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Series Title

Chapter Title Selective Attention as a Mediator Between Food Motivation and Disposition to Act

Chapter SubTitle

Copyright Year 2011

Copyright Holder Springer Science+Business Media, LLC

Family Name LelandParticleGiven Name David S.

Corresponding Author

SuffixDivisionOrganization Pitzer CollegeAddress 1050 N Mills Ave, 91711, Claremont, CA, USAEmail [email protected]

Family Name PinedaParticleGiven Name Jaime A.

Author

SuffixDivision Department of Cognitive Science and Group in NeuroscienceOrganization University of CaliforniaAddress San Diego, 9500 Gilman Drive, 92037-0515, La Jolla, CA, USAEmail [email protected]

Abstract In this chapter, we present a framework for understanding how selective attention can mediate theinfluence of food motivation on food-related action, taking into account current research and perspectivesfrom psychology and neuroscience. Subcortical and cortical mechanisms allow for flexible determinationof food preferences and goals. The recent shift in thinking about mesolimbic dopamine function frompleasure-based explanations to ones based on reward learning, incentive salience, and behavioral effortmakes clearer how mechanisms underlying motivation can produce not only relatively direct action, butalso great flexibility by recruiting selective attention mechanisms, such as the forebrain acetylcholinesystem. Recent work with behavioral tasks, electrophysiology, and functional imaging provide evidencefor attentional biases toward food-related stimuli, modulated in some cases by food deprivation and hungerconditions. Such biases may increase disposition to act via a positive feedback loop in which motivationdirects attention and behavioral approach toward food-related stimuli, increasing exposure to them andthus further heightening motivational salience, and ultimately producing eating behavior. This mayoccur both via subcortical circuits and via modulation of cortical regions comprising the mirror neuronsystem which, by representing both self-executed action and action observed in others, may increase thepropensity to eat when in the presence of others doing the same. Focusing on the relationship betweenmotivation, attention, and action systems provides a goal-directed cognitive perspective on eating, withabnormalities in these interactions serving as potential risk factors for eating disorders.

V.R. Preedy et al. (eds.), Handbook of Behavior, Food and Nutrition, DOI 10.1007/978-0-387-92271-3_43, © Springer Science+Business Media, LLC 2011

Abbreviations

ERP Event-related potentialfMRI Functional magnetic resonance imagingIFG Inferior frontal gyrusIPL Inferior parietal lobuleLC Locus coeruleusMNS Mirror neuron systemNA Nucleus accumbensOFC Orbitofrontal cortexPF Parietal frontalPFC Prefrontal cortexPMv Premotor ventralPPC Posterior parietal cortexPWS Prader-Willi syndromeRT Reaction timeSMA Supplementary motor areaSTS Superior temporal sulcusVTA Ventral tegmental area

43.1 Introduction

Food is a primary motivator of behavior. It is a fundamental physiological requirement for all ani-mals and, in humans and other social species, central to a host of social interactions, such as hunting, foraging, shared meals, and trade, which can yield other tangible and social rewards. In order to suc-cessfully acquire food, one must make effective use of relevant cues, for example colors indicating ripe fruit. This is complicated, however, by the fact that the physical and social environments offer a near-limitless supply of information, only some of which is useful to the pursuit of food. This over-abundance of information, coupled with limitations on time and neural resources, provided evolu-tionary pressure for brain mechanisms enabling selective attention toward motivationally salient

Chapter 43Selective Attention as a Mediator Between Food Motivation and Disposition to Act

David S. Leland and Jaime A. Pineda [AU1]

D.S. Leland (*) Pitzer College, 1050 N Mills Ave, Claremont, CA 91711, USA e-mail: [email protected]

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information. That is, there is a bias toward enhanced processing of goal-related information at the expense of other information. Attentional biases toward food-related stimuli afford them preferential access to perceptual and cognitive resources, prioritizing learning and decision-making related to food and facilitating action to acquire and consume food. This chapter explores the psychological and neural underpinnings of selective attention toward food-related stimuli in the context of its mediation between motivation and action (Fig. 43.1), providing a framework for understanding the multidimensional factors that contribute to normal and disordered eating.

43.2 Motivation

43.2.1 Subcortical Mechanisms

Motivation is the goal-oriented force in behavior, contributing to its initiation, direction, intensity, and persistence in the face of obstacles. Motivation to seek and consume food arises in part from internal cues generated by homeostatic processes that monitor and regulate nutritional status and immediate energy needs. A significant amount of motivation-related neural circuitry lies below the cerebral cortex. The hypothalamus, in particular, is an important region for regulating neural and endocrine systems. Discrete nuclei of the hypothalamus play significant roles in the control of homeostatic signals relating to eating, drinking, and temperature regulation (Garcia-Segura et al. 2008). Electrical stimulation of these areas leads to an enhancement or inhibition of the correspond-ing behavior, while lesions produce the opposite results. The hypothalamus and related structures regulate homeostatic processes using chemical signals in the form of neurotransmitters, neuromodu-lators, and neurohormones.

External cues are another major influence on food motivation, and they, too, exert their influence through chemical signaling (see Table 43.1). The mesolimbic dopamine pathway is a key neurotrans-mitter circuit for motivation that responds to food and food-related cues. It originates in the ventral tegmental area (VTA) of the midbrain and projects to the nucleus accumbens (NA) of the striatum and other forebrain limbic targets. This neural system is important not only for food motivation but

Fig. 43.1 Attention as mediator between motivation and action. Brain regions that attribute motivational salience to incentive stimuli can trigger action through relatively direct connections but also via their influence on attentional net-works, allowing more flexibility and control over behavior. Movement and attention toward these appetitive stimuli also can have reciprocal effects, increasing motivational salience by facilitating the sensory and evaluative processes that identify and empower them as incentives. LC locus coeruleus, MNS mirror neuron system, NA nucleus accumbens, OFC orbitofrontal cortex, PFC prefrontal cortex, PPC posterior parietal cortex, VTA ventral tegmental area

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43 Selective Attention as a Mediator Between Food Motivation and Disposition to Act

for other conditioned and unconditioned reinforcers, including sex, addictive drugs, and money. As a natural (unconditioned) reinforcer, food generally increases the probability of behaviors that lead to its acquisition and consumption. Through associative learning, stimuli associated with food can become conditioned reinforcers in their own right.

Positive reinforcers are commonly referred to as “rewards,” and because rewards of various kinds cause a release of dopamine in the NA, many researchers once concluded that dopamine serves as a common denominator for pleasure in the brain. This hedonic theory of mesolimbic dopamine has been challenged over the past several years and is being replaced by a set of theories focusing on cognition and disposition to act rather than subjective feelings, as a way to more spe-cifically account for how dopamine activity contributes to goal-directed behavior (Schultz 2006; Salamone et al. 2007; Berridge 2009). The evidence for this new perspective comes in large part from studies of food motivation. For instance, when mesolimbic dopamine function is compro-mised by lesions or dopamine blockers, animals still prefer and will seek larger food rewards if they do not require substantially more effort to obtain than smaller ones (Salamone et al. 2007), and will still produce hedonic facial expressions when force-fed sweet solutions, even when they will not work to obtain them (Berridge 2009). Berridge has argued that there are distinct but func-tionally integrated circuits mediating food “liking” (hedonia) and “wanting” (incentive salience), with mesolimbic dopamine more closely (but not exclusively) tied to the latter. Furthermore, VTA dopamine neurons have been observed to shift their response from presentation of actual food rewards to presentation of the cues that predict them over the course of instrumental learning (Schultz 2006). Computational modeling and empirical findings suggest that VTA neurons signal a violation of reward expectancy and are important in learning to predict rewards on the basis of associated cues.

43.2.2 Cortical Mechanisms

Such cues, both environmental and social, along with affective states, also contribute to appetitive behavior. While subcortical circuits account for basic aspects of food motivation and are relatively well-conserved across species, mammals in general and primates especially have cortical mecha-nisms that allow for more complex motivations. Examples of this include flexible and relative prefer-ences between food alternatives, inhibition of appetitive urges, and social facilitation of eating. These more recently evolved mechanisms have not replaced the subcortical ones, but are anatomically and functionally integrated with them, such that subcortical circuits serve as a foundation while cortical elements allow for an expanded repertoire of motivations, behaviors, and subjective experiences.

Table 43.1 Major neurotransmitters and their roles in food-related behavior

Neurotransmitter Roles in food-related behavior

Glutamate Food-cue association learningGABA Disinhibition of circuits for food-directed attention and actionAcetylcholine Attention to food stimuli; control of muscles for eatingDopamine Food-related reinforcement, cognition, and movementNorepinephrine Food-related arousal and attentionSerotonin Appetite and food-related mood effects

Listed in this table are six of the central nervous system’s major neurotransmitters. Each has a wide variety of functions, some of which pertain to appetite, food acquisition, and eating as indicated

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Wang et al. (2004) showed that at least two cortical regions in particular, the insula and orbitofrontal cortex (OFC), appear to play such a role and are critically involved in processing food-related stimuli and influencing the appetitive behavior of humans.

The insula represents certain sensory qualities of food such as taste and texture (exteroceptive cues; Rolls 2006). It is especially important, however, for the sensation of internal physiological states such as hunger (interoceptive cues) and appears to play a role in conscious awareness of these states (Craig 2003). The insula receives inputs from areas that include the amygdala, somatosensory cortex, and various thalamic nuclei. The OFC receives projections from the insula as well as the amygdala, eating-related subcortical nuclei (e.g., lateral hypothalamus), and multimodal sensory regions (Rolls 2006). Functional neuroimaging in humans shows that visual stimuli associated with the taste of glucose and pictures of foods, as compared to pictures of locations, activate the OFC and some interconnected areas (Simmons et al. 2005). OFC activity is not directly related to the primary stimulus properties of food but instead shows highly flexible responses reflecting context-specific motivational and affective value. For instance, monkey OFC neurons that initially respond to multi-ple foods will reduce their response to those that have been consumed to satiation but not to others, suggesting a neural basis for food-specific satiety (Rolls 2006). The OFC also contains a number of neurons that respond to reward-predicting stimuli in a manner similar to that of dopamine neurons in the VTA (Schultz 2006).

The insula and OFC can be thought of as limbic-related cortices, given their functional roles and dense interconnections with limbic structures such as the amygdala, which influences behavior by linking sensory properties of a stimulus with its incentive value. All of these regions carry out their reward functions in conjunction with the dopamine system, including its sources (VTA and substan-tia nigra) and target structures (e.g., striatum, anterior cingulate cortex). Together, this circuitry allows for the evaluation of context-specific relative reward value and for the learning and prediction of reward contingencies.

The effect of motivation on disposition to act is mediated in part by subcortical efferent connec-tions from the NA to the ventral pallidum and hypothalamus, which in turn can trigger overt eating behavior. Likewise, the OFC is important for preparation of more complex motor action via its con-nections to regions such as premotor cortex, which is involved in the simulation of action (Cavada et al. 2000). Motivated behaviors are, however, distinct from reflexive ones in that they do not involve fixed, obligatory motor patterns. Rather, goal-directed behavior is adaptive to changing internal and external conditions, and as such requires cognitive processes to provide flexibility of approach. Selective attention is one of the key components of the cognitive apparatus that provides such flexi-bility and that is recruited in the pursuit of food and other goals.

43.3 Selective Attention

43.3.1 Theories of Selective Attention

Selective attention (see Table 43.2) is one of the most studied topics in cognitive neuroscience. One traditional view of attention is as a unitary, supramodal mechanism subserved by anatomical circuits distinct from those involved in information processing (Posner and Petersen 1990). Posner and col-leagues (Posner and Dehaene 1994; Posner and Rothbart 2007) have proposed a modern version of this idea by suggesting a triarchic model consisting of orienting, alerting, and executive attention subsystems. The orienting or posterior system appears to subserve spatial attention with or without

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movement of the eyes toward attended stimuli, and is associated primarily with areas in the superior parietal cortex, temporal–parietal junction, frontal eye fields, and superior colliculi. The alerting system involves the noradrenergic-locus coeruleus (LC) system and the right frontal as well as parietal cortices. Finally, the executive or anterior attentional system appears to be involved in attentional recruitment and control of brain areas in order to perform complex cognitive tasks. This anterior system primarily involves the anterior cingulate, lateral ventral prefrontal cortex (PFC), and basal ganglia. Although consistent with a great deal of observations, the existence of such unique and anatomically circumscribed neural systems devoted specifically to attention has been criticized (Corbetta and Shulman 2002). One alternative that is potentially more consistent with the disposition to act as presented in this chapter is the premotor theory of attention. In this perspective, attention derives from activation of the same circuits that process sensory and motor information. For exam-ple, selective attention for spatial locations would result from the activity of circuits involved in the computations necessary for eye movement, arm reaching movements, walking, and other motor activities (Eimer et al. 2005), while selective attention for object recognition would derive from activity in cortical areas responsible for object property processing (Duncan and Nimmo-Smith 1996). According to this view of attention, the difference between selective spatial attention and overt actions directed toward a target in space is that in both cases a motor plan is prepared but only in the latter case is that plan executed.

Evidence in favor of the premotor theory of attention derives primarily from findings that some parietal and frontal cortical areas appear to incorporate and share systems for spatial representation, action control, and attention (Graziano and Gross 1998). Damage to these areas can produce inatten-tion (neglect) to particular regions of space and deficits in movement directed toward those regions of space, as well as motor deficits for effectors (e.g., the hand) represented in the damaged areas. The cortical areas that program spatially specific movements are influenced by other cortical areas (e.g., presupplementary motor area or pre-SMA) and by subcortical centers (e.g., basal ganglia). These centers are thought to exert inhibitory control that, when released, allows movement to occur. Without such a release, the portion of the spatial map activated by the intended movement nonetheless gains a selective attention advantage over other locations for information-processing resources (Rizzolatti et al. 1987).

Table 43.2 Key features of selective attention

1. Selective attention in a process by which certain information receives increased cognitive processing at the expense of other information

2. Attention helps guide the sensory organs (orienting), increase the perceived intensity of stimuli (alerting), organize and control the flow of information (executive attention), and prepare the body for action (premotor attention)

3. The triarchic model of attention focuses on brain structures thought to produce attention-specific effects that are separate from other information processing

4. The premotor theory suggests that attention is the result of brain activity for sensory and motor processing that is under inhibition to prevent action until that inhibition is released

5. Attention can be directed to regions of space (spatial attention) even without movement of the sensory organs, making it possible to isolate and study attention effects (e.g., by having subjects keep their eyes fixated at one location while they pay attention for events at others)

6. Tools such as functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) can be used to detect the neural processes underlying attention

7. Behavioral studies, brain imaging, and neuroanatomy indicate that selective attention is controlled in part by motivational processes, consistent with its role in facilitating goal-directed behavior

This table lists key facts about selective attention, including some of its theories, purposes, and means of investigation

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43.3.2 Attention to Motivational Targets

Selective attention toward motivationally salient stimuli may result as a natural consequence of the mesolimbic dopamine activity associated with them. “Wanted” stimuli are those that acquire incen-tive salience, becoming “attractive” and “attention-grabbing” (Berridge 2009, p. 538), which helps them compete with other stimuli for cognitive processing and the triggering of action. VTA neurons increase their baseline firing in response to the earliest unexpected reward or cue predictive of reward (Schultz 2006), suggesting that these cues may garner selective attention as the animal learns reward associations and prepares for action. One way this may occur is through disinhibition of basal forebrain cholinergic neurons, which potentiate sensory cortex activity and may underlie attention shifts and motor preparation in the PFC (Parikh et al. 2007) and posterior parietal cortex (PPC; Reep and Corwin 2009). These cholinergic neurons are under inhibitory control by GABAergic neurons in the NA, which in turn are inhibited by dopaminergic VTA neurons. Thus, disinhibition of basal forebrain cholinergic activity by mesolimbic dopamine may constitute a neu-ral substrate for the preferential allocation of attentional resources toward motivationally salient stimuli such as food cues.

43.3.3 Attention to Food Stimuli

Selective attention toward food-related stimuli has been demonstrated behaviorally in humans, primarily using modified Stroop and spatial attention paradigms (see “Features of Selective Attention Tasks”). A Stroop bias toward food-related words has been demonstrated in subjects with normal eating patterns following food deprivation (Channon and Hayward 1990; Formea and Burns 1996; Francis et al. 1997; Braet and Crombez 2003) and in some cases even without (Lavy and Vandenhout 1993; Overduin et al. 1995). A spatial attentional bias toward the location of food stimuli has been shown as well in normal subjects who are especially hungry (Mogg et al. 1998) or have fasted (Placanica et al. 2002), and again in some cases whether or not subjects fasted (Leland and Pineda 2006). Most food attentional bias studies have focused on groups with eating disorders and dietary restraint. Dobson and Dozois (2004) conducted a meta-analysis of modified Stroop studies and concluded that bulimics but not anorexics or dieters exhibit a greater food word Stroop effect than controls (although both bulimics and anorexics did demonstrate a larger Stroop effect for words related to weight and body image). One spatial attention task has demonstrated bias toward food images that is greater in those with eating disorders (Shafran et al. 2007), while another found, in a nonclinical sample, greater bias among those who report that external cues (e.g., food stimuli) have a particularly large influence on their motivation to eat (Brignell et al. 2009).

Mohanty et al. (2008) used functional magnetic resonance imaging (fMRI) in their study of food-related attentional bias. In hungry but not satiated subjects, cues predicting the location of food image targets activated the amygdala, posterior cingulate, LC, and substantia nigra more than did cues predicting the location of nonfood (tool image) targets. PPC and OFC activations, meanwhile, were correlated with speed of attentional shifts. This study grouped food image trials and tool image trials into separate blocks, which can produce carry-over effects from trial to trial within each block. Thus, the food block effects could be due to general arousal as opposed to selective spatial attention, but the results are consistent with expected spatial attention effects, particularly in the PPC, given its association with visuospatial processing.

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The finding of increased activation in the LC is of particular interest as that area, the primary source of norepinephrine signals in the central nervous system, projects to limbic and cortical struc-tures and appears to mediate attention effects indexed by the P3 component of the electrophysiological event-related potential (ERP; Foote et al. 1991). Various factors influence the amplitude and latency of the P3, including attentional focus. Kok (2001) has suggested that the P3 reflects allocation of attentional resources in the categorization of important events. In our study of food words as cues in a spatial attention task (Leland and Pineda 2006), we found a P3-type component with greater amplitude evoked by food words than neutral words (Fig. 43.2). This appeared to be an effect of selective attention and not general arousal since food- and neutral-word trials were randomly mixed within each block. Attention-related ERP effects also have been found in response to food odor stimuli in normal eaters although not restrained eaters, which may reflect a motivation to suppress attention to food-related stimuli (Kemmotsu and Murphy 2006). Furthermore, attention-related ERPs to images of food varying in degree of suitability for human consumption (e.g., sanitary ver-sus contaminated) appear to differentiate controls from individuals with Prader-Willi syndrome (PWS; Key and Dykens 2008). The ERPs of PWS patients, who are characterized by intellectual deficits and hyperphagia (abnormally increased appetite for and consumption of food), may reflect the impact of maladaptive food cue salience on selective attention. Attending excessively to food quantity and/or not enough to food quality/safety may be an important contributor to this and other eating disorders.

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Fig. 43.2 Event-related Potentials (ERPs) to food and neutral cue words Words serving as spatial cues in a selective attention paradigm (see “Features of Selective Attention Tasks”) evoked brain electrical activity that differed based on semantic category. A positivity peaking approximately 420 ms after stimulus onset (shown with gray background) had greater amplitude in response to food words (e.g., “PIZZA”) than a control set of school/art supply words (e.g., “PAINT”). This P3-like positivity may reflect enhanced attention as a consequence of motivational salience. Waveforms represent grand averages (n = 20). F3 left frontal, F4 right frontal, C3 left central, C4 right central, P3 left parietal, P4 right parietal (Adapted with permission from Leland and Pineda 2006, p. 77)

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43.4 Action

43.4.1 A Feedback Loop for Eating

The mesolimbic dopamine pathway associated with motivation projects to areas such as the ventral pallidum and hypothalamus, which in turn can activate brainstem circuits for eating. One manner in which selective attention can mediate the guidance, initiation, and intensity of eating behavior is by successively narrowing the range of decisions and behaviors toward food-related stimuli (including food itself). The orienting effects of selective attention can lead to shifts of sensory organs toward attended stimuli, for instance movement of the eyes so as to place cues in the center of the visual field. Attended stimuli have greater sensory salience and detectability, which may in turn facilitate their identification and evaluation as incentives. Siep et al. (2009), for instance, found that focusing attention on food images during fMRI modulated food reward processing activity in the OFC and amygdala. Thus, motivation, attention, and action may work together in a positive feedback loop until physical proximity and motivational salience are sufficient to trigger food consumption. A feedback loop of this sort would be consistent with the reciprocal connectivity of the VTA, which receives excitatory inputs from nearly all of its direct and indirect cortical targets, and it is consistent with contemporary views of mesolimbic dopamine as playing a role in incentive salience (Berridge 2009), reward learning (Schultz 2006), and behavioral activation (Salamone et al. 2007).

43.4.2 Social Eating and the Mirror Neuron System

Higher level cognitive mechanisms may help explain the power of food cues in the social context, in particular the impact of seeing others eat. People tend to eat more at meals shared with others (de Castro and de Castro 1989), which may be due in part to mimicry of others’ behavior. Mirror neurons in the frontal and parietal cortices show increased firing rates during not only execution of action but also during observation of the corresponding action performed by others and may be a substrate for this influence (Rizzolatti and Craighero 2004). The mirror neuron system (MNS; Fig. 43.3) has been widely defined as consisting of three interrelated regions: ventral premotor area (PMv) of the inferior frontal gyrus (IFG; area F5 in monkeys), parietal frontal (PF) in the rostral cortical convexity of the inferior parietal lobule (IPL) of the PPC, and the superior temporal sulcus (STS). Since the MNS is involved in both motor representation/execution and visuomotor representation, it is hypothesized to be important for observational learning, empathy, and mimicry. The MNS has often been thought of as reacting automatically in a bottom-up fashion to observed action, but neuroimaging and behavioral studies show that top–down influences, including selective attention, increase MNS activity and facili-tate subjects’ responses that are congruent with observed actions (Chong and Mattingley 2009). Furthermore, selective attention may be drawn to stimuli not only endogenously through top-down control but exogenously by the motivational salience of stimuli, as suggested in the previous section.

In fact, Gallese et al. (1996) noted that when macaques observed actions oriented toward food-related stimuli, mirror neurons in the premotor cortex were reliably activated whereas the response to similar actions toward non-food items had a tendency to habituate. Similarly, Fogassi et al. (2005) found mirror neurons in the inferior parietal cortex that would respond differently to grasping (exe-cuted or observed) for the purpose of eating as compared to the purpose of placing an object in a container. In fact, a majority of those parietal neurons studied were influenced by the ultimate goal of the action even during the time period in which the grasping motions were identical. Studying

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humans with fMRI, Cheng et al. (2007), reported that hunger enhanced activation in response to food-related stimuli in the parahippocampal formation, OFC, and amygdala, consistent with their motivational salience, but also that hunger increased activation in areas of the MNS, including IFG and PPC. Indeed, IFG and amygdala activations were positively correlated with self-reported hun-ger. These studies demonstrate a special influence of food-related cues and intentions on MNS activ-ity that could be mediated by selective attention mechanisms. As described previously, forebrain acetylcholine plays a role in selective attention and is disinhibited by mesolimbic dopamine. These cholinergic projections target various parts of the cortex, including specifically PPC, one of the MNS areas activated in the Cheng et al. study. Thus, consistent with more general findings that selective attention influences the MNS and motor-matching behavior, eating more with others could reflect in part a chain of events in which food stimuli activate motivational systems that focus attention on visuomotor stimuli serving as a model for one’s own potential eating behavior.

Human behavior in uncertain environments, particularly with respect to food, appears to be grounded in flexible actions. Evidence shows not only that action is biased toward food but that such actions may be prepared but not executed in a type of virtual simulation, in accordance with the

Fig. 43.3 The mirror neuron system (MNS). Schematic of areas in the human brain, such as inferior frontal gyrus (IFG) and inferior parietal lobule (IPL), that contain mirror neurons. Along with the superior temporal sulcus (STS), these make up the “core” of the mirror neuron system (MNS). Additional areas, such as sensorimotor cortex, comprise an “extended” mirror system

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premotor theory of attention. The ability to interrupt and cancel these types of preparatory responses to external events would confer flexibility and adaptability on individual behavior. The human MNS is one mechanism that allows for such preparation of actions toward food. More broadly, mecha-nisms both subcortical and cortical, evolutionarily old and new, enable the formation of dynamic goal states that can shape equally dynamic behaviors via the influence of selective attention.

43.5 Applications to Other Areas of Health and Disease

Much of the attentional bias work reviewed in this chapter has been conducted using participants with eating disorders. The framework presented suggests that it might be prudent to consider differ-ences in motivation, attention, and action, as well as the connections between them psychologically and neurologically, in exploring the etiology of eating disorders (see Table 43.3). For example, it has been suggested that dopaminergic differences constitute a risk factor for obesity in the form of increased sensitivity to reward (e.g., Davis et al. 2007). Peciña et al. (2003) have shown increased motivation and effort to obtain food (wanting) but no increase in orofacial expressions suggesting increased hedonia (liking) in mice genetically engineered to have abnormally high dopamine levels. Motivation to eat is not synonymous with nor necessarily caused by increased pleasure from eating, in much the same way that drug craving is by no means equivalent to or consistently related to drug-induced pleasure. On that point, it is noteworthy that all of the research areas covered in this chapter with respect to food have also been the subject of study in the realm of drug use and drug dependence research, and the implications are essentially the same for how motivation, attention, and action appear to interact to produce drug-seeking and consumption behavior.

43.6 Features of Selective Attention Tasks

In a modified Stroop task, one assesses whether subjects take longer to name the color of words with emotional or motivational salience (e.g., food-related words) than nonsalient control words. Such a difference in reaction time (RT) is presumed to result in part from added difficulty in shifting attention from the semantic properties of salient words to the color in which those words

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Table 43.3 Questions for theory, research, and treatment

1. How separable are pathways for food motivation versus other rewards? What impact might pharmacological treatment targeting food motivation in eating disorders have on other goal-directed behaviors? How about effects of treatment for drug dependence on food motivation?

2. What roles do controlled (conscious) and automatic (unconscious) processes play in the links between food motivation, attention, and action? Can raising individuals’ awareness of these links help treat disorders involving impulsive eating?

3. How do neural pathways for food motivation interact with circuitry underlying cognitive processes other than attention (e.g., perception, memory, and decision-making) to ultimately influence normal and disordered eating behavior?

4. If the mirror neuron system plays a role in facilitating eating and other consumptive behaviors, can it also play a role in behavioral treatments aimed at inhibiting or otherwise changing such behavior through modeling and imitation?

The role of attention in food motivation and behavior is one small piece of a larger puzzle involving other cognitive mediators and other motivations. Addressing the questions in this table will be important for furthering our under-standing of both normal and disordered behaviors, food-related and otherwise

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are displayed, although other sources of response conflict can produce RT differences. Attentional biases also have been investigated using modified tests of visual spatial attention. For instance, in the classic “Posner paradigm” subjects respond to visual targets (e.g., dots) that are preceded by nontarget cues (e.g., boxes). Cues that correctly indicate the location of subsequent targets (e.g., a box surrounding the area where the dot will soon appear) are considered “valid” while cues associated with another location (usually the opposite hemifield) are considered “invalid.” The “validity effect” refers to the RT benefit for target responses on validly as opposed to inval-idly cued trials. By directing attention to the correct location, valid cues are thought to facilitate detection and response, while invalid cues impair detection and response by diverting attention from the correct location. Ordinarily, cues in this paradigm convey spatial information but have no other meaning. The task is easily modified, however, by using emotionally or motivationally salient stimuli, such as food-related words (Fig. 43.4), as cues. Since the subject’s task is simply to respond to targets, the semantic content of the cues is irrelevant, yet those stimuli with special salience may nonetheless increase the focus of attention to their location, magnifying the validity effect by increasing the benefit of valid cueing and/or increasing the cost of invalid cueing. A similar spatial cueing task that is used more commonly to assess attentional bias is the visual probe (or dot probe) task. In this paradigm, two cues appear simultaneously (one in each hemi-field), followed by a target at one or the other location. One of the two cues is an emotionally or motivationally salient stimulus while the other cue has no such salience. If RT is faster to targets appearing at salient cue locations than neutral cue locations, the effect is interpreted as reflecting increased attention as a result of the emotional or motivational content of the cue stimulus, just as it is in the Posner paradigm.

Fig. 43.4 Spatial attention task using words as cues. Each trial of this task begins with visual fixation at a central cross and masks (filler letters) at top and bottom locations. The mask is replaced by a word at one of the two locations (50% chance each; word/mask color also counterbalanced). After a variable delay, the box outline surrounding either the word or the mask briefly flashes magenta (shown with a dashed line above), signaling the subject to respond by pressing a button. The target surrounds the cue 75% of the time (valid trials) and surrounds the mask 25% of the time (invalid trials), creating an attentional set whereby subjects tend to focus attention on the frequently predictive cue location. Responses to validly cued targets are faster than those to invalidly cued targets (the “validity effect”), reflect-ing the costs/benefits of attention. Effects of emotion and motivation on attention can be studied by comparing salient and neutral cue word conditions (e.g., food words versus school/art supply words) and testing for a difference in the validity effect (Adapted with permission from Leland and Pineda 2006, p. 70)

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Summary Points

Food is a primary motivator of behavior because it is both a physiological necessity and a central •element to much social activity.Motivation is based not simply on a pleasure principle but on neural systems involved in predict-•ing rewards and directing attention and behavior toward them even in the absence of pleasure.Selective attention is important for motivation because it prioritizes the processing of goal-rele-•vant information and allows for adaptive responses to a changing environment rather than mere reflexive eating.Selective attention to food-related information has been demonstrated with both behavioral tasks •and brain activity measures.Evolutionarily old brain systems allow for relatively simple motivational states and attentional •influences on action, while their integration with more recently evolved structures enables more flexible, dynamic behavior.The MNS appears to play a role in translating seeing into doing and thus may help explain why •people tend to eat more in the presence of others.Differences in how food motivation, attention, and action processes interact in the brain may help •explain particular eating behavioral patterns, including those associated with eating disorders.

Key Terms

Feedback loop: A system that feeds some of its outputs back to itself as inputs. Positive feedback occurs when such input is excitatory, causing a continual increase in system activity, while negative feedback tends to stabilize system activity since the more active it is the more it opposes itself.

Hedonic theory of dopamine: A theory that argues that mesolimbic dopamine mediates the subjective pleasure associated with delivery of a reward.

Homeostasis: The tendency to maintain stability of an internal state by monitor-ing for changes and making adjustments to compensate for them.

Limbic system: A network of brain structures that is important for aspects of emotion, motivation, memory, and other behavioral functions.

Mirror neuron system: A network of frontal, parietal, and temporal lobe regions with neurons that increase firing rates during execution of an action or observation of a corresponding action performed by others. The MNS may be a neural basis for translating seeing into doing or performing a “simulation” of action without executing it.

Motivation: The goal-oriented force in behavior, contributing to its initiation, direction, intensity, and persistence in the face of obstacles.

Premotor theory of attention: A theory that argues that attention derives from an activation of the same circuits that process sensory and motor information.

Reward: A positive reinforcer; a stimulus whose presentation increases the future probability of behaviors leading to its delivery. The term “reward” can be controversial due to its connotation of subjective pleasure and the notion that such pleasure gives rewards their reinforcing quality.

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Acknowledgements The authors thank Gabriel Loewinger for his feedback on a draft of the manuscript.

References

Berridge KC. Physiol Behav. 2009;97:537–50.Braet C, Crombez G. J Clin Child Adolesc. 2003;32:32–9.Brignell C, Griffiths T, Bradley BP, Mogg K. Appetite 2009;52:299–306.Cavada C, Company T, Tejedor J, Cruz-Rizzolo RJ, Reinoso-Suarez F. Cereb Cortex. 2000;10:220–42.Channon S, Hayward A. Int J Eat Disorder. 1990;9:447–52.Cheng Y, Meltzoff AN, Decety J. Cereb Cortex. 2007;17:1979–86.Chong TTJ, Mattingley JB. In: Pineda JA, editor. Mirror neuron systems: the role of mirroring processes in social

cognition. New York: Humana; 2009. p. 213–33.Corbetta M, Shulman GL. Nat Rev Neurosci. 2002;3:201–15.Craig AD. Curr Opin Neurobiol. 2003;13:500–5.Davis C, Patte K, Levitan R, Reid C, Tweed S, Curtis C. Appetite 2007;48:12–9.de Castro JM, de Castro ES. Am J Clin Nutr. 1989;50:237–47.Dobson KS, Dozois DJA. Clin Psychol Rev. 2004;23:1001–22.Duncan J, Nimmo-Smith I. Percept Psychophys. 1996;58:1076–84.Eimer M, Forster B, Van VJ, Prabhu G. Neuropsychologia.2005; 43:957–66.Fogassi L, Ferrari PF, Gesierich B, Rozzi S, Chersi F, Rizzolatti G. Science 2005;308:662–7.Foote SL, Berridge CW, Adams LM, Pineda JA. Prog Brain Res. 1991;88:521–32.Formea GM, Burns GL. J Psychopathol Behav. 1996;18:105–18.Francis JA, Stewart SH, Hounsell S. Cognitive Ther Res. 1997;21:633–46.Gallese V, Fadiga L, Fogassi L, Rizzolatti G. Brain 1996;119:593–609.Garcia-Segura LM, Lorenz B, Don Carlos LL. Reproduction 2008;135:419–29.Graziano MS, Gross CG. Exp Brain Res. 1998;118:373–80.Kemmotsu N, Murphy C. Physiol Behav. 2006;87:323–9.Key APF, Dykens EM. J Intell Disabil Res. 2008;52:536–46.Kok A. Psychophysiology. 2001;38:557–77.Lavy EH, Vandenhout MA. Behav Cogn Psychoth. 1993;21:297–310.Leland DS, Pineda JA. Clin Neurophysiol. 2006;117:67–84.Mogg K, Bradley BP, Hyare H, Lee S. Behav Res Ther. 1998;36:227–37.Mohanty A, Gitelman DR, Small DM, Mesulam MM. Cereb Cortex. 2008;18:2604–13.Overduin J, Jansen A, Louwerse E. Int J Eat Disorder. 1995;18:277–85.Parikh V, Kozak R, Martinez V, Sarter M. Neuron 2007;56:141–54.Pecina S, Cagniard B, Berridge KC, Aldridge JW, Zhuang XX. J Neurosci. 2003;23:9395–402.Posner MI, Dehaene S. Trends Neurosci. 1994;17:75–9.Posner MI, Petersen SE. Annu Rev Neurosci. 1990;13:25–42.Posner MI, Rothbart MK. Annu Rev Psychol. 2007;58:1–23.

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Salience: The state or quality of standing out, for instance due to atten-tional selection, greater sensory intensity (sensory salience), or goal-relevance (motivational salience). According to Berridge (2009), rewards and the cues that predict them acquire “incen-tive salience,” which leads to “wanting” them.

Selective attention: The selection of some information for increased processing at the expense of other (unattended) information.

Spatial attention: Attention selectively directed toward a location in space, confer-ring its information-processing benefits to stimuli at that location.

Triarchic model of attention: A theory that argues that attention is a mechanism separate from information processing and that it consists of orienting, alerting, and executive subsystems.

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Reep RL, Corwin JV. Neurobiol Learn Mem. 2009;91:104–13.Rizzolatti G, Craighero L. Annu Rev Neurosci. 2004;27:169–92.Rizzolatti G, Riggio L, Dascola I, Umilta C. Neuropsychologia 1987;25:31–40.Rolls ET. Philos T Roy Soc B. 2006;361:1123–36.Salamone JD, Correa M, Farrar A, Mingote SM. Psychopharmacology 2007;191:461–82.Schultz W. Annu Rev Psychol. 2006;57:87–115.Shafran R, Lee M, Cooper Z, Palmer RL, Fairburn CG. Int J Eat Disorder. 2007;40:369–80.Siep N, Roefs A, Roebroeck A, Havermans R, Bonte ML, Jansen A. Behav Brain Res. 2009;198:149–58.Simmons WK, Martin A, Barsalou LW. Cereb Cortex. 2005;15:1602–8.Wang GJ, Volkow ND, Telang F, Jayne M, Ma J, Rao M, Zhu W, Wong CT, Pappas NR, Geliebter A, Fowler JS.

Neuroimage 2004;21:1790–7.

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Author QueriesChapter No.: 43 0001200966

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AU4 Should the “Features of Selective Attention Tasks” section be set as separate unnum-bered “Key facts” section? Please advise.

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