kirker, W. S. (1977). Self-reference and the encoding of personal information. Journal of Personality and Social Psychology 35: 677–688, DOI: https://doi.org/10.1037/0022-3514.35.9.677 

  175. Roper, Z. J. J. and Vecera, S. P. (2016). Funny money: the attentional role of monetary feedback detached from expected value. Attention, Perception, & Psychophysics 78: 2199–2212, DOI: https://doi.org/10.3758/s13414-016-1147-y 

  176. Rosati, A. G. and Hare, B. (2016). Reward currency modulates human risk preferences. Evolution and Human Behavior 37: 159–168, DOI: https://doi.org/10.1016/j.evolhumbehav.2015.10.003 

  177. Samanez Larkin, G. R., Gibbs, S. E. B., Khanna, K., Nielsen, L., Carstensen, L. L. and Knutson, B. (2007). Anticipation of monetary gain but not loss in healthy older adults. Nature Neuroscience 10: 787–791, DOI: https://doi.org/10.1038/nn1894 

  178. Schmidt, L. J., Belopolsky, A. V. and Theeuwes, J. (2015). Attentional capture by signals of threat. Cognition and Emotion 29: 687–694, DOI: https://doi.org/10.1080/02699931.2014.924484 

  179. Schultz, W. (2015). Neuronal reward and decision signals: From theories to data. Physiological Reviews 95: 853–951, DOI: https://doi.org/10.1152/physrev.00023.2014 

  180. Sescousse, G., Barbalat, G., Domenech, P. and Dreher, J.-C. (2013a). Imbalance in the sensitivity to different types of rewards in pathological gambling. Brain 136: 2527–2538, DOI: https://doi.org/10.1093/brain/awt126 

  181. Sescousse, G., Caldú, X., Segura, B. and Dreher, J.-C. (2013b). Processing of primary and secondary rewards: A quantitative meta-analysis and review of human functional neuroimaging studies. Neuroscience & Biobehavioral Reviews 37: 681–696, DOI: https://doi.org/10.1016/j.neubiorev.2013.02.002 

  182. Sescousse, G., Redoute, J. and Dreher, J.-C. (2010). The architecture of reward value coding in the human orbitofrontal cortex. Journal of Neuroscience 30: 13095–13104, DOI: https://doi.org/10.1523/JNEUROSCI.3501-10.2010 

  183. Shafer, A. T., Matveychuk, D., Penney, T., O’Hare, A. J., Stokes, J. and Dolcos, F. (2012). Processing of emotional distraction is both automatic and modulated by attention: Evidence from an event-related fMRI investigation. Journal of Cognitive Neuroscience 24: 1233–1252, DOI: https://doi.org/10.1162/jocna00206 

  184. Shebani, Z. and Pulvermüller, F. (2013). Moving the hands and feet specifically impairs working memory for arm- and leg-related action words. Cortex 49: 222–231, DOI: https://doi.org/10.1016/j.cortex.2011.10.005 

  185. Shigemune, Y., Abe, N., Suzuki, M., Ueno, A., Mori, E., Tashiro, M., Itoh, M. and Fujii, T. (2010). Effects of emotion and reward motivation on neural correlates of episodic memory encoding: A PET study. Neuroscience Research 67: 72–79, DOI: https://doi.org/10.1016/j.neures.2010.01.003 

  186. Shohamy, D. and Adcock, R. A. (2010). Dopamine and adaptive memory. Trends in Cognitive Sciences 14: 464–472, DOI: https://doi.org/10.1016/j.tics.2010.08.002 

  187. Skiba, R. M. and Snow, J. C. (2016). Attentional capture for tool images is driven by the head end of the tool, not the handle. Attention, Perception, & Psychophysics 78: 2500–2514, DOI: https://doi.org/10.3758/s13414-016-1179-3 

  188. Skrynka, J. and Vincent, B. (2017). Subjective hunger, not blood glucose, influences domain general time preference. PsyArXiv, : qgp54.DOI: https://doi.org/10.17605/OSF.IO/QGP54 

  189. Snow, J. C., Pettypiece, C. E., McAdam, T. D., McLean, A. D., Stroman, P. W., Goodale, M. A. and Culham, J. C. (2011). Bringing the real world into the fMRI scanner: Repetition effects for pictures versus real objects. Scientific Reports 1DOI: https://doi.org/10.1038/srep00130 

  190. Snow, J. C., Skiba, R. M., Coleman, T. L. and Berryhill, M. E. (2014). Real-world objects are more memorable than photographs of objects. Frontiers in Human Neuroscience 8: 837.DOI: https://doi.org/10.3389/fnhum.2014.00837 

  191. Soderstrom, N. C. and McCabe, D. P. (2011). Are survival processing memory advantages based on ancestral priorities?. Psychonomic Bulletin & Review 18: 564–569, DOI: https://doi.org/10.3758/s13423-011-0060-6 

  192. Spaniol, J., Schain, C. and Bowen, H. J. (2013). Reward-enhanced memory in younger and older adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences 69: 730–740, DOI: https://doi.org/10.1093/geronb/gbt044 

  193. Squires, S. D., Macdonald, S. N., Culham, J. C. and Snow, J. C. (2016). Priming tool actions: Are real objects more effective primes than pictures?. Experimental Brain Research 234: 963–976, DOI: https://doi.org/10.1007/s00221-015-4518-z 

  194. Steblay, N. M. (1992). A meta-analytic review of the weapon focus effect. Law and Human Behavior 16: 413–424, DOI: https://doi.org/10.1007/BF02352267 

  195. Strange, B. A., Hurlemann, R. and Dolan, R. J. (2003). An emotion-induced retrograde amnesia in humans is amygdala- and β- adrenergic-dependent. Proceedings of the National Academy of Sciences 100: 13626–13631, DOI: https://doi.org/10.1073/pnas.1635116100 

  196. Symons, C. S. and Johnson, B. T. (1997). The self-reference effect in memory: A meta-analysis. Psychological Bulletin 121: 371–394, DOI: https://doi.org/10.1037/0033-2909.121.3.371 

  197. Tacikowski, P. and Nowicka, A. (2010). Allocation of attention to self-name and self-face: An ERP study. Biological Psychology 84: 318–324, DOI: https://doi.org/10.1016/j.biopsycho.2010.03.009 

  198. Talmi, D. (2013). Enhanced emotional memory. Current Directions in Psychological Science 22: 430–436, DOI: https://doi.org/10.1177/0963721413498893 

  199. Talmi, D., Dayan, P., Kiebel, S. J., Frith, C. D. and Dolan, R. J. (2009). How humans integrate the prospects of pain and reward during choice. Journal of Neuroscience 29: 14617–14626, DOI: https://doi.org/10.1523/JNEUROSCI.2026-09.2009 

  200. Talmi, D. and Moscovitch, M. (2004). Can semantic relatedness explain the enhancement of memory for emotional words?. Memory & Cognition 32: 742–751, DOI: https://doi.org/10.3758/BF03195864 

  201. Talmi, D., Ziegler, M., Hawksworth, J., Lalani, S., Herman, C. P. and Moscovitch, M. (2013). Emotional stimuli exert parallel effects on attention and memory. Cognition & Emotion 27: 530–538, DOI: https://doi.org/10.1080/02699931.2012.722527 

  202. Taylor, S. E. (1991). Asymmetrical effects of positive and negative events: The mobilization-minimization hypothesis. Psychological Bulletin 110: 67–85, DOI: https://doi.org/10.1037/0033-2909.110.1.67 

  203. Tiedemann, L. J., Schmid, S. M., Hettel, J., Giesen, K., Francke, P., Büchel, C. and Brassen, S. (2017). Central insulin modulates food valuation via mesolimbic pathways. Nature Communications 8: 16052.DOI: https://doi.org/10.1038/ncomms16052 

  204. Tousignant, C. and Pexman, P. M. (2012). Flexible recruitment of semantic richness: context modulates body-object interaction effects in lexical-semantic processing. Frontiers in Human Neuroscience 6: 53.DOI: https://doi.org/10.3389/fnhum.2012.00053 

  205. Truong, G., Chapman, C. S., Chisholm, J. D., Enns, J. T. and Handy, T. C. (2016). Mine in motion: How physical actions impact the psychological sense of object ownership. Journal of Experimental Psychology: Human Perception and Performance 42: 375–385, DOI: https://doi.org/10.1037/xhp0000142 

  206. Truong, G., Roberts, K. H. and Todd, R. M. (2017). I saw mine first: A prior-entry effect for newly acquired ownership. Journal of Experimental Psychology: Human Perception and Performance 43: 192–205, DOI: https://doi.org/10.1037/xhp0000295 

  207. Tsetsos, K., Chater, N. and Usher, M. (2012). Salience driven value integration explains decision biases and preference reversal. Proceedings of the National Academy of Sciences 109: 9659–9664, DOI: https://doi.org/10.1073/pnas.1119569109 

  208. Tsukiura, T. and Cabeza, R. (2008). Orbitofrontal and hippocampal contributions to memory for face–name associations: The rewarding power of a smile. Neuropsychologia 46: 2310–2319, DOI: https://doi.org/10.1016/j.neuropsychologia.2008.03.013 

  209. Tucker, M. and Ellis, R. (1998). On the relations between seen objects and components of potential actions. Journal of Experimental Psychology: Human Perception and Performance 24: 830–846, DOI: https://doi.org/10.1037/0096-1523.24.3.830 

  210. Vlaev, I., Seymour, B., Chater, N., Winston, J. S., Yoshida, W., Wright, N., Symmonds, M. and Dolan, R. (2014). Prices need no preferences: Social trends determine decisions in experimental markets for pain relief. Health Psychology 33: 66–76, DOI: https://doi.org/10.1037/a0030372 

  211. Vlaev, I., Seymour, B., Dolan, R. J. and Chater, N. (2009). The price of pain and the value of suffering. Psychological Science 20: 309–317, DOI: https://doi.org/10.1111/j.1467-9280.2009.02304.x 

  212. Vrijsen, J. N., van Oostrom, I., Speckens, A., Becker, E. S. and Rinck, M. (2013). Approach and avoidance of emotional faces in happy and sad mood. Cognitive Therapy and Research 37: 1–6, DOI: https://doi.org/10.1007/s10608-012-9436-9 

  213. Vuilleumier, P. and Schwartz, S. (2001). Emotional facial expressions capture attention. Neurology 56: 153–158, DOI: https://doi.org/10.1212/WNL.56.2.153 

  214. Wadlinger, H. A. and Isaacowitz, D. M. (2006). Positive mood broadens visual attention to positive stimuli. Motivation and Emotion 30: 87–99, DOI: https://doi.org/10.1007/s11031-006-9021-1 

  215. Wagner, D. D., Boswell, R. G., Kelley, W. M. and Heatherton, T. F. (2012). Inducing negative affect increases the reward value of appetizing foods in dieters. Journal of Cognitive Neuroscience 24: 1625–1633, DOI: https://doi.org/10.1162/jocna00238 

  216. Wang, L., Yu, H. and Zhou, X. (2013). Interaction between value and perceptual salience in value-driven attentional capture. Journal of Vision 13: 5–5, DOI: https://doi.org/10.1167/13.3.5 

  217. Weiner, B. and Walker, E. L. (1966). Motivational factors in short-term retention. Journal of Experimental Psychology 71: 190–193, DOI: https://doi.org/10.1037/h0022848 

  218. Weinstein, Y., Bugg, J. M. and Roediger, H. L. (2008). Can the survival recall advantage be explained by basic memory processes?. Memory & Cognition 36: 913–919, DOI: https://doi.org/10.3758/MC.36.5.913 

  219. Wentura, D., Rothermund, K. and Bak, P. (2000). Automatic vigilance: The attention-grabbing power of approach- and avoidance-related social information. Journal of Personality and Social Psychology 78: 1024–1037, DOI: https://doi.org/10.1037/0022-3514.78.6.1024 

  220. Williams, L. A. and DeSteno, D. (2008). Pride and perseverance: The motivational role of pride. Journal of Personality and Social Psychology 94: 1007–1017, DOI: https://doi.org/10.1037/0022-3514.94.6.1007 

  221. Wilson, A. D. and Golonka, S. (2013). Embodied cognition is not what you think it is. Frontiers in Psychology 4: 58.DOI: https://doi.org/10.3389/fpsyg.2013.00058 

  222. Wispinski, N. J., Truong, G., Handy, T. C. and Chapman, C. S. (2017). Reaching reveals that best-versus-rest processing contributes to biased decision making. Acta Psychologica 176: 32–38, DOI: https://doi.org/10.1016/j.actpsy.2017.03.006 

  223. Witt, J. K., Kemmerer, D., Linkenauger, S. A. and Culham, J. (2010). A functional role for motor simulation in identifying tools. Psychological Science 21: 1215–1219, DOI: https://doi.org/10.1177/0956797610378307 

  224. Wolpert, D. M., Ghahramani, Z. and Flanagan, J. (2001). Perspectives and problems in motor learning. Trends in Cognitive Sciences 5: 487–494, DOI: https://doi.org/10.1016/S1364-6613(00)01773-3 

  225. Wood, N. and Cowan, N. (1995). The cocktail party phenomenon revisited: How frequent are attention shifts to one’s name in an irrelevant auditory channel?. Journal of Experimental Psychology: Learning, Memory, and Cognition 21: 255–260, DOI: https://doi.org/10.1037/0278-7393.21.1.255 

  226. Woud, M. L., Becker, E. S., Lange, W.-G. and Rinck, M. (2013). Effects of approach-avoidance training on implicit and explicit evaluations of neutral, angry, and smiling face stimuli. Psychological Reports 113: 199–216, DOI: https://doi.org/10.2466/21.07.PR0.113x10z1 

  227. Xie, W. and Zhang, W. (2016). Negative emotion boosts quality of visual working memory representation. Emotion 16: 760–774, DOI: https://doi.org/10.1037/emo0000159 

  228. Xie, W. and Zhang, W. (2017). Negative emotion enhances mnemonic precision and subjective feelings of remembering in visual long-term memory. Cognition 166: 73–83, DOI: https://doi.org/10.1016/j.cognition.2017.05.025 

  229. Yamawaki, R., Nakamura, K., Aso, T., Shigemune, Y., Fukuyama, H. and Tsukiura, T. (). Remembering my friends: Medial prefrontal and hippocampal contributions to the self-reference effect on face memories in a social context. Human Brain Mapping, DOI: https://doi.org/10.1002/hbm.23662 (in press). 

  230. Yee, D. M., Krug, M. K., Allen, A. Z. and Braver, T. S. (2016). Humans integrate monetary and liquid incentives to motivate cognitive task performance. Frontiers in Psychology 6: 2037.DOI: https://doi.org/10.3389/fpsyg.2015.02037 

  231. Yoon, S., Vo, K. and Venkatraman, V. (2017). Variability in decision strategies across description-based and experience-based decision making. Journal of Behavioral Decision Making, DOI: https://doi.org/10.1002/bdm.2009 

  232. Zeigenfuse, M. D., Pleskac, T. J. and Liu, T. (2014). Rapid decisions from experience. Cognition 131: 181–194, DOI: https://doi.org/10.1016/j.cognition.2013.12.012 

  233. Zhou, X. and Gao, D.-G. (2008). Social support and money as pain management mechanisms. Psychological Inquiry 19: 127–144, DOI: https://doi.org/10.1080/10478400802587679 

  234. Zimmerman, C. A. and Kelley, C. M. (2010). ‘I’ll remember this!’ effects of emotionality on memory predictions versus memory performance. Journal of Memory and Language 62: 240–253, DOI: https://doi.org/10.1016/j.jml.2009.11.004 

  235. Zink, C. F., Tong, Y., Chen, Q., Bassett, D. S., Stein, J. L. and Meyer-Lindenberg, A. (2008). Know your place: Neural processing of social hierarchy in humans. Neuron 58: 273–283, DOI: https://doi.org/10.1016/j.neuron.2008.01.025 

Peer Review Comments

The author(s) of this paper chose the Open Review option, and the peer review comments are available at: http://doi.org/10.1525/collabra.111.pr

comments powered by Disqus