CHAPTER

21 Neuroscience and Human Motivation

Johnmarshall Reeve andWoogul Lee

Abstract

Recognizing the potential for interdisciplinary research in motivational neuroscience, the goal of the present chapter is to show the relevance of neuroscience research to human motivation researchers and to suggest ways to expand their programs of research , methodological options, and theoretical conceptualizations of the motivational constructs with which they work. T 0 illustrate the neural bases 。f human motivation, we highlight 15 key motivation-relevant brain structures, identify the neural core 。f reward-based motivated action, and discuss a range of brain-generated motivational states that extend from those that are relatively automatic and stimulus dependent (e.g., pleasure from taste) t.。those that are relatively intentional and context sensitive (e.g., goals). We then examine the following 10 well-researched concepts from the human motivation literature to suggest how each might be enriched through neuroscientific investigation: agency, volition, value, intrinsic motivation, extrinsic motiva디。n ， flow, expectancy, self-efficacy, self-regulation, and goals. We conclude with suggestions for future research

Key Words: motivation, neuroscience, striatum, reward, dopamine, prefrontal c。πex

Introduction 따1e “and" in the chapter title is imporrant, as it

reflects the contemporary view that human motiva­

tion study and neuroscience are rwo different lields. 까lat is, the people who study human motivation, the journals they publish in, and the empirical methods they rely on are not generally pop띠ated by a neuroscience focus, though these same researchers (and journ띠s) recognize the potenti쇠 contrihution of neuroscience to human motivation study. Neu­roscientists ohen study the same content-the same

motivational constructs, though they routinely concepcualize these motivational constructs more narrowly. Neuroscientists also tend tO study basic, stimulus-driven motivations, such as hunger, thirst, pleasure and reward, though more complex motiva­tions (e.g., volition, self-regulation) are 외so mves­tigated. Overall, equal measures of optimism and

skepticism are in the air when human motivation researchers sÎt down at the table with neuroscientists to discuss collaborations and points of integration

A decade ago, Richard Mayer (1 998) character­

ized the relationship berween neuroscience and his field-educational psychology-through the imag­ery of dead-end, one-waι and two-way streets. He characterized (and lamented) the then-present rela­tion berween neuroscience and his field as an intel­

lectual landscape characterized by dead-end streets in which the rwo fields of study had litde in com­mon and contributed litde to the enrichment of the

other. He also observed (and again lamented) an intellectual landscape of one-way streets in which neuroscience research was unidirectionally applied to educational psychology. For instance, neurosci­entists identified the limits of hippocampal-based

short-term memory (e.g. , cognitive overload) , and

’ / 0 3

educational psychologists revised their theories of learning and their recommendations for the design of instruction accordingly (e.g., Paas, Tuovinen, Tabbers, & Van Gerven, 2003)

The metaphor Mayer offered to enrich interdis­ciplinary activiry was that of a rwo-way streer. 1n rhis scenario, neuroscience study in f1uences moti­vation research, while motivation study influences neuroscience research. Such a rwo-way relationship is only possible with the. emergence and contribu­tions of interdisciplinary researchers. Interdisci­plinary researchers are those who feel free and able ro traverse not only the landscape of their home field of srudy but also the landscape of the allied field. Several examples of such successful interdis ciplinary research have emerged, including cogni­tive neuroscience (Gazzaniga, Ivry, & Mangun, 2008) , affective neuroscience (Davidson & Surron, 1995), social neuroscience (Decery & Cacioppo, 2010) , and neuroeconomics (Loewenstein, Rick, & Cohen, 2008).

The goal of the present chapter is ro embrace this rwo-way street imagery and, in doing 50, embrace rhe potential value in intεrdisciplina..ty motivational

neuroscience. If interdisciplinary motivational neu­ros디entists are to become a critical mass of scholars, researchers in both fields will need ro consider the merits of reengineering these otherwise one-way and dead-εnd streets into two-way streets of infor­mation, methodology, and theory development. To facilitate such progress in the present chapter, we first overview the neuroscience research mat is broadly relevant ro probably all contemporary human motivation srudy as we illuminate the biological substrates of human motivation. We then address conceptual points of convergence and divergence berween neuroscience and human motivation study across the following 10 감equendy srudied motiva tional constructs: agency, voIition, v:꾀ue， intrinsic motivation, extrinsic motivation, B.ow, expectancy, self-ef!ìcacy, selεregulation， and goals.

Any new field of study (e.g., motivational neurosci­ence) necessarily beginswirh description and taxonomy. 1n rhat spirit, Figure 2 1.1lisrs 15 key brain strucrures identified by neuroscience research as motivation rel­evant and illustrates rhe anatomic location for each Five structures reside within the neocortex: prefrontal cortex, venrromedial prefrontal cortex, dorsolateral

Fig.21.1. Anatomic location of 15 key motivatiolHdevant brain.strucrures. (A) A medial sagittal section of the brain 끼.1e dotted line represenrs the point that a coronal sec(ion of the brain (C) ‘ acquired. (B) A lateral sagittal seιtion of the brain

366 I NEUROSCIENCE AND HUMAN MOTIVATION

prefrontal cortex, orhitofrontal cortex, and anterior디n­

gulate cortex. Sα structures reside with the basal 뽕n­

빙ia: dot혜 striat l1m-cal1date 띠cleus and p l1tamen, vεntral striatum-nucle l1s accumbens, glob l1s p떠lidus，

ventral tegmental area, suhstantia nigra, and venual palladillm. And four stcuctures reside within the lim­bic system: amygd쇠a， hypothalamlls, hippOcampllS, and insular cortex. It is with these 15 brain stcuc­tures that we will illllstrate the neural bases of hllman motlvatlon‘

When defined in the cOntext of behavioral sci­ence, motivation concerns the study of all those processes that give behavior its energy and direc­tion (Reeve, 2009). In neuroscience, motivation is generally conceptualized as energy for behaviors related to obtaining rewarding stimuli or situa­tions (Mogenson, Jones, & Yim, 1980; Robbins & Evericc, 1996). That which energizes behavior is subscribed to a rather narrow set of neura! pro­cesses, such as those in 버e mesolimbic dopamine system. While these basic neural processes energize behavior, the sources that actÎvate these basic neu­ral processes are many (e.g., natural rewards, social rewards; Berridge, 2004; Berridge & Robinson, 2003; Wise, 2004). In the next section, we summa­rize the basic subcortical neural core that energizes reward-related action. Once done, we overview the more specific types of motivation that activate these basic subcortical neural processes

Neural Core ofReward-‘ßased Motivated Action

From a biological perspective, the role of reward in motivation is fund잉nental. !t is fundamental to survival, to learning, to well-being, and to the gen­eration of goal-directed effort (Schultz, 2000). The energization or generation of goa!-directed effort (motivated action) follows from and is dependent on fi.rsr extracting reward-related information from environmental 0비ects， events, and circumstances, and this reward-related information consists largely of the release of the neurotransmiccer dopamine (Berridge & Kringelbach, 2008).' The reward­related information that people extract from their surroundings includes the presence and availability of reward, the value of the available reward, the pre­dictability of the reward, and the costs associated with trying to obtain that reward ‘

In addition, repeated experiences with objects and events a110w people to form mental repre­sentations in which these environmental stimuli come to signal reward information in a predictive

fashion . In this way, past reward-related informarion helps esrablish an anticipatory motivationa! va!ue of objects and events. Reward receipt and reward expeccation both involve neural activations that ryp­ically give rise to pleasant feelings and a good mood and, hence, to the subjective experiences of pleasure and positive a라ct (at !east in hlunans). This same reward-related information also serves as the basis offuture goals, which are mental representations of sought-after (reward-relared) environmental events In addition, when the reward valu앙 of mu!tiple environmental events are compared, people show preferences (in terms of choice and the amount of effort expended) for different objects and events. Hence, biologically experienced reward serves as the basis nor on!y for reward but for the additional motivarional constr l1cts of value, expectancy, plea­sure/affect, goal, and preference 끼1e neural substrates of 버is dopaminergic family

of reward-based motivational states appear in Figure 21 .2. Theneuralcoreofgoal-directedmotivatedacrion is the pathway from the motivation-generating dop­amine system to the movement-preparation and behavior-generating supplementary motor 앙ea and premotor cortex (see righr side ofFig. 2 1.2). Within the phrase 끼notivated acdon," the Dopamine system box represents 며e fundamental core of “motivated)) while the S"bstantia nigm, glob，μ pallidus box rep­resents the fundamental core of “action." Feeding mto 비is b잉ic reward processing core are a number of brain areas that process reward information by releasing dopamine, such as responsiveness to natural rewards (hypothalamus) , the particu!ar characteris­tics of any one particular reward in the limbic regions (e.g., arnygdala), and the inreroceptive information of rewards in the limbic-related regions (e.g. , insu!ar cortex) as well as responsiveness to the values (and relative v띠ues) of various rewards (orbitofrontal cor­tex), the mental representation of reward as a goal 。bject (dorso!ateral prefrontal cortex) , and executive control over goal-directed action (anterior cingu­late cortex) . In addition, as depicred in the boldface double-sided arrow on the left-hand side of rhe fi.gl1re, reciprocal relations connect the limbic regions with rhe prefrontal cortex as limbic regions gener­ally feed-forward pr이eαions into the prefron때

cortex while prefrontal regions generally feed-bacl< pr，이ec디ons to the various limbic regions

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빠

Limbic Regions Hypothalamus Responsive ‘。 n:uural I'eward‘

AMYGDALA Rcsponsive ro panicubr reward ch.미ζten “，~ Dop잉mnesystem

Insul:u corteJ[

Reprcsenlalion of cmolÌonal ‘디“c$ ofreward‘

Substantia Nigra, Globus f버 lid여

Bchavior prepantlion and cx<<ution. Thcse basal g:m잉" “ ruClU rcs pro)ec‘

Prefronta1 C씨''''

Orbitofronttl Co rlC‘ Respon‘ive ‘。 information of rcw:u닝， . Nuclμus Aa:umben$

inlo thc pre-supplcmenrnl mo{or arca, ‘he supplemen비 m。‘。r area. and Úle pnmary mOlor ∞no: O.e., mc mOlor _of‘b，∞nu)

Respon‘;V(' 10 rhc valuc of rcwards; respon‘… ‘。 prefcrcnces bctwccn rcwards.

’ c::.udarc Nudcω • I'urnmcn

Dorsolatcral Prcfrontal ConcJ[

Mcmal rcprescma lÎon of rcward :lS a goal 얘cr.

Antcrior CinguJa‘, ç.,‘<x ，""ιulivc control of goal-diπCIOO aClion

Fig. 21.2. NeuraJ core of reward-based morivared acrioll

Sources ofReward-Based Motivation Ir is imporranr ro undersrand rhe narure of

various biological sources of mocivation (depicced 。n che left-hand side of Fig. 21.2) because differ­ent sources of motivation lead co different types of motivation. For instance, S01ne sources of morivation are implicir and objective (e.g. , rhirsr, hunger) , while orher sources are more conscious and cognitive (e.g. , ultimate goals). As we will see, che types of mocivation induced by relatively implicir and objecrive sources rend to generate rarher automaric motivational srares, whereas rhe types of motivation induced by more conscious and cognitive sources tend to be rather rarional motivarional srares. Accordingly, ro classify and co underscand che different types of biologically generated motivarional srares, we need to rhink carefully abouc (1) what che sources of che moci­vacional state are, (2) how much the source of the morivational srare is implicir and objecrive (versus explicit and cognicive) , and βv how much che var­ious sources of morivarion conAict when sources of motivation are divergen r. Based on these con siderarions, we present four sections to illustrate a l'ange of brain-generared motivational srates chac extend from chose chac are largely subcorci­cal, relatively autOJnatic, and stimulus dependent (e.g. , pleasure from caste) Co chose thac are largely cortical, intentional, and context sensitive (e.g. , personal scrivings)

Relatively Automatic Motivational States Neuroscientific approaches ro motivation d。

a particularly good job of explaining relatively auco­ffiaric homeostatic motivational processes that are driven by ingestibles (or consumables) , such as food and warer. Ingesred substances are natural rewards (e.g., food, wacer) chat play a key role in energizing consumacoty behaviors chat chen lead co changes in homeostatic and hedonic motivational stares. These motivational stares are closely monirored and regu­lated by subcorticallimbic scructures (Saper, Chou, & Elmquist, 2002), as the hypochalamus plays an imporrant role in relatively auromaric consumarory behavior while che dopamine-based mesolimbic sys­cem plays an important role in learned instrurnental behaviors. Homeosraric motivational states such as hunger (appecite) and satiety arise racher automati­cally (and reliably) from cooperative networks dis­tribuced chroughouc che body, including chose in the brain (hypothalamus, mesolimbic system) but also chose in che endocrine/hormonal and auCO­nomic syscems (Powley, 2009)

1hirst is a brain-generated motivational srate rhar arises when people physiologically need co ingesc water co maincain adequate fluid balance chrough­out che body. Reduced wacer generates thirsc 버e

urge co ingesc wacer, and che body's remarkable constancy of inrracellular and extracellular wate l'

is regulared by neura l, hormonal!endocrine, and behavioral mechanisms (McKinley, 2009) 까lough

368 I NEUROSCI ENCE AND HUMAN MOTIVATION

hypothalamic-based thirst contributes to water intake (drinking) and to the involllntary regulation of water conservation (e.g.) hormone release, kid­ney function) , most human beverage consumption is determined by the reward aspects of the ingested ßuid, including those related to taste, odor, rem­perature, alcohol, caffeine, and social consequences (Booth, 1991). Thus, brain structures sllch as the orbitofrontal cortex and amygdala respond to the rewarding properties of fluid intake (RolIs, 2000), and these brain structures then feed this reward­relared information inro the striaturn that underlies the dopamine reward system that energizes fluid intake (Wise, 2002), as depi다ed in Figure 21.2. Recognizing 나le important motivational role of the rewarding properties of ingestibles (e.g. , sweet taste) expands the neutal bases of motivation from hypothalarnic-centric homeostatic motivational states to include srimulus-driven, dopamine-cenrcic motivarional states (i.e. , incentive motivation).

Motiν'ational States B.ιsed on Associative Learning (Close to Automatic)

Environmental incentives are those we tend [0

approach and Ie [UIfl to after experiencing rheir rewatding properties. Incentives have rewarding properties and promote approach-oriented behav­ior because they send information through the five senses 버at reach the mesolimbic dopamine-based reward circuitry to (1) activate those reward path­ways (e.g., Fig. 21.2) , (2) activate those reward pathways powerfully (above threshold) , β~ activare rhose reward parhways with litr\e delay in reinfotce­ment (so to yield a high degree of reward effective­ness) , and (4) produce rewarding effects that decay rapidly (half-second after onset) (、JV'ise ， 2002) . Some incentive values are universal or objective, such as a sweet taste or a roxic smell‘ Other incenrive val­ues (e.g., color preference) are learned subjecrively or circumstantially. The more an incentive value is universal or objective, the rnore Îr will be associared with rnotivational states rhat are auromatÍc.

1he learning (remembering, conditionin밍 of rhe incentive value of environmental events r와<es

place in several brain areas. The amygdala evaluares a stimulus as associated with eirher reward or pun­ishment, signals that it is porenrially important (or nor) , and evaluares the stimulus as unpredicted or nor (Whalen, 1999, 2007). In rhis w씬 때ygdala

activity builds associarive knowledge about a srimll­IllS’'s motivational and emotional significance (Baxrer er 야， 2000; Baxter & Murray, 2002; Schoenballm, Chiba, & Gallagher, 1999). This informarion is

mainly stored in the hippocampus and insular .cortex, though it is a1so stored in corrical regions as well, inclllding the orbitofronral cortex. τhe more auromarÍc or simple rhe incentive-based information is, rhe more Iikely it is that it will be srored subcorti­cally in 버e limbic system or in the limbic-r，려ared regions (e.g. , insular corcex)j rhe more cognitive and less auromated the incentive-based information is, the more Iikely it is that it will be srored corrically in the orbirofronral cortex. When insrrumental behaviors are needed, these various brain regions deliver their stored incentive value information t。the mesolimbic dopamine system, which then ener­gizes consumatory morivated action (when intense enough ro exceed a threshold of response) ‘ 1n addi­tion, the nucleus accumbens (within the venrral srrέarum) is active in rhe experience of rewarding and pleasurable feelings, as rhe presentation of pleasant images, pleasant rastes, and many addicrive drugs (e.g., opiates, cocaine, amphetamine) are dopamine releasers in the nucleus accumbens (Sabatinelli er a1., 2007; Wise, 2002)

To explain how associative learning processes occuι some researchers parse reward informarion inro rhree psychological componenrs-Iearning, affect (emorion), and morivation (Berridge, 2004; Berridge & Robinson, 2003). Learning has tw。forms-associatÎve and cognitive. Associative learn­ing refers to the relatively auromatic forms of incen­tive learning, while cognitive refers to the relativ，εIy

more complex and less auromatic learning relared to actlVltles lfl 마e correx (e.g., orbirofrontal cortex) AJfect a1so has two forms: Iiking and conscious plea­sure. Liking is one'’'s implicit (nonconscious), hedo­nic reacrion to an objective environmenral stimulus (e.g., sweet taste) that arises from nondopamine mesolimbic activiry (e.g. , opioid neurotransmis­sion). Conscious pleasure is a more general form of liking that involves awareness and arisεs from cortέC혀 aαivity. Motivation too has rwo forms-want­ing which is implicir (nonconscious) and objective, and wanring that is cognitive, conscious, and goal direcred 끼1e affecrive distinction between implicir liking

and explicir pleasure and the morivarional distinc­tion between implicit desire and explicit goal striv­ing is importanr for several reasons. Firsr, affect 때d

motivation can diverge. Liking and wanring rypi­c며ly converge in natural situations (i.e. , we wan

n / r o 3 E

다

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wanting) that brings little or no pleasure (conscious liking). Second, these two forms of Iiking and these two forms of wanting mean that incentive values will sometimes be conßicting in naturally occurring behavior (e.g. , should 1 watch the television show 1 Iike or should 1 go to a social event to meet poten­tial nεw friends?). In these situations, people need to resolve these motivational conßicts using higher order cognitive, emotional, and motivational pro­cesses (Li tman, 2005).

j‘’ψlicit Motivational States /nvolved in Decision Making and Action

Subcortic꾀 (Iimbic system) processing of envi­ronmenral events plays an imporrant role in deci­sion making and action. In daily Iife, few situations involve only a single stimulus, as decision making in the 상ce of diverging and conßicting incentive values is the llOIffi (rwo restauranrs, two social events, 30 di라rent chapters in this Handbook). When people make decisions, they rely on a great deal on both cognitive processes and emotional processes, even to the point that it is diflìcult to separate out cogni­tive activity from emotional aαivity， as the two are so neurally intertwined that it makes Iittle sense to

treat them as separare entities during decision mak­ing. In this secdoll, we review how nonconscious processing creates feelings (e.g. , affect, intuition) rhat bias what memory content emergεs into C011-scious awareness that is then acted 011 in terms of decision making and action. Such affectively based decision making can be demonstrated through the dopamine hypothesis of positive 빠능ct， pnmmg, and the somatic marker hypothesis

DOPAMINE HYPOTHESIS OF POSITIVE AFFECT

Positive a없ct influences decision making and problem solving such 다1at people who feel good, compared to people in a neutral mood, are more Iikely to recall positive materi와 from memo대 and this accessibility has been shown to promote ßexibil-ity in thinking, creative problem solving, eflìciency and thoroughness in decision making, improved thinking on complex tasks, variery seeking, enhanced intrinsic motivation. and a greater willingness to help (Isen, 1987, 2003). 꺼1e dopamine hypothesis 。f positive affect (Ashby, Isen, & Turken, 1999) proposes that the presence of mild positive feelings systemically affects cognitive processes and that it is increased dopamine in certain brain regions that produces the mild positive feelings and facilitating . effects on cognition. For instance, the receipt of a small unexpected positive event (unexpected gift,

humor, task success) activates dopamine neurons in the ventral tegmental area, which sends dopamine projections into many cortical areas, including μ:J the prefrontal cortex, which enriches working memory, openness to information, willingness t。

explore, creative problem solving, and the integra tion of ideas; and (b) the anterior cingulate cortex, which increases attention, flexible thinking, switch­ing easily among alternative objects or action plans, and the sort of enhanced perspective 때이ng that leads to prosocial behaviors such as cooperativeness, generosiry. soci꾀 responsibility, and improved nego­t1at l11g sμIIs (Ashby et al. , 1999)

Cruciallι the dopamine hypothesis of positive affect proposes that it is only mild, evetyday positive feelings-the type of positive a라ct that remains outside of conscious attention-that produces these facilitating eß능cts on decision m와dng， problem solving, creativity, and prosocial behavior (Isen, 2003). If the dopamine increase is relatively large or if the person is made aware of the positive affect state (e.g., "My, areá’'t we in a good mood roday?") , then research shows that the facilitating effect is lost (Isen, 1987). The dopamine hypothesis, however, seems to contradict 마e wanting versus Iiking dis­tinction introduced in 바e previous section, as lik­ing is not dopamine based‘ 까le difference berween the two hypotheses might suggest that the positive affect (liμng) is epiphenomen꾀 and that it is only the dopamine increase (not the positive affect expe­rience per se) that facilitates cognitive processes and proSOCl떠 behavior

PRIMING

Priming is the procedure 마at evokes an implicit response from an individual upon exposure to a stimulus that is outside his or her conscious aware­ness. While priming occurs outside of the person's conscious awareness, the prime itself can be deliv­ered unconsciously or consciously. An example of an unconsciously delivered prime might be a word that is ßashed so brießy on a computer screen (e.g ’ 30 msec) that it is not recognizεd， though it still produces an implicit e딴ct. An example of a con­sciously delivered prÎme might occur as the person is asked to judge if a dot appears above or below a word, a word whose content induces an implicit effect (e.g. , the words “good" or “:pleasant" might produce impli디t positive feelings)

Primes that activate a mental representation of a behavior (outside the person'’'s awareness) prepare people to enact behaviors consistent Witl1 tl1at mental representation. For instance, the smell of a cleaning

370 I NEUROSCIENCE AND H뼈AN MOTIVATION

solution, the site of. briefc.se, .nd viewing • Iibrary painting le.d people to eng.ge in cle.ning beh.v­ior, competitive behavioI, and hushed COflversation, compared to the absence of these primes, though p'다icipanrs report being unaware of the aroma, briefc.se, or painting (Aarts & Dijksterhuis, 2003; HolI.nd, Hendriks, & A.rts, 2005; K.y, Wheeler, Bargh, & Ross, 2004). 1hese findings show that nonconscious prirnes prepare (i.e., motivate) action

Primes .Iso influence • wide r.nge of π。riva­

tions. Primes have been shown to acrivate implicit motives such .s power and af!iliation (Schultheiss, 2008), olltcome expectan디es (Cusrers, Aans, Oikaw., & Elliot, 2009) , autonomous motiv.­tions (Hodgins, Yacko, & Gott!ieb, 2006), and so forth. For instance, students who were asked to solve I.nguage puzzles populated by .chievement­related words (“'win") outperformed and outper­sisted students who were asked to solve the same language puzzles populated by neutral words when both groups worked on a second task unrelated to the langllage-puzzle task (B.rgh et .1., 2001). 1his means that the nonconscious activation of the moti­vationa1 state promores behavioral activation if 버e

morivarional state irself is associated wirh positive valence (Aarts, Custers, & Marien, 2008; Custers & A.rts, 2005) . 1hat is, primes f.cilitate motiv.ted action by activating mental representations of action (i.e., the subliminal presenration of the words “exen" and “vigorous") , implicit motivational states, and positive affec(; furtherffiore, rhese effecrs occur even though panicipants are unaware of the presen­tation of the primes

SOMATIC MARKER HYPOTHESIS

Another hypothesis .bout the role of feelings in dεcision making is the som.tic m.rker hypothesis (Bechara & Damasio, 2005; Bechar., D.masio, & Dam.sio, 2000). In this hypothesis, the key brain structure is the insul.r cortex (Singer, Critchley, & Preuschoff, 2009). 1he insula (inslll.r cortex) pro­cesses interoceptive (visceral, homeostatic) informa­rion abour the state of one’'s body .nd a1lows the person to cons[[uct a consciously aware representa­tion of how he or she feels (Craig, 2009; Wicker et al., 2003). Furthermore, insul •• ctivityseems to be mv이ved in practically 011 su비ective feelings (Cr.ig, 2009). In the .nterior insul., people consolid.te this feeling-st.te inform.tion with social-contextual information abour 마e task they .re involved in .nd the people .round them to form • b.sis of the conscious experience (subjective .w.reness) of emo­Uon or a빠ct (Cr.ig, 2002, 2008). 1he insular a1so

processes and Iearns .bout risk .nd uncert입nty. 1his

is import.nt becallse the role of the insula seems (0 be [Q integrate current feeling, a risk prε:diction forεcast (that h.s a degree of llncertainty) that arises from the anticipation or consideration of the future Qutcomes of one’'5 aC[Ìon5, and contextual informa­tion to produce a global feeling st.te that guides decision making (Singer et 01., 2009) 까1e somatic marker hypothesis w.s originally

based on observations thar patÎenrs with ventro medial prefrontal cortex lesions commonly showed emotiona1 impairmenrs and made destructive soci피 deζisions， even rhough rheit cognirive capacities were unaffected. Based on these c1inical observa­tions, researchers proposεd th.t emotional processes (bodily st.tes .nd feelings in this case) pl.y'εd .n important and construcCÌve role in the ::lecision­m와이ng process (D.m.sio, 1994, 1996). 1he body'’s primary inducer of bodily st.tes is the amygdal., and the ventromedial prefront피 cortex works as a second.ty inducer ofbodily st.tes (e.g., p잉n， hean­beat aw.reness, rhythm, af!ili.tion) (Baxter & Mur­r.y, 2002; Baxter et .1., 2000; Schoenbaum et .1., 1999) ‘ As incenrive-related events (those associated with morivarional and emotional significance for the person) change the body, the insula integrates these changes into a conscious, su에ec띠eemotlon싱

experience (much in the spirit of the James-L.nge 나1∞ry of emotion; James, 1894).

Ne",'al Bases 01 Rational Motivational States in Decisioη Making and Action

Sever쇠 regions in the prefrontal cortex exert executive or cognitive control over decision mak­ing and action. For instance, 이1e medial prefrontal cortex (both dorsal .nd ventral), inferior frontal cortex, dorsal section of the anterior cingulate co1'­

tex, .nd the dorsol.teral prefrontal cortex aII work for cognitive control of decision 떠따cing and action (D.vidson & Irwin, 1999; Ochsner & Gross, 2005; Ridderinkhof, v.n den Wildenberg, Segalowitz, & Carter, 2004). As • c.se in point, the dorsol.teral prefrontal cortex activations occur when one pur­sues a long-term reward in favor of a shorter term, stri.cum-b.sed rew.rd (McClure, Laibson, Loewen­stein, & Cohen, 2004).

In understanding the cognitive control over decision making and action, one needs ro recognize the m.ssive cortical feedback th.t occurs through­out the br.in. For inst.nce, the amygdala not only procε:sses 버e emotional significance of sensory inform.tion and sends th.t inform.tion to the prefrontal cortex (feed-forward), but the amygd며a

REEVE , LEE I 37 1

쇠so receives information from the prefrontal cortex (Freese & Amaral, 2005) . Similar (and mas­sive) feedback flows of information occur through­out cortic외 and subcortical brain regions (as depicted by the large double-sided arrow between them in Fig. 2 1.2) 까üs prefrontal cortex flow of feedback information adds information abour the environmental context and conscious intentions into the neural core depicted on the right-hand side of Figure 2 1.2. Furthermore, this prefrontal lobe information comes in cydes of continuolls infor­mation and, according to some estimates, chese cop­down feedback projections likely exceed the number ofbottom-up feed-forward projections, at least with adults (Salin & B띠lier， 1995). 1he result is an inte­grated feed-forward and feedback system in which basic sensory information feeds-forward rather auto­matically and rapidly, while top-down deliberative information (intentions, goals), which is a없다ed

and biased by the aforementioned feed-forward information, contributes regulatory and intentional processing (Cunningham & Zelazo, 2007; Miller 8ι Cohen, 2001)

Motivationally relevant brain struc(ures are clearly reactive and responsive [0 environmental event$. In this sense, motivation “ happens" to rhe person as an adaptive reaction to these environmenral evεnts . !t is also true, however, 이1at brai l1 actÎvi ry is proactive in that people regularly anticipate the future (Bar, 2007). According to Bar, people are not so much passively waiting to be activated by environmental events as chey are continuously busy generating pre­dictions about the future. These predictions have motivational and emotional implications and there­fore focus attention on the neural basε:s of proactive and purposive motivational states.

At one extreme, the brain is involved in proxi­mal predictions, such as expecting to receive a shot upon walking in the doctor’'s office. But, at another extreme, the brain is involved in distal predictions, as the person anticipates experiences, plans far al1ead, and uses memory-guided simulations to mentally travel into 마e future (Szpunar, Watson, & McDer­mott, 2007; Add.is, Wong, & Schacter, 2007) 까1e

important point is that people plan, imagine, and project themselves into the future in a way that allows them to better prepare for that futllre, and these activities are subserved by brain processes specifìc for complex executive forecasts and predic­tl

2006) . lt is this set of complex executive predictions and forecasts that dominate current thinking about human motivation (e.g., goals, plans, expectations, futllre time perspective, possible selves) , the topic t。which we now turn ‘

Key Motivational Constructs in Human Motivation Study

To this point in the chapter, the çonversation has been rather one sided, as we have presented and summarized 나le neuroscientifìc perspective on motivation. In the present secrion, we focus on sev­eral central motivational constructs 야lat are richly studied in the human motivation research litera­ture that occurs outside of a neuroscience focus. In doing so, we will compare and contrast the hurnan morivation understanding of these complex motiva­tional states with the neuroscienti fi.c understanding 。f these same phenomena. In particu1ar, we discuss agency, volition, value, intrinsic motivation, extrin­sic morivation, flow, expectan양 selεeflìcacy， self­regulation, and goals

Agency Agency is the sense that “ 1 did that," and it lies

at the center of intentional, voluntary, and purpose­driven action. Human motivation researchers tend to study agency broadly, defìning it, for instance, as self-generated motivation to act on the environ­ment-the proacrive desire to create, manipulate, in A. uence, and transform the environment 비at one is in so to improve it in some way (Bandura, 2006) Neuroscientists study agency more narrowly, as they contrast an experience of selεas-cause versus other­as-cause of an action (Engbert, Wohlschlager, & Haggard, 2008; Farrer & Frith, 2002; Spengler, von Cramon, & Brass, 2009). In these investigations, the person performs a simple action (e.g., move a joystick) that causes an event to happen (e.g. , m와<e an image appear on the screen) , and the causal source of 버at action is manipulated experimentally such that what happens is direcdy linked to d,e per­son’'s own intentions and behaviors or is unrelated to them, because a computer program or the experi­menter causes the action such that anything done by the parti디pant is superfluous. Results show that an experience of agency is closely linked to and depen­dent on the acrivities of moror-related brain regions, such as the supplemental motor area and the presup­plemental motor area, which plan and enact an effer­ent motor command-that is, agency arises from a tight relation between action and effect as the person must self-generate 다1e motor instruction to perform

372 I NEUROSCIENCE AND HUMAN MOTIVATION

an action to feel a true sense of perso l1al agency. If the person el1acts the same behavior without self­Ìnst[uction to do 80 (e.g. , an outside agent actually causes the perso l1'’'s behavior) , litcle agency is experi­enced. Furthermore, the greater the length of time that elapses betwξenon안 action and the effect it pro­duces, the less the resulting sense of agency will be, as the sense of“ I did that" is put into dOllbt by the rival belief that “'maybe something or someone else did it" (Spengler et 꾀.， 2009). Such agency is asso디ated

with activarion 1n the insula, while such nonagency is associated with acdvation in rhe inferior parietal cortex (Farrer et al., 2003; Farrer & Frith, 2002). Pressing a butwn while Iying in al1 fMRI machine is a long way from improving one’'s working condi­tions or changing one’'s career path, but the premise is the s잉ne-“unless people believe they can produce desired effects by their actions, they have litcle incen­tive to act" {Bandura, 2006, p. 17이

Volition Some neurosclenrists study mental control over

action as volition, rather than as agency (Haggard, 2008). In this research, neuroscientists use experi mental tasks that give parti디pants freedom whether to perform acrions, when (0 perform actions, Or how many rimεs w perform actions, and they then search for related neural activities (Haggard, 2008; Libet, Gleason, Wright, & Pearl, 1983; Nachev, 2006; Nachev, Rees, Praton, Kennard, & Husain, 2005). The results consistencly indicate that (1) vol­untary cont!ol activates motor-related brain regions, such as the supplementary mowr area and the pre­supplementary mowr area, and (2) conRict moni­toring during this volllntary control activates the dorsal anterior cingulate cortex, as the individual attempts w cope with the cognitive conRicts that arise. In the human motÎvation research literature, Heinz Heckhausen distinguished what was termed agency in the preceding paragraph from volition by defining agency (motivation) as that which initiates action (e.g., need, goal), whereas volition involved the persistent striving of that morivaced action over time and in the face of obstacles (Heckhausen, 1977). In other words, human motivation research­ers view volition 앓 the cognirive. emotional, 때d

motivational control that Qccurs over time (0 carry out (not w initiate) goal-directed behavior (Goll­w1tzeι 1996). As such, volition encompasses diverse cognitive, emotional, and motivational processes (e.g. , conRict monitoring). To expand the study of volition beyond that of agency, it would seem that interdisciplinary motivational neuroscience

researchers need to examine the neural circuits of . various aspects of cognitive, emotion꾀， and moti­

vational control over action, and some neuroscien tist have begun to do this (Haggard, 2008; Nachev, 2006; Nachev et al., 2005)

Wzlue Value is a central concept in contemporary moti­

vation study, as it serves as the core constrllct under­Iying the expectancy X value family of motivation theories (Wigfield & Eccles, 2002). In expectancy X value theories, value is a ffiultirumensiona1 con­struct composed of four divergent sources: intrinsic interest, utility value. attainment value, and cost. High values on each of thεse components of value (cost needs to be reversed scored) generally cor­relate with choice behavior and peπistence (Wig­field & Eccles, 2002) 까lÌs conceptualization of value is noticeably different from the neuroscience conceptualization of value, which is the incentive­based, reward-related i뼈rmation of an 0비ect or event, and that reward value is sometimes natural (e.g., water, orange juice) but often learned or con­ditioned (Dickinson & Balleine, 2002). When 버e

learned reward-based information is su에ectlve or circumstantial (rather 버an universal or objective), orbitofrontal conex information is active and, once the incentive value of variolls environmental 。비ects

and events is learned, activity in the orbitofrontal cortex helps people make choices between options, consider their options, rememher the incentive value associated with each of those options, and make their selection arnong the differendy valued obje다S to pursue (Arana et 뇌 , 2003; Rushworth, Behrens, Rudebeck, & W:쇠ton， 2007) .

While expectancy X value theorists emphasize divergent sources of valuing. neuroscientists gener­ally do the opposite and emphasize the converging sources of valuing 까le orbitofron때 stnat외 ClrCu1t

is viewed as a valuation system in whïch this circuit continually computes valuation (how rewarding, how p"nishing) across a broad range of stimuli and environmental events (Montague & Berns, 2002) !t does so by valuing all these potential stimuli and events on a common dopamine-hased sc꾀e， which is sort of like the neural equivalent of monetary currency in a nation’'s economic system. Rewards vary on their type, magnitude, salience, and imme­diacy, and the orbitofrontal-striatal circuit (and the striatum in particular) convert and integrate these diverse sources of teward-based informa­tion into a common currency and, hy doing so, value all rewards on a common scale. Once diverse

꺼

따

,

廳

environmental incentives can be compared and contrasted via a conlmon currency, people can compare disparate stimuli (which would you rather do一drink a gl싫s of orange juice, go for a walk in the park, or play a videogame?) so to assign their attention and plan their action. Perhaps some simi­lar process allows people to integrate 바le vanous sources of value within expectancy X value theory (intrinsic value, utility value, and attainment value) on a common scale to compare the value of an inrer­esting but not useful event (play) with an uninter­esting but useful event (work)

A second perspective on value in the human motivation lirerature conceprualizes it as an inrer­nalization process in which socially recommended prescriptions “do this, believe that") and pro­scriptions “dOll’t do this, dO r1’t believe that") are accepted as ono's own (Ryan & Connell, 1989) 까1e

inrernalization process of valuing is not so much an emotionally associative process (as valuing is srudied in neuroscience) as it is a process in which a particu lar way of thinking, feeling, or behaving is accepted as personally beneficial for self-functioning (similar to the “utili ty value" Ín expectancy Xva1ue theories) It is an acrive and intentional proc야s that is based not on reward bur in selεdevelopment and a이ust­

ment (Ryan, 1993). In both the expectancy X v，꾀ue literature and in the internalization literature, value (1 ike volition in the previous section) is conceptu­alized more broadly than Îr is in the neuroscience lirerarure

lntrinsic Motivation aηdExtrinsic Motivatioη

Inrrinsic motivation is rhe inherenr propensiry to engage one’'s inreresrs and to exercise one’s CapaCltleS and, in doing so, to seek our and masrer oprimal challenges (Deci & Ryan, 1985). When people are intrinsically motivated, they act out of interest and because they find the task at hand to be inherencly enjoyable-producing sponraneous satisfacrions such as “It’'s fun)) and “ Irs inreresting)) during acriv­iry engagemenr. 1his behavior occurs sponraneously and is not enacted for any insrrumental (extrinsic) reasons. Intrinsic 1110rivation is a concept that neu­roscientists have not been able co explain (or under­stand). What is known, however, is that during grearer inslllar cortical activiry people become awarlε of how the task they are engaged in is affecting their subjective feelings and thεy consolidate this feeling­state information with social-contextllal information about their task engagement (e.g. , is there a deadline involved?) co fotm a global conscious experience of

374 I NEUR

“my feelings about that thing" (Craig, 2009, p. 65) As one example, people experience greater insular activity as they enjoy (experience spontaneous satis factions from the experience) music (Koelsch, Fritz, Cramon, MuIler, & Friederici, 2006).

In the neuroscience literarure, extrinsic moti­varion is synonymolls wirh incentive morivation, which we reviewed under the heading of “ Moti vational States Based on Associative Learning." In rhe human motivarion literature, extrinsic motiva­tion arises from environmental incentives and con­sequences (e.g. , food , money; tokens, extra credit points) in which approach motivation is based not on the chatacteristics of the task itselfbut on the condi tioned incentive value of the separate environmental event/consequence. As people experience extrinsic motivation toward a task, they show greater orb­icofrontal cortex activity as they weigh the value of the incentive being offered and greater anterior cin­gulate cortex as they go through a decision-making process as co whether engagement in the activity will bring enough benefit tO justifY the efforr expendi­ture (Plassmann, 0 ’Doherty, & Rangel, 2007). 1n the human motivation literature, however, extrinsic motivation is a complex construct in which rypes of extrinsic motivation exist, including external regula­tion (the protorype of extrinsic motivation, which is incentive motivation), introjected regulation (the person-rather than the environment per se-selε administers rewards and punishments, as in feeling contingent pride or contingent shame) , and iden­tified regulation (discussed in the previous section as the internalized process of valuing) 까1is differ­entiated view of extrinsic motivation has not been explored in the neuroscientific research literature. Furrhermore, almost no researιh exists co date on the neuroscientific study of intrinsic motivatiOll.

Intrinsic motivation and extrinsic motivation interact with one another, and the tendency of highly salient extrinsic rewards to decrease intrinsic motivation reprεsents the “undermining efFect" in the human motivation !irerature (Deci, Koestner, & Ryan, 1999). To investigate this s。디al psychologi­cal process within a neuroscienζe perspective, one group of researchers asked participants to engage 니lemselves in an interesting task either with the promise of a contingent extrinsic reward (money) or simply co experience the inherend

was inherently rewarding and cognitively engaging When the s잉ne task was paired with the promise of a contingent monetary reward, striatal and lar­eral prefromal cortical activiry increased signifi­cantly, suggesting that the extrinsic reward added [Q the task-inherent intrinsic motivation. In a sec­ond phase of the studι rhe extrinsic reward was removed ‘ The researchers then examined how much striatal and lateral prefrontal cortical activiry thε task itself could generate. For panicipants in 버e

no-reward condition, striatal and lateral prefromal cortical activiry were essemially the same on the second encounter with the activity-the task was just as rewarding and engaging as before. For par­tIClpanrs m 바e reward condition, however, striatal and lateral prefromal cortical activiry practically disappeared-the capaciry of the once imeresting and challenging task to generate pleasure (striatum) and cognitive engagemem (lateral prefromal cortex) had been undermined by the previously contingem extrinsic reward 까lis program of research nicely shows how a complex human motivational CQnüεpt (imrinsic motivation) can be better understood by a neuroscience emphasis, and it therefore provides an exemplary model for how future researchers might imegrate neutosciemific methods and per­spectives within human motivatÏon study.

Flow Flow is a state of concentration rhar involves

a holistic absorption and deep involvement in an activiry (Csikszentmihalyi, 1990). It is a highly pleasurable feeling that involves a sense of opti­mal challenge and perceived competence, and it is characretized by a loss of time perspective in which time passes relatively slowly. The anterior insular cortex integrates feelings generated by homeostatic, environmenral, hedonic, motivational, social, and cognitive inputs to produce a “global emotional moment," which represenrs conscious awareness of one’'s feelings at one (presem) moment in time (Craig, 2008, 2009). Under conditions of strong emotion (joy, or flow from achieving competem functioning during a challenging task), 미e anrenor insular cortex produces a dilation of time in which manyglobal εmotional momems occur rapidly (Tse, Imriligator, Rivest, & Cavanagh, 2004). Hence, subjective time dilates, as the actor sllbjectively feels that little time has passed even when engagemem has cominued for an objectively long(er) period of time. Like the study of the undermining effect of rewards on intrinsic motivarion, rhe human moti­vation and neurosciemific studies of flow represent

a second case of rather high convergence berween rhese rwo lireratures

E꺼pectancy Expecrancy is a cenrral concepr in rhe contem­

porary study of human motivation; it serves as the core explanatory construct underlying motivations such as personal comrol beliefs, mastery motiva­tion, selεef!icacy， and learned helplessness, among others (Skinner, 1995, 1996) 까lese “expectancy-of­control)} consrructs involve the inrerrelations among person, behavior, and outcome such that people have expectancies of being able to generate effective cop­ing behavior (e.g., ef!icacy expectations) and they have expect때cies of whether their coping behavior, once enacred, will produce rhe ourcome they seek (outcome expecrations). In neuroscientific invesri­garions of reward learning, however, expectancy is largely investigated as how expected a reward 1s.

Th is research, which t와<05 place under the umbrella term of“reward prediction error" (Schultz, 1998), shows that dopamine neurons are responsive when a reward is received unexpectedly. When rhat same reward is expecred, based on prior experience, the neurons respond not to reward receipt but to the informative nature of the predicrive cue. 1hus, dopamine neurons are responsive to reward-related novelry (Schott et al., 2004) , the amicipation of cued reward (Schott et 쇠 , 2008), and 버e difference berween expected reward and acrual reward, which is the reward prediction error (Schultz, 1998). Overall, dopamine neurons throllghout the basal ganglia dorsal srriatum, venrral striatum, ventral tegmenral area, and substantia nigra-report ongoing reward prediction errors, and they do so by providing antic­ipatory, unexpected, and actual signals of motiva­tional relevance (i .e., rεwardcues) 까1is information is rhen passed on to target brain regions, including the prefrontal cortex and anterior cingulate cortex, to coordinate reward-based learning and the moti­vation to learn about goals. For instance, once this information is passed on to the anterior cingulare cortex, approach versus avoidance decisional con­flicts can be resolved b잉ed on expected probabilities of reward, payoff, and costs, just as this same infor­marion can be passed on to the prefromal cortex t。guide goal setting and prioritizing. 까le neuroscientin.c srudy of reward prediction

errors is similar to the “ outcome expectancy" concept in the human motivation literature. Reward prεdic­tion errors mostly serve the function oflearning (not of morivation per se), as dopamine

REEVE , LEE … ”

1earning. However, these same dopamine-based responses can be used to influence future choice behavior (Sch띠tz， Dayan, & Montague, 1997) 꺼1at is, as peop1e navigate their surroundings, they evaluate various courses of aζtion that have di라r

enria1 predictions of reward associated with them. These predictions of f，니ture rewards (outcomes) are influenced by past expected reward 1earning. Hence, dopamine responses provide information ro enact tbe most basic expectancy-based motivational prin­cip1e-namε1y， approach and 이gage in action cor­related with increased dopamine activity and avoid action correlated with decreased dopamine activity.

Dopamine-based 1earning p1ays a key ro1e in reward expectation and receipt, which are closely related [0 outcome expectancies. But it also facili­tates episodic memory formation that is used for future adaptive behavior. That is, dopamine info마 mation during 1earning helps build and enab1e the forging of memory from one’'s past experience that then becomes 바e basis for future adaptive behav­ior (Shohamy & Adcock, 2010). It is this “adaptive memory" that then forms the basis of tbe second major type of expectancy motivation studied in the human motivation literature-namely, self-efficacy.

Self-.댈pcacy Efficacy expectations are rooted in questions such

as “ Can 1 cope well with the task at hand?" and “ If things start to go wrong during my performance, do 1 have the personal resources witbin me to cope well and turn things around for the better?" Selεef!icacy is tbe generative capacity in which the individual (the “self" in selεef!icacy) organizes and orches­trates his or her skills in the pursuit of goa1-directed action to cope with the demands and circumstances he or she faces. Formal1y defined, self-ef!icacy is one’'s judgment of how well (or poorly) one will cope with a situation, given the skills one possesses and the circumstances one faces (Bandura, 1997). 까1e precuneus (embedded within the parieta11obe) is invo1ved in many of these processes, including selεrelated imagery, episodic memory retrieval, pre­paring future action, and the experience of agency (Cavanna & 파imb1e， 2006; den Ouden, Frith, Frith, 8ι Blakemore, 2005)

1he primarγ determinanr of self-ef!icacy expecta­tlons IS one’'s histoty of episodic memory-based mas­tery enactments, whim might be conceptualized by neuroscientists as perceived skill in that domain. Srud ies of motor skill acquisition (Po1drack et al. , 2005) . and cognitiv1ε skill acquisition (Fincham & Anderson, 2006) show that trained individuals come to direct

their attenrion not to inrermediate goal-d.irected steps bur to tbe 1arger aim (as automation of skill occurs) ‘

Auromation of procedural skills al10ws one to focus attention to environmenral demands and chal1enges, retrieve relevant episodic memories, and predict and p1an effective future courses of action, while it further lessens cognitive confusion 때d 따1Xiety (Bandura, 1988). The hippocampus is importanr to automation 。f procedural know1edge, and tbe downregu1ation of competenr self-represenrations has been shown to1εssen negative affect, a많ct intensiry, and corrisol reactivity during coping (Sapols에" 1992).

Perhaps tbe most productive way that human motivation research on self-efficacy can contribme to interdisciplinary motivational neuroscience r앙earchis

ro stress the point that neural systems that focus atten­tion, mentally represent value, detect the causal struc­ture of the world, and inregrate tbis information into e라ctive decision making and action is on1y one part of the adaptive stoty (Bandura, 2001). The other part 。f the adaptive stoty is selεef!icacy-fueled agency in which peop1e proactively devise ways to adapt flexib1y to a wide range of physical and social environments to redesign them to their liking 잉1d conrrollabiliry. Such a perspective places lesser inßuence on environ­mentally responsive and adaptive brain processes and relatively greater influence on proactive and agentic br혀n processes in the exercise of personal control OV1εl

environments ro be encountered in 바e future

Self-Reguμtion and Goals Selε[εgulation is an ongoing, cyclical process

that invo1ves foretbought, action, and reflection (Zimmerman, 2000). Forethought invo1ves goal set­ting and strategic planning, while reßection involves assessment and making adjustments ro produce more informed forethought prior to the next performance opportunity. What is reg띠ated during self-regu1ation are the persod’'s goals (and, to a lesser extent, the means to these goals, such as plans, strategies, emotions, and envlro미nents). In the human motivation literature, goals are future-focused cognitive representations that guide behavior to an end state that the individual is committed to either approach or avoid (Hul1eman, Schrager, Bodmann, & Harackiewicz, 2010). Ir is the prefrontal ζ:ortex that houses a person's conscious goals (MiIler & Cohen, 2001) , 리.1d this information is used in goal-directed action in the top-down flow of information depicted in Figure 2 1.2

From a neuroscience point of view, several brain structures exercise executive control and inhibition Qver action. The prefrontal cortex contributes top­down contro1 that guides behavior by activating

37 6 I NEUROSCIE N CE AND HUMAN MOTIVATION

inrernal represencations of action such as goals and intentions by sending information to other areas of the brain to promote goal-relevant actions. While the prefrontal cortex generates goals and intentions, executive control over action seems to be carried out in many additional prefrontal cortex regions, includ­ing the ventral medial prefrontal cortex, the anterior cingulate cortex, and the dorsolateral prefrontal cor­tex, as each is involved in a high-Ievel reglllation of action, including self-control and the self-regulation 。f action such as planning, organizing, and chang­ing action (Damasio, 1994, 2003; Oschsner & Gross, 2005; Rueda et al. , 2004) 낀le anterior cin­

gulate cortex, for example, plays a high-Ievel role in the regulation of action, as it not only receives infor­mation about sensory events, monitors conHict, and integrates emotional information (Botvinick er al. , 2004; Craig, 2008), it is active during any decision to change one'’'s course of action (Devinsky, Mor­rell, & Vogt, 1995) and is involved in adjusting past learning about environmental contingencies when rheir reliabiliry changes over time (Behrens, Wool­rich, Walton, & Rushworth, 2007). 1hese research findings suggest a possible convergence between human motivation researchers and neuroscientists, as nellroscientists have done an especially impr야sive

job in explaining the neural bases of forethought, decision making, and reHective action

Conclusion 까1e intellectual landscape that connects human

motivation study and neuroscience is not currencly pop띠ated by ever-present two-way information highways in whicl1 the methodologies, fi뼈ngs，

and theoretical developments in one field flow into the other and rerurn back in a more informed and sophisticated way. It is clear, however, that human motivation researchers have a lot to gain from such interconnectiviry. To date, the most obvious benefit for human motivation research has been 마ar neuro­scientific investigations have brought to light the neu­ral meditational processes that underlie the how and the why of the basic motivation mediation model environment • motivation • adaptive action. 1hat is, neuroscientific investigations have enriched the understanding of both the generation of motiva­tion며 states (i.e., environment • neural activations • motivation) and 마eir adap디ve functions (motiva­tion • neural activations • adaptive functioning)

It is equally clear that neuroscience researchers have gained from greater motivation-neuroscience interconnectivity. 까1e most obvious benefit “r neuroscience research has been to 뿜ln a greater

theoretical depth and complexiry for the motiva­.tional constructs it studies. Motivarional concepts such as volition, agency, valuε， mtnnSlC motlva­tion, self-eflìcacy, and self-regulation can be under­stood more richly when neuroscientific analyses are supplemented and informed by behavioral and psychological findings, methodologies, and espe­cially theories. Once understood in their theoretical richness, these motivational constructs can be stud­ied in ways that increasingly map onto and reflect what is known about them from traditional human motivation study. Such integration, if Ìr is to occuι will likely be carried out by a generation of inter­disciplinary motivation neuroscience researchers­scholars whose inreresrs, professional rraining, and inrellectual home Îs as much in neuroscience as ir is in human motivarion srudy, and vice versa.

Future Directions

1. Will the relationship between neuroscience and human motivation become more reciprocal and bidirectional in the furure, or will it remain largely a landscape of one-way-and even dead end-streets? TI디s trend will depend on human motivation researchers' openness to neuroscience and to their willingn앉S to form collaborations and leam the methods and knowledge base of neurosclence

2. Is neuroscience relev때t (Q only some dasses or facers of morivarion-for example, homeostasis and reward-or is it more generally relevant to more complex motivations such as inrrinsÏc

motivation and self-eflìcacy? This is a question of whether rhe motivation-neuroscience collaborarion will be a narrow or a broad one

3. What are the benefits of maintaining the 앉isting distinction between the two di없rent

levels of analyses (neurological versus behavioral and selεreport) embraced by neuroscience on the one hand and human motivation study on the other? How well can the dependent measures used in neuroscience (e.g., reaction times, neural activations) align with the dependent measures used in human morivarion srudy (e.g. , effort, phenomenology)? 1his future direction will likely be determined by the extent to which neural-dependent measures align (correlate) with behavioral and self-report measures of motivation

4. Can the brain generate morivation of its own? Or is brain-based motivation always an adaptive response to environmental events? Neuroscientific invesrigarions of motivation have

꺼

따

’

없

revealed much about environmental sources

of motivation and reward. It is still an open

question, however, as to how mllch this

paradigm might reveal abollt intrinsic

sOllrces of motivatÎon

5‘ Lastly, the past decade of motivational

neuroscience has largely sought to identify the

neural bases of various motivational states

This has been and continues to be a produαive

enterprise. As the neural bases of various

motivational states become well understood, motivational neuroscience will need to ask new

questions and take on a new sensè of pllrpOSe

It is interesting to speculate what this furure

direction w ill be, but it willlike be one 야lat

transcends description (e.g. , the amygdala is

involved in this, the anterÎor cingulate cortex is

involved in that) to addrεss explanation.

Acknowledgments 끼1is research was supported by the WCU (World Class Uni­

versity) Program funded by the Korean Ministry of Education, Science and Technology, consigned to the Korea Science and Engineering Foundation (grant R32-2008-000-20023-0)

Note 1. Wh ile dopamine is the key neurotransminer involved

in rhe processing of reward, orher neurorransmiucrs 뇌s。

conrribute to the processing ofκward， including choline, GABA, glutamate, opiod , and serotonin (Knapp & Kometsky, 2009)

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